Three subsystems of the inferior parietal cortex are differently affected in mild cognitive impairment.

PubMed

Liang, Peipeng; Wang, Zhiqun; Yang, Yanhui; Li, Kuncheng

2012-01-01

The Inferior parietal cortex (IPC), including the intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus (SG), plays an important role in episodic memory, and is considered to be one of the specific neuroimaging markers in predicting the conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD). However, it is still unclear whether the connectivity of the IPC is impaired in MCI patients. In the present study, we used resting state fMRI to examine the functional connectivity of the three subdivisions of the IPC in MCI patients after controlling the impact of regional grey matter atrophy. It was found that, using IPS, AG, and SG as seeds of functional connectivity, three canonical functional networks could be correspondingly traced, i.e., executive control network (ECN), default mode network (DMN), and salience network (SN), and the three networks are differently altered in MCI patients. In contrast to the healthy controls, it was found that in MCI patients: 1) AG connectivity was significantly reduced within the DMN; 2) IPS showed decreased connectivity with the right inferior frontal gyrus while showing increased connectivity with the left frontal regions within the ECN; and 3) SG displayed decreased connectivity with a distribution of regions including the frontal and parietal regions, and increased connectivity with some sub-cortical areas within the SN. Moreover, the connectivity within the three networks was correlated with episodic memory and general cognitive impairment in MCI patients. These results extend well beyond the DMN, and further suggest that MCI is associated with alteration of large-scale functional brain networks.

Understanding marijuana's effects on functional connectivity of the default mode network in patients with schizophrenia and co-occurring cannabis use disorder: A pilot investigation.

PubMed

Whitfield-Gabrieli, Susan; Fischer, Adina S; Henricks, Angela M; Khokhar, Jibran Y; Roth, Robert M; Brunette, Mary F; Green, Alan I

2018-04-01

Nearly half of patients with schizophrenia (SCZ) have co-occurring cannabis use disorder (CUD), which has been associated with decreased treatment efficacy, increased risk of psychotic relapse, and poor global functioning. While reports on the effects of cannabis on cognitive performance in patients with SCZ have been mixed, study of brain networks related to executive function may clarify the relationship between cannabis use and cognition in these dual-diagnosis patients. In the present pilot study, patients with SCZ and CUD (n=12) and healthy controls (n=12) completed two functional magnetic resonance imaging (fMRI) resting scans. Prior to the second scan, patients smoked a 3.6% tetrahydrocannabinol (THC) cannabis cigarette or ingested a 15mg delta-9-tetrahydrocannabinol (THC) pill. We used resting-state functional connectivity to examine the default mode network (DMN) during both scans, as connectivity/activity within this network is negatively correlated with connectivity of the network involved in executive control and shows reduced activity during task performance in normal individuals. At baseline, relative to controls, patients exhibited DMN hyperconnectivity that correlated with positive symptom severity, and reduced anticorrelation between the DMN and the executive control network (ECN). Cannabinoid administration reduced DMN hyperconnectivity and increased DMN-ECN anticorrelation. Moreover, the magnitude of anticorrelation in the controls, and in the patients after cannabinoid administration, positively correlated with WM performance. The finding that DMN brain connectivity is plastic may have implications for future pharmacotherapeutic development, as treatment efficacy could be assessed through the ability of therapies to normalize underlying circuit-level dysfunction. Copyright © 2017. Published by Elsevier B.V.

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Altered Functional Connectivity of Insular Subregions in Alzheimer’s Disease

PubMed Central

Liu, Xingyun; Chen, Xiaodan; Zheng, Weimin; Xia, Mingrui; Han, Ying; Song, Haiqing; Li, Kuncheng; He, Yong; Wang, Zhiqun

2018-01-01

Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer’s disease (AD). However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI) data including 32 AD patients and 38 healthy controls (HCs). By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC) and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1) an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN); (2) a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN); (3) a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN). In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN) regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN), suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients. PMID:29695961

Altered Functional Connectivity of Insular Subregions in Alzheimer's Disease.

PubMed

Liu, Xingyun; Chen, Xiaodan; Zheng, Weimin; Xia, Mingrui; Han, Ying; Song, Haiqing; Li, Kuncheng; He, Yong; Wang, Zhiqun

2018-01-01

Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer's disease (AD). However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI) data including 32 AD patients and 38 healthy controls (HCs). By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC) and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1) an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN); (2) a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN); (3) a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN). In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN) regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN), suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

PubMed

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

Changes of intranetwork and internetwork functional connectivity in Alzheimer’s disease and mild cognitive impairment

NASA Astrophysics Data System (ADS)

Zhu, Haoze; Zhou, Peng; Alcauter, Sarael; Chen, Yuanyuan; Cao, Hongbao; Tian, Miao; Ming, Dong; Qi, Hongzhi; Wang, Xuemin; Zhao, Xin; He, Feng; Ni, Hongyan; Gao, Wei

2016-08-01

Objective. Alzheimer’s disease (AD) is a serious neurodegenerative disorder characterized by deficits of working memory, attention, language and many other cognitive functions. Although different stages of the disease are relatively well characterized by clinical criteria, stage-specific pathological changes in the brain remain relatively poorly understood, especially at the level of large-scale functional networks. In this study, we aimed to characterize the potential disruptions of large-scale functional brain networks based on a sample including amnestic mild cognition impairment (aMCI) and AD patients to help delineate the underlying stage-dependent AD pathology. Approach. We sought to identify the neural connectivity mechanisms of aMCI and AD through examination of both intranetwork and internetwork interactions among four of the brain’s key networks, namely dorsal attention network (DAN), default mode network (DMN), executive control network (ECN) and salience network (SAL). We analyzed functional connectivity based on resting-state functional magnetic resonance imaging (rs-fMRI) data from 25 Alzheimer’s disease patients, 20 aMCI patients and 35 elderly normal controls (NC). Main results. Intranetwork functional disruptions within the DAN and ECN were detected in both aMCI and AD patients. Disrupted intranetwork connectivity of DMN and anti-correlation between DAN and DMN were observed in AD patients. Moreover, aMCI-specific alterations in the internetwork functional connectivity of SAL were observed. Significance. Our results confirmed previous findings that AD pathology was related to dysconnectivity both within and between resting-state networks but revealed more spatial details. Moreover, the SAL network, reportedly flexibly coupling either with the DAN or DMN networks during different brain states, demonstrated interesting alterations specifically in the early stage of the disease.

Frame Transmission Efficiency-Based Cross-Layer Congestion Notification Scheme in Wireless Ad Hoc Networks.

PubMed

He, Huaguang; Li, Taoshen; Feng, Luting; Ye, Jin

2017-07-15

Different from the traditional wired network, the fundamental cause of transmission congestion in wireless ad hoc networks is medium contention. How to utilize the congestion state from the MAC (Media Access Control) layer to adjust the transmission rate is core work for transport protocol design. However, recent works have shown that the existing cross-layer congestion detection solutions are too complex to be deployed or not able to characterize the congestion accurately. We first propose a new congestion metric called frame transmission efficiency (i.e., the ratio of successful transmission delay to the frame service delay), which describes the medium contention in a fast and accurate manner. We further present the design and implementation of RECN (ECN and the ratio of successful transmission delay to the frame service delay in the MAC layer, namely, the frame transmission efficiency), a general supporting scheme that adjusts the transport sending rate through a standard ECN (Explicit Congestion Notification) signaling method. Our method can be deployed on commodity switches with small firmware updates, while making no modification on end hosts. We integrate RECN transparently (i.e., without modification) with TCP on NS2 simulation. The experimental results show that RECN remarkably improves network goodput across multiple concurrent TCP flows.

Improving Explicit Congestion Notification with the Mark-Front Strategy

NASA Technical Reports Server (NTRS)

Liu, Chunlei; Jain, Raj

2001-01-01

Delivering congestion signals is essential to the performance of networks. Current TCP/IP networks use packet losses to signal congestion. Packet losses not only reduces TCP performance, but also adds large delay. Explicit Congestion Notification (ECN) delivers a faster indication of congestion and has better performance. However, current ECN implementations mark the packet from the tail of the queue. In this paper, we propose the mark-front strategy to send an even faster congestion signal. We show that mark-front strategy reduces buffer size requirement, improves link efficiency and provides better fairness among users. Simulation results that verify our analysis are also presented.

In Vitro Evaluation of the Impact of the Probiotic E. coli Nissle 1917 on Campylobacter jejuni's Invasion and Intracellular Survival in Human Colonic Cells.

PubMed

Helmy, Yosra A; Kassem, Issmat I; Kumar, Anand; Rajashekara, Gireesh

2017-01-01

Campylobacter jejuni is a leading cause of bacterial food poisoning in humans. Due to the rise in antibiotic-resistant Campylobacter , there exists a need to develop antibiotic-independent interventions to control infections in humans. Here, we evaluated the impact of Escherichia coli Nissle 1917 (EcN), a probiotic strain, on C. jejuni's invasion and intracellular survival in polarized human colonic cells (HT-29). To further understand how EcN mediates its impact, the expression of 84 genes associated with tight junctions and cell adhesion was profiled in HT-29 cells after treatment with EcN and challenge with C. jejuni . The pre-treatment of polarized HT-29 cells with EcN for 4 h showed a significant effect on C. jejuni 's invasion (∼2 log reduction) of the colonic cells. Furthermore, no intracellular C. jejuni were recovered from EcN pre-treated HT-29 cells at 24 h post-infection. Other probiotic strains tested had no significant impact on C. jejuni invasion and intracellular survival. C. jejuni decreased the expression of genes associated with epithelial cells permeability and barrier function in untreated HT-29 cells. However, EcN positively affected the expression of genes that are involved in enhanced intestinal barrier function, decreased cell permeability, and increased tight junction integrity. The results suggest that EcN impedes C. jejuni invasion and subsequent intracellular survival by affecting HT-29 cells barrier function and tight junction integrity. We conclude that EcN might be a viable alternative for controlling C. jejuni infections.

Prophylaxis of acute respiratory infections via improving the immune system in late preterm newborns with E. coli strain Nissle 1917: a controlled pilot trial.

PubMed

Aryayev, Mykola L; Senkivska, Liudmyla I; Bredeleva, Nataliya K; Talashova, Irina V

2018-01-01

Acute respiratory infections (ARIs), caused by the high level of immaturity of the immune system, are a major cause of morbidity in preterm newborns. The probiotic Escherichia coli strain Nissle 1917 (EcN) is well known for its immuno-modulatory properties and may therefore enhance the immune competence. Thus, EcN administration may provide a promising possibility to decrease the risk of ARIs in this vulnerable group of children. However, clinical data supporting or refuting this hypothesis are, to our knowledge, not available. Therefore, the aim of the presented pilot trial was to collect first data on the efficacy and safety of EcN treatment to prevent ARIs in late preterm newborns. Right after birth, 62 late preterm newborns were included into an open-labeled, controlled 4-week trial with two parallel groups and a follow-up phase until the age of 1 year. All children of the treatment group received an EcN suspension orally for 3 weeks, whereas the control group was only observed. Primary efficacy variable was the number of participants with at least one ARI during the first 28 days of life. Secondary efficacy variables were the number of ARIs and the number and duration of hospitalizations caused by ARIs during the first year of life. The number of participants with at least one ARI during the first 28 days of life was significantly lower in the group treated with EcN compared to that in the control group. Although only of exploratory nature, analyses of secondary efficacy variables suggest that EcN treatment may also reduce the average number of ARIs, the average number of hospitalizations caused by ARIs, and the mean duration of such hospitalizations. There is also some evidence that early EcN treatment may have long-term benefits on newborns' health status. The present pilot trial provides first evidence that EcN is able to reduce the incidence of ARIs in the neonatal period of late preterm newborns. Additionally, EcN is characterized by an excellent individual biocompatibility in the absence of adverse drug reactions. Limitations of the current trial are discussed and recommendations for future confirmatory studies are made. ClinicalTrials.gov identifier: NCT01540162; retrospectively registered on 16 February 2012.

Networked Leadership in Educational Collaborative Networks

ERIC Educational Resources Information Center

Díaz-Gibson, Jordi; Zaragoza, Mireia Civís; Daly, Alan J.; Mayayo, Jordi Longás; Romaní, Jordi Riera

2017-01-01

Educational Collaborative Networks (ECNs) aim to achieve educational goals at the community level and base their actions on collaborative partnering between schools and community organizations. These approaches are an emergent and innovative leadership and policy strategy being used increasingly across the globe, given the interconnected and…

Survival of the probiotic Escherichia coli Nissle 1917 (EcN) in the gastrointestinal tract given in combination with oral mesalamine to healthy volunteers.

PubMed

Joeres-Nguyen-Xuan, Thai Hoa; Boehm, Stephan Karl; Joeres, Lars; Schulze, Juergen; Kruis, Wolfgang

2010-02-01

Mesalamine and the probiotic E. coli Nissle 1917 (EcN) are both effective agents for the treatment of ulcerative colitis. A combined therapy may have more than additive efficacy. However, mesalamine may have antimicrobial effects on EcN. In this prospective, randomized, double-blind, placebo-controlled study, 48 healthy volunteers took EcN in a run-in phase for 17 days (5-50 x 10(9) viable bacteria od). If stool samples became positive for EcN, volunteers received combination treatment with EcN plus either mesalamine (1500 mg twice a day) or placebo for 1 week. Fecal samples were further tested for EcN in 2- to 3-day intervals until a maximum of 48 weeks after treatment. Patient diaries, blood, and urine were checked to assess safety, compliance, and tolerance. During run-in, viable EcN were detected in 45 of the 48 volunteers (94%); 2 volunteers were positive before taking EcN. From days 1 to 7 of combination treatment (n = 40), the number of EcN-positive volunteers varied between 70% and 80% in the mesalamine group and between 85% and 95% in the placebo group. Differences between the groups were not significant (normal approximation: day 3, P > 0.15; day 5, P > 0.25; day 7, P > 0.076). At treatment discontinuation, 16 of 20 volunteers in the mesalamine group and 15 of 20 volunteers in the placebo group were EcN positive, whereas this figure dropped continuously up to week 12 after discontinuation (mesalamine, 7 of 20; placebo, 4 of 20). No differences between the groups were seen with regard to tolerance and safety. The combination of EcN and mesalamine has no significant effect on the survival of EcN in healthy volunteers.

Exposure control strategies in the carbonaceous nanomaterial industry.

PubMed

Dahm, Matthew M; Yencken, Marianne S; Schubauer-Berigan, Mary K

2011-06-01

Little is known about exposure control strategies currently being implemented to minimize exposures during the production or use of nanomaterials in the United States. Our goal was to estimate types and quantities of materials used and factors related to workplace exposure reductions among companies manufacturing or using engineered carbonaceous nanomaterials (ECNs). Information was collected through phone surveys on work practices and exposure control strategies from 30 participating producers and users of ECN. The participants were classified into three groups for further examination. We report here the use of exposure control strategies. Observed patterns suggest that large-scale manufacturers report greater use of nanospecific exposure control strategies particularly for respiratory protection. Workplaces producing or using ECN generally report using engineering and administrative controls as well as personal protective equipment to control workplace employee exposure.

Delivering Faster Congestion Feedback with the Mark-Front Strategy

NASA Technical Reports Server (NTRS)

Liu, Chunlei; Jain, Raj

2001-01-01

Computer networks use congestion feedback from the routers and destinations to control the transmission load. Delivering timely congestion feedback is essential to the performance of networks. Reaction to the congestion can be more effective if faster feedback is provided. Current TCP/IP networks use timeout, duplicate Acknowledgement Packets (ACKs) and explicit congestion notification (ECN) to deliver the congestion feedback, each provides a faster feedback than the previous method. In this paper, we propose a markfront strategy that delivers an even faster congestion feedback. With analytical and simulation results, we show that mark-front strategy reduces buffer size requirement, improves link efficiency and provides better fairness among users. Keywords: Explicit Congestion Notification, mark-front, congestion control, buffer size requirement, fairness.

Is Traumatic Brain Injury Associated with Reduced Inter-Hemispheric Functional Connectivity? A Study of Large-Scale Resting State Networks following Traumatic Brain Injury

PubMed Central

Duff, Melissa C.; McAuley, Edward; Kramer, Arthur F.; Voss, Michelle W.

2016-01-01

Abstract Traumatic brain injury (TBI) often has long-term debilitating sequelae in cognitive and behavioral domains. Understanding how TBI impacts functional integrity of brain networks that underlie these domains is key to guiding future approaches to TBI rehabilitation. In the current study, we investigated the differences in inter-hemispheric functional connectivity (FC) of resting state networks (RSNs) between chronic mild-to-severe TBI patients and normal comparisons (NC), focusing on two externally oriented networks (i.e., the fronto-parietal network [FPN] and the executive control network [ECN]), one internally oriented network (i.e., the default mode network [DMN]), and one somato-motor network (SMN). Seed voxel correlation analysis revealed that TBI patients displayed significantly less FC between lateralized seeds and both homologous and non-homologous regions in the opposite hemisphere for externally oriented networks but not for DMN or SMN; conversely, TBI patients showed increased FC within regions of the DMN, especially precuneus and parahippocampal gyrus. Region of interest correlation analyses confirmed the presence of significantly higher inter-hemispheric FC in NC for the FPN (p < 0.01), and ECN (p < 0.05), but not for the DMN (p > 0.05) or SMN (p > 0.05). Further analysis revealed that performance on a neuropsychological test measuring organizational skills and visuo-spatial abilities administered to the TBI group, the Rey-Osterrieth Complex Figure Test, positively correlated with FC between the right FPN and homologous regions. Our findings suggest that distinct RSNs display specific patterns of aberrant FC following TBI; this represents a step forward in the search for biomarkers useful for early diagnosis and treatment of TBI-related cognitive impairment. PMID:25719433

Escherichia coli Nissle 1917 in Ulcerative Colitis Treatment: Systematic Review and Meta-analysis.

PubMed

Losurdo, Giuseppe; Iannone, Andrea; Contaldo, Antonella; Ierardi, Enzo; Di Leo, Alfredo; Principi, Mariabeatrice

2015-12-01

Escherichia coli Nissle 1917 (EcN) has been recommended as a therapeutic tool for ulcerative colitis (UC) treatment. However, to date, no meta-analysis has been performed on this topic. We performed a literature search on PubMed, MEDLINE, Science Direct and EMBASE. We evaluated success rates for induction of remission, relapse rates and side effects, expressed as Intention-To-Treat. Odd ratios (OR), pooled OR and 95% confidence intervals (CI) were calculated, based on the Mantel-Haenszel method. Heterogeneity was assessed by using the χ2 and I2 statistics and, if present, a random-effects model was adopted. We selected six eligible trials, with 719 patients, 390 assigned to the study group and 329 to the control group. EcN induced remission in 61.6% of cases, while in the control group (mesalazine) the remission was achieved in 69.5% of cases, with a mean difference of 7.9%. The pooled OR was 0.92 (95% CI 0.15-9.66, p=0.93). A single study showed a better performance of EcN than the placebo. A relapse of the disease occurred in 36.8% in the EcN group and in 36.1% in the control group (mesalazine), with a mean difference of 0.8%, OR=1.07, with a 95% CI of 0.70-1.64 (p=0.74). Side effects were comparable (OR=1.44, 95% CI 0.80-2.59, p=0.22). EcN is equivalent to mesalazine in preventing disease relapse, thus confirming current guideline recommendations. EcN seems to be as effective as controls in inducing remission and therefore, its use cannot be recommended as in one study the comparison was performed against placebo. Further studies may be helpful for this subject.

Functional Connectivity Substrates for tDCS Response in Minimally Conscious State Patients

PubMed Central

Cavaliere, Carlo; Aiello, Marco; Di Perri, Carol; Amico, Enrico; Martial, Charlotte; Thibaut, Aurore; Laureys, Steven; Soddu, Andrea

2016-01-01

Transcranial direct current stimulation (tDCS) is a non-invasive technique recently employed in disorders of consciousness, and determining a transitory recovery of signs of consciousness in almost half of minimally conscious state (MCS) patients. Although the rising evidences about its possible role in the treatment of many neurological and psychiatric conditions exist, no evidences exist about brain functional connectivity substrates underlying tDCS response. We retrospectively evaluated resting state functional Magnetic Resonance Imaging (fMRI) of 16 sub-acute and chronic MCS patients (6 tDCS responders) who successively received a single left dorsolateral prefrontal cortex (DLPFC) tDCS in a double-blind randomized cross-over trial. A seed-based approach for regions of left extrinsic control network (ECN) and default-mode network (DMN) was performed. tDCS responders showed an increased left intra-network connectivity for regions co-activated with left DLPFC, and significantly with left inferior frontal gyrus. Non-responders (NR) MCS patients showed an increased connectivity between left DLPFC and midline cortical structures, including anterior cingulate cortex and precuneus. Our findings suggest that a prior high connectivity with regions belonging to ECN can facilitate transitory recovery of consciousness in a subgroup of MCS patients that underwent tDCS treatment. Therefore, resting state-fMRI could be very valuable in detecting the neuronal conditions necessary for tDCS to improve behavior in MCS. PMID:27857682

Functional Connectivity Substrates for tDCS Response in Minimally Conscious State Patients.

PubMed

Cavaliere, Carlo; Aiello, Marco; Di Perri, Carol; Amico, Enrico; Martial, Charlotte; Thibaut, Aurore; Laureys, Steven; Soddu, Andrea

2016-01-01

Transcranial direct current stimulation (tDCS) is a non-invasive technique recently employed in disorders of consciousness, and determining a transitory recovery of signs of consciousness in almost half of minimally conscious state (MCS) patients. Although the rising evidences about its possible role in the treatment of many neurological and psychiatric conditions exist, no evidences exist about brain functional connectivity substrates underlying tDCS response. We retrospectively evaluated resting state functional Magnetic Resonance Imaging (fMRI) of 16 sub-acute and chronic MCS patients (6 tDCS responders) who successively received a single left dorsolateral prefrontal cortex (DLPFC) tDCS in a double-blind randomized cross-over trial. A seed-based approach for regions of left extrinsic control network (ECN) and default-mode network (DMN) was performed. tDCS responders showed an increased left intra-network connectivity for regions co-activated with left DLPFC, and significantly with left inferior frontal gyrus. Non-responders (NR) MCS patients showed an increased connectivity between left DLPFC and midline cortical structures, including anterior cingulate cortex and precuneus. Our findings suggest that a prior high connectivity with regions belonging to ECN can facilitate transitory recovery of consciousness in a subgroup of MCS patients that underwent tDCS treatment. Therefore, resting state-fMRI could be very valuable in detecting the neuronal conditions necessary for tDCS to improve behavior in MCS.

75 FR 44830 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-29

...-dealers and aggregators such as electronic communications networks. A member firm is able to select any... (`ATSs') and electronic communications networks (`ECNs') that the Commission has also nurtured and... the following methods: Electronic Comments Use the Commission's Internet comment form ( http://www.sec...

Early Functional Connectome Integrity and 1-Year Recovery in Comatose Survivors of Cardiac Arrest.

PubMed

Sair, Haris I; Hannawi, Yousef; Li, Shanshan; Kornbluth, Joshua; Demertzi, Athena; Di Perri, Carol; Chabanne, Russell; Jean, Betty; Benali, Habib; Perlbarg, Vincent; Pekar, James; Luyt, Charles-Edouard; Galanaud, Damien; Velly, Lionel; Puybasset, Louis; Laureys, Steven; Caffo, Brian; Stevens, Robert D

2018-04-01

Purpose To assess whether early brain functional connectivity is associated with functional recovery 1 year after cardiac arrest (CA). Materials and Methods Enrolled in this prospective multicenter cohort were 46 patients who were comatose after CA. Principal outcome was cerebral performance category at 12 months, with favorable outcome (FO) defined as cerebral performance category 1 or 2. All participants underwent multiparametric structural and functional magnetic resonance (MR) imaging less than 4 weeks after CA. Within- and between-network connectivity was measured in dorsal attention network (DAN), default-mode network (DMN), salience network (SN), and executive control network (ECN) by using seed-based analysis of resting-state functional MR imaging data. Structural changes identified with fluid-attenuated inversion recovery and diffusion-weighted imaging sequences were analyzed by using validated morphologic scales. The association between connectivity measures, structural changes, and the principal outcome was explored with multivariable modeling. Results Patients underwent MR imaging a mean 12.6 days ± 5.6 (standard deviation) after CA. At 12 months, 11 patients had an FO. Patients with FO had higher within-DMN connectivity and greater anticorrelation between SN and DMN and between SN and ECN compared with patients with unfavorable outcome, an effect that was maintained after multivariable adjustment. Anticorrelation of SN-DMN predicted outcomes with higher accuracy than fluid-attenuated inversion recovery or diffusion-weighted imaging scores (area under the receiver operating characteristic curves, respectively, 0.88, 0.74, and 0.71). Conclusion MR imaging-based measures of cerebral functional network connectivity obtained in the acute phase of CA were independently associated with FO at 1 year, warranting validation as early markers of long-term recovery potential in patients with anoxic-ischemic encephalopathy. © RSNA, 2017.

Differential Contribution of Bilateral Supplementary Motor Area to the Effective Connectivity Networks Induced by Task Conditions Using Dynamic Causal Modeling

PubMed Central

Tao, Zhongping; Zhang, Mu

2014-01-01

Abstract Functional imaging studies have indicated hemispheric asymmetry of activation in bilateral supplementary motor area (SMA) during unimanual motor tasks. However, the hemispherically special roles of bilateral SMAs on primary motor cortex (M1) in the effective connectivity networks (ECN) during lateralized tasks remain unclear. Aiming to study the differential contribution of bilateral SMAs during the motor execution and motor imagery tasks, and the hemispherically asymmetric patterns of ECN among regions involved, the present study used dynamic causal modeling to analyze the functional magnetic resonance imaging data of the unimanual motor execution/imagery tasks in 12 right-handed subjects. Our results demonstrated that distributions of network parameters underlying motor execution and motor imagery were significantly different. The variation was mainly induced by task condition modulations of intrinsic coupling. Particularly, regardless of the performing hand, the task input modulations of intrinsic coupling from the contralateral SMA to contralateral M1 were positive during motor execution, while varied to be negative during motor imagery. The results suggested that the inhibitive modulation suppressed the overt movement during motor imagery. In addition, the left SMA also helped accomplishing left hand tasks through task input modulation of left SMA→right SMA connection, implying that hemispheric recruitment occurred when performing nondominant hand tasks. The results specified differential and altered contributions of bilateral SMAs to the ECN during unimanual motor execution and motor imagery, and highlighted the contributions induced by the task input of motor execution/imagery. PMID:24606178

Amelioration of cadmium- and mercury-induced liver and kidney damage in rats by genetically engineered probiotic Escherichia coli Nissle 1917 producing pyrroloquinoline quinone with oral supplementation of citric acid.

PubMed

Raghuvanshi, Ruma; Chaudhari, Archana; Kumar, G Naresh

2016-01-01

Antioxidants, chelating agents, and probiotics are used to manage the toxic effects of cadmium (Cd) and mercury (Hg). The aim of this study was to investigate the combined effects of antioxidants, chelating agents, and probiotics against heavy metal toxicity. Genetically modified probiotic Escherichia coli Nissle 1917 (EcN-20) producing a potent water soluble antioxidant pyrroloquinoline quinone (PQQ) was supplemented with oral citric acid and compared with another genetically modified probiotic EcN-21 producing PQQ and citric acid against oxidative stress induced by Cd and Hg. Rats were independently given 100 ppm Cd and 80 ppm Hg in drinking water for 4 wk. EcN-20 was found to be more effective than EcN-2 (EcN strain with genomic integration of vgb and gfp genes) with orally given PQQ against oxidative stress induced by Cd and Hg. EcN-20 supplemented with oral citric acid was more effective against Cd and Hg toxicity compared with EcN-2+citric acid (oral), EcN-2+PQQ (oral), EcN-2+PQQ (oral)+citric acid (oral), EcN-20, and EcN-21. However, protection shown by EcN-21 was similar to EcN-20. The combination therapy involving probiotic EcN-20 producing PQQ with citric acid given orally was found to be a moderately effective strategy against toxicity induced by Cd and Hg, whereas the protective effect of EcN-21 was the same as EcN-20. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictive functional control for active queue management in congested TCP/IP networks.

PubMed

Bigdeli, N; Haeri, M

2009-01-01

Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

Stereotactic Radiation Therapy can Safely and Durably Control Sites of Extra-Central Nervous System Oligoprogressive Disease in Anaplastic Lymphoma Kinase-Positive Lung Cancer Patients Receiving Crizotinib

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

Gan, Gregory N., E-mail: gregory.gan@ucdenver.edu; Weickhardt, Andrew J.; Scheier, Benjamin

Purpose: To analyze the durability and toxicity of radiotherapeutic local ablative therapy (LAT) applied to extra-central nervous system (eCNS) disease progression in anaplastic lymphoma kinase-positive non-small cell lung cancer (NSCLC) patients. Methods and Materials: Anaplastic lymphoma kinase-positive NSCLC patients receiving crizotinib and manifesting ≤4 discrete sites of eCNS progression were classified as having oligoprogressive disease (OPD). If subsequent progression met OPD criteria, additional courses of LAT were considered. Crizotinib was continued until eCNS progression was beyond OPD criteria or otherwise not suitable for further LAT. Results: Of 38 patients, 33 progressed while taking crizotinib. Of these, 14 had eCNS progressionmore » meeting OPD criteria suitable for radiotherapeutic LAT. Patients with eCNS OPD received 1-3 courses of LAT with radiation therapy. The 6- and 12-month actuarial local lesion control rates with radiation therapy were 100% and 86%, respectively. The 12-month local lesion control rate with single-fraction equivalent dose >25 Gy versus ≤25 Gy was 100% versus 60% (P=.01). No acute or late grade >2 radiation therapy-related toxicities were observed. Median overall time taking crizotinib among those treated with LAT versus those who progressed but were not suitable for LAT was 28 versus 10.1 months, respectively. Patients continuing to take crizotinib for >12 months versus ≤12 months had a 2-year overall survival rate of 72% versus 12%, respectively (P<.0001). Conclusions: Local ablative therapy safely and durably eradicated sites of individual lesion progression in anaplastic lymphoma kinase-positive NSCLC patients receiving crizotinib. A dose–response relationship for local lesion control was observed. The suppression of OPD by LAT in patients taking crizotinib allowed an extended duration of exposure to crizotinib, which was associated with longer overall survival.« less

75 FR 69717 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-15

... new Nasdaq product offerings, pending the resolution to this matter. Thus, offering a Managed Data... trading systems (``ATSs''), including dark pools and electronic communication networks (``ECNs''). Each.... A proliferation of dark pools and other ATSs operate profitably with fragmentary shares of...

76 FR 64409 - Self-Regulatory Organizations; EDGX Exchange, Inc.; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-18

... eliminate the FIX (ECN Translator) \\4\\ logical port fee effective as of October 1, 2011, as the ECN Translator is no longer being used by its Members and non-members.\\5\\ \\4\\ The ECN Translator allows a Member... the ECN Translator ports would no longer be available as of August 1, 2011. The Exchange proposes to...

Catechol-O-methyltransferase (COMT) influences the connectivity of the prefrontal cortex at rest

PubMed Central

Tunbridge, Elizabeth M.; Farrell, Sarah M.; Harrison, Paul J.; Mackay, Clare E.

2013-01-01

Catechol-O-methyltransferase (COMT) modulates dopamine in the prefrontal cortex (PFC) and influences PFC dopamine-dependent cognitive task performance. A human COMT polymorphism (Val158Met) alters enzyme activity and is associated with both the activation and functional connectivity of the PFC during task performance, particularly working memory. Here, we used functional magnetic resonance imaging and a data-driven, independent components analysis (ICA) approach to compare resting state functional connectivity within the executive control network (ECN) between young, male COMT Val158 (n = 27) and Met158 (n = 28) homozygotes. COMT genotype effects on grey matter were assessed using voxel-based morphometry. COMT genotype significantly modulated functional connectivity within the ECN, which included the head of the caudate, and anterior cingulate and frontal cortical regions. Val158 homozygotes showed greater functional connectivity between a cluster within the left ventrolateral PFC and the rest of the ECN (using a threshold of Z > 2.3 and a family-wise error cluster significance level of p < 0.05). This difference occurred in the absence of any alterations in grey matter. Our data show that COMT Val158Met affects the functional connectivity of the PFC at rest, complementing its prominent role in the activation and functional connectivity of this region during cognitive task performance. The results suggest that genotype-related differences in prefrontal dopaminergic tone result in neuroadaptive changes in basal functional connectivity, potentially including subtle COMT genotype-dependent differences in the relative coupling of task-positive and task-negative regions, which could in turn contribute to its effects on brain activation, connectivity, and behaviour. PMID:23228511

Genetically Engineered Escherichia coli Nissle 1917 Synbiotics Reduce Metabolic Effects Induced by Chronic Consumption of Dietary Fructose

PubMed Central

Somabhai, Chaudhari Archana; Raghuvanshi, Ruma; Nareshkumar, G.

2016-01-01

Aims To assess protective efficacy of genetically modified Escherichia coli Nissle 1917 (EcN) on metabolic effects induced by chronic consumption of dietary fructose. Materials and Methods EcN was genetically modified with fructose dehydrogenase (fdh) gene for conversion of fructose to 5-keto-D-fructose and mannitol-2-dehydrogenase (mtlK) gene for conversion to mannitol, a prebiotic. Charles foster rats weighing 150–200 g were fed with 20% fructose in drinking water for two months. Probiotic treatment of EcN (pqq), EcN (pqq-glf-mtlK), EcN (pqq-fdh) was given once per week 109 cells for two months. Furthermore, blood and liver parameters for oxidative stress, dyslipidemia and hyperglycemia were estimated. Fecal samples were collected to determine the production of short chain fatty acids and pyrroloquinoline quinone (PQQ) production. Results EcN (pqq-glf-mtlK), EcN (pqq-fdh) transformants were confirmed by restriction digestion and functionality was checked by PQQ estimation and HPLC analysis. There was significant increase in body weight, serum glucose, liver injury markers, lipid profile in serum and liver, and decrease in antioxidant enzyme activity in high-fructose-fed rats. However the rats treated with EcN (pqq-glf-mtlK) and EcN (pqq-fdh) showed significant reduction in lipid peroxidation along with increase in serum and hepatic antioxidant enzyme activities. Restoration of liver injury marker enzymes was also seen. Increase in short chain fatty acids (SCFA) demonstrated the prebiotic effects of mannitol and gluconic acid. Conclusions Our study demonstrated the effectiveness of probiotic EcN producing PQQ and fructose metabolizing enzymes against the fructose induced hepatic steatosis suggesting that its potential for use in treating fructose induced metabolic syndrome. PMID:27760187

Role of F1C fimbriae, flagella, and secreted bacterial components in the inhibitory effect of probiotic Escherichia coli Nissle 1917 on atypical enteropathogenic E. coli infection.

PubMed

Kleta, Sylvia; Nordhoff, Marcel; Tedin, Karsten; Wieler, Lothar H; Kolenda, Rafal; Oswald, Sibylle; Oelschlaeger, Tobias A; Bleiss, Wilfried; Schierack, Peter

2014-05-01

Enteropathogenic Escherichia coli (EPEC) is recognized as an important intestinal pathogen that frequently causes acute and persistent diarrhea in humans and animals. The use of probiotic bacteria to prevent diarrhea is gaining increasing interest. The probiotic E. coli strain Nissle 1917 (EcN) is known to be effective in the treatment of several gastrointestinal disorders. While both in vitro and in vivo studies have described strong inhibitory effects of EcN on enteropathogenic bacteria, including pathogenic E. coli, the underlying molecular mechanisms remain largely unknown. In this study, we examined the inhibitory effect of EcN on infections of porcine intestinal epithelial cells with atypical enteropathogenic E. coli (aEPEC) with respect to single infection steps, including adhesion, microcolony formation, and the attaching and effacing phenotype. We show that EcN drastically reduced the infection efficiencies of aEPEC by inhibiting bacterial adhesion and growth of microcolonies, but not the attaching and effacing of adherent bacteria. The inhibitory effect correlated with EcN adhesion capacities and was predominantly mediated by F1C fimbriae, but also by H1 flagella, which served as bridges between EcN cells. Furthermore, EcN seemed to interfere with the initial adhesion of aEPEC to host cells by secretion of inhibitory components. These components do not appear to be specific to EcN, but we propose that the strong adhesion capacities enable EcN to secrete sufficient local concentrations of the inhibitory factors. The results of this study are consistent with a mode of action whereby EcN inhibits secretion of virulence-associated proteins of EPEC, but not their expression.

77 FR 2331 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing and Immediate Effectiveness of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-17

... trading systems (``ATSs''), including dark pools and electronic communication networks (``ECNs''). Each... data at no charge on its Web site in order to attract more order flow, and it uses market data revenue... users.\\19\\ A proliferation of dark pools and other [[Page 2335

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2013-01-17

... Report regarding a Nasdaq security through the NasdaqTrader.com Web site shall be determined in... improvement of web functionality and the inclusion of supplementary equity information, but has not increased... dark pools and electronic communication networks (``ECNs''). Each SRO market competes to produce...

Genetically engineered Escherichia coli Nissle 1917 synbiotic counters fructose-induced metabolic syndrome and iron deficiency.

PubMed

Chaudhari, Archana Somabhai; Raghuvanshi, Ruma; Kumar, G Naresh

2017-06-01

Consumption of fructose leads to metabolic syndrome, but it is also known to increase iron absorption. Present study investigates the effect of genetically modified Escherichia coli Nissle 1917 (EcN) synbiotic along with fructose on non-heme iron absorption. Charles foster rats weighing 150-200 g were fed with iron-deficient diet for 2 months. Probiotic treatment of EcN (pqq) and EcN (pqq-glf-mtlK) was given once per week, 10 9  cells after 2 months with fructose in drinking water. Iron levels, blood, and liver parameters for oxidative stress, hyperglycemia, and dyslipidemia were estimated. Transferrin-bound iron levels in the blood decreased significantly after 10 weeks of giving iron-deficient diet. Probiotic treatment of EcN (pqq-glf-mtlK) and fructose together led to the restoration of normal transferrin-bound iron levels and blood and hepatic antioxidant levels as compared to iron-deficient control group. The probiotic also led to the restoration of body weight along with levels of serum and hepatic lipid, blood glucose, and antioxidant in the blood and liver as compared to iron-deficient control group. Restoration of liver injury marker enzymes was also seen. Administration of EcN-producing PQQ and mannitol dehydrogenase enzyme together with fructose led to increase in the transferrin-bound iron levels in the blood and amelioration of consequences of metabolic syndrome caused due to fructose consumption.

78 FR 51775 - Self-Regulatory Organizations; NYSE MKT LLC; Notice of Filing and Immediate Effectiveness of...

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2013-08-21

... change is available on the Exchange's Web site at www.nyse.com , at the principal office of the Exchange... (``ATSs''), including dark pools and electronic communication networks (``ECNs''). Competition among... at no charge on their Web sites in order to attract more order flow, and use revenue rebates from...

Quantification of biogenic volatile organic compounds with a flame ionization detector using the effective carbon number concept

DOE PAGES

Faiola, C. L.; Erickson, M. H.; Fricaud, V. L.; ...

2012-08-10

Biogenic volatile organic compounds (BVOCs) are emitted into the atmosphere by plants and include isoprene, monoterpenes, sesquiterpenes, and their oxygenated derivatives. These BVOCs are among the principal factors influencing the oxidative capacity of the atmosphere in forested regions. BVOC emission rates are often measured by collecting samples onto adsorptive cartridges in the field and then transporting these samples to the laboratory for chromatographic analysis. One of the most commonly used detectors in chromatographic analysis is the flame ionization detector (FID). For quantitative analysis with an FID, relative response factors may be estimated using the effective carbon number (ECN) concept. Themore » purpose of this study was to determine the ECN for a variety of terpenoid compounds to enable improved quantification of BVOC measurements. A dynamic dilution system was developed to make quantitative gas standards of VOCs with mixing ratios from 20–55 ppb. For each experiment using this system, one terpene standard was co-injected with an internal reference, n-octane, and analyzed via an automated cryofocusing system interfaced to a gas chromatograph flame ionization detector and mass spectrometer (GC/MS/FID). The ECNs of 16 compounds (14 BVOCs) were evaluated with this approach, with each test compound analyzed at least three times. The difference between the actual carbon number and measured ECN ranged from -24% to -2%. Furthermore, the difference between theoretical ECN and measured ECN ranged from -22% to 9%. Measured ECN values were within 10% of theoretical ECN values for most terpenoid compounds.« less

78 FR 51781 - Self-Regulatory Organizations; New York Stock Exchange LLC; Notice of Filing and Immediate...

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2013-08-21

... proposed rule change is available on the Exchange's Web site at www.nyse.com , at the principal office of... dark pools and electronic communication networks (``ECNs''). Competition among trading platforms can be... provide certain market data at no charge on their Web sites in order to attract more order flow, and use...

The Probiotic Escherichia coli Strain Nissle 1917 Combats Lambdoid Bacteriophages stx and λ.

PubMed

Bury, Susanne; Soundararajan, Manonmani; Bharti, Richa; von Bünau, Rudolf; Förstner, Konrad U; Oelschlaeger, Tobias A

2018-01-01

Shiga toxin (Stx) producing E. coli (STEC) such as Enterohemorrhagic E. coli (EHEC) are the major cause of foodborne illness in humans. In vitro studies showed the probiotic Escherichia coli strain Nissle 1917 (EcN) to efficiently inhibit the production of Stx. Life threatening EHEC strains as for example the serotype O104:H4, responsible for the great outbreak in 2011 in Germany, evolutionary developed from certain E. coli strains which got infected by stx2 -encoding lambdoid phages turning the E. coli into lysogenic and subsequently Stx producing strains. Since antibiotics induce stx genes and Stx production, EHEC infected persons are not recommended to be treated with antibiotics. Therefore, EcN might be an alternative medication. However, because even commensal E. coli strains might be converted into Stx-producers after becoming host to a stx encoding prophage, we tested EcN for stx -phage genome integration. Our experiments revealed the resistance of EcN toward not only stx -phages but also against lambda-phages. This resistance was not based on the lack of or by mutated phage receptors. Rather it involved the expression of a phage repressor ( pr ) gene of a defective prophage in EcN which was able to partially protect E. coli K-12 strain MG1655 against stx and lambda phage infection. Furthermore, we observed EcN to inactivate phages and thereby to protect E. coli K-12 strains against infection by stx - as well as lambda-phages. Inactivation of lambda-phages was due to binding of lambda-phages to LamB of EcN whereas inactivation of stx -phages was caused by a thermostable protein of EcN. These properties together with its ability to inhibit Stx production make EcN a good candidate for the prevention of illness caused by EHEC and probably for the treatment of already infected people.

Neuroprotection against 6-OHDA toxicity in PC12 cells and mice through the Nrf2 pathway by a sesquiterpenoid from Tussilago farfara.

PubMed

Lee, Joohee; Song, Kwangho; Huh, Eugene; Oh, Myung Sook; Kim, Yeong Shik

2018-06-01

Oxidative stress plays a key role in neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Therefore, the nuclear factor-E2-related factor 2 (Nrf2), a key regulator of the antioxidative response, is considered to be important as a therapeutic target for neurodegenerative diseases. We investigated the underlying mechanism of Nrf2-mediated neuroprotective effects against oxidative stress in the PC12 cell line by 7β-(3-ethyl-cis-crotonoyloxy)-1α-(2-methylbutyryloxy)-3,14-dehydro-Z-notonipetranone (ECN), one of the sesquiterpenoids in Farfarae Flos. Pretreatment of PC12 cells with ECN had a protective effect against hydrogen peroxide (H 2 O 2 )- or 6-hydroxydopamine (6-OHDA)-induced cytotoxicity. ECN upregulated the ARE-luciferase activity and induced the mRNA expression of Nrf2 and antioxidant enzyme heme oxygenase-1 (HO-1). Knockdown of Nrf2 by small, interfering RNA (siRNA) abrogated the upregulation of HO-1, indicating that ECN had induced HO-1 via the Nrf2 pathway. Pretreatment with the thiol reducing agents, N-acetylcysteine (NAC) or dithiothreitol (DTT), attenuated Nrf2 activation and HO-1 expression. However, the non-thiol reducing antioxidant, Trolox, failed to inhibit HO-1 induction by ECN. These results suggest that ECN may directly interact with Kelch-like ECH-associated protein 1 (Keap1) and modify critical cysteine thiols present in the proteins responsible for Nrf2-mediated upregulation of HO-1. In a 6-OHDA-induced mouse model of PD, administration of ECN ameliorated motor impairments and dopaminergic neuronal damage. Taken together, ECN exerts neuroprotective effects by activating the Nrf2/HO-1 signaling pathway in both PC12 cells and mice. Thus, ECN, as an Nrf2 activator, could be an attractive therapeutic candidate for the neuroprotection or treatment of neurodegenerative diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Econazole imprinted textiles with antifungal activity.

PubMed

Hossain, Mirza Akram; Lalloz, Augustine; Benhaddou, Aicha; Pagniez, Fabrice; Raymond, Martine; Le Pape, Patrice; Simard, Pierre; Théberge, Karine; Leblond, Jeanne

2016-04-01

In this work, we propose pharmaceutical textiles imprinted with lipid microparticles of Econazole nitrate (ECN) as a mean to improve patient compliance while maintaining drug activity. Lipid microparticles were prepared and characterized by laser diffraction (3.5±0.1 μm). Using an optimized screen-printing method, microparticles were deposited on textiles, as observed by scanning electron microscopy. The drug content of textiles (97±3 μg/cm(2)) was reproducible and stable up to 4 months storage at 25 °C/65% Relative Humidity. Imprinted textiles exhibited a thermosensitive behavior, as witnessed by a fusion temperature of 34.8 °C, which enabled a larger drug release at 32 °C (temperature of the skin) than at room temperature. In vitro antifungal activity of ECN textiles was compared to commercial 1% (wt/wt) ECN cream Pevaryl®. ECN textiles maintained their antifungal activity against a broad range of Candida species as well as major dermatophyte species. In vivo, ECN textiles also preserved the antifungal efficacy of ECN on cutaneous candidiasis infection in mice. Ex vivo percutaneous absorption studies demonstrated that ECN released from pharmaceutical textiles concentrated more in the upper skin layers, where the fungal infections develop, as compared to dermal absorption of Pevaryl®. Overall, these results showed that this technology is promising to develop pharmaceutical garments textiles for the treatment of superficial fungal infections. Copyright © 2016 Elsevier B.V. All rights reserved.

75 FR 1678 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-12

... Accelerated Approval to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity... Substance of the Proposed Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN... immediate effectiveness a proposed rule change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE...

75 FR 19451 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-14

... Rule Change Relating To Amending the Direct Edge ECN Fee Schedule April 7, 2010. Pursuant to Section 19... of the Proposed Rule Change The Exchange proposes to amend Direct Edge ECN's (``DECN'') fee schedule... EDGA Exchange, Inc. and EDGX Exchange, Inc. Direct Edge ECN LLC (EDGA and EDGX) will cease to operate...

75 FR 32528 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

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2010-06-08

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... immediate effectiveness a proposed rule change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE...

75 FR 6782 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

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2010-02-10

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... effectiveness a proposed rule change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE Members \\3\\ to...

75 FR 27034 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-13

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE Members \\4\\ to: (i) Change the rates...

75 FR 6743 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

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2010-02-10

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... effectiveness a proposed rule change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE Members \\3\\ to...

75 FR 19437 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-14

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... rule change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE Members \\4\\ to: (i) Eliminate a...

75 FR 39311 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... Exchange, Inc. (``EDGA and EDGX Exchanges'') [sic] Direct Edge ECN will cease to operate in its capacity as...

75 FR 17983 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and Order...

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2010-04-08

... to a Proposed Rule Change Relating to the Amounts That Direct Edge ECN, in Its Capacity as an... Rule Change The Exchange proposes to modify the amounts that Direct Edge ECN (``DECN''), in its... effectiveness a proposed rule change to amend Direct Edge ECN's (``DECN'') fee schedule for ISE Members \\4\\ to...

75 FR 78794 - Self-Regulatory Organizations; EDGX Exchange, Inc.; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-16

... (Direct) \\4\\ or through the ECN Translator.\\5\\ Members and non-members will receive the first ten (10... sessions will not apply to ECN Translator sessions to incent members and non-members to use Direct Sessions... the Exchange's secondary data center. \\5\\ The ECN translator allows a Member or non-member who...

75 FR 78791 - Self-Regulatory Organizations; EDGA Exchange, Inc.; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-16

... (Direct) \\4\\ or through the ECN Translator.\\5\\ Members and non-members will receive the first ten (10... sessions will not apply to ECN Translator sessions to incent members and non-members to use Direct Sessions... the Exchange's secondary data center. \\5\\ The ECN translator allows a Member or non-member who...

Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries

NASA Astrophysics Data System (ADS)

Propp, Karsten; Marinescu, Monica; Auger, Daniel J.; O'Neill, Laura; Fotouhi, Abbas; Somasundaram, Karthik; Offer, Gregory J.; Minton, Geraint; Longo, Stefano; Wild, Mark; Knap, Vaclav

2016-10-01

Lithium-sulfur (Li-S) batteries are described extensively in the literature, but existing computational models aimed at scientific understanding are too complex for use in applications such as battery management. Computationally simple models are vital for exploitation. This paper proposes a non-linear state-of-charge dependent Li-S equivalent circuit network (ECN) model for a Li-S cell under discharge. Li-S batteries are fundamentally different to Li-ion batteries, and require chemistry-specific models. A new Li-S model is obtained using a 'behavioural' interpretation of the ECN model; as Li-S exhibits a 'steep' open-circuit voltage (OCV) profile at high states-of-charge, identification methods are designed to take into account OCV changes during current pulses. The prediction-error minimization technique is used. The model is parameterized from laboratory experiments using a mixed-size current pulse profile at four temperatures from 10 °C to 50 °C, giving linearized ECN parameters for a range of states-of-charge, currents and temperatures. These are used to create a nonlinear polynomial-based battery model suitable for use in a battery management system. When the model is used to predict the behaviour of a validation data set representing an automotive NEDC driving cycle, the terminal voltage predictions are judged accurate with a root mean square error of 32 mV.

75 FR 32526 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

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2010-06-08

... Rule Change Relating to Amending the Direct Edge ECN Fee Schedule June 2, 2010. Pursuant to Section 19... Direct Edge ECN's (``DECN'') fee schedule for ISE Members \\3\\ to pass through rebates/fees from other... by ISE and not EDGA Exchange, Inc. and EDGX Exchange, Inc. Direct Edge ECN LLC (EDGA and EDGX) will...

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2011-10-18

... (ECN Translator) \\4\\ logical port fee effective as of October 1, 2011, as the ECN Translator is no longer being used by its Members and non-members.\\5\\ \\4\\ The ECN Translator allows a Member or non-member... Translator ports would no longer be available as of August 1, 2011. The Exchange also proposes to make...

78 FR 1901 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-09

... Direct Edge ECN LLC (``DE ECN''), DE ECN is no longer a facility of the Exchange, and ISE (including its...-reference number in paragraph (a), as well as to add non-substantive words to correct the sentence structure..., competition, and capital formation. See 15 U.S.C. 78c(f). At any time within 60 days of the filing of the...

Synchrony between sensory and cognitive networks is associated with subclinical variation in autistic traits

PubMed Central

Young, Jacob S.; Smith, David V.; Coutlee, Christopher G.; Huettel, Scott A.

2015-01-01

Individuals with autistic spectrum disorders exhibit distinct personality traits linked to attentional, social, and affective functions, and those traits are expressed with varying levels of severity in the neurotypical and subclinical population. Variation in autistic traits has been linked to reduced functional and structural connectivity (i.e., underconnectivity, or reduced synchrony) with neural networks modulated by attentional, social, and affective functions. Yet, it remains unclear whether reduced synchrony between these neural networks contributes to autistic traits. To investigate this issue, we used functional magnetic resonance imaging to record brain activation while neurotypical participants who varied in their subclinical scores on the Autism-Spectrum Quotient (AQ) viewed alternating blocks of social and nonsocial stimuli (i.e., images of faces and of landscape scenes). We used independent component analysis (ICA) combined with a spatiotemporal regression to quantify synchrony between neural networks. Our results indicated that decreased synchrony between the executive control network (ECN) and a face-scene network (FSN) predicted higher scores on the AQ. This relationship was not explained by individual differences in head motion, preferences for faces, or personality variables related to social cognition. Our findings build on clinical reports by demonstrating that reduced synchrony between distinct neural networks contributes to a range of subclinical autistic traits. PMID:25852527

Entericidin Is Required for a Probiotic Treatment (Enterobacter sp. Strain C6-6) To Protect Trout from Cold-Water Disease Challenge

PubMed Central

Schubiger, Carla B.; Orfe, Lisa H.; Sudheesh, Ponnerassery S.; Cain, Kenneth D.; Shah, Devendra H.

2014-01-01

Flavobacterium psychrophilum causes bacterial cold-water disease in multiple fish species, including salmonids. An autochthonous Enterobacter strain (C6-6) inhibits the in vitro growth of F. psychrophilum, and when ingested as a putative probiotic, it provides protection against injection challenge with F. psychrophilum in rainbow trout. In this study, low-molecular-mass (≤3 kDa) fractions from both Enterobacter C6-6 and Escherichia coli K-12 culture supernatants inhibited the growth of F. psychrophilum. The ≤3-kDa fraction from Enterobacter C6-6 was analyzed by SDS-PAGE, and subsequent tandem mass spectroscopy identified EcnB, which is a small membrane lipoprotein that is a putative pore-forming toxin. Agar plate diffusion assays demonstrated that ecnAB knockout strains of both Enterobacter C6-6 and E. coli K-12 no longer inhibited F. psychrophilum (P < 0.001), while ecnAB-complemented knockout strains recovered the inhibitory phenotype (P < 0.001). In fish experiments, the engineered strains (C6-6 ΔecnAB and C6-6 ΔecnAB) and the wild-type strain (C6-6) were added to the fish diet every day for 38 days. On day 11, the fish were challenged by injection with a virulent strain of F. psychrophilum (CSF 259-93). Fish that were fed C6-6 had significantly longer survival than fish fed the ecnAB knockout strain (P < 0.0001), while fish fed the complemented knockout strain recovered the probiotic phenotype (P = 0.61). This entericidin is responsible for the probiotic activity of Enterobacter C6-6, and it may present new opportunities for therapeutic and prophylactic treatments against similarly susceptible pathogens. PMID:25381243

Non-toxic engineered carbon nanodiamond concentrations induce oxidative/nitrosative stress, imbalance of energy metabolism, and mitochondrial dysfunction in microglial and alveolar basal epithelial cells.

PubMed

Fresta, Claudia G; Chakraborty, Aishik; Wijesinghe, Manjula B; Amorini, Angela M; Lazzarino, Giacomo; Lazzarino, Giuseppe; Tavazzi, Barbara; Lunte, Susan M; Caraci, Filippo; Dhar, Prajnaparamita; Caruso, Giuseppe

2018-02-14

Engineered nanoparticles are finding a wide spectrum of biomedical applications, including drug delivery and capacity to trigger cytotoxic phenomena, potentially useful against tumor cells. The full understanding of their biosafety and interactions with cell processes is mandatory. Using microglial (BV-2) and alveolar basal epithelial (A549) cells, in this study we determined the effects of engineered carbon nanodiamonds (ECNs) on cell viability, nitric oxide (NO) and reactive oxygen species (ROS) production, as well as on energy metabolism. Particularly, we initially measured decrease in cell viability as a function of increasing ECNs doses, finding similar cytotoxic ECN effects in the two cell lines. Subsequently, using apparently non-cytotoxic ECN concentrations (2 µg/mL causing decrease in cell number < 5%) we determined NO and ROS production, and measured the concentrations of compounds related to energy metabolism, mitochondrial functions, oxido-reductive reactions, and antioxidant defences. We found that in both cell lines non-cytotoxic ECN concentrations increased NO and ROS production with sustained oxidative/nitrosative stress, and caused energy metabolism imbalance (decrease in high energy phosphates and nicotinic coenzymes) and mitochondrial malfunctioning (decrease in ATP/ADP ratio).These results underline the importance to deeply investigate the molecular and biochemical changes occurring upon the interaction of ECNs (and nanoparticles in general) with living cells, even at apparently non-toxic concentration. Since the use of ECNs in biomedical field is attracting increasing attention the complete evaluation of their biosafety, toxicity and/or possible side effects both in vitro and in vivo is mandatory before these highly promising tools might find the correct application.

Escherichia coli Nissle 1917 enhances bioavailability of serotonin in gut tissues through modulation of synthesis and clearance

PubMed Central

Nzakizwanayo, Jonathan; Dedi, Cinzia; Standen, Guy; Macfarlane, Wendy M.; Patel, Bhavik A.; Jones, Brian V.

2015-01-01

Accumulating evidence shows indigenous gut microbes can interact with the human host through modulation of serotonin (5-HT) signaling. Here we investigate the impact of the probiotic Escherichia coli Nissle 1917 (EcN) on 5-HT signalling in gut tissues. Ex-vivo mouse ileal tissue sections were treated with either EcN or the human gut commensal MG1655, and effects on levels of 5-HT, precursors, and metabolites, were evaluated using amperometry and high performance liquid chromatography with electrochemical detection (HPLC-EC). Exposure of tissue to EcN cells, but not MG1655 cells, was found to increase levels of extra-cellular 5-HT. These effects were not observed when tissues were treated with cell-free supernatant from bacterial cultures. In contrast, when supernatant recovered from untreated ileal tissue was pre-incubated with EcN, the derivative cell-free supernatant was able to elevate 5-HT overflow when used to treat fresh ileal tissue. Measurement of 5-HT precursors and metabolites indicated EcN also increases intracellular 5-HTP and reduces 5-HIAA. The former pointed to modulation of tryptophan hydroxylase-1 to enhance 5-HT synthesis, while the latter indicates an impact on clearance into enterocytes through SERT. Taken together, these findings show EcN is able to enhance 5-HT bioavailability in ileal tissues through interaction with compounds secreted from host tissues. PMID:26616662

Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

Chen, Jingyuan E.; Chang, Catie; Greicius, Michael D.; Glover, Gary H.

2015-01-01

Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses. PMID:25662866

Regular cannabis and alcohol use is associated with resting-state time course power spectra in incarcerated adolescents.

PubMed

Thijssen, Sandra; Rashid, Barnaly; Gopal, Shruti; Nyalakanti, Prashanth; Calhoun, Vince D; Kiehl, Kent A

2017-09-01

Cannabis and alcohol are believed to have widespread effects on the brain. Although adolescents are at increased risk for substance use, the adolescent brain may also be particularly vulnerable to the effects of drug exposure due to its rapid maturation. Here, we examined the association between cannabis and alcohol use duration and resting-state functional connectivity in a large sample of male juvenile delinquents. The present sample was drawn from the Southwest Advanced Neuroimaging Cohort, Youth sample, and from a youth detention facility in Wisconsin. All participants were scanned at the maximum-security facilities using The Mind Research Network's 1.5T Avanto SQ Mobile MRI scanner. Information on cannabis and alcohol regular use duration was collected using self-report. Resting-state networks were computed using group independent component analysis in 201 participants. Associations with cannabis and alcohol use were assessed using Mancova analyses controlling for age, IQ, smoking and psychopathy scores in the complete case sample of 180 male juvenile delinquents. No associations between alcohol or cannabis use and network spatial maps were found. Longer cannabis use was associated with decreased low frequency power of the default mode network, the executive control networks (ECNs), and several sensory networks, and with decreased functional network connectivity. Duration of alcohol use was associated with decreased low frequency power of the right frontoparietal network, salience network, dorsal attention network, and several sensory networks. Our findings suggest that adolescent cannabis and alcohol use are associated with widespread differences in resting-state time course power spectra, which may persist even after abstinence. Copyright © 2017 Elsevier B.V. All rights reserved.

Numerical Simulations of Evaporating Sprays in High Pressure and Temperature Operating Conditions (Engine Combustion Network [ECN])

DTIC Science & Technology

2014-05-01

temperature effect in nonreacting and reacting diesel sprays using a novel injector , and imaging diagnostics for liquid phase penetration, light-off...ambient conditions. A single hole, modern common rail injector with an injector diameter of 90 µ (Bosch CRIN 2.4) is used at typical diesel injection... diesel engine operating conditions. The objective of this report is to demonstrate the modeling capability of a recently adopted 3D-Computational Fluid

Entericidin is required for a probiotic treatment (Enterobacter sp. strain C6-6) to protect trout from cold-water disease challenge.

PubMed

Schubiger, Carla B; Orfe, Lisa H; Sudheesh, Ponnerassery S; Cain, Kenneth D; Shah, Devendra H; Call, Douglas R

2015-01-01

Flavobacterium psychrophilum causes bacterial cold-water disease in multiple fish species, including salmonids. An autochthonous Enterobacter strain (C6-6) inhibits the in vitro growth of F. psychrophilum, and when ingested as a putative probiotic, it provides protection against injection challenge with F. psychrophilum in rainbow trout. In this study, low-molecular-mass (≤3 kDa) fractions from both Enterobacter C6-6 and Escherichia coli K-12 culture supernatants inhibited the growth of F. psychrophilum. The ≤3-kDa fraction from Enterobacter C6-6 was analyzed by SDS-PAGE, and subsequent tandem mass spectroscopy identified EcnB, which is a small membrane lipoprotein that is a putative pore-forming toxin. Agar plate diffusion assays demonstrated that ecnAB knockout strains of both Enterobacter C6-6 and E. coli K-12 no longer inhibited F. psychrophilum (P < 0.001), while ecnAB-complemented knockout strains recovered the inhibitory phenotype (P < 0.001). In fish experiments, the engineered strains (C6-6 ΔecnAB and C6-6 ΔecnAB) and the wild-type strain (C6-6) were added to the fish diet every day for 38 days. On day 11, the fish were challenged by injection with a virulent strain of F. psychrophilum (CSF 259-93). Fish that were fed C6-6 had significantly longer survival than fish fed the ecnAB knockout strain (P < 0.0001), while fish fed the complemented knockout strain recovered the probiotic phenotype (P = 0.61). This entericidin is responsible for the probiotic activity of Enterobacter C6-6, and it may present new opportunities for therapeutic and prophylactic treatments against similarly susceptible pathogens. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Excited State Properties of 3'-Hydroxyechinenone in Solvents and in the Orange Carotenoid Protein from Synechocystis sp. PCC 6803

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

Niedzwiedzki, Dariusz M.; Liu, Haijun; Blankenship, Robert E.

The orange carotenoid protein (OCP) is a 35 kDa water-soluble protein involved in a photoprotective mechanism of the photosynthetic apparatus of cyanobacteria. The OCP contains a single molecule of the carotenoid 3'-hydroxyechinenone (3'-hECN). We have performed transient absorption studies at 77 K in the visible and near-infrared spectral ranges on 3'-hECN in solvent glass and in both inactive (orange) and active (red) forms of OCP. In the OCP the cryogenic temperature prohibited the protein from spontaneous conversion between activity stages and allowed us to study well-defined spectral forms of the protein. The studies show that each form of the OCPmore » consists of two protein subpopulations having different photophysical properties of the bound 3'-hECN. At 77 K the inactive OCP reveals two lifetimes of the first excited state of 3'-hECN of 5.2 and 11 ps while in the active form of OCP these are 3.2 and 7.1 ps. We have also determined the energy of the first excited singlet state of 3'-hECN in long-lived subpopulations of both OCP forms at 77 K. This is 13,750 cm –1 in the inactive OCP and 12,300 cm -1 in the active OCP. Shortening of the lifetime and decrease of the energy of the first excited singlet state of 3'-hECN confirm the lengthening of the effective conjugation of the carotenoid upon the inactive-to-active conversion of OCP.« less

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Resting-state functional connectivity of neurotransmitter producing sites in female patients with borderline personality disorder.

PubMed

Wagner, Gerd; Krause-Utz, Annegret; de la Cruz, Feliberto; Schumann, Andy; Schmahl, Christian; Bär, Karl-Jürgen

2018-04-20

Impulsive behavior, difficulties in controlling anger and suicidal behavior are typical patterns of affective/behavioral dysregulation in patients with borderline personality disorder (BPD). Previous functional MRI studies in the resting state condition demonstrated altered functional connectivity (FC) between the anterior cingulate cortex (ACC) and the frontoparietal executive control network (ECN), which was significantly associated with impulsivity in BPD. Impulsivity is often defined as a function of inhibitory control, strongly relying on the proper functioning of the fronto-cingulo-striatal network. Noradrenergic, dopaminergic and serotonergic neurotransmitter systems are assumed to be involved in different forms of impulsive behavior and inhibitory control. In our previous study, we investigated the FC of the main monoamine-producing nuclei within the midbrain and brainstem, which were functionally integrated in specific resting-state networks. In the present study we investigated the resting-state FC of midbrain/brainstem nuclei in 33 unmedicated female patients with BPD and 33 matched healthy controls. We further related altered functional connectivity of these nuclei to the patient's degree of impulsivity. The main finding was that BPD patients showed stronger FC from the noradrenergic locus coeruleus (LC) to the ACC. Functional connectivity between the LC and ACC was positively associated with the degree of motor impulsivity in the total group. Controlling for aggression, a stronger FC was also found between serotonergic nucleus centralis superior (NCS) and the frontopolar cortex (FPC) in patients compared to controls. Furthermore, patients showed a weaker "anti-correlation" from the substantia nigra (SNc) to the left dorsolateral prefrontal cortex (DLPFC). The observed enhanced LC-ACC FC in BPD and its association with the motor impulsivity might be indicative of a noradrenergic dysfunction in the neural inhibitory control network, whereas the significant relationship between NCS-FPC FC and aggression points toward serotonergic contribution to prefrontal control of aggressive reactions. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluating the Record of the Coalition Provisional Authority’s Macroeconomic Reforms in Iraq

DTIC Science & Technology

2011-12-01

Economic Review 6, no. 3 (1992): 355, http://www.cedeplar.ufmg.br/ economia /disciplinas/ecn933a/crocco/Operacao_governanca_Bancos_Centrai s... economia /disciplinas/ecn933a/crocco/Operacao_governanca_Bancos_Centrai s/CUKIERMANAWEBBNEYAPTIMeas.pdf. 34 This finding is consistent with empirical

Quality of Service for Real-Time Applications Over Next Generation Data Networks

NASA Technical Reports Server (NTRS)

Ivancic, William; Atiquzzaman, Mohammed; Bai, Haowei; Su, Hongjun; Jain, Raj; Duresi, Arjan; Goyal, Mukyl; Bharani, Venkata; Liu, Chunlei; Kota, Sastri

2001-01-01

This project, which started on January 1, 2000, was funded by NASA Glenn Research Center for duration of one year. The deliverables of the project included the following tasks: Study of QoS mapping between the edge and core networks envisioned in the Next Generation networks will provide us with the QoS guarantees that can be obtained from next generation networks. Buffer management techniques to provide strict guarantees to real-time end-to-end applications through preferential treatment to packets belonging to real-time applications. In particular, use of ECN to help reduce the loss on high bandwidth-delay product satellite networks needs to be studied. Effect of Prioritized Packet Discard to increase goodput of the network and reduce the buffering requirements in the ATM switches. Provision of new IP circuit emulation services over Satellite IP backbones using MPLS will be studied. Determine the architecture and requirements for internetworking ATN and the Next Generation Internet for real-time applications.

Role and mechanisms of action of Escherichia coli Nissle 1917 in the maintenance of remission in ulcerative colitis patients: An update

PubMed Central

Scaldaferri, Franco; Gerardi, Viviana; Mangiola, Francesca; Lopetuso, Loris Riccardo; Pizzoferrato, Marco; Petito, Valentina; Papa, Alfredo; Stojanovic, Jovana; Poscia, Andrea; Cammarota, Giovanni; Gasbarrini, Antonio

2016-01-01

Ulcerative colitis (UC) is a chronic inflammatory disease, whose etiology is still unclear. Its pathogenesis involves an interaction between genetic factors, immune response and the “forgotten organ”, Gut Microbiota. Several studies have been conducted to assess the role of antibiotics and probiotics as additional or alternative therapies for Ulcerative Colitis. Escherichia coli Nissle (EcN) is a nonpathogenic Gram-negative strain isolated in 1917 by Alfred Nissle and it is the active component of microbial drug Mutaflor® (Ardeypharm GmbH, Herdecke, Germany and EcN, Cadigroup, In Italy) used in many gastrointestinal disorder including diarrhea, uncomplicated diverticular disease and UC. It is the only probiotic recommended in ECCO guidelines as effective alternative to mesalazine in maintenance of remission in UC patients. In this review we propose an update on the role of EcN 1917 in maintenance of remission in UC patients, including data about efficacy and safety. Further studies may be helpful for this subject to further the full use of potential of EcN. PMID:27350728

Escherichia coli Nissle 1917 protects gnotobiotic pigs against human rotavirus by modulating pDC and NK-cell responses.

PubMed

Vlasova, Anastasia N; Shao, Lulu; Kandasamy, Sukumar; Fischer, David D; Rauf, Abdul; Langel, Stephanie N; Chattha, Kuldeep S; Kumar, Anand; Huang, Huang-Chi; Rajashekara, Gireesh; Saif, Linda J

2016-10-01

Lactobacillus rhamnosus GG (LGG), a gram-positive lactic acid bacterium, is one of the most widely used probiotics; while fewer gram-negative probiotics including Escherichia coli Nissle 1917 (EcN) are characterized. A mechanistic understanding of their individual and interactive effects on human rotavirus (HRV) and immunity is lacking. In this study, noncolonized, EcN-, LGG-, and EcN + LGG-colonized neonatal gnotobiotic (Gn) pigs were challenged with HRV. EcN colonization is associated with a greater protection against HRV, and induces the highest frequencies of plasmacytoid dendritic cells (pDCs), significantly increased NK-cell function and decreased frequencies of apoptotic and TLR4 + mononuclear cells (MNCs). Consistent with the highest NK-cell activity, splenic CD172 + MNCs (DC enriched fraction) of EcN-colonized pigs produced the highest levels of IL-12 in vitro. LGG colonization has little effect on the above parameters, which are intermediate in EcN + LGG-colonized pigs, suggesting that probiotics modulate each other's effects. Additionally, in vitro EcN-treated splenic or intestinal MNCs produce higher levels of innate, immunoregulatory and immunostimulatory cytokines, IFN-α, IL-12, and IL-10, compared to MNCs of pigs treated with LGG. These results indicate that the EcN-mediated greater protection against HRV is associated with potent stimulation of the innate immune system and activation of the DC-IL-12-NK immune axis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Evolutionary Computation Approach to Examine Functional Brain Plasticity.

PubMed

Roy, Arnab; Campbell, Colin; Bernier, Rachel A; Hillary, Frank G

2016-01-01

One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs) evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC) based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair) such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN) and the executive control network (ECN) during recovery from traumatic brain injury (TBI); the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in the strength of functional relationship between DMN and ECN for TBI subjects, which is consistent with prior findings in the TBI-literature. The EC-approach also allowed us to separate sub-regional-pairs contributing to positive and negative plasticity; the detected sub-regional-pairs significantly overlap across runs thus highlighting the reliability of the EC-approach. These sub-regional-pairs may be useful in performing nuanced analyses of brain-behavior relationships during recovery from TBI.

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Escherichia coli strain Nissle 1917-from bench to bedside and back: history of a special Escherichia coli strain with probiotic properties.

PubMed

Sonnenborn, Ulrich

2016-10-01

Among the gram-negative microorganisms with probiotic properties, Escherichia coli strain Nissle 1917 (briefly EcN) is probably the most intensively investigated bacterial strain today. Since nearly 100 years, the EcN strain is used as the active pharmaceutical ingredient in a licensed medicinal product that is distributed in Germany and several other countries. Over the last few decades, novel probiotic activities have been detected, which taken together are specific of this versatile E. coli strain. This review gives a short overview on the discovery and history of the EcN strain. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Educational Cultural Negotiators for Students of Color: A Descriptive Study of Racial Advocacy Leaders

ERIC Educational Resources Information Center

Warren Grice, April; Parker, Laurence

2018-01-01

The research presented in this study focuses on Educational Cultural Negotiators (ECNs). The participants were teachers, administrators, and graduate students in an after-school program in the Midwest and a community-based school/university partnership in the Western U.S. We posit that the roles of the ECNs function as advocacy leaders to invoke…

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Improved Method for the Incorporation of Heme Cofactors into Recombinant Proteins Using Escherichia coli Nissle 1917.

PubMed

Fiege, Kerstin; Querebillo, Christine Joy; Hildebrandt, Peter; Frankenberg-Dinkel, Nicole

2018-05-15

Recombinant production of heme proteins in Escherichia coli is often limited by the availability of heme in the host. Therefore, several methods, including the reconstitution of heme proteins after production but prior to purification or the HPEX system, conferring the ability to take up external heme have been developed and used in the past. Here we describe the use of the apathogenic E. coli strain Nissle 1917 (EcN) as a suitable host for the recombinant production of heme proteins. EcN has an advantage over commonly used lab strains in that it is able to take up heme from the environment through the heme receptor ChuA. Expression of several heme proteins from different prokaryotic sources led to high yield and quantitative incorporation of the cofactor when heme was supplied in the growth medium. Comparative UV-vis and resonance Raman measurements revealed that the method employed has significant influence on heme coordination with the EcN system representing the most native situation. Therefore, the use of EcN as a host for recombinant heme protein production represents an inexpensive and straightforward method to facilitate further investigations of structure and function.

Use of a Pro-Fibrogenic Mechanisms-Based Predictive Toxicological Approach for Tiered Testing and Decision Analysis of Carbonaceous Nanomaterials

PubMed Central

Wang, Xiang; Duch, Matthew C.; Mansukhani, Nikhita; Ji, Zhaoxia; Liao, Yu-Pei; Wang, Meiying; Zhang, Haiyuan; Sun, Bingbing; Chang, Chong Hyun; Li, Ruibin; Lin, Sijie; Meng, Huan; Xia, Tian; Hersam, Mark C.; Nel, André E.

2015-01-01

Engineered carbonaceous nanomaterials (ECNs), including single-wall carbon nanotubes (SWCNTs), multi-wall carbon nanotubes (MWCNTs), graphene and graphene oxide (GO), are potentially hazardous to the lung. With incremental experience in the use of predictive toxicological approaches, seeking to relate ECN physicochemical properties to adverse outcome pathways (AOPs), it is logical to explore the existence of a common AOP that allows comparative analysis of broad ECN categories. We established an ECN library comprised of three different types of SWCNTs, graphene and graphene oxide (two sizes) for comparative analysis according to a cell-based AOP that also plays a role in the pathogenesis of pulmonary fibrosis. SWCNTs synthesized by Hipco, arc discharge and Co-Mo catalyst (CoMoCAT®) methods were obtained in their as-prepared (AP) state, following which they were further purified (PD) or coated with Pluronic (PF108) or bovine serum albumin (BSA) to improve dispersal and colloidal stability. Graphene oxide (GO) was prepared as two sizes, GO-small (S) and GO-large (L), while the graphene samples were coated with BSA and PF108 to enable dispersion in aqueous solution. In vitro screening showed that AP- and PD-SWCNTs, irrespective of the method of synthesis, as well as graphene (BSA) and GO (S and L) could trigger interleukin 1β (IL-1β) and transforming growth factor (TGF-β1) production in myeloid (THP-1) and epithelial (BEAS-2B) cell lines, respectively. Oropharyngeal aspiration in mice confirmed that AP-Hipco tubes, graphene (BSA), GO-S and GO-L could induce IL-1β and TGF-β1 production in the lung in parallel with lung fibrosis. Notably, GO-L was the most pro-fibrogenic material based on rapid kinetics of pulmonary injury. In contrast, PF108-dispersed SWCNTs and -graphene failed to exert fibrogenic effects. Collectively, these data indicate that the dispersal state and surface reactivity of ECNs play key roles in triggering a pro-fibrogenic AOP, which could prove helpful for hazard ranking and a proposed tiered testing approach for large ECN categories. PMID:25646681

In situ characterization of natural pyrite bioleaching using electrochemical noise technique

NASA Astrophysics Data System (ADS)

Chen, Guo-bao; Yang, Hong-ying; Li, Hai-jun

2016-02-01

An in situ characterization technique called electrochemical noise (ECN) was used to investigate the bioleaching of natural pyrite. ECN experiments were conducted in four active systems (sulfuric acid, ferric-ion, 9k culture medium, and bioleaching solutions). The ECN data were analyzed in both the time and frequency domains. Spectral noise impedance spectra obtained from power spectral density (PSD) plots for different systems were compared. A reaction mechanism was also proposed on the basis of the experimental data analysis. The bioleaching system exhibits the lowest noise resistance of 0.101 MΩ. The bioleaