Multi-focus image fusion and robust encryption algorithm based on compressive sensing

NASA Astrophysics Data System (ADS)

Xiao, Di; Wang, Lan; Xiang, Tao; Wang, Yong

2017-06-01

Multi-focus image fusion schemes have been studied in recent years. However, little work has been done in multi-focus image transmission security. This paper proposes a scheme that can reduce data transmission volume and resist various attacks. First, multi-focus image fusion based on wavelet decomposition can generate complete scene images and optimize the perception of the human eye. The fused images are sparsely represented with DCT and sampled with structurally random matrix (SRM), which reduces the data volume and realizes the initial encryption. Then the obtained measurements are further encrypted to resist noise and crop attack through combining permutation and diffusion stages. At the receiver, the cipher images can be jointly decrypted and reconstructed. Simulation results demonstrate the security and robustness of the proposed scheme.

Robustness of larval development of intertidal sea urchin species to simulated ocean warming and acidification.

PubMed

García, Eliseba; Hernández, José Carlos; Clemente, Sabrina

2018-08-01

Ocean warming and acidification are the two most significant side effects of carbone dioxide emissions in the world's oceans. By changing water, temperature and pH are the main environmental factors controlling the distribution, physiology, morphology and behaviour of marine invertebrates. This study evaluated the combined effects of predicted high temperature levels, and predicted low pH values, on fertilization and early development stages of the sea urchins Arbacia lixula, Paracentrotus lividus, Sphaerechinus granularis and Diadema africanum. Twelve treatments, combining different temperatures (19, 21, 23 and 25 °C) and pH values (8.1, 7.7 and 7.4 units), were tested in laboratory experiments. All of the tested temperatures and pH values were within the open coast seawater range expected within the next century. We examined fertilization rate, cleavage rate, 3-day larvae survival, and development of the different sea urchin species at set time intervals after insemination. Our results highlight the susceptibility of subtidal species to environmental changes, and the robustness of intertidal species to ocean warming and acidification. Copyright © 2018 Elsevier Ltd. All rights reserved.

A high performance parallel computing architecture for robust image features

NASA Astrophysics Data System (ADS)

Zhou, Renyan; Liu, Leibo; Wei, Shaojun

2014-03-01

A design of parallel architecture for image feature detection and description is proposed in this article. The major component of this architecture is a 2D cellular network composed of simple reprogrammable processors, enabling the Hessian Blob Detector and Haar Response Calculation, which are the most computing-intensive stage of the Speeded Up Robust Features (SURF) algorithm. Combining this 2D cellular network and dedicated hardware for SURF descriptors, this architecture achieves real-time image feature detection with minimal software in the host processor. A prototype FPGA implementation of the proposed architecture achieves 1318.9 GOPS general pixel processing @ 100 MHz clock and achieves up to 118 fps in VGA (640 × 480) image feature detection. The proposed architecture is stand-alone and scalable so it is easy to be migrated into VLSI implementation.

Constraint treatment techniques and parallel algorithms for multibody dynamic analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chiou, Jin-Chern

1990-01-01

Computational procedures for kinematic and dynamic analysis of three-dimensional multibody dynamic (MBD) systems are developed from the differential-algebraic equations (DAE's) viewpoint. Constraint violations during the time integration process are minimized and penalty constraint stabilization techniques and partitioning schemes are developed. The governing equations of motion, a two-stage staggered explicit-implicit numerical algorithm, are treated which takes advantage of a partitioned solution procedure. A robust and parallelizable integration algorithm is developed. This algorithm uses a two-stage staggered central difference algorithm to integrate the translational coordinates and the angular velocities. The angular orientations of bodies in MBD systems are then obtained by using an implicit algorithm via the kinematic relationship between Euler parameters and angular velocities. It is shown that the combination of the present solution procedures yields a computationally more accurate solution. To speed up the computational procedures, parallel implementation of the present constraint treatment techniques, the two-stage staggered explicit-implicit numerical algorithm was efficiently carried out. The DAE's and the constraint treatment techniques were transformed into arrowhead matrices to which Schur complement form was derived. By fully exploiting the sparse matrix structural analysis techniques, a parallel preconditioned conjugate gradient numerical algorithm is used to solve the systems equations written in Schur complement form. A software testbed was designed and implemented in both sequential and parallel computers. This testbed was used to demonstrate the robustness and efficiency of the constraint treatment techniques, the accuracy of the two-stage staggered explicit-implicit numerical algorithm, and the speed up of the Schur-complement-based parallel preconditioned conjugate gradient algorithm on a parallel computer.

A bi-objective model for robust yard allocation scheduling for outbound containers

NASA Astrophysics Data System (ADS)

Liu, Changchun; Zhang, Canrong; Zheng, Li

2017-01-01

This article examines the yard allocation problem for outbound containers, with consideration of uncertainty factors, mainly including the arrival and operation time of calling vessels. Based on the time buffer inserting method, a bi-objective model is constructed to minimize the total operational cost and to maximize the robustness of fighting against the uncertainty. Due to the NP-hardness of the constructed model, a two-stage heuristic is developed to solve the problem. In the first stage, initial solutions are obtained by a greedy algorithm that looks n-steps ahead with the uncertainty factors set as their respective expected values; in the second stage, based on the solutions obtained in the first stage and with consideration of uncertainty factors, a neighbourhood search heuristic is employed to generate robust solutions that can fight better against the fluctuation of uncertainty factors. Finally, extensive numerical experiments are conducted to test the performance of the proposed method.

Multi-Stage Target Tracking with Drift Correction and Position Prediction

NASA Astrophysics Data System (ADS)

Chen, Xin; Ren, Keyan; Hou, Yibin

2018-04-01

Most existing tracking methods are hard to combine accuracy and performance, and do not consider the shift between clarity and blur that often occurs. In this paper, we propound a multi-stage tracking framework with two particular modules: position prediction and corrective measure. We conduct tracking based on correlation filter with a corrective measure module to increase both performance and accuracy. Specifically, a convolutional network is used for solving the blur problem in realistic scene, training methodology that training dataset with blur images generated by the three blur algorithms. Then, we propose a position prediction module to reduce the computation cost and make tracker more capable of fast motion. Experimental result shows that our tracking method is more robust compared to others and more accurate on the benchmark sequences.

Parallax-Robust Surveillance Video Stitching

PubMed Central

He, Botao; Yu, Shaohua

2015-01-01

This paper presents a parallax-robust video stitching technique for timely synchronized surveillance video. An efficient two-stage video stitching procedure is proposed in this paper to build wide Field-of-View (FOV) videos for surveillance applications. In the stitching model calculation stage, we develop a layered warping algorithm to align the background scenes, which is location-dependent and turned out to be more robust to parallax than the traditional global projective warping methods. On the selective seam updating stage, we propose a change-detection based optimal seam selection approach to avert ghosting and artifacts caused by moving foregrounds. Experimental results demonstrate that our procedure can efficiently stitch multi-view videos into a wide FOV video output without ghosting and noticeable seams. PMID:26712756

Robust, Optimal Water Infrastructure Planning Under Deep Uncertainty Using Metamodels

NASA Astrophysics Data System (ADS)

Maier, H. R.; Beh, E. H. Y.; Zheng, F.; Dandy, G. C.; Kapelan, Z.

2015-12-01

Optimal long-term planning plays an important role in many water infrastructure problems. However, this task is complicated by deep uncertainty about future conditions, such as the impact of population dynamics and climate change. One way to deal with this uncertainty is by means of robustness, which aims to ensure that water infrastructure performs adequately under a range of plausible future conditions. However, as robustness calculations require computationally expensive system models to be run for a large number of scenarios, it is generally computationally intractable to include robustness as an objective in the development of optimal long-term infrastructure plans. In order to overcome this shortcoming, an approach is developed that uses metamodels instead of computationally expensive simulation models in robustness calculations. The approach is demonstrated for the optimal sequencing of water supply augmentation options for the southern portion of the water supply for Adelaide, South Australia. A 100-year planning horizon is subdivided into ten equal decision stages for the purpose of sequencing various water supply augmentation options, including desalination, stormwater harvesting and household rainwater tanks. The objectives include the minimization of average present value of supply augmentation costs, the minimization of average present value of greenhouse gas emissions and the maximization of supply robustness. The uncertain variables are rainfall, per capita water consumption and population. Decision variables are the implementation stages of the different water supply augmentation options. Artificial neural networks are used as metamodels to enable all objectives to be calculated in a computationally efficient manner at each of the decision stages. The results illustrate the importance of identifying optimal staged solutions to ensure robustness and sustainability of water supply into an uncertain long-term future.

Baseline estimation in flame's spectra by using neural networks and robust statistics

NASA Astrophysics Data System (ADS)

Garces, Hugo; Arias, Luis; Rojas, Alejandro

2014-09-01

This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.

Robust Speech Enhancement Using Two-Stage Filtered Minima Controlled Recursive Averaging

NASA Astrophysics Data System (ADS)

Ghourchian, Negar; Selouani, Sid-Ahmed; O'Shaughnessy, Douglas

In this paper we propose an algorithm for estimating noise in highly non-stationary noisy environments, which is a challenging problem in speech enhancement. This method is based on minima-controlled recursive averaging (MCRA) whereby an accurate, robust and efficient noise power spectrum estimation is demonstrated. We propose a two-stage technique to prevent the appearance of musical noise after enhancement. This algorithm filters the noisy speech to achieve a robust signal with minimum distortion in the first stage. Subsequently, it estimates the residual noise using MCRA and removes it with spectral subtraction. The proposed Filtered MCRA (FMCRA) performance is evaluated using objective tests on the Aurora database under various noisy environments. These measures indicate the higher output SNR and lower output residual noise and distortion.

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach

PubMed Central

Tan, Robin; Perkowski, Marek

2017-01-01

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems. PMID:28230745

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach.

PubMed

Tan, Robin; Perkowski, Marek

2017-02-20

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems.

Impacts of toxic thresholds of sediment-associated contaminants to robust redhorse (Moxostoma robustum) in the Lower Oconee River

USGS Publications Warehouse

Lasier, P.; Winger, P.; Bogenrieder, K.; Shelton, J.

2000-01-01

The robust redhorse is a ?Species-at-Risk? in the lower Oconee River, GA. The population is composed of aging adults with little natural recruitment. Factors contributing to the loss of early-life stages are unknown, but contaminants associated with fine sediments may play a role. The objectives of this study were to determine toxicities of sediments and pore waters from the Oconee River to early-life stages of robust redhorse and to establish toxic thresholds of metals (Cd, Cu, Mn, Zn) and ammonia, elements potentially threatening this species. Depositional sediments were collected from the only known spawning site and three sites downstream of major tributaries. Sediment pore waters were extracted in the laboratory from all sites and in situ at two sites. Toxicity tests with sediments, pore waters and metal solutions were initiated with eggs, yolk-sac fry and swim-up fry to determine effects on the life stage initially exposed as well as effects manifested in later developmental stages. Survival and growth were test endpoints, and toxicity was observed in both sediments and pore waters. Although the yolk- sac stage was the most sensitive across all tests, sediment toxicity was elicited only in tests initiated with eggs that developed through the yolk-sac stage. Toxicity appeared to be due to Mn in sediment and pore water exposures, but was more prevalent in pore waters. Sediment handling and the associated effects on redox potential contributed to the elevated concentrations of Mn in pore waters. Pore waters extracted in situ had significantly less Mn and were less toxic than laboratory-extracted pore waters. These data suggest that sediment-associated Mn may impact early-life stages of robust redhorse in the Oconee River.

qFibrosis: A fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients

PubMed Central

Tai, Dean C.S.; Wang, Shi; Cheng, Chee Leong; Peng, Qiwen; Yan, Jie; Chen, Yongpeng; Sun, Jian; Liang, Xieer; Zhu, Youfu; Rajapakse, Jagath C.; Welsch, Roy E.; So, Peter T.C.; Wee, Aileen; Hou, Jinlin; Yu, Hanry

2014-01-01

Background & Aims There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients. Methods qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison. Results qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p <0.001) and human biopsies (p <0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93–0.99 for animal samples: 1–16 mm2; AUC: 0.84–0.97 for biopsies: 10–44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p <0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p = 0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts. Conclusions qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice. PMID:24583249

Characterization of atherosclerotic plaques by cross-polarization optical coherence tomography

NASA Astrophysics Data System (ADS)

Gubarkova, Ekaterina V.; Dudenkova, Varvara V.; Feldchtein, Felix I.; Timofeeva, Lidia B.; Kiseleva, Elena B.; Kuznetsov, Sergei S.; Moiseev, Alexander A.; Gelikonov, Gregory V.; Vitkin, Alex I.; Gladkova, Natalia D.

2016-02-01

We combined cross-polarization optical coherence tomography (CP OCT) and non-linear microscopy based on second harmonic generation (SHG) and two-photon-excited fluorescence (2PEF) to assess collagen and elastin fibers in the development of the atherosclerotic plaque (AP). The study shows potential of CP OCT for the assessment of collagen and elastin fibers condition in atherosclerotic arteries. Specifically, the additional information afforded by CP OCT, related to birefringence and cross-scattering properties of arterial tissues, may improve the robustness and accuracy of assessment about the microstructure and composition of the plaque for different stages of atherosclerosis.

The stage-specific in vitro efficacy of a malaria antigen cocktail provides valuable insights into the development of effective multi-stage vaccines.

PubMed

Spiegel, Holger; Boes, Alexander; Kastilan, Robin; Kapelski, Stephanie; Edgue, Güven; Beiss, Veronique; Chubodova, Ivana; Scheuermayer, Matthias; Pradel, Gabriele; Schillberg, Stefan; Reimann, Andreas; Fischer, Rainer

2015-10-01

Multicomponent vaccines targeting different stages of Plasmodium falciparum represent a promising, holistic concept towards better malaria vaccines. Additionally, an effective vaccine candidate should demonstrate cross-strain specificity because many antigens are polymorphic, which can reduce vaccine efficacy. A cocktail of recombinant fusion proteins (VAMAX-Mix) featuring three diversity-covering variants of the blood-stage antigen PfAMA1, each combined with the conserved sexual-stage antigen Pfs25 and one of the pre-erythrocytic-stage antigens PfCSP_TSR or PfCelTOS, or the additional blood-stage antigen PfMSP1_19, was produced in Pichia pastoris and used to immunize rabbits. The immune sera and purified IgG were used to perform various assays determining antigen specific titers and in vitro efficacy against different parasite stages and strains. In functional in vitro assays we observed robust inhibition of blood-stage (up to 90%), and sexual-stage parasites (up to 100%) and biased inhibition of pre-erythrocytic parasites (0-40%). Cross-strain blood-stage efficacy was observed in erythrocyte invasion assays using four different P. falciparum strains. The quantification of antigen-specific IgGs allowed the determination of specific IC50 values. The significant difference in antigen-specific IC50 requirements, the direct correlation between antigen-specific IgG and the relative quantitative representation of antigens within the cocktail, provide valuable implementations for future multi-stage, multi-component vaccine designs. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust multiperson detection and tracking for mobile service and social robots.

PubMed

Li, Liyuan; Yan, Shuicheng; Yu, Xinguo; Tan, Yeow Kee; Li, Haizhou

2012-10-01

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

Modelling the impact of vector control interventions on Anopheles gambiae population dynamics

PubMed Central

2011-01-01

Background Intensive anti-malaria campaigns targeting the Anopheles population have demonstrated substantial reductions in adult mosquito density. Understanding the population dynamics of Anopheles mosquitoes throughout their whole lifecycle is important to assess the likely impact of vector control interventions alone and in combination as well as to aid the design of novel interventions. Methods An ecological model of Anopheles gambiae sensu lato populations incorporating a rainfall-dependent carrying capacity and density-dependent regulation of mosquito larvae in breeding sites is developed. The model is fitted to adult mosquito catch and rainfall data from 8 villages in the Garki District of Nigeria (the 'Garki Project') using Bayesian Markov Chain Monte Carlo methods and prior estimates of parameters derived from the literature. The model is used to compare the impact of vector control interventions directed against adult mosquito stages - long-lasting insecticide treated nets (LLIN), indoor residual spraying (IRS) - and directed against aquatic mosquito stages, alone and in combination on adult mosquito density. Results A model in which density-dependent regulation occurs in the larval stages via a linear association between larval density and larval death rates provided a good fit to seasonal adult mosquito catches. The effective mosquito reproduction number in the presence of density-dependent regulation is dependent on seasonal rainfall patterns and peaks at the start of the rainy season. In addition to killing adult mosquitoes during the extrinsic incubation period, LLINs and IRS also result in less eggs being oviposited in breeding sites leading to further reductions in adult mosquito density. Combining interventions such as the application of larvicidal or pupacidal agents that target the aquatic stages of the mosquito lifecycle with LLINs or IRS can lead to substantial reductions in adult mosquito density. Conclusions Density-dependent regulation of anopheline larvae in breeding sites ensures robust, stable mosquito populations that can persist in the face of intensive vector control interventions. Selecting combinations of interventions that target different stages in the vector's lifecycle will result in maximum reductions in mosquito density. PMID:21798055

A queuing-theory-based interval-fuzzy robust two-stage programming model for environmental management under uncertainty

NASA Astrophysics Data System (ADS)

Sun, Y.; Li, Y. P.; Huang, G. H.

2012-06-01

In this study, a queuing-theory-based interval-fuzzy robust two-stage programming (QB-IRTP) model is developed through introducing queuing theory into an interval-fuzzy robust two-stage (IRTP) optimization framework. The developed QB-IRTP model can not only address highly uncertain information for the lower and upper bounds of interval parameters but also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties when the promised targets are violated. Moreover, it can reflect uncertainties in queuing theory problems. The developed method has been applied to a case of long-term municipal solid waste (MSW) management planning. Interval solutions associated with different waste-generation rates, different waiting costs and different arriving rates have been obtained. They can be used for generating decision alternatives and thus help managers to identify desired MSW management policies under various economic objectives and system reliability constraints.

Direct-acting antivirals combination for elderly patients with chronic hepatitis C: A cost-effectiveness analysis.

PubMed

Ciaccio, Antonio; Cortesi, Paolo A; Bellelli, Giuseppe; Rota, Matteo; Conti, Sara; Okolicsanyi, Stefano; Rota, Monica; Cesana, Giancarlo; Mantovani, Lorenzo G; Annoni, Giorgio; Strazzabosco, Mario

2017-07-01

Chronic hepatitis C (CHC) has been undertreated among elderly patients. Interferon-free treatment represents an opportunity for these patients. The aim of this study was to assess the cost-effectiveness of directly acting antivirals (DAAs) in CHC elderly patients. A Markov model of CHC natural history was built. This study focuses on CHC patients older than 65 years, stratified according to genotype (1/4, 2 and 3), liver fibrosis (METAVIR F1 to F4), age and frailty phenotype (robust, pre-frail and frail). DAAs combination vs no treatment was simulated for each theoretical population, assessing life years, quality-adjusted life years (QALYs), costs, incremental cost-effectiveness ratios (ICERs) in a lifetime time horizon and by the Healthcare System perspective. Incremental cost-effectiveness ratio increased with age and frailty status in all fibrosis stages. For robust F3 and F4 patients ICERs remained below the willingness-to-pay threshold (WTP) of 40 000€/QALY up to age 75 and 86 years, respectively, depending on drug price and sustained virological response probability (sensitivity analysis). Notably, in F4 and frail subjects older than 75 years, ICER was more sensitive to non-liver-related mortality rate. In elderly F1 and F2 patients, ICERs were below WTP only up to 77 years old, with wide variability among frailty phenotypes. Cost-effectiveness of DAAs treatment of elderly CHC patients is solid in those with advanced fibrosis, but it depends strongly on frailty status and age, particularly in patients with milder fibrosis stages. Accurate assessment of clinical variables, including frailty, is necessary to allocate limited resources to this special population. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

GC × GC-TOFMS and supervised multivariate approaches to study human cadaveric decomposition olfactive signatures.

PubMed

Stefanuto, Pierre-Hugues; Perrault, Katelynn A; Stadler, Sonja; Pesesse, Romain; LeBlanc, Helene N; Forbes, Shari L; Focant, Jean-François

2015-06-01

In forensic thanato-chemistry, the understanding of the process of soft tissue decomposition is still limited. A better understanding of the decomposition process and the characterization of the associated volatile organic compounds (VOC) can help to improve the training of victim recovery (VR) canines, which are used to search for trapped victims in natural disasters or to locate corpses during criminal investigations. The complexity of matrices and the dynamic nature of this process require the use of comprehensive analytical methods for investigation. Moreover, the variability of the environment and between individuals creates additional difficulties in terms of normalization. The resolution of the complex mixture of VOCs emitted by a decaying corpse can be improved using comprehensive two-dimensional gas chromatography (GC × GC), compared to classical single-dimensional gas chromatography (1DGC). This study combines the analytical advantages of GC × GC coupled to time-of-flight mass spectrometry (TOFMS) with the data handling robustness of supervised multivariate statistics to investigate the VOC profile of human remains during early stages of decomposition. Various supervised multivariate approaches are compared to interpret the large data set. Moreover, early decomposition stages of pig carcasses (typically used as human surrogates in field studies) are also monitored to obtain a direct comparison of the two VOC profiles and estimate the robustness of this human decomposition analog model. In this research, we demonstrate that pig and human decomposition processes can be described by the same trends for the major compounds produced during the early stages of soft tissue decomposition.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo

PubMed Central

2018-01-01

ABSTRACT Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivo. In silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo. Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients. PMID:29588406

Enhancing Flood Prediction Reliability Using Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Liu, Z.; Merwade, V.

2017-12-01

Uncertainty analysis is an indispensable part of modeling the hydrology and hydrodynamics of non-idealized environmental systems. Compared to reliance on prediction from one model simulation, using on ensemble of predictions that consider uncertainty from different sources is more reliable. In this study, Bayesian model averaging (BMA) is applied to Black River watershed in Arkansas and Missouri by combining multi-model simulations to get reliable deterministic water stage and probabilistic inundation extent predictions. The simulation ensemble is generated from 81 LISFLOOD-FP subgrid model configurations that include uncertainty from channel shape, channel width, channel roughness and discharge. Model simulation outputs are trained with observed water stage data during one flood event, and BMA prediction ability is validated for another flood event. Results from this study indicate that BMA does not always outperform all members in the ensemble, but it provides relatively robust deterministic flood stage predictions across the basin. Station based BMA (BMA_S) water stage prediction has better performance than global based BMA (BMA_G) prediction which is superior to the ensemble mean prediction. Additionally, high-frequency flood inundation extent (probability greater than 60%) in BMA_G probabilistic map is more accurate than the probabilistic flood inundation extent based on equal weights.

A simple and predictive phenotypic High Content Imaging assay for Plasmodium falciparum mature gametocytes to identify malaria transmission blocking compounds

PubMed Central

Lucantoni, Leonardo; Silvestrini, Francesco; Signore, Michele; Siciliano, Giulia; Eldering, Maarten; Dechering, Koen J.; Avery, Vicky M.; Alano, Pietro

2015-01-01

Plasmodium falciparum gametocytes, specifically the mature stages, are the only malaria parasite stage in humans transmissible to the mosquito vector. Anti-malarial drugs capable of killing these forms are considered essential for the eradication of malaria and tools allowing the screening of large compound libraries with high predictive power are needed to identify new candidates. As gametocytes are not a replicative stage it is difficult to apply the same drug screening methods used for asexual stages. Here we propose an assay, based on high content imaging, combining “classic” gametocyte viability readout based on gametocyte counts with a functional viability readout, based on gametocyte activation and the discrimination of the typical gamete spherical morphology. This simple and rapid assay has been miniaturized to a 384-well format using acridine orange staining of wild type P. falciparum 3D7A sexual forms, and was validated by screening reference antimalarial drugs and the MMV Malaria Box. The assay demonstrated excellent robustness and ability to identify quality hits with high likelihood of confirmation of transmission reducing activity in subsequent mosquito membrane feeding assays. PMID:26553647

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

PubMed Central

2012-01-01

Background Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation. Methods An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis. Results Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored. Conclusions The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations. PMID:22462519

Low doses of killed parasite in CpG elicit vigorous CD4+ T cell responses against blood-stage malaria in mice

PubMed Central

Pinzon-Charry, Alberto; McPhun, Virginia; Kienzle, Vivian; Hirunpetcharat, Chakrit; Engwerda, Christian; McCarthy, James; Good, Michael F.

2010-01-01

Development of a vaccine that targets blood-stage malaria parasites is imperative if we are to sustainably reduce the morbidity and mortality caused by this infection. Such a vaccine should elicit long-lasting immune responses against conserved determinants in the parasite population. Most blood-stage vaccines, however, induce protective antibodies against surface antigens, which tend to be polymorphic. Cell-mediated responses, on the other hand, offer the theoretical advantage of targeting internal antigens that are more likely to be conserved. Nonetheless, few of the current blood-stage vaccine candidates are able to harness vigorous T cell immunity. Here, we present what we believe to be a novel blood-stage whole-organism vaccine that, by combining low doses of killed parasite with CpG-oligodeoxynucleotide (CpG-ODN) adjuvant, was able to elicit strong and cross-reactive T cell responses in mice. Our data demonstrate that immunization of mice with 1,000 killed parasites in CpG-ODN engendered durable and cross-strain protection by inducing a vigorous response that was dependent on CD4+ T cells, IFN-γ, and nitric oxide. If applicable to humans, this approach should facilitate the generation of robust, cross-reactive T cell responses against malaria as well as antigen availability for vaccine manufacture. PMID:20628205

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

On the contributions of topological features to transcriptional regulatory network robustness

PubMed Central

2012-01-01

Background Because biological networks exhibit a high-degree of robustness, a systemic understanding of their architecture and function requires an appraisal of the network design principles that confer robustness. In this project, we conduct a computational study of the contribution of three degree-based topological properties (transcription factor-target ratio, degree distribution, cross-talk suppression) and their combinations on the robustness of transcriptional regulatory networks. We seek to quantify the relative degree of robustness conferred by each property (and combination) and also to determine the extent to which these properties alone can explain the robustness observed in transcriptional networks. Results To study individual properties and their combinations, we generated synthetic, random networks that retained one or more of the three properties with values derived from either the yeast or E. coli gene regulatory networks. Robustness of these networks were estimated through simulation. Our results indicate that the combination of the three properties we considered explains the majority of the structural robustness observed in the real transcriptional networks. Surprisingly, scale-free degree distribution is, overall, a minor contributor to robustness. Instead, most robustness is gained through topological features that limit the complexity of the overall network and increase the transcription factor subnetwork sparsity. Conclusions Our work demonstrates that (i) different types of robustness are implemented by different topological aspects of the network and (ii) size and sparsity of the transcription factor subnetwork play an important role for robustness induction. Our results are conserved across yeast and E Coli, which suggests that the design principles examined are present within an array of living systems. PMID:23194062

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

PubMed Central

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

2011-01-01

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

Integration of Host Strain Bioengineering and Bioprocess Development Using Ultra-Scale Down Studies to Select the Optimum Combination: An Antibody Fragment Primary Recovery Case Study

PubMed Central

Aucamp, Jean P; Davies, Richard; Hallet, Damien; Weiss, Amanda; Titchener-Hooker, Nigel J

2014-01-01

An ultra scale-down primary recovery sequence was established for a platform E. coli Fab production process. It was used to evaluate the process robustness of various bioengineered strains. Centrifugal discharge in the initial dewatering stage was determined to be the major cause of cell breakage. The ability of cells to resist breakage was dependant on a combination of factors including host strain, vector, and fermentation strategy. Periplasmic extraction studies were conducted in shake flasks and it was demonstrated that key performance parameters such as Fab titre and nucleic acid concentrations were mimicked. The shake flask system also captured particle aggregation effects seen in a large scale stirred vessel, reproducing the fine particle size distribution that impacts the final centrifugal clarification stage. The use of scale-down primary recovery process sequences can be used to screen a larger number of engineered strains. This can lead to closer integration with and better feedback between strain development, fermentation development, and primary recovery studies. Biotechnol. Bioeng. 2014;111: 1971–1981. © 2014 Wiley Periodicals, Inc. PMID:24838387

Two-stage fuzzy-stochastic robust programming: a hybrid model for regional air quality management.

PubMed

Li, Yongping; Huang, Guo H; Veawab, Amornvadee; Nie, Xianghui; Liu, Lei

2006-08-01

In this study, a hybrid two-stage fuzzy-stochastic robust programming (TFSRP) model is developed and applied to the planning of an air-quality management system. As an extension of existing fuzzy-robust programming and two-stage stochastic programming methods, the TFSRP can explicitly address complexities and uncertainties of the study system without unrealistic simplifications. Uncertain parameters can be expressed as probability density and/or fuzzy membership functions, such that robustness of the optimization efforts can be enhanced. Moreover, economic penalties as corrective measures against any infeasibilities arising from the uncertainties are taken into account. This method can, thus, provide a linkage to predefined policies determined by authorities that have to be respected when a modeling effort is undertaken. In its solution algorithm, the fuzzy decision space can be delimited through specification of the uncertainties using dimensional enlargement of the original fuzzy constraints. The developed model is applied to a case study of regional air quality management. The results indicate that reasonable solutions have been obtained. The solutions can be used for further generating pollution-mitigation alternatives with minimized system costs and for providing a more solid support for sound environmental decisions.

Properties of Starless Clumps through Protoclusters from the Bolocam Galactic Plane Survey

NASA Astrophysics Data System (ADS)

Svoboda, Brian E.; Shirley, Yancy

2014-07-01

High mass stars play a key role in the physical and chemical evolution of the interstellar medium, yet the evolution of physical properties for high-mass star-forming regions remains unclear. We sort a sample of ~4668 molecular cloud clumps from the Bolocam Galactic Plane Survey (BGPS) into different evolutionary stages by combining the BGPS 1.1 mm continuum and observational diagnostics of star-formation activity from a variety of Galactic plane surveys: 70 um compact sources, mid-IR color-selected YSOs, H2O and CH3OH masers, EGOs, and UCHII regions. We apply Monte Carlo techniques to distance probability distribution functions (DPDFs) in order to marginalize over the kinematic distance ambiguity and calculate distributions for derived quantities of clumps in different evolutionary stages. We also present a combined NH3 and H2O maser catalog for ~1590 clumps from the literature and our own GBT 100m observations. We identify a sub-sample of 440 dense clumps with no star-formation indicators, representing the largest and most robust sample of pre-protocluster candidates from a blind survey to date. Distributions of I(HCO+), I(N2H+), dv(HCO+), dv(N2H+), mass surface density, and kinetic temperature show strong progressions when separated by evolutionary stage. No progressions are found in size or dust mass; however, weak progressions are observed in area > 2 pc^2 and dust mass > 3 10^3 Msun. An observed breakdown occurs in the size-linewidth relationship and we find no improvement when sampling by evolutionary stage.

Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

NASA Astrophysics Data System (ADS)

Ju, Yaping; Zhang, Chuhua

2016-03-01

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.

Mining manufacturing data for discovery of high productivity process characteristics.

PubMed

Charaniya, Salim; Le, Huong; Rangwala, Huzefa; Mills, Keri; Johnson, Kevin; Karypis, George; Hu, Wei-Shou

2010-06-01

Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 'trains' comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses. 2010 Elsevier B.V. All rights reserved.

Anti-angiogenesis in hepatocellular carcinoma treatment: Current evidence and future perspectives

PubMed Central

Welker, Martin-Walter; Trojan, Joerg

2011-01-01

Hepatocellular carcinoma (HCC) is among the most common cancer diseases worldwide. Arterial hypervascularisation is an essential step for HCC tumorigenesis and can be targeted by transarterial chemoembolization (TACE). This interventional method is the standard treatment for patients with intermediate stage HCC, but is also applied as “bridging” therapy for patients awaiting liver transplantation in many centers worldwide. Usually the devascularization effect induced by TACE is transient, consequently resulting in repeated cycles of TACE every 4-8 wk. Despite documented survival benefits, TACE can also induce the up-regulation of proangiogenic and growth factors, which might contribute to accelerated progression in patients with incomplete response. In 2007, sorafenib, a multi-tyrosine kinase and angiogenesis inhibitor, was approved as the first systemic treatment for advanced stage HCC. Other active targeted compounds, either inhibitors of angiogenesis and/or growth factors, are currently being investigated in numerous clinical trials. To overcome revascularisation or tumor progression under TACE treatment it seems therefore attractive to combine TACE with systemic targeted agents, which might theoretically block the effects of proangiogenic and growth factors. Over the last 12 mo, several retrospective or prospective cohort studies combining TACE and sorafenib have been published. Nevertheless, robust results of the efficacy and tolerability of such combination strategies as proven by randomized, controlled trials are awaited in the next two years. PMID:21912449

An improved robust buffer allocation method for the project scheduling problem

NASA Astrophysics Data System (ADS)

Ghoddousi, Parviz; Ansari, Ramin; Makui, Ahmad

2017-04-01

Unpredictable uncertainties cause delays and additional costs for projects. Often, when using traditional approaches, the optimizing procedure of the baseline project plan fails and leads to delays. In this study, a two-stage multi-objective buffer allocation approach is applied for robust project scheduling. In the first stage, some decisions are made on buffer sizes and allocation to the project activities. A set of Pareto-optimal robust schedules is designed using the meta-heuristic non-dominated sorting genetic algorithm (NSGA-II) based on the decisions made in the buffer allocation step. In the second stage, the Pareto solutions are evaluated in terms of the deviation from the initial start time and due dates. The proposed approach was implemented on a real dam construction project. The outcomes indicated that the obtained buffered schedule reduces the cost of disruptions by 17.7% compared with the baseline plan, with an increase of about 0.3% in the project completion time.

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

The optimality of different strategies for supplemental staging of non-small-cell lung cancer: a health economic decision analysis.

PubMed

Søgaard, Rikke; Fischer, Barbara Malene B; Mortensen, Jann; Rasmussen, Torben R; Lassen, Ulrik

2013-01-01

To assess the expected costs and outcomes of alternative strategies for staging of lung cancer to inform a Danish National Health Service perspective about the most cost-effective strategy. A decision tree was specified for patients with a confirmed diagnosis of non-small-cell lung cancer. Six strategies were defined from relevant combinations of mediastinoscopy, endoscopic or endobronchial ultrasound with needle aspiration, and combined positron emission tomography-computed tomography with F18-fluorodeoxyglucose. Patients without distant metastases and central or contralateral nodal involvement (N2/N3) were considered to be candidates for surgical resection. Diagnostic accuracies were informed from literature reviews, prevalence and survival from the Danish Lung Cancer Registry, and procedure costs from national average tariffs. All parameters were specified probabilistically to determine the joint decision uncertainty. The cost-effectiveness analysis was based on the net present value of expected costs and life years accrued over a time horizon of 5 years. At threshold values of around €30,000 for cost-effectiveness, it was found to be cost-effective to send all patients to positron emission tomography-computed tomography with confirmation of positive findings on nodal involvement by endobronchial ultrasound. This result appeared robust in deterministic sensitivity analysis. The expected value of perfect information was estimated at €52 per patient, indicating that further research might be worthwhile. The policy recommendation is to make combined positron emission tomography-computed tomography and endobronchial ultrasound available for supplemental staging of patients with non-small-cell lung cancer. The effects of alternative strategies on patients' quality of life, however, should be examined in future studies. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Prostate cancer detection: Fusion of cytological and textural features.

PubMed

Nguyen, Kien; Jain, Anil K; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification.

Prostate cancer detection: Fusion of cytological and textural features

PubMed Central

Nguyen, Kien; Jain, Anil K.; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification. PMID:22811959

An adaptive modeling and simulation environment for combined-cycle data reconciliation and degradation estimation

NASA Astrophysics Data System (ADS)

Lin, Tsungpo

Performance engineers face the major challenge in modeling and simulation for the after-market power system due to system degradation and measurement errors. Currently, the majority in power generation industries utilizes the deterministic data matching method to calibrate the model and cascade system degradation, which causes significant calibration uncertainty and also the risk of providing performance guarantees. In this research work, a maximum-likelihood based simultaneous data reconciliation and model calibration (SDRMC) is used for power system modeling and simulation. By replacing the current deterministic data matching with SDRMC one can reduce the calibration uncertainty and mitigate the error propagation to the performance simulation. A modeling and simulation environment for a complex power system with certain degradation has been developed. In this environment multiple data sets are imported when carrying out simultaneous data reconciliation and model calibration. Calibration uncertainties are estimated through error analyses and populated to performance simulation by using principle of error propagation. System degradation is then quantified by performance comparison between the calibrated model and its expected new & clean status. To mitigate smearing effects caused by gross errors, gross error detection (GED) is carried out in two stages. The first stage is a screening stage, in which serious gross errors are eliminated in advance. The GED techniques used in the screening stage are based on multivariate data analysis (MDA), including multivariate data visualization and principal component analysis (PCA). Subtle gross errors are treated at the second stage, in which the serial bias compensation or robust M-estimator is engaged. To achieve a better efficiency in the combined scheme of the least squares based data reconciliation and the GED technique based on hypotheses testing, the Levenberg-Marquardt (LM) algorithm is utilized as the optimizer. To reduce the computation time and stabilize the problem solving for a complex power system such as a combined cycle power plant, meta-modeling using the response surface equation (RSE) and system/process decomposition are incorporated with the simultaneous scheme of SDRMC. The goal of this research work is to reduce the calibration uncertainties and, thus, the risks of providing performance guarantees arisen from uncertainties in performance simulation.

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…

Fuzzy Energy and Reserve Co-optimization With High Penetration of Renewable Energy

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

Liu, Cong; Botterud, Audun; Zhou, Zhi

In this study, we propose a fuzzy-based energy and reserve co-optimization model with consideration of high penetration of renewable energy. Under the assumption of a fixed uncertainty set of renewables, a two-stage robust model is proposed for clearing energy and reserves in the first stage and checking the feasibility and robustness of re-dispatches in the second stage. Fuzzy sets and their membership functions are introduced into the optimization model to represent the satisfaction degree of the variable uncertainty sets. The lower bound of the uncertainty set is expressed as fuzzy membership functions. The solutions are obtained by transforming the fuzzymore » mathematical programming formulation into traditional mixed integer linear programming problems.« less

Fuzzy Energy and Reserve Co-optimization With High Penetration of Renewable Energy

DOE PAGES

Liu, Cong; Botterud, Audun; Zhou, Zhi; ...

2016-10-21

In this study, we propose a fuzzy-based energy and reserve co-optimization model with consideration of high penetration of renewable energy. Under the assumption of a fixed uncertainty set of renewables, a two-stage robust model is proposed for clearing energy and reserves in the first stage and checking the feasibility and robustness of re-dispatches in the second stage. Fuzzy sets and their membership functions are introduced into the optimization model to represent the satisfaction degree of the variable uncertainty sets. The lower bound of the uncertainty set is expressed as fuzzy membership functions. The solutions are obtained by transforming the fuzzymore » mathematical programming formulation into traditional mixed integer linear programming problems.« less

Morphological change in machines accelerates the evolution of robust behavior

PubMed Central

Bongard, Josh

2011-01-01

Most animals exhibit significant neurological and morphological change throughout their lifetime. No robots to date, however, grow new morphological structure while behaving. This is due to technological limitations but also because it is unclear that morphological change provides a benefit to the acquisition of robust behavior in machines. Here I show that in evolving populations of simulated robots, if robots grow from anguilliform into legged robots during their lifetime in the early stages of evolution, and the anguilliform body plan is gradually lost during later stages of evolution, gaits are evolved for the final, legged form of the robot more rapidly—and the evolved gaits are more robust—compared to evolving populations of legged robots that do not transition through the anguilliform body plan. This suggests that morphological change, as well as the evolution of development, are two important processes that improve the automatic generation of robust behaviors for machines. It also provides an experimental platform for investigating the relationship between the evolution of development and robust behavior in biological organisms. PMID:21220304

Seismic isolation of Advanced LIGO: Review of strategy, instrumentation and performance

NASA Astrophysics Data System (ADS)

Matichard, F.; Lantz, B.; Mittleman, R.; Mason, K.; Kissel, J.; Abbott, B.; Biscans, S.; McIver, J.; Abbott, R.; Abbott, S.; Allwine, E.; Barnum, S.; Birch, J.; Celerier, C.; Clark, D.; Coyne, D.; DeBra, D.; DeRosa, R.; Evans, M.; Foley, S.; Fritschel, P.; Giaime, J. A.; Gray, C.; Grabeel, G.; Hanson, J.; Hardham, C.; Hillard, M.; Hua, W.; Kucharczyk, C.; Landry, M.; Le Roux, A.; Lhuillier, V.; Macleod, D.; Macinnis, M.; Mitchell, R.; O'Reilly, B.; Ottaway, D.; Paris, H.; Pele, A.; Puma, M.; Radkins, H.; Ramet, C.; Robinson, M.; Ruet, L.; Sarin, P.; Shoemaker, D.; Stein, A.; Thomas, J.; Vargas, M.; Venkateswara, K.; Warner, J.; Wen, S.

2015-09-01

The new generation of gravitational waves detectors require unprecedented levels of isolation from seismic noise. This article reviews the seismic isolation strategy and instrumentation developed for the Advanced LIGO observatories. It summarizes over a decade of research on active inertial isolation and shows the performance recently achieved at the Advanced LIGO observatories. The paper emphasizes the scientific and technical challenges of this endeavor and how they have been addressed. An overview of the isolation strategy is given. It combines multiple layers of passive and active inertial isolation to provide suitable rejection of seismic noise at all frequencies. A detailed presentation of the three active platforms that have been developed is given. They are the hydraulic pre-isolator, the single-stage internal isolator and the two-stage internal isolator. The architecture, instrumentation, control scheme and isolation results are presented for each of the three systems. Results show that the seismic isolation sub-system meets Advanced LIGO’s stringent requirements and robustly supports the operation of the two detectors.

Microbial communities involved in biogas production exhibit high resilience to heat shocks.

PubMed

Abendroth, Christian; Hahnke, Sarah; Simeonov, Claudia; Klocke, Michael; Casani-Miravalls, Sonia; Ramm, Patrice; Bürger, Christoph; Luschnig, Olaf; Porcar, Manuel

2018-02-01

We report here the impact of heat-shock treatments (55 and 70 °C) on the biogas production within the acidification stage of a two-stage reactor system for anaerobic digestion and biomethanation of grass. The microbiome proved both taxonomically and functionally very robust, since heat shocks caused minor community shifts compared to the controls, and biogas yield was not decreased. The strongest impact on the microbial profile was observed with a combination of heat shock and low pH. Since no transient reduction of microbial diversity occured after the shock, biogas keyplayers, but also potential pathogens, survived the treatment. All along the experiment, the heat-resistant bacterial profile consisted mainly of Firmicutes, Bacteroidetes and Proteobacteria. Bacteroides and Acholeplasma were reduced after heat shocks. An increase was observed for Aminobacterium. Our results prove the stability to thermal stresses of the microbial communities involved in acidification, and the resilience in biogas production irrespectively of the thermal treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust Smoothing: Smoothing Parameter Selection and Applications to Fluorescence Spectroscopy∂

PubMed Central

Lee, Jong Soo; Cox, Dennis D.

2009-01-01

Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. Various robust smoothing methods for estimating fluorescence emission spectra are compared and data driven methods for the selection of smoothing parameter are suggested. The methods currently implemented in R for smoothing parameter selection proved to be unsatisfactory, and a computationally efficient procedure that approximates robust leave-one-out cross validation is presented. PMID:20729976

Robust inertia-free attitude takeover control of postcapture combined spacecraft with guaranteed prescribed performance.

PubMed

Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yin, Zeyang; Wei, Xing; Yuan, Jianping

2018-03-01

In this paper, a robust inertia-free attitude takeover control scheme with guaranteed prescribed performance is investigated for postcapture combined spacecraft with consideration of unmeasurable states, unknown inertial property and external disturbance torque. Firstly, to estimate the unavailable angular velocity of combination accurately, a novel finite-time-convergent tracking differentiator is developed with a quite computationally achievable structure free from the unknown nonlinear dynamics of combined spacecraft. Then, a robust inertia-free prescribed performance control scheme is proposed, wherein, the transient and steady-state performance of combined spacecraft is first quantitatively studied by stabilizing the filtered attitude tracking errors. Compared with the existing works, the prominent advantage is that no parameter identifications and no neural or fuzzy nonlinear approximations are needed, which decreases the complexity of robust controller design dramatically. Moreover, the prescribed performance of combined spacecraft is guaranteed a priori without resorting to repeated regulations of the controller parameters. Finally, four illustrative examples are employed to validate the effectiveness of the proposed control scheme and tracking differentiator. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Stochastic Robust Mathematical Programming Model for Power System Optimization

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

Liu, Cong; Changhyeok, Lee; Haoyong, Chen

2016-01-01

This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.

Tail mean and related robust solution concepts

NASA Astrophysics Data System (ADS)

Ogryczak, Włodzimierz

2014-01-01

Robust optimisation might be viewed as a multicriteria optimisation problem where objectives correspond to the scenarios although their probabilities are unknown or imprecise. The simplest robust solution concept represents a conservative approach focused on the worst-case scenario results optimisation. A softer concept allows one to optimise the tail mean thus combining performances under multiple worst scenarios. We show that while considering robust models allowing the probabilities to vary only within given intervals, the tail mean represents the robust solution for only upper bounded probabilities. For any arbitrary intervals of probabilities the corresponding robust solution may be expressed by the optimisation of appropriately combined mean and tail mean criteria thus remaining easily implementable with auxiliary linear inequalities. Moreover, we use the tail mean concept to develope linear programming implementable robust solution concepts related to risk averse optimisation criteria.

Multi-stage robust scheme for citrus identification from high resolution airborne images

NASA Astrophysics Data System (ADS)

Amorós-López, Julia; Izquierdo Verdiguier, Emma; Gómez-Chova, Luis; Muñoz-Marí, Jordi; Zoilo Rodríguez-Barreiro, Jorge; Camps-Valls, Gustavo; Calpe-Maravilla, Javier

2008-10-01

Identification of land cover types is one of the most critical activities in remote sensing. Nowadays, managing land resources by using remote sensing techniques is becoming a common procedure to speed up the process while reducing costs. However, data analysis procedures should satisfy the accuracy figures demanded by institutions and governments for further administrative actions. This paper presents a methodological scheme to update the citrus Geographical Information Systems (GIS) of the Comunidad Valenciana autonomous region, Spain). The proposed approach introduces a multi-stage automatic scheme to reduce visual photointerpretation and ground validation tasks. First, an object-oriented feature extraction process is carried out for each cadastral parcel from very high spatial resolution (VHR) images (0.5m) acquired in the visible and near infrared. Next, several automatic classifiers (decision trees, multilayer perceptron, and support vector machines) are trained and combined to improve the final accuracy of the results. The proposed strategy fulfills the high accuracy demanded by policy makers by means of combining automatic classification methods with visual photointerpretation available resources. A level of confidence based on the agreement between classifiers allows us an effective management by fixing the quantity of parcels to be reviewed. The proposed methodology can be applied to similar problems and applications.

Advanced Parkinson's or "complex phase" Parkinson's disease? Re-evaluation is needed.

PubMed

Titova, Nataliya; Martinez-Martin, Pablo; Katunina, Elena; Chaudhuri, K Ray

2017-12-01

Holistic management of Parkinson's disease, now recognised as a combined motor and nonmotor disorder, remains a key unmet need. Such management needs relatively accurate definition of the various stages of Parkinson's from early untreated to late palliative as each stage calls for personalised therapies. Management also needs to have a robust knowledge of the progression pattern and clinical heterogeneity of the presentation of Parkinson's which may manifest in a motor dominant or nonmotor dominant manner. The "advanced" stages of Parkinson's disease qualify for advanced treatments such as with continuous infusion or stereotactic surgery yet the concept of "advanced Parkinson's disease" (APD) remains controversial in spite of growing knowledge of the natural history of the motor syndrome of PD. Advanced PD is currently largely defined on the basis of consensus opinion and thus with several caveats. Nonmotor aspects of PD may also reflect advancing course of the disorder, so far not reflected in usual scale based assessments which are largely focussed on motor symptoms. In this paper, we discuss the problems with current definitions of "advanced" PD and also propose the term "complex phase" Parkinson's disease as an alternative which takes into account a multimodal symptoms and biomarker based approach in addition to patient preference.

Interactive outlining: an improved approach using active contours

NASA Astrophysics Data System (ADS)

Daneels, Dirk; van Campenhout, David; Niblack, Carlton W.; Equitz, Will; Barber, Ron; Fierens, Freddy

1993-04-01

The purpose of our work is to outline objects on images in an interactive environment. We use an improved method based on energy minimizing active contours or `snakes.' Kass et al., proposed a variational technique; Amini used dynamic programming; and Williams and Shah introduced a fast, greedy algorithm. We combine the advantages of the latter two methods in a two-stage algorithm. The first stage is a greedy procedure that provides fast initial convergence. It is enhanced with a cost term that extends over a large number of points to avoid oscillations. The second stage, when accuracy becomes important, uses dynamic programming. This step is accelerated by the use of alternating search neighborhoods and by dropping stable points from the iterations. We have also added several features for user interaction. First, the user can define points of high confidence. Mathematically, this results in an extra cost term and, in that way, the robustness in difficult areas (e.g., noisy edges, sharp corners) is improved. We also give the user the possibility of incremental contour tracking, thus providing feedback on the refinement process. The algorithm has been tested on numerous photographic clip art images and extensive tests on medical images are in progress.

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network1[OPEN

PubMed Central

Herman, Dorota; Slabbinck, Bram; Pè, Mario Enrico

2016-01-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. PMID:26754667

Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network.

PubMed

Baute, Joke; Herman, Dorota; Coppens, Frederik; De Block, Jolien; Slabbinck, Bram; Dell'Acqua, Matteo; Pè, Mario Enrico; Maere, Steven; Nelissen, Hilde; Inzé, Dirk

2016-03-01

Leaves are vital organs for biomass and seed production because of their role in the generation of metabolic energy and organic compounds. A better understanding of the molecular networks underlying leaf development is crucial to sustain global requirements for food and renewable energy. Here, we combined transcriptome profiling of proliferative leaf tissue with in-depth phenotyping of the fourth leaf at later stages of development in 197 recombinant inbred lines of two different maize (Zea mays) populations. Previously, correlation analysis in a classical biparental mapping population identified 1,740 genes correlated with at least one of 14 traits. Here, we extended these results with data from a multiparent advanced generation intercross population. As expected, the phenotypic variability was found to be larger in the latter population than in the biparental population, although general conclusions on the correlations among the traits are comparable. Data integration from the two diverse populations allowed us to identify a set of 226 genes that are robustly associated with diverse leaf traits. This set of genes is enriched for transcriptional regulators and genes involved in protein synthesis and cell wall metabolism. In order to investigate the molecular network context of the candidate gene set, we integrated our data with publicly available functional genomics data and identified a growth regulatory network of 185 genes. Our results illustrate the power of combining in-depth phenotyping with transcriptomics in mapping populations to dissect the genetic control of complex traits and present a set of candidate genes for use in biomass improvement. © 2016 American Society of Plant Biologists. All Rights Reserved.

Robust multiperson tracking from a mobile platform.

PubMed

Ess, Andreas; Leibe, Bastian; Schindler, Konrad; van Gool, Luc

2009-10-01

In this paper, we address the problem of multiperson tracking in busy pedestrian zones using a stereo rig mounted on a mobile platform. The complexity of the problem calls for an integrated solution that extracts as much visual information as possible and combines it through cognitive feedback cycles. We propose such an approach, which jointly estimates camera position, stereo depth, object detection, and tracking. The interplay between those components is represented by a graphical model. Since the model has to incorporate object-object interactions and temporal links to past frames, direct inference is intractable. We, therefore, propose a two-stage procedure: for each frame, we first solve a simplified version of the model (disregarding interactions and temporal continuity) to estimate the scene geometry and an overcomplete set of object detections. Conditioned on these results, we then address object interactions, tracking, and prediction in a second step. The approach is experimentally evaluated on several long and difficult video sequences from busy inner-city locations. Our results show that the proposed integration makes it possible to deliver robust tracking performance in scenes of realistic complexity.

No-Reference Image Quality Assessment by Wide-Perceptual-Domain Scorer Ensemble Method.

PubMed

Liu, Tsung-Jung; Liu, Kuan-Hsien

2018-03-01

A no-reference (NR) learning-based approach to assess image quality is presented in this paper. The devised features are extracted from wide perceptual domains, including brightness, contrast, color, distortion, and texture. These features are used to train a model (scorer) which can predict scores. The scorer selection algorithms are utilized to help simplify the proposed system. In the final stage, the ensemble method is used to combine the prediction results from selected scorers. Two multiple-scale versions of the proposed approach are also presented along with the single-scale one. They turn out to have better performances than the original single-scale method. Because of having features from five different domains at multiple image scales and using the outputs (scores) from selected score prediction models as features for multi-scale or cross-scale fusion (i.e., ensemble), the proposed NR image quality assessment models are robust with respect to more than 24 image distortion types. They also can be used on the evaluation of images with authentic distortions. The extensive experiments on three well-known and representative databases confirm the performance robustness of our proposed model.

Robust independent modal space control of a coupled nano-positioning piezo-stage

NASA Astrophysics Data System (ADS)

Zhu, Wei; Yang, Fufeng; Rui, Xiaoting

2018-06-01

In order to accurately control a coupled 3-DOF nano-positioning piezo-stage, this paper designs a hybrid controller. In this controller, a hysteresis observer based on a Bouc-Wen model is established to compensate the hysteresis nonlinearity of the piezoelectric actuator first. Compared to hysteresis compensations using Preisach model and Prandt-Ishlinskii model, the compensation method using the hysteresis observer is computationally lighter. Then, based on the proposed dynamics model, by constructing the modal filter, a robust H∞ independent modal space controller is designed and utilized to decouple the piezo-stage and deal with the unmodeled dynamics, disturbance, and hysteresis compensation error. The effectiveness of the proposed controller is demonstrated experimentally. The experimental results show that the proposed controller can significantly achieve the high-precision positioning.

On adaptive robustness approach to Anti-Jam signal processing

NASA Astrophysics Data System (ADS)

Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

Robust vascular invasion concurrent with intense EGFR immunostaining can predict recurrence in patients with stage IB node-negative gastric cancer.

PubMed

Araki, Ippeita; Washio, Marie; Yamashita, Keishi; Hosoda, Kei; Ema, Akira; Mieno, Hiroaki; Moriya, Hiromitsu; Katada, Natsuya; Kikuchi, Shiro; Watanabe, Masahiko

2018-05-01

The prognosis of most patients with stage IB node-negative gastric cancer is good without postoperative chemotherapy; however, about 10% suffer recurrence and inevitably die. We conducted this study to establish the optimal indications for postoperative adjuvant chemotherapy in patients at risk of recurrence. The subjects of this retrospective study were 124 patients with stage IB node-negative gastric cancer, who underwent gastrectomy at the Kitasato University East Hospital, between 2001 and 2010. We reviewed EGFR immunohistochemistry (IHC) as well as clinicopathological factors. Of the 124 patients, 47 (38%) showed intense EGFR IHC (2+ or 3+), with significantly less frequency than in stage II/III advanced gastric cancer (p < 0.001). According to univariate analysis, intense EGFR IHC was significantly associated with relapse-free survival (RFS) (p = 0.023) and associated with overall survival (OS) (p = 0.045) as well as vascular invasion (p = 0.031). On the multivariate Cox proportional hazards model, intense EGFR IHC(p = 0.016) was an independent prognostic predictor for RFS, and both vascular invasion (p = 0.033) and intense EGFR IHC (p = 0.031) were independent prognostic predictors for OS. The combination of both factors increased the risk of recurrence (p = 0.001). In stage IB node-negative gastric cancer, vascular invasion and intense EGFR IHC increase the likelihood of recurrence. We recommend adjuvant chemotherapy for such patients because of the high risk of metachronous recurrence.

Analytical redundancy and the design of robust failure detection systems

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Willsky, A. S.

1984-01-01

The Failure Detection and Identification (FDI) process is viewed as consisting of two stages: residual generation and decision making. It is argued that a robust FDI system can be achieved by designing a robust residual generation process. Analytical redundancy, the basis for residual generation, is characterized in terms of a parity space. Using the concept of parity relations, residuals can be generated in a number of ways and the design of a robust residual generation process can be formulated as a minimax optimization problem. An example is included to illustrate this design methodology. Previously announcedd in STAR as N83-20653

Robustness-Based Design Optimization Under Data Uncertainty

NASA Technical Reports Server (NTRS)

Zaman, Kais; McDonald, Mark; Mahadevan, Sankaran; Green, Lawrence

2010-01-01

This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distributions of the random variables. A decoupled approach is proposed in this paper to un-nest the robustness-based design from the analysis of non-design epistemic variables to achieve computational efficiency. The proposed methods are illustrated for the upper stage design problem of a two-stage-to-orbit (TSTO) vehicle, where the information on the random design inputs are only available as sparse point and/or interval data. As collecting more data reduces uncertainty but increases cost, the effect of sample size on the optimality and robustness of the solution is also studied. A method is developed to determine the optimal sample size for sparse point data that leads to the solutions of the design problem that are least sensitive to variations in the input random variables.

A family of high-order gas-kinetic schemes and its comparison with Riemann solver based high-order methods

NASA Astrophysics Data System (ADS)

Ji, Xing; Zhao, Fengxiang; Shyy, Wei; Xu, Kun

2018-03-01

Most high order computational fluid dynamics (CFD) methods for compressible flows are based on Riemann solver for the flux evaluation and Runge-Kutta (RK) time stepping technique for temporal accuracy. The advantage of this kind of space-time separation approach is the easy implementation and stability enhancement by introducing more middle stages. However, the nth-order time accuracy needs no less than n stages for the RK method, which can be very time and memory consuming due to the reconstruction at each stage for a high order method. On the other hand, the multi-stage multi-derivative (MSMD) method can be used to achieve the same order of time accuracy using less middle stages with the use of the time derivatives of the flux function. For traditional Riemann solver based CFD methods, the lack of time derivatives in the flux function prevents its direct implementation of the MSMD method. However, the gas kinetic scheme (GKS) provides such a time accurate evolution model. By combining the second-order or third-order GKS flux functions with the MSMD technique, a family of high order gas kinetic methods can be constructed. As an extension of the previous 2-stage 4th-order GKS, the 5th-order schemes with 2 and 3 stages will be developed in this paper. Based on the same 5th-order WENO reconstruction, the performance of gas kinetic schemes from the 2nd- to the 5th-order time accurate methods will be evaluated. The results show that the 5th-order scheme can achieve the theoretical order of accuracy for the Euler equations, and present accurate Navier-Stokes solutions as well due to the coupling of inviscid and viscous terms in the GKS formulation. In comparison with Riemann solver based 5th-order RK method, the high order GKS has advantages in terms of efficiency, accuracy, and robustness, for all test cases. The 4th- and 5th-order GKS have the same robustness as the 2nd-order scheme for the capturing of discontinuous solutions. The current high order MSMD GKS is a multi-dimensional scheme with incorporation of both normal and tangential spatial derivatives of flow variables at a cell interface in the flux evaluation. The scheme can be extended straightforwardly to viscous flow computation in unstructured mesh. It provides a promising direction for the development of high-order CFD methods for the computation of complex flows, such as turbulence and acoustics with shock interactions.

Early Stages of the Evolution of Life: a Cybernetic Approach

NASA Astrophysics Data System (ADS)

Melkikh, Alexey V.; Seleznev, Vladimir D.

2008-08-01

Early stages of the evolution of life are considered in terms of control theory. A model is proposed for the transport of substances in a protocell possessing the property of robustness with regard to changes in the environmental concentration of a substance.

Early stages of the evolution of life: a cybernetic approach.

PubMed

Melkikh, Alexey V; Seleznev, Vladimir D

2008-08-01

Early stages of the evolution of life are considered in terms of control theory. A model is proposed for the transport of substances in a protocell possessing the property of robustness with regard to changes in the environmental concentration of a substance.

ARIANE 5 upper-stage ignition conditions improvement, and return to operation with ''Envisat'' payload

NASA Astrophysics Data System (ADS)

Dutheil, J. Ph.; Langel, G.

2003-08-01

ARIANE 5 experienced a flight anomaly with the 10 th model mission (F 510), having placed its both satellites in a lower orbit than the planned GTO. Only one satellite (Artemis) could be retrieved due to its own propulsion systems. Arianespace, CNES and Astrium-GmbH (former DaimlerChrysler Aerospace Dasa) immediately set up a recovery team, combining forces for carrying deep and schedule-driven investigations, and later qualifying recovery measures. A failure in such an important program: is immediately triggering a large "post-shock" reaction from the ARIANE community implied in the relevant business and technology. The investigation fields are summarised in the following chapters, showing how failure analysis, engineering investigations and basic research have been combined in order to have a schedule and methodic efficient approach. The combination of all available European resources in space vehicle design has been implemented, involving industry, agency technical centers and research laboratories. The investigation methodology applied has been driven by the particular situation of a flight anomaly investigation, which has to take into account the reduced amount of measurement available in flight and the necessary combination with ground test data for building a strategy to reach identification of possible failure scenario. From the investigations and from extensive sensitivity characterisation test of EPS engine (AESTUS) ignition transient, stability margins have been deeply investigated and introduced in the post-anomaly upgraded stage design. The identification and implementation of recovery measures, extended as well to - potential ignition margin reduction factors even beyond the observed flight anomaly allowed to establish a robust complementary qualification status, thus allowing resuming of operational flight, starting with the valuable "Envisat" payload of European Space Agency, dedicated to earth and climate monitoring, on flight 511, the 28/02/2002, from Kourou Spaceport.

A Robust High Current Density Electron Gun

NASA Astrophysics Data System (ADS)

Mako, F.; Peter, W.; Shiloh, J.; Len, L. K.

1996-11-01

Proof-of-principle experiments are proposed to validate a new concept for a robust, high-current density Pierce electron gun (RPG) for use in klystrons and high brightness electron sources for accelerators. This rugged, long-life electron gun avoids the difficulties associated with plasma cathodes, thermionic emitters, and field emission cathodes. The RPG concept employs the emission of secondary electrons in a transmission mode as opposed to the conventional mode of reflection, i.e., electrons exit from the back face of a thin negative electron affinity (NEA) material, and in the same direction as the incident beam. Current amplification through one stage of a NEA material could be over 50 times. The amplification is accomplished in one or more stages consisting of one primary emitter and one or more secondary emitters. The primary emitter is a low current density robust emitter (e.g., thoriated tungsten). The secondary emitters are thin NEA electrodes which emit secondary electrons in the same direction as the incident beam. Specific application is targeted for a klystron gun to be used by SLAC with a cold cathode at 30-40 amps/cm^2 output from the secondary emission stage, a ~2 μs pulse length, and ~200 pulses/second.

Analysis of a New Rocket-Based Combined-Cycle Engine Concept at Low Speed

NASA Technical Reports Server (NTRS)

Yungster, S.; Trefny, C. J.

1999-01-01

An analysis of the Independent Ramjet Stream (IRS) cycle is presented. The IRS cycle is a variation of the conventional ejector-Ramjet, and is used at low speed in a rocket-based combined-cycle (RBCC) propulsion system. In this new cycle, complete mixing between the rocket and ramjet streams is not required, and a single rocket chamber can be used without a long mixing duct. Furthermore, this concept allows flexibility in controlling the thermal choke process. The resulting propulsion system is intended to be simpler, more robust, and lighter than an ejector-ramjet. The performance characteristics of the IRS cycle are analyzed for a new single-stage-to-orbit (SSTO) launch vehicle concept, known as "Trailblazer." The study is based on a quasi-one-dimensional model of the rocket and air streams at speeds ranging from lift-off to Mach 3. The numerical formulation is described in detail. A performance comparison between the IRS and ejector-ramjet cycles is also presented.

Teacher Research as a Robust and Reflective Path to Professional Development

ERIC Educational Resources Information Center

Roberts, Sherron Killingsworth; Crawford, Patricia A.; Hickmann, Rosemary

2010-01-01

This article explores the role of teacher research as part of a robust program of professional development. Teacher research offers teachers at every stage of development a recursive and reflective means of bridging the gap between current practice and potential professional growth. The purpose of this dual level inquiry was to probe the concept…

Deficient prepulse inhibition in schizophrenia in a multi-site cohort: Internal replication and extension.

PubMed

Swerdlow, Neal R; Light, Gregory A; Thomas, Michael L; Sprock, Joyce; Calkins, Monica E; Green, Michael F; Greenwood, Tiffany A; Gur, Raquel E; Gur, Ruben C; Lazzeroni, Laura C; Nuechterlein, Keith H; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

2017-05-23

The Consortium on the Genetics of Schizophrenia (COGS) collected case-control endophenotype and genetic information from 2457 patients and healthy subjects (HS) across 5 test sites over 3.5 years. Analysis of the first "wave" (W1) of 1400 subjects identified prepulse inhibition (PPI) deficits in patients vs. HS. Data from the second COGS "wave" (W2), and the combined W(1+2), were used to assess: 1) the replicability of PPI deficits in this design; 2) the impact of response criteria on PPI deficits; and 3) PPI in a large cohort of antipsychotic-free patients. PPI in W2 HS (n=315) and schizophrenia patients (n=326) was compared to findings from W1; planned analyses assessed the impact of diagnosis, "wave" (1 vs. 2), and startle magnitude criteria. Combining waves allowed us to assess PPI in 120 antipsychotic-free patients, including many in the early course of illness. ANOVA of all W(1+2) subjects revealed robust PPI deficits in patients across "waves" (p<0.0004). Strict response criteria excluded almost 39% of all subjects, disproportionately impacting specific subgroups; ANOVA in this smaller cohort confirmed no significant effect of "wave" or "wave x diagnosis" interaction, and a significant effect of diagnosis (p<0.002). Antipsychotic-free, early-illness patients had particularly robust PPI deficits. Schizophrenia-linked PPI deficits were replicable across two multi-site "waves" of subjects collected over 3.5years. Strict response criteria disproportionately excluded older, male, non-Caucasian patients with low-normal hearing acuity. These findings set the stage for genetic analyses of PPI using the combined COGS wave 1 and 2 cohorts. Copyright © 2017 Elsevier B.V. All rights reserved.

Construction and analysis of tissue microarrays in the era of digital pathology: a pilot study targeting CDX1 and CDX2 in a colon cancer cohort of 612 patients

PubMed Central

Nolte, Sarah; Zlobec, Inti; Lugli, Alessandro; Hohenberger, Werner; Croner, Roland; Merkel, Susanne; Hartmann, Arndt; Geppert, Carol I

2017-01-01

Abstract CDX1 and CDX2 are possibly predictive biomarkers in colorectal cancer. We combined digitally‐guided (next generation) TMA construction (ngTMA) and the utility of digital image analysis (DIA) to assess accuracy, tumour heterogeneity and the selective impact of different combined intensity‐percentage levels on prognosis.CDX1 and CDX2 immunohistochemistry was performed on ngTMAs covering normal tissue, tumour centre and invasive front. The percentages of all epithelial cells per staining intensity per core were analysed digitally. Beyond classical prognosis analysis following REMARK guidelines, we investigated pre‐analytical conditions, three different types of heterogeneity (mosaic‐like, targeted and haphazard) and influences on cohort segregation and patient selection. The ngTMA‐DIA approach produced robust biomarker data with infrequent core loss and excellent on‐target punching. The detailed assessment of tumour heterogeneity could – except for a certain diffuse mosaic‐like heterogeneity – exclude differences between the invasive front and tumour centre, as well as detect haphazard clonal heterogeneous elements. Moreover, lower CDX1 and CDX2 counts correlated with mucinous histology, higher TNM stage, higher tumour grade and worse survival (p < 0.01, all). Different protein expression intensity levels shared comparable prognostic power and a great overlap in patient selection. The combination of ngTMA with DIA enhances accuracy and controls for biomarker analysis. Beyond the confirmation of CDX1 and CDX2 as prognostically relevant markers in CRC, this study highlights the greater robustness of CDX2 in comparison to CDX1. For the assessment of CDX2 protein loss, cut‐points as percentage data of complete protein loss can be deduced as a recommendation. PMID:28138402

Quality-by-design-based ultra high performance liquid chromatography related substances method development by establishing the proficient design space for sumatriptan and naproxen combination.

PubMed

Patel, Prinesh N; Karakam, Vijaya Saradhi; Samanthula, Gananadhamu; Ragampeta, Srinivas

2015-10-01

Quality-by-design-based methods hold greater level of confidence for variations and greater success in method transfer. A quality-by-design-based ultra high performance liquid chromatography method was developed for the simultaneous assay of sumatriptan and naproxen along with their related substances. The first screening was performed by fractional factorial design comprising 44 experiments for reversed-phase stationary phases, pH, and organic modifiers. The results of screening design experiments suggested phenyl hexyl column and acetonitrile were the best combination. The method was further optimized for flow rate, temperature, and gradient time by experimental design of 20 experiments and the knowledge space was generated for effect of variable on response (number of peaks ≥ 1.50 - resolution). Proficient design space was generated from knowledge space by applying Monte Carlo simulation to successfully integrate quantitative robustness metrics during optimization stage itself. The final method provided the robust performance which was verified and validated. Final conditions comprised Waters® Acquity phenyl hexyl column with gradient elution using ammonium acetate (pH 4.12, 0.02 M) buffer and acetonitrile at 0.355 mL/min flow rate and 30°C. The developed method separates all 13 analytes within a 15 min run time with fewer experiments compared to the traditional quality-by-testing approach. ©2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomimetics of fetal alveolar flow phenomena using microfluidics.

PubMed

Tenenbaum-Katan, Janna; Fishler, Rami; Rothen-Rutishauser, Barbara; Sznitman, Josué

2015-01-01

At the onset of life in utero, the respiratory system begins as a liquid-filled tubular organ and undergoes significant morphological changes during fetal development towards establishing a respiratory organ optimized for gas exchange. As airspace morphology evolves, respiratory alveolar flows have been hypothesized to exhibit evolving flow patterns. In the present study, we have investigated flow topologies during increasing phases of embryonic life within an anatomically inspired microfluidic device, reproducing real-scale features of fetal airways representative of three distinct phases of in utero gestation. Micro-particle image velocimetry measurements, supported by computational fluid dynamics simulations, reveal distinct respiratory alveolar flow patterns throughout different stages of fetal life. While attached, streamlined flows characterize the shallow structures of premature alveoli indicative of the onset of saccular stage, separated recirculating vortex flows become the signature of developed and extruded alveoli characteristic of the advanced stages of fetal development. To further mimic physiological aspects of the cellular environment of developing airways, our biomimetic devices integrate an alveolar epithelium using the A549 cell line, recreating a confluent monolayer that produces pulmonary surfactant. Overall, our in vitro biomimetic fetal airways model delivers a robust and reliable platform combining key features of alveolar morphology, flow patterns, and physiological aspects of fetal lungs developing in utero.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Staged anticonvulsant screening for chronic epilepsy.

PubMed

Berdichevsky, Yevgeny; Saponjian, Yero; Park, Kyung-Il; Roach, Bonnie; Pouliot, Wendy; Lu, Kimberly; Swiercz, Waldemar; Dudek, F Edward; Staley, Kevin J

2016-12-01

Current anticonvulsant screening programs are based on seizures evoked in normal animals. One-third of epileptic patients do not respond to the anticonvulsants discovered with these models. We evaluated a tiered program based on chronic epilepsy and spontaneous seizures, with compounds advancing from high-throughput in vitro models to low-throughput in vivo models. Epileptogenesis in organotypic hippocampal slice cultures was quantified by lactate production and lactate dehydrogenase release into culture media as rapid assays for seizure-like activity and cell death, respectively. Compounds that reduced these biochemical measures were retested with in vitro electrophysiological confirmation (i.e., second stage). The third stage involved crossover testing in the kainate model of chronic epilepsy, with blinded analysis of spontaneous seizures after continuous electrographic recordings. We screened 407 compound-concentration combinations. The cyclooxygenase inhibitor, celecoxib, had no effect on seizures evoked in normal brain tissue but demonstrated robust antiseizure activity in all tested models of chronic epilepsy. The use of organotypic hippocampal cultures, where epileptogenesis occurs on a compressed time scale, and where seizure-like activity and seizure-induced cell death can be easily quantified with biomarker assays, allowed us to circumvent the throughput limitations of in vivo chronic epilepsy models. Ability to rapidly screen compounds in a chronic model of epilepsy allowed us to find an anticonvulsant that would be missed by screening in acute models.

The development of a standardised diet history tool to support the diagnosis of food allergy.

PubMed

Skypala, Isabel J; Venter, Carina; Meyer, Rosan; deJong, Nicolette W; Fox, Adam T; Groetch, Marion; Oude Elberink, J N; Sprikkelman, Aline; Diamandi, Louiza; Vlieg-Boerstra, Berber J

2015-01-01

The disparity between reported and diagnosed food allergy makes robust diagnosis imperative. The allergy-focussed history is an important starting point, but published literature on its efficacy is sparse. Using a structured approach to connect symptoms, suspected foods and dietary intake, a multi-disciplinary task force of the European Academy of Allergy and Clinical Immunology developed paediatric and adult diet history tools. Both tools are divided into stages using traffic light labelling (red, amber and green). The red stage requires the practitioner to gather relevant information on symptoms, atopic history, food triggers, foods eaten and nutritional issues. The amber stage facilitates interpretation of the responses to the red-stage questions, thus enabling the practitioner to prepare to move forward. The final green stage provides a summary template and test algorithm to support continuation down the diagnostic pathway. These tools will provide a standardised, practical approach to support food allergy diagnosis, ensuring that all relevant information is captured and interpreted in a robust manner. Future work is required to validate their use in diverse age groups, disease entities and in different countries, in order to account for differences in health care systems, food availability and dietary norms.

Functional genomics platform for pooled screening and mammalian genetic interaction maps

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2014-01-01

Systematic genetic interaction maps in microorganisms are powerful tools for identifying functional relationships between genes and defining the function of uncharacterized genes. We have recently implemented this strategy in mammalian cells as a two-stage approach. First, genes of interest are robustly identified in a pooled genome-wide screen using complex shRNA libraries. Second, phenotypes for all pairwise combinations of hit genes are measured in a double-shRNA screen and used to construct a genetic interaction map. Our protocol allows for rapid pooled screening under various conditions without a requirement for robotics, in contrast to arrayed approaches. Each stage of the protocol can be implemented in ~2 weeks, with additional time for analysis and generation of reagents. We discuss considerations for screen design, and present complete experimental procedures as well as a full computational analysis suite for identification of hits in pooled screens and generation of genetic interaction maps. While the protocols outlined here were developed for our original shRNA-based approach, they can be applied more generally, including to CRISPR-based approaches. PMID:24992097

Regime switching model for financial data: Empirical risk analysis

NASA Astrophysics Data System (ADS)

Salhi, Khaled; Deaconu, Madalina; Lejay, Antoine; Champagnat, Nicolas; Navet, Nicolas

2016-11-01

This paper constructs a regime switching model for the univariate Value-at-Risk estimation. Extreme value theory (EVT) and hidden Markov models (HMM) are combined to estimate a hybrid model that takes volatility clustering into account. In the first stage, HMM is used to classify data in crisis and steady periods, while in the second stage, EVT is applied to the previously classified data to rub out the delay between regime switching and their detection. This new model is applied to prices of numerous stocks exchanged on NYSE Euronext Paris over the period 2001-2011. We focus on daily returns for which calibration has to be done on a small dataset. The relative performance of the regime switching model is benchmarked against other well-known modeling techniques, such as stable, power laws and GARCH models. The empirical results show that the regime switching model increases predictive performance of financial forecasting according to the number of violations and tail-loss tests. This suggests that the regime switching model is a robust forecasting variant of power laws model while remaining practical to implement the VaR measurement.

Deregulation of MiR-34b/Sox2 Predicts Prostate Cancer Progression.

PubMed

Forno, Irene; Ferrero, Stefano; Russo, Maria Veronica; Gazzano, Giacomo; Giangiobbe, Sara; Montanari, Emanuele; Del Nero, Alberto; Rocco, Bernardo; Albo, Giancarlo; Languino, Lucia R; Altieri, Dario C; Vaira, Valentina; Bosari, Silvano

2015-01-01

Most men diagnosed with prostate cancer will have an indolent and curable disease, whereas approximately 15% of these patients will rapidly progress to a castrate-resistant and metastatic stage with high morbidity and mortality. Therefore, the identification of molecular signature(s) that detect men at risk of progressing disease remains a pressing and still unmet need for these patients. Here, we used an integrated discovery platform combining prostate cancer cell lines, a Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP) model and clinically-annotated human tissue samples to identify loss of expression of microRNA-34b as consistently associated with prostate cancer relapse. Mechanistically, this was associated with epigenetics silencing of the MIR34B/C locus and increased DNA copy number loss, selectively in androgen-dependent prostate cancer. In turn, loss of miR-34b resulted in downstream deregulation and overexpression of the "stemness" marker, Sox2. These findings identify loss of miR-34b as a robust biomarker for prostate cancer progression in androgen-sensitive tumors, and anticipate a potential role of progenitor/stem cell signaling in this stage of disease.

Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

PubMed

Slater, Graham J; Pennell, Matthew W

2014-05-01

A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.

Multilevel robustness

NASA Astrophysics Data System (ADS)

Girard, Henri-Louis; Khan, Sami; Varanasi, Kripa K.

2018-03-01

A combination of hard, soft and nanoscale organic components results in robust superhydrophobic surfaces that can withstand mechanical abrasion and chemical oxidation, and exhibit excellent substrate adhesion.

Joint detection and localization of multiple anatomical landmarks through learning

NASA Astrophysics Data System (ADS)

Dikmen, Mert; Zhan, Yiqiang; Zhou, Xiang Sean

2008-03-01

Reliable landmark detection in medical images provides the essential groundwork for successful automation of various open problems such as localization, segmentation, and registration of anatomical structures. In this paper, we present a learning-based system to jointly detect (is it there?) and localize (where?) multiple anatomical landmarks in medical images. The contributions of this work exist in two aspects. First, this method takes the advantage from the learning scenario that is able to automatically extract the most distinctive features for multi-landmark detection. Therefore, it is easily adaptable to detect arbitrary landmarks in various kinds of imaging modalities, e.g., CT, MRI and PET. Second, the use of multi-class/cascaded classifier architecture in different phases of the detection stage combined with robust features that are highly efficient in terms of computation time enables a seemingly real time performance, with very high localization accuracy. This method is validated on CT scans of different body sections, e.g., whole body scans, chest scans and abdominal scans. Aside from improved robustness (due to the exploitation of spatial correlations), it gains a run time efficiency in landmark detection. It also shows good scalability performance under increasing number of landmarks.

Cellular mechanisms underlying spatiotemporal features of cholinergic retinal waves

PubMed Central

Ford, Kevin J.; Félix, Aude L.; Feller, Marla B.

2012-01-01

Prior to vision, a transient network of recurrently connected cholinergic interneurons, called starburst amacrine cells (SACs), generates spontaneous retinal waves. Despite an absence of robust inhibition, cholinergic retinal waves initiate infrequently and propagate within finite boundaries. Here we combine a variety of electrophysiological and imaging techniques and computational modeling to elucidate the mechanisms underlying these spatial and temporal properties of waves in developing mouse retina. Waves initiate via rare spontaneous depolarizations of SACs. Waves propagate through recurrent cholinergic connections between SACs and volume release of ACh as demonstrated using paired recordings and a cell-based ACh optical sensor. Perforated patch recordings and two-photon calcium imaging reveal that individual SACs have slow afterhyperpolarizations that induce SACs to have variable depolarizations during sequential waves. Using a computational model in which the properties of SACs are based on these physiological measurements, we reproduce the slow frequency, speed, and finite size of recorded waves. This study represents a detailed description of the circuit that mediates cholinergic retinal waves and indicates that variability of the interneurons that generate this network activity may be critical for the robustness of waves across different species and stages of development. PMID:22262883

Rapid quantification of casein in skim milk using Fourier transform infrared spectroscopy, enzymatic perturbation, and multiway partial least squares regression: Monitoring chymosin at work.

PubMed

Baum, A; Hansen, P W; Nørgaard, L; Sørensen, John; Mikkelsen, J D

2016-08-01

In this study, we introduce enzymatic perturbation combined with Fourier transform infrared (FTIR) spectroscopy as a concept for quantifying casein in subcritical heated skim milk using chemometric multiway analysis. Chymosin is a protease that cleaves specifically caseins. As a result of hydrolysis, all casein proteins clot to form a creamy precipitate, and whey proteins remain in the supernatant. We monitored the cheese-clotting reaction in real time using FTIR and analyzed the resulting evolution profiles to establish calibration models using parallel factor analysis and multiway partial least squares regression. Because we observed casein-specific kinetic changes, the retrieved models were independent of the chemical background matrix and were therefore robust against possible covariance effects. We tested the robustness of the models by spiking the milk solutions with whey, calcium, and cream. This method can be used at different stages in the dairy production chain to ensure the quality of the delivered milk. In particular, the cheese-making industry can benefit from such methods to optimize production control. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Robust Speaker Authentication Based on Combined Speech and Voiceprint Recognition

NASA Astrophysics Data System (ADS)

Malcangi, Mario

2009-08-01

Personal authentication is becoming increasingly important in many applications that have to protect proprietary data. Passwords and personal identification numbers (PINs) prove not to be robust enough to ensure that unauthorized people do not use them. Biometric authentication technology may offer a secure, convenient, accurate solution but sometimes fails due to its intrinsically fuzzy nature. This research aims to demonstrate that combining two basic speech processing methods, voiceprint identification and speech recognition, can provide a very high degree of robustness, especially if fuzzy decision logic is used.

Collaborative Research: Equipment for and Running of the PSI MUSE Experiment

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

Kohl, Michael

The R&D funding from this award has been a significant tool to move the Muon Scattering Experiment (MUSE) at the Paul Scherrer Institute in Switzerland forward to the stage of realization. Specifically, this award has enabled Dr. Michael Kohl and his working group at Hampton University to achieve substantial progress toward the goal of providing beam particle tracking with Gas Electron Multiplier (GEM) detectors for MUSE experiment. Establishing a particle detection system that is capable of operating in a high-intensity environment, with a data acquisition system capable of running at several kHz, combined with robust tracking software providing high efficiencymore » for track reconstruction in the presence of noise and backgrounds will have immediate application in many other experiments.« less

Robust, High-Speed Network Design for Large-Scale Multiprocessing

DTIC Science & Technology

1993-09-01

3.17 Left: Non-expansive Wiring of Processors to First Stage Routing Elements . ... 38 3.18 Right: Expansive Wiring of Processors to First Stage...162 8.2 RNI Micro -architecture ........ .............................. 163 8.3 Packaged RN I IC...169 11.1 MLUNK Message Formats ........ .............................. 173 12.1 Routing Board Arrangement for 64- processor Machine

Robust Group Sparse Beamforming for Multicast Green Cloud-RAN With Imperfect CSI

NASA Astrophysics Data System (ADS)

Shi, Yuanming; Zhang, Jun; Letaief, Khaled B.

2015-09-01

In this paper, we investigate the network power minimization problem for the multicast cloud radio access network (Cloud-RAN) with imperfect channel state information (CSI). The key observation is that network power minimization can be achieved by adaptively selecting active remote radio heads (RRHs) via controlling the group-sparsity structure of the beamforming vector. However, this yields a non-convex combinatorial optimization problem, for which we propose a three-stage robust group sparse beamforming algorithm. In the first stage, a quadratic variational formulation of the weighted mixed l1/l2-norm is proposed to induce the group-sparsity structure in the aggregated beamforming vector, which indicates those RRHs that can be switched off. A perturbed alternating optimization algorithm is then proposed to solve the resultant non-convex group-sparsity inducing optimization problem by exploiting its convex substructures. In the second stage, we propose a PhaseLift technique based algorithm to solve the feasibility problem with a given active RRH set, which helps determine the active RRHs. Finally, the semidefinite relaxation (SDR) technique is adopted to determine the robust multicast beamformers. Simulation results will demonstrate the convergence of the perturbed alternating optimization algorithm, as well as, the effectiveness of the proposed algorithm to minimize the network power consumption for multicast Cloud-RAN.

Assessing the robustness of passive scattering proton therapy with regard to local recurrence in stage III non-small cell lung cancer: a secondary analysis of a phase II trial.

PubMed

Zhu, Zhengfei; Liu, Wei; Gillin, Michael; Gomez, Daniel R; Komaki, Ritsuko; Cox, James D; Mohan, Radhe; Chang, Joe Y

2014-05-06

We assessed the robustness of passive scattering proton therapy (PSPT) plans for patients in a phase II trial of PSPT for stage III non-small cell lung cancer (NSCLC) by using the worst-case scenario method, and compared the worst-case dose distributions with the appearance of locally recurrent lesions. Worst-case dose distributions were generated for each of 9 patients who experienced recurrence after concurrent chemotherapy and PSPT to 74 Gy(RBE) for stage III NSCLC by simulating and incorporating uncertainties associated with set-up, respiration-induced organ motion, and proton range in the planning process. The worst-case CT scans were then fused with the positron emission tomography (PET) scans to locate the recurrence. Although the volumes enclosed by the prescription isodose lines in the worst-case dose distributions were consistently smaller than enclosed volumes in the nominal plans, the target dose coverage was not significantly affected: only one patient had a recurrence outside the prescription isodose lines in the worst-case plan. PSPT is a relatively robust technique. Local recurrence was not associated with target underdosage resulting from estimated uncertainties in 8 of 9 cases.

Identifying elderly people at risk for cognitive decline by using the 2-step test.

PubMed

Maruya, Kohei; Fujita, Hiroaki; Arai, Tomoyuki; Hosoi, Toshiki; Ogiwara, Kennichi; Moriyama, Shunnichiro; Ishibashi, Hideaki

2018-01-01

[Purpose] The purpose is to verify the effectiveness of the 2-step test in predicting cognitive decline in elderly individuals. [Subjects and Methods] One hundred eighty-two participants aged over 65 years underwent the 2-step test, cognitive function tests and higher level competence testing. Participants were classified as Robust, <1.3, and <1.1 using criteria regarding the locomotive syndrome risk stage for the 2-step test, variables were compared between groups. In addition, ordered logistic analysis was used to analyze cognitive functions as independent variables in the three groups, using the 2-step test results as the dependent variable, with age, gender, etc. as adjustment factors. [Results] In the crude data, the <1.3 and <1.1 groups were older and displayed lower motor and cognitive functions than did the Robust group. Furthermore, the <1.3 group exhibited significantly lower memory retention than did the Robust group. The 2-step test was related to the Stroop test (β: 0.06, 95% confidence interval: 0.01-0.12). [Conclusion] The finding is that the risk stage of the 2-step test is related to cognitive functions, even at an initial risk stage. The 2-step test may help with earlier detection and implementation of prevention measures for locomotive syndrome and mild cognitive impairment.

Meta-analysis reveals complex marine biological responses to the interactive effects of ocean acidification and warming

PubMed Central

Harvey, Ben P; Gwynn-Jones, Dylan; Moore, Pippa J

2013-01-01

Ocean acidification and warming are considered two of the greatest threats to marine biodiversity, yet the combined effect of these stressors on marine organisms remains largely unclear. Using a meta-analytical approach, we assessed the biological responses of marine organisms to the effects of ocean acidification and warming in isolation and combination. As expected biological responses varied across taxonomic groups, life-history stages, and trophic levels, but importantly, combining stressors generally exhibited a stronger biological (either positive or negative) effect. Using a subset of orthogonal studies, we show that four of five of the biological responses measured (calcification, photosynthesis, reproduction, and survival, but not growth) interacted synergistically when warming and acidification were combined. The observed synergisms between interacting stressors suggest that care must be made in making inferences from single-stressor studies. Our findings clearly have implications for the development of adaptive management strategies particularly given that the frequency of stressors interacting in marine systems will be likely to intensify in the future. There is now an urgent need to move toward more robust, holistic, and ecologically realistic climate change experiments that incorporate interactions. Without them accurate predictions about the likely deleterious impacts to marine biodiversity and ecosystem functioning over the next century will not be possible. PMID:23610641

Meta-analysis reveals complex marine biological responses to the interactive effects of ocean acidification and warming.

PubMed

Harvey, Ben P; Gwynn-Jones, Dylan; Moore, Pippa J

2013-04-01

Ocean acidification and warming are considered two of the greatest threats to marine biodiversity, yet the combined effect of these stressors on marine organisms remains largely unclear. Using a meta-analytical approach, we assessed the biological responses of marine organisms to the effects of ocean acidification and warming in isolation and combination. As expected biological responses varied across taxonomic groups, life-history stages, and trophic levels, but importantly, combining stressors generally exhibited a stronger biological (either positive or negative) effect. Using a subset of orthogonal studies, we show that four of five of the biological responses measured (calcification, photosynthesis, reproduction, and survival, but not growth) interacted synergistically when warming and acidification were combined. The observed synergisms between interacting stressors suggest that care must be made in making inferences from single-stressor studies. Our findings clearly have implications for the development of adaptive management strategies particularly given that the frequency of stressors interacting in marine systems will be likely to intensify in the future. There is now an urgent need to move toward more robust, holistic, and ecologically realistic climate change experiments that incorporate interactions. Without them accurate predictions about the likely deleterious impacts to marine biodiversity and ecosystem functioning over the next century will not be possible.

Characterisation of the HLA-DRB1*07:01 biomarker for lapatinib-induced liver toxicity during treatment of early-stage breast cancer patients with lapatinib in combination with trastuzumab and/or taxanes.

PubMed

Spraggs, C F; Parham, L R; Briley, L P; Warren, L; Williams, L S; Fraser, D J; Jiang, Z; Aziz, Z; Ahmed, S; Demetriou, G; Mehta, A; Jackson, N; Byrne, J; Andersson, M; Toi, M; Harris, L; Gralow, J; Zujewski, J A; Crescenzo, R; Armour, A; Perez, E; Piccart, M

2018-05-22

HLA-DRB1*07:01 allele carriage was characterised as a risk biomarker for lapatinib-induced liver injury in a large global study evaluating lapatinib, alone and in combination with trastuzumab and taxanes, as adjuvant therapy for advanced breast cancer (adjuvant lapatinib and/or trastuzumab treatment optimisation). HLA-DRB1*07:01 carriage was associated with serum alanine aminotransferase (ALT) elevations in lapatinib-treated patients (odds ratio 6.5, P=3 × 10 -26 , n=4482) and the risk and severity of ALT elevation for lapatinib-treated patients was higher in homozygous than heterozygous HLA-DRB1*07:01 genotype carriers. A higher ALT case incidence plus weaker HLA association observed during concurrent administration of lapatinib and taxane suggested a subset of liver injury in this combination group that was HLA-DRB1*07:01 independent. Furthermore, the incidence of ALT elevation demonstrated an expected correlation with geographic HLA-DRB1*07:01 carriage frequency. Robust ALT elevation risk estimates for HLA-DRB1*07:01 may support causality discrimination and safety risk management during the use of lapatinib combination therapy for the treatment of metastatic breast cancer.

Intermittent administration of MEK inhibitor GDC-0973 plus PI3K inhibitor GDC-0941 triggers robust apoptosis and tumor growth inhibition.

PubMed

Hoeflich, Klaus P; Merchant, Mark; Orr, Christine; Chan, Jocelyn; Den Otter, Doug; Berry, Leanne; Kasman, Ian; Koeppen, Hartmut; Rice, Ken; Yang, Nai-Ying; Engst, Stefan; Johnston, Stuart; Friedman, Lori S; Belvin, Marcia

2012-01-01

Combinations of MAP/ERK kinase (MEK) and phosphoinositide 3-kinase (PI3K) inhibitors have shown promise in preclinical cancer models, leading to the initiation of clinical trials cotargeting these two key cancer signaling pathways. GDC-0973, a novel selective MEK inhibitor, and GDC-0941, a class I PI3K inhibitor, are in early stage clinical trials as both single agents and in combination. The discovery of these selective inhibitors has allowed investigation into the precise effects of combining inhibitors of two major signaling branches downstream of RAS. Here, we investigated multiple biomarkers in the mitogen-activated protein kinase (MAPK) and PI3K pathway to search for points of convergence that explain the increased apoptosis seen in combination. Using washout studies in vitro and alternate dosing schedules in mice, we showed that intermittent inhibition of the PI3K and MAPK pathway is sufficient for efficacy in BRAF and KRAS mutant cancer cells. The combination of GDC-0973 with the PI3K inhibitor GDC-0941 resulted in combination efficacy in vitro and in vivo via induction of biomarkers associated with apoptosis, including Bcl-2 family proapoptotic regulators. Therefore, these data suggest that continuous exposure of MEK and PI3K inhibitors in combination is not required for efficacy in preclinical cancer models and that sustained effects on downstream apoptosis biomarkers can be observed in response to intermittent dosing. ©2011 AACR.

Multi-surface topography targeted plateau honing for the processing of cylinder liner surfaces of automotive engines

NASA Astrophysics Data System (ADS)

Lawrence, K. Deepak; Ramamoorthy, B.

2016-03-01

Cylinder bores of automotive engines are 'engineered' surfaces that are processed using multi-stage honing process to generate multiple layers of micro geometry for meeting the different functional requirements of the piston assembly system. The final processed surfaces should comply with several surface topographic specifications that are relevant for the good tribological performance of the engine. Selection of the process parameters in three stages of honing to obtain multiple surface topographic characteristics simultaneously within the specification tolerance is an important module of the process planning and is often posed as a challenging task for the process engineers. This paper presents a strategy by combining the robust process design and gray-relational analysis to evolve the operating levels of honing process parameters in rough, finish and plateau honing stages targeting to meet multiple surface topographic specifications on the final running surface of the cylinder bores. Honing experiments were conducted in three stages namely rough, finish and plateau honing on cast iron cylinder liners by varying four honing process parameters such as rotational speed, oscillatory speed, pressure and honing time. Abbott-Firestone curve based functional parameters (Rk, Rpk, Rvk, Mr1 and Mr2) coupled with mean roughness depth (Rz, DIN/ISO) and honing angle were measured and identified as the surface quality performance targets to be achieved. The experimental results have shown that the proposed approach is effective to generate cylinder liner surface that would simultaneously meet the explicit surface topographic specifications currently practiced by the industry.

A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

PubMed

Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

2014-03-01

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

Development of habitat suitability indices for the Candy Darter, with cross-scale validation across representative populations

USGS Publications Warehouse

Dunn, Corey G.; Angermeier, Paul

2016-01-01

Understanding relationships between habitat associations for individuals and habitat factors that limit populations is a primary challenge for managers of stream fishes. Although habitat use by individuals can provide insight into the adaptive significance of selected microhabitats, not all habitat parameters will be significant at the population level, particularly when distributional patterns partially result from habitat degradation. We used underwater observation to quantify microhabitat selection by an imperiled stream fish, the Candy Darter Etheostoma osburni, in two streams with robust populations. We developed multiple-variable and multiple-life-stage habitat suitability indices (HSIs) from microhabitat selection patterns and used them to assess the suitability of available habitat in streams where Candy Darter populations were extirpated, localized, or robust. Next, we used a comparative framework to examine relationships among (1) habitat availability across streams, (2) projected habitat suitability of each stream, and (3) a rank for the likely long-term viability (robustness) of the population inhabiting each stream. Habitat selection was characterized by ontogenetic shifts from the low-velocity, slightly embedded areas used by age-0 Candy Darters to the swift, shallow areas with little fine sediment and complex substrate, which were used by adults. Overall, HSIs were strongly correlated with population rank. However, we observed weak or inverse relationships between predicted individual habitat suitability and population robustness for multiple life stages and variables. The results demonstrated that microhabitat selection by individuals does not always reflect population robustness, particularly when based on a single life stage or season, which highlights the risk of generalizing habitat selection that is observed during nonstressful periods or for noncritical resources. These findings suggest that stream fish managers may need to be cautious when implementing conservation measures based solely on observations of habitat selection by individuals and that detailed study at the individual and population levels may be necessary to identify habitat that limits populations.

Recent advances in malaria drug discovery

PubMed Central

Biamonte, Marco A.; Wanner, Jutta; Le Roch, Karine G.

2013-01-01

This digest covers some of the most relevant progress in malaria drug disco very published betwe en 2010 and 2012. There is an urgent need to develop new antimalarial drugs. Such drugs can target the blood stage of the disease to alleviate the symptoms, the liver stage to prevent relapses, and the transmission stage to protect other humans. The pipeline for the blood stage is becoming robust, but this should not be a source of complacency, as the current therapies set a high standard. Drug disco very efforts directed towards the liver and transmission stages are in their infancy but are receiving increasing attention as targeting these stages could be instrumental in eradicating malaria. PMID:23587422

Efficient Robust Regression via Two-Stage Generalized Empirical Likelihood

PubMed Central

Bondell, Howard D.; Stefanski, Leonard A.

2013-01-01

Large- and finite-sample efficiency and resistance to outliers are the key goals of robust statistics. Although often not simultaneously attainable, we develop and study a linear regression estimator that comes close. Efficiency obtains from the estimator’s close connection to generalized empirical likelihood, and its favorable robustness properties are obtained by constraining the associated sum of (weighted) squared residuals. We prove maximum attainable finite-sample replacement breakdown point, and full asymptotic efficiency for normal errors. Simulation evidence shows that compared to existing robust regression estimators, the new estimator has relatively high efficiency for small sample sizes, and comparable outlier resistance. The estimator is further illustrated and compared to existing methods via application to a real data set with purported outliers. PMID:23976805

Matlab as a robust control design tool

NASA Technical Reports Server (NTRS)

Gregory, Irene M.

1994-01-01

This presentation introduces Matlab as a tool used in flight control research. The example used to illustrate some of the capabilities of this software is a robust controller designed for a single stage to orbit air breathing vehicles's ascent to orbit. The global requirements of the controller are to stabilize the vehicle and follow a trajectory in the presence of atmospheric disturbances and strong dynamic coupling between airframe and propulsion.

Performance analysis of visual tracking algorithms for motion-based user interfaces on mobile devices

NASA Astrophysics Data System (ADS)

Winkler, Stefan; Rangaswamy, Karthik; Tedjokusumo, Jefry; Zhou, ZhiYing

2008-02-01

Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping.

Study on Multi-stage Logistics System Design Problem with Inventory Considering Demand Change by Hybrid Genetic Algorithm

NASA Astrophysics Data System (ADS)

Inoue, Hisaki; Gen, Mitsuo

The logistics model used in this study is 3-stage model employed by an automobile company, which aims to solve traffic problems at a total minimum cost. Recently, research on the metaheuristics method has advanced as an approximate means for solving optimization problems like this model. These problems can be solved using various methods such as the genetic algorithm (GA), simulated annealing, and tabu search. GA is superior in robustness and adjustability toward a change in the structure of these problems. However, GA has a disadvantage in that it has a slightly inefficient search performance because it carries out a multi-point search. A hybrid GA that combines another method is attracting considerable attention since it can compensate for a fault to a partial solution that early convergence gives a bad influence on a result. In this study, we propose a novel hybrid random key-based GA(h-rkGA) that combines local search and parameter tuning of crossover rate and mutation rate; h-rkGA is an improved version of the random key-based GA (rk-GA). We attempted comparative experiments with spanning tree-based GA, priority based GA and random key-based GA. Further, we attempted comparative experiments with “h-GA by only local search” and “h-GA by only parameter tuning”. We reported the effectiveness of the proposed method on the basis of the results of these experiments.

Study of drain-extended NMOS under electrostatic discharge stress in 28 nm and 40 nm CMOS process

NASA Astrophysics Data System (ADS)

Wang, Weihuai; Jin, Hao; Dong, Shurong; Zhong, Lei; Han, Yan

2016-02-01

Researches on the electrostatic discharge (ESD) performance of drain-extended NMOS (DeNMOS) under the state-of-the-art 28 nm and 40 nm bulk CMOS process are performed in this paper. Three distinguishing phases of avalanche breakdown stage, depletion region push-out stage and parasitic NPN turn on stage of the gate-grounded DeNMOS (GG-DeNMOS) fabricated under 28 nm CMOS process measured with transmission line pulsing (TLP) test are analyzed through TCAD simulations and tape-out silicon verification detailedly. Damage mechanisms and failure spots of GG-DeNMOS under both CMOS processes are thermal breakdown of drain junction. Improvements based on the basic structure adjustments can increase the GG-DeNMOS robustness from original 2.87 mA/μm to the highest 5.41 mA/μm. Under 40 nm process, parameter adjustments based on the basic structure have no significant benefits on the robustness improvements. By inserting P+ segments in the N+ implantation of drain or an entire P+ strip between the N+ implantation of drain and polysilicon gate to form the typical DeMOS-SCR (silicon-controlled rectifier) structure, the ESD robustness can be enhanced from 1.83 mA/μm to 8.79 mA/μm and 29.78 mA/μm, respectively.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

PubMed Central

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis

2018-01-01

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505

Challenges of advanced hepatocellular carcinoma

PubMed Central

Colagrande, Stefano; Inghilesi, Andrea L; Aburas, Sami; Taliani, Gian G; Nardi, Cosimo; Marra, Fabio

2016-01-01

Hepatocellular carcinoma (HCC) is an aggressive malignancy, resulting as the third cause of death by cancer each year. The management of patients with HCC is complex, as both the tumour stage and any underlying liver disease must be considered conjointly. Although surveillance by imaging, clinical and biochemical parameters is routinely performed, a lot of patients suffering from cirrhosis have an advanced stage HCC at the first diagnosis. Advanced stage HCC includes heterogeneous groups of patients with different clinical condition and radiological features and sorafenib is the only approved treatment according to Barcelona Clinic Liver Cancer. Since the introduction of sorafenib in clinical practice, several phase III clinical trials have failed to demonstrate any superiority over sorafenib in the frontline setting. Loco-regional therapies have also been tested as first line treatment, but their role in advanced HCC is still matter of debate. No single agent or combination therapies have been shown to impact outcomes after sorafenib failure. Therefore this review will focus on the range of experimental therapeutics for patients with advanced HCC and highlights the successes and failures of these treatments as well as areas for future development. Specifics such as dose limiting toxicity and safety profile in patients with liver dysfunction related to the underlying chronic liver disease should be considered when developing therapies in HCC. Finally, robust validated and reproducible surrogate end-points as well as predictive biomarkers should be defined in future randomized trials. PMID:27678348

A two-stage approach for fully automatic segmentation of venous vascular structures in liver CT images

NASA Astrophysics Data System (ADS)

Kaftan, Jens N.; Tek, Hüseyin; Aach, Til

2009-02-01

The segmentation of the hepatic vascular tree in computed tomography (CT) images is important for many applications such as surgical planning of oncological resections and living liver donations. In surgical planning, vessel segmentation is often used as basis to support the surgeon in the decision about the location of the cut to be performed and the extent of the liver to be removed, respectively. We present a novel approach to hepatic vessel segmentation that can be divided into two stages. First, we detect and delineate the core vessel components efficiently with a high specificity. Second, smaller vessel branches are segmented by a robust vessel tracking technique based on a medialness filter response, which starts from the terminal points of the previously segmented vessels. Specifically, in the first phase major vessels are segmented using the globally optimal graphcuts algorithm in combination with foreground and background seed detection, while the computationally more demanding tracking approach needs to be applied only locally in areas of smaller vessels within the second stage. The method has been evaluated on contrast-enhanced liver CT scans from clinical routine showing promising results. In addition to the fully-automatic instance of this method, the vessel tracking technique can also be used to easily add missing branches/sub-trees to an already existing segmentation result by adding single seed-points.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.

PubMed

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid

2018-05-15

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.

Hydraulic design to optimize the treatment capacity of Multi-Stage Filtration units

NASA Astrophysics Data System (ADS)

Mushila, C. N.; Ochieng, G. M.; Otieno, F. A. O.; Shitote, S. M.; Sitters, C. W.

2016-04-01

Multi-Stage Filtration (MSF) can provide a robust treatment alternative for surface water sources of variable water quality in rural communities at low operation and maintenance costs. MSF is a combination of Slow Sand Filters (SSFs) and Pre-treatment systems. The general objective of this research was to optimize the treatment capacity of MSF. A pilot plant study was undertaken to meet this objective. The pilot plant was monitored for a continuous 98 days from commissioning till the end of the project. Three main stages of MSF namely: The Dynamic Gravel Filter (DGF), Horizontal-flow Roughing Filter (HRF) and SSF were identified, designed and built. The response of the respective MSF units in removal of selected parameters guiding drinking water quality such as microbiological (Faecal and Total coliform), Suspended Solids, Turbidity, PH, Temperature, Iron and Manganese was investigated. The benchmark was the Kenya Bureau (KEBS) and World Health Organization (WHO) Standards for drinking water quality. With respect to microbiological raw water quality improvement, MSF units achieved on average 98% Faecal and 96% Total coliform removal. Results obtained indicate that implementation of MSF in rural communities has the potential to increase access to portable water to the rural populace with a probable consequent decrease in waterborne diseases. With a reduced down time due to illness, more time would be spent in undertaking other economic activities.

Generation and customization of biosynthetic excitable tissues for electrophysiological studies and cell-based therapies.

PubMed

Nguyen, Hung X; Kirkton, Robert D; Bursac, Nenad

2018-05-01

We describe a two-stage protocol to generate electrically excitable and actively conducting cell networks with stable and customizable electrophysiological phenotypes. Using this method, we have engineered monoclonally derived excitable tissues as a robust and reproducible platform to investigate how specific ion channels and mutations affect action potential (AP) shape and conduction. In the first stage of the protocol, we combine computational modeling, site-directed mutagenesis, and electrophysiological techniques to derive optimal sets of mammalian and/or prokaryotic ion channels that produce specific AP shape and conduction characteristics. In the second stage of the protocol, selected ion channels are stably expressed in unexcitable human cells by means of viral or nonviral delivery, followed by flow cytometry or antibiotic selection to purify the desired phenotype. This protocol can be used with traditional heterologous expression systems or primary excitable cells, and application of this method to primary fibroblasts may enable an alternative approach to cardiac cell therapy. Compared with existing methods, this protocol generates a well-defined, relatively homogeneous electrophysiological phenotype of excitable cells that facilitates experimental and computational studies of AP conduction and can decrease arrhythmogenic risk upon cell transplantation. Although basic cell culture and molecular biology techniques are sufficient to generate excitable tissues using the described protocol, experience with patch-clamp techniques is required to characterize and optimize derived cell populations.

A Critical Assessment of Combined Ligand-based and Structure-based Approaches to hERG Channel Blocker Modeling

PubMed Central

Du-Cuny, Lei; Chen, Lu; Zhang, Shuxing

2014-01-01

Blockade of hERG channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining QSAR modeling, pharmacophore analysis, and molecular docking. Our consensus models demonstrated high predictive capacity and improved enrichment, and they could correctly classify 91.8% of 147 hERG blockers from 351 inactives. To further enhance our modeling effort, hERG homology models were constructed and molecular docking studies were conducted, resulting in high correlations (R2=0.81) between predicted and experimental binding affinities. We expect our unique models can be applied to efficient screening for hERG blockades, and our extensive understanding of the hERG-inhibitor interactions will facilitate the rational design of drugs devoid of hERG channel activity and hence with reduced cardiac toxicities. PMID:21902220

Tissue Gene Expression Analysis Using Arrayed Normalized cDNA Libraries

PubMed Central

Eickhoff, Holger; Schuchhardt, Johannes; Ivanov, Igor; Meier-Ewert, Sebastian; O'Brien, John; Malik, Arif; Tandon, Neeraj; Wolski, Eryk-Witold; Rohlfs, Elke; Nyarsik, Lajos; Reinhardt, Richard; Nietfeld, Wilfried; Lehrach, Hans

2000-01-01

We have used oligonucleotide-fingerprinting data on 60,000 cDNA clones from two different mouse embryonic stages to establish a normalized cDNA clone set. The normalized set of 5,376 clones represents different clusters and therefore, in almost all cases, different genes. The inserts of the cDNA clones were amplified by PCR and spotted on glass slides. The resulting arrays were hybridized with mRNA probes prepared from six different adult mouse tissues. Expression profiles were analyzed by hierarchical clustering techniques. We have chosen radioactive detection because it combines robustness with sensitivity and allows the comparison of multiple normalized experiments. Sensitive detection combined with highly effective clustering algorithms allowed the identification of tissue-specific expression profiles and the detection of genes specifically expressed in the tissues investigated. The obtained results are publicly available (http://www.rzpd.de) and can be used by other researchers as a digital expression reference. [The sequence data described in this paper have been submitted to the EMBL data library under accession nos. AL360374–AL36537.] PMID:10958641

FE calculations on a three stage metal forming process of Sandvik Nanoflex™

NASA Astrophysics Data System (ADS)

Voncken, R. M. J.; van der Sluis, O.; Post, J.; Huétink, J.

2004-06-01

Sandvik Nanoflex™ combines good corrosion resistance with high strength. This steel has good deformability in austenitic conditions. It belongs to the group of metastable austenites, which means that during deformation a strain-induced transformation into martensite takes place. After deformation, transformation continues as a result of internal stresses. Both transformations are stress-state and temperature dependent. A constitutive model for this steel has been formulated, based on the macroscopic material behaviour measured by inductive measurements. Both the stress-assisted and the strain-induced transformation into martensite have been incorporated in this model. Path-dependent work hardening has also been taken into account. This article describes how the model is implemented in an internal Philips FE code called Crystal, which is a dedicated robust and accurate finite element solver. The implementation is based on lookup tables in combination with feed-forward neural networks. The radial return method is used to determine the material state during and after plastic flow, however, it has been extended to cope with the stiff character of the partial differential equation that describes the transformation behaviour.

Guidance Concept for a Mars Ascent Vehicle First Stage

NASA Technical Reports Server (NTRS)

Queen, Eric M.

2000-01-01

This paper presents a guidance concept for use on the first stage of a Mars Ascent Vehicle (MAV). The guidance is based on a calculus of variations approach similar to that used for the final phase of the Apollo Earth return guidance. A three degree-of-freedom (3DOF) Monte Carlo simulation is used to evaluate performance and robustness of the algorithm.

Self-Organizing and Stochastic Behaviors During the Regeneration of Hair Stem Cells

PubMed Central

Plikus, Maksim V.; Baker, Ruth E.; Chen, Chih-Chiang; Fare, Clyde; de la Cruz, Damon; Andl, Thomas; Maini, Philip K.; Millar, Sarah E.; Widelitz, Randall; Chuong, Cheng-Ming

2012-01-01

Stem cells cycle through active and quiescent states. Large populations of stem cells in an organ may cycle randomly or in a coordinated manner. Although stem cell cycling within single hair follicles has been studied, less is known about regenerative behavior in a hair follicle population. By combining predictive mathematical modeling with in vivo studies in mice and rabbits, we show that a follicle progresses through cycling stages by continuous integration of inputs from intrinsic follicular and extrinsic environmental signals based on universal patterning principles. Signaling from the WNT/bone morphogenetic protein activator/inhibitor pair is coopted to mediate interactions among follicles in the population. This regenerative strategy is robust and versatile because relative activator/inhibitor strengths can be modulated easily, adapting the organism to different physiological and evolutionary needs. PMID:21527712

The birth of quantum networks: merging remote entanglement with local multi-qubit control

NASA Astrophysics Data System (ADS)

Hanson, Ronald

The realization of a highly connected network of qubit registers is a central challenge for quantum information processing and long-distance quantum communication. Diamond spins associated with NV centers are promising building blocks for such a network: they combine a coherent spin-photon interface that has already enabled creation of spin-spin entanglement over 1km with a local register of robust and well-controlled nuclear spin qubits for information processing and error correction. We are now entering a new research stage in which we can exploit these features simultaneously and build multi-qubit networks. I will present our latest results towards the first of such experiments: entanglement distillation between remote quantum network nodes. Finally, I will discuss the challenges and opportunities ahead on the road to large-scale networks of qubit registers for quantum computation and communication.

Knowledge-based segmentation and feature analysis of hand and wrist radiographs

NASA Astrophysics Data System (ADS)

Efford, Nicholas D.

1993-07-01

The segmentation of hand and wrist radiographs for applications such as skeletal maturity assessment is best achieved by model-driven approaches incorporating anatomical knowledge. The reasons for this are discussed, and a particular frame-based or 'blackboard' strategy for the simultaneous segmentation of the hand and estimation of bone age via the TW2 method is described. The new approach is structured for optimum robustness and computational efficiency: features of interest are detected and analyzes in order of their size and prominence in the image, the largest and most distinctive being dealt with first, and the evidence generated by feature analysis is used to update a model of hand anatomy and hence guide later stages of the segmentation. Closed bone boundaries are formed by a hybrid technique combining knowledge-based, one-dimensional edge detection with model-assisted heuristic tree searching.

A robust multi-objective global supplier selection model under currency fluctuation and price discount

NASA Astrophysics Data System (ADS)

Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman

2017-06-01

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.

Optimisation robuste des aeronefs et des groupes turboreacteurs

NASA Astrophysics Data System (ADS)

Couturier, Philippe

Future aircraft and powerplant designs will need to meet and perhaps anticipate increasingly demanding operational constraints. This progressive evolution in design requirements is already at work and arises from the combined impacts of increasingly stringent environmental norms with regards to noise and atmospheric emissions, a depletion of fossil fuel reserves which is expected to drive fuel costs upwards, as well as a steady increase in air traffic. In order to adapt to these market shifts, aircraft and powerplant companies will need to explore the potential range of benefits and risks associated with a wide spectrum of new designs and technologies. At the same time, it will be necessary to ensure that the resulting end products provide cost effective solutions when operated in the economic environment foreseen for the next generation of aircrafts. The objective of this study is to develop a methodology which enables the selection of optimal robust designs at the preliminary design stage as well as to quantify the compromise between a robust design and a potential gain in performance. The developed methodology is used in the design of a seventy passenger aircraft in order to determine the effects of uncertainty. The methodology seeks to optimize the design while attenuating its sensitivity to uncertainties. The goal is to reduce the likelihood of costly concept reformulations in the later stages of the product development process. A design platform was developed to enable the study at a conceptual level of aircraft and engine performance. It comprises four modules namely: the aircraft design and performance software Pacelab APD, a metamodel constructed with the software GasTurb to calculate engine performance, a module to predict the noise level, and a module to determine the operating costs. The last two modules were constructed using data from the literature. The effects related to two types of uncertainties present at the preliminary design stage were analyzed. These are uncertainties related to the market forecast for when the next generation of aircrafts will be in service as well as uncertainties of the level of fidelity of the models used. Based on predictions for future oil costs, the research found that an aircraft built for a similar cruising speed as today's jet aircrafts will minimize the mean of the predicted operating cost by having a configuration that minimizes fuel consumption. Conversely, it has been determined that fuel cost does not affect the design optimized to minimize the mean of the predicted operating costs when the cruise Mach number is variable. Furthermore, the use of Pareto fronts in order to quantify the compromise between a robust design and a potential gain in performance showed that the design variables have little influence on the sensitivity of the operating cost subject to model uncertainties. It has also been determined that neglecting uncertainties during the design process can lead to the selection of a configuration with a high risk of not satisfying the constraints.

Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme

PubMed Central

Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei

2015-01-01

Molecular biologists have long recognized carcinogenesis as an evolutionary process that involves natural selection. Cancer is driven by the somatic evolution of cell lineages. In this study, the evolution of somatic cancer cell lineages during carcinogenesis was modeled as an equilibrium point (ie, phenotype of attractor) shifting, the process of a nonlinear stochastic evolutionary biological network. This process is subject to intrinsic random fluctuations because of somatic genetic and epigenetic variations, as well as extrinsic disturbances because of carcinogens and stressors. In order to maintain the normal function (ie, phenotype) of an evolutionary biological network subjected to random intrinsic fluctuations and extrinsic disturbances, a network robustness scheme that incorporates natural selection needs to be developed. This can be accomplished by selecting certain genetic and epigenetic variations to modify the network structure to attenuate intrinsic fluctuations efficiently and to resist extrinsic disturbances in order to maintain the phenotype of the evolutionary biological network at an equilibrium point (attractor). However, during carcinogenesis, the remaining (or neutral) genetic and epigenetic variations accumulate, and the extrinsic disturbances become too large to maintain the normal phenotype at the desired equilibrium point for the nonlinear evolutionary biological network. Thus, the network is shifted to a cancer phenotype at a new equilibrium point that begins a new evolutionary process. In this study, the natural selection scheme of an evolutionary biological network of carcinogenesis was derived from a robust negative feedback scheme based on the nonlinear stochastic Nash game strategy. The evolvability and phenotypic robustness criteria of the evolutionary cancer network were also estimated by solving a Hamilton–Jacobi inequality – constrained optimization problem. The simulation revealed that the phenotypic shift of the lung cancer-associated cell network takes 54.5 years from a normal state to stage I cancer, 1.5 years from stage I to stage II cancer, and 2.5 years from stage II to stage III cancer, with a reasonable match for the statistical result of the average age of lung cancer. These results suggest that a robust negative feedback scheme, based on a stochastic evolutionary game strategy, plays a critical role in an evolutionary biological network of carcinogenesis under a natural selection scheme. PMID:26244004

Performance analysis of robust road sign identification

NASA Astrophysics Data System (ADS)

Ali, Nursabillilah M.; Mustafah, Y. M.; Rashid, N. K. A. M.

2013-12-01

This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able to detect the three standard types of colored images namely Red, Yellow and Blue. The hypothesis of the study is that road sign images can be used to detect and identify signs that are involved with the existence of occlusions and rotational changes. PCA is known as feature extraction technique that reduces dimensional size. The sign image can be easily recognized and identified by the PCA method as is has been used in many application areas. Based on the experimental result, it shows that the HSV is robust in road sign detection with minimum of 88% and 77% successful rate for non-partial and partial occlusions images. For successful recognition rates using PCA can be achieved in the range of 94-98%. The occurrences of all classes are recognized successfully is between 5% and 10% level of occlusions.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo.

PubMed

Inglesfield, Sarah; Jasiulewicz, Aleksandra; Hopwood, Matthew; Tyrrell, James; Youlden, George; Mazon-Moya, Maria; Millington, Owain R; Mostowy, Serge; Jabbari, Sara; Voelz, Kerstin

2018-03-27

Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivo In silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients. IMPORTANCE Mucormycosis is a dramatic fungal infection frequently leading to the death of patients. We know little about the immune response to the fungus causing this infection, although evidence points toward defects in early immune events after infection. Here, we dissect this early immune response to infectious fungal spores. We show that specialized white blood cells (phagocytes) rapidly respond to these spores and accumulate around the fungus. However, we demonstrate that the mechanisms that enable phagocytes to kill the fungus fail, allowing for survival of spores. Instead a cluster of phagocytes resembling an early granuloma is formed around spores to control the latent infection. This study is the first detailed analysis of early granuloma formation during a fungal infection highlighting a latent stage that needs to be considered for clinical management of patients. Copyright © 2018 Inglesfield et al.

Possibility of spoof attack against robustness of multibiometric authentication systems

NASA Astrophysics Data System (ADS)

Hariri, Mahdi; Shokouhi, Shahriar Baradaran

2011-07-01

Multibiometric systems have been recently developed in order to overcome some weaknesses of single biometric authentication systems, but security of these systems against spoofing has not received enough attention. In this paper, we propose a novel practical method for simulation of possibilities of spoof attacks against a biometric authentication system. Using this method, we model matching scores from standard to completely spoofed genuine samples. Sum, product, and Bayes fusion rules are applied for score level combination. The security of multimodal authentication systems are examined and compared with the single systems against various spoof possibilities. However, vulnerability of fused systems is considerably increased against spoofing, but their robustness is generally higher than single matcher systems. In this paper we show that robustness of a combined system is not always higher than a single system against spoof attack. We propose empirical methods for upgrading the security of multibiometric systems, which contain how to organize and select biometric traits and matchers against various possibilities of spoof attack. These methods provide considerable robustness and present an appropriate reason for using combined systems against spoof attacks.

Image Alignment for Multiple Camera High Dynamic Range Microscopy.

PubMed

Eastwood, Brian S; Childs, Elisabeth C

2012-01-09

This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera.

Image Alignment for Multiple Camera High Dynamic Range Microscopy

PubMed Central

Eastwood, Brian S.; Childs, Elisabeth C.

2012-01-01

This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera. PMID:22545028

Evaluation of Oil-Palm Fungal Disease Infestation with Canopy Hyperspectral Reflectance Data

PubMed Central

Lelong, Camille C. D.; Roger, Jean-Michel; Brégand, Simon; Dubertret, Fabrice; Lanore, Mathieu; Sitorus, Nurul A.; Raharjo, Doni A.; Caliman, Jean-Pierre

2010-01-01

Fungal disease detection in perennial crops is a major issue in estate management and production. However, nowadays such diagnostics are long and difficult when only made from visual symptom observation, and very expensive and damaging when based on root or stem tissue chemical analysis. As an alternative, we propose in this study to evaluate the potential of hyperspectral reflectance data to help detecting the disease efficiently without destruction of tissues. This study focuses on the calibration of a statistical model of discrimination between several stages of Ganoderma attack on oil palm trees, based on field hyperspectral measurements at tree scale. Field protocol and measurements are first described. Then, combinations of pre-processing, partial least square regression and linear discriminant analysis are tested on about hundred samples to prove the efficiency of canopy reflectance in providing information about the plant sanitary status. A robust algorithm is thus derived, allowing classifying oil-palm in a 4-level typology, based on disease severity from healthy to critically sick stages, with a global performance close to 94%. Moreover, this model discriminates sick from healthy trees with a confidence level of almost 98%. Applications and further improvements of this experiment are finally discussed. PMID:22315565

Flower Development

PubMed Central

Alvarez-Buylla, Elena R.; Benítez, Mariana; Corvera-Poiré, Adriana; Chaos Cador, Álvaro; de Folter, Stefan; Gamboa de Buen, Alicia; Garay-Arroyo, Adriana; García-Ponce, Berenice; Jaimes-Miranda, Fabiola; Pérez-Ruiz, Rigoberto V.; Piñeyro-Nelson, Alma; Sánchez-Corrales, Yara E.

2010-01-01

Flowers are the most complex structures of plants. Studies of Arabidopsis thaliana, which has typical eudicot flowers, have been fundamental in advancing the structural and molecular understanding of flower development. The main processes and stages of Arabidopsis flower development are summarized to provide a framework in which to interpret the detailed molecular genetic studies of genes assigned functions during flower development and is extended to recent genomics studies uncovering the key regulatory modules involved. Computational models have been used to study the concerted action and dynamics of the gene regulatory module that underlies patterning of the Arabidopsis inflorescence meristem and specification of the primordial cell types during early stages of flower development. This includes the gene combinations that specify sepal, petal, stamen and carpel identity, and genes that interact with them. As a dynamic gene regulatory network this module has been shown to converge to stable multigenic profiles that depend upon the overall network topology and are thus robust, which can explain the canalization of flower organ determination and the overall conservation of the basic flower plan among eudicots. Comparative and evolutionary approaches derived from Arabidopsis studies pave the way to studying the molecular basis of diverse floral morphologies. PMID:22303253

Deregulation of MiR-34b/Sox2 Predicts Prostate Cancer Progression

PubMed Central

Russo, Maria Veronica; Gazzano, Giacomo; Giangiobbe, Sara; Montanari, Emanuele; Del Nero, Alberto; Rocco, Bernardo; Albo, Giancarlo; Languino, Lucia R.; Altieri, Dario C.; Vaira, Valentina; Bosari, Silvano

2015-01-01

Most men diagnosed with prostate cancer will have an indolent and curable disease, whereas approximately 15% of these patients will rapidly progress to a castrate-resistant and metastatic stage with high morbidity and mortality. Therefore, the identification of molecular signature(s) that detect men at risk of progressing disease remains a pressing and still unmet need for these patients. Here, we used an integrated discovery platform combining prostate cancer cell lines, a Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP) model and clinically-annotated human tissue samples to identify loss of expression of microRNA-34b as consistently associated with prostate cancer relapse. Mechanistically, this was associated with epigenetics silencing of the MIR34B/C locus and increased DNA copy number loss, selectively in androgen-dependent prostate cancer. In turn, loss of miR-34b resulted in downstream deregulation and overexpression of the “stemness” marker, Sox2. These findings identify loss of miR-34b as a robust biomarker for prostate cancer progression in androgen-sensitive tumors, and anticipate a potential role of progenitor/stem cell signaling in this stage of disease. PMID:26107383

Identification and Construction of Combinatory Cancer Hallmark-Based Gene Signature Sets to Predict Recurrence and Chemotherapy Benefit in Stage II Colorectal Cancer.

PubMed

Gao, Shanwu; Tibiche, Chabane; Zou, Jinfeng; Zaman, Naif; Trifiro, Mark; O'Connor-McCourt, Maureen; Wang, Edwin

2016-01-01

Decisions regarding adjuvant therapy in patients with stage II colorectal cancer (CRC) have been among the most challenging and controversial in oncology over the past 20 years. To develop robust combinatory cancer hallmark-based gene signature sets (CSS sets) that more accurately predict prognosis and identify a subset of patients with stage II CRC who could gain survival benefits from adjuvant chemotherapy. Thirteen retrospective studies of patients with stage II CRC who had clinical follow-up and adjuvant chemotherapy were analyzed. Respective totals of 162 and 843 patients from 2 and 11 independent cohorts were used as the discovery and validation cohorts, respectively. A total of 1005 patients with stage II CRC were included in the 13 cohorts. Among them, 84 of 416 patients in 3 independent cohorts received fluorouracil-based adjuvant chemotherapy. Identification of CSS sets to predict relapse-free survival and identify a subset of patients with stage II CRC who could gain substantial survival benefits from fluorouracil-based adjuvant chemotherapy. Eight cancer hallmark-based gene signatures (30 genes each) were identified and used to construct CSS sets for determining prognosis. The CSS sets were validated in 11 independent cohorts of 767 patients with stage II CRC who did not receive adjuvant chemotherapy. The CSS sets accurately stratified patients into low-, intermediate-, and high-risk groups. Five-year relapse-free survival rates were 94%, 78%, and 45%, respectively, representing 60%, 28%, and 12% of patients with stage II disease. The 416 patients with CSS set-defined high-risk stage II CRC who received fluorouracil-based adjuvant chemotherapy showed a substantial gain in survival benefits from the treatment (ie, recurrence reduced by 30%-40% in 5 years). The CSS sets substantially outperformed other prognostic predictors of stage 2 CRC. They are more accurate and robust for prognostic predictions and facilitate the identification of patients with stage II disease who could gain survival benefit from fluorouracil-based adjuvant chemotherapy.

Comparative psychology and the grand challenge of drug discovery in psychiatry and neurodegeneration.

PubMed

Brunner, Dani; Balcı, Fuat; Ludvig, Elliot A

2012-02-01

Drug discovery for brain disorders is undergoing a period of upheaval. Faced with an empty drug pipeline and numerous failures of potential new drugs in clinical trials, many large pharmaceutical companies have been shrinking or even closing down their research divisions that focus on central nervous system (CNS) disorders. In this paper, we argue that many of the difficulties facing CNS drug discovery stem from a lack of robustness in pre-clinical (i.e., non-human animal) testing. There are two main sources for this lack of robustness. First, there is the lack of replicability of many results from the pre-clinical stage, which we argue is driven by a combination of publication bias and inappropriate selection of statistical and experimental designs. Second, there is the frequent failure to translate results in non-human animals to parallel results in humans in the clinic. This limitation can only be overcome by developing new behavioral tests for non-human animals that have predictive, construct, and etiological validity. Here, we present these translational difficulties as a "grand challenge" to researchers from comparative cognition, who are well positioned to provide new methods for testing behavior and cognition in non-human animals. These new experimental protocols will need to be both statistically robust and target behavioral and cognitive processes that allow for better connection with human CNS disorders. Our hope is that this downturn in industrial research may represent an opportunity to develop new protocols that will re-kindle the search for more effective and safer drugs for CNS disorders. Copyright © 2011 Elsevier B.V. All rights reserved.

Dauer larva quiescence alters the circuitry of microRNA pathways regulating cell fate progression in C. elegans.

PubMed

Karp, Xantha; Ambros, Victor

2012-06-01

In C. elegans larvae, the execution of stage-specific developmental events is controlled by heterochronic genes, which include those encoding a set of transcription factors and the microRNAs that regulate the timing of their expression. Under adverse environmental conditions, developing larvae enter a stress-resistant, quiescent stage called 'dauer'. Dauer larvae are characterized by the arrest of all progenitor cell lineages at a stage equivalent to the end of the second larval stage (L2). If dauer larvae encounter conditions favorable for resumption of reproductive growth, they recover and complete development normally, indicating that post-dauer larvae possess mechanisms to accommodate an indefinite period of interrupted development. For cells to progress to L3 cell fate, the transcription factor Hunchback-like-1 (HBL-1) must be downregulated. Here, we describe a quiescence-induced shift in the repertoire of microRNAs that regulate HBL-1. During continuous development, HBL-1 downregulation (and consequent cell fate progression) relies chiefly on three let-7 family microRNAs, whereas after quiescence, HBL-1 is downregulated primarily by the lin-4 microRNA in combination with an altered set of let-7 family microRNAs. We propose that this shift in microRNA regulation of HBL-1 expression involves an enhancement of the activity of lin-4 and let-7 microRNAs by miRISC modulatory proteins, including NHL-2 and LIN-46. These results illustrate how the employment of alternative genetic regulatory pathways can provide for the robust progression of progenitor cell fates in the face of temporary developmental quiescence.

Optimization of the HyPer sensor for robust real-time detection of hydrogen peroxide in the rice blast fungus.

PubMed

Huang, Kun; Caplan, Jeff; Sweigard, James A; Czymmek, Kirk J; Donofrio, Nicole M

2017-02-01

Reactive oxygen species (ROS) production and breakdown have been studied in detail in plant-pathogenic fungi, including the rice blast fungus, Magnaporthe oryzae; however, the examination of the dynamic process of ROS production in real time has proven to be challenging. We resynthesized an existing ROS sensor, called HyPer, to exhibit optimized codon bias for fungi, specifically Neurospora crassa, and used a combination of microscopy and plate reader assays to determine whether this construct could detect changes in fungal ROS during the plant infection process. Using confocal microscopy, we were able to visualize fluctuating ROS levels during the formation of an appressorium on an artificial hydrophobic surface, as well as during infection on host leaves. Using the plate reader, we were able to ascertain measurements of hydrogen peroxide (H 2 O 2 ) levels in conidia as detected by the MoHyPer sensor. Overall, by the optimization of codon usage for N. crassa and related fungal genomes, the MoHyPer sensor can be used as a robust, dynamic and powerful tool to both monitor and quantify H 2 O 2 dynamics in real time during important stages of the plant infection process. © 2016 BSPP AND JOHN WILEY & SONS LTD.

Tracking and recognition face in videos with incremental local sparse representation model

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Robust moving mesh algorithms for hybrid stretched meshes: Application to moving boundaries problems

NASA Astrophysics Data System (ADS)

Landry, Jonathan; Soulaïmani, Azzeddine; Luke, Edward; Ben Haj Ali, Amine

2016-12-01

A robust Mesh-Mover Algorithm (MMA) approach is designed to adapt meshes of moving boundaries problems. A new methodology is developed from the best combination of well-known algorithms in order to preserve the quality of initial meshes. In most situations, MMAs distribute mesh deformation while preserving a good mesh quality. However, invalid meshes are generated when the motion is complex and/or involves multiple bodies. After studying a few MMA limitations, we propose the following approach: use the Inverse Distance Weighting (IDW) function to produce the displacement field, then apply the Geometric Element Transformation Method (GETMe) smoothing algorithms to improve the resulting mesh quality, and use an untangler to revert negative elements. The proposed approach has been proven efficient to adapt meshes for various realistic aerodynamic motions: a symmetric wing that has suffered large tip bending and twisting and the high-lift components of a swept wing that has moved to different flight stages. Finally, the fluid flow problem has been solved on meshes that have moved and they have produced results close to experimental ones. However, for situations where moving boundaries are too close to each other, more improvements need to be made or other approaches should be taken, such as an overset grid method.

A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

PubMed Central

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-01-01

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel. PMID:25264951

A soft sensor for bioprocess control based on sequential filtering of metabolic heat signals.

PubMed

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-09-26

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

Robust Combining of Disparate Classifiers Through Order Statistics

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Robust Fault Detection Using Robust Z1 Estimation and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Curry, Tramone; Collins, Emmanuel G., Jr.; Selekwa, Majura; Guo, Ten-Huei (Technical Monitor)

2001-01-01

This research considers the application of robust Z(sub 1), estimation in conjunction with fuzzy logic to robust fault detection for an aircraft fight control system. It begins with the development of robust Z(sub 1) estimators based on multiplier theory and then develops a fixed threshold approach to fault detection (FD). It then considers the use of fuzzy logic for robust residual evaluation and FD. Due to modeling errors and unmeasurable disturbances, it is difficult to distinguish between the effects of an actual fault and those caused by uncertainty and disturbance. Hence, it is the aim of a robust FD system to be sensitive to faults while remaining insensitive to uncertainty and disturbances. While fixed thresholds only allow a decision on whether a fault has or has not occurred, it is more valuable to have the residual evaluation lead to a conclusion related to the degree of, or probability of, a fault. Fuzzy logic is a viable means of determining the degree of a fault and allows the introduction of human observations that may not be incorporated in the rigorous threshold theory. Hence, fuzzy logic can provide a more reliable and informative fault detection process. Using an aircraft flight control system, the results of FD using robust Z(sub 1) estimation with a fixed threshold are demonstrated. FD that combines robust Z(sub 1) estimation and fuzzy logic is also demonstrated. It is seen that combining the robust estimator with fuzzy logic proves to be advantageous in increasing the sensitivity to smaller faults while remaining insensitive to uncertainty and disturbances.

Fast detection of the main anatomical structures in digital retinal images based on intra- and inter-structure relational knowledge.

PubMed

Molina-Casado, José M; Carmona, Enrique J; García-Feijoó, Julián

2017-10-01

The anatomical structure detection in retinal images is an open problem. However, most of the works in the related literature are oriented to the detection of each structure individually or assume the previous detection of a structure which is used as a reference. The objective of this paper is to obtain simultaneous detection of the main retinal structures (optic disc, macula, network of vessels and vascular bundle) in a fast and robust way. We propose a new methodology oriented to accomplish the mentioned objective. It consists of two stages. In an initial stage, a set of operators is applied to the retinal image. Each operator uses intra-structure relational knowledge in order to produce a set of candidate blobs that belongs to the desired structure. In a second stage, a set of tuples is created, each of which contains a different combination of the candidate blobs. Next, filtering operators, using inter-structure relational knowledge, are used in order to find the winner tuple. A method using template matching and mathematical morphology is implemented following the proposed methodology. A success is achieved if the distance between the automatically detected blob center and the actual structure center is less than or equal to one optic disc radius. The success rates obtained in the different public databases analyzed were: MESSIDOR (99.33%, 98.58%, 97.92%), DIARETDB1 (96.63%, 100%, 97.75%), DRIONS (100%, n/a, 100%) and ONHSD (100%, 98.85%, 97.70%) for optic disc (OD), macula (M) and vascular bundle (VB), respectively. Finally, the overall success rate obtained in this study for each structure was: 99.26% (OD), 98.69% (M) and 98.95% (VB). The average time of processing per image was 4.16 ± 0.72 s. The main advantage of the use of inter-structure relational knowledge was the reduction of the number of false positives in the detection process. The implemented method is able to simultaneously detect four structures. It is fast, robust and its detection results are competitive in relation to other methods of the recent literature. Copyright © 2017 Elsevier B.V. All rights reserved.

On the robustness of Herlihy's hierarchy

NASA Technical Reports Server (NTRS)

Jayanti, Prasad

1993-01-01

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

Intravoxel water diffusion heterogeneity MR imaging of nasopharyngeal carcinoma using stretched exponential diffusion model.

PubMed

Lai, Vincent; Lee, Victor Ho Fun; Lam, Ka On; Sze, Henry Chun Kin; Chan, Queenie; Khong, Pek Lan

2015-06-01

To determine the utility of stretched exponential diffusion model in characterisation of the water diffusion heterogeneity in different tumour stages of nasopharyngeal carcinoma (NPC). Fifty patients with newly diagnosed NPC were prospectively recruited. Diffusion-weighted MR imaging was performed using five b values (0-2,500 s/mm(2)). Respective stretched exponential parameters (DDC, distributed diffusion coefficient; and alpha (α), water heterogeneity) were calculated. Patients were stratified into low and high tumour stage groups based on the American Joint Committee on Cancer (AJCC) staging for determination of the predictive powers of DDC and α using t test and ROC curve analyses. The mean ± standard deviation values were DDC = 0.692 ± 0.199 (×10(-3) mm(2)/s) for low stage group vs 0.794 ± 0.253 (×10(-3) mm(2)/s) for high stage group; α = 0.792 ± 0.145 for low stage group vs 0.698 ± 0.155 for high stage group. α was significantly lower in the high stage group while DDC was negatively correlated. DDC and α were both reliable independent predictors (p < 0.001), with α being more powerful. Optimal cut-off values were (sensitivity, specificity, positive likelihood ratio, negative likelihood ratio) DDC = 0.692 × 10(-3) mm(2)/s (94.4 %, 64.3 %, 2.64, 0.09), α = 0.720 (72.2 %, 100 %, -, 0.28). The heterogeneity index α is robust and can potentially help in staging and grading prediction in NPC. • Stretched exponential diffusion models can help in tissue characterisation in nasopharyngeal carcinoma • α and distributed diffusion coefficient (DDC) are negatively correlated • α is a robust heterogeneity index marker • α can potentially help in staging and grading prediction.

Robust, nonlinear, high angle-of-attack control design for a supermaneuverable vehicle

NASA Technical Reports Server (NTRS)

Adams, Richard J.

1993-01-01

High angle-of-attack flight control laws are developed for a supermaneuverable fighter aircraft. The methods of dynamic inversion and structured singular value synthesis are combined into an approach which addresses both the nonlinearity and robustness problems of flight at extreme operating conditions. The primary purpose of the dynamic inversion control elements is to linearize the vehicle response across the flight envelope. Structured singular value synthesis is used to design a dynamic controller which provides robust tracking to pilot commands. The resulting control system achieves desired flying qualities and guarantees a large margin of robustness to uncertainties for high angle-of-attack flight conditions. The results of linear simulation and structured singular value stability analysis are presented to demonstrate satisfaction of the design criteria. High fidelity nonlinear simulation results show that the combined dynamics inversion/structured singular value synthesis control law achieves a high level of performance in a realistic environment.

Subject independent facial expression recognition with robust face detection using a convolutional neural network.

PubMed

Matsugu, Masakazu; Mori, Katsuhiko; Mitari, Yusuke; Kaneda, Yuji

2003-01-01

Reliable detection of ordinary facial expressions (e.g. smile) despite the variability among individuals as well as face appearance is an important step toward the realization of perceptual user interface with autonomous perception of persons. We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network. In this study, we address the problem of subject independence as well as translation, rotation, and scale invariance in the recognition of facial expression. The result shows reliable detection of smiles with recognition rate of 97.6% for 5600 still images of more than 10 subjects. The proposed algorithm demonstrated the ability to discriminate smiling from talking based on the saliency score obtained from voting visual cues. To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance.

Processing Robustness for A Phenylethynyl Terminated Polyimide Composite

NASA Technical Reports Server (NTRS)

Hou, Tan-Hung

2004-01-01

The processability of a phenylethynyl terminated imide resin matrix (designated as PETI-5) composite is investigated. Unidirectional prepregs are made by coating an N-methylpyrrolidone solution of the amide acid oligomer (designated as PETAA-5/NMP) onto unsized IM7 fibers. Two batches of prepregs are used: one is made by NASA in-house, and the other is from an industrial source. The composite processing robustness is investigated with respect to the prepreg shelf life, the effect of B-staging conditions, and the optimal processing window. Prepreg rheology and open hole compression (OHC) strengths are found not to be affected by prolonged (i.e., up to 60 days) ambient storage. Rheological measurements indicate that the PETAA-5/NMP processability is only slightly affected over a wide range of B-stage temperatures from 250 deg C to 300 deg C. The OHC strength values are statistically indistinguishable among laminates consolidated using various B-staging conditions. An optimal processing window is established by means of the response surface methodology. IM7/PETAA-5/NMP prepreg is more sensitive to consolidation temperature than to pressure. A good consolidation is achievable at 371 deg C (700 deg F)/100 Psi, which yields an RT OHC strength of 62 Ksi. However, processability declines dramatically at temperatures below 350 deg C (662 deg F), as evidenced by the OHC strength values. The processability of the IM7/LARC(TM) PETI-5 prepreg was found to be robust.

Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons

NASA Astrophysics Data System (ADS)

Takadama, Keiki; Hirose, Kazuyuki; Matsushima, Hiroyasu; Hattori, Kiyohiko; Nakajima, Nobuo

This paper proposes the sleep stage estimation method that can provide an accurate estimation for each person without connecting any devices to human's body. In particular, our method learns the appropriate multiple band-pass filters to extract the specific wave pattern of heartbeat, which is required to estimate the sleep stage. For an accurate estimation, this paper employs Learning Classifier System (LCS) as the data-mining techniques and extends it to estimate the sleep stage. Extensive experiments on five subjects in mixed health confirm the following implications: (1) the proposed method can provide more accurate sleep stage estimation than the conventional method, and (2) the sleep stage estimation calculated by the proposed method is robust regardless of the physical condition of the subject.

Using decision mapping to inform the development of a stated choice survey to elicit youth preferences for sexual and reproductive health and HIV services in rural Malawi.

PubMed

Michaels-Igbokwe, Christine; Lagarde, Mylene; Cairns, John; Terris-Prestholt, Fern

2014-03-01

The process of designing and developing discrete choice experiments (DCEs) is often under reported. The need to adequately report the results of qualitative work used to identify attributes and levels used in a DCE is recognised. However, one area that has received relatively little attention is the exploration of the choice question of interest. This paper provides a case study of the process used to design a stated preference survey to assess youth preferences for integrated sexual and reproductive health (SRH) and HIV outreach services in Malawi. Development and design consisted of six distinct but overlapping and iterative stages. Stage one was a review of the literature. Stage two involved developing a decision map to conceptualise the choice processes involved. Stage three included twelve focus group discussions with young people aged 15-24 (n = 113) and three key informant interviews (n = 3) conducted in Ntcheu District, Malawi. Stage four involved analysis of qualitative data and identification of potential attributes and levels. The choice format and experimental design were selected in stages five and six. The results of the literature review were used to develop a decision map outlining the choices that young people accessing SRH services may face. For youth that would like to use services two key choices were identified: the choice between providers and the choice of service delivery attributes within a provider type. Youth preferences for provider type are best explored using a DCE with a labelled design, while preferences for service delivery attributes associated with a particular provider are better understood using an unlabelled design. Consequently, two DCEs were adopted to jointly assess preferences in this context. Used in combination, the results of the literature review, the decision mapping process and the qualitative work provided robust approach to designing the DCEs individually and as complementary pieces of work. Copyright © 2014 Elsevier Ltd. All rights reserved.

IL1RN Coding Variant Is Associated with Lower Risk of Acute Respiratory Distress Syndrome and Increased Plasma IL-1 Receptor Antagonist

PubMed Central

Feng, Rui; Li, Mingyao; Zhao, Yang; Sheu, Chau-Chyun; Tejera, Paula; Gallop, Robert; Bellamy, Scarlett; Rushefski, Melanie; Lanken, Paul N.; Aplenc, Richard; O’Keefe, Grant E.; Wurfel, Mark M.; Christiani, David C.; Christie, Jason D.

2013-01-01

Rationale: Acute respiratory distress syndrome (ARDS) behaves as a complex genetic trait, yet knowledge of genetic susceptibility factors remains incomplete. Objectives: To identify genetic risk variants for ARDS using large scale genotyping. Methods: A multistage genetic association study was conducted of three critically ill populations phenotyped for ARDS. Stage I, a trauma cohort study (n = 224), was genotyped with a 50K gene-centric single-nucleotide polymorphism (SNP) array. We tested SNPs associated with ARDS at P < 5 × 10−4 for replication in stage II, a trauma case–control population (n = 778). SNPs replicating their association in stage II (P < 0.005) were tested in a stage III nested case–control population of mixed subjects in the intensive care unit (n = 2,063). Logistic regression was used to adjust for potential clinical confounders. We performed ELISA to test for an association between ARDS-associated genotype and plasma protein levels. Measurements and Main Results: A total of 12 SNPs met the stage I threshold for an association with ARDS. rs315952 in the IL1RN gene encoding IL-1 receptor antagonist (IL1RA) replicated its association with reduced ARDS risk in stages II (P < 0.004) and III (P < 0.02), and was robust to clinical adjustment (combined odds ratio = 0.81; P = 4.2 × 10−5). Plasma IL1RA level was associated with rs315952C in a subset of critically ill subjects. The effect of rs315952 was independent from the tandem repeat variant in IL1RN. Conclusions: The IL1RN SNP rs315952C is associated with decreased risk of ARDS in three populations with heterogeneous ARDS risk factors, and with increased plasma IL1RA response. IL1RA may attenuate ARDS risk. PMID:23449693

Robust object matching for persistent tracking with heterogeneous features.

PubMed

Guo, Yanlin; Hsu, Steve; Sawhney, Harpreet S; Kumar, Rakesh; Shan, Ying

2007-05-01

This paper addresses the problem of matching vehicles across multiple sightings under variations in illumination and camera poses. Since multiple observations of a vehicle are separated in large temporal and/or spatial gaps, thus prohibiting the use of standard frame-to-frame data association, we employ features extracted over a sequence during one time interval as a vehicle fingerprint that is used to compute the likelihood that two or more sequence observations are from the same or different vehicles. Furthermore, since our domain is aerial video tracking, in order to deal with poor image quality and large resolution and quality variations, our approach employs robust alignment and match measures for different stages of vehicle matching. Most notably, we employ a heterogeneous collection of features such as lines, points, and regions in an integrated matching framework. Heterogeneous features are shown to be important. Line and point features provide accurate localization and are employed for robust alignment across disparate views. The challenges of change in pose, aspect, and appearances across two disparate observations are handled by combining a novel feature-based quasi-rigid alignment with flexible matching between two or more sequences. However, since lines and points are relatively sparse, they are not adequate to delineate the object and provide a comprehensive matching set that covers the complete object. Region features provide a high degree of coverage and are employed for continuous frames to provide a delineation of the vehicle region for subsequent generation of a match measure. Our approach reliably delineates objects by representing regions as robust blob features and matching multiple regions to multiple regions using Earth Mover's Distance (EMD). Extensive experimentation under a variety of real-world scenarios and over hundreds of thousands of Confirmatory Identification (CID) trails has demonstrated about 95 percent accuracy in vehicle reacquisition with both visible and Infrared (IR) imaging cameras.

Robust 3D face landmark localization based on local coordinate coding.

PubMed

Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Maybank, Stephen J

2014-12-01

In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.

Robust head pose estimation via supervised manifold learning.

PubMed

Wang, Chao; Song, Xubo

2014-05-01

Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Land-Energy Nexus: Life Cycle Land Use of Natural Gas-Fired Electricity

NASA Astrophysics Data System (ADS)

Heath, G.; Jordaan, S.; Macknick, J.; Mohammadi, E.; Ben-Horin, D.; Urrea, V.

2014-12-01

Comparisons of the land required for different types of energy are challenging due to the fact that upstream land use of fossil fuel technologies is not well characterized. This research focuses on improving estimates of the life cycle land use of natural gas-fired electricity through the novel combination of inventories of the location of natural gas-related infrastructure, satellite imagery analysis and gas production data. Land area per unit generation is calculated as the sum of natural gas life cycle stages divided by the throughput of natural gas, combined with the land use of the power plant divided by the generation of the power plant. Five natural gas life cycle stages are evaluated for their area: production, gathering, processing, transmission and disposal. The power plant stage is characterized by a thermal efficiency ηth, which converts MegaJoules (MJ) to kilowatt hours (kWh). We focus on seven counties in the Barnett shale region in Texas that represent over 90% of total Barnett Shale gas production. In addition to assessing the gathering and transmission pipeline network, approximately 500 sites are evaluated from the five life cycle stages plus power plants. For instance, assuming a 50 foot right-of-way for transmission pipelines, this part of the Barnett pipeline network occupies nearly 26,000 acres. Site, road and water components to total area are categorized. Methods are developed to scale up sampled results for each component type to the full population of sites within the Barnett. Uncertainty and variability are charaterized. Well-level production data are examined by integrating commercial datasets with advanced methods for quantifying estimated ultimate recovery (EUR) for wells, then summed to estimate natural gas produced in an entire play. Wells that are spatially coincident are merged using ArcGIS. All other sites are normalized by an estimate of gas throughput. Prior land use estimates are used to validate the satellite imagery analysis. Results of this research will provide a step towards better quantifying the land footprint of energy production activities and a methodologically consistent baseline from which more robust comparisons with alternative energy choices can be made.

A novel protein-based prognostic signature improves risk stratification to guide clinical management in early lung adenocarcinoma patients.

PubMed

Martínez-Terroba, Elena; Behrens, Carmen; de Miguel, Fernando J; Agorreta, Jackeline; Monsó, Eduard; Millares, Laura; Sainz, Cristina; Mesa-Guzman, Miguel; Pérez-Gracia, Jose Luis; Lozano, María Dolores; Zulueta, Javier J; Pio, Ruben; Wistuba, Ignacio I; Montuenga, Luis M; Pajares, María J

2018-05-13

Each of the pathological stages (I-IIIa) in which surgically resected non-small cell lung cancer patients are classified conceals hidden biological heterogeneity, manifested in heterogeneous outcomes within each stage. Thus, the finding of robust and precise molecular classifiers to assess individual patient risk is an unmet medical need. Here we identified and validated the clinical utility of a new prognostic signature based on three proteins (BRCA1, QKI and SLC2A1) to stratify early lung adenocarcinoma patients according to their risk of recurrence or death. Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (8 th edition, 2018). A test cohort (n=239) was used to assess the value of this new prognostic index (PI) based on the three proteins. The prognostic signature was developed by Cox regression following stringent statistical criteria (TRIPOD: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). The model resulted in a highly significant predictor of five-year outcome for disease-free survival (P<0.001) and overall survival (P<0.001). The prognostic ability of the model was externally validated in an independent multi-institutional cohort of patients (n=114, P=0.021). We also demonstrated that this molecular classifier adds relevant information to the gold standard TNM-based pathological staging with a highly significant improvement of likelihood ratio. We subsequently developed a combined prognostic index (CPI) including both the molecular and the pathological data which improved the risk stratification in both cohorts (P≤0.001). Moreover, the signature may help to select stage I-IIA patients who might benefit from adjuvant chemotherapy. In summary, this protein-based signature accurately identifies those patients with high risk of recurrence and death, and adds further prognostic information to the TNM-based clinical staging, even applying the new IASLC 8 th edition staging criteria. More importantly, it may be a valuable tool for selecting patients for adjuvant therapy. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A Two-Stage Kalman Filter Approach for Robust and Real-Time Power System State Estimation

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

Zhang, Jinghe; Welch, Greg; Bishop, Gary

2014-04-01

As electricity demand continues to grow and renewable energy increases its penetration in the power grid, realtime state estimation becomes essential for system monitoring and control. Recent development in phasor technology makes it possible with high-speed time-synchronized data provided by Phasor Measurement Units (PMU). In this paper we present a two-stage Kalman filter approach to estimate the static state of voltage magnitudes and phase angles, as well as the dynamic state of generator rotor angles and speeds. Kalman filters achieve optimal performance only when the system noise characteristics have known statistical properties (zero-mean, Gaussian, and spectrally white). However in practicemore » the process and measurement noise models are usually difficult to obtain. Thus we have developed the Adaptive Kalman Filter with Inflatable Noise Variances (AKF with InNoVa), an algorithm that can efficiently identify and reduce the impact of incorrect system modeling and/or erroneous measurements. In stage one, we estimate the static state from raw PMU measurements using the AKF with InNoVa; then in stage two, the estimated static state is fed into an extended Kalman filter to estimate the dynamic state. Simulations demonstrate its robustness to sudden changes of system dynamics and erroneous measurements.« less

Modeling scintillator and WLS fiber signals for fast Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Sánchez, F. A.; Medina-Tanco, G.

2010-08-01

In this work we present a fast, robust and flexible procedure to simulate electronic signals of scintillator units: plastic scintillator material embedded with a wavelength shifter optical fiber coupled to a photo-multiplier tube which, in turn, is plugged to a front-end electronic board. The simple rationale behind the simulation chain allows to adapt the procedure to a broad range of detectors based on that kind of units. We show that, in order to produce realistic results, the simulation parameters can be properly calibrated against laboratory measurements and used thereafter as input of the simulations. Simulated signals of atmospheric background cosmic ray muons are presented and their main features analyzed and validated using actual measured data. Conversely, for any given practical application, the present simulation scheme can be used to find an adequate combination of photo-multiplier tube and optical fiber at the prototyping stage.

Optimized graph-based mosaicking for virtual microscopy

NASA Astrophysics Data System (ADS)

Steckhan, Dirk G.; Wittenberg, Thomas

2009-02-01

Virtual microscopy has the potential to partially replace traditional microscopy. For virtualization, the slide is scanned once by a fully automatized robotic microscope and saved digitally. Typically, such a scan results in several hundreds to thousands of fields of view. Since robotic stages have positioning errors, these fields of view have to be registered locally and globally in an additional step. In this work we propose a new global mosaicking method for the creation of virtual slides based on sub-pixel exact phase correlation for local alignment in combination with Prim's minimum spanning tree algorithm for global alignment. Our algorithm allows for a robust reproduction of the original slide even in the presence of views with little to no information content. This makes it especially suitable for the mosaicking of cervical smears. These smears often exhibit large empty areas, which do not contain enough information for common stitching approaches.

MIRATE: MIps RATional dEsign Science Gateway.

PubMed

Busato, Mirko; Distefano, Rosario; Bates, Ferdia; Karim, Kal; Bossi, Alessandra Maria; López Vilariño, José Manuel; Piletsky, Sergey; Bombieri, Nicola; Giorgetti, Alejandro

2018-06-13

Molecularly imprinted polymers (MIPs) are high affinity robust synthetic receptors, which can be optimally synthesized and manufactured more economically than their biological equivalents (i.e. antibody). In MIPs production, rational design based on molecular modeling is a commonly employed technique. This mostly aids in (i) virtual screening of functional monomers (FMs), (ii) optimization of monomer-template ratio, and (iii) selectivity analysis. We present MIRATE, an integrated science gateway for the intelligent design of MIPs. By combining and adapting multiple state-of-the-art bioinformatics tools into automated and innovative pipelines, MIRATE guides the user through the entire process of MIPs' design. The platform allows the user to fully customize each stage involved in the MIPs' design, with the main goal to support the synthesis in the wet-laboratory. MIRATE is freely accessible with no login requirement at http://mirate.di.univr.it/. All major browsers are supported.

Simple fibre based dispersion management for two-photon excited fluorescence imaging through an endoscope

NASA Astrophysics Data System (ADS)

Dimopoulos, Konstantinos; Marti, Dominik; Andersen, Peter E.

2018-02-01

We want to implement two-photon excitation fluorescence microscopy (TPEFM) into endoscopes, since TPEFM can provide relevant biomarkers for cancer staging and grading in hollow organs, endoscopically accessible through natural orifices. However, many obstacles must be overcome, among others the delivery of short laser pulses to the distal end of the endoscope. To this avail, we present imaging results using an all-fibre dispersion management scheme in a TPEFM setup. The scheme has been conceived by Jespersen et al. in 20101 and relies on the combination of a single mode fibre with normal and a higher order mode fibre with anomalous dispersion properties, fused in series using a long period grating. We show that using this fibre assembly, a simple and robust pulsed laser delivery system without any free-space optics, which is thus suitable for clinical use, can be realised.

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

PubMed

Niu, Bing; Yuan, Xiao-Cheng; Roeper, Preston; Su, Qiang; Peng, Chun-Rong; Yin, Jing-Yuan; Ding, Juan; Li, HaiPeng; Lu, Wen-Cong

2013-03-01

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.

Robust Operation of Soft Open Points in Active Distribution Networks with High Penetration of Photovoltaic Integration

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

Ding, Fei; Ji, Haoran; Wang, Chengshan

Distributed generators (DGs) including photovoltaic panels (PVs) have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built tomore » tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation (C&CG) algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program (SOCP) to facilitate the accuracy and computation efficiency. Case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method.« less

Second-stage labor: how long is too long?

PubMed

Leveno, Kenneth J; Nelson, David B; McIntire, Donald D

2016-04-01

The management of labor has come under increased scrutiny due to the rapid escalation of cesarean delivery in the United States. A workshop of the Society for Maternal-Fetal Medicine, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and the American Congress of Obstetricians and Gynecologists was convened to address the rising cesarean delivery rates and one of their recommendations was that the accepted upper limit of the second stage of labor should be increased to ≥4 hours in nulliparous women with epidural analgesia and to ≥3 hours in parous women with epidural. This led to the inaugural Obstetric Care Consensus series document, "Safe Prevention of the Primary Cesarean Delivery," wherein the workshop recommendations on second-stage labor were promulgated nationally. The result is that the now acceptable maximum length of the second stage of labor exceeds the obstetric precepts that have been in use for >50 years. In this Clinical Opinion, we review the evidence on infant safety, vis-à-vis length of the second stage of labor. Our examination of the evidence begins at the outset of the 20th century and culminates in the very recent (2014) recommendation to abandon the long accepted obstetric paradigm that second-stage labor >3 hours in nulliparous women with labor epidural is unsafe for the unborn infant. We conclude that the currently available evidence fails to support the Obstetric Care Consensus position that longer second-stage labor is safe for the unborn infant. Indeed, the evidence suggests quite the opposite. We suggest that when infant safety is at stake the evidence should be robust before a new clinical road is taken. The evidence is not robust. Copyright © 2016 Elsevier Inc. All rights reserved.

Investigating Robustness of Item Response Theory Proficiency Estimators to Atypical Response Behaviors under Two-Stage Multistage Testing. ETS GRE® Board Research Report. ETS GRE®-16-03. ETS Research Report No. RR-16-22

ERIC Educational Resources Information Center

Kim, Sooyeon; Moses, Tim

2016-01-01

The purpose of this study is to evaluate the extent to which item response theory (IRT) proficiency estimation methods are robust to the presence of aberrant responses under the "GRE"® General Test multistage adaptive testing (MST) design. To that end, a wide range of atypical response behaviors affecting as much as 10% of the test items…

Systematic analysis of transcription start sites in avian development.

PubMed

Lizio, Marina; Deviatiiarov, Ruslan; Nagai, Hiroki; Galan, Laura; Arner, Erik; Itoh, Masayoshi; Lassmann, Timo; Kasukawa, Takeya; Hasegawa, Akira; Ros, Marian A; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Kawaji, Hideya; Gusev, Oleg; Sheng, Guojun

2017-09-01

Cap Analysis of Gene Expression (CAGE) in combination with single-molecule sequencing technology allows precision mapping of transcription start sites (TSSs) and genome-wide capture of promoter activities in differentiated and steady state cell populations. Much less is known about whether TSS profiling can characterize diverse and non-steady state cell populations, such as the approximately 400 transitory and heterogeneous cell types that arise during ontogeny of vertebrate animals. To gain such insight, we used the chick model and performed CAGE-based TSS analysis on embryonic samples covering the full 3-week developmental period. In total, 31,863 robust TSS peaks (>1 tag per million [TPM]) were mapped to the latest chicken genome assembly, of which 34% to 46% were active in any given developmental stage. ZENBU, a web-based, open-source platform, was used for interactive data exploration. TSSs of genes critical for lineage differentiation could be precisely mapped and their activities tracked throughout development, suggesting that non-steady state and heterogeneous cell populations are amenable to CAGE-based transcriptional analysis. Our study also uncovered a large set of extremely stable housekeeping TSSs and many novel stage-specific ones. We furthermore demonstrated that TSS mapping could expedite motif-based promoter analysis for regulatory modules associated with stage-specific and housekeeping genes. Finally, using Brachyury as an example, we provide evidence that precise TSS mapping in combination with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-on technology enables us, for the first time, to efficiently target endogenous avian genes for transcriptional activation. Taken together, our results represent the first report of genome-wide TSS mapping in birds and the first systematic developmental TSS analysis in any amniote species (birds and mammals). By facilitating promoter-based molecular analysis and genetic manipulation, our work also underscores the value of avian models in unravelling the complex regulatory mechanism of cell lineage specification during amniote development.

Insight into k13-propeller gene polymorphism and ex vivo DHA-response profiles from Cameroonian isolates.

PubMed

Menard, Sandie; Tchoufack, Joëlle Njila; Maffo, Christelle Ngou; Nsango, Sandrine E; Iriart, Xavier; Abate, Luc; Tsapi, Majoline Tchioffo; Awono-Ambéné, Parfait H; Abega Mekongo, Francis A; Morlais, Isabelle; Berry, Antoine

2016-11-26

The spread of Plasmodium falciparum resistance to artemisinin derivatives in Southeast Asia is a major source of concern and the emergence of resistance in Africa would have dramatic consequences, by increasing malaria mortality and morbidity. It is therefore urgent to implement regular monitoring in sentinel sites in sub-Saharan Africa using robust and easy-to-implement tools. The prevalence of k13-propeller mutations and the phenotypic profiles are poorly known in sub-Saharan Africa. Here, the k13-propeller polymorphism was compared to both ex vivo susceptibility to DHA and early parasitological and clinical responses to artemisinin combination therapy (ACT). Plasmodium falciparum isolates were collected in 2015 in Yaoundé (Cameroon) from patients treated with dihydroartemisinin-piperaquine combination. Samples were analysed for their susceptibility to artemisinin using the k13-propeller sequencing, the ex vivo ring-stage survival assay, the in vivo parasite positive rate and the clinical statute at day 2. None of the collected isolates revealed the presence of resistance mutations in the k13-propeller sequence. The median ring-stage survival rate for all the 64 interpretable isolates after a 6-hour pulse of 700 nM dihydroartemisinin was low, 0.49% (IQR: 0-1.3). Total parasite clearance was observed for 87.5% of patients and the remaining parasitaemic isolates (12.5%) showed a high reduction of parasite load, ranging from 97.5 to 99.9%. Clinical symptoms disappeared in 92.8% of cases. This study demonstrated the absence of k13-resistant genotypes in P. falciparum isolates from Cameroon. Only synonymous mutations were found with a low prevalence (4.3%). A good association between k13 genotypes and the ex vivo ring-stage survival assay or parasitological and clinical data was obtained. These results give a baseline for the long-term monitoring of artemisinin derivative efficacy in Africa.

Texture analysis based on the Hermite transform for image classification and segmentation

NASA Astrophysics Data System (ADS)

Estudillo-Romero, Alfonso; Escalante-Ramirez, Boris; Savage-Carmona, Jesus

2012-06-01

Texture analysis has become an important task in image processing because it is used as a preprocessing stage in different research areas including medical image analysis, industrial inspection, segmentation of remote sensed imaginary, multimedia indexing and retrieval. In order to extract visual texture features a texture image analysis technique is presented based on the Hermite transform. Psychovisual evidence suggests that the Gaussian derivatives fit the receptive field profiles of mammalian visual systems. The Hermite transform describes locally basic texture features in terms of Gaussian derivatives. Multiresolution combined with several analysis orders provides detection of patterns that characterizes every texture class. The analysis of the local maximum energy direction and steering of the transformation coefficients increase the method robustness against the texture orientation. This method presents an advantage over classical filter bank design because in the latter a fixed number of orientations for the analysis has to be selected. During the training stage, a subset of the Hermite analysis filters is chosen in order to improve the inter-class separability, reduce dimensionality of the feature vectors and computational cost during the classification stage. We exhaustively evaluated the correct classification rate of real randomly selected training and testing texture subsets using several kinds of common used texture features. A comparison between different distance measurements is also presented. Results of the unsupervised real texture segmentation using this approach and comparison with previous approaches showed the benefits of our proposal.

Robust Control Design for Systems With Probabilistic Uncertainty

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.

2005-01-01

This paper presents a reliability- and robustness-based formulation for robust control synthesis for systems with probabilistic uncertainty. In a reliability-based formulation, the probability of violating design requirements prescribed by inequality constraints is minimized. In a robustness-based formulation, a metric which measures the tendency of a random variable/process to cluster close to a target scalar/function is minimized. A multi-objective optimization procedure, which combines stability and performance requirements in time and frequency domains, is used to search for robustly optimal compensators. Some of the fundamental differences between the proposed strategy and conventional robust control methods are: (i) unnecessary conservatism is eliminated since there is not need for convex supports, (ii) the most likely plants are favored during synthesis allowing for probabilistic robust optimality, (iii) the tradeoff between robust stability and robust performance can be explored numerically, (iv) the uncertainty set is closely related to parameters with clear physical meaning, and (v) compensators with improved robust characteristics for a given control structure can be synthesized.

Non-linear control of the output stage of a solar microinverter

NASA Astrophysics Data System (ADS)

Lopez-Santos, Oswaldo; Garcia, Germain; Martinez-Salamero, Luis; Avila-Martinez, Juan C.; Seguier, Lionel

2017-01-01

This paper presents a proposal to control the output stage of a two-stage solar microinverter to inject real power into the grid. The input stage of the microinverter is used to extract the maximum available power of a photovoltaic module enforcing a power source behavior in the DC-link to feed the output stage. The work here reported is devoted to control a grid-connected power source inverter with a high power quality level at the grid side ensuring the power balance of the microinverter regulating the voltage of the DC-link. The proposed control is composed of a sinusoidal current reference generator and a cascade type controller composed by a current tracking loop and a voltage regulation loop. The current reference is obtained using a synchronized generator based on phase locked loop (PLL) which gives the shape, the frequency and phase of the current signal. The amplitude of the reference is obtained from a simple controller regulating the DC-link voltage. The tracking of the current reference is accomplished by means of a first-order sliding mode control law. The solution takes advantage of the rapidity and inherent robustness of the sliding mode current controller allowing a robust behavior in the regulation of the DC-link using a simple linear controller. The analytical expression to determine the power quality indicators of the micro-inverter's output is theoretically solved giving expressions relating the converter parameters. The theoretical approach is validated using simulation and experimental results.

Multi-wavelength approach towards on-product overlay accuracy and robustness

NASA Astrophysics Data System (ADS)

Bhattacharyya, Kaustuve; Noot, Marc; Chang, Hammer; Liao, Sax; Chang, Ken; Gosali, Benny; Su, Eason; Wang, Cathy; den Boef, Arie; Fouquet, Christophe; Huang, Guo-Tsai; Chen, Kai-Hsiung; Cheng, Kevin; Lin, John

2018-03-01

Success of diffraction-based overlay (DBO) technique1,4,5 in the industry is not just for its good precision and low toolinduced shift, but also for the measurement accuracy2 and robustness that DBO can provide. Significant efforts are put in to capitalize on the potential that DBO has to address measurement accuracy and robustness. Introduction of many measurement wavelength choices (continuous wavelength) in DBO is one of the key new capabilities in this area. Along with the continuous choice of wavelengths, the algorithms (fueled by swing-curve physics) on how to use these wavelengths are of high importance for a robust recipe setup that can avoid the impact from process stack variations (symmetric as well as asymmetric). All these are discussed. Moreover, another aspect of boosting measurement accuracy and robustness is discussed that deploys the capability to combine overlay measurement data from multiple wavelength measurements. The goal is to provide a method to make overlay measurements immune from process stack variations and also to report health KPIs for every measurement. By combining measurements from multiple wavelengths, a final overlay measurement is generated. The results show a significant benefit in accuracy and robustness against process stack variation. These results are supported by both measurement data as well as simulation from many product stacks.

Concerted evolution of life stage performances signals recent selection on yeast nitrogen use.

PubMed

Ibstedt, Sebastian; Stenberg, Simon; Bagés, Sara; Gjuvsland, Arne B; Salinas, Francisco; Kourtchenko, Olga; Samy, Jeevan K A; Blomberg, Anders; Omholt, Stig W; Liti, Gianni; Beltran, Gemma; Warringer, Jonas

2015-01-01

Exposing natural selection driving phenotypic and genotypic adaptive differentiation is an extraordinary challenge. Given that an organism's life stages are exposed to the same environmental variations, we reasoned that fitness components, such as the lag, rate, and efficiency of growth, directly reflecting performance in these life stages, should often be selected in concert. We therefore conjectured that correlations between fitness components over natural isolates, in a particular environmental context, would constitute a robust signal of recent selection. Critically, this test for selection requires fitness components to be determined by different genetic loci. To explore our conjecture, we exhaustively evaluated the lag, rate, and efficiency of asexual population growth of natural isolates of the model yeast Saccharomyces cerevisiae in a large variety of nitrogen-limited environments. Overall, fitness components were well correlated under nitrogen restriction. Yeast isolates were further crossed in all pairwise combinations and coinheritance of each fitness component and genetic markers were traced. Trait variations tended to map to quantitative trait loci (QTL) that were private to a single fitness component. We further traced QTLs down to single-nucleotide resolution and uncovered loss-of-function mutations in RIM15, PUT4, DAL1, and DAL4 as the genetic basis for nitrogen source use variations. Effects of SNPs were unique for a single fitness component, strongly arguing against pleiotropy between lag, rate, and efficiency of reproduction under nitrogen restriction. The strong correlations between life stage performances that cannot be explained by pleiotropy compellingly support adaptive differentiation of yeast nitrogen source use and suggest a generic approach for detecting selection. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Deep Sequencing of T-cell Receptor DNA as a Biomarker of Clonally Expanded TILs in Breast Cancer after Immunotherapy.

PubMed

Page, David B; Yuan, Jianda; Redmond, David; Wen, Y Hanna; Durack, Jeremy C; Emerson, Ryan; Solomon, Stephen; Dong, Zhiwan; Wong, Phillip; Comstock, Christopher; Diab, Adi; Sung, Janice; Maybody, Majid; Morris, Elizabeth; Brogi, Edi; Morrow, Monica; Sacchini, Virgilio; Elemento, Olivier; Robins, Harlan; Patil, Sujata; Allison, James P; Wolchok, Jedd D; Hudis, Clifford; Norton, Larry; McArthur, Heather L

2016-10-01

In early-stage breast cancer, the degree of tumor-infiltrating lymphocytes (TIL) predicts response to chemotherapy and overall survival. Combination immunotherapy with immune checkpoint antibody plus tumor cryoablation can induce lymphocytic infiltrates and improve survival in mice. We used T-cell receptor (TCR) DNA sequencing to evaluate both the effect of cryoimmunotherapy in humans and the feasibility of TCR sequencing in early-stage breast cancer. In a pilot clinical trial, 18 women with early-stage breast cancer were treated preoperatively with cryoablation, single-dose anti-CTLA-4 (ipilimumab), or cryoablation + ipilimumab. TCRs within serially collected peripheral blood and tumor tissue were sequenced. In baseline tumor tissues, T-cell density as measured by TCR sequencing correlated with TIL scores obtained by hematoxylin and eosin (H&E) staining. However, tumors with little or no lymphocytes by H&E contained up to 3.6 × 10 6 TCR DNA sequences, highlighting the sensitivity of the ImmunoSEQ platform. In this dataset, ipilimumab increased intratumoral T-cell density over time, whereas cryoablation ± ipilimumab diversified and remodeled the intratumoral T-cell clonal repertoire. Compared with monotherapy, cryoablation plus ipilimumab was associated with numerically greater numbers of peripheral blood and intratumoral T-cell clones expanding robustly following therapy. In conclusion, TCR sequencing correlates with H&E lymphocyte scoring and provides additional information on clonal diversity. These findings support further study of the use of TCR sequencing as a biomarker for T-cell responses to therapy and for the study of cryoimmunotherapy in early-stage breast cancer. Cancer Immunol Res; 4(10); 835-44. ©2016 AACR. ©2016 American Association for Cancer Research.

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Full scale implementation of the nutrient limited BAS process at Södra Cell Värö.

PubMed

Malmqvist, A; Berggren, B; Sjölin, C; Welander, T; Heuts, L; Fransén, A; Ling, D

2004-01-01

A combination of the suspended carrier biofilm process and the activated sludge process (biofilm-activated sludge--BAS) has been shown to be very successful for the treatment of different types of pulp and paper mill effluents. The robust biofilm pre-treatment in combination with activated sludge results in a stable, compact and highly efficient process. Recent findings have shown that nutrient limited operation of the biofilm process greatly improves the sludge characteristics in the following activated sludge stage, while minimising sludge production and effluent discharge of nutrients. The nutrient limited BAS process was implemented at full scale at the Södra Cell Värö kraft mill and taken into operation in July 2002. After start-up and optimisation over about 5 months, the process meets all effluent discharge limits. The removal of COD is close to 70% and the removal of EDTA greater than 90%. Typical effluent concentrations of suspended solids and nutrients during stable operations have been 20-30 mg/L TSS, 0.3-0.5 mg/L phosphorus and 3-5 mg/L nitrogen. The sludge production was 0.09 kgSS/kg COD removed and the sludge volume index was 50-100 mL/g.

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

A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness.

PubMed

Li, Gang; Chung, Wan-Young

2015-08-21

Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness.

A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness

PubMed Central

Li, Gang; Chung, Wan-Young

2015-01-01

Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness. PMID:26308002

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables in the North Central USA

NASA Astrophysics Data System (ADS)

Hoss, F.; Fischbeck, P. S.

2014-10-01

This study further develops the method of quantile regression (QR) to predict exceedance probabilities of flood stages by post-processing forecasts. Using data from the 82 river gages, for which the National Weather Service's North Central River Forecast Center issues forecasts daily, this is the first QR application to US American river gages. Archived forecasts for lead times up to six days from 2001-2013 were analyzed. Earlier implementations of QR used the forecast itself as the only independent variable (Weerts et al., 2011; López López et al., 2014). This study adds the rise rate of the river stage in the last 24 and 48 h and the forecast error 24 and 48 h ago to the QR model. Including those four variables significantly improved the forecasts, as measured by the Brier Skill Score (BSS). Mainly, the resolution increases, as the original QR implementation already delivered high reliability. Combining the forecast with the other four variables results in much less favorable BSSs. Lastly, the forecast performance does not depend on the size of the training dataset, but on the year, the river gage, lead time and event threshold that are being forecast. We find that each event threshold requires a separate model configuration or at least calibration.

HINTW, a W-chromosome HINT gene in chick, is expressed ubiquitously and is a robust female cell marker applicable in intraspecific chimera studies.

PubMed

Nagai, Hiroki; Sezaki, Maiko; Bertocchini, Federica; Fukuda, Kimiko; Sheng, Guojun

2014-05-01

Grafting and transplantation experiments in embryology require proper distinction between host and donor tissues. For the avian model this has traditionally been achieved by using two closely related species (e.g., chick and quail) followed by species-specific antibody staining. Here, we show that an in situ hybridization probe against the HINTW gene is a robust and reliable marker for female-derived chicken cells. At all pre-circulation stages tested, all cells in female embryos, independently confirmed by PCR analysis, were strongly positive for HINTW, whereas all male embryos were negative. This probe is broadly applicable in intra-specific chick/chick chimera studies, and as a proof of principle, we utilized this probe to detect female cells in three experimental settings: (1) to mark female donor cells in a node transplantation assay; (2) to distinguish female cells in male/female twins generated by the Cornish pasty culture; and (3) to detect female half of the embryo in artificially generated bilateral gynandromorphs. A rapid, PCR based pre-screening step increases the efficiency of obtaining desired donor/host sex combination from 25% to 100%. For most avian chimera studies, this female-specific in situ probe is a low cost alternative to the commonly used QCPN antibody and to ubiquitous-GFP chicken strains which are not widely available to the research community. © 2014 Wiley Periodicals, Inc.

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Robust photometric invariant features from the color tensor.

PubMed

van de Weijer, Joost; Gevers, Theo; Smeulders, Arnold W M

2006-01-01

Luminance-based features are widely used as low-level input for computer vision applications, even when color data is available. The extension of feature detection to the color domain prevents information loss due to isoluminance and allows us to exploit the photometric information. To fully exploit the extra information in the color data, the vector nature of color data has to be taken into account and a sound framework is needed to combine feature and photometric invariance theory. In this paper, we focus on the structure tensor, or color tensor, which adequately handles the vector nature of color images. Further, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. We circumvent the drawback of unstable photometric invariants by deriving an uncertainty measure to accompany the photometric invariant derivatives. The uncertainty is incorporated in the color tensor, hereby allowing the computation of robust photometric invariant features. The combination of the photometric invariance theory and tensor-based features allows for detection of a variety of features such as photometric invariant edges, corners, optical flow, and curvature. The proposed features are tested for noise characteristics and robustness to photometric changes. Experiments show that the proposed features are robust to scene incidental events and that the proposed uncertainty measure improves the applicability of full invariants.

A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle

NASA Astrophysics Data System (ADS)

Nejlaoui, Mohamed; Houidi, Ajmi; Affi, Zouhaier; Romdhane, Lotfi

2017-10-01

This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.

A microscale human liver platform that supports the hepatic stages of Plasmodium falciparum and vivax

PubMed Central

March, Sandra; Ng, Shengyong; Velmurugan, Soundarapandian; Galstian, Ani; Shan, Jing; Logan, David; Carpenter, Anne; Thomas, David; Lee Sim, B. Kim; Mota, Maria M.; Hoffman, Stephen L.; Bhatia, Sangeeta N.

2013-01-01

SUMMARY The Plasmodium liver stage is an attractive target for the development of anti-malarial drugs and vaccines, as it provides an opportunity to interrupt the life cycle of the parasite at a critical early stage. However, targeting the liver stage has been difficult. Undoubtedly, a major barrier has been the lack of robust, reliable and reproducible in vitro liver stage cultures. Here, we establish the liver stages for both Plasmodium falciparum and Plasmodium vivax in a microscale human liver platform composed of cryopreserved, micropatterned human primary hepatocytes surrounded by supportive stromal cells. Using this system, we have successfully recapitulated the full liver stage of P. falciparum including the release of infected merozoites and infection of overlaid erythrocytes, and also the establishment of small forms in late liver stages of P. vivax. Finally, we validate the potential of this platform as a tool for medium-throughput anti-malarial drug screening and vaccine development. PMID:23870318

A transgenic Plasmodium falciparum NF54 strain that expresses GFP-luciferase throughout the parasite life cycle.

PubMed

Vaughan, Ashley M; Mikolajczak, Sebastian A; Camargo, Nelly; Lakshmanan, Viswanathan; Kennedy, Mark; Lindner, Scott E; Miller, Jessica L; Hume, Jen C C; Kappe, Stefan H I

2012-12-01

Plasmodium falciparum is the pathogenic agent of the most lethal of human malarias. Transgenic P. falciparum parasites expressing luciferase have been created to study drug interventions of both asexual and sexual blood stages but luciferase-expressing mosquito stage and liver stage parasites have not been created which has prevented the easy quantification of mosquito stage development (e.g. for transmission blocking interventions) and liver stage development (for interventions that prevent infection). To overcome this obstacle, we have created a transgenic P. falciparum NF54 parasite that expresses a GFP-luciferase transgene throughout the life cycle. Luciferase expression is robust and measurable at all life cycle stages, including midgut oocyst, salivary gland sporozoites and liver stages, where in vivo development is easily measurable using humanized mouse infections in conjunction with an in vivo imaging system. This parasite reporter strain will accelerate testing of interventions against pre-erythrocytic life cycle stages. Copyright © 2012 Elsevier B.V. All rights reserved.

Chemometric optimization of the robustness of the near infrared spectroscopic method in wheat quality control.

PubMed

Pojić, Milica; Rakić, Dušan; Lazić, Zivorad

2015-01-01

A chemometric approach was applied for the optimization of the robustness of the NIRS method for wheat quality control. Due to the high number of experimental (n=6) and response variables to be studied (n=7) the optimization experiment was divided into two stages: screening stage in order to evaluate which of the considered variables were significant, and optimization stage to optimize the identified factors in the previously selected experimental domain. The significant variables were identified by using fractional factorial experimental design, whilst Box-Wilson rotatable central composite design (CCRD) was run to obtain the optimal values for the significant variables. The measured responses included: moisture, protein and wet gluten content, Zeleny sedimentation value and deformation energy. In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE). The simultaneous optimization of factors was conducted by desirability function. The highest desirability of 87.63% was accomplished by setting up experimental conditions as follows: 19.9°C for sample temperature, 19.3°C for ambient temperature and 240V for instrument voltage. Copyright © 2014 Elsevier B.V. All rights reserved.

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies

PubMed Central

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-01-01

Abstract Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. PMID:29106476

Inexpensive, Robust Water Stage Sensor for Rural Community Footbridges

NASA Astrophysics Data System (ADS)

Bradley, A.; McDermot, D. J.; Langenfeld, K.; Kruger, A.; Niemeier, J. J.

2014-12-01

Footbridges across streams and rivers provide rural communities in many countries essential access to hospitals, schools, and economic opportunities. Without these, communities experience isolation during the rainy season. However, many of these bridges are subject to immersion at times, and there is a need for sensing the river stage before venturing onto a bridge. We have developed an inexpensive, robust, self-contained sensor that meets this need. A two-wire electrical cord, purchased in bulk from a home improvement supplier, is the basic sensing element. The two conductors of the cord form a transmission line capacitor. The cord is suspended below the footbridge and the capacitance is a function of the fraction of the electrical cord that is immersed in water. The cord/capacitor is part of the timing element of an electronic oscillator circuit. As the water level rises, the capacitance and oscillator frequency decrease. The oscillator frequency is measured with a microcontroller. The microcontroller calculates the corresponding water stage and displays it on a small LCD display. The electronics are contained in a 12×7×7 cm watertight container. Four AA batteries power the sensor. The device has calibration features to accommodate different types of electrical cord.

Rapamycin and CHIR99021 Coordinate Robust Cardiomyocyte Differentiation From Human Pluripotent Stem Cells Via Reducing p53-Dependent Apoptosis.

PubMed

Qiu, Xiao-Xu; Liu, Yang; Zhang, Yi-Fan; Guan, Ya-Na; Jia, Qian-Qian; Wang, Chen; Liang, He; Li, Yong-Qin; Yang, Huang-Tian; Qin, Yong-Wen; Huang, Shuang; Zhao, Xian-Xian; Jing, Qing

2017-10-02

Cardiomyocytes differentiated from human pluripotent stem cells can serve as an unexhausted source for a cellular cardiac disease model. Although small molecule-mediated cardiomyocyte differentiation methods have been established, the differentiation efficiency is relatively unsatisfactory in multiple lines due to line-to-line variation. Additionally, hurdles including line-specific low expression of endogenous growth factors and the high apoptotic tendency of human pluripotent stem cells also need to be overcome to establish robust and efficient cardiomyocyte differentiation. We used the H9-human cardiac troponin T-eGFP reporter cell line to screen for small molecules that promote cardiac differentiation in a monolayer-based and growth factor-free differentiation model. We found that collaterally treating human pluripotent stem cells with rapamycin and CHIR99021 during the initial stage was essential for efficient and reliable cardiomyocyte differentiation. Moreover, this method maintained consistency in efficiency across different human embryonic stem cell and human induced pluripotent stem cell lines without specifically optimizing multiple parameters (the efficiency in H7, H9, and UQ1 human induced pluripotent stem cells is 98.3%, 93.3%, and 90.6%, respectively). This combination also increased the yield of cardiomyocytes (1:24) and at the same time reduced medium consumption by about 50% when compared with the previous protocols. Further analysis indicated that inhibition of the mammalian target of rapamycin allows efficient cardiomyocyte differentiation through overcoming p53-dependent apoptosis of human pluripotent stem cells during high-density monolayer culture via blunting p53 translation and mitochondrial reactive oxygen species production. We have demonstrated that mammalian target of rapamycin exerts a stage-specific and multifaceted regulation over cardiac differentiation and provides an optimized approach for generating large numbers of functional cardiomyocytes for disease modeling and in vitro drug screening. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Cromolyn Reduces Levels of the Alzheimer's Disease-Associated Amyloid β-Protein by Promoting Microglial Phagocytosis.

PubMed

Zhang, Can; Griciuc, Ana; Hudry, Eloise; Wan, Yu; Quinti, Luisa; Ward, Joseph; Forte, Angela M; Shen, Xunuo; Ran, ChongZhao; Elmaleh, David R; Tanzi, Rudolph E

2018-01-18

Amyloid-beta protein (Aβ) deposition is a pathological hallmark of Alzheimer's disease (AD). Aβ deposition triggers both pro-neuroinflammatory microglial activation and neurofibrillary tangle formation. Cromolyn sodium is an asthma therapeutic agent previously shown to reduce Aβ levels in transgenic AD mouse brains after one-week of treatment. Here, we further explored these effects as well as the mechanism of action of cromolyn, alone, and in combination with ibuprofen in APP Swedish -expressing Tg2576 mice. Mice were treated for 3 months starting at 5 months of age, when the earliest stages of β-amyloid deposition begin. Cromolyn, alone, or in combination with ibuprofen, almost completely abolished longer insoluble Aβ species, i.e. Aβ40 and Aβ42, but increased insoluble Aβ38 levels. In addition to its anti-aggregation effects on Aβ, cromolyn, alone, or plus ibuprofen, but not ibuprofen alone, increased microglial recruitment to, and phagocytosis of β-amyloid deposits in AD mice. Cromolyn also promoted Aβ42 uptake in microglial cell-based assays. Collectively, our data reveal robust effects of cromolyn, alone, or in combination with ibuprofen, in reducing aggregation-prone Aβ levels and inducing a neuroprotective microglial activation state favoring Aβ phagocytosis versus a pro-neuroinflammatory state. These findings support the use of cromolyn, alone, or with ibuprofen, as a potential AD therapeutic.

Simulating Protein Mediated Hydrolysis of ATP and Other Nucleoside Triphosphates by Combining QM/MM Molecular Dynamics with Advances in Metadynamics

PubMed Central

2017-01-01

The protein mediated hydrolysis of nucleoside triphosphates such as ATP or GTP is one of the most important and challenging biochemical reactions in nature. The chemical environment (water structure, catalytic metal, and amino acid residues) adjacent to the hydrolysis site contains hundreds of atoms, usually greatly limiting the amount of the free energy sampling that one can achieve from computationally demanding electronic structure calculations such as QM/MM simulations. Therefore, the combination of QM/MM molecular dynamics with the recently developed transition-tempered metadynamics (TTMetaD), an enhanced sampling method that can provide a high-quality free energy estimate at an early stage in a simulation, is an ideal approach to address the biomolecular nucleoside triphosphate hydrolysis problem. In this work the ATP hydrolysis process in monomeric and filamentous actin is studied as an example application of the combined methodology. The performance of TTMetaD in these demanding QM/MM simulations is compared with that of the more conventional well-tempered metadynamics (WTMetaD). Our results show that TTMetaD exhibits much better exploration of the hydrolysis reaction free energy surface in two key collective variables (CVs) during the early stages of the QM/MM simulation than does WTMetaD. The TTMetaD simulations also reveal that a key third degree of freedom, the O–H bond-breaking and proton transfer from the lytic water, must be biased for TTMetaD to converge fully. To perturb the NTP hydrolysis dynamics to the least extent and to properly focus the MetaD free energy sampling, we also adopt here the recently developed metabasin metadynamics (MBMetaD) to construct a self-limiting bias potential that only applies to the lytic water after its nucleophilic attack of the phosphate of ATP. With these new, state-of-the-art enhanced sampling metadynamics techniques, we present an effective and accurate computational strategy for combining QM/MM molecular dynamics simulation with free energy sampling methodology, including a means to analyze the convergence of the calculations through robust numerical criteria. PMID:28345907

Simulating Protein Mediated Hydrolysis of ATP and Other Nucleoside Triphosphates by Combining QM/MM Molecular Dynamics with Advances in Metadynamics.

PubMed

Sun, Rui; Sode, Olaseni; Dama, James F; Voth, Gregory A

2017-05-09

The protein mediated hydrolysis of nucleoside triphosphates such as ATP or GTP is one of the most important and challenging biochemical reactions in nature. The chemical environment (water structure, catalytic metal, and amino acid residues) adjacent to the hydrolysis site contains hundreds of atoms, usually greatly limiting the amount of the free energy sampling that one can achieve from computationally demanding electronic structure calculations such as QM/MM simulations. Therefore, the combination of QM/MM molecular dynamics with the recently developed transition-tempered metadynamics (TTMetaD), an enhanced sampling method that can provide a high-quality free energy estimate at an early stage in a simulation, is an ideal approach to address the biomolecular nucleoside triphosphate hydrolysis problem. In this work the ATP hydrolysis process in monomeric and filamentous actin is studied as an example application of the combined methodology. The performance of TTMetaD in these demanding QM/MM simulations is compared with that of the more conventional well-tempered metadynamics (WTMetaD). Our results show that TTMetaD exhibits much better exploration of the hydrolysis reaction free energy surface in two key collective variables (CVs) during the early stages of the QM/MM simulation than does WTMetaD. The TTMetaD simulations also reveal that a key third degree of freedom, the O-H bond-breaking and proton transfer from the lytic water, must be biased for TTMetaD to converge fully. To perturb the NTP hydrolysis dynamics to the least extent and to properly focus the MetaD free energy sampling, we also adopt here the recently developed metabasin metadynamics (MBMetaD) to construct a self-limiting bias potential that only applies to the lytic water after its nucleophilic attack of the phosphate of ATP. With these new, state-of-the-art enhanced sampling metadynamics techniques, we present an effective and accurate computational strategy for combining QM/MM molecular dynamics simulation with free energy sampling methodology, including a means to analyze the convergence of the calculations through robust numerical criteria.

Fractal dimension based damage identification incorporating multi-task sparse Bayesian learning

NASA Astrophysics Data System (ADS)

Huang, Yong; Li, Hui; Wu, Stephen; Yang, Yongchao

2018-07-01

Sensitivity to damage and robustness to noise are critical requirements for the effectiveness of structural damage detection. In this study, a two-stage damage identification method based on the fractal dimension analysis and multi-task Bayesian learning is presented. The Higuchi’s fractal dimension (HFD) based damage index is first proposed, directly examining the time-frequency characteristic of local free vibration data of structures based on the irregularity sensitivity and noise robustness analysis of HFD. Katz’s fractal dimension is then presented to analyze the abrupt irregularity change of the spatial curve of the displacement mode shape along the structure. At the second stage, the multi-task sparse Bayesian learning technique is employed to infer the final damage localization vector, which borrow the dependent strength of the two fractal dimension based damage indication information and also incorporate the prior knowledge that structural damage occurs at a limited number of locations in a structure in the absence of its collapse. To validate the capability of the proposed method, a steel beam and a bridge, named Yonghe Bridge, are analyzed as illustrative examples. The damage identification results demonstrate that the proposed method is capable of localizing single and multiple damages regardless of its severity, and show superior robustness under heavy noise as well.

Intelligent nonsingular terminal sliding-mode control using MIMO Elman neural network for piezo-flexural nanopositioning stage.

PubMed

Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan

2012-12-01

The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.

A robust two-stage design identifying the optimal biological dose for phase I/II clinical trials.

PubMed

Zang, Yong; Lee, J Jack

2017-01-15

We propose a robust two-stage design to identify the optimal biological dose for phase I/II clinical trials evaluating both toxicity and efficacy outcomes. In the first stage of dose finding, we use the Bayesian model averaging continual reassessment method to monitor the toxicity outcomes and adopt an isotonic regression method based on the efficacy outcomes to guide dose escalation. When the first stage ends, we use the Dirichlet-multinomial distribution to jointly model the toxicity and efficacy outcomes and pick the candidate doses based on a three-dimensional volume ratio. The selected candidate doses are then seamlessly advanced to the second stage for dose validation. Both toxicity and efficacy outcomes are continuously monitored so that any overly toxic and/or less efficacious dose can be dropped from the study as the trial continues. When the phase I/II trial ends, we select the optimal biological dose as the dose obtaining the minimal value of the volume ratio within the candidate set. An advantage of the proposed design is that it does not impose a monotonically increasing assumption on the shape of the dose-efficacy curve. We conduct extensive simulation studies to examine the operating characteristics of the proposed design. The simulation results show that the proposed design has desirable operating characteristics across different shapes of the underlying true dose-toxicity and dose-efficacy curves. The software to implement the proposed design is available upon request. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Molecular Phenotyping in Predicting Response in Patients With Stage IB-III Esophageal Cancer Receiving Combination Chemotherapy

ClinicalTrials.gov

2018-01-16

Stage IB Esophageal Adenocarcinoma; Stage IIA Esophageal Adenocarcinoma; Stage IIB Esophageal Adenocarcinoma; Stage IIIA Esophageal Adenocarcinoma; Stage IIIB Esophageal Adenocarcinoma; Stage IIIC Esophageal Adenocarcinoma

A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

NASA Astrophysics Data System (ADS)

Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu

This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

NASA Astrophysics Data System (ADS)

Matheja, Timo; Buck, Markus; Fingscheidt, Tim

2013-12-01

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers' signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

Probabilistic Risk Assessment of Hydraulic Fracturing in Unconventional Reservoirs by Means of Fault Tree Analysis: An Initial Discussion

NASA Astrophysics Data System (ADS)

Rodak, C. M.; McHugh, R.; Wei, X.

2016-12-01

The development and combination of horizontal drilling and hydraulic fracturing has unlocked unconventional hydrocarbon reserves around the globe. These advances have triggered a number of concerns regarding aquifer contamination and over-exploitation, leading to scientific studies investigating potential risks posed by directional hydraulic fracturing activities. These studies, balanced with potential economic benefits of energy production, are a crucial source of information for communities considering the development of unconventional reservoirs. However, probabilistic quantification of the overall risk posed by hydraulic fracturing at the system level are rare. Here we present the concept of fault tree analysis to determine the overall probability of groundwater contamination or over-exploitation, broadly referred to as the probability of failure. The potential utility of fault tree analysis for the quantification and communication of risks is approached with a general application. However, the fault tree design is robust and can handle various combinations of regional-specific data pertaining to relevant spatial scales, geological conditions, and industry practices where available. All available data are grouped into quantity and quality-based impacts and sub-divided based on the stage of the hydraulic fracturing process in which the data is relevant as described by the USEPA. Each stage is broken down into the unique basic events required for failure; for example, to quantify the risk of an on-site spill we must consider the likelihood, magnitude, composition, and subsurface transport of the spill. The structure of the fault tree described above can be used to render a highly complex system of variables into a straightforward equation for risk calculation based on Boolean logic. This project shows the utility of fault tree analysis for the visual communication of the potential risks of hydraulic fracturing activities on groundwater resources.

Pre-vascularization Enhances Therapeutic Effects of Human Mesenchymal Stem Cell Sheets in Full Thickness Skin Wound Repair.

PubMed

Chen, Lei; Xing, Qi; Zhai, Qiyi; Tahtinen, Mitchell; Zhou, Fei; Chen, Lili; Xu, Yingbin; Qi, Shaohai; Zhao, Feng

2017-01-01

Split thickness skin graft (STSG) implantation is one of the standard therapies for full thickness wound repair when full thickness autologous skin grafts (FTG) or skin flap transplants are inapplicable. Combined transplantation of STSG with dermal substitute could enhance its therapeutic effects but the results remain unsatisfactory due to insufficient blood supply at early stages, which causes graft necrosis and fibrosis. Human mesenchymal stem cell (hMSC) sheets are capable of accelerating the wound healing process. We hypothesized that pre-vascularized hMSC sheets would further improve regeneration by providing more versatile angiogenic factors and pre-formed microvessels. In this work, in vitro cultured hMSC cell sheets (HCS) and pre-vascularized hMSC cell sheets (PHCS) were implanted in a rat full thickness skin wound model covered with an autologous STSG. Results demonstrated that the HCS and the PHCS implantations significantly reduced skin contraction and improved cosmetic appearance relative to the STSG control group. The PHCS group experienced the least hemorrhage and necrosis, and lowest inflammatory cell infiltration. It also induced the highest neovascularization in early stages, which established a robust blood micro-circulation to support grafts survival and tissue regeneration. Moreover, the PHCS grafts preserved the largest amount of skin appendages, including hair follicles and sebaceous glands, and developed the smallest epidermal thickness. The superior therapeutic effects seen in PHCS groups were attributed to the elevated presence of growth factors and cytokines in the pre-vascularized cell sheet, which exerted a beneficial paracrine signaling during wound repair. Hence, the strategy of combining STSG with PHCS implantation appears to be a promising approach in regenerative treatment of full thickness skin wounds.

Predictive Factor Analysis of Response-Adapted Radiation Therapy for Chemotherapy-Sensitive Pediatric Hodgkin Lymphoma: Analysis of the Children's Oncology Group AHOD 0031 Trial

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

Charpentier, Anne-Marie; Friedman, Debra L.; Wolden, Suzanne

Purpose: To evaluate whether clinical risk factors could further distinguish children with intermediate-risk Hodgkin lymphoma (HL) with rapid early and complete anatomic response (RER/CR) who benefit significantly from involved-field RT (IFRT) from those who do not, and thereby aid refinement of treatment selection. Methods and Materials: Children with intermediate-risk HL treated on the Children's Oncology Group AHOD 0031 trial who achieved RER/CR with 4 cycles of chemotherapy, and who were randomized to 21-Gy IFRT or no additional therapy (n=716) were the subject of this study. Recursive partitioning analysis was used to identify factors associated with clinically and statistically significant improvement inmore » event-free survival (EFS) after randomization to IFRT. Bootstrap sampling was used to evaluate the robustness of the findings. Result: Although most RER/CR patients did not benefit significantly from IFRT, those with a combination of anemia and bulky limited-stage disease (n=190) had significantly better 4-year EFS with the addition of IFRT (89.3% vs 77.9% without IFRT; P=.019); this benefit was consistently reproduced in bootstrap analyses and after adjusting for other prognostic factors. Conclusion: Although most patients achieving RER/CR had favorable outcomes with 4 cycles of chemotherapy alone, those children with initial bulky stage I/II disease and anemia had significantly better EFS with the addition of IFRT as part of combined-modality therapy. Further work evaluating the interaction of clinical and biologic factors and imaging response is needed to further optimize and refine treatment selection.« less

Acute Effects of Ambient Particulate Matter on Mortality in Europe and North America: Results from the APHENA Study

PubMed Central

Samoli, Evangelia; Peng, Roger; Ramsay, Tim; Pipikou, Marina; Touloumi, Giota; Dominici, Francesca; Burnett, Rick; Cohen, Aaron; Krewski, Daniel; Samet, Jon; Katsouyanni, Klea

2008-01-01

Background The APHENA (Air Pollution and Health: A Combined European and North American Approach) study is a collaborative analysis of multicity time-series data on the effect of air pollution on population health, bringing together data from the European APHEA (Air Pollution and Health: A European Approach) and U.S. NMMAPS (National Morbidity, Mortality and Air Pollution Study) projects, along with Canadian data. Objectives The main objective of APHENA was to assess the coherence of the findings of the multicity studies carried out in Europe and North America, when analyzed with a common protocol, and to explore sources of possible heterogeneity. We present APHENA results on the effects of particulate matter (PM) ≤ 10 μm in aerodynamic diameter (PM10) on the daily number of deaths for all ages and for those < 75 and ≥ 75 years of age. We explored the impact of potential environmental and socioeconomic factors that may modify this association. Methods In the first stage of a two-stage analysis, we used Poisson regression models, with natural and penalized splines, to adjust for seasonality, with various degrees of freedom. In the second stage, we used meta-regression approaches to combine time-series results across cites and to assess effect modification by selected ecologic covariates. Results Air pollution risk estimates were relatively robust to different modeling approaches. Risk estimates from Europe and United States were similar, but those from Canada were substantially higher. The combined effect of PM10 on all-cause mortality across all ages for cities with daily air pollution data ranged from 0.2% to 0.6% for a 10-μg/m3 increase in ambient PM10 concentration. Effect modification by other pollutants and climatic variables differed in Europe and the United States. In both of these regions, a higher proportion of older people and higher unemployment were associated with increased air pollution risk. Conclusions Estimates of the increased mortality associated with PM air pollution based on the APHENA study were generally comparable with results of previous reports. Overall, risk estimates were similar in Europe and in the United States but higher in Canada. However, PM10 effect modification patterns were somewhat different in Europe and the United States. PMID:19057700

Efficient Robust Optimization of Metal Forming Processes using a Sequential Metamodel Based Strategy

NASA Astrophysics Data System (ADS)

Wiebenga, J. H.; Klaseboer, G.; van den Boogaard, A. H.

2011-08-01

The coupling of Finite Element (FE) simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a new and generally applicable structured methodology for modeling and solving robust optimization problems. Stochastic design variables or noise variables are taken into account explicitly in the optimization procedure. The metamodel-based strategy is combined with a sequential improvement algorithm to efficiently increase the accuracy of the objective function prediction. This is only done at regions of interest containing the optimal robust design. Application of the methodology to an industrial V-bending process resulted in valuable process insights and an improved robust process design. Moreover, a significant improvement of the robustness (>2σ) was obtained by minimizing the deteriorating effects of several noise variables. The robust optimization results demonstrate the general applicability of the robust optimization strategy and underline the importance of including uncertainty and robustness explicitly in the numerical optimization procedure.

Cell based assays for anti-Plasmodium activity evaluation.

PubMed

Mokgethi-Morule, Thabang; N'Da, David D

2016-03-10

Malaria remains one of the most common and deadly infectious diseases worldwide. The severity of this global public health challenge is reflected by the approximately 198 million people, who were reportedly infected in 2013 and by the more than 584,000 related deaths in that same year. The rising emergence of drug resistance towards the once effective artemisinin combination therapies (ACTs) has become a serious concern and warrants more robust drug development strategies, with the objective of eradicating malaria infections. The intricate biology and life cycle of Plasmodium parasites complicate the understanding of the disease in such a way that would enhance the development of more effective chemotherapies that would achieve radical clinical cure and that would prevent disease relapse. Phenotypic cell based assays have for long been a valuable approach and involve the screening and analysis of diverse compounds with regards to their activities towards whole Plasmodium parasites in vitro. To achieve the Millennium Development Goal (MDG) of malaria eradication by 2020, new generation drugs that are active against all parasite stages (erythrocytic (blood), exo-erythrocytic (liver stages and gametocytes)) are needed. Significant advances are being made in assay development to overcome some of the practical challenges of assessing drug efficacy, particularly in the liver and transmission stage Plasmodium models. This review discusses primary screening models and the fundamental progress being made in whole cell based efficacy screens of anti-malarial activity. Ongoing challenges and some opportunities for improvements in assay development that would assist in the discovery of effective, safe and affordable drugs for malaria treatments are also discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Combining fluorescent in situ hybridization data with ISS staging improves risk assessment in myeloma: an International Myeloma Working Group collaborative project.

PubMed

Avet-Loiseau, H; Durie, B G M; Cavo, M; Attal, M; Gutierrez, N; Haessler, J; Goldschmidt, H; Hajek, R; Lee, J H; Sezer, O; Barlogie, B; Crowley, J; Fonseca, R; Testoni, N; Ross, F; Rajkumar, S V; Sonneveld, P; Lahuerta, J; Moreau, P; Morgan, G

2013-03-01

The combination of serum β2-microglobulin and albumin levels has been shown to be highly prognostic in myeloma as the International Staging System (ISS). The aim of this study was to assess the independent contributions of ISS stage and cytogenetic abnormalities in predicting outcomes. A retrospective analysis of international studies looking at both ISS and cytogenetic abnormalities was performed in order to assess the potential role of combining ISS stage and cytogenetics to predict survival. This international effort used the International Myeloma Working Group database of 12 137 patients treated worldwide for myeloma at diagnosis, of whom 2309 had cytogenetic studies and 5387 had analyses by fluorescent in situ hybridization (iFISH). Comprehensive analyses used 2642 patients with sufficient iFISH data available. Using the comprehensive iFISH data, combining both t(4;14) and deletion (17p), along with ISS stage, significantly improved the prognostic assessment in terms of progression-free survival and overall survival. The additional impact of patient age and use of high-dose therapy was also demonstrated. In conclusion, the combination of iFISH data with ISS staging significantly improves risk assessment in myeloma.

A blood pressure monitor with robust noise reduction system under linear cuff inflation and deflation.

PubMed

Usuda, Takashi; Kobayashi, Naoki; Takeda, Sunao; Kotake, Yoshifumi

2010-01-01

We have developed the non-invasive blood pressure monitor which can measure the blood pressure quickly and robustly. This monitor combines two measurement mode: the linear inflation and the linear deflation. On the inflation mode, we realized a faster measurement with rapid inflation rate. On the deflation mode, we realized a robust noise reduction. When there is neither noise nor arrhythmia, the inflation mode incorporated on this monitor provides precise, quick and comfortable measurement. Once the inflation mode fails to calculate appropriate blood pressure due to body movement or arrhythmia, then the monitor switches automatically to the deflation mode and measure blood pressure by using digital signal processing as wavelet analysis, filter bank, filter combined with FFT and Inverse FFT. The inflation mode succeeded 2440 measurements out of 3099 measurements (79%) in an operating room and a rehabilitation room. The new designed blood pressure monitor provides the fastest measurement for patient with normal circulation and robust measurement for patients with body movement or severe arrhythmia. Also this fast measurement method provides comfortableness for patients.

Habitat heterogeneity hypothesis and edge effects in model metacommunities.

PubMed

Hamm, Michaela; Drossel, Barbara

2017-08-07

Spatial heterogeneity is an inherent property of any living environment and is expected to favour biodiversity due to a broader niche space. Furthermore, edges between different habitats can provide additional possibilities for species coexistence. Using computer simulations, this study examines metacommunities consisting of several trophic levels in heterogeneous environments in order to explore the above hypotheses on a community level. We model heterogeneous landscapes by using two different sized resource pools and evaluate the combined effect of dispersal and heterogeneity on local and regional species diversity. This diversity is obtained by running population dynamics and evaluating the robustness (i.e., the fraction of surviving species). The main results for regional robustness are in agreement with the habitat heterogeneity hypothesis, as the largest robustness is found in heterogeneous systems with intermediate dispersal rates. This robustness is larger than in homogeneous systems with the same total amount of resources. We study the edge effect by arranging the two types of resources in two homogeneous blocks. Different edge responses in diversity are observed, depending on dispersal strength. Local robustness is highest for edge habitats that contain the smaller amount of resource in combination with intermediate dispersal. The results show that dispersal is relevant to correctly identify edge responses on community level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites.

PubMed

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-03-08

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

PubMed Central

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

Diagnostic performance of combined canine and second molar maturity for identification of growth phase.

PubMed

Perinetti, Giuseppe; Di Lenarda, Roberto; Contardo, Luca

2013-05-20

The objective of this research is to analyze the diagnostic performance of the circumpubertal dental maturation stages of the mandibular canine and second molar, as individual teeth and in combination, for the identification of growth phase. A total of 300 healthy subjects, 192 females and 108 males, were enrolled in the study (mean age, 11.4±2.4 years; range, 6.8 to 17.1 years). Dental maturity was assessed through the calcification stages from panoramic radiographs of the mandibular canine and second molar. Determination of growth phase (as pre-pubertal, pubertal, and post-pubertal) was carried out according to the cervical vertebral maturation method. The diagnostic performances of the dental maturation stages, as both individual teeth and in combination, for the identification of the growth phase were evaluated using positive likelihood ratios (LHRs), with a threshold of ≥10 for satisfactory performance. For the individual dental maturation stages, most of these positive LHRs were ≤1.6, with values≥10 seen only for the identification of the pre-pubertal growth phase for canine stage F and second molar stages D and E, and for the post-pubertal growth phase for second molar stage H. All of the combined dental maturation stages yielded positive LHRs up to 2.6. Dental maturation of either individual or combined teeth has little role in the identification of the pubertal growth spurt and should not be used to assess timing for treatments that are required to be performed at this growth phase.

Per- and Polyfluoroalkyl Substances (PFAS): Sampling ...

EPA Pesticide Factsheets

Per- and polyfluoroalkyl substances (PFAS) are a large group of manufactured compounds used in a variety of industries, such as aerospace, automotive, textiles, and electronics, and are used in some food packaging and firefighting materials. For example, they may be used to make products more resistant to stains, grease and water. In the environment, some PFAS break down very slowly, if at all, allowing bioaccumulation (concentration) to occur in humans and wildlife. Some have been found to be toxic to laboratory animals, producing reproductive, developmental, and systemic effects in laboratory tests. EPA's methods for analyzing PFAS in environmental media are in various stages of development. This technical brief summarizes the work being done to develop robust analytical methods for groundwater, surface water, wastewater, and solids, including soils, sediments, and biosolids. The U.S. Environmental Protection Agency’s (EPA) methods for analyzing PFAS in environmental media are in various stages of development. EPA is working to develop robust analytical methods for groundwater, surface water, wastewater, and solids, including soils, sediments, and biosolids.

A feedback control for the advanced launch system

NASA Technical Reports Server (NTRS)

Seywald, Hans; Cliff, Eugene M.

1991-01-01

A robust feedback algorithm is presented for a near-minimum-fuel ascent of a two-stage launch vehicle operating in the equatorial plane. The development of the algorithm is based on the ideas of neighboring optimal control and can be derived into three phases. In phase 1, the formalism of optimal control is employed to calculate fuel-optimal ascent trajectories for a simple point-mass model. In phase 2, these trajectories are used to numerically calculate gain functions of time for the control(s), the total flight time, and possibly, for other variables of interest. In phase 3, these gains are used to determine feedback expressions for the controls associated with a more realistic model of a launch vehicle. With the Advanced Launch System in mind, all calculations are performed on a two-stage vehicle with fixed thrust history, but this restriction is by no means important for the approach taken. Performance and robustness of the algorithm is found to be excellent.

A Robust High-Performance GPS L1 Receiver with Single-stage Quadrature Redio-Frequency Circuit

NASA Astrophysics Data System (ADS)

Liu, Jianghua; Xu, Weilin; Wan, Qinq; Liu, Tianci

2018-03-01

A low power current reuse single-stage quadrature raido-frequency part (SQRF) is proposed for GPS L1 receiver in 180nm CMOS process. The proposed circuit consists of LNA, Mixer, QVCO, is called the QLMV cell. A two blocks stacked topology is adopted in this design. The parallel QVCO and mixer placed on the top forms the upper stacked block, and the LNA placed on the bottom forms the other stacked block. The two blocks share the current and achieve low power performance. To improve the stability, a float current source is proposed. The float current isolated the local oscillation signal and the input RF signal, which bring the whole circuit robust high-performance. The result shows conversion gain is 34 dB, noise figure is three dB, the phase noise is -110 dBc/Hz at 1MHz and IIP3 is -20 dBm. The proposed circuit dissipated 1.7mW with 1 V supply voltage.

Feedforward control of a closed-loop piezoelectric translation stage for atomic force microscope.

PubMed

Li, Yang; Bechhoefer, John

2007-01-01

Simple feedforward ideas are shown to lead to a nearly tenfold increase in the effective bandwidth of a closed-loop piezoelectric positioning stage used in scanning probe microscopy. If the desired control signal is known in advance, the feedforward filter can be acausal: the information about the future can be used to make the output of the stage have almost no phase lag with respect to the input. This keeps in register the images assembled from right and left scans. We discuss the design constraints imposed by the need for the feedforward filter to work robustly under a variety of circumstances. Because the feedforward needs only to modify the input signal, it can be added to any piezoelectric stage, whether closed or open loop.

Stages as models of scene geometry.

PubMed

Nedović, Vladimir; Smeulders, Arnold W M; Redert, André; Geusebroek, Jan-Mark

2010-09-01

Reconstruction of 3D scene geometry is an important element for scene understanding, autonomous vehicle and robot navigation, image retrieval, and 3D television. We propose accounting for the inherent structure of the visual world when trying to solve the scene reconstruction problem. Consequently, we identify geometric scene categorization as the first step toward robust and efficient depth estimation from single images. We introduce 15 typical 3D scene geometries called stages, each with a unique depth profile, which roughly correspond to a large majority of broadcast video frames. Stage information serves as a first approximation of global depth, narrowing down the search space in depth estimation and object localization. We propose different sets of low-level features for depth estimation, and perform stage classification on two diverse data sets of television broadcasts. Classification results demonstrate that stages can often be efficiently learned from low-dimensional image representations.

Combining heterogenous features for 3D hand-held object recognition

NASA Astrophysics Data System (ADS)

Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

2014-10-01

Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

Generation of functional podocytes from human induced pluripotent stem cells.

PubMed

Ciampi, Osele; Iacone, Roberto; Longaretti, Lorena; Benedetti, Valentina; Graf, Martin; Magnone, Maria Chiara; Patsch, Christoph; Xinaris, Christodoulos; Remuzzi, Giuseppe; Benigni, Ariela; Tomasoni, Susanna

2016-07-01

Generating human podocytes in vitro could offer a unique opportunity to study human diseases. Here, we describe a simple and efficient protocol for obtaining functional podocytes in vitro from human induced pluripotent stem cells. Cells were exposed to a three-step protocol, which induced their differentiation into intermediate mesoderm, then into nephron progenitors and, finally, into mature podocytes. After differentiation, cells expressed the main podocyte markers, such as synaptopodin, WT1, α-Actinin-4, P-cadherin and nephrin at the protein and mRNA level, and showed the low proliferation rate typical of mature podocytes. Exposure to Angiotensin II significantly decreased the expression of podocyte genes and cells underwent cytoskeleton rearrangement. Cells were able to internalize albumin and self-assembled into chimeric 3D structures in combination with dissociated embryonic mouse kidney cells. Overall, these findings demonstrate the establishment of a robust protocol that, mimicking developmental stages, makes it possible to derive functional podocytes in vitro. Copyright © 2016. Published by Elsevier B.V.

Influence Function Learning in Information Diffusion Networks.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-06-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data.

Clairvoyant fusion: a new methodology for designing robust detection algorithms

NASA Astrophysics Data System (ADS)

Schaum, Alan

2016-10-01

Many realistic detection problems cannot be solved with simple statistical tests for known alternative probability models. Uncontrollable environmental conditions, imperfect sensors, and other uncertainties transform simple detection problems with likelihood ratio solutions into composite hypothesis (CH) testing problems. Recently many multi- and hyperspectral sensing CH problems have been addressed with a new approach. Clairvoyant fusion (CF) integrates the optimal detectors ("clairvoyants") associated with every unspecified value of the parameters appearing in a detection model. For problems with discrete parameter values, logical rules emerge for combining the decisions of the associated clairvoyants. For many problems with continuous parameters, analytic methods of CF have been found that produce closed-form solutions-or approximations for intractable problems. Here the principals of CF are reviewed and mathematical insights are described that have proven useful in the derivation of solutions. It is also shown how a second-stage fusion procedure can be used to create theoretically superior detection algorithms for ALL discrete parameter problems.

Binary classification of aqueous solubility using support vector machines with reduction and recombination feature selection.

PubMed

Cheng, Tiejun; Li, Qingliang; Wang, Yanli; Bryant, Stephen H

2011-02-28

Aqueous solubility is recognized as a critical parameter in both the early- and late-stage drug discovery. Therefore, in silico modeling of solubility has attracted extensive interests in recent years. Most previous studies have been limited in using relatively small data sets with limited diversity, which in turn limits the predictability of derived models. In this work, we present a support vector machines model for the binary classification of solubility by taking advantage of the largest known public data set that contains over 46 000 compounds with experimental solubility. Our model was optimized in combination with a reduction and recombination feature selection strategy. The best model demonstrated robust performance in both cross-validation and prediction of two independent test sets, indicating it could be a practical tool to select soluble compounds for screening, purchasing, and synthesizing. Moreover, our work may be used for comparative evaluation of solubility classification studies ascribe to the use of completely public resources.

From dots to doughnuts: Two-dimensionally confined deposition of polyelectrolytes on block copolymer templates

DOE PAGES

Oded, Meirav; Kelly, Stephen T.; Gilles, Mary K.; ...

2016-07-05

The combination of block copolymer templating with electrostatic self-assembly provides a simple and robust method for creating nano-patterned polyelectrolyte multilayers over large areas. The deposition of the first polyelectrolyte layer provides important insights on the initial stages of multilayer buildup. Here, we focus on two-dimensionally confined “dots” patterns afforded by block copolymer films featuring hexagonally-packed cylinders that are oriented normal to the substrate. Rendering the cylinder caps positively charged enables the selective deposition of negatively charged polyelectrolytes on them under salt-free conditions. The initially formed polyelectrolyte nanostructures adopt a toroidal (“doughnut”) shape, which results from retraction of dangling polyelectrolyte segmentsmore » into the “dots” upon drying. With increasing exposure time to the polyelectrolyte solution, the final shape of the deposited polyelectrolyte transitions from a doughnut to a hemisphere. In conclusion, these insights would enable the creation of patterned polyelectrolyte multilayers with increased control over adsorption selectivity of the additional incoming polyelectrolytes.« less

From dots to doughnuts: Two-dimensionally confined deposition of polyelectrolytes on block copolymer templates

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

Oded, Meirav; Kelly, Stephen T.; Gilles, Mary K.

The combination of block copolymer templating with electrostatic self-assembly provides a simple and robust method for creating nano-patterned polyelectrolyte multilayers over large areas. The deposition of the first polyelectrolyte layer provides important insights on the initial stages of multilayer buildup. Here, we focus on two-dimensionally confined “dots” patterns afforded by block copolymer films featuring hexagonally-packed cylinders that are oriented normal to the substrate. Rendering the cylinder caps positively charged enables the selective deposition of negatively charged polyelectrolytes on them under salt-free conditions. The initially formed polyelectrolyte nanostructures adopt a toroidal (“doughnut”) shape, which results from retraction of dangling polyelectrolyte segmentsmore » into the “dots” upon drying. With increasing exposure time to the polyelectrolyte solution, the final shape of the deposited polyelectrolyte transitions from a doughnut to a hemisphere. In conclusion, these insights would enable the creation of patterned polyelectrolyte multilayers with increased control over adsorption selectivity of the additional incoming polyelectrolytes.« less

Fluorescence Imaging of Posterior Spiracles from Second and Third Instars of Forensically-important Chrysomya rufifacies (Diptera: Calliphoridae)*

PubMed Central

Flores, Danielle; Miller, Amy L.; Showman, Angelique; Tobita, Caitlyn; Shimoda, Lori M.N.; Sung, Carl; Stokes, Alexander J.; Tomberlin, Jeffrey K.; Carter, David O.; Turner, Helen

2016-01-01

Entomological protocols for aging blow fly (Diptera: Calliphoridae) larvae to estimate the time of colonization (TOC) are commonly used to assist in death investigations. While the methodologies for analysing fly larvae differ, most rely on light microscopy, genetic analysis or, more rarely, electron microscopy. This pilot study sought to improve resolution of larval stage in the forensically-important blow fly Chrysomya rufifacies using high-content fluorescence microscopy and biochemical measures of developmental marker proteins. We established fixation and mounting protocols, defined a set of measurable morphometric criteria and captured developmental transitions of 2nd instar to 3rd instar using both fluorescence microscopy and anti-ecdysone receptor Western blot analysis. The data show that these instars can be distinguished on the basis of robust, non-bleaching, autofluorescence of larval posterior spiracles. High content imaging techniques using confocal microscopy, combined with morphometric and biochemical techniques, may therefore aid forensic entomologists in estimating TOC. PMID:27706817

Quadratic Programming for Allocating Control Effort

NASA Technical Reports Server (NTRS)

Singh, Gurkirpal

2005-01-01

A computer program calculates an optimal allocation of control effort in a system that includes redundant control actuators. The program implements an iterative (but otherwise single-stage) algorithm of the quadratic-programming type. In general, in the quadratic-programming problem, one seeks the values of a set of variables that minimize a quadratic cost function, subject to a set of linear equality and inequality constraints. In this program, the cost function combines control effort (typically quantified in terms of energy or fuel consumed) and control residuals (differences between commanded and sensed values of variables to be controlled). In comparison with prior control-allocation software, this program offers approximately equal accuracy but much greater computational efficiency. In addition, this program offers flexibility, robustness to actuation failures, and a capability for selective enforcement of control requirements. The computational efficiency of this program makes it suitable for such complex, real-time applications as controlling redundant aircraft actuators or redundant spacecraft thrusters. The program is written in the C language for execution in a UNIX operating system.

Towards the Development of THz-Sensors for the Detection of African Trypanosomes

NASA Astrophysics Data System (ADS)

Knieß, Robert; Wagner, Carolin B.; Ulrich Göringer, H.; Mueh, Mario; Damm, Christian; Sawallich, Simon; Chmielak, Bartos; Plachetka, Ulrich; Lemme, Max

2018-03-01

Human African trypanosomiasis (HAT) is a neglected tropical disease (NTD) for which adequate therapeutic and diagnostic measures are still lacking. Causative agent of HAT is the African trypanosome, a single-cell parasite, which propagates in the blood and cerebrospinal fluid of infected patients. Although different testing methods for the pathogen exist, none is robust, reliable and cost-efficient enough to support large-scale screening and control programs. Here we propose the design of a new sensor-type for the detection of infective-stage trypanosomes. The sensor exploits the highly selective binding capacity of nucleic acid aptamers to the surface of the parasite in combination with passive sensor structures to allow an electromagnetic remote read-out using terahertz (THz)-radiation. The short wavelength provides a superior interaction with the parasite cells than longer wavelengths, which is essential for a high sensitivity. We present two different sensor structures using both, micro- and nano-scale elements, as well as different measurement principles.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

2001-03-01

This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies.

PubMed

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-11-01

Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

Processing and Properties of Fiber Reinforced Polymeric Matrix Composites. Part 2; Processing Robustness of IM7/PETI Polyimide Composites

NASA Technical Reports Server (NTRS)

Hou, Tan-Hung

1996-01-01

The processability of a phenylethynyl terminated imide (PETI) resin matrix composite was investigated. Unidirectional prepregs were made by coating an N-methylpyrrolidone solution of the amide acid oligomer onto unsized IM7. Two batches of prepregs were used: one was made by NASA in-house, and the other was from an industrial source. The composite processing robustness was investigated with respect to the effect of B-staging conditions, the prepreg shelf life, and the optimal processing window. Rheological measurements indicated that PETI's processability was only slightly affected over a wide range of B-staging temperatures (from 250 C to 300 C). The open hole compression (OHC) strength values were statistically indistinguishable among specimens consolidated using various B-staging conditions. Prepreg rheology and OHC strengths were also found not to be affected by prolonged (i.e., up to 60 days) ambient storage. An optimal processing window was established using response surface methodology. It was found that IM7/PETI composite is more sensitive to the consolidation temperature than to the consolidation pressure. A good consolidation was achievable at 371 C/100 Psi, which yielded an OHC strength of 62 Ksi at room temperature. However, processability declined dramatically at temperatures below 350 C.

Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects.

PubMed

Schwaibold, M; Schöchlin, J; Bolz, A

2002-01-01

For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems. Methodological aspects were assessed to attain optimum performance and maximum transparency for the user. Due to their effective and robust learning behavior, artificial neural networks could be recommended for pattern recognition, while neuro-fuzzy systems performed best for the processing of contextual information.

Automatic segmentation of bones from digital hand radiographs

NASA Astrophysics Data System (ADS)

Liu, Brent J.; Taira, Ricky K.; Shim, Hyeonjoon; Keaton, Patricia

1995-05-01

The purpose of this paper is to develop a robust and accurate method that automatically segments phalangeal and epiphyseal bones from digital pediatric hand radiographs exhibiting various stages of growth. The algorithm uses an object-oriented approach comprising several stages beginning with the most general objects to be segmented, such as the outline of the hand from background, and proceeding in a succession of stages to the most specific object, such as a specific phalangeal bone from a digit of the hand. Each stage carries custom operators unique to the needs of that specific stage which will aid in more accurate results. The method is further aided by a knowledge base where all model contours and other information such as age, race, and sex, are stored. Shape models, 1-D wrist profiles, as well as an interpretation tree are used to map model and data contour segments. Shape analysis is performed using an arc-length orientation transform. The method is tested on close to 340 phalangeal and epiphyseal objects to be segmented from 17 cases of pediatric hand images obtained from our clinical PACS. Patient age ranges from 2 - 16 years. A pediatric radiologist preliminarily assessed the results of the object contours and were found to be accurate to within 95% for cases with non-fused bones and to within 85% for cases with fused bones. With accurate and robust results, the method can be applied toward areas such as the determination of bone age, the development of a normal hand atlas, and the characterization of many congenital and acquired growth diseases. Furthermore, this method's architecture can be applied to other image segmentation problems.

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.

Computational fluid dynamics applications to improve crop production systems

USDA-ARS?s Scientific Manuscript database

Computational fluid dynamics (CFD), numerical analysis and simulation tools of fluid flow processes have emerged from the development stage and become nowadays a robust design tool. It is widely used to study various transport phenomena which involve fluid flow, heat and mass transfer, providing det...

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions.

PubMed

Fox, Naomi J; Marion, Glenn; Davidson, Ross S; White, Piran C L; Hutchings, Michael R

2012-03-06

Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery

PubMed Central

Taravat, Alireza; Oppelt, Natascha

2014-01-01

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376

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.

Single-stage evaluation of highly-loaded high-Mach-number compressor stages 5. Data and performance of baseline, corner-blow wall suction and combined corner blow wall suction stator

NASA Technical Reports Server (NTRS)

Nikkanen, J. P.; Brooky, J. P.

1972-01-01

A single-stage compressor with a rotor tip speed of 1600 ft/sec and a 0.5 hub tip ratio was used to investigate the effects of several stator endwall treatment methods on stage range and performance. These endwall treatment methods consisted of stator corner-blow, annular wall suction upstream of stator leading edge, and combined corner-blow and annular wall suction. The overall stage performance with corner blow was essentially the same as the baseline performance. The performance for the annular wall suction and the combined corner-blow and wall suction showed a reduction in peak efficiency of 2.5 percentage points compared to the baseline data.

Flexible transparent aerogels as window retrofitting films and optical elements with tunable birefringence

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

Liu, Qingkun; Frazier, Allister W.; Zhao, Xinpeng

Experimental realization of optically transparent, mechanically robust and flexible aerogels has been a longstanding challenge, which limits their practical applications in energy-saving devices, such as thermally insulating films for enhancing energy efficiency of windows. The poor transparency precluded even hypothetical consideration of the possibility of birefringent aerogels. We develop birefringent and optically isotropic aerogels that combine properties of thermal super-insulation, mechanical robustness and flexibility, and transparency to visible-spectrum light. This unusual combination of physical properties is achieved by combining liquid crystalline self-organization of cellulose nanofibers with polysiloxane cross-linking and control of the nanoscale porosity to form hybrid organic-inorganic mesostructured aerogels.more » Potential applications of these inexpensive materials range from single pane window retrofitting to smart fabrics.« less

Memorial familiarity remains intact for pictures but not for words in patients with amnestic mild cognitive impairment.

PubMed

Embree, Lindsay M; Budson, Andrew E; Ally, Brandon A

2012-07-01

Understanding how memory breaks down in the earliest stages of Alzheimer's disease (AD) process has significant implications, both clinically and with respect to intervention development. Previous work has highlighted a robust picture superiority effect in patients with amnestic mild cognitive impairment (aMCI). However, it remains unclear as to how pictures improve memory compared to words in this patient population. In the current study, we utilized receiver operating characteristic (ROC) curves to obtain estimates of familiarity and recollection for pictures and words in patients with aMCI and healthy older controls. Analysis of accuracy shows that even when performance is matched between pictures and words in the healthy control group, patients with aMCI continue to show a significant picture superiority effect. The results of the ROC analysis showed that patients demonstrated significantly impaired recollection and familiarity for words compared controls. In contrast, patients with aMCI demonstrated impaired recollection, but intact familiarity for pictures, compared to controls. Based on previous work from our lab, we speculate that patients can utilize the rich conceptual information provided by pictures to enhance familiarity, and perceptual information may allow for post-retrieval monitoring or verification of the enhanced sense of familiarity. Alternatively, the combination of enhanced conceptual and perceptual fluency of the test item might drive a stronger or more robust sense of familiarity that can be accurately attributed to a studied item. Copyright © 2012 Elsevier Ltd. All rights reserved.

Memorial familiarity remains intact for pictures but not for words in patients with amnestic mild cognitive impairment

PubMed Central

Embree, Lindsay M.; Budson, Andrew E.; Ally, Brandon A.

2012-01-01

Understanding how memory breaks down in the earliest stages of the Alzheimer’s disease (AD) process has significant implications, both clinically and with respect to intervention development. Previous work has highlighted a robust picture superiority effect in patients with amnestic mild cognitive impairment (aMCI). However, it remains unclear as to how pictures improve memory compared to words in this patient population. In the current study, we utilized receiver operating characteristic (ROC) curves to obtain estimates of familiarity and recollection for pictures and words in patients with aMCI and healthy older controls. Analysis of accuracy shows that even when performance is matched between pictures and words in the healthy control group, patients with aMCI continue to show a significant picture superiority effect. The results of the ROC analysis showed that patients demonstrated significantly impaired recollection and familiarity for words compared controls. In contrast, patients with aMCI demonstrated impaired recollection, but intact familiarity for pictures, compared to controls. Based on previous work from our lab, we speculate that patients can utilize the rich conceptual information provided by pictures to enhance familiarity, and perceptual information may allow for post-retrieval monitoring or verification of the enhanced sense of familiarity. Alternatively, the combination of enhanced conceptual and perceptual fluency of the test item might drive a stronger or more robust sense of familiarity that can be accurately attributed to a studied item. PMID:22705441

Hybrid DG/FV schemes for magnetohydrodynamics and relativistic hydrodynamics

NASA Astrophysics Data System (ADS)

Núñez-de la Rosa, Jonatan; Munz, Claus-Dieter

2018-01-01

This paper presents a high order hybrid discontinuous Galerkin/finite volume scheme for solving the equations of the magnetohydrodynamics (MHD) and of the relativistic hydrodynamics (SRHD) on quadrilateral meshes. In this approach, for the spatial discretization, an arbitrary high order discontinuous Galerkin spectral element (DG) method is combined with a finite volume (FV) scheme in order to simulate complex flow problems involving strong shocks. Regarding the time discretization, a fourth order strong stability preserving Runge-Kutta method is used. In the proposed hybrid scheme, a shock indicator is computed at the beginning of each Runge-Kutta stage in order to flag those elements containing shock waves or discontinuities. Subsequently, the DG solution in these troubled elements and in the current time step is projected onto a subdomain composed of finite volume subcells. Right after, the DG operator is applied to those unflagged elements, which, in principle, are oscillation-free, meanwhile the troubled elements are evolved with a robust second/third order FV operator. With this approach we are able to numerically simulate very challenging problems in the context of MHD and SRHD in one, and two space dimensions and with very high order polynomials. We make convergence tests and show a comprehensive one- and two dimensional testbench for both equation systems, focusing in problems with strong shocks. The presented hybrid approach shows that numerical schemes of very high order of accuracy are able to simulate these complex flow problems in an efficient and robust manner.

Energy metabolic reprogramming in the hypertrophied and early stage failing heart: a multisystems approach.

PubMed

Lai, Ling; Leone, Teresa C; Keller, Mark P; Martin, Ola J; Broman, Aimee T; Nigro, Jessica; Kapoor, Kapil; Koves, Timothy R; Stevens, Robert; Ilkayeva, Olga R; Vega, Rick B; Attie, Alan D; Muoio, Deborah M; Kelly, Daniel P

2014-11-01

An unbiased systems approach was used to define energy metabolic events that occur during the pathological cardiac remodeling en route to heart failure (HF). Combined myocardial transcriptomic and metabolomic profiling were conducted in a well-defined mouse model of HF that allows comparative assessment of compensated and decompensated (HF) forms of cardiac hypertrophy because of pressure overload. The pressure overload data sets were also compared with the myocardial transcriptome and metabolome for an adaptive (physiological) form of cardiac hypertrophy because of endurance exercise training. Comparative analysis of the data sets led to the following conclusions: (1) expression of most genes involved in mitochondrial energy transduction were not significantly changed in the hypertrophied or failing heart, with the notable exception of a progressive downregulation of transcripts encoding proteins and enzymes involved in myocyte fatty acid transport and oxidation during the development of HF; (2) tissue metabolite profiles were more broadly regulated than corresponding metabolic gene regulatory changes, suggesting significant regulation at the post-transcriptional level; (3) metabolomic signatures distinguished pathological and physiological forms of cardiac hypertrophy and served as robust markers for the onset of HF; and (4) the pattern of metabolite derangements in the failing heart suggests bottlenecks of carbon substrate flux into the Krebs cycle. Mitochondrial energy metabolic derangements that occur during the early development of pressure overload-induced HF involve both transcriptional and post-transcriptional events. A subset of the myocardial metabolomic profile robustly distinguished pathological and physiological cardiac remodeling. © 2014 American Heart Association, Inc.

Multisensory integration in early vestibular processing in mice: the encoding of passive vs. active motion

PubMed Central

Medrea, Ioana

2013-01-01

The mouse has become an important model system for studying the cellular basis of learning and coding of heading by the vestibular system. Here we recorded from single neurons in the vestibular nuclei to understand how vestibular pathways encode self-motion under natural conditions, during which proprioceptive and motor-related signals as well as vestibular inputs provide feedback about an animal's movement through the world. We recorded neuronal responses in alert behaving mice focusing on a group of neurons, termed vestibular-only cells, that are known to control posture and project to higher-order centers. We found that the majority (70%, n = 21/30) of neurons were bimodal, in that they responded robustly to passive stimulation of proprioceptors as well as passive stimulation of the vestibular system. Additionally, the linear summation of a given neuron's vestibular and neck sensitivities predicted well its responses when both stimuli were applied simultaneously. In contrast, neuronal responses were suppressed when the same motion was actively generated, with the one striking exception that the activity of bimodal neurons similarly and robustly encoded head on body position in all conditions. Our results show that proprioceptive and motor-related signals are combined with vestibular information at the first central stage of vestibular processing in mice. We suggest that these results have important implications for understanding the multisensory integration underlying accurate postural control and the neural representation of directional heading in the head direction cell network of mice. PMID:24089394

Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso; Elena, Santiago F

2009-01-01

Background Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes. Results We show that the A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feed-forward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures. Conclusions These data suggest that A. thaliana has evolved high connectivity in terms of transcriptional regulation among cellular functions involved in response and adaptation to changing environments, while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this eukaryote. PMID:19754933

Consensus between Pipelines in Structural Brain Networks

PubMed Central

Parker, Christopher S.; Deligianni, Fani; Cardoso, M. Jorge; Daga, Pankaj; Modat, Marc; Dayan, Michael; Clark, Chris A.

2014-01-01

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. PMID:25356977

The Spatial Footprint of Natural Gas-Fired Electricity

NASA Astrophysics Data System (ADS)

Jordaan, S. M.; Heath, G.; Macknick, J.; Mohammadi, E.; Ben-Horin, D.; Urrea, V.; Marceau, D.

2015-12-01

Consistent comparisons of the amount of land required for different electricity generation technologies are challenging because land use associated with fossil fuel acquisition and delivery has not been well characterized or empirically grounded. This research focuses on improving estimates of the life cycle land use of natural gas-fired electricity (m2/MWh generated) through the novel combination of inventories of natural gas-related infrastructure, satellite imagery analysis and gas production estimates. We focus on seven counties that represent 98% of the total gas production in the Barnett Shale (Texas), evaluating over 500 sites across five life cycle stages (gas production, gathering, processing, transmission, and power generation as well as produced water disposal). We find that a large fraction of total life cycle land use is related to gathering (midstream) infrastructure, particularly pipelines; access roads related to all stages also contribute a large life cycle share. Results were sensitive to several inputs, including well lifetime, pipeline right of way, number of wells per site, variability of heat rate for electricity generation, and facility lifetime. Through this work, we have demonstrated a novel, highly-resolved and empirical method for estimating life cycle land use from natural gas infrastructure in an important production region. When replicated for other gas production regions and other fuels, the results can enable more empirically-grounded and robust comparisons of the land footprint of alternative energy choices.

Strategy for design NIR calibration sets based on process spectrum and model space: An innovative approach for process analytical technology.

PubMed

Cárdenas, V; Cordobés, M; Blanco, M; Alcalà, M

2015-10-10

The pharmaceutical industry is under stringent regulations on quality control of their products because is critical for both, productive process and consumer safety. According to the framework of "process analytical technology" (PAT), a complete understanding of the process and a stepwise monitoring of manufacturing are required. Near infrared spectroscopy (NIRS) combined with chemometrics have lately performed efficient, useful and robust for pharmaceutical analysis. One crucial step in developing effective NIRS-based methodologies is selecting an appropriate calibration set to construct models affording accurate predictions. In this work, we developed calibration models for a pharmaceutical formulation during its three manufacturing stages: blending, compaction and coating. A novel methodology is proposed for selecting the calibration set -"process spectrum"-, into which physical changes in the samples at each stage are algebraically incorporated. Also, we established a "model space" defined by Hotelling's T(2) and Q-residuals statistics for outlier identification - inside/outside the defined space - in order to select objectively the factors to be used in calibration set construction. The results obtained confirm the efficacy of the proposed methodology for stepwise pharmaceutical quality control, and the relevance of the study as a guideline for the implementation of this easy and fast methodology in the pharma industry. Copyright © 2015 Elsevier B.V. All rights reserved.

Multifidelity, multidisciplinary optimization of turbomachines with shock interaction

NASA Astrophysics Data System (ADS)

Joly, Michael Marie

Research on high-speed air-breathing propulsion aims at developing aircraft with antipodal range and space access. Before reaching high speed at high altitude, the flight vehicle needs to accelerate from takeoff to scramjet takeover. Air turbo rocket engines combine turbojet and rocket engine cycles to provide the necessary thrust in the so-called low-speed regime. Challenges related to turbomachinery components are multidisciplinary, since both the high compression ratio compressor and the powering high-pressure turbine operate in the transonic regime in compact environments with strong shock interactions. Besides, lightweight is vital to avoid hindering the scramjet operation. Recent progress in evolutionary computing provides aerospace engineers with robust and efficient optimization algorithms to address concurrent objectives. The present work investigates Multidisciplinary Design Optimization (MDO) of innovative transonic turbomachinery components. Inter-stage aerodynamic shock interaction in turbomachines are known to generate high-cycle fatigue on the rotor blades compromising their structural integrity. A soft-computing strategy is proposed to mitigate the vane downstream distortion, and shown to successfully attenuate the unsteady forcing on the rotor of a high-pressure turbine. Counter-rotation offers promising prospects to reduce the weight of the machine, with fewer stages and increased load per row. An integrated approach based on increasing level of fidelity and aero-structural coupling is then presented and allows achieving a highly loaded compact counter-rotating compressor.

Ensemble Sparse Classification of Alzheimer’s Disease

PubMed Central

Liu, Manhua; Zhang, Daoqiang; Shen, Dinggang

2012-01-01

The high-dimensional pattern classification methods, e.g., support vector machines (SVM), have been widely investigated for analysis of structural and functional brain images (such as magnetic resonance imaging (MRI)) to assist the diagnosis of Alzheimer’s disease (AD) including its prodromal stage, i.e., mild cognitive impairment (MCI). Most existing classification methods extract features from neuroimaging data and then construct a single classifier to perform classification. However, due to noise and small sample size of neuroimaging data, it is challenging to train only a global classifier that can be robust enough to achieve good classification performance. In this paper, instead of building a single global classifier, we propose a local patch-based subspace ensemble method which builds multiple individual classifiers based on different subsets of local patches and then combines them for more accurate and robust classification. Specifically, to capture the local spatial consistency, each brain image is partitioned into a number of local patches and a subset of patches is randomly selected from the patch pool to build a weak classifier. Here, the sparse representation-based classification (SRC) method, which has shown effective for classification of image data (e.g., face), is used to construct each weak classifier. Then, multiple weak classifiers are combined to make the final decision. We evaluate our method on 652 subjects (including 198 AD patients, 225 MCI and 229 normal controls) from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using MR images. The experimental results show that our method achieves an accuracy of 90.8% and an area under the ROC curve (AUC) of 94.86% for AD classification and an accuracy of 87.85% and an AUC of 92.90% for MCI classification, respectively, demonstrating a very promising performance of our method compared with the state-of-the-art methods for AD/MCI classification using MR images. PMID:22270352

Oblimersen Sodium and Combination Chemotherapy in Treating Patients With Newly Diagnosed Stage I, Stage II, Stage III, or Stage IV Diffuse Large B-Cell Lymphoma

ClinicalTrials.gov

2012-10-11

Contiguous Stage II Adult Diffuse Large Cell Lymphoma; Noncontiguous Stage II Adult Diffuse Large Cell Lymphoma; Stage I Adult Diffuse Large Cell Lymphoma; Stage III Adult Diffuse Large Cell Lymphoma; Stage IV Adult Diffuse Large Cell Lymphoma

[Mechanisms for the increased fertilizer nitrogen use efficiency of rice in wheat-rice rotation system under combined application of inorganic and organic fertilizers].

PubMed

Liu, Yi-Ren; Li, Xiang; Yu, Jie; Shen, Qi-Rong; Xu, Yang-Chun

2012-01-01

A pot experiment was conducted to study the effects of combined application of organic and inorganic fertilizers on the nitrogen uptake by rice and the nitrogen supply by soil in a wheat-rice rotation system, and approach the mechanisms for the increased fertilizer nitrogen use efficiency of rice under the combined fertilization from the viewpoint of microbiology. Comparing with applying inorganic fertilizers, combined application of organic and inorganic fertilizers decreased the soil microbial biomass carbon and nitrogen and soil mineral nitrogen contents before tillering stage, but increased them significantly from heading to filling stage. Under the combined fertilization, the dynamics of soil nitrogen supply matched best the dynamics of rice nitrogen uptake and utilization, which promoted the nitrogen accumulation in rice plant and the increase of rice yield and biomass, and increased the fertilizer nitrogen use efficiency of rice significantly. Combined application of inorganic and organic fertilizers also promoted the propagation of soil microbes, and consequently, more mineral nitrogen in soil was immobilized by the microbes at rice early growth stage, and the immobilized nitrogen was gradually released at the mid and late growth stages of rice, being able to better satisfy the nitrogen demand of rice in its various growth and development stages.

Optimality, sample size, and power calculations for the sequential parallel comparison design.

PubMed

Ivanova, Anastasia; Qaqish, Bahjat; Schoenfeld, David A

2011-10-15

The sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials in therapeutic areas where high-placebo response is a concern. The trial is run in two stages, and subjects are randomized into three groups: (i) placebo in both stages; (ii) placebo in the first stage and drug in the second stage; and (iii) drug in both stages. We consider the case of binary response data (response/no response). In the SPCD, all first-stage and second-stage data from placebo subjects who failed to respond in the first stage of the trial are utilized in the efficacy analysis. We develop 1 and 2 degree of freedom score tests for treatment effect in the SPCD. We give formulae for asymptotic power and for sample size computations and evaluate their accuracy via simulation studies. We compute the optimal allocation ratio between drug and placebo in stage 1 for the SPCD to determine from a theoretical viewpoint whether a single-stage design, a two-stage design with placebo only in the first stage, or a two-stage design is the best design for a given set of response rates. As response rates are not known before the trial, a two-stage approach with allocation to active drug in both stages is a robust design choice. Copyright © 2011 John Wiley & Sons, Ltd.

Application of Boston matrix combined with SWOT analysis on operational development and evaluations of hospital development.

PubMed

Tao, Z-Q; Shi, A-M

2016-05-01

The aim of this study is to explore the application of Boston matrix combined with SWOT analysis on operational development and evaluations of hospital departments. We selected 73 clinical and medical technology departments of our hospital from 2011 to 2013, and evaluated our hospital by Boston matrix combined with SWOT analysis according to the volume of services, medical quality, work efficiency, patients' evaluations, development capacity, operational capability, economic benefits, comprehensive evaluation of hospital achievement, innovation ability of hospital, influence of hospital, human resources of hospital, health insurance costs, etc. It was found that among clinical departments, there were 11 in Stars (22.4%), 17 in cash cow (34.7%), 15 in question marks (31.2%), 6 Dogs (12.2%), 16 in the youth stage of life cycle assessment (27.6%), 14 in the prime stage (24.1%), 12 in the stationary stage (20.7%), 9 in the aristocracy stage (15.5%) and 7 in the recession stage (12.1%). Among medical technology departments, there were 5 in Stars (20.8%), 1 in Cash cow (4.2%), 10 in question marks (41.6%), 8 Dogs (29.1%), 9 in the youth stage of life cycle assessment (37.5%), 4 in the prime stage (16.7%), 4 in the stable stage (16.7%), 1 in the aristocracy stage (4.2%) and 6 in the recession stage (25%). In conclusion, Boston matrix combined with SWOT analysis is suitable for operational development and comprehensive evaluations of hospital development, and it plays an important role in providing hospitals with development strategies.

Early, Equivalent ERP Masked Priming Effects for Regular and Irregular Morphology

ERIC Educational Resources Information Center

Morris, Joanna; Stockall, Linnaea

2012-01-01

Converging evidence from behavioral masked priming (Rastle & Davis, 2008), EEG masked priming (Morris, Frank, Grainger, & Holcomb, 2007) and single word MEG (Zweig & Pylkkanen, 2008) experiments has provided robust support for a model of lexical processing which includes an early, automatic, visual word form based stage of morphological parsing…

Adding flexibility to the search for robust portfolios in non-linear water resource planning

NASA Astrophysics Data System (ADS)

Tomlinson, James; Harou, Julien

2017-04-01

To date robust optimisation of water supply systems has sought to find portfolios or strategies that are robust to a range of uncertainties or scenarios. The search for a single portfolio that is robust in all scenarios is necessarily suboptimal compared to portfolios optimised for a single scenario deterministic future. By contrast establishing a separate portfolio for each future scenario is unhelpful to the planner who must make a single decision today under deep uncertainty. In this work we show that a middle ground is possible by allowing a small number of different portfolios to be found that are each robust to a different subset of the global scenarios. We use evolutionary algorithms and a simple water resource system model to demonstrate this approach. The primary contribution is to demonstrate that flexibility can be added to the search for portfolios, in complex non-linear systems, at the expense of complete robustness across all future scenarios. In this context we define flexibility as the ability to design a portfolio in which some decisions are delayed, but those decisions that are not delayed are themselves shown to be robust to the future. We recognise that some decisions in our portfolio are more important than others. An adaptive portfolio is found by allowing no flexibility for these near-term "important" decisions, but maintaining flexibility in the remaining longer term decisions. In this sense we create an effective 2-stage decision process for a non-linear water resource supply system. We show how this reduces a measure of regret versus the inflexible robust solution for the same system.

Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screen thermomechanical properties of solids

NASA Astrophysics Data System (ADS)

Toher, Cormac; Oses, Corey; Plata, Jose J.; Hicks, David; Rose, Frisco; Levy, Ohad; de Jong, Maarten; Asta, Mark; Fornari, Marco; Buongiorno Nardelli, Marco; Curtarolo, Stefano

2017-06-01

Thorough characterization of the thermomechanical properties of materials requires difficult and time-consuming experiments. This severely limits the availability of data and is one of the main obstacles for the development of effective accelerated materials design strategies. The rapid screening of new potential materials requires highly integrated, sophisticated, and robust computational approaches. We tackled the challenge by developing an automated, integrated workflow with robust error-correction within the AFLOW framework which combines the newly developed "Automatic Elasticity Library" with the previously implemented GIBBS method. The first extracts the mechanical properties from automatic self-consistent stress-strain calculations, while the latter employs those mechanical properties to evaluate the thermodynamics within the Debye model. This new thermoelastic workflow is benchmarked against a set of 74 experimentally characterized systems to pinpoint a robust computational methodology for the evaluation of bulk and shear moduli, Poisson ratios, Debye temperatures, Grüneisen parameters, and thermal conductivities of a wide variety of materials. The effect of different choices of equations of state and exchange-correlation functionals is examined and the optimum combination of properties for the Leibfried-Schlömann prediction of thermal conductivity is identified, leading to improved agreement with experimental results than the GIBBS-only approach. The framework has been applied to the AFLOW.org data repositories to compute the thermoelastic properties of over 3500 unique materials. The results are now available online by using an expanded version of the REST-API described in the Appendix.

Vorinostat, Rituximab, and Combination Chemotherapy in Treating Patients With Newly Diagnosed Stage II, Stage III, or Stage IV Diffuse Large B-Cell Lymphoma

ClinicalTrials.gov

2017-09-12

Stage II Contiguous Adult Diffuse Large Cell Lymphoma; Stage II Non-Contiguous Adult Diffuse Large Cell Lymphoma; Stage III Adult Diffuse Large Cell Lymphoma; Stage IV Adult Diffuse Large Cell Lymphoma

Structural and Functional Maturation of Cardiomyocytes Derived from Human Pluripotent Stem Cells

PubMed Central

Lundy, Scott D.; Zhu, Wei-Zhong

2013-01-01

Despite preclinical studies demonstrating the functional benefit of transplanting human pluripotent stem cell-derived cardiomyocytes (PSC-CMs) into damaged myocardium, the ability of these immature cells to adopt a more adult-like cardiomyocyte (CM) phenotype remains uncertain. To address this issue, we tested the hypothesis that prolonged in vitro culture of human embryonic stem cell (hESC)- and human induced pluripotent stem cell (hiPSC)-derived CMs would result in the maturation of their structural and contractile properties to a more adult-like phenotype. Compared to their early-stage counterparts (PSC-CMs after 20–40 days of in vitro differentiation and culture), late-stage hESC-CMs and hiPSC-CMs (80–120 days) showed dramatic differences in morphology, including increased cell size and anisotropy, greater myofibril density and alignment, sarcomeres visible by bright-field microscopy, and a 10-fold increase in the fraction of multinucleated CMs. Ultrastructural analysis confirmed improvements in the myofibrillar density, alignment, and morphology. We measured the contractile performance of late-stage hESC-CMs and hiPSC-CMs and noted a doubling in shortening magnitude with slowed contraction kinetics compared to the early-stage cells. We then examined changes in the calcium-handling properties of these matured CMs and found an increase in calcium release and reuptake rates with no change in the maximum amplitude. Finally, we performed electrophysiological assessments in hESC-CMs and found that late-stage myocytes have hyperpolarized maximum diastolic potentials, increased action potential amplitudes, and faster upstroke velocities. To correlate these functional changes with gene expression, we performed qPCR and found a robust induction of the key cardiac structural markers, including β-myosin heavy chain and connexin-43, in late-stage hESC-CMs and hiPSC-CMs. These findings suggest that PSC-CMs are capable of slowly maturing to more closely resemble the phenotype of adult CMs and may eventually possess the potential to regenerate the lost myocardium with robust de novo force-producing tissue. PMID:23461462

Development and testing of a de novo clinical staging system for podoconiosis (endemic non-filarial elephantiasis).

PubMed

Tekola, Fasil; Ayele, Zewdu; Mariam, Dereje Haile; Fuller, Claire; Davey, Gail

2008-10-01

To develop and test a robust clinical staging system for podoconiosis, a geochemical disease in individuals exposed to red clay soil. We adapted the Dreyer system for staging filarial lymphoedema and tested it in four re-iterative field tests conducted in an area of high-podoconiosis prevalence in Southern Ethiopia. The system has five stages according to proximal spread of disease and presence of dermal nodules, ridges and bands. We measured the 1-week repeatability and the inter-observer agreement of the final staging system. The five-stage system is readily understood by community workers with little health training. Kappa for 1-week repeatability was 0.88 (95% CI 0.80-0.96), for agreement between health professionals was 0.71 (95% CI 0.60-0.82), while that between health professionals and community podoconiosis agents without formal health training averaged 0.64 (95% CI 0.52-0.78). This simple staging system with good inter-observer agreement and repeatability can assist in the management and further study of podoconiosis.

A Gradient Taguchi Method for Engineering Optimization

NASA Astrophysics Data System (ADS)

Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song

2017-10-01

To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.

Review: Deciphering animal robustness. A synthesis to facilitate its use in livestock breeding and management.

PubMed

Friggens, N C; Blanc, F; Berry, D P; Puillet, L

2017-12-01

As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal's capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal's ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.

TAS102 in Combination With NAL-IRI in Advanced GI Cancers

ClinicalTrials.gov

2018-03-29

Colorectal Adenocarcinoma; Gastric Adenocarcinoma; Metastatic Pancreatic Adenocarcinoma; Non-Resectable Cholangiocarcinoma; Stage IV Colorectal Cancer; Stage IV Gastric Cancer; Stage IV Pancreatic Cancer; Stage IVA Colorectal Cancer; Stage IVB Colorectal Cancer; Unresectable Pancreatic Carcinoma

Review of the Pyrolysis Platform for Producing Bio-oil and Biochar: Technology, Logistics, and Potential Impacts on Greenhouse Gas Emissions, Water Quality, Soil Quality, and Agricultural Productivity

USDA-ARS?s Scientific Manuscript database

Pyrolysis is a relatively simple, inexpensive, and robust thermochemical technology for transforming biomass into bio-oil, biochar, and syngas. The robust nature of the pyrolysis technology, which allows considerable flexibility in both the type and quality of the biomass feedstock, combined with a ...

Brentuximab Vedotin and Combination Chemotherapy in Treating Children and Young Adults With Stage IIB or Stage IIIB-IVB Hodgkin Lymphoma

ClinicalTrials.gov

2018-06-25

Ann Arbor Stage IIB Hodgkin Lymphoma; Ann Arbor Stage IIIB Hodgkin Lymphoma; Ann Arbor Stage IV Hodgkin Lymphoma; Ann Arbor Stage IVA Hodgkin Lymphoma; Ann Arbor Stage IVB Hodgkin Lymphoma; Childhood Hodgkin Lymphoma; Classic Hodgkin Lymphoma

Combination Chemotherapy With or Without Oregovomab Followed by Stereotactic Body Radiation Therapy and Nelfinavir Mesylate in Treating Patients With Locally Advanced Pancreatic Cancer

ClinicalTrials.gov

2018-04-24

Pancreatic Adenocarcinoma; Resectable Pancreatic Carcinoma; Stage I Pancreatic Cancer; Stage IA Pancreatic Cancer; Stage IB Pancreatic Cancer; Stage II Pancreatic Cancer; Stage IIA Pancreatic Cancer; Stage IIB Pancreatic Cancer; Stage III Pancreatic Cancer

Artemisone and artemiside - potent pan-reactive antimalarial agents that also synergize redox imbalance in P. falciparum transmissible gametocyte stages.

PubMed

Coertzen, Dina; Reader, Janette; van der Watt, Mariëtte; Nondaba, Sindisiwe H; Gibhard, Liezl; Wiesner, Lubbe; Smith, Peter; D'Alessandro, Sarah; Taramelli, Donatella; Ning Wong, Ho; du Preez, Jan L; Wu, Ronald Wai Keung; Birkholtz, Lyn-Marie; Haynes, Richard K

2018-06-04

The emergence of resistance towards artemisinin combination therapies (ACTs) by the malaria parasite Plasmodium falciparum has the potential to severely compromise malaria control. Therefore, development of new artemisinins in combination with new drugs that impart activities towards both intraerythrocytic proliferative asexual and transmissible gametocyte stages, in particular those of resistant parasites, are urgently required. We define artemisinins as oxidant drugs through their ability to oxidize reduced flavin cofactors of flavin disulfide reductases critical for maintaining redox-homeostasis in the malaria parasite. Here we compare the activities of 10-amino artemisinin derivatives towards the asexual and gametocyte stages of P. falciparum parasites. Of these, artemisone and artemiside inhibited asexual and gametocyte stages, particularly stage V gametocytes in the low nM range. Further, treatment of both early and late gametocyte stages with artemisone or artemiside combined with the pro-oxidant redox partner methylene blue displays notable synergism. These data suggest that modulation of redox-homeostasis likely is an important druggable process, particularly in gametocytes, and thereby enhances the prospect of using combinations of oxidant and redox drugs for malaria control. Copyright © 2018 American Society for Microbiology.

Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan T.

2012-01-01

Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…

RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement.

PubMed

Sandhu, Maninder; Sureshkumar, V; Prakash, Chandra; Dixit, Rekha; Solanke, Amolkumar U; Sharma, Tilak Raj; Mohapatra, Trilochan; S V, Amitha Mithra

2017-09-30

Genome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice. RiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. 'Physical position search' is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the 'common genes across varieties' search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search. The aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201.

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

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

Stevens, Garrison Nicole; Van Buren, Kendra Lu; Hemez, Francois M.

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, andmore » finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where uncertainty is added to the system through noise in the measurements.« less

Robustness and quality of precipitation and river flow data obtained through participatory monitoring and citizen scienc

NASA Astrophysics Data System (ADS)

Buytaert, W.; Ochoa-Tocachi, B. F.

2016-12-01

Apart for the most basic measurements of manual rain and staff gauges, hydrology and water resources are not an evident disciplines for the application of citizen science. High-resolution measurements require elaborate equipment, installation, and maintenance that is typically beyond the scope of non-scientists. Additionally, hydrological analysis has traditionally relied upon long time series of consistent accuracy and precision. Nevertheless, new opportunities for public participation in hydrological research are emerging, driven by increasingly affordable, robust, and more user-friendly technology. Here we analyse the results generated by participatory monitoring of river flow and precipitation in around 30 catchments in the tropical Andes. This monitoring network was set up through a collaborative effort between scientists, NGOs and local communities, with the intention to generate evidence about the impact of land-use change on streamflow. Monitoring was implemented using automatic but low-cost sensors operated and maintained by local users. Tipping bucket rain gauges are used for precipitation, and river flow is monitored with pressure transducers in combination with a V-notch weir to obtain a stable stage-discharge relation. Jointly, the sensors have now collected an equivalent of more than 30 years of data, with a measurement interval of typically 5 or 15 minutes. Analysing the data, we find that the observations themselves tend to be of a quality comparable to scientific observations. However, main issues are related to the continuity of the time series, as sensors eventually fail or run out of capacity in dataloggers or batteries in the most remote locations. Despite these shortcomings, the data have proven to be useful in characterizing land-use impacts well beyond what can be achieved with conventional data collection, thus filling long-standing gaps in local hydrological knowledge. Furthermore, we expect that the advent of new, more robust, resilient, and automatized sensor technologies will alleviate some of the current issues.

Practical Results from the Application of Model Checking and Test Generation from UML/SysML Models of On-Board Space Applications

NASA Astrophysics Data System (ADS)

Faria, J. M.; Mahomad, S.; Silva, N.

2009-05-01

The deployment of complex safety-critical applications requires rigorous techniques and powerful tools both for the development and V&V stages. Model-based technologies are increasingly being used to develop safety-critical software, and arguably, turning to them can bring significant benefits to such processes, however, along with new challenges. This paper presents the results of a research project where we tried to extend current V&V methodologies to be applied on UML/SysML models and aiming at answering the demands related to validation issues. Two quite different but complementary approaches were investigated: (i) model checking and the (ii) extraction of robustness test-cases from the same models. These two approaches don't overlap and when combined provide a wider reaching model/design validation ability than each one alone thus offering improved safety assurance. Results are very encouraging, even though they either fell short of the desired outcome as shown for model checking, or still appear as not fully matured as shown for robustness test case extraction. In the case of model checking, it was verified that the automatic model validation process can become fully operational and even expanded in scope once tool vendors help (inevitably) to improve the XMI standard interoperability situation. For the robustness test case extraction methodology, the early approach produced interesting results but need further systematisation and consolidation effort in order to produce results in a more predictable fashion and reduce reliance on expert's heuristics. Finally, further improvements and innovation research projects were immediately apparent for both investigated approaches, which point to either circumventing current limitations in XMI interoperability on one hand and bringing test case specification onto the same graphical level as the models themselves and then attempting to automate the generation of executable test cases from its standard UML notation.

A robust H∞ control-based hierarchical mode transition control system for plug-in hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Yang, Chao; Jiao, Xiaohong; Li, Liang; Zhang, Yuanbo; Chen, Zheng

2018-01-01

To realize a fast and smooth operating mode transition process from electric driving mode to engine-on driving mode, this paper presents a novel robust hierarchical mode transition control method for a plug-in hybrid electric bus (PHEB) with pre-transmission parallel hybrid powertrain. Firstly, the mode transition process is divided into five stages to clearly describe the powertrain dynamics. Based on the dynamics models of powertrain and clutch actuating mechanism, a hierarchical control structure including two robust H∞ controllers in both upper layer and lower layer is proposed. In upper layer, the demand clutch torque can be calculated by a robust H∞controller considering the clutch engaging time and the vehicle jerk. While in lower layer a robust tracking controller with L2-gain is designed to perform the accurate position tracking control, especially when the parameters uncertainties and external disturbance occur in the clutch actuating mechanism. Simulation and hardware-in-the-loop (HIL) test are carried out in a traditional driving condition of PHEB. Results show that the proposed hierarchical control approach can obtain the good control performance: mode transition time is greatly reduced with the acceptable jerk. Meanwhile, the designed control system shows the obvious robustness with the uncertain parameters and disturbance. Therefore, the proposed approach may offer a theoretical reference for the actual vehicle controller.

Combined radar-radiometer surface soil moisture and roughness estimation

USDA-ARS?s Scientific Manuscript database

A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution rad...

Combined Transcriptome and Proteome Analysis Identifies Pathways and Markers Associated with the Establishment of Rapeseed Microspore-Derived Embryo Development1[W

PubMed Central

Joosen, Ronny; Cordewener, Jan; Supena, Ence Darmo Jaya; Vorst, Oscar; Lammers, Michiel; Maliepaard, Chris; Zeilmaker, Tieme; Miki, Brian; America, Twan; Custers, Jan; Boutilier, Kim

2007-01-01

Microspore-derived embryo (MDE) cultures are used as a model system to study plant cell totipotency and as an in vitro system to study embryo development. We characterized and compared the transcriptome and proteome of rapeseed (Brassica napus) MDEs from the few-celled stage to the globular/heart stage using two MDE culture systems: conventional cultures in which MDEs initially develop as unorganized clusters that usually lack a suspensor, and a novel suspensor-bearing embryo culture system in which the embryo proper originates from the distal cell of a suspensor-like structure and undergoes the same ordered cell divisions as the zygotic embryo. Improved histodifferentiation of suspensor-bearing MDEs suggests a new role for the suspensor in driving embryo cell identity and patterning. An MDE culture cDNA array and two-dimensional gel electrophoresis and protein sequencing were used to compile global and specific expression profiles for the two types of MDE cultures. Analysis of the identities of 220 candidate embryo markers, as well as the identities of 32 sequenced embryo up-regulated protein spots, indicate general roles for protein synthesis, glycolysis, and ascorbate metabolism in the establishment of MDE development. A collection of 135 robust markers for the transition to MDE development was identified, a number of which may be coregulated at the gene and protein expression level. Comparison of the expression profiles of preglobular-stage conventional MDEs and suspensor-bearing MDEs identified genes whose differential expression may reflect improved histodifferentiation of suspensor-bearing embryos. This collection of early embryo-expressed genes and proteins serves as a starting point for future marker development and gene function studies aimed at understanding the molecular regulation of cell totipotency and early embryo development in plants. PMID:17384159

The Interactive Role of Immature Stage Competition, Cohort Overlap, and Resource Limitation on the Population Viability of the Treehole Mosquito Aedes triseriatus (Diptera: Culicidae).

PubMed

Hanly, Patrick J; Haase, Amanda T

2016-05-01

The size and success of epidemiologically significant adult mosquito populations are inherently tied to the conditions of the aquatic habitat in which juvenile stages grow until eclosion. While resource competition and quality are well-established controls to juvenile growth and survival, the implications to overall population rates of increase are less understood due to the large sample sizes needed to parameterize population models for all five juvenile life stages under multiple environmental and demographic conditions. Here, we present the results of >4,300 trials of wild-caught Aedes triseriatus (Say, 1823) larvae and pupae reared under varying resource quantity crossed by the presence or absence of competition within a single cohort as well as multiple overlapping cohorts. Demographic projection was used to make predictions of the realized growth rates of simulated Ae. triseriatus populations across the range of potential Ae. triseriatus fecundity. Further, to inform control efforts on juvenile habitat, we constructed a stochastic simulation to estimate the rates of successful emergence from habitats under different resource regimes and levels of cohort overlap. We found that while Ae. triseriatus populations were robust to low resource levels and competition within a cohort, the combination of these stressors with multiple cohort overlap led to self-limitation or complete collapse of mosquito populations. Despite this importance of intraspecific competition to population viability, the stochastic simulation revealed only a modest self-limitation of adult emergence, with the clear implication that high-resource habitats are a higher value control target. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multi-objective robust design of energy-absorbing components using coupled process-performance simulations

NASA Astrophysics Data System (ADS)

Najafi, Ali; Acar, Erdem; Rais-Rohani, Masoud

2014-02-01

The stochastic uncertainties associated with the material, process and product are represented and propagated to process and performance responses. A finite element-based sequential coupled process-performance framework is used to simulate the forming and energy absorption responses of a thin-walled tube in a manner that both material properties and component geometry can evolve from one stage to the next for better prediction of the structural performance measures. Metamodelling techniques are used to develop surrogate models for manufacturing and performance responses. One set of metamodels relates the responses to the random variables whereas the other relates the mean and standard deviation of the responses to the selected design variables. A multi-objective robust design optimization problem is formulated and solved to illustrate the methodology and the influence of uncertainties on manufacturability and energy absorption of a metallic double-hat tube. The results are compared with those of deterministic and augmented robust optimization problems.

3D shape extraction segmentation and representation of soil microstructures using generalized cylinders

NASA Astrophysics Data System (ADS)

Ngom, Ndèye Fatou; Monga, Olivier; Ould Mohamed, Mohamed Mahmoud; Garnier, Patricia

2012-02-01

This paper focuses on the modeling of soil microstructures using generalized cylinders, with a specific application to pore space. The geometric modeling of these microstructures is a recent area of study, made possible by the improved performance of computed tomography techniques. X-scanners provide very-high-resolution 3D volume images ( 3-5μm) of soil samples in which pore spaces can be extracted by thresholding. However, in most cases, the pore space defines a complex volume shape that cannot be approximated using simple analytical functions. We propose representing this shape using a compact, stable, and robust piecewise approximation by means of generalized cylinders. This intrinsic shape representation conserves its topological and geometric properties. Our algorithm includes three main processing stages. The first stage consists in describing the volume shape using a minimum number of balls included within the shape, such that their union recovers the shape skeleton. The second stage involves the optimum extraction of simply connected chains of balls. The final stage copes with the approximation of each simply optimal chain using generalized cylinders: circular generalized cylinders, tori, cylinders, and truncated cones. This technique was applied to several data sets formed by real volume computed tomography soil samples. It was possible to demonstrate that our geometric representation supplied a good approximation of the pore space. We also stress the compactness and robustness of this method with respect to any changes affecting the initial data, as well as its coherence with the intuitive notion of pores. During future studies, this geometric pore space representation will be used to simulate biological dynamics.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Optically enhanced acoustophoresis

NASA Astrophysics Data System (ADS)

McDougall, Craig; O'Mahoney, Paul; McGuinn, Alan; Willoughby, Nicholas A.; Qiu, Yongqiang; Demore, Christine E. M.; MacDonald, Michael P.

2017-08-01

Regenerative medicine has the capability to revolutionise many aspects of medical care, but for it to make the step from small scale autologous treatments to larger scale allogeneic approaches, robust and scalable label free cell sorting technologies are needed as part of a cell therapy bioprocessing pipeline. In this proceedings we describe several strategies for addressing the requirements for high throughput without labeling via: dimensional scaling, rare species targeting and sorting from a stable state. These three approaches are demonstrated through a combination of optical and ultrasonic forces. By combining mostly conservative and non-conservative forces from two different modalities it is possible to reduce the influence of flow velocity on sorting efficiency, hence increasing robustness and scalability. One such approach can be termed "optically enhanced acoustophoresis" which combines the ability of acoustics to handle large volumes of analyte with the high specificity of optical sorting.

A robust high-order lattice adaptive notch filter and its application to narrowband noise cancellation

NASA Astrophysics Data System (ADS)

Kim, Seong-woo; Park, Young-cheol; Seo, Young-soo; Youn, Dae Hee

2014-12-01

In this paper, we propose a high-order lattice adaptive notch filter (LANF) that can robustly track multiple sinusoids. Unlike the conventional cascade structure, the proposed high-order LANF has robust tracking characteristics regardless of the frequencies of reference sinusoids and initial notch frequencies. The proposed high-order LANF is applied to a narrowband adaptive noise cancellation (ANC) to mitigate the effect of the broadband disturbance in the reference signal. By utilizing the gradient adaptive lattice (GAL) ANC algorithm and approximately combining it with the proposed high-order LANF, a computationally efficient narrowband ANC system is obtained. Experimental results demonstrate the robustness of the proposed high-order LANF and the effectiveness of the obtained narrowband ANC system.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

NASA Astrophysics Data System (ADS)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

Pan FGFR Kinase Inhibitor BGJ398 and Combination Chemotherapy in Treating Patients With Untreated Metastatic Pancreatic Cancer

ClinicalTrials.gov

2016-05-19

Colon Adenocarcinoma; Metastatic Pancreatic Adenocarcinoma; Pancreatic Adenocarcinoma; Pancreatic Ductal Adenocarcinoma; Rectal Adenocarcinoma; Stage III Pancreatic Cancer; Stage IIIA Colon Cancer; Stage IIIA Rectal Cancer; Stage IIIB Colon Cancer; Stage IIIB Rectal Cancer; Stage IIIC Colon Cancer; Stage IIIC Rectal Cancer; Stage IV Pancreatic Cancer; Stage IVA Colon Cancer; Stage IVA Rectal Cancer; Stage IVB Colon Cancer; Stage IVB Rectal Cancer

Grid Integration of Single Stage Solar PV System using Three-level Voltage Source Converter

NASA Astrophysics Data System (ADS)

Hussain, Ikhlaq; Kandpal, Maulik; Singh, Bhim

2016-08-01

This paper presents a single stage solar PV (photovoltaic) grid integrated power generating system using a three level voltage source converter (VSC) operating at low switching frequency of 900 Hz with robust synchronizing phase locked loop (RS-PLL) based control algorithm. To track the maximum power from solar PV array, an incremental conductance algorithm is used and this maximum power is fed to the grid via three-level VSC. The use of single stage system with three level VSC offers the advantage of low switching losses and the operation at high voltages and high power which results in enhancement of power quality in the proposed system. Simulated results validate the design and control algorithm under steady state and dynamic conditions.

Lane marking detection based on waveform analysis and CNN

NASA Astrophysics Data System (ADS)

Ye, Yang Yang; Chen, Hou Jin; Hao, Xiao Li

2017-06-01

Lane markings detection is a very important part of the ADAS to avoid traffic accidents. In order to obtain accurate lane markings, in this work, a novel and efficient algorithm is proposed, which analyses the waveform generated from the road image after inverse perspective mapping (IPM). The algorithm includes two main stages: the first stage uses an image preprocessing including a CNN to reduce the background and enhance the lane markings. The second stage obtains the waveform of the road image and analyzes the waveform to get lanes. The contribution of this work is that we introduce local and global features of the waveform to detect the lane markings. The results indicate the proposed method is robust in detecting and fitting the lane markings.

Robust inference for group sequential trials.

PubMed

Ganju, Jitendra; Lin, Yunzhi; Zhou, Kefei

2017-03-01

For ethical reasons, group sequential trials were introduced to allow trials to stop early in the event of extreme results. Endpoints in such trials are usually mortality or irreversible morbidity. For a given endpoint, the norm is to use a single test statistic and to use that same statistic for each analysis. This approach is risky because the test statistic has to be specified before the study is unblinded, and there is loss in power if the assumptions that ensure optimality for each analysis are not met. To minimize the risk of moderate to substantial loss in power due to a suboptimal choice of a statistic, a robust method was developed for nonsequential trials. The concept is analogous to diversification of financial investments to minimize risk. The method is based on combining P values from multiple test statistics for formal inference while controlling the type I error rate at its designated value.This article evaluates the performance of 2 P value combining methods for group sequential trials. The emphasis is on time to event trials although results from less complex trials are also included. The gain or loss in power with the combination method relative to a single statistic is asymmetric in its favor. Depending on the power of each individual test, the combination method can give more power than any single test or give power that is closer to the test with the most power. The versatility of the method is that it can combine P values from different test statistics for analysis at different times. The robustness of results suggests that inference from group sequential trials can be strengthened with the use of combined tests. Copyright © 2017 John Wiley & Sons, Ltd.

A method for extending stage-discharge relationships using a hydrodynamic model and quantifying the associated uncertainty

NASA Astrophysics Data System (ADS)

Shao, Quanxi; Dutta, Dushmanta; Karim, Fazlul; Petheram, Cuan

2018-01-01

Streamflow discharge is a fundamental dataset required to effectively manage water and land resources. However, developing robust stage - discharge relationships called rating curves, from which streamflow discharge is derived, is time consuming and costly, particularly in remote areas and especially at high stage levels. As a result stage - discharge relationships are often heavily extrapolated. Hydrodynamic (HD) models are physically based models used to simulate the flow of water along river channels and over adjacent floodplains. In this paper we demonstrate a method by which a HD model can be used to generate a 'synthetic' stage - discharge relationship at high stages. The method uses a both-side Box-Cox transformation to calibrate the synthetic rating curve such that the regression residuals are as close to the normal distribution as possible. By doing this both-side transformation, the statistical uncertainty in the synthetically derived stage - discharge relationship can be calculated. This enables people trying to make decisions to determine whether the uncertainty in the synthetically generated rating curve at high stage levels is acceptable for their decision. The proposed method is demonstrated in two streamflow gauging stations in north Queensland, Australia.

Summary Stage 2018 - SEER

Cancer.gov

Access this manual of codes and coding instructions for the summary stage field for cases diagnosed January 1, 2018 and forward. 2018 version applies to every site and/or histology combination, including lymphomas and leukemias. Historically, also called General Staging, California Staging, and SEER Staging.

Combining semiquantitative measures of fibrosis and qualitative features of parenchymal remodelling to identify fibrosis regression in hepatitis C: a multiple biopsy study.

PubMed

Pattullo, Venessa; Thein, Hla-Hla; Heathcote, Elizabeth Jenny; Guindi, Maha

2012-09-01

A fall in hepatic fibrosis stage may be observed in patients with chronic hepatitis C (CHC); however, parenchymal architectural changes may also signify hepatic remodelling associated with fibrosis regression. The aim of this study was to utilize semiquantitative and qualitative methods to report the prevalence and factors associated with fibrosis regression in CHC. Paired liver biopsies were scored for fibrosis (Ishak), and for the presence of eight qualitative features of parenchymal remodelling, to derive a qualitative regression score (QR score). Combined fibrosis regression was defined as ≥2-stage fall in Ishak stage (Reg-I) or <2-stage fall in Ishak stage with a rise in QR score (Reg-Qual). Among 159 patients (biopsy interval 5.4 ± 3.1 years), Reg-I was observed in 12 (7.5%) and Reg-Qual in 26 (16.4%) patients. The combined diagnostic criteria increased the diagnosis rate for fibrosis regression (38 patients, 23.9%) compared with use of Reg-I alone (P < 0.001). Combined fibrosis regression was observed in nine patients (50%) who achieved sustained virological response (SVR), and in 29 of 141 (21%) patients despite persistent viraemia. SVR was the only clinical factor associated independently with combined fibrosis regression (odds ratio 3.05). The combination of semiquantitative measures and qualitative features aids the identification of fibrosis regression in CHC. © 2012 Blackwell Publishing Ltd.

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.

Coupling-Induced Bipartite Pointer States in Arrays of Electron Billiards: Quantum Darwinism in Action?

NASA Astrophysics Data System (ADS)

Brunner, R.; Akis, R.; Ferry, D. K.; Kuchar, F.; Meisels, R.

2008-07-01

We discuss a quantum system coupled to the environment, composed of an open array of billiards (dots) in series. Beside pointer states occurring in individual dots, we observe sets of robust states which arise only in the array. We define these new states as bipartite pointer states, since they cannot be described in terms of simple linear combinations of robust single-dot states. The classical existence of bipartite pointer states is confirmed by comparing the quantum-mechanical and classical results. The ability of the robust states to create “offspring” indicates that quantum Darwinism is in action.

Coupling-induced bipartite pointer states in arrays of electron billiards: quantum Darwinism in action?

PubMed

Brunner, R; Akis, R; Ferry, D K; Kuchar, F; Meisels, R

2008-07-11

We discuss a quantum system coupled to the environment, composed of an open array of billiards (dots) in series. Beside pointer states occurring in individual dots, we observe sets of robust states which arise only in the array. We define these new states as bipartite pointer states, since they cannot be described in terms of simple linear combinations of robust single-dot states. The classical existence of bipartite pointer states is confirmed by comparing the quantum-mechanical and classical results. The ability of the robust states to create "offspring" indicates that quantum Darwinism is in action.

A Robust Zero-Watermarking Algorithm for Audio

NASA Astrophysics Data System (ADS)

Chen, Ning; Zhu, Jie

2007-12-01

In traditional watermarking algorithms, the insertion of watermark into the host signal inevitably introduces some perceptible quality degradation. Another problem is the inherent conflict between imperceptibility and robustness. Zero-watermarking technique can solve these problems successfully. Instead of embedding watermark, the zero-watermarking technique extracts some essential characteristics from the host signal and uses them for watermark detection. However, most of the available zero-watermarking schemes are designed for still image and their robustness is not satisfactory. In this paper, an efficient and robust zero-watermarking technique for audio signal is presented. The multiresolution characteristic of discrete wavelet transform (DWT), the energy compression characteristic of discrete cosine transform (DCT), and the Gaussian noise suppression property of higher-order cumulant are combined to extract essential features from the host audio signal and they are then used for watermark recovery. Simulation results demonstrate the effectiveness of our scheme in terms of inaudibility, detection reliability, and robustness.

Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor.

PubMed

Wu, Hao; Chen, Shuxin; Yang, Binfeng; Chen, Kun

2016-05-09

The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers' misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors.

Robust optimization model and algorithm for railway freight center location problem in uncertain environment.

PubMed

Liu, Xing-Cai; He, Shi-Wei; Song, Rui; Sun, Yang; Li, Hao-Dong

2014-01-01

Railway freight center location problem is an important issue in railway freight transport programming. This paper focuses on the railway freight center location problem in uncertain environment. Seeing that the expected value model ignores the negative influence of disadvantageous scenarios, a robust optimization model was proposed. The robust optimization model takes expected cost and deviation value of the scenarios as the objective. A cloud adaptive clonal selection algorithm (C-ACSA) was presented. It combines adaptive clonal selection algorithm with Cloud Model which can improve the convergence rate. Design of the code and progress of the algorithm were proposed. Result of the example demonstrates the model and algorithm are effective. Compared with the expected value cases, the amount of disadvantageous scenarios in robust model reduces from 163 to 21, which prove the result of robust model is more reliable.

Robust nonlinear control of vectored thrust aircraft

NASA Technical Reports Server (NTRS)

Doyle, John C.; Murray, Richard; Morris, John

1993-01-01

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations.

Analysis of market penetration of renewable energy alternatives under uncertain and carbon constrained world

EPA Science Inventory

Future energy prices and supply, availability and costs can have a significant impact on how fast and cost effectively we could abate carbon emissions. Two-staged decision making methods embedded in U.S. EPA's MARKAL modeling system will be utilized to find the most robust mitig...

The Effect of Feedback Schedule Manipulation on Speech Priming Patterns and Reaction Time

ERIC Educational Resources Information Center

Slocomb, Dana; Spencer, Kristie A.

2009-01-01

Speech priming tasks are frequently used to delineate stages in the speech process such as lexical retrieval and motor programming. These tasks, often measured in reaction time (RT), require fast and accurate responses, reflecting maximized participant performance, to result in robust priming effects. Encouraging speed and accuracy in responding…

OVERVIEW: USING MODE OF ACTION AND LIFE STAGE INFORMATION TO EVALUATE THE HUMAN RELEVANCE OF ANIMAL TOXICITY DATA.

EPA Science Inventory

A manuscript summarizes a workshop aimed at developing a framework to determine the relevancy of animal modes-of-action for extrapolation to humans. A complete mode of action human relevance analysis - as distinct from mode of action (MOA) analysis alone - depends on robust info...

Functionalization of MEMS cantilever beams for interconnect reliability investigation: development practice

NASA Astrophysics Data System (ADS)

Bieniek, T.; Janczyk, G.; Dobrowolski, R.; Wojciechowska, K.; Malinowska, A.; Panas, A.; Nieprzecki, M.; Kłos, H.

2016-11-01

This paper covers research results on development of the cantilevers beams test structures for interconnects reliability and robustness investigation. Presented results include design, modelling, simulation, optimization and finally fabrication stage performed on 4 inch Si wafers using the ITE microfabrication facility. This paper also covers experimental results from the test structures characterization.

The Syntax-PF Interface in Children's Negative Sentences

ERIC Educational Resources Information Center

Thornton, Rosalind; Rombough, Kelly

2015-01-01

To test between two recent accounts of the early stages in the acquisition of negation, we conducted an elicited production study with 25 children, between 2;05 and 3;04 (mean 2;11). The experimental study produced a robust set of negative sentences, with considerable individual variation. Although 13 of the child participants mainly produced…

A Robust Deep Model for Improved Classification of AD/MCI Patients

PubMed Central

Li, Feng; Tran, Loc; Thung, Kim-Han; Ji, Shuiwang; Shen, Dinggang; Li, Jiang

2015-01-01

Accurate classification of Alzheimer’s Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), plays a critical role in possibly preventing progression of memory impairment and improving quality of life for AD patients. Among many research tasks, it is of particular interest to identify noninvasive imaging biomarkers for AD diagnosis. In this paper, we present a robust deep learning system to identify different progression stages of AD patients based on MRI and PET scans. We utilized the dropout technique to improve classical deep learning by preventing its weight co-adaptation, which is a typical cause of over-fitting in deep learning. In addition, we incorporated stability selection, an adaptive learning factor, and a multi-task learning strategy into the deep learning framework. We applied the proposed method to the ADNI data set and conducted experiments for AD and MCI conversion diagnosis. Experimental results showed that the dropout technique is very effective in AD diagnosis, improving the classification accuracies by 5.9% on average as compared to the classical deep learning methods. PMID:25955998

An efficient and robust method for predicting helicopter rotor high-speed impulsive noise

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

1996-01-01

A new formulation for the Ffowcs Williams-Hawkings quadrupole source, which is valid for a far-field in-plane observer, is presented. The far-field approximation is new and unique in that no further approximation of the quadrupole source strength is made and integrands with r(exp -2) and r(exp -3) dependence are retained. This paper focuses on the development of a retarded-time formulation in which time derivatives are analytically taken inside the integrals to avoid unnecessary computational work when the observer moves with the rotor. The new quadrupole formulation is similar to Farassat's thickness and loading formulation 1A. Quadrupole noise prediction is carried out in two parts: a preprocessing stage in which the previously computed flow field is integrated in the direction normal to the rotor disk, and a noise computation stage in which quadrupole surface integrals are evaluated for a particular observer position. Preliminary predictions for hover and forward flight agree well with experimental data. The method is robust and requires computer resources comparable to thickness and loading noise prediction.

IGFBP-2 Vaccine and Combination Chemotherapy in Treating Patients With Stage III-IV Ovarian, Fallopian Tube, or Primary Peritoneal Cancer Undergoing Surgery

ClinicalTrials.gov

2018-05-01

Stage III Fallopian Tube Cancer; Stage III Ovarian Cancer; Stage III Primary Peritoneal Cancer; Stage IIIA Fallopian Tube Cancer; Stage IIIA Ovarian Cancer; Stage IIIA Primary Peritoneal Cancer; Stage IIIB Fallopian Tube Cancer; Stage IIIB Ovarian Cancer; Stage IIIB Primary Peritoneal Cancer; Stage IIIC Fallopian Tube Cancer; Stage IIIC Ovarian Cancer; Stage IIIC Primary Peritoneal Cancer; Stage IV Fallopian Tube Cancer; Stage IV Ovarian Cancer; Stage IV Primary Peritoneal Cancer

a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

NASA Astrophysics Data System (ADS)

Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

2017-09-01

Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network.

PubMed

Islam, Kh Tohidul; Raj, Ram Gopal

2017-04-13

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

PubMed Central

Islam, Kh Tohidul; Raj, Ram Gopal

2017-01-01

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471

Carfilzomib, Rituximab, and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Lymphoma

ClinicalTrials.gov

2018-05-16

Contiguous Stage II Adult Diffuse Large Cell Lymphoma; Noncontiguous Stage II Adult Diffuse Large Cell Lymphoma; Stage I Adult Diffuse Large Cell Lymphoma; Stage III Adult Diffuse Large Cell Lymphoma; Stage IV Adult Diffuse Large Cell Lymphoma

Loss of Robustness and Addiction to IGF1 during Early Keratinocyte Transformation by Human Papilloma Virus 16

PubMed Central

Geiger, Tamar; Levitzki, Alexander

2007-01-01

Infection of keratinocytes with high risk human Papilloma virus causes immortalization, and when followed by further mutations, leads to cervical cancer and other anogenital tumors. Here we monitor the progressive loss of robustness in an in vitro model of the early stages of transformation that comprises normal keratinocytes and progressive passages of HPV16 immortalized cells. As transformation progresses, the cells acquire higher proliferation rates and gain the ability to grow in soft agar. Concurrently, the cells lose robustness, becoming more sensitive to serum starvation and DNA damage by Cisplatin. Loss of robustness in the course of transformation correlates with significant reductions in the activities of the anti-apoptotic proteins PKB/Akt, Erk, Jnk and p38 both under normal growth conditions and upon stress. In parallel, loss of robustness is manifested by the shrinkage of the number of growth factors that can rescue starving cells from apoptosis, with the emergence of dependence solely on IGF1. Treatment with IGF1 activates PKB/Akt and Jnk and through them inhibits p53, rescuing the cells from starvation. We conclude that transformation in this model induces higher susceptibility of cells to stress due to reduced anti-apoptotic signaling and hyper-activation of p53 upon stress. PMID:17622350

Turbine Based Combined/Combination Cycle/RTA Project Overview

NASA Technical Reports Server (NTRS)

Bartolotta, Paul A.; Quigley, Brian F.

2000-01-01

This viewgraph presentation gives an overview of the Revolutionary Turbine Accelerator (RTA) program. Details are given on the Single Stage To Orbit (SSTO) and Two Stage To Orbit (TSTO) aircraft, and the technological challenges associated with the RTA, SSTO, and TSTO.

Serum amyloid A as a prognostic marker in melanoma identified by proteomic profiling.

PubMed

Findeisen, Peter; Zapatka, Marc; Peccerella, Teresa; Matzk, Heike; Neumaier, Michael; Schadendorf, Dirk; Ugurel, Selma

2009-05-01

Currently known prognostic serum biomarkers of melanoma are powerful in metastatic disease, but weak in early-stage patients. This study was aimed to identify new prognostic biomarkers of melanoma by serum mass spectrometry (MS) proteomic profiling, and to validate candidates compared with established markers. Two independent sets of serum samples from 596 melanoma patients were investigated. The first set (stage I = 102; stage IV = 95) was analyzed by matrix assisted laser desorption and ionization time of flight (MALDI TOF) MS for biomarkers differentiating between stage I and IV. In the second set (stage I = 98; stage II = 91; stage III = 87; stage IV = 103), the serum concentrations of the candidate marker serum amyloid A (SAA) and the known biomarkers S100B, lactate dehydrogenase, and C reactive protein (CRP) were measured using immunoassays. MALDI TOF MS revealed a peak at m/z 11.680 differentiating between stage I and IV, which could be identified as SAA. High peak intensities at m/z 11.680 correlated with poor survival. In univariate analysis, SAA was a strong prognostic marker in stage I to III (P = .043) and stage IV (P = .000083) patients. Combination of SAA and CRP increased the prognostic impact to P = .011 in early-stage (I to III) patients. Multivariate analysis revealed sex, stage, tumor load, S100B, SAA, and CRP as independent prognostic factors, with an interaction between SAA and CRP. In stage I to III patients, SAA combined with CRP was superior to S100B in predicting patients' progression-free and overall survival. SAA combined with CRP might be used as prognostic serological biomarkers in early-stage melanoma patients, helping to discriminate low-risk patients from high-risk patients needing adjuvant treatment.

Brentuximab Vedotin and Combination Chemotherapy in Treating Patients With Stage II-IV HIV-Associated Hodgkin Lymphoma

ClinicalTrials.gov

2018-06-11

AIDS-Related Hodgkin Lymphoma; Ann Arbor Stage II Hodgkin Lymphoma; Ann Arbor Stage IIA Hodgkin Lymphoma; Ann Arbor Stage IIB Hodgkin Lymphoma; Ann Arbor Stage III Hodgkin Lymphoma; Ann Arbor Stage IIIA Hodgkin Lymphoma; Ann Arbor Stage IIIB Hodgkin Lymphoma; Ann Arbor Stage IV Hodgkin Lymphoma; Ann Arbor Stage IVA Hodgkin Lymphoma; Ann Arbor Stage IVB Hodgkin Lymphoma; Classic Hodgkin Lymphoma; HIV Infection

Robust Rocket Engine Concept

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.

1995-01-01

The potential for a revolutionary step in the durability of reusable rocket engines is made possible by the combination of several emerging technologies. The recent creation and analytical demonstration of life extending (or damage mitigating) control technology enables rapid rocket engine transients with minimum fatigue and creep damage. This technology has been further enhanced by the formulation of very simple but conservative continuum damage models. These new ideas when combined with recent advances in multidisciplinary optimization provide the potential for a large (revolutionary) step in reusable rocket engine durability. This concept has been named the robust rocket engine concept (RREC) and is the basic contribution of this paper. The concept also includes consideration of design innovations to minimize critical point damage.

From Stats to Stage-Translational Research in Performing Arts Medicine.

PubMed

Ackermann, Bronwen J

2016-12-01

Medical Problems of Performing Artists, since its inception under the legendary Alice Brandfonbrener's guidance and vision, has always recognized the need for voices to be heard from the clinic, stage, and experimental research. This has been important in a relatively young field like performing arts medicine, where there is not yet a robust base of evidence to draw from for the complex range of physical, psychological, and institutional challenges that can affect performer health. Evidence-based medicine has long been described as using the best available research in conjunction with clinical expertise, while considering patient beliefs, characteristics, and circumstances.

Optimal control of mode transition for four-wheel-drive hybrid electric vehicle with dry dual-clutch transmission

NASA Astrophysics Data System (ADS)

Zhao, Zhiguo; Lei, Dan; Chen, Jiayi; Li, Hangyu

2018-05-01

When the four-wheel-drive hybrid electric vehicle (HEV) equipped with a dry dual clutch transmission (DCT) is in the mode transition process from pure electrical rear wheel drive to front wheel drive with engine or hybrid drive, the problem of vehicle longitudinal jerk is prominent. A mode transition robust control algorithm which resists external disturbance and model parameter fluctuation has been developed, by taking full advantage of fast and accurate torque (or speed) response of three electrical power sources and getting the clutch of DCT fully involved in the mode transition process. Firstly, models of key components of driveline system have been established, and the model of five-degrees-of-freedom vehicle longitudinal dynamics has been built by using a Uni-Tire model. Next, a multistage optimal control method has been produced to realize the decision of engine torque and clutch-transmitted torque. The sliding-mode control strategy for measurable disturbance has been proposed at the stage of engine speed dragged up. Meanwhile, the double tracking control architecture that integrates the model calculating feedforward control with H∞ robust feedback control has been presented at the stage of speed synchronization. Finally, the results from Matlab/Simulink software and hardware-in-the-loop test both demonstrate that the proposed control strategy for mode transition can not only coordinate the torque among different power sources and clutch while minimizing vehicle longitudinal jerk, but also provide strong robustness to model uncertainties and external disturbance.

A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

PubMed

Zhang, Qingxue; Zhou, Dian; Zeng, Xuan

2016-11-01

This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous heart rate (IHR) from wrist-electrocardiography (ECG) signals continuously and heavily corrupted by random motion artifacts in wearable applications. The framework includes two stages, i.e. heartbeat identification and refinement, respectively. In the first stage, an adaptive threshold-based auto-segmentation approach is proposed to select out heartbeat candidates, including the real heartbeats and large amounts of motion-artifact-induced interferential spikes. Then twenty-six features are extracted for each candidate in time, spatial, frequency and statistical domains, and evaluated by a spare support vector machine (SVM) to select out ten critical features which can effectively reveal residual heartbeat information. Afterwards, an SVM model, created on the training data using the selected feature set, is applied to find high confident heartbeats from a large number of candidates in the testing data. In the second stage, the SVM classification results are further refined by two steps: (1) a rule-based classifier with two attributes named 'continuity check' and 'locality check' for outlier (false positives) removal, and (2) a heartbeat interpolation strategy for missing-heartbeat (false negatives) recovery. The framework is evaluated on a wrist-ECG dataset acquired by a semi-customized platform and also a public dataset. When the signal-to-noise ratio is as low as  -7 dB, the mean absolute error of the estimated IHR is 1.4 beats per minute (BPM) and the root mean square error is 6.5 BPM. The proposed framework greatly outperforms well-established approaches, demonstrating that it can effectively identify the heartbeats from ECG signals continuously corrupted by intense motion artifacts and robustly estimate the IHR. This study is expected to contribute to robust long-term wearable IHR monitoring for pervasive heart health and fitness management.

Developpement d'une plateforme de simulation et d'un pilote automatique - Application aux Cessna Citation X et Hawker 800XP

NASA Astrophysics Data System (ADS)

Ghazi, Georges

This report presents several methodologies for the design of tools intended to the analysis of the stability and the control of a business aircraft. At first, a generic flight dynamic model was developed to predict the behavior of the aircraft further to a movement on the control surfaces or further to any disturbance. For that purpose, different categories of winds were considered in the module of simulation to generate various scenarios and conclude about the efficiency of the autopilot. Besides being realistic, the flight model takes into account the variation of the mass parameters according to fuel consumption. A comparison with a simulator of the company CAE Inc. and certified level D allowed to validate this first stage with an acceptable success rate. Once the dynamics is validated, the next stage deals with the stability around a flight condition. For that purpose, a first static analysis is established to find the trim conditions inside the flight envelop. Then, two algorithms of linearization generate the state space models which approximate the decoupled dynamics (longitudinal and lateral) of the aircraft. Then to test the viability of the linear models, 1,500 comparisons with the nonlinear dynamics have been done with a 100% rate of success. The study of stability allowed to highlight the need of control systems to improve first the performances of the plane, then to control its different axes. A methodology based on a coupling between a modern control technique (LQR) and a genetic algorithm is presented. This methodology allowed to find optimal and successful controllers which satisfy a large number of specifications. Besides being successful, they have to be robust to uncertainties owed to the variation of mass. Thus, an analysis of robustness using the theory of the guardian maps was applied to uncertain dynamics. However, because of a too sensitive region of the flight envelop, some analyses are biased. Nevertheless, a validation with the nonlinear dynamics allowed to prove the robustness of the controllers over the entire flight envelope. Finally, the last stage of this project concerned the control laws for the autopilot. Once again, the proposed methodology, bases itself on the association of flight mechanic equations, control theory and a metaheuristic optimization method. Afterward, four detailed test scenarios are presented to illustrate the efficiency and the robustness of the entire autopilot.

Bin Ratio-Based Histogram Distances and Their Application to Image Classification.

PubMed

Hu, Weiming; Xie, Nianhua; Hu, Ruiguang; Ling, Haibin; Chen, Qiang; Yan, Shuicheng; Maybank, Stephen

2014-12-01

Large variations in image background may cause partial matching and normalization problems for histogram-based representations, i.e., the histograms of the same category may have bins which are significantly different, and normalization may produce large changes in the differences between corresponding bins. In this paper, we deal with this problem by using the ratios between bin values of histograms, rather than bin values' differences which are used in the traditional histogram distances. We propose a bin ratio-based histogram distance (BRD), which is an intra-cross-bin distance, in contrast with previous bin-to-bin distances and cross-bin distances. The BRD is robust to partial matching and histogram normalization, and captures correlations between bins with only a linear computational complexity. We combine the BRD with the ℓ1 histogram distance and the χ(2) histogram distance to generate the ℓ1 BRD and the χ(2) BRD, respectively. These combinations exploit and benefit from the robustness of the BRD under partial matching and the robustness of the ℓ1 and χ(2) distances to small noise. We propose a method for assessing the robustness of histogram distances to partial matching. The BRDs and logistic regression-based histogram fusion are applied to image classification. The experimental results on synthetic data sets show the robustness of the BRDs to partial matching, and the experiments on seven benchmark data sets demonstrate promising results of the BRDs for image classification.

Statistics based sampling for controller and estimator design

NASA Astrophysics Data System (ADS)

Tenne, Dirk

The purpose of this research is the development of statistical design tools for robust feed-forward/feedback controllers and nonlinear estimators. This dissertation is threefold and addresses the aforementioned topics nonlinear estimation, target tracking and robust control. To develop statistically robust controllers and nonlinear estimation algorithms, research has been performed to extend existing techniques, which propagate the statistics of the state, to achieve higher order accuracy. The so-called unscented transformation has been extended to capture higher order moments. Furthermore, higher order moment update algorithms based on a truncated power series have been developed. The proposed techniques are tested on various benchmark examples. Furthermore, the unscented transformation has been utilized to develop a three dimensional geometrically constrained target tracker. The proposed planar circular prediction algorithm has been developed in a local coordinate framework, which is amenable to extension of the tracking algorithm to three dimensional space. This tracker combines the predictions of a circular prediction algorithm and a constant velocity filter by utilizing the Covariance Intersection. This combined prediction can be updated with the subsequent measurement using a linear estimator. The proposed technique is illustrated on a 3D benchmark trajectory, which includes coordinated turns and straight line maneuvers. The third part of this dissertation addresses the design of controller which include knowledge of parametric uncertainties and their distributions. The parameter distributions are approximated by a finite set of points which are calculated by the unscented transformation. This set of points is used to design robust controllers which minimize a statistical performance of the plant over the domain of uncertainty consisting of a combination of the mean and variance. The proposed technique is illustrated on three benchmark problems. The first relates to the design of prefilters for a linear and nonlinear spring-mass-dashpot system and the second applies a feedback controller to a hovering helicopter. Lastly, the statistical robust controller design is devoted to a concurrent feed-forward/feedback controller structure for a high-speed low tension tape drive.

Can early hepatic fibrosis stages be discriminated by combining ultrasonic parameters?

PubMed

Bouzitoune, Razika; Meziri, Mahmoud; Machado, Christiano Bittencourt; Padilla, Frédéric; Pereira, Wagner Coelho de Albuquerque

2016-05-01

In this study, we put forward a new approach to classify early stages of fibrosis based on a multiparametric characterization using backscatter ultrasonic signals. Ultrasonic parameters, such as backscatter coefficient (Bc), speed of sound (SoS), attenuation coefficient (Ac), mean scatterer spacing (MSS), and spectral slope (SS), have shown their potential to differentiate between healthy and pathologic samples in different organs (eye, breast, prostate, liver). Recently, our group looked into the characterization of stages of hepatic fibrosis using the parameters cited above. The results showed that none of them could individually distinguish between the different stages. Therefore, we explored a multiparametric approach by combining these parameters in two and three, to test their potential to discriminate between the stages of liver fibrosis: F0 (normal), F1, F3, and/without F4 (cirrhosis), according to METAVIR Score. Discriminant analysis showed that the most relevant individual parameter was Bc, followed by SoS, SS, MSS, and Ac. The combination of (Bc, SoS) along with the four stages was the best in differentiating between the stages of fibrosis and correctly classified 85% of the liver samples with a high level of significance (p<0.0001). Nevertheless, when taking into account only stages F0, F1, and F3, the discriminant analysis showed that the parameters (Bc, SoS) and (Bc, Ac) had a better classification (93%) with a high level of significance (p<0.0001). The combination of the three parameters (Bc, SoS, and Ac) led to a 100% correct classification. In conclusion, the current findings show that the multiparametric approach has great potential in differentiating between the stages of fibrosis, and thus could play an important role in the diagnosis and follow-up of hepatic fibrosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Chinese License Plates Recognition Method Based on A Robust and Efficient Feature Extraction and BPNN Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Ming; Xie, Fei; Zhao, Jing; Sun, Rui; Zhang, Lei; Zhang, Yue

2018-04-01

The prosperity of license plate recognition technology has made great contribution to the development of Intelligent Transport System (ITS). In this paper, a robust and efficient license plate recognition method is proposed which is based on a combined feature extraction model and BPNN (Back Propagation Neural Network) algorithm. Firstly, the candidate region of the license plate detection and segmentation method is developed. Secondly, a new feature extraction model is designed considering three sets of features combination. Thirdly, the license plates classification and recognition method using the combined feature model and BPNN algorithm is presented. Finally, the experimental results indicate that the license plate segmentation and recognition both can be achieved effectively by the proposed algorithm. Compared with three traditional methods, the recognition accuracy of the proposed method has increased to 95.7% and the consuming time has decreased to 51.4ms.

Pembrolizumab and Combination Chemotherapy in Treating Patients With Previously Untreated Diffuse Large B-cell Lymphoma or Grade 3b Follicular Lymphoma

ClinicalTrials.gov

2017-10-24

Composite Lymphoma; Grade 3b Follicular Lymphoma; Stage I Diffuse Large B-Cell Lymphoma; Stage I Follicular Lymphoma; Stage II Diffuse Large B-Cell Lymphoma; Stage II Follicular Lymphoma; Stage III Diffuse Large B-Cell Lymphoma; Stage III Follicular Lymphoma; Stage IV Diffuse Large B-Cell Lymphoma; Stage IV Follicular Lymphoma

Irinotecan Compared With Combination Chemotherapy in Treating Patients With Advanced Colorectal Cancer

ClinicalTrials.gov

2013-05-01

Mucinous Adenocarcinoma of the Colon; Mucinous Adenocarcinoma of the Rectum; Recurrent Colon Cancer; Recurrent Rectal Cancer; Signet Ring Adenocarcinoma of the Colon; Signet Ring Adenocarcinoma of the Rectum; Stage IIIA Colon Cancer; Stage IIIA Rectal Cancer; Stage IIIB Colon Cancer; Stage IIIB Rectal Cancer; Stage IIIC Colon Cancer; Stage IIIC Rectal Cancer; Stage IVA Colon Cancer; Stage IVA Rectal Cancer; Stage IVB Colon Cancer; Stage IVB Rectal Cancer

Seasonal variation in nutrient utilization shapes gut microbiome structure and function in wild giant pandas.

PubMed

Wu, Qi; Wang, Xiao; Ding, Yun; Hu, Yibo; Nie, Yonggang; Wei, Wei; Ma, Shuai; Yan, Li; Zhu, Lifeng; Wei, Fuwen

2017-09-13

Wild giant pandas use different parts of bamboo (shoots, leaves and stems) and different bamboo species at different times of the year. Their usage of bamboo can be classified temporally into a distinct leaf stage, shoot stage and transition stage. An association between this usage pattern and variation in the giant panda gut microbiome remains unknown. Here, we found associations using a gut metagenomic approach and nutritional analyses whereby diversity of the gut microbial community in the leaf and shoot stages was significantly different. Functional metagenomic analysis showed that in the leaf stage, bacteria species over-represented genes involved in raw fibre utilization and cell cycle control. Thus, raw fibre utilization by the gut microbiome was guaranteed during the nutrient-deficient leaf stage by reinforcing gut microbiome robustness. During the protein-abundant shoot stage, the functional capacity of the gut microbiome expanded to include prokaryotic secretion and signal transduction activity, suggesting active interactions between the gut microbiome and host. These results illustrate that seasonal nutrient variation in wild giant pandas substantially influences gut microbiome composition and function. Nutritional interactions between gut microbiomes and hosts appear to be complex and further work is needed. © 2017 The Author(s).

Rocket Based Combined Cycle (RBCC) engine inlet

NASA Technical Reports Server (NTRS)

2004-01-01

Pictured is a component of the Rocket Based Combined Cycle (RBCC) engine. This engine was designed to ultimately serve as the near term basis for Two Stage to Orbit (TSTO) air breathing propulsion systems and ultimately a Single Stage to Orbit (SSTO) air breathing propulsion system.

Incompressible SPH (ISPH) with fast Poisson solver on a GPU

NASA Astrophysics Data System (ADS)

Chow, Alex D.; Rogers, Benedict D.; Lind, Steven J.; Stansby, Peter K.

2018-05-01

This paper presents a fast incompressible SPH (ISPH) solver implemented to run entirely on a graphics processing unit (GPU) capable of simulating several millions of particles in three dimensions on a single GPU. The ISPH algorithm is implemented by converting the highly optimised open-source weakly-compressible SPH (WCSPH) code DualSPHysics to run ISPH on the GPU, combining it with the open-source linear algebra library ViennaCL for fast solutions of the pressure Poisson equation (PPE). Several challenges are addressed with this research: constructing a PPE matrix every timestep on the GPU for moving particles, optimising the limited GPU memory, and exploiting fast matrix solvers. The ISPH pressure projection algorithm is implemented as 4 separate stages, each with a particle sweep, including an algorithm for the population of the PPE matrix suitable for the GPU, and mixed precision storage methods. An accurate and robust ISPH boundary condition ideal for parallel processing is also established by adapting an existing WCSPH boundary condition for ISPH. A variety of validation cases are presented: an impulsively started plate, incompressible flow around a moving square in a box, and dambreaks (2-D and 3-D) which demonstrate the accuracy, flexibility, and speed of the methodology. Fragmentation of the free surface is shown to influence the performance of matrix preconditioners and therefore the PPE matrix solution time. The Jacobi preconditioner demonstrates robustness and reliability in the presence of fragmented flows. For a dambreak simulation, GPU speed ups demonstrate up to 10-18 times and 1.1-4.5 times compared to single-threaded and 16-threaded CPU run times respectively.

A Proinflammatory Function of Toll-Like Receptor 2 in the Retinal Pigment Epithelium as a Novel Target for Reducing Choroidal Neovascularization in Age-Related Macular Degeneration.

PubMed

Feng, Lili; Ju, Meihua; Lee, Kei Ying V; Mackey, Ashley; Evangelista, Mariasilvia; Iwata, Daiju; Adamson, Peter; Lashkari, Kameran; Foxton, Richard; Shima, David; Ng, Yin Shan

2017-10-01

Current treatments for choroidal neovascularization, a major cause of blindness for patients with age-related macular degeneration, treat symptoms but not the underlying causes of the disease. Inflammation has been strongly implicated in the pathogenesis of choroidal neovascularization. We examined the inflammatory role of Toll-like receptor 2 (TLR2) in age-related macular degeneration. TLR2 was robustly expressed by the retinal pigment epithelium in mouse and human eyes, both normal and with macular degeneration/choroidal neovascularization. Nuclear localization of NF-κB, a major downstream target of TLR2 signaling, was detected in the retinal pigment epithelium of human eyes, particularly in eyes with advanced stages of age-related macular degeneration. TLR2 antagonism effectively suppressed initiation and growth of spontaneous choroidal neovascularization in a mouse model, and the combination of anti-TLR2 and antivascular endothelial growth factor receptor 2 yielded an additive therapeutic effect on both area and number of spontaneous choroidal neovascularization lesions. Finally, in primary human fetal retinal pigment epithelium cells, ligand binding to TLR2 induced robust expression of proinflammatory cytokines, and end products of lipid oxidation had a synergistic effect on TLR2 activation. Our data illustrate a functional role for TLR2 in the pathogenesis of choroidal neovascularization, likely by promoting inflammation of the retinal pigment epithelium, and validate TLR2 as a novel therapeutic target for reducing choroidal neovascularization. Copyright © 2017 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Reliability of simulated robustness testing in fast liquid chromatography, using state-of-the-art column technology, instrumentation and modelling software.

PubMed

Kormány, Róbert; Fekete, Jenő; Guillarme, Davy; Fekete, Szabolcs

2014-02-01

The goal of this study was to evaluate the accuracy of simulated robustness testing using commercial modelling software (DryLab) and state-of-the-art stationary phases. For this purpose, a mixture of amlodipine and its seven related impurities was analyzed on short narrow bore columns (50×2.1mm, packed with sub-2μm particles) providing short analysis times. The performance of commercial modelling software for robustness testing was systematically compared to experimental measurements and DoE based predictions. We have demonstrated that the reliability of predictions was good, since the predicted retention times and resolutions were in good agreement with the experimental ones at the edges of the design space. In average, the retention time relative errors were <1.0%, while the predicted critical resolution errors were comprised between 6.9 and 17.2%. Because the simulated robustness testing requires significantly less experimental work than the DoE based predictions, we think that robustness could now be investigated in the early stage of method development. Moreover, the column interchangeability, which is also an important part of robustness testing, was investigated considering five different C8 and C18 columns packed with sub-2μm particles. Again, thanks to modelling software, we proved that the separation was feasible on all columns within the same analysis time (less than 4min), by proper adjustments of variables. Copyright © 2013 Elsevier B.V. All rights reserved.

Rituximab and Combination Chemotherapy in Treating Patients With Previously Untreated High- or High-Intermediate-Risk Diffuse Large B-Cell Lymphoma

ClinicalTrials.gov

2016-03-01

Contiguous Stage II Adult Diffuse Large Cell Lymphoma; Noncontiguous Stage II Adult Diffuse Large Cell Lymphoma; Stage I Adult Diffuse Large Cell Lymphoma; Stage III Adult Diffuse Large Cell Lymphoma; Stage IV Adult Diffuse Large Cell Lymphoma

Combination Chemotherapy and Surgery in Treating Young Patients With Wilms Tumor

ClinicalTrials.gov

2018-06-19

Adult Kidney Wilms Tumor; Beckwith-Wiedemann Syndrome; Childhood Kidney Wilms Tumor; Diffuse Hyperplastic Perilobar Nephroblastomatosis; Hemihypertrophy; Rhabdoid Tumor of the Kidney; Stage I Kidney Wilms Tumor; Stage II Kidney Wilms Tumor; Stage III Kidney Wilms Tumor; Stage IV Kidney Wilms Tumor; Stage V Kidney Wilms Tumor

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.

An advancing front Delaunay triangulation algorithm designed for robustness

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.

1992-01-01

A new algorithm is described for generating an unstructured mesh about an arbitrary two-dimensional configuration. Mesh points are generated automatically by the algorithm in a manner which ensures a smooth variation of elements, and the resulting triangulation constitutes the Delaunay triangulation of these points. The algorithm combines the mathematical elegance and efficiency of Delaunay triangulation algorithms with the desirable point placement features, boundary integrity, and robustness traditionally associated with advancing-front-type mesh generation strategies. The method offers increased robustness over previous algorithms in that it cannot fail regardless of the initial boundary point distribution and the prescribed cell size distribution throughout the flow-field.

Automated tumour boundary delineation on 18F-FDG PET images using active contour coupled with shifted-optimal thresholding method

NASA Astrophysics Data System (ADS)

Khamwan, Kitiwat; Krisanachinda, Anchali; Pluempitiwiriyawej, Charnchai

2012-10-01

This study presents an automatic method to trace the boundary of the tumour in positron emission tomography (PET) images. It has been discovered that Otsu's threshold value is biased when the within-class variances between the object and the background are significantly different. To solve the problem, a double-stage threshold search that minimizes the energy between the first Otsu's threshold and the maximum intensity value is introduced. Such shifted-optimal thresholding is embedded into a region-based active contour so that both algorithms are performed consecutively. The efficiency of the method is validated using six sphere inserts (0.52-26.53 cc volume) of the IEC/2001 torso phantom. Both spheres and phantom were filled with 18F solution with four source-to-background ratio (SBR) measurements of PET images. The results illustrate that the tumour volumes segmented by combined algorithm are of higher accuracy than the traditional active contour. The method had been clinically implemented in ten oesophageal cancer patients. The results are evaluated and compared with the manual tracing by an experienced radiation oncologist. The advantage of the algorithm is the reduced erroneous delineation that improves the precision and accuracy of PET tumour contouring. Moreover, the combined method is robust, independent of the SBR threshold-volume curves, and it does not require prior lesion size measurement.

Practical considerations in clinical strategy to support the development of injectable drug-device combination products for biologics.

PubMed

Li, Zhaoyang; Easton, Rachael

2018-01-01

The development of an injectable drug-device combination (DDC) product for biologics is an intricate and evolving process that requires substantial investments of time and money. Consequently, the commercial dosage form(s) or presentation(s) are often not ready when pivotal trials commence, and it is common to have drug product changes (manufacturing process or presentation) during clinical development. A scientifically sound and robust bridging strategy is required in order to introduce these changes into the clinic safely. There is currently no single developmental paradigm, but a risk-based hierarchical approach has been well accepted. The rigor required of a bridging package depends on the level of risk associated with the changes. Clinical pharmacokinetic/pharmacodynamic comparability or outcome studies are only required when important changes occur at a late stage. Moreover, an injectable DDC needs to be user-centric, and usability assessment in real-world clinical settings may be required to support the approval of a DDC. In this review, we discuss the common issues during the manufacturing process and presentation development of an injectable DDC and practical considerations in establishing a clinical strategy to address these issues, including key elements of clinical studies. We also analyze the current practice in the industry and review relevant and status of regulatory guidance in the DDC field.

The potential impact of a prophylactic vaccine for human papillomavirus on the current cervical screening programme in Hong Kong.

PubMed

Koljonen, Paul A

2007-08-01

To review and summarise current controversies in cervical screening in Hong Kong and discuss the potential impact of prophylactic human papillomavirus vaccination. Literature search of Medline to December 2006, the Hong Kong Cancer Registry, and Centre of Disease Control. Key words search terms were: 'human papillomavirus', 'vaccine', 'cervical cancer', 'screening programme', and 'Hong Kong'. Original articles, review papers, books, and the worldwide web. Cervical cancer is one of the most common cancers in Hong Kong, and can be prevented if detected at its pre-cancerous stage. Despite the huge disease burden this imposes on our society and robust advocacy by the academic sector, an appropriate screening programme is still not in place. Existence of a vaccine that could potentially reduce the costs of universal screening should prompt our government to re-consider subsidising such a programme. While a combined screening-vaccination programme may be more cost-effective than screening alone, the vaccine is still costly, and the government must consider all the pros and cons. The new human papillomavirus vaccine, combined with an organised screening programme, is probably a more cost-effective way of preventing morbidity and mortality due to cervical cancer than the current programme in Hong Kong. More research and cost-effectiveness analyses are needed to decide on the ideal ages for primary vaccination and the requirement for booster shots.

Practical considerations in clinical strategy to support the development of injectable drug-device combination products for biologics

PubMed Central

Easton, Rachael

2018-01-01

ABSTRACT The development of an injectable drug-device combination (DDC) product for biologics is an intricate and evolving process that requires substantial investments of time and money. Consequently, the commercial dosage form(s) or presentation(s) are often not ready when pivotal trials commence, and it is common to have drug product changes (manufacturing process or presentation) during clinical development. A scientifically sound and robust bridging strategy is required in order to introduce these changes into the clinic safely. There is currently no single developmental paradigm, but a risk-based hierarchical approach has been well accepted. The rigor required of a bridging package depends on the level of risk associated with the changes. Clinical pharmacokinetic/pharmacodynamic comparability or outcome studies are only required when important changes occur at a late stage. Moreover, an injectable DDC needs to be user-centric, and usability assessment in real-world clinical settings may be required to support the approval of a DDC. In this review, we discuss the common issues during the manufacturing process and presentation development of an injectable DDC and practical considerations in establishing a clinical strategy to address these issues, including key elements of clinical studies. We also analyze the current practice in the industry and review relevant and status of regulatory guidance in the DDC field. PMID:29035675

Application of Phase Shifted, Laser Feedback Interferometry to Fluid Physics

NASA Technical Reports Server (NTRS)

Ovryn, Ben; Eppell, Steven J.; Andrews, James H.; Khaydarov, John

1996-01-01

We have combined the principles of phase-shifting interferometry (PSI) and laser-feedback interferometry (LFI) to produce a new instrument that can measure both optical path length (OPL) changes and discern sample reflectivity variations. In LFI, coherent feedback of the incident light either reflected directly from a surface or reflected after transmission through a region of interest will modulate the output intensity of the laser. LFI can yield a high signal-to-noise ratio even for low reflectivity samples. By combining PSI and LFI, we have produced a robust instrument, based upon a HeNe laser, with high dynamic range that can be used to measure either static (dc) or oscillatory changes along the optical path. As with other forms of interferometry, large changes in OPL require phase unwrapping. Conversely, small phase changes are limited by the fraction of a fringe that can be measured. We introduce the phase shifts with an electro-optic modulator (EOM) and use either the Carre or Hariharan algorithms to determine the phase and visibility. We have determined the accuracy and precision of our technique by measuring both the bending of a cantilevered piezoelectric bimorph and linear ramps to the EOM. Using PSI, sub-nanometer displacements can be measured. We have combined our interferometer with a commercial microscope and scanning piezoelectric stage and have measured the variation in OPL and visibility for drops of PDMS (silicone oil) on coated single crystal silicon. Our measurement of the static contact angle agrees with the value of 68 deg stated in the literature.

Towards robust optimal design of storm water systems

NASA Astrophysics Data System (ADS)

Marquez Calvo, Oscar; Solomatine, Dimitri

2015-04-01

In this study the focus is on the design of a storm water or a combined sewer system. Such a system should be capable to handle properly most of the storm to minimize the damages caused by flooding due to the lack of capacity of the system to cope with rain water at peak times. This problem is a multi-objective optimization problem: we have to take into account the minimization of the construction costs, the minimization of damage costs due to flooding, and possibly other criteria. One of the most important factors influencing the design of storm water systems is the expected amount of water to deal with. It is common that this infrastructure is developed with the capacity to cope with events that occur once in, say 10 or 20 years - so-called design rainfall events. However, rainfall is a random variable and such uncertainty typically is not taken explicitly into account in optimization. Rainfall design data is based on historical information of rainfalls, but many times this data is based on unreliable measures; or in not enough historical information; or as we know, the patterns of rainfall are changing regardless of historical information. There are also other sources of uncertainty influencing design, for example, leakages in the pipes and accumulation of sediments in pipes. In the context of storm water or combined sewer systems design or rehabilitation, robust optimization technique should be able to find the best design (or rehabilitation plan) within the available budget but taking into account uncertainty in those variables that were used to design the system. In this work we consider various approaches to robust optimization proposed by various authors (Gabrel, Murat, Thiele 2013; Beyer, Sendhoff 2007) and test a novel method ROPAR (Solomatine 2012) to analyze robustness. References Beyer, H.G., & Sendhoff, B. (2007). Robust optimization - A comprehensive survey. Comput. Methods Appl. Mech. Engrg., 3190-3218. Gabrel, V.; Murat, C., Thiele, A. (2014). Recent advances in robust optimization: An overview. European Journal of Operational Research. 471-483. Solomatine, D.P. (2012). Robust Optimization and Probabilistic Analysis of Robustness (ROPAR). http://www.unesco-ihe.org/hi/sol/papers/ ROPAR.pdf.

Functional vascular smooth muscle cells derived from human induced pluripotent stem cells via mesenchymal stem cell intermediates

PubMed Central

Bajpai, Vivek K.; Mistriotis, Panagiotis; Loh, Yuin-Han; Daley, George Q.; Andreadis, Stelios T.

2012-01-01

Aims Smooth muscle cells (SMC) play an important role in vascular homeostasis and disease. Although adult mesenchymal stem cells (MSC) have been used as a source of contractile SMC, they suffer from limited proliferation potential and culture senescence, particularly when originating from older donors. By comparison, human induced pluripotent stem cells (hiPSC) can provide an unlimited source of functional SMC for autologous cell-based therapies and for creating models of vascular disease. Our goal was to develop an efficient strategy to derive functional, contractile SMC from hiPSC. Methods and results We developed a robust, stage-wise, feeder-free strategy for hiPSC differentiation into functional SMC through an intermediate stage of multipotent MSC, which could be coaxed to differentiate into fat, bone, cartilage, and muscle. At this stage, the cells were highly proliferative and displayed higher clonogenic potential and reduced senescence when compared with parental hair follicle mesenchymal stem cells. In addition, when exposed to differentiation medium, the myogenic proteins such as α-smooth muscle actin, calponin, and myosin heavy chain were significantly upregulated and displayed robust fibrillar organization, suggesting the development of a contractile phenotype. Indeed, tissue constructs prepared from these cells exhibited high levels of contractility in response to receptor- and non-receptor-mediated agonists. Conclusion We developed an efficient stage-wise strategy that enabled hiPSC differentiation into contractile SMC through an intermediate population of clonogenic and multipotent MSC. The high yield of MSC and SMC derivation suggests that our strategy may facilitate an acquisition of the large numbers of cells required for regenerative medicine or for studying vascular disease pathophysiology. PMID:22941255

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.

Exploratory Study of 4D Versus 3D Robust Optimization in Intensity-Modulated Proton Therapy for Lung Cancer

PubMed Central

Liu, Wei; Schild, Steven E.; Chang, Joe Y.; Liao, Zhongxing; Chang, Yu-Hui; Wen, Zhifei; Shen, Jiajian; Stoker, Joshua B.; Ding, Xiaoning; Hu, Yanle; Sahoo, Narayan; Herman, Michael G.; Vargas, Carlos; Keole, Sameer; Wong, William; Bues, Martin

2015-01-01

Background To compare the impact of uncertainties and interplay effect on 3D and 4D robustly optimized intensity-modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study. Methods IMPT plans were created for 11 non-randomly selected non-small-cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D CTs to irradiate clinical target volume (CTV). Regular fractionation (66 Gy[RBE] in 33 fractions) were considered. In 4D optimization, the CTV of individual phases received non-uniform doses to achieve a uniform cumulative dose. The root-mean-square-dose volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed-rank test. Results 4D robust optimization plans led to smaller AUC for CTV (14.26 vs. 18.61 (p=0.001), better CTV coverage (Gy[RBE]) [D95% CTV: 60.6 vs 55.2 (p=0.001)], and better CTV homogeneity [D5%–D95% CTV: 10.3 vs 17.7 (p=0.002)] in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage [D95% CTV: 64.5 vs 63.8 (p=0.0068)], comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients. Conclusions Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions. PMID:26725727

Combination Chemotherapy, Radiation Therapy, and/or Surgery in Treating Patients With High-Risk Kidney Tumors

ClinicalTrials.gov

2017-06-22

Childhood Renal Cell Carcinoma; Clear Cell Renal Cell Carcinoma; Clear Cell Sarcoma of the Kidney; Papillary Renal Cell Carcinoma; Rhabdoid Tumor of the Kidney; Stage I Renal Cell Cancer; Stage I Renal Wilms Tumor; Stage II Renal Cell Cancer; Stage II Renal Wilms Tumor; Stage III Renal Cell Cancer; Stage III Renal Wilms Tumor; Stage IV Renal Cell Cancer; Stage IV Renal Wilms Tumor

Phase I Study of Intravenous Triapine (IND # 68338) in Combination With Pelvic Radiation Therapy With or Without Weekly Intravenous Cisplatin Chemotherapy for Locally Advanced Cervical, Vaginal, or Pelvic Gynecologic Malignancies

ClinicalTrials.gov

2013-01-10

Recurrent Cervical Cancer; Recurrent Ovarian Epithelial Cancer; Recurrent Vaginal Cancer; Recurrent Vulvar Cancer; Stage III Vaginal Cancer; Stage IIIA Cervical Cancer; Stage IIIA Ovarian Epithelial Cancer; Stage IIIA Vulvar Cancer; Stage IIIB Cervical Cancer; Stage IIIB Ovarian Epithelial Cancer; Stage IIIB Vulvar Cancer; Stage IIIC Ovarian Epithelial Cancer; Stage IIIC Vulvar Cancer; Stage IV Ovarian Epithelial Cancer; Stage IVA Cervical Cancer; Stage IVA Vaginal Cancer; Stage IVB Cervical Cancer; Stage IVB Vaginal Cancer

Bevacizumab and Combination Chemotherapy Before Surgery in Treating Patients With Locally Advanced Esophageal or Stomach Cancer

ClinicalTrials.gov

2018-02-23

Adenocarcinoma of the Esophagus; Adenocarcinoma of the Gastroesophageal Junction; Diffuse Adenocarcinoma of the Stomach; Intestinal Adenocarcinoma of the Stomach; Mixed Adenocarcinoma of the Stomach; Squamous Cell Carcinoma of the Esophagus; Stage IA Esophageal Cancer; Stage IA Gastric Cancer; Stage IB Esophageal Cancer; Stage IB Gastric Cancer; Stage IIA Esophageal Cancer; Stage IIA Gastric Cancer; Stage IIB Esophageal Cancer; Stage IIB Gastric Cancer; Stage IIIA Esophageal Cancer; Stage IIIA Gastric Cancer; Stage IIIB Esophageal Cancer; Stage IIIB Gastric Cancer; Stage IIIC Esophageal Cancer; Stage IIIC Gastric Cancer

Histology-based Combination Induction Chemotherapy for Elderly Patients with Clinical Stage III Non-small Cell Lung Cancer.

PubMed

Banna, Giuseppe L; Parra, Hector Josè Soto; Castaing, Marine; Dieci, Maria Vittoria; Anile, Giuseppe; Nicolosi, Maurizio; Strano, Salvatore; Marletta, Francesco; Guarneri, Valentina; Conte, Pierfranco; Lal, Rohit

2017-07-01

To explore the feasibility and activity of a histology-based induction combination chemotherapy for elderly patients with clinical stage III non-small cell lung cancer (NSCLC). Patients aged ≥70 years with stage IIIA and IIIB lung squamous cell carcinoma (SCC) or adenocarcinoma were treated with three cycles of carboplatin and gemcitabine or pemetrexed, respectively, followed by definitive radiotherapy or surgery. The primary endpoint was the overall response rate (ORR) following induction. Twenty-seven patients, with a median age of 74 years (range=70-80 years) were treated for adenocarcinoma in 14 (52%) and SCC in 13 (48%), clinical stage IIIA in eight (30%) and IIIB in 19 (70%). Grade 3 or 4 toxicity was reported for five patients (18.5%). The ORR was 46% in 12 (partial responses) out of 26 assessable patients. Histology-based induction combination chemotherapy is active and feasible in elderly patients with stage III NSCLC. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The Snowmastodon Project: A view of the Last Interglacial Period from high in the Colorado Rockies

USGS Publications Warehouse

Pigati, Jeffery S.

2015-01-01

In North America, terrestrial records of biodiversity and climate change that span the Last Interglacial Period [or Marine Oxygen Isotope Stage (MIS) 5] are rare. In 2010-11, construction at Ziegler Reservoir near Snowmass Village, Colorado revealed a lacustrine/wetland sedimentary sequence that preserved evidence of past plant communities between ~140 and 55 ka, including all of MIS 5. At an elevation of 2705 m, the Ziegler Reservoir fossil site (ZRFS) also contained thousands of well-preserved bones and teeth of Pleistocene megafauna, including mastodons, mammoths, ground sloths, horses, camels, deer, bison, black bear, coyotes, and bighorn sheep. In addition, the site contained more than 26,000 bones from at least 30 species of small animals, including salamanders, otters, muskrats, minks, rabbits, beavers, frogs, lizards, snakes, fish, and birds. The combination of macro- and micro-vertebrates, invertebrates, terrestrial and aquatic plant macrofossils, a detailed pollen record, and a robust, directly dated stratigraphic framework, shows that high-elevation ecosystems in the Rocky Mountains of Colorado are climatically sensitive and varied dramatically throughout MIS 5.

Influence Function Learning in Information Diffusion Networks

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data. PMID:25973445

Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex

PubMed Central

Nir, Yuval; Mukamel, Roy; Dinstein, Ilan; Privman, Eran; Harel, Michal; Fisch, Lior; Gelbard-Sagiv, Hagar; Kipervasser, Svetlana; Andelman, Fani; Neufeld, Miri Y; Kramer, Uri; Arieli, Amos; Fried, Itzhak; Malach, Rafael

2009-01-01

Animal studies have shown robust electrophysiological activity in the sensory cortex in the absence of stimuli or tasks. Similarly, recent human functional magnetic resonance imaging (fMRI) revealed widespread, spontaneously emerging cortical fluctuations. However, it is unknown what neuronal dynamics underlie this spontaneous activity in the human brain. Here we studied this issue by combining bilateral single-unit, local field potentials (LFPs) and intracranial electrocorticography (ECoG) recordings in individuals undergoing clinical monitoring. We found slow (<0.1 Hz, following 1/f-like profiles) spontaneous fluctuations of neuronal activity with significant interhemispheric correlations. These fluctuations were evident mainly in neuronal firing rates and in gamma (40–100 Hz) LFP power modulations. Notably, the interhemispheric correlations were enhanced during rapid eye movement and stage 2 sleep. Multiple intracranial ECoG recordings revealed clear selectivity for functional networks in the spontaneous gamma LFP power modulations. Our results point to slow spontaneous modulations in firing rate and gamma LFP as the likely correlates of spontaneous fMRI fluctuations in the human sensory cortex. PMID:19160509

Multi-strategy coevolving aging particle optimization.

PubMed

Iacca, Giovanni; Caraffini, Fabio; Neri, Ferrante

2014-02-01

We propose Multi-Strategy Coevolving Aging Particles (MS-CAP), a novel population-based algorithm for black-box optimization. In a memetic fashion, MS-CAP combines two components with complementary algorithm logics. In the first stage, each particle is perturbed independently along each dimension with a progressively shrinking (decaying) radius, and attracted towards the current best solution with an increasing force. In the second phase, the particles are mutated and recombined according to a multi-strategy approach in the fashion of the ensemble of mutation strategies in Differential Evolution. The proposed algorithm is tested, at different dimensionalities, on two complete black-box optimization benchmarks proposed at the Congress on Evolutionary Computation 2010 and 2013. To demonstrate the applicability of the approach, we also test MS-CAP to train a Feedforward Neural Network modeling the kinematics of an 8-link robot manipulator. The numerical results show that MS-CAP, for the setting considered in this study, tends to outperform the state-of-the-art optimization algorithms on a large set of problems, thus resulting in a robust and versatile optimizer.

Evaluation of nonlinear impact resonance spectroscopy method for detecting delayed ettringite formation

NASA Astrophysics Data System (ADS)

Rashidi, M. M. N.; Paul, A.; Kim, J.-Y.; Jacobs, L. J.; Kurtis, K. E.

2015-03-01

The use of the Nonlinear Impact Resonance Acoustic Spectroscopy (NIRAS) method to monitor the evolution of damage due to delayed ettringite formation (DEF) is examined. In practice, the temperature of concrete during casting of precast concrete members or massive concrete structures may reach higher than 70°C which can provide suitable conditions for damage to occur due to DEF, particularly in concrete which is subsequently exposed to wet environments. While expansion - often in excess of 1% - is characteristic of DEF, the evolution of damage begins with microcracking. Unfortunately, there is no standard to test the susceptibility of materials or material combinations to DEF. On the other hand, NIRAS shows great sensitivity to the detection of microcracks and has been successfully applied to concrete to detect thermal and alkali silica reaction in concrete. In this preliminary research, the NIRAS method is used to discriminate among mortar samples which are relatively undamaged and those in the early stages of DEF. The results show that NIRAS could be a reliable and robust method in the detection of microcracks due to DEF.

Using genetically modified tomato crop plants with purple leaves for absolute weed/crop classification.

PubMed

Lati, Ran N; Filin, Sagi; Aly, Radi; Lande, Tal; Levin, Ilan; Eizenberg, Hanan

2014-07-01

Weed/crop classification is considered the main problem in developing precise weed-management methodologies, because both crops and weeds share similar hues. Great effort has been invested in the development of classification models, most based on expensive sensors and complicated algorithms. However, satisfactory results are not consistently obtained due to imaging conditions in the field. We report on an innovative approach that combines advances in genetic engineering and robust image-processing methods to detect weeds and distinguish them from crop plants by manipulating the crop's leaf color. We demonstrate this on genetically modified tomato (germplasm AN-113) which expresses a purple leaf color. An autonomous weed/crop classification is performed using an invariant-hue transformation that is applied to images acquired by a standard consumer camera (visible wavelength) and handles variations in illumination intensities. The integration of these methodologies is simple and effective, and classification results were accurate and stable under a wide range of imaging conditions. Using this approach, we simplify the most complicated stage in image-based weed/crop classification models. © 2013 Society of Chemical Industry.

Experimental testing of a foam/multilayer insulation (FMLI) thermal control system (TCS) for use on a cryogenic upper stage

NASA Astrophysics Data System (ADS)

Hastings, Leon J.; Martin, James J.

1998-01-01

An 18-m3 system-level test bed termed the Multipurpose Hydrogen Test Bed (MHTB has been used to evaluate a foam/multilayer combination insulation concept. The foam element (Isofoam SS-1171) protects against ground hold/ascent flight environments, and allows the use of dry nitrogen purge as opposed to a more complex/heavy helium purge subsystem. The MLI (45 layers of Double Aluminized Mylar with Dacron spacers) is designed for an on-orbit storage period of 45 days. Unique MLI features included; a variable layer density (reduces weight and radiation losses), larger but fewer DAM vent perforations (reduces radiation losses), and a roll wrap installation which resulted in a very robust MLI and reduced both assembly man-hours and seam heat leak. Ground hold testing resulted in an average heat leak of 63 W/m2 and purge gas liquefaction was successfully prevented. The orbit hold simulation produced a heat leak of 0.22 W/m2 with 305 K boundary which, compared to historical data, represents a 50-percent heat leak reduction.

Microfluidic guillotine for single-cell wound repair studies

NASA Astrophysics Data System (ADS)

Blauch, Lucas R.; Gai, Ya; Khor, Jian Wei; Sood, Pranidhi; Marshall, Wallace F.; Tang, Sindy K. Y.

2017-07-01

Wound repair is a key feature distinguishing living from nonliving matter. Single cells are increasingly recognized to be capable of healing wounds. The lack of reproducible, high-throughput wounding methods has hindered single-cell wound repair studies. This work describes a microfluidic guillotine for bisecting single Stentor coeruleus cells in a continuous-flow manner. Stentor is used as a model due to its robust repair capacity and the ability to perform gene knockdown in a high-throughput manner. Local cutting dynamics reveals two regimes under which cells are bisected, one at low viscous stress where cells are cut with small membrane ruptures and high viability and one at high viscous stress where cells are cut with extended membrane ruptures and decreased viability. A cutting throughput up to 64 cells per minute—more than 200 times faster than current methods—is achieved. The method allows the generation of more than 100 cells in a synchronized stage of their repair process. This capacity, combined with high-throughput gene knockdown in Stentor, enables time-course mechanistic studies impossible with current wounding methods.

Junior temperament character inventory together with quantitative EEG discriminate children with attention deficit hyperactivity disorder combined subtype from children with attention deficit hyperactivity disorder combined subtype plus oppositional defiant disorder.

PubMed

Chiarenza, Giuseppe A; Villa, Stefania; Galan, Lidice; Valdes-Sosa, Pedro; Bosch-Bayard, Jorge

2018-05-19

Oppositional defiant disorder (ODD) is frequently associated with Attention Deficit Hyperactivity Disorder (ADHD) but no clear neurophysiological evidence exists that distinguishes the two groups. Our aim was to identify biomarkers that distinguish children with Attention Deficit Hyperactivity Disorder combined subtype (ADHD_C) from children with ADHD_C + ODD, by combining the results of quantitative EEG (qEEG) and the Junior Temperament Character Inventory (JTCI). 28 ADHD_C and 22 ADHD_C + ODD children who met the DSMV criteria participated in the study. JTCI and EEG were analyzed. Stability based Biomarkers identification methodology was applied to the JTCI and the qEEG separately and combined. The qEEG was tested at the scalp and the sources levels. The classification power of the selected biomarkers was tested with a robust ROC technique. The best discriminant power was obtained when TCI and qEEG were analyzed together. Novelty seeking, self-directedness and cooperativeness were selected as biomarkers together with F4 and Cz in Delta; Fz and F4 in Theta and F7 and F8 in Beta, with a robust AUC of 0.95 for the ROC. At sources level: the regions were the right lateral and medial orbito-frontal cortex, cingular region, angular gyrus, right inferior occipital gyrus, occipital pole and the left insula in Theta, Alpha and Beta. The robust estimate of the total AUC was 0.91. These structures are part of extensive networks of novelty seeking, self-directedness and cooperativeness systems that seem dysregulated in these children. These methods represent an original approach to associate differences of personality and behavior to specific neuronal systems and subsystems. Copyright © 2018 Elsevier B.V. All rights reserved.

A regulatory sequence from the retinoid X receptor γ gene directs expression to horizontal cells and photoreceptors in the embryonic chicken retina.

PubMed

Blixt, Maria K E; Hallböök, Finn

2016-01-01

Combining techniques of episomal vector gene-specific Cre expression and genomic integration using the piggyBac transposon system enables studies of gene expression-specific cell lineage tracing in the chicken retina. In this work, we aimed to target the retinal horizontal cell progenitors. A 208 bp gene regulatory sequence from the chicken retinoid X receptor γ gene (RXRγ208) was used to drive Cre expression. RXRγ is expressed in progenitors and photoreceptors during development. The vector was combined with a piggyBac "donor" vector containing a floxed STOP sequence followed by enhanced green fluorescent protein (EGFP), as well as a piggyBac helper vector for efficient integration into the host cell genome. The vectors were introduced into the embryonic chicken retina with in ovo electroporation. Tissue electroporation targets specific developmental time points and in specific structures. Cells that drove Cre expression from the regulatory RXRγ208 sequence excised the floxed STOP-sequence and expressed GFP. The approach generated a stable lineage with robust expression of GFP in retinal cells that have activated transcription from the RXRγ208 sequence. Furthermore, GFP was expressed in cells that express horizontal or photoreceptor markers when electroporation was performed between developmental stages 22 and 28. Electroporation of a stage 12 optic cup gave multiple cell types in accordance with RXRγ gene expression in the early retina. In this study, we describe an easy, cost-effective, and time-efficient method for testing regulatory sequences in general. More specifically, our results open up the possibility for further studies of the RXRγ-gene regulatory network governing the formation of photoreceptor and horizontal cells. In addition, the method presents approaches to target the expression of effector genes, such as regulators of cell fate or cell cycle progression, to these cells and their progenitor.

Does aggressive surgical resection improve survival in advanced stage 3 and 4 neuroblastoma? A systematic review and meta-analysis.

PubMed

Mullassery, Dhanya; Farrelly, Paul; Losty, Paul D

2014-11-01

The role of surgery in the management of advanced staged neuroblastoma (NBL) is controversial. A systematic review and meta-analysis is reported to address robust evidence for curative "gross total tumor resection" (GTR) in Stage 3 and Stage 4 neuroblastoma. Studies were identified using Medline, Embase, and Cochrane databases using pre-specified search terms. Primary outcomes were 5-year overall (OS) and disease-free survival (DFS) after GTR and subtotal resection (STR) in Stage 3 or 4 NBL. Data were analyzed using Review Manager. The Mantel-Haenszel method and a random effects model was utilized to calculate odds ratios (95% CI). Fifteen studies (five Stage 3 and 13 Stage 4) met full inclusion criteria. The pooled odds ratio for 5 year OS in Stage 3 following GTR compared to STR was 2.4 (95% CI 1.19-4.85). In Stage 4 disease, the pooled odds ratio for 5 year overall survival (OS) following GTR compared to STR was 1.65 (95% CI 0.96-1.91); a pooled odds ratio for 5 year DFS following GTR compared to STR was 1.55 (95% CI 1.12-2.14). A clear survival benefit is shown for GTR over STR in Stage 3 NBL only. Though some advantage can be demonstrated for GTR as defined by DFS in Stage 4 NBL GTR did not significantly improve OS in Stage 4 disease.

What can we learn from fitness landscapes?

PubMed

Hartl, Daniel L

2014-10-01

A combinatorially complete data set consists of studies of all possible combinations of a set of mutant sites in a gene or mutant alleles in a genome. Among the most robust conclusions from these studies is that epistasis between beneficial mutations often shows a pattern of diminishing returns, in which favorable mutations are less fit when combined than would be expected. Another robust inference is that the number of adaptive evolutionary paths is often limited to a relatively small fraction of the theoretical possibilities, owing largely to sign epistasis requiring evolutionary steps that would entail a decrease in fitness. Here we summarize these and other results while also examining issues that remain unresolved and future directions that seem promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

A novel methodology for building robust design rules by using design based metrology (DBM)

NASA Astrophysics Data System (ADS)

Lee, Myeongdong; Choi, Seiryung; Choi, Jinwoo; Kim, Jeahyun; Sung, Hyunju; Yeo, Hyunyoung; Shim, Myoungseob; Jin, Gyoyoung; Chung, Eunseung; Roh, Yonghan

2013-03-01

This paper addresses a methodology for building robust design rules by using design based metrology (DBM). Conventional method for building design rules has been using a simulation tool and a simple pattern spider mask. At the early stage of the device, the estimation of simulation tool is poor. And the evaluation of the simple pattern spider mask is rather subjective because it depends on the experiential judgment of an engineer. In this work, we designed a huge number of pattern situations including various 1D and 2D design structures. In order to overcome the difficulties of inspecting many types of patterns, we introduced Design Based Metrology (DBM) of Nano Geometry Research, Inc. And those mass patterns could be inspected at a fast speed with DBM. We also carried out quantitative analysis on PWQ silicon data to estimate process variability. Our methodology demonstrates high speed and accuracy for building design rules. All of test patterns were inspected within a few hours. Mass silicon data were handled with not personal decision but statistical processing. From the results, robust design rules are successfully verified and extracted. Finally we found out that our methodology is appropriate for building robust design rules.

Info-Gap robustness pathway method for transitioning of urban drainage systems under deep uncertainties.

PubMed

Zischg, Jonatan; Goncalves, Mariana L R; Bacchin, Taneha Kuzniecow; Leonhardt, Günther; Viklander, Maria; van Timmeren, Arjan; Rauch, Wolfgang; Sitzenfrei, Robert

2017-09-01

In the urban water cycle, there are different ways of handling stormwater runoff. Traditional systems mainly rely on underground piped, sometimes named 'gray' infrastructure. New and so-called 'green/blue' ambitions aim for treating and conveying the runoff at the surface. Such concepts are mainly based on ground infiltration and temporal storage. In this work a methodology to create and compare different planning alternatives for stormwater handling on their pathways to a desired system state is presented. Investigations are made to assess the system performance and robustness when facing the deeply uncertain spatial and temporal developments in the future urban fabric, including impacts caused by climate change, urbanization and other disruptive events, like shifts in the network layout and interactions of 'gray' and 'green/blue' structures. With the Info-Gap robustness pathway method, three planning alternatives are evaluated to identify critical performance levels at different stages over time. This novel methodology is applied to a real case study problem where a city relocation process takes place during the upcoming decades. In this case study it is shown that hybrid systems including green infrastructures are more robust with respect to future uncertainties, compared to traditional network design.

Robust, synergistic regulation of human gene expression using TALE activators.

PubMed

Maeder, Morgan L; Linder, Samantha J; Reyon, Deepak; Angstman, James F; Fu, Yanfang; Sander, Jeffry D; Joung, J Keith

2013-03-01

Artificial activators designed using transcription activator-like effector (TALE) technology have broad utility, but previous studies suggest that these monomeric proteins often exhibit low activities. Here we demonstrate that TALE activators can robustly function individually or in synergistic combinations to increase expression of endogenous human genes over wide dynamic ranges. These findings will encourage applications of TALE activators for research and therapy, and guide design of monomeric TALE-based fusion proteins.

In Vitro Activities of Primaquine-Schizonticide Combinations on Asexual Blood Stages and Gametocytes of Plasmodium falciparum

PubMed Central

Cabrera, Mynthia

2015-01-01

Currently, the World Health Organization recommends addition of a 0.25-mg base/kg single dose of primaquine (PQ) to artemisinin combination therapies (ACTs) for Plasmodium falciparum malaria as a gametocytocidal agent for reducing transmission. Here, we investigated the potential interactions of PQ with the long-lasting components of the ACT drugs for eliminating the asexual blood stages and gametocytes of in vitro-cultured P. falciparum strains. Using the SYBR green I assay for asexual parasites and a flow cytometry-based assay for gametocytes, we determined the interactions of PQ with the schizonticides chloroquine, mefloquine, piperaquine, lumefantrine, and naphthoquine. With the sums of fractional inhibitory concentrations and isobolograms, we were able to determine mostly synergistic interactions for the various PQ and schizonticide combinations on the blood stages of P. falciparum laboratory strains. The synergism in inhibiting asexual stages and gametocytes was highly evident with PQ-naphthoquine, whereas synergism was moderate for the PQ-piperaquine, PQ-chloroquine, and PQ-mefloquine combinations. We have detected potentially antagonistic interactions between PQ and lumefantrine under certain drug combination ratios, suggesting that precautions might be needed when PQ is added as the gametocytocide to the artemether-lumefantrine ACT (Coartem). PMID:26416869

Graphical Evaluation of the Ridge-Type Robust Regression Estimators in Mixture Experiments

PubMed Central

Erkoc, Ali; Emiroglu, Esra

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set. PMID:25202738

Graphical evaluation of the ridge-type robust regression estimators in mixture experiments.

PubMed

Erkoc, Ali; Emiroglu, Esra; Akay, Kadri Ulas

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set.

PET-Adjusted Intensity Modulated Radiation Therapy and Combination Chemotherapy in Treating Patients With Stage II-IV Non-small Cell Lung Cancer

ClinicalTrials.gov

2018-05-24

Metastatic Malignant Neoplasm in the Brain; Recurrent Non-Small Cell Lung Carcinoma; Stage IIA Non-Small Cell Lung Carcinoma; Stage IIB Non-Small Cell Lung Carcinoma; Stage IIIA Non-Small Cell Lung Cancer; Stage IIIB Non-Small Cell Lung Cancer; Stage IV Non-Small Cell Lung Cancer

The separate and combined effects of monoamine oxidase A inhibition and nicotine on resting state EEG.

PubMed

Smith, Dylan M; Fisher, Derek; Blier, Pierre; Ilivitsky, Vadim; Knott, Verner

2016-01-01

While nicotine is often associated with the neuropsychological effects of tobacco smoke, the robust monoamine oxidase (MAO) inhibition observed in chronic smokers is also likely to play a role. Electroencephalographically-indexed alterations in baseline neural oscillations by nicotine have previously been reported in both smokers and non-smokers, however, little is known about the effects of MAO inhibition in combination with nicotine on resting state EEG. In a sample of 24 healthy non-smoking males, the effects of 6 mg nicotine gum, as well as MAO-A inhibition via 75 mg moclobemide, were investigated in separate and combined conditions over four separate test sessions. Drug effects were observed in the alpha2, beta2, and theta band frequencies. Nicotine increased alpha2 power, and moclobemide decreased beta2 power. Theta power was decreased most robustly by the combination of both drugs. Therefore, this study demonstrated that the nicotinic and MAO inhibiting properties of tobacco may differentially influence fast-wave oscillations (alpha2 and beta2), while acting in synergy to influence theta oscillations. © The Author(s) 2015.

Robustness and management adaptability in tropical rangelands: a viability-based assessment under the non-equilibrium paradigm.

PubMed

Accatino, F; Sabatier, R; De Michele, C; Ward, D; Wiegand, K; Meyer, K M

2014-08-01

Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.

Brentuximab Vedotin and Combination Chemotherapy in Treating Older Patients With Previously Untreated Stage II-IV Hodgkin Lymphoma

ClinicalTrials.gov

2018-02-01

Adult Lymphocyte Depletion Hodgkin Lymphoma; Adult Lymphocyte Predominant Hodgkin Lymphoma; Adult Mixed Cellularity Hodgkin Lymphoma; Adult Nodular Sclerosis Hodgkin Lymphoma; Stage II Adult Hodgkin Lymphoma; Stage III Adult Hodgkin Lymphoma; Stage IV Adult Hodgkin Lymphoma

Superior therapeutic efficacy of nab-paclitaxel over cremophor-based paclitaxel in locally advanced and metastatic models of human pancreatic cancer.

PubMed

Rajeshkumar, N V; Yabuuchi, Shinichi; Pai, Shweta G; Tong, Zeen; Hou, Shihe; Bateman, Scott; Pierce, Daniel W; Heise, Carla; Von Hoff, Daniel D; Maitra, Anirban; Hidalgo, Manuel

2016-08-09

Albumin-bound paclitaxel (nab-paclitaxel, nab-PTX) plus gemcitabine (GEM) combination has demonstrated efficient antitumour activity and statistically significant overall survival of patients with metastatic pancreatic ductal adenocarcinoma (PDAC) compared with GEM monotherapy. This regimen is currently approved as a standard of care treatment option for patients with metastatic PDAC. It is unclear whether cremophor-based PTX combined with GEM provide a similar level of therapeutic efficacy in PDAC. We comprehensively explored the antitumour efficacy, effect on metastatic dissemination, tumour stroma and survival advantage following GEM, PTX and nab-PTX as monotherapy or in combination with GEM in a locally advanced, and a highly metastatic orthotopic model of human PDAC. Nab-PTX treatment resulted in significantly higher paclitaxel tumour plasma ratio (1.98-fold), robust stromal depletion, antitumour efficacy (3.79-fold) and survival benefit compared with PTX treatment. PTX plus GEM treatment showed no survival gain over GEM monotherapy. However, nab-PTX in combination with GEM decreased primary tumour burden, metastatic dissemination and significantly increased median survival of animals compared with either agents alone. These therapeutic effects were accompanied by depletion of dense fibrotic tumour stroma and decreased proliferation of carcinoma cells. Notably, nab-PTX monotherapy was equivalent to nab-PTX plus GEM in providing survival advantage to mice in a highly aggressive metastatic PDAC model, indicating that nab-PTX could potentially stop the progression of late-stage pancreatic cancer. Our data confirmed that therapeutic efficacy of PTX and nab-PTX vary widely, and the contention that these agents elicit similar antitumour response was not supported. The addition of PTX to GEM showed no survival advantage, concluding that a clinical combination of PTX and GEM may unlikely to provide significant survival advantage over GEM monotherapy and may not be a viable alternative to the current standard-of-care nab-PTX plus GEM regimen for the treatment of PDAC patients.

Adjuvant therapy in early-stage non-small cell lung cancer.

PubMed

Serke, Monika

2010-01-01

Evidence clearly supports adjuvant chemotherapy following resection in patients with stage II or III non-small cell lung cancer (NSCLC). Based on 3 landmark studies, adjuvant chemotherapy has become standard in completely resected NSCLC stage II and IIIA. Survival benefit from adjuvant chemotherapy is estimated to be between 3% and 15%, depending on stage. Treatment should include 4 cycles of platinum-based combination chemotherapy. There is uncertainty about chemotherapy prescription in those patients with resected stage IB NSCLC, as the risk of recurrence is lower in early NSCLC and the magnitude of benefit of adjuvant therapy is proportional to the risk of relapse according to stage. Postoperative radiotherapy (PORT) should not be used for stage I or II NSCLC, and remains controversial in resected stage IIIA (N2) disease. All positive adjuvant trials have utilized a cisplatin-based regimen, usually in combination with vinorelbine, and this should be considered the standard approach. Prognostic factors to select patients who will benefit from adjuvant therapy in general or from platinum-based chemotherapy are under discussion, but not yet established. In future we hope to optimize treatment convenience for the patients by using other combinations with the hope of better efficacy results. Work is currently under way to identify prognostic factors which in future may help to identify patients who are most likely to benefit from chemotherapy. Copyright 2010 S. Karger AG, Basel.

DT-CWT Robust Filtering Algorithm for The Extraction of Reference and Waviness from 3-D Nano Scalar Surfaces

NASA Astrophysics Data System (ADS)

Ren, Zhi Ying.; Gao, ChengHui.; Han, GuoQiang.; Ding, Shen; Lin, JianXing.

2014-04-01

Dual tree complex wavelet transform (DT-CWT) exhibits superiority of shift invariance, directional selectivity, perfect reconstruction (PR), and limited redundancy and can effectively separate various surface components. However, in nano scale the morphology contains pits and convexities and is more complex to characterize. This paper presents an improved approach which can simultaneously separate reference and waviness and allows an image to remain robust against abnormal signals. We included a bilateral filtering (BF) stage in DT-CWT to solve imaging problems. In order to verify the feasibility of the new method and to test its performance we used a computer simulation based on three generations of Wavelet and Improved DT-CWT and we conducted two case studies. Our results show that the improved DT-CWT not only enhances the robustness filtering under the conditions of abnormal interference, but also possesses accuracy and reliability of the reference and waviness from the 3-D nano scalar surfaces.

Bio-Inspired Microsystem for Robust Genetic Assay Recognition

PubMed Central

Lue, Jaw-Chyng; Fang, Wai-Chi

2008-01-01

A compact integrated system-on-chip (SoC) architecture solution for robust, real-time, and on-site genetic analysis has been proposed. This microsystem solution is noise-tolerable and suitable for analyzing the weak fluorescence patterns from a PCR prepared dual-labeled DNA microchip assay. In the architecture, a preceding VLSI differential logarithm microchip is designed for effectively computing the logarithm of the normalized input fluorescence signals. A posterior VLSI artificial neural network (ANN) processor chip is used for analyzing the processed signals from the differential logarithm stage. A single-channel logarithmic circuit was fabricated and characterized. A prototype ANN chip with unsupervised winner-take-all (WTA) function was designed, fabricated, and tested. An ANN learning algorithm using a novel sigmoid-logarithmic transfer function based on the supervised backpropagation (BP) algorithm is proposed for robustly recognizing low-intensity patterns. Our results show that the trained new ANN can recognize low-fluorescence patterns better than an ANN using the conventional sigmoid function. PMID:18566679

Robust cubature Kalman filter for GNSS/INS with missing observations and colored measurement noise.

PubMed

Cui, Bingbo; Chen, Xiyuan; Tang, Xihua; Huang, Haoqian; Liu, Xiao

2018-01-01

In order to improve the accuracy of GNSS/INS working in GNSS-denied environment, a robust cubature Kalman filter (RCKF) is developed by considering colored measurement noise and missing observations. First, an improved cubature Kalman filter (CKF) is derived by considering colored measurement noise, where the time-differencing approach is applied to yield new observations. Then, after analyzing the disadvantages of existing methods, the measurement augment in processing colored noise is translated into processing the uncertainties of CKF, and new sigma point update framework is utilized to account for the bounded model uncertainties. By reusing the diffused sigma points and approximation residual in the prediction stage of CKF, the RCKF is developed and its error performance is analyzed theoretically. Results of numerical experiment and field test reveal that RCKF is more robust than CKF and extended Kalman filter (EKF), and compared with EKF, the heading error of land vehicle is reduced by about 72.4%. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Evolution of Boolean networks under selection for a robust response to external inputs yields an extensive neutral space

NASA Astrophysics Data System (ADS)

Szejka, Agnes; Drossel, Barbara

2010-02-01

We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.

Development and Validation of a qRT-PCR Classifier for Lung Cancer Prognosis

PubMed Central

Chen, Guoan; Kim, Sinae; Taylor, Jeremy MG; Wang, Zhuwen; Lee, Oliver; Ramnath, Nithya; Reddy, Rishindra M; Lin, Jules; Chang, Andrew C; Orringer, Mark B; Beer, David G

2011-01-01

Purpose This prospective study aimed to develop a robust and clinically-applicable method to identify high-risk early stage lung cancer patients and then to validate this method for use in future translational studies. Patients and Methods Three published Affymetrix microarray data sets representing 680 primary tumors were used in the survival-related gene selection procedure using clustering, Cox model and random survival forest (RSF) analysis. A final set of 91 genes was selected and tested as a predictor of survival using a qRT-PCR-based assay utilizing an independent cohort of 101 lung adenocarcinomas. Results The RSF model built from 91 genes in the training set predicted patient survival in an independent cohort of 101 lung adenocarcinomas, with a prediction error rate of 26.6%. The mortality risk index (MRI) was significantly related to survival (Cox model p < 0.00001) and separated all patients into low, medium, and high-risk groups (HR = 1.00, 2.82, 4.42). The MRI was also related to survival in stage 1 patients (Cox model p = 0.001), separating patients into low, medium, and high-risk groups (HR = 1.00, 3.29, 3.77). Conclusions The development and validation of this robust qRT-PCR platform allows prediction of patient survival with early stage lung cancer. Utilization will now allow investigators to evaluate it prospectively by incorporation into new clinical trials with the goal of personalized treatment of lung cancer patients and improving patient survival. PMID:21792073

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

The Investigation of the Cox-2 Selective Inhibitor Parecoxib Effects in Spinal Cord Injury in Rat.

PubMed

Yuksel, Ulas; Bakar, Bulent; Dincel, Gungor Cagdas; Budak Yildiran, Fatma Azize; Ogden, Mustafa; Kisa, Ucler

2018-01-22

Today, spinal cord injury (SCI) can be rehabilitated but cannot be treated adequately. This experimental study was conducted to investigate possible beneficial effects of methylprednisolone and parecoxib in treatment of SCI. Forty-eight male Wistar albino rats were assigned into CONTROL, acute (MP-A, PX-A, and PXMP-A), and subacute (MP-S, PX-S, and PXMP-S) stage groups. Then, to induce SCI, a temporary aneurysm clip was applied to the spinal cord following T7-8 laminectomy, except in the CONTROL group. Four hours later parecoxib, methylprednisolone, or their combination was administered to rats intraperitoneally except CONTROL, SHAM-A, and SHAM-S groups. Rats in the acute stage group were sacrificed 72 h later, and whereas rats in the subacute stage were sacrificed 7 days later for histopathological and biochemical investigation and for gene-expression analyses. Parecoxib and methylprednisolone and their combination could not improve histopathological grades in any stage. They also could not decrease malondialdehyde or caspase-3, myeloperoxidase levels in any stage. Parecoxib and methylprednisolone could decrease the TNF-α gene expression in subacute stage. Methylprednisolone could increase TGF-1β gene-expression level in acute stage. Neither of the experimental drugs, either alone or in combination, did not show any beneficial effects in SCI model in rats.

Splenectomy combined with gastrectomy and immunotherapy for advanced gastric cancer.

PubMed

Miwa, H; Orita, K

1983-06-01

We studied the effects of a splenectomy in combination with immunotherapy on the survival of patients who had undergone a total gastrectomy. It was found that a splenectomy was not effective against advanced gastric cancer at stage III, and that the spleen should be retained for immunotherapy. Splenectomy for gastric cancer at terminal stage IV, particularly in combination with immunotherapy, produced not only augmentation of cellular immunity, but also increased survival.

Expendable solid rocket motor upper stages for the Space Shuttle

NASA Technical Reports Server (NTRS)

Davis, H. P.; Jones, C. M.

1974-01-01

A family of expendable solid rocket motor upper stages has been conceptually defined to provide the payloads for the Space Shuttle with performance capability beyond the low earth operational range of the Shuttle Orbiter. In this concept-feasibility assessment, three new solid rocket motors of fixed impulse are defined for use with payloads requiring levels of higher energy. The conceptual design of these motors is constrained to limit thrusting loads into the payloads and to conserve payload bay length. These motors are combined in various vehicle configurations with stage components derived from other programs for the performance of a broad range of upper-stage missions from spin-stabilized, single-stage transfers to three-axis stabilized, multistage insertions. Estimated payload delivery performance and combined payload mission loading configurations are provided for the upper-stage configurations.

A Secure Trust Establishment Scheme for Wireless Sensor Networks

PubMed Central

Ishmanov, Farruh; Kim, Sung Won; Nam, Seung Yeob

2014-01-01

Trust establishment is an important tool to improve cooperation and enhance security in wireless sensor networks. The core of trust establishment is trust estimation. If a trust estimation method is not robust against attack and misbehavior, the trust values produced will be meaningless, and system performance will be degraded. We present a novel trust estimation method that is robust against on-off attacks and persistent malicious behavior. Moreover, in order to aggregate recommendations securely, we propose using a modified one-step M-estimator scheme. The novelty of the proposed scheme arises from combining past misbehavior with current status in a comprehensive way. Specifically, we introduce an aggregated misbehavior component in trust estimation, which assists in detecting an on-off attack and persistent malicious behavior. In order to determine the current status of the node, we employ previous trust values and current measured misbehavior components. These components are combined to obtain a robust trust value. Theoretical analyses and evaluation results show that our scheme performs better than other trust schemes in terms of detecting an on-off attack and persistent misbehavior. PMID:24451471

Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: robust virtual sensor design.

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-03-01

The work was aimed to develop a robust virtual sensing design methodology for sensing and active control applications of vibro-acoustic systems. The proposed virtual sensor was designed to estimate a broadband acoustic interior sound pressure using structural sensors, with robustness against certain dynamic uncertainties occurring in an acoustic-structural coupled enclosure. A convex combination of Kalman sub-filters was used during the design, accommodating different sets of perturbed dynamic model of the vibro-acoustic enclosure. A minimax optimization problem was set up to determine an optimal convex combination of Kalman sub-filters, ensuring an optimal worst-case virtual sensing performance. The virtual sensing and active noise control performance was numerically investigated on a rectangular panel-cavity system. It was demonstrated that the proposed virtual sensor could accurately estimate the interior sound pressure, particularly the one dominated by cavity-controlled modes, by using a structural sensor. With such a virtual sensing technique, effective active noise control performance was also obtained even for the worst-case dynamics. © 2011 Acoustical Society of America

Robust current control-based generalized predictive control with sliding mode disturbance compensation for PMSM drives.

PubMed

Liu, Xudong; Zhang, Chenghui; Li, Ke; Zhang, Qi

2017-11-01

This paper addresses the current control of permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and disturbances. A generalized predictive current control method combined with sliding mode disturbance compensation is proposed to satisfy the requirement of fast response and strong robustness. Firstly, according to the generalized predictive control (GPC) theory based on the continuous time model, a predictive current control method is presented without considering the disturbance, which is convenient to be realized in the digital controller. In fact, it's difficult to derive the exact motor model and parameters in the practical system. Thus, a sliding mode disturbance compensation controller is studied to improve the adaptiveness and robustness of the control system. The designed controller attempts to combine the merits of both predictive control and sliding mode control, meanwhile, the controller parameters are easy to be adjusted. Lastly, the proposed controller is tested on an interior PMSM by simulation and experiment, and the results indicate that it has good performance in both current tracking and disturbance rejection. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Predictive Validity of National Basketball Association Draft Combine on Future Performance.

PubMed

Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

2018-02-01

Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

Saturn Apollo Program

NASA Image and Video Library

1960-01-01

H-1 engine characteristics: The H-1 engine was developed under the management of the Marshall Space Flight Center (MSFC). The cluster of eight H-1 engines was used to power the first stage of the Saturn I (S-I stage) and Saturn IB (S-IVB stage) launch vehicles, and produced 188,00 pounds of thrust, a combined thrust of 1,500,000 pounds, later uprated to 205,000 pounds of thrust and a combined total thrust of 1,650,000 pounds for the Saturn IB program.

The sensitivity and specificity of thermometry and plethysmography in the assessment of hand-arm vibration syndrome.

PubMed

Thompson, Aaron; House, Ron; Manno, Michael

2008-05-01

Finger plethysmography and thermometry are objective measures used to assess the vascular aspect of hand-arm vibration syndrome (HAVS). Research to date shows poor correlation between these tests and Stockholm Workshop Scale (SWS) vascular stage. Clinicians, researchers and compensation boards require objective means to diagnose and quantify HAVS. To define the specificity and sensitivity of thermometry and plethysmography using the SWS as the reference criterion. A secondary goal was to consider cut points for the tests optimizing sensitivity and specificity. A cross-sectional analysis was conducted on HAVS patients seen at an occupational medicine specialty clinic. Plethysmography and thermometry were analyzed using SWS vascular stage as the outcome variable. Logistic regression controlled for age, smoking and time since last vibration exposure and use of vasoactive medications. The sensitivity and specificity of the combined tests were calculated using varying cut points. A total of 139 patients consented to participate in the study. Plethysmography stage 1 or greater showed the highest sensitivity (sensitivity 94% and specificity 15%). Specificity was optimized combining plethysmography stage 3 and thermometry stage 3 (specificity 98% and sensitivity 23%). Maximal diagnostic accuracy was achieved by plethysmography alone setting the criteria for a positive test as being stage 1 or greater (70%). Neither plethysmography nor thermometry either alone or in combination demonstrated sufficient sensitivity and specificity to serve as an objective correlate for SWS vascular stage. All combinations of plethysmography and thermometry showed a lower specificity than sensitivity indicating that the SWS may be less sensitive in detecting vascular pathology than the objective tests.

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

Lu, Bo, E-mail: luboufl@gmail.com; Park, Justin C.; Fan, Qiyong

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparsemore » optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.« less

Continuous EEG signal analysis for asynchronous BCI application.

PubMed

Hsu, Wei-Yen

2011-08-01

In this study, we propose a two-stage recognition system for continuous analysis of electroencephalogram (EEG) signals. An independent component analysis (ICA) and correlation coefficient are used to automatically eliminate the electrooculography (EOG) artifacts. Based on the continuous wavelet transform (CWT) and Student's two-sample t-statistics, active segment selection then detects the location of active segment in the time-frequency domain. Next, multiresolution fractal feature vectors (MFFVs) are extracted with the proposed modified fractal dimension from wavelet data. Finally, the support vector machine (SVM) is adopted for the robust classification of MFFVs. The EEG signals are continuously analyzed in 1-s segments, and every 0.5 second moves forward to simulate asynchronous BCI works in the two-stage recognition architecture. The segment is first recognized as lifted or not in the first stage, and then is classified as left or right finger lifting at stage two if the segment is recognized as lifting in the first stage. Several statistical analyses are used to evaluate the performance of the proposed system. The results indicate that it is a promising system in the applications of asynchronous BCI work.

Raytheon RSP2 Cryocooler Low Temperature Testing and Design Enhancements

NASA Astrophysics Data System (ADS)

Hon, R. C.; Kirkconnell, C. S.; Shrago, J. A.

2010-04-01

The High Capacity Raytheon Stirling/Pulse Tube Hybrid 2-Stage cryocooler (HC-RSP2) was originally developed to provide simultaneous cooling at temperatures of 85 K and 35 K. During testing performed in 2008 it was demonstrated that this stock-configuration cryocooler is capable of providing significant amounts of heat lift at 2nd stage temperatures as low as 12 K, and modeling indicated that minor changes to the 2nd stage inertance tube/surge volume setup could yield improved performance. These changes were implemented and the cooler was successfully retested, producing >350 mW of heat lift at 12 K. A comprehensive redesign of the system has been performed, the result of which is a robust 2-stage cryocooler system that is intended to efficiently produce relatively large amounts of cooling at 2nd stage temperatures <12 K. This cryocooler, called the Low Temperature RSP2 (LT-RSP2) will be fabricated and tested over the next 12 months. This paper reports on the recently-completed test activities, as well as details relating to the system redesign. Expected performance, mass and packaging volume are addressed.

Health condition identification of multi-stage planetary gearboxes using a mRVM-based method

NASA Astrophysics Data System (ADS)

Lei, Yaguo; Liu, Zongyao; Wu, Xionghui; Li, Naipeng; Chen, Wu; Lin, Jing

2015-08-01

Multi-stage planetary gearboxes are widely applied in aerospace, automotive and heavy industries. Their key components, such as gears and bearings, can easily suffer from damage due to tough working environment. Health condition identification of planetary gearboxes aims to prevent accidents and save costs. This paper proposes a method based on multiclass relevance vector machine (mRVM) to identify health condition of multi-stage planetary gearboxes. In this method, a mRVM algorithm is adopted as a classifier, and two features, i.e. accumulative amplitudes of carrier orders (AACO) and energy ratio based on difference spectra (ERDS), are used as the input of the classifier to classify different health conditions of multi-stage planetary gearboxes. To test the proposed method, seven health conditions of a two-stage planetary gearbox are considered and vibration data is acquired from the planetary gearbox under different motor speeds and loading conditions. The results of three tests based on different data show that the proposed method obtains an improved identification performance and robustness compared with the existing method.

Primed for Reform: A District's Use of Existing Assets to Drive Improvement

ERIC Educational Resources Information Center

Region IX Equity Assistance Center at WestEd, 2014

2014-01-01

This brief reports on the early stages and initial successes of turnaround efforts in a California school district. With administrators and educators in the midst of implementing a robust reform agenda, there are clear signs that the district is on the rise. The reform initiatives have stopped a downward slide in student attendance, behavior, and…

Automatic Requirements Specification Extraction from Natural Language (ARSENAL)

DTIC Science & Technology

2014-10-01

designers, implementers) involved in the design of software systems. However, natural language descriptions can be informal, incomplete, imprecise...communication of technical descriptions between the various stakeholders (e.g., customers, designers, imple- menters) involved in the design of software systems...the accuracy of the natural language processing stage, the degree of automation, and robustness to noise. 1 2 Introduction Software systems operate in

Factors Affecting Grammatical and Lexical Complexity of Long-Term L2 Speakers' Oral Proficiency

ERIC Educational Resources Information Center

Lahmann, Cornelia; Steinkrauss, Rasmus; Schmid, Monika S.

2016-01-01

There remains considerable disagreement about which factors drive second language (L2) ultimate attainment. Age of onset (AO) appears to be a robust factor, lending support to theories of maturational constraints on L2 acquisition. The present study is an investigation of factors that influence grammatical and lexical complexity at the stage of L2…

The Dynamics of Network Change for Older People: Social Policy and Social Theory.

ERIC Educational Resources Information Center

Litwak, Eugene; Kulis, Steve

This paper discusses how networks of elderly people change with stages of disability. Senior citizens in 80 nursing homes (40 in New York and 40 in Florida) were interviewed. The authors examine how spouses, relatives, neighbors, friends, and acquaintances help out when the elderly are robust, how these patterns of help change when the elderly…

"Would You Like to Tidy up Now?" An Analysis of Adult Questioning in the English Foundation Stage

ERIC Educational Resources Information Center

Siraj-Blatchford, Iram; Manni, Laura

2008-01-01

This study provides an extension of analysis concerned with adult questioning carried out in the Researching Effective Pedagogy in the Early Years (REPEY) study. The REPEY study drew on robust quantitative data provided by the Effective Provision of Pre-School Education (EPPE) project to identify the particular pedagogical strategies being applied…

A Six‐Stage Workflow for Robust Application of Systems Pharmacology

PubMed Central

Gadkar, K; Kirouac, DC; Mager, DE; van der Graaf, PH

2016-01-01

Quantitative and systems pharmacology (QSP) is increasingly being applied in pharmaceutical research and development. One factor critical to the ultimate success of QSP is the establishment of commonly accepted language, technical criteria, and workflows. We propose an integrated workflow that bridges conceptual objectives with underlying technical detail to support the execution, communication, and evaluation of QSP projects. PMID:27299936

Experimental investigation of shaping disturbance observer design for motion control of precision mechatronic stages with resonances

NASA Astrophysics Data System (ADS)

Yang, Jin; Hu, Chuxiong; Zhu, Yu; Wang, Ze; Zhang, Ming

2017-08-01

In this paper, shaping disturbance observer (SDOB) is investigated for precision mechatronic stages with middle-frequency zero/pole type resonance to achieve good motion control performance in practical manufacturing situations. Compared with traditional standard disturbance observer (DOB), in SDOB a pole-zero cancellation based shaping filter is cascaded to the mechatronic stage plant to meet the challenge of motion control performance deterioration caused by actual resonance. Noting that pole-zero cancellation is inevitably imperfect and the controller may even consequently become unstable in practice, frequency domain stability analysis is conducted to find out how each parameter of the shaping filter affects the control stability. Moreover, the robust design criterion of the shaping filter, and the design procedure of SDOB, are both proposed to guide the actual design and facilitate practical implementation. The SDOB with the proposed design criterion is applied to a linear motor driven stage and a voice motor driven stage, respectively. Experimental results consistently validate the effectiveness nature of the proposed SDOB scheme in practical mechatronics motion applications. The proposed SDOB design actually could be an effective unit in the controller design for motion stages of mechanical manufacture equipments.

Pembrolizumab, Combination Chemotherapy, and Radiation Therapy Before Surgery in Treating Adult Patients With Locally Advanced Gastroesophageal Junction or Gastric Cardia Cancer That Can Be Removed by Surgery

ClinicalTrials.gov

2018-04-13

Gastric Cardia Adenocarcinoma; Gastroesophageal Junction Adenocarcinoma; Stage IB Gastric Cancer AJCC v7; Stage II Gastric Cancer AJCC v7; Stage IIA Gastric Cancer AJCC v7; Stage IIB Gastric Cancer AJCC v7; Stage IIIA Gastric Cancer AJCC v7; Stage IIIB Gastric Cancer AJCC v7

The R148.3 Gene Modulates Caenorhabditis elegans Lifespan and Fat Metabolism

PubMed Central

Roy-Bellavance, Catherine; Grants, Jennifer M.; Miard, Stéphanie; Lee, Kayoung; Rondeau, Évelyne; Guillemette, Chantal; Simard, Martin J.; Taubert, Stefan; Picard, Frédéric

2017-01-01

Despite many advances, the molecular links between energy metabolism and longevity are not well understood. Here, we have used the nematode model Caenorhabditis elegans to study the role of the yet-uncharacterized gene R148.3 in fat accumulation and lifespan. In wild-type worms, a R148.3p::GFP reporter showed enhanced expression throughout life in the pharynx, in neurons, and in muscles. Functionally, a protein fusing a predicted 22 amino acid N-terminal signal sequence (SS) of R148.3 to mCherry displayed robust accumulation in coelomyocytes, indicating that R148.3 is a secreted protein. Systematic depletion of R148.3 by RNA interference (RNAi) at L1 but not at young-adult stage enhanced triglyceride accumulation, which was associated with increased food uptake and lower expression of genes involved in lipid oxidation. However, RNAi of R148.3 at both L1 and young-adult stages robustly diminished mean and maximal lifespan of wild-type worms, and also abolished the long-lived phenotypes of eat-2 and daf-2/InsR mutants. Based on these data, we propose that R148.3 is an SS that modulates fat mass and longevity in an independent manner. PMID:28620088

A simple whole cell based high throughput screening protocol using Mycobacterium bovis BCG for inhibitors against dormant and active tubercle bacilli.

PubMed

Khan, Arshad; Sarkar, Dhiman

2008-04-01

This study aimed at developing a whole cell based high throughput screening protocol to identify inhibitors against both active and dormant tubercle bacilli. A respiratory type of nitrate reductase (NarGHJI), which was induced during dormancy, could reflect the viability of dormant bacilli of Mycobacterium bovis BCG in microplate adopted model of in vitro dormancy. Correlation between reduction in viability and nitrate reductase activity was seen clearly when dormant stage inhibitor metronidazole and itaconic anhydride were applied in this in vitro microplate model. Active replicating stage could also be monitored in the same assay by measuring the A(620) of the culture. MIC values of 0.08, 0.075, 0.3 and 3.0 microg/ml, determined through monitoring A(620) in this assay for rifampin, isoniazid, streptomycin and ethambutol respectively, were well in agreement with previously reported by BACTEC and Bio-Siv assays. S/N ratio and Z' factor for the assay were 8.5 and 0.81 respectively which indicated the robustness of the protocol. Altogether the assay provides an easy, inexpensive, rapid, robust and high content screening tool to search novel antitubercular molecules against both active and dormant bacilli.

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

Audren, Benjamin; Lesgourgues, Julien; Benabed, Karim

Models for the latest stages of the cosmological evolution rely on a less solid theoretical and observational ground than the description of earlier stages like BBN and recombination. As suggested in a previous work by Vonlanthen et al., it is possible to tweak the analysis of CMB data in such way to avoid making assumptions on the late evolution, and obtain robust constraints on ''early cosmology parameters''. We extend this method in order to marginalise the results over CMB lensing contamination, and present updated results based on recent CMB data. Our constraints on the minimal early cosmology model are weakermore » than in a standard ΛCDM analysis, but do not conflict with this model. Besides, we obtain conservative bounds on the effective neutrino number and neutrino mass, showing no hints for extra relativistic degrees of freedom, and proving in a robust way that neutrinos experienced their non-relativistic transition after the time of photon decoupling. This analysis is also an occasion to describe the main features of the new parameter inference code MONTE PYTHON, that we release together with this paper. MONTE PYTHON is a user-friendly alternative to other public codes like COSMOMC, interfaced with the Boltzmann code CLASS.« less

Transmission-line model to design matching stage for light coupling into two-dimensional photonic crystals.

PubMed

Miri, Mehdi; Khavasi, Amin; Mehrany, Khashayar; Rashidian, Bizhan

2010-01-15

The transmission-line analogy of the planar electromagnetic reflection problem is exploited to obtain a transmission-line model that can be used to design effective, robust, and wideband interference-based matching stages. The proposed model based on a new definition for a scalar impedance is obtained by using the reflection coefficient of the zeroth-order diffracted plane wave outside the photonic crystal. It is shown to be accurate for in-band applications, where the normalized frequency is low enough to ensure that the zeroth-order diffracted plane wave is the most important factor in determining the overall reflection. The frequency limitation of employing the proposed approach is explored, highly dispersive photonic crystals are considered, and wideband matching stages based on binomial impedance transformers are designed to work at the first two photonic bands.

A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications.

PubMed

Ma, JiaLi; Zhang, TanTan; Dong, MingChui

2015-05-01

This paper presents a novel electrocardiogram (ECG) compression method for e-health applications by adapting an adaptive Fourier decomposition (AFD) algorithm hybridized with a symbol substitution (SS) technique. The compression consists of two stages: first stage AFD executes efficient lossy compression with high fidelity; second stage SS performs lossless compression enhancement and built-in data encryption, which is pivotal for e-health. Validated with 48 ECG records from MIT-BIH arrhythmia benchmark database, the proposed method achieves averaged compression ratio (CR) of 17.6-44.5 and percentage root mean square difference (PRD) of 0.8-2.0% with a highly linear and robust PRD-CR relationship, pushing forward the compression performance to an unexploited region. As such, this paper provides an attractive candidate of ECG compression method for pervasive e-health applications.

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

PubMed

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

10 CFR 51.50 - Environmental report-construction permit, early site permit, or combined license stage.

Code of Federal Regulations, 2011 CFR

2011-01-01

... costs of the proposed action or an evaluation of alternative energy sources. (3) For other than light... 10 Energy 2 2011-01-01 2011-01-01 false Environmental report-construction permit, early site permit, or combined license stage. 51.50 Section 51.50 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED...

10 CFR 51.50 - Environmental report-construction permit, early site permit, or combined license stage.

Code of Federal Regulations, 2013 CFR

2013-01-01

... costs of the proposed action or an evaluation of alternative energy sources. (3) For other than light... 10 Energy 2 2013-01-01 2013-01-01 false Environmental report-construction permit, early site permit, or combined license stage. 51.50 Section 51.50 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED...

10 CFR 51.50 - Environmental report-construction permit, early site permit, or combined license stage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... costs of the proposed action or an evaluation of alternative energy sources. (3) For other than light... 10 Energy 2 2010-01-01 2010-01-01 false Environmental report-construction permit, early site permit, or combined license stage. 51.50 Section 51.50 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED...

10 CFR 51.50 - Environmental report-construction permit, early site permit, or combined license stage.

Code of Federal Regulations, 2014 CFR

2014-01-01

... costs of the proposed action or an evaluation of alternative energy sources. (3) For other than light... 10 Energy 2 2014-01-01 2014-01-01 false Environmental report-construction permit, early site permit, or combined license stage. 51.50 Section 51.50 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED...

10 CFR 51.50 - Environmental report-construction permit, early site permit, or combined license stage.

Code of Federal Regulations, 2012 CFR

2012-01-01

... costs of the proposed action or an evaluation of alternative energy sources. (3) For other than light... 10 Energy 2 2012-01-01 2012-01-01 false Environmental report-construction permit, early site permit, or combined license stage. 51.50 Section 51.50 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED...

A Framework for Remediating Number Combination Deficits

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Powell, Sarah R.; Seethaler, Pamela M.; Fuchs, Douglas; Hamlett, Carol L.; Cirino, Paul T.; Fletcher, Jack M.

2010-01-01

This article introduces a framework for the remediation of number combination (NC) deficits. Research on the remediation of NC deficits is summarized, and research program studies are used to illustrate the 3 approaches to remediation. The Framework comprises a 2-stage system of remediation. The less intensive stage implementing 1 of 3…

Evaluation of a biological wastewater treatment system combining an OSA process with ultrasound for sludge reduction.

PubMed

Romero-Pareja, P M; Aragon, C A; Quiroga, J M; Coello, M D

2017-05-01

Sludge production is an undesirable by-product of biological wastewater treatment. The oxic-settling-anaerobic (OSA) process constitutes one of the most promising techniques for reducing the sludge produced at the treatment plant without negative consequences for its overall performance. In the present study, the OSA process is applied in combination with ultrasound treatment, a lysis technique, in a lab-scale wastewater treatment plant to assess whether sludge reduction is enhanced as a result of mechanical treatment. Reported sludge reductions of 45.72% and 78.56% were obtained for the two regimes of combined treatment tested in this study during two respective stages: UO1 and UO2. During the UO1 stage, the general performance and nutrient removal improved, obtaining 47.28% TN removal versus 21.95% in the conventional stage. However, the performance of the system was seriously damaged during the UO2 stage. Increases in dehydrogenase and protease activities were observed during both stages. The advantages of the combined process are not necessarily economic, but operational, as US treatment acts as contributing factor in the OSA process, inducing mechanisms that lead to sludge reduction in the OSA process and improving performance parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

Advancing Access to New Technology for Sustained High Resolution Observations of Plankton: From Bloom Dynamics to Climate Change

NASA Astrophysics Data System (ADS)

Sosik, H. M.; Olson, R. J.

2012-12-01

The combination of ocean observatory infrastructure and automated submersible flow cytometry can provide unprecedented capability for sustained high resolution time series of plankton, including taxa that are harmful or early indicators of ecosystem response to environmental change. Over the past decade, we have developed the FlowCytobot series of instruments that exemplify this capability. FlowCytobot and Imaging FlowCytobot use a combination of laser-based scattering and fluorescence measurements and video imaging of individual particles to enumerate and characterize cells ranging from picocyanobacteria to large chaining-forming diatoms. The process of developing these complex instruments was streamlined by access to the Martha's Vineyard Coastal Observatory (MVCO), a cabled facility on the New England Shelf, where real time two-way communications and access to shore power expedited cycles of instrument evaluation and design refinement. Repeated deployments at MVCO, typically 6 months in duration, have produced multi-year high resolution (hourly to daily) time series that are providing new insights into dynamics of community structure such as blooms, seasonality, and possibly even trends linked to regional climate change. The high temporal resolution observations of single cell properties make it possible not only to characterize taxonomic composition and size structure, but also to quantify taxon-specific growth rates. To meet the challenge of broadening access to this enabling technology, we have taken a two-step approach. First, we are partnering with a few scientific collaborators interested in using the instruments in different environments and to address different applications, notably the detection and characterization of harmful algal bloom events. Collaboration at this stage ensured that these first users outside the developers' lab had access to technical know-how required for successful outcomes; it also provided additional feedback that could be incorporated into more robust and user-friendly design. In the second and most recent stage, we have partnered with McLane Research Laboratories, Inc., a commercial vendor licensed to produce and market Imaging FlowCytobot. This stage of the development process has involved interactions between the scientific developers and company engineers, emphasizing joint construction of a pre-commercial prototype. A first run of commercially available units is anticipated to begin in the coming months paving the way for an expanding set of sustained high resolution plankton observations in conjunction with existing and emerging ocean observing systems.

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

Baker, Kyri; Dall'Anese, Emiliano; Summers, Tyler

This paper outlines a data-driven, distributionally robust approach to solve chance-constrained AC optimal power flow problems in distribution networks. Uncertain forecasts for loads and power generated by photovoltaic (PV) systems are considered, with the goal of minimizing PV curtailment while meeting power flow and voltage regulation constraints. A data- driven approach is utilized to develop a distributionally robust conservative convex approximation of the chance-constraints; particularly, the mean and covariance matrix of the forecast errors are updated online, and leveraged to enforce voltage regulation with predetermined probability via Chebyshev-based bounds. By combining an accurate linear approximation of the AC power flowmore » equations with the distributionally robust chance constraint reformulation, the resulting optimization problem becomes convex and computationally tractable.« less

Stochastic simulation and robust design optimization of integrated photonic filters

NASA Astrophysics Data System (ADS)

Weng, Tsui-Wei; Melati, Daniele; Melloni, Andrea; Daniel, Luca

2017-01-01

Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic coupled ring resonator filters are considered as an example of significant interest. The sparsity structure in photonic circuits is exploited to construct a sparse combined generalized polynomial chaos model, which is then used to analyze related statistics and perform robust design optimization. Simulation results show that the optimized circuits are more robust to fabrication process variations and achieve a reduction of 11%-35% in the mean square errors of the 3 dB bandwidth compared to unoptimized nominal designs.

A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring.

PubMed

Pantelopoulos, Alexandros; Saldivar, Enrique; Roham, Masoud

2011-01-01

In this paper a wireless modular, multi-modal, multi-node patch platform is described. The platform comprises low-cost semi-disposable patch design aiming at unobtrusive ambulatory monitoring of multiple physiological parameters. Owing to its modular design it can be interfaced with various low-power RF communication and data storage technologies, while the data fusion of multi-modal and multi-node features facilitates measurement of several biosignals from multiple on-body locations for robust feature extraction. Preliminary results of the patch platform are presented which illustrate the capability to extract respiration rate from three different independent metrics, which combined together can give a more robust estimate of the actual respiratory rate.

A robust internal control for high-precision DNA methylation analyses by droplet digital PCR.

PubMed

Pharo, Heidi D; Andresen, Kim; Berg, Kaja C G; Lothe, Ragnhild A; Jeanmougin, Marine; Lind, Guro E

2018-01-01

Droplet digital PCR (ddPCR) allows absolute quantification of nucleic acids and has potential for improved non-invasive detection of DNA methylation. For increased precision of the methylation analysis, we aimed to develop a robust internal control for use in methylation-specific ddPCR. Two control design approaches were tested: (a) targeting a genomic region shared across members of a gene family and (b) combining multiple assays targeting different pericentromeric loci on different chromosomes. Through analyses of 34 colorectal cancer cell lines, the performance of the control assay candidates was optimized and evaluated, both individually and in various combinations, using the QX200™ droplet digital PCR platform (Bio-Rad). The best-performing control was tested in combination with assays targeting methylated CDO1 , SEPT9 , and VIM . A 4Plex panel consisting of EPHA3 , KBTBD4 , PLEKHF1 , and SYT10 was identified as the best-performing control. The use of the 4Plex for normalization reduced the variability in methylation values, corrected for differences in template amount, and diminished the effect of chromosomal aberrations. Positive Droplet Calling (PoDCall), an R-based algorithm for standardized threshold determination, was developed, ensuring consistency of the ddPCR results. Implementation of a robust internal control, i.e., the 4Plex, and an algorithm for automated threshold determination, PoDCall, in methylation-specific ddPCR increase the precision of DNA methylation analysis.

Artesunate-tafenoquine combination therapy promotes clearance and abrogates transmission of the avian malaria parasite Plasmodium gallinaceum.

PubMed

Tasai, Suchada; Saiwichai, Tawee; Kaewthamasorn, Morakot; Tiawsirisup, Sonthaya; Buddhirakkul, Prayute; Chaichalotornkul, Sirintip; Pattaradilokrat, Sittiporn

2017-01-15

Clinical manifestations of malaria infection in vertebrate hosts arise from the multiplication of the asexual stage parasites in the blood, while the gametocytes are responsible for the transmission of the disease. Antimalarial drugs that target the blood stage parasites and transmissible gametocytes are rare, but are essentially needed for the effective control of malaria and for limiting the spread of resistance. Artemisinin and its derivatives are the current first-line antimalarials that are effective against the blood stage parasites and gametocytes, but resistance to artemisinin has now emerged and spread in various malaria endemic areas. Therefore, a novel antimalarial drug, or a new drug combination, is critically needed to overcome this problem. The objectives of this study were to evaluate the efficacy of a relatively new antimalarial compound, tafenoquine (TQ), and a combination of TQ and a low dose of artesunate (ATN) on the in vivo blood stage multiplication, gametocyte development and transmission of the avian malaria parasite Plasmodium gallinaceum to the vector Aedes aegypti. The results showed that a 5-d treatment with TQ alone was unable to clear the blood stage parasites, but was capable of reducing the mortality rate, while TQ monotherapy at a high dose of 30mg/kg was highly effective against the gametocytes and completely blocked the transmission of P. gallinaceum. In addition, the combination therapy of TQ+ATN completely cleared P. gallinaceum blood stages and sped up the gametocyte clearance from chickens, suggesting the synergistic effect of the two drugs. In conclusion, TQ is demonstrated to be effective for limiting avian malaria transmission and may be used in combination with a low dose of ATN for safe and effective treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

A robust control strategy for mitigating renewable energy fluctuations in a real hybrid power system combined with SMES

NASA Astrophysics Data System (ADS)

Magdy, G.; Shabib, G.; Elbaset, Adel A.; Qudaih, Yaser; Mitani, Yasunori

2018-05-01

Utilizing Renewable Energy Sources (RESs) is attracting great attention as a solution to future energy shortages. However, the irregular nature of RESs and random load deviations cause a large frequency and voltage fluctuations. Therefore, in order to benefit from a maximum capacity of the RESs, a robust mitigation strategy of power fluctuations from RESs must be applied. Hence, this paper proposes a design of Load Frequency Control (LFC) coordinated with Superconducting Magnetic Energy Storage (SMES) technology (i.e., an auxiliary LFC), using an optimal PID controller-based Particle Swarm Optimization (PSO) in the Egyptian Power System (EPS) considering high penetration of Photovoltaics (PV) power generation. Thus, from the perspective of LFC, the robust control strategy is proposed to maintain the nominal system frequency and mitigating the power fluctuations from RESs against all disturbances sources for the EPS with the multi-source environment. The EPS is decomposed into three dynamics subsystems, which are non-reheat, reheat and hydro power plants taking into consideration the system nonlinearity. The results by nonlinear simulation Matlab/Simulink for the EPS combined with SMES system considering PV solar power approves that, the proposed control strategy achieves a robust stability by reducing transient time, minimizing the frequency deviations, maintaining the system frequency, preventing conventional generators from exceeding their power ratings during load disturbances, and mitigating the power fluctuations from the RESs.

Robust optimization of a tandem grating solar thermal absorber

NASA Astrophysics Data System (ADS)

Choi, Jongin; Kim, Mingeon; Kang, Kyeonghwan; Lee, Ikjin; Lee, Bong Jae

2018-04-01

Ideal solar thermal absorbers need to have a high value of the spectral absorptance in the broad solar spectrum to utilize the solar radiation effectively. Majority of recent studies about solar thermal absorbers focus on achieving nearly perfect absorption using nanostructures, whose characteristic dimension is smaller than the wavelength of sunlight. However, precise fabrication of such nanostructures is not easy in reality; that is, unavoidable errors always occur to some extent in the dimension of fabricated nanostructures, causing an undesirable deviation of the absorption performance between the designed structure and the actually fabricated one. In order to minimize the variation in the solar absorptance due to the fabrication error, the robust optimization can be performed during the design process. However, the optimization of solar thermal absorber considering all design variables often requires tremendous computational costs to find an optimum combination of design variables with the robustness as well as the high performance. To achieve this goal, we apply the robust optimization using the Kriging method and the genetic algorithm for designing a tandem grating solar absorber. By constructing a surrogate model through the Kriging method, computational cost can be substantially reduced because exact calculation of the performance for every combination of variables is not necessary. Using the surrogate model and the genetic algorithm, we successfully design an effective solar thermal absorber exhibiting a low-level of performance degradation due to the fabrication uncertainty of design variables.

On Motion Planning and Control of Multi-Link Lightweight Robotic Manipulators

NASA Technical Reports Server (NTRS)

Cetinkunt, Sabri

1987-01-01

A general gross and fine motion planning and control strategy is needed for lightweight robotic manipulator applications such as painting, welding, material handling, surface finishing, and spacecraft servicing. The control problem of lightweight manipulators is to perform fast, accurate, and robust motions despite the payload variations, structural flexibility, and other environmental disturbances. Performance of the rigid manipulator model based computed torque and decoupled joint control methods are determined and simulated for the counterpart flexible manipulators. A counterpart flexible manipulator is defined as a manipulator which has structural flexibility, in addition to having the same inertial, geometric, and actuation properties of a given rigid manipulator. An adaptive model following control (AMFC) algorithm is developed to improve the performance in speed, accuracy, and robustness. It is found that the AMFC improves the speed performance by a factor of two over the conventional non-adaptive control methods for given accuracy requirements while proving to be more robust with respect to payload variations. Yet there are clear limitations on the performance of AMFC alone as well, which are imposed by the arm flexibility. In the search to further improve speed performance while providing a desired accuracy and robustness, a combined control strategy is developed. Furthermore, the problem of switching from one control structure to another during the motion and implementation aspects of combined control are discussed.

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

PubMed Central

Steiner, Christopher F.

2012-01-01

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

Combination Chemotherapy and Lenalidomide in Treating Patients With Newly Diagnosed Stage II-IV Peripheral T-cell Non-Hodgkin's Lymphoma

ClinicalTrials.gov

2017-07-07

Anaplastic Large Cell Lymphoma, ALK-Negative; Anaplastic Large Cell Lymphoma, ALK-Positive; Hepatosplenic T-Cell Lymphoma; Peripheral T-Cell Lymphoma, Not Otherwise Specified; Stage II Angioimmunoblastic T-cell Lymphoma; Stage II Enteropathy-Associated T-Cell Lymphoma; Stage III Angioimmunoblastic T-cell Lymphoma; Stage III Enteropathy-Associated T-Cell Lymphoma; Stage IV Angioimmunoblastic T-cell Lymphoma; Stage IV Enteropathy-Associated T-Cell Lymphoma

Automatic computation of 2D cardiac measurements from B-mode echocardiography

NASA Astrophysics Data System (ADS)

Park, JinHyeong; Feng, Shaolei; Zhou, S. Kevin

2012-03-01

We propose a robust and fully automatic algorithm which computes the 2D echocardiography measurements recommended by America Society of Echocardiography. The algorithm employs knowledge-based imaging technologies which can learn the expert's knowledge from the training images and expert's annotation. Based on the models constructed from the learning stage, the algorithm searches initial location of the landmark points for the measurements by utilizing heart structure of left ventricle including mitral valve aortic valve. It employs the pseudo anatomic M-mode image generated by accumulating the line images in 2D parasternal long axis view along the time to refine the measurement landmark points. The experiment results with large volume of data show that the algorithm runs fast and is robust comparable to expert.

Functional morphology of mouthparts and digestive system during larval development of the cleaner shrimp Lysmata amboinensis (de Man, 1888).

PubMed

Tziouveli, Vasiliki; Bastos Gomes, Giana; Bastos-Gomez, Giana; Bellwood, Orpha

2011-09-01

Mouthpart and alimentary canal development was examined in Lysmata amboinensis larvae using scanning electron microscopy and histology. The gross morphological features of external mouthparts and internal digestive tract structures of larvae at different developmental stages indicate that ingestive and digestive capabilities are well developed from early on. With increasing age of the larvae the mouthpart appendages increased in size, the hepatopancreas in tubular density and the midgut in length. The density of setae and robustness of teeth and spines of individual structures increased. The most pronounced changes from early to late stage larvae involved formation of pores on the paragnaths and labrum, transformation of the mandibular spine-like teeth to molar cusps, development of the filter press in the proventriculus and of infoldings in the previously straight hindgut. The results suggest that early stage L. amboinensis larvae may benefit from soft, perhaps gelatinous prey, whereas later stages are better equipped to handle larger, muscular or more fibrous foods. 2011 Wiley-Liss, Inc.

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

2005-01-01

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

Assessment Methodology for Process Validation Lifecycle Stage 3A.

PubMed

Sayeed-Desta, Naheed; Pazhayattil, Ajay Babu; Collins, Jordan; Chen, Shu; Ingram, Marzena; Spes, Jana

2017-07-01

The paper introduces evaluation methodologies and associated statistical approaches for process validation lifecycle Stage 3A. The assessment tools proposed can be applied to newly developed and launched small molecule as well as bio-pharma products, where substantial process and product knowledge has been gathered. The following elements may be included in Stage 3A: number of 3A batch determination; evaluation of critical material attributes, critical process parameters, critical quality attributes; in vivo in vitro correlation; estimation of inherent process variability (IPV) and PaCS index; process capability and quality dashboard (PCQd); and enhanced control strategy. US FDA guidance on Process Validation: General Principles and Practices, January 2011 encourages applying previous credible experience with suitably similar products and processes. A complete Stage 3A evaluation is a valuable resource for product development and future risk mitigation of similar products and processes. Elements of 3A assessment were developed to address industry and regulatory guidance requirements. The conclusions made provide sufficient information to make a scientific and risk-based decision on product robustness.

Robust Classification and Segmentation of Planar and Linear Features for Construction Site Progress Monitoring and Structural Dimension Compliance Control

NASA Astrophysics Data System (ADS)

Maalek, R.; Lichti, D. D.; Ruwanpura, J.

2015-08-01

The application of terrestrial laser scanners (TLSs) on construction sites for automating construction progress monitoring and controlling structural dimension compliance is growing markedly. However, current research in construction management relies on the planned building information model (BIM) to assign the accumulated point clouds to their corresponding structural elements, which may not be reliable in cases where the dimensions of the as-built structure differ from those of the planned model and/or the planned model is not available with sufficient detail. In addition outliers exist in construction site datasets due to data artefacts caused by moving objects, occlusions and dust. In order to overcome the aforementioned limitations, a novel method for robust classification and segmentation of planar and linear features is proposed to reduce the effects of outliers present in the LiDAR data collected from construction sites. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a robust clustering method. A method is also proposed to robustly extract the points belonging to the flat-slab floors and/or ceilings without performing the aforementioned stages in order to preserve computational efficiency. The applicability of the proposed method is investigated in two scenarios, namely, a laboratory with 30 million points and an actual construction site with over 150 million points. The results obtained by the two experiments validate the suitability of the proposed method for robust segmentation of planar and linear features in contaminated datasets, such as those collected from construction sites.

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

Combination Efficacy of Astragalus membranaceus and Curcuma wenyujin at Different Stages of Tumor Progression in an Imageable Orthotopic Nude Mouse Model of Metastatic Human Ovarian Cancer Expressing Red Fluorescent Protein.

PubMed

Yin, Gang; Tang, Decai; Dai, Jianguo; Liu, Min; Wu, Mianhua; Sun, Y U; Yang, Zhijian; Hoffman, Robert M; Li, Lin; Zhang, Shuo; Guo, Xiuxia

2015-06-01

The present study determined the efficacy of extracts of Astragalus membranaceus (AM) and Curcuma wenyujin (CW), a traditional Chinese medicine herbal mixture, at different tumor stages of an orthotopic nude mouse model of human ovarian cancer expressing red fluorescent protein. The tumor-bearing mice were treated with cisplatinum (CDDP), AM, CW, or a combination of AM and CW in each of three tumor stages, using the same regimen. Group 1 received saline as negative control. Group 2 received CDDP i.p. as positive control with a dose of 2 mg/kg, every three days. Group 3 received AM daily via oral gavage, at a dose of 9120 mg/kg. Group 4 received CW daily via oral gavage, at a dose of 4560 mg/kg. Groups 5, 6 and 7 received combinations of AM and CW daily via oral gavage at low (AM, 2280 mg/kg; CW, 1140 mg/kg), medium (AM, 4560 mg/kg; CW 2280 mg/kg), and high (AM, 9120 mg/kg; CW, 4560 mg/kg) doses. The expression of angiogenesis- and apoptosis-related genes in the tumors were analyzed by immunohistochemistry for matrix metalloproteinase 2 (MMP-2), vascular endothelial growth factor (VEGF) fibroblast growth factor 2 (FGF-2), B-cell lymphoma 2 (Bcl-2) and cyclooxygenase 2 (Cox-2), and by polymerase chain reaction for MMP-2, FGF-2 and Bcl-2. CDDP, AM, and its combination with CW-induced significant growth inhibition of Stage I tumors. Strong efficacy of the combination of AM and CW at high dose was observed. Monotherapy with CDDP, AM, CW, and the combination treatments did not significantly inhibit Stage II and III tumors. The expression of MMP-2, VEGF, FGF-2, and Cox-2 was significantly reduced in Stage I tumors treated with AM, CW, and their combination, suggesting a possible role of these angiogenesis- and apoptosis-related genes in the observed efficacy of the agents tested. This study is the first report on the efficacy of anticancer agents at different stages of ovarian cancer in an orthotopic mouse model. As the tumor progressed, it became treatment-resistant, similar to the clinical situation, further demonstrating the utility of the model and the need for agents acrtive in advanced-stage ovarian cancer. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Phase I-II Study of Fluorouracil in Combination With Phenylbutyrate in Advanced Colorectal Cancer

ClinicalTrials.gov

2013-01-31

Mucinous Adenocarcinoma of the Colon; Mucinous Adenocarcinoma of the Rectum; Recurrent Colon Cancer; Recurrent Rectal Cancer; Signet Ring Adenocarcinoma of the Colon; Signet Ring Adenocarcinoma of the Rectum; Stage IVA Colon Cancer; Stage IVA Rectal Cancer; Stage IVB Colon Cancer; Stage IVB Rectal Cancer

Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency.

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-05-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rituximab, Rasburicase, and Combination Chemotherapy in Treating Young Patients With Newly Diagnosed Advanced B-Cell Leukemia or Lymphoma

ClinicalTrials.gov

2014-09-10

Childhood Burkitt Lymphoma; Childhood Diffuse Large Cell Lymphoma; Childhood Immunoblastic Large Cell Lymphoma; Stage I Childhood Large Cell Lymphoma; Stage I Childhood Small Noncleaved Cell Lymphoma; Stage II Childhood Large Cell Lymphoma; Stage II Childhood Small Noncleaved Cell Lymphoma; Stage III Childhood Large Cell Lymphoma; Stage III Childhood Small Noncleaved Cell Lymphoma; Stage IV Childhood Large Cell Lymphoma; Stage IV Childhood Small Noncleaved Cell Lymphoma; Untreated Childhood Acute Lymphoblastic Leukemia

Options for Robust Airfoil Optimization under Uncertainty

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Li, Wu

2002-01-01

A robust optimization method is developed to overcome point-optimization at the sampled design points. This method combines the best features from several preliminary methods proposed by the authors and their colleagues. The robust airfoil shape optimization is a direct method for drag reduction over a given range of operating conditions and has three advantages: (1) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (2) it uses a large number of spline control points as design variables yet the resulting airfoil shape does not need to be smoothed, and (3) it allows the user to make a tradeoff between the level of optimization and the amount of computing time consumed. For illustration purposes, the robust optimization method is used to solve a lift-constrained drag minimization problem for a two-dimensional (2-D) airfoil in Euler flow with 20 geometric design variables.

Topological properties of robust biological and computational networks

PubMed Central

Navlakha, Saket; He, Xin; Faloutsos, Christos; Bar-Joseph, Ziv

2014-01-01

Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields. PMID:24789562

Robust Fuzzy Logic Stabilization with Disturbance Elimination

PubMed Central

Danapalasingam, Kumeresan A.

2014-01-01

A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design. PMID:25177713

Robust image watermarking using DWT and SVD for copyright protection

NASA Astrophysics Data System (ADS)

Harjito, Bambang; Suryani, Esti

2017-02-01

The Objective of this paper is proposed a robust combined Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The RGB image is called a cover medium, and watermark image is converted into gray scale. Then, they are transformed using DWT so that they can be split into several subbands, namely sub-band LL2, LH2, HL2. The watermark image embeds into the cover medium on sub-band LL2. This scheme aims to obtain the higher robustness level than the previous method which performs of SVD matrix factorization image for copyright protection. The experiment results show that the proposed method has robustness against several image processing attacks such as Gaussian, Poisson and Salt and Pepper Noise. In these attacks, noise has average Normalized Correlation (NC) values of 0.574863 0.889784, 0.889782 respectively. The watermark image can be detected and extracted.

Comparison of Two Combination Chemotherapy Regimens Plus Radiation Therapy in Treating Patients With Stage III or Stage IV Endometrial Cancer

ClinicalTrials.gov

2015-04-30

Endometrial Adenocarcinoma; Endometrial Adenosquamous Carcinoma; Endometrial Clear Cell Adenocarcinoma; Endometrial Endometrioid Adenocarcinoma, Variant With Squamous Differentiation; Endometrial Serous Adenocarcinoma; Stage III Uterine Corpus Cancer

Experimental vibration damping characteristics of the third-stage rotor of a three-stage transonic axial-flow compressor

NASA Technical Reports Server (NTRS)

Newman, Frederick A.

1988-01-01

Rotor blade aerodynamic damping is experimentally determined in a three-stage transonic axial flow compressor having design aerodynamic performance goals of 4.5:1 pressure ratio and 65.5 lbm/sec weight flow. The combined damping associated with each mode is determined by a least squares fit of a single degree of freedom system transfer function to the nonsynchronous portion of the rotor blade strain gage output power spectra. The combined damping consists of the aerodynanmic damping and the structural and mechanical damping. The aerodynamic damping varies linearly with the inlet total pressure for a given corrected speed, weight flow, and pressure ratio while the structural and mechanical damping is assumed to remain constant. The combined damping is determined at three inlet total pressure levels to obtain the aerodynamic damping. The third-stage rotor blade aerodynamic damping is presented and discussed for the design equivalent speed with the stator blades reset for maximum efficiency. The compressor overall performance and experimental Campbell diagrams for the third-stage rotor blade row are also presented.

Experimental Vibration Damping Characteristics of the Third-stage Rotor of a Three-stage Transonic Axial-flow Compressor

NASA Technical Reports Server (NTRS)

Newman, Frederick A.

1988-01-01

Rotor blade aerodynamic damping is experimentally determined in a three-stage transonic axial flow compressor having design aerodynamic performance goals of 4.5:1 pressure ratio and 65.5 lbm/sec weight flow. The combined damping associated with each mode is determined by a least squares fit of a single degree of freedom system transfer function to the nonsynchronous portion of the rotor blade strain gage output power spectra. The combined damping consists of the aerodynamic damping and the structural and mechanical damping. The aerodynamic damping varies linearly with the inlet total pressure for a given corrected speed, weight flow, and pressure ratio while the structural and mechanical damping is assumed to remain constant. The combined damping is determined at three inlet total pressure levels to obtain the aerodynamic damping. The third-stage rotor blade aerodynamic damping is presented and discussed for the design equivalent speed with the stator blades reset for maximum efficiency. The compressor overall preformance and experimental Campbell diagrams for the third-stage rotor blade row are also presented.

Variation in advanced stage at diagnosis of lung and female breast cancer in an English region 2006-2009.

PubMed

Lyratzopoulos, G; Abel, G A; Barbiere, J M; Brown, C H; Rous, B A; Greenberg, D C

2012-03-13

Understanding variation in stage at diagnosis can inform interventions to improve the timeliness of diagnosis for patients with different cancers and characteristics. We analysed population-based data on 17,836 and 13,286 East of England residents diagnosed with (female) breast and lung cancer during 2006-2009, with stage information on 16,460 (92%) and 10,435 (79%) patients, respectively. Odds ratios (ORs) of advanced stage at diagnosis adjusted for patient and tumour characteristics were derived using logistic regression. We present adjusted ORs of diagnosis in stages III/IV compared with diagnosis in stages I/II. For breast cancer, the frequency of advanced stage at diagnosis increased stepwise among old women (ORs: 1.21, 1.46, 1.68 and 1.78 for women aged 70-74, 75-79, 80-84 and ≥85, respectively, compared with those aged 65-69 , P<0.001). In contrast, for lung cancer advanced stage at diagnosis was less frequent in old patients (ORs: 0.82, 0.74, 0.73 and 0.66, P<0.001). Advanced stage at diagnosis was more frequent in more deprived women with breast cancer (OR: 1.23 for most compared with least deprived, P=0.002), and in men with lung cancer (OR: 1.14, P=0.011). The observed patterns were robust to sensitivity analyses approaches for handling missing stage data under different assumptions. Interventions to help improve the timeliness of diagnosis of different cancers should be targeted at specific age groups.

Active learning based segmentation of Crohns disease from abdominal MRI.

PubMed

Mahapatra, Dwarikanath; Vos, Franciscus M; Buhmann, Joachim M

2016-05-01

This paper proposes a novel active learning (AL) framework, and combines it with semi supervised learning (SSL) for segmenting Crohns disease (CD) tissues from abdominal magnetic resonance (MR) images. Robust fully supervised learning (FSL) based classifiers require lots of labeled data of different disease severities. Obtaining such data is time consuming and requires considerable expertise. SSL methods use a few labeled samples, and leverage the information from many unlabeled samples to train an accurate classifier. AL queries labels of most informative samples and maximizes gain from the labeling effort. Our primary contribution is in designing a query strategy that combines novel context information with classification uncertainty and feature similarity. Combining SSL and AL gives a robust segmentation method that: (1) optimally uses few labeled samples and many unlabeled samples; and (2) requires lower training time. Experimental results show our method achieves higher segmentation accuracy than FSL methods with fewer samples and reduced training effort. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

MDM2 antagonists synergize broadly and robustly with compounds targeting fundamental oncogenic signaling pathways

PubMed Central

Yu, Dongyin; Lofgren, Julie A.; Osgood, Tao; Robertson, Rebecca; Canon, Jude; Su, Cheng; Jones, Adrie; Zhao, Xiaoning; Deshpande, Chetan; Payton, Marc; Ledell, Jebediah; Hughes, Paul E.; Oliner, Jonathan D.

2014-01-01

While MDM2 inhibitors hold great promise as cancer therapeutics, drug resistance will likely limit their efficacy as single agents. To identify drug combinations that might circumvent resistance, we screened for agents that could synergize with MDM2 inhibition in the suppression of cell viability. We observed broad and robust synergy when combining MDM2 antagonists with either MEK or PI3K inhibitors. Synergy was not limited to cell lines harboring MAPK or PI3K pathway mutations, nor did it depend on which node of the PI3K axis was targeted. MDM2 inhibitors also synergized strongly with BH3 mimetics, BCR-ABL antagonists, and HDAC inhibitors. MDM2 inhibitor-mediated synergy with agents targeting these mechanisms was much more prevalent than previously appreciated, implying that clinical translation of these combinations could have far-reaching implications for public health. These findings highlight the importance of combinatorial drug targeting and provide a framework for the rational design of MDM2 inhibitor clinical trials. PMID:24810962

A robust response to combination immune checkpoint inhibitor therapy in HPV-related small cell cancer: a case report.

PubMed

Ho, Won Jin; Rooper, Lisa; Sagorsky, Sarah; Kang, Hyunseok

2018-05-09

Human papillomavirus-related small cell carcinoma of the head and neck is an extremely rare, aggressive subtype with poor outcomes. Therapeutic options are limited and are largely adopted from small cell lung cancer treatment paradigms. This report describes a 69-year old male who was diagnosed of HPV-related oropharyngeal cancer with mixed small cell and squamous cell pathology which was clinically aggressive and progressed through multimodal platinum-based therapies. Upon manifestation of worsening metastatic disease, the patient was initiated on a combination of ipilimumab and nivolumab. Within 2 months of starting immunotherapy, a robust partial response was observed. During the treatment course, the patient developed immune-related adverse effects including new diabetes mellitus, colitis, and hypothyroidism. The disease-specific survival was 26 months. Combination immunotherapy may be an attractive option for HPV-related small cell head and neck cancers resistant to other treatment modalities and thus warrants further evaluation.

Nivolumab After Combined Modality Therapy in Treating Patients With High Risk Stage II-IIIB Anal Cancer

ClinicalTrials.gov

2018-06-20

Anal Basaloid Carcinoma; Anal Canal Cloacogenic Carcinoma; Anal Margin Squamous Cell Carcinoma; Stage II Anal Canal Cancer AJCC v6 and v7; Stage IIB Anal Cancer AJCC v8; Stage III Anal Canal Cancer AJCC v6 and v7; Stage IIIA Anal Canal Cancer AJCC v6 and v7; Stage IIIB Anal Canal Cancer AJCC v6 and v7

In Vitro Activities of Primaquine-Schizonticide Combinations on Asexual Blood Stages and Gametocytes of Plasmodium falciparum.

PubMed

Cabrera, Mynthia; Cui, Liwang

2015-12-01

Currently, the World Health Organization recommends addition of a 0.25-mg base/kg single dose of primaquine (PQ) to artemisinin combination therapies (ACTs) for Plasmodium falciparum malaria as a gametocytocidal agent for reducing transmission. Here, we investigated the potential interactions of PQ with the long-lasting components of the ACT drugs for eliminating the asexual blood stages and gametocytes of in vitro-cultured P. falciparum strains. Using the SYBR green I assay for asexual parasites and a flow cytometry-based assay for gametocytes, we determined the interactions of PQ with the schizonticides chloroquine, mefloquine, piperaquine, lumefantrine, and naphthoquine. With the sums of fractional inhibitory concentrations and isobolograms, we were able to determine mostly synergistic interactions for the various PQ and schizonticide combinations on the blood stages of P. falciparum laboratory strains. The synergism in inhibiting asexual stages and gametocytes was highly evident with PQ-naphthoquine, whereas synergism was moderate for the PQ-piperaquine, PQ-chloroquine, and PQ-mefloquine combinations. We have detected potentially antagonistic interactions between PQ and lumefantrine under certain drug combination ratios, suggesting that precautions might be needed when PQ is added as the gametocytocide to the artemether-lumefantrine ACT (Coartem). Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Linear Combinations of Multiple Outcome Measures to Improve the Power of Efficacy Analysis ---Application to Clinical Trials on Early Stage Alzheimer Disease

PubMed Central

Xiong, Chengjie; Luo, Jingqin; Morris, John C; Bateman, Randall

2018-01-01

Modern clinical trials on Alzheimer disease (AD) focus on the early symptomatic stage or even the preclinical stage. Subtle disease progression at the early stages, however, poses a major challenge in designing such clinical trials. We propose a multivariate mixed model on repeated measures to model the disease progression over time on multiple efficacy outcomes, and derive the optimum weights to combine multiple outcome measures by minimizing the sample sizes to adequately power the clinical trials. A cross-validation simulation study is conducted to assess the accuracy for the estimated weights as well as the improvement in reducing the sample sizes for such trials. The proposed methodology is applied to the multiple cognitive tests from the ongoing observational study of the Dominantly Inherited Alzheimer Network (DIAN) to power future clinical trials in the DIAN with a cognitive endpoint. Our results show that the optimum weights to combine multiple outcome measures can be accurately estimated, and that compared to the individual outcomes, the combined efficacy outcome with these weights significantly reduces the sample size required to adequately power clinical trials. When applied to the clinical trial in the DIAN, the estimated linear combination of six cognitive tests can adequately power the clinical trial. PMID:29546251

Autologous microtia reconstruction combined with ancillary procedures: a comprehensive reconstructive approach.

PubMed

Cugno, S; Farhadieh, R D; Bulstrode, N W

2013-11-01

Autologous microtia reconstruction is generally performed in two stages. The second stage presents a unique opportunity to carry out other complementary procedures. The present study describes our approach to microtia reconstruction, wherein the second stage of reconstruction is combined with final refinements to the ear construct and/or additional procedures to enhance facial contour and symmetry. Retrospective analysis of patients who underwent two-stage microtia reconstruction by a single surgeon (NWB) was conducted in order to ascertain those that had ancillary procedures at the time of the second stage. Patient and operative details were collected. Thirty-four patients (male, 15, median age and age range at second stage, 11 and 10-18 years, respectively) who had complementary procedures executed during the second stage of auricular reconstruction were identified. Collectively, these included centralizing genioplasty (n = 1), fat transfer (n = 22), ear piercing (n = 7), and contralateral prominauris correction (n = 7). Six patients had correction for unilateral isolated microtia and in the remaining 28 patients, auricular reconstruction for microtia associated with a named syndrome. All patients reported a high rate of satisfaction with the result achieved and the majority (85%) reported no perceived need for additional surgical refinements to the ear or procedure(s) to achieve further facial symmetry. No peri- or post-operative complications were noted. Combining the final stage of autologous microtia reconstruction with other ancillary procedures affords a superior aesthetic outcome and decreased patient morbidity. Copyright © 2013 British Association of Plastic, Reconstructive and Aesthetic Surgeons. All rights reserved.

Development and testing of a de novo clinical staging system for podoconiosis (endemic non-filarial elephantiasis)

PubMed Central

Tekola, Fasil; Ayele, Zewdu; HaileMariam, Dereje; Fuller, Claire; Davey, Gail

2010-01-01

Summary Background Podoconiosis (endemic non-filarial elephantiasis) is a geochemical disease in individuals exposed to red-clay soil. Despite the prevalence and public health importance of podoconiosis, there is as yet no accepted clinical staging system. Objective We aimed to develop and test a robust clinical staging system for podoconiosis. Methods We adapted the Dreyer system for staging filarial lymphoedema and tested it in four re-iterative field tests conducted in an area of high podoconiosis prevalence in Southern Ethiopia. The system finally arrived at has five stages according to proximal spread of disease and presence of dermal nodules, ridges and bands. We measured the one-week repeatability and the inter-observer agreement of the final staging system. Results We have developed a five-stage system that is readily understood by community workers with little health training. Kappa for one-week repeatability was 0.88 (95% CI 0.80 to 0.96), Kappa for agreement between health professionals was 0.71 (95% CI 0.60 to 0.82), while that between health professionals and community podoconiosis agents without formal health training averaged 0.64 (95% CI 0.52 to 0.78). Conclusions A simple staging system with good inter-observer agreement and repeatability has been developed to assist in the management and further study of podoconiosis. PMID:18721188

A Technology Pathway for Airbreathing, Combined-Cycle, Horizontal Space Launch Through SR-71 Based Trajectory Modeling

NASA Technical Reports Server (NTRS)

Kloesel, Kurt J.; Ratnayake, Nalin A.; Clark, Casie M.

2011-01-01

Access to space is in the early stages of commercialization. Private enterprises, mainly under direct or indirect subsidy by the government, have been making headway into the LEO launch systems infrastructure, of small-weight-class payloads of approximately 1000 lbs. These moderate gains have emboldened the launch industry and they are poised to move into the middle-weight class (roughly 5000 lbs). These commercially successful systems are based on relatively straightforward LOX-RP, two-stage, bi-propellant rocket technology developed by the government 40 years ago, accompanied by many technology improvements. In this paper we examine a known generic LOX-RP system with the focus on the booster stage (1st stage). The booster stage is then compared to modeled Rocket-Based and Turbine-Based Combined Cycle booster stages. The air-breathing propulsion stages are based on/or extrapolated from known performance parameters of ground tested RBCC (the Marquardt Ejector Ramjet) and TBCC (the SR-71/J-58 engine) data. Validated engine models using GECAT and SCCREAM are coupled with trajectory optimization and analysis in POST-II to explore viable launch scenarios using hypothetical aerospaceplane platform obeying the aerodynamic model of the SR-71. Finally, and assessment is made of the requisite research technology advances necessary for successful commercial and government adoption of combined-cycle engine systems for space access.

A 1-W, 30-ghz, CPW Amplifier for ACTS Small Terminal Uplink

NASA Technical Reports Server (NTRS)

Taub, Susan R.; Simons, Rainee N.

1992-01-01

The progress is described of the development of a 1 W, 30 GHz, coplanar waveguide (CPW) amplifier for the Advanced Communication Technology Satellite (ACTS)Small Terminal Uplink. The amplifier is based on Texas Instruments' monolithic microwave integrated circuit (MMIC) amplifiers; a three stage, low power amplifier, and a single stage, high power amplifier. The amplifiers have a power output of 190 mW and 0.710 W, gain of 23 and 4.2 dB, and efficiencies of 30.2 and 24 percent for the three stage and one stage amplifiers, respectively. The chips are to be combined via a CPW power divider/combiner circuit to yield the desired 1 W of output power.

Improved blood glucose estimation through multi-sensor fusion.

PubMed

Xiong, Feiyu; Hipszer, Brian R; Joseph, Jeffrey; Kam, Moshe

2011-01-01

Continuous glucose monitoring systems are an integral component of diabetes management. Efforts to improve the accuracy and robustness of these systems are at the forefront of diabetes research. Towards this goal, a multi-sensor approach was evaluated in hospitalized patients. In this paper, we report on a multi-sensor fusion algorithm to combine glucose sensor measurements in a retrospective fashion. The results demonstrate the algorithm's ability to improve the accuracy and robustness of the blood glucose estimation with current glucose sensor technology.

Trametinib, Combination Chemotherapy, and Radiation Therapy in Treating Patients With Stage III Non-small Cell Lung Cancer That Cannot Be Removed by Surgery

ClinicalTrials.gov

2018-05-23

KRAS Activating Mutation; Recurrent Non-Small Cell Lung Carcinoma; Stage III Non-Small Cell Lung Cancer AJCC v7; Stage IIIA Non-Small Cell Lung Cancer AJCC v7; Stage IIIB Non-Small Cell Lung Cancer AJCC v7

Combination Chemotherapy and Filgrastim Before Surgery in Treating Patients With HER2-Positive Breast Cancer That Can Be Removed By Surgery

ClinicalTrials.gov

2018-02-12

Estrogen Receptor-negative Breast Cancer; Estrogen Receptor-positive Breast Cancer; HER2-positive Breast Cancer; Progesterone Receptor-negative Breast Cancer; Progesterone Receptor-positive Breast Cancer; Stage IA Breast Cancer; Stage IB Breast Cancer; Stage II Breast Cancer; Stage IIIA Breast Cancer

Brentuximab Vedotin or Crizotinib and Combination Chemotherapy in Treating Patients With Newly Diagnosed Stage II-IV Anaplastic Large Cell Lymphoma

ClinicalTrials.gov

2018-06-25

Anaplastic Large Cell Lymphoma, ALK-Positive; Ann Arbor Stage II Noncutaneous Childhood Anaplastic Large Cell Lymphoma; Ann Arbor Stage III Noncutaneous Childhood Anaplastic Large Cell Lymphoma; Ann Arbor Stage IV Noncutaneous Childhood Anaplastic Large Cell Lymphoma; CD30-Positive Neoplastic Cells Present

Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer

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

Liu, Wei, E-mail: Liu.Wei@mayo.edu; Schild, Steven E.; Chang, Joe Y.

Purpose: The purpose of this study was to compare the impact of uncertainties and interplay on 3-dimensional (3D) and 4D robustly optimized intensity modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study. Methods and Materials: IMPT plans were created for 11 nonrandomly selected non-small cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D computed tomography (CT) to irradiate clinical target volume (CTV). Regular fractionation (66 Gy [relative biological effectiveness; RBE] in 33 fractions) was considered.more » In 4D optimization, the CTV of individual phases received nonuniform doses to achieve a uniform cumulative dose. The root-mean-square dose-volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram (DVH) indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed rank test. Results: 4D robust optimization plans led to smaller AUC for CTV (14.26 vs 18.61, respectively; P=.001), better CTV coverage (Gy [RBE]) (D{sub 95%} CTV: 60.6 vs 55.2, respectively; P=.001), and better CTV homogeneity (D{sub 5%}-D{sub 95%} CTV: 10.3 vs 17.7, resspectively; P=.002) in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage (D{sub 95%} CTV: 64.5 vs 63.8, respectively; P=.0068), comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients. Conclusions: Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions.« less

Lunar lander and return propulsion system trade study

NASA Technical Reports Server (NTRS)

Hurlbert, Eric A.; Moreland, Robert; Sanders, Gerald B.; Robertson, Edward A.; Amidei, David; Mulholland, John

1993-01-01

This trade study was initiated at NASA/JSC in May 1992 to develop and evaluate main propulsion system alternatives to the reference First Lunar Outpost (FLO) lander and return-stage transportation system concept. Thirteen alternative configurations were developed to explore the impacts of various combinations of return stage propellants, using either pressure or pump-fed propulsion systems and various staging options. Besides two-stage vehicle concepts, the merits of single-stage and stage-and-a-half options were also assessed in combination with high-performance liquid oxygen and liquid hydrogen propellants. Configurations using an integrated modular cryogenic engine were developed to assess potential improvements in packaging efficiency, mass performance, and system reliability compared to non-modular cryogenic designs. The selection process to evaluate the various designs was the analytic hierarchy process. The trade study showed that a pressure-fed MMH/N2O4 return stage and RL10-based lander stage is the best option for a 1999 launch. While results of this study are tailored to FLO needs, the design date, criteria, and selection methodology are applicable to the design of other crewed lunar landing and return vehicles.

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery rate

PubMed Central

Motulsky, Harvey J; Brown, Ronald E

2006-01-01

Background Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads to the familiar goal of regression: to minimize the sum of the squares of the vertical or Y-value distances between the points and the curve. Outliers can dominate the sum-of-the-squares calculation, and lead to misleading results. However, we know of no practical method for routinely identifying outliers when fitting curves with nonlinear regression. Results We describe a new method for identifying outliers when fitting data with nonlinear regression. We first fit the data using a robust form of nonlinear regression, based on the assumption that scatter follows a Lorentzian distribution. We devised a new adaptive method that gradually becomes more robust as the method proceeds. To define outliers, we adapted the false discovery rate approach to handling multiple comparisons. We then remove the outliers, and analyze the data using ordinary least-squares regression. Because the method combines robust regression and outlier removal, we call it the ROUT method. When analyzing simulated data, where all scatter is Gaussian, our method detects (falsely) one or more outlier in only about 1–3% of experiments. When analyzing data contaminated with one or several outliers, the ROUT method performs well at outlier identification, with an average False Discovery Rate less than 1%. Conclusion Our method, which combines a new method of robust nonlinear regression with a new method of outlier identification, identifies outliers from nonlinear curve fits with reasonable power and few false positives. PMID:16526949

Human neuron-astrocyte 3D co-culture-based assay for evaluation of neuroprotective compounds.

PubMed

Terrasso, Ana Paula; Silva, Ana Carina; Filipe, Augusto; Pedroso, Pedro; Ferreira, Ana Lúcia; Alves, Paula Marques; Brito, Catarina

Central nervous system drug development has registered high attrition rates, mainly due to the lack of efficacy of drug candidates, highlighting the low reliability of the models used in early-stage drug development and the need for new in vitro human cell-based models and assays to accurately identify and validate drug candidates. 3D human cell models can include different tissue cell types and represent the spatiotemporal context of the original tissue (co-cultures), allowing the establishment of biologically-relevant cell-cell and cell-extracellular matrix interactions. Nevertheless, exploitation of these 3D models for neuroprotection assessment has been limited due to the lack of data to validate such 3D co-culture approaches. In this work we combined a 3D human neuron-astrocyte co-culture with a cell viability endpoint for the implementation of a novel in vitro neuroprotection assay, over an oxidative insult. Neuroprotection assay robustness and specificity, and the applicability of Presto Blue, MTT and CytoTox-Glo viability assays to the 3D co-culture were evaluated. Presto Blue was the adequate endpoint as it is non-destructive and is a simpler and reliable assay. Semi-automation of the cell viability endpoint was performed, indicating that the assay setup is amenable to be transferred to automated screening platforms. Finally, the neuroprotection assay setup was applied to a series of 36 test compounds and several candidates with higher neuroprotective effect than the positive control, Idebenone, were identified. The robustness and simplicity of the implemented neuroprotection assay with the cell viability endpoint enables the use of more complex and reliable 3D in vitro cell models to identify and validate drug candidates. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

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

Uehara, Takeki, E-mail: takeki.uehara@shionogi.co.jp; Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085; Minowa, Yohsuke

2011-09-15

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificitymore » in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: >We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. >The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. >This model enables us to detect genotoxic as well as non-genotoxic hepatocarcinogens.« less

A Multi-Level Parallelization Concept for High-Fidelity Multi-Block Solvers

NASA Technical Reports Server (NTRS)

Hatay, Ferhat F.; Jespersen, Dennis C.; Guruswamy, Guru P.; Rizk, Yehia M.; Byun, Chansup; Gee, Ken; VanDalsem, William R. (Technical Monitor)

1997-01-01

The integration of high-fidelity Computational Fluid Dynamics (CFD) analysis tools with the industrial design process benefits greatly from the robust implementations that are transportable across a wide range of computer architectures. In the present work, a hybrid domain-decomposition and parallelization concept was developed and implemented into the widely-used NASA multi-block Computational Fluid Dynamics (CFD) packages implemented in ENSAERO and OVERFLOW. The new parallel solver concept, PENS (Parallel Euler Navier-Stokes Solver), employs both fine and coarse granularity in data partitioning as well as data coalescing to obtain the desired load-balance characteristics on the available computer platforms. This multi-level parallelism implementation itself introduces no changes to the numerical results, hence the original fidelity of the packages are identically preserved. The present implementation uses the Message Passing Interface (MPI) library for interprocessor message passing and memory accessing. By choosing an appropriate combination of the available partitioning and coalescing capabilities only during the execution stage, the PENS solver becomes adaptable to different computer architectures from shared-memory to distributed-memory platforms with varying degrees of parallelism. The PENS implementation on the IBM SP2 distributed memory environment at the NASA Ames Research Center obtains 85 percent scalable parallel performance using fine-grain partitioning of single-block CFD domains using up to 128 wide computational nodes. Multi-block CFD simulations of complete aircraft simulations achieve 75 percent perfect load-balanced executions using data coalescing and the two levels of parallelism. SGI PowerChallenge, SGI Origin 2000, and a cluster of workstations are the other platforms where the robustness of the implementation is tested. The performance behavior on the other computer platforms with a variety of realistic problems will be included as this on-going study progresses.

Robust multiple frequency multiple power localization schemes in the presence of multiple jamming attacks

PubMed Central

2017-01-01

Localization of the wireless sensor network is a vital area acquiring an impressive research concern and called upon to expand more with the rising of its applications. As localization is gaining prominence in wireless sensor network, it is vulnerable to jamming attacks. Jamming attacks disrupt communication opportunity among the sender and receiver and deeply impact the localization process, leading to a huge error of the estimated sensor node position. Therefore, detection and elimination of jamming influence are absolutely indispensable. Range-based techniques especially Received Signal Strength (RSS) is facing severe impact of these attacks. This paper proposes algorithms based on Combination Multiple Frequency Multiple Power Localization (C-MFMPL) and Step Function Multiple Frequency Multiple Power Localization (SF-MFMPL). The algorithms have been tested in the presence of multiple types of jamming attacks including capture and replay, random and constant jammers over a log normal shadow fading propagation model. In order to overcome the impact of random and constant jammers, the proposed method uses two sets of frequencies shared by the implemented anchor nodes to obtain the averaged RSS readings all over the transmitted frequencies successfully. In addition, three stages of filters have been used to cope with the replayed beacons caused by the capture and replay jammers. In this paper the localization performance of the proposed algorithms for the ideal case which is defined by without the existence of the jamming attack are compared with the case of jamming attacks. The main contribution of this paper is to achieve robust localization performance in the presence of multiple jamming attacks under log normal shadow fading environment with a different simulation conditions and scenarios. PMID:28493977

Activated AMPK and prostaglandins are involved in the response to conjugated linoleic acid and are sufficient to cause lipid reductions in adipocytes.

PubMed

Jiang, Shan; Chen, Han; Wang, Zhigang; Riethoven, Jean-Jack; Xia, Yuannan; Miner, Jess; Fromm, Michael

2011-07-01

trans-10, cis-12 Conjugated linoleic acid (t10c12 CLA) reduces triglyceride levels in adipocytes. AMP-activated protein kinase (AMPK) and inflammation were recently demonstrated to be involved in the emerging pathways regulating this response. This study further investigated the role of AMPK and inflammation by testing the following hypotheses: (1) a moderate activation of AMPK and an inflammatory response are sufficient to reduce triglycerides, and (2) strong activation of AMPK is also sufficient. Experiments were performed by adding compounds that affect these pathways and by measuring their effects in 3T3-L1 adipocytes. A comparison of four AMPK activators (metformin, phenformin, TNF-α and t10c12 CLA) found a correlation between AMPK activity and triglyceride reduction. This correlation appeared to be modulated by the level of cyclo-oxygenase (COX)-2 mRNA produced. Inhibitors of the prostaglandin (PG) biosynthetic pathway interfered with t10c12 CLA's ability to reduce triglycerides. A combination of metformin and PGH2, or phenformin alone, efficiently reduced triglyceride levels in adipocytes. Microarray analysis indicated that the transcriptional responses to phenformin or t10c12 CLA were very similar, suggesting similar pathways were activated. 3T3-L1 fibroblasts were found to weakly induce the integrated stress response (ISR) in response to phenformin or t10c12 CLA and to respond robustly as they differentiated into adipocytes. This indicated that both chemicals required adipocytes at the same stage of differentiation to be competent for this response. These results support the above hypotheses and suggest compounds that moderately activate AMPK and increase PG levels or robustly activate AMPK in adipocytes may be beneficial for reducing adiposity. Copyright © 2011 Elsevier Inc. All rights reserved.

Essential energy space random walks to accelerate molecular dynamics simulations: Convergence improvements via an adaptive-length self-healing strategy

NASA Astrophysics Data System (ADS)

Zheng, Lianqing; Yang, Wei

2008-07-01

Recently, accelerated molecular dynamics (AMD) technique was generalized to realize essential energy space random walks so that further sampling enhancement and effective localized enhanced sampling could be achieved. This method is especially meaningful when essential coordinates of the target events are not priori known; moreover, the energy space metadynamics method was also introduced so that biasing free energy functions can be robustly generated. Despite the promising features of this method, due to the nonequilibrium nature of the metadynamics recursion, it is challenging to rigorously use the data obtained at the recursion stage to perform equilibrium analysis, such as free energy surface mapping; therefore, a large amount of data ought to be wasted. To resolve such problem so as to further improve simulation convergence, as promised in our original paper, we are reporting an alternate approach: the adaptive-length self-healing (ALSH) strategy for AMD simulations; this development is based on a recent self-healing umbrella sampling method. Here, the unit simulation length for each self-healing recursion is increasingly updated based on the Wang-Landau flattening judgment. When the unit simulation length for each update is long enough, all the following unit simulations naturally run into the equilibrium regime. Thereafter, these unit simulations can serve for the dual purposes of recursion and equilibrium analysis. As demonstrated in our model studies, by applying ALSH, both fast recursion and short nonequilibrium data waste can be compromised. As a result, combining all the data obtained from all the unit simulations that are in the equilibrium regime via the weighted histogram analysis method, efficient convergence can be robustly ensured, especially for the purpose of free energy surface mapping.

Veliparib and Atezolizumab Either Alone or in Combination in Treating Patients With Stage III-IV Triple Negative Breast Cancer

ClinicalTrials.gov

2018-03-20

BRCA1 Gene Mutation; BRCA2 Gene Mutation; Estrogen Receptor Negative; HER2/Neu Negative; Progesterone Receptor Negative; Recurrent Breast Carcinoma; Stage III Breast Cancer AJCC v7; Stage IIIA Breast Cancer AJCC v7; Stage IIIB Breast Cancer AJCC v7; Stage IIIC Breast Cancer AJCC v7; Stage IV Breast Cancer AJCC v6 and v7; Triple-Negative Breast Carcinoma

Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity

PubMed Central

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Wörgötter, Florentin

2011-01-01

Synaptic scaling is a slow process that modifies synapses, keeping the firing rate of neural circuits in specific regimes. Together with other processes, such as conventional synaptic plasticity in the form of long term depression and potentiation, synaptic scaling changes the synaptic patterns in a network, ensuring diverse, functionally relevant, stable, and input-dependent connectivity. How synaptic patterns are generated and stabilized, however, is largely unknown. Here we formally describe and analyze synaptic scaling based on results from experimental studies and demonstrate that the combination of different conventional plasticity mechanisms and synaptic scaling provides a powerful general framework for regulating network connectivity. In addition, we design several simple models that reproduce experimentally observed synaptic distributions as well as the observed synaptic modifications during sustained activity changes. These models predict that the combination of plasticity with scaling generates globally stable, input-controlled synaptic patterns, also in recurrent networks. Thus, in combination with other forms of plasticity, synaptic scaling can robustly yield neuronal circuits with high synaptic diversity, which potentially enables robust dynamic storage of complex activation patterns. This mechanism is even more pronounced when considering networks with a realistic degree of inhibition. Synaptic scaling combined with plasticity could thus be the basis for learning structured behavior even in initially random networks. PMID:22203799

Trametinib or Combination Chemotherapy in Treating Patients With Refractory or Advanced Biliary or Gallbladder Cancer or That Cannot Be Removed by Surgery

ClinicalTrials.gov

2017-08-11

Adult Cholangiocarcinoma; Advanced Adult Hepatocellular Carcinoma; BCLC Stage C Adult Hepatocellular Carcinoma; BCLC Stage D Adult Hepatocellular Carcinoma; Hilar Cholangiocarcinoma; Localized Non-Resectable Adult Liver Carcinoma; Recurrent Adult Liver Carcinoma; Recurrent Childhood Liver Cancer; Recurrent Extrahepatic Bile Duct Carcinoma; Recurrent Gallbladder Carcinoma; Stage II Gallbladder Cancer; Stage III Childhood Hepatocellular Carcinoma; Stage IIIA Gallbladder Cancer; Stage IIIB Gallbladder Cancer; Stage IV Childhood Hepatocellular Carcinoma; Stage IV Distal Bile Duct Cancer; Stage IVA Gallbladder Cancer; Stage IVB Gallbladder Cancer; Unresectable Extrahepatic Bile Duct Carcinoma

Architecture and robustness tradeoffs in speed-scaled queues with application to energy management

NASA Astrophysics Data System (ADS)

Dinh, Tuan V.; Andrew, Lachlan L. H.; Nazarathy, Yoni

2014-08-01

We consider single-pass, lossless, queueing systems at steady-state subject to Poisson job arrivals at an unknown rate. Service rates are allowed to depend on the number of jobs in the system, up to a fixed maximum, and power consumption is an increasing function of speed. The goal is to control the state dependent service rates such that both energy consumption and delay are kept low. We consider a linear combination of the mean job delay and energy consumption as the performance measure. We examine both the 'architecture' of the system, which we define as a specification of the number of speeds that the system can choose from, and the 'design' of the system, which we define as the actual speeds available. Previous work has illustrated that when the arrival rate is precisely known, there is little benefit in introducing complex (multi-speed) architectures, yet in view of parameter uncertainty, allowing a variable number of speeds improves robustness. We quantify the tradeoffs of architecture specification with respect to robustness, analysing both global robustness and a newly defined measure which we call local robustness.

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.

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

PubMed

Wang, Ding; Liu, Derong

2018-06-01

The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

Use of Adjuvant 5-Fluorouracil and Radiation Therapy After Gastric Cancer Resection Among the Elderly and Impact on Survival

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

Strauss, Joshua; Hershman, Dawn L.; Department of Herbert Irving Comprehensive Cancer Center, College of Physicians and Surgeons, Columbia University, New York, NY

2010-04-15

Purpose: In randomized trials patients with resected nonmetastatic gastric cancer who received adjuvant chemotherapy and radiotherapy (chemoRT) had better survival than those who did not. We investigated the effectiveness of adjuvant chemoRT after gastric cancer resection in an elderly general population and its effects by stage. Methods and Materials: We identified individuals in the Surveillance, Epidemiology, and End Results-Medicare database aged 65 years or older with Stage IB through Stage IV (M0) gastric cancer, from 1991 to 2002, who underwent gastric resection, using multivariate modeling to analyze predictors of chemoRT use and survival. Results: Among 1,993 patients who received combinedmore » chemoRT or no adjuvant therapy after resection, having a later year of diagnosis, having a more advanced stage, being younger, being white, being married, and having fewer comorbidities were associated with combined treatment. Among 1,476 patients aged less than 85 years who survived more than 4 months, the 313 who received combined treatment had a lower mortality rate (hazard ratio, 0.83; 95% confidence interval, 0.71-0.98) than the 1,163 who received surgery alone. Adjuvant therapy significantly reduced the mortality rate for Stages III and IV (M0), trended toward improved survival for Stage II, and showed no benefit for Stage IB. We observed trends toward improved survival in all age categories except 80 to 85 years. Conclusions: The association of combined adjuvant chemoRT with improved survival in an overall analysis of Stage IB through Stage IV (M0) resected gastric cancer is consistent with clinical trial results and suggests that, in an elderly population, adjuvant chemoradiotherapy is effective. However, our observational data suggest that adjuvant treatment may not be effective for Stage IB cancer, is possibly appropriate for Stage II, and shows significant survival benefits for Stages III and IV (M0) for those aged less than 80 years.« less

Combination Chemotherapy With or Without Bortezomib in Treating Younger Patients With Newly Diagnosed T-Cell Acute Lymphoblastic Leukemia or Stage II-IV T-Cell Lymphoblastic Lymphoma

ClinicalTrials.gov

2018-06-27

Adult T Acute Lymphoblastic Leukemia; Ann Arbor Stage II Adult Lymphoblastic Lymphoma; Ann Arbor Stage II Childhood Lymphoblastic Lymphoma; Ann Arbor Stage III Adult Lymphoblastic Lymphoma; Ann Arbor Stage III Childhood Lymphoblastic Lymphoma; Ann Arbor Stage IV Adult Lymphoblastic Lymphoma; Ann Arbor Stage IV Childhood Lymphoblastic Lymphoma; Childhood T Acute Lymphoblastic Leukemia; Untreated Adult Acute Lymphoblastic Leukemia; Untreated Childhood Acute Lymphoblastic Leukemia

Evaluation of Robustness to Setup and Range Uncertainties for Head and Neck Patients Treated With Pencil Beam Scanning Proton Therapy

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

Malyapa, Robert; Lowe, Matthew; Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester

Purpose: To evaluate the robustness of head and neck plans for treatment with intensity modulated proton therapy to range and setup errors, and to establish robustness parameters for the planning of future head and neck treatments. Methods and Materials: Ten patients previously treated were evaluated in terms of robustness to range and setup errors. Error bar dose distributions were generated for each plan, from which several metrics were extracted and used to define a robustness database of acceptable parameters over all analyzed plans. The patients were treated in sequentially delivered series, and plans were evaluated for both the first seriesmore » and for the combined error over the whole treatment. To demonstrate the application of such a database in the head and neck, for 1 patient, an alternative treatment plan was generated using a simultaneous integrated boost (SIB) approach and plans of differing numbers of fields. Results: The robustness database for the treatment of head and neck patients is presented. In an example case, comparison of single and multiple field plans against the database show clear improvements in robustness by using multiple fields. A comparison of sequentially delivered series and an SIB approach for this patient show both to be of comparable robustness, although the SIB approach shows a slightly greater sensitivity to uncertainties. Conclusions: A robustness database was created for the treatment of head and neck patients with intensity modulated proton therapy based on previous clinical experience. This will allow the identification of future plans that may benefit from alternative planning approaches to improve robustness.« less

The Influence of Assortativity on the Robustness of Signal-Integration Logic in Gene Regulatory Networks

PubMed Central

Pechenick, Dov A.; Payne, Joshua L.; Moore, Jason H.

2011-01-01

Gene regulatory networks (GRNs) drive the cellular processes that sustain life. To do so reliably, GRNs must be robust to perturbations, such as gene deletion and the addition or removal of regulatory interactions. GRNs must also be robust to genetic changes in regulatory regions that define the logic of signal-integration, as these changes can affect how specific combinations of regulatory signals are mapped to particular gene expression states. Previous theoretical analyses have demonstrated that the robustness of a GRN is influenced by its underlying topological properties, such as degree distribution and modularity. Another important topological property is assortativity, which measures the propensity with which nodes of similar connectivity are connected to one another. How assortativity influences the robustness of the signal-integration logic of GRNs remains an open question. Here, we use computational models of GRNs to investigate this relationship. We separately consider each of the three dynamical regimes of this model for a variety of degree distributions. We find that in the chaotic regime, robustness exhibits a pronounced increase as assortativity becomes more positive, while in the critical and ordered regimes, robustness is generally less sensitive to changes in assortativity. We attribute the increased robustness to a decrease in the duration of the gene expression pattern, which is caused by a reduction in the average size of a GRN’s in-components. This study provides the first direct evidence that assortativity influences the robustness of the signal-integration logic of computational models of GRNs, illuminates a mechanistic explanation for this influence, and furthers our understanding of the relationship between topology and robustness in complex biological systems. PMID:22155134

Design and results of the pretest of the IDEFICS study.

PubMed

Suling, M; Hebestreit, A; Peplies, J; Bammann, K; Nappo, A; Eiben, G; Alvira, J M Fernández; Verbestel, V; Kovács, E; Pitsiladis, Y P; Veidebaum, T; Hadjigeorgiou, C; Knof, K; Ahrens, W

2011-04-01

During the preparatory phase of the baseline survey of the IDEFICS (Identification and prevention of dietary- and lifestyle-induced health effects in children and infants) study, standardised survey procedures including instruments, examinations, methods, biological sampling and software tools were developed and pretested for their feasibility, robustness and acceptability. A pretest was conducted of full survey procedures in 119 children aged 2-9 years in nine European survey centres (N(per centre)=4-27, mean 13.22). Novel techniques such as ultrasound measurements to assess subcutaneous fat and bone health, heart rate monitors combined with accelerometers and sensory taste perception tests were used. Biological sampling, physical examinations, sensory taste perception tests, parental questionnaire and medical interview required only minor amendments, whereas physical fitness tests required major adaptations. Callipers for skinfold measurements were favoured over ultrasonography, as the latter showed only a low-to-modest agreement with calliper measurements (correlation coefficients of r=-0.22 and r=0.67 for all children). The combination of accelerometers with heart rate monitors was feasible in school children only. Implementation of the computer-based 24-h dietary recall required a complex and intensive developmental stage. It was combined with the assessment of school meals, which was changed after the pretest from portion weighing to the more feasible observation of the consumed portion size per child. The inclusion of heel ultrasonometry as an indicator of bone stiffness was the most important amendment after the pretest. Feasibility and acceptability of all procedures had to be balanced against their scientific value. Extensive pretesting, training and subsequent refinement of the methods were necessary to assess the feasibility of all instruments and procedures in routine fieldwork and to exchange or modify procedures that would otherwise give invalid or misleading results.

CALiPER Report 20.3: Robustness of LED PAR38 Lamps

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

Poplawski, Michael E.; Royer, Michael P.; Brown, Charles C.

2014-12-01

Three samples of 40 of the Series 20 PAR38 lamps underwent multi-stress testing, whereby samples were subjected to increasing levels of simultaneous thermal, humidity, electrical, and vibrational stress. The results do not explicitly predict expected lifetime or reliability, but they can be compared with one another, as well as with benchmark conventional products, to assess the relative robustness of the product designs. On average, the 32 LED lamp models tested were substantially more robust than the conventional benchmark lamps. As with other performance attributes, however, there was great variability in the robustness and design maturity of the LED lamps. Severalmore » LED lamp samples failed within the first one or two levels of the ten-level stress plan, while all three samples of some lamp models completed all ten levels. One potential area of improvement is design maturity, given that more than 25% of the lamp models demonstrated a difference in failure level for the three samples that was greater than or equal to the maximum for the benchmarks. At the same time, the fact that nearly 75% of the lamp models exhibited better design maturity than the benchmarks is noteworthy, given the relative stage of development for the technology.« less

Design optimization for cost and quality: The robust design approach

NASA Technical Reports Server (NTRS)

Unal, Resit

1990-01-01

Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.

Robust power spectral estimation for EEG data

PubMed Central

Melman, Tamar; Victor, Jonathan D.

2016-01-01

Background Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. New method Using the multitaper method[1] as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Results Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. Comparison to existing method The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. Conclusion In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. PMID:27102041

Robust power spectral estimation for EEG data.

PubMed

Melman, Tamar; Victor, Jonathan D

2016-08-01

Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.

Formation of Si{sup 1+} in the early stages of the oxidation of the Si[001] 2 × 1 surface

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

Herrera-Gomez, Alberto, E-mail: aherrerag@cinvestav.mx; Aguirre-Tostado, Francisco-Servando; Pianetta, Piero

2016-03-15

The early stages of the oxidation of the Si[001] 2 × 1 surface were studied with synchrotron radiation photoelectron spectroscopy. The analysis was based on the block approach, which is a refinement of spectra-subtraction that accounts for changes on the background signal and for band-bending shifts. By this method, it was possible to robustly show that the formation of Si{sup 1+} is due to oxygen bonding to the upper dimer atoms. Our results contrast with ab initio calculation, which indicates that the most favorable bonding site is the back-bond of the down-dimer.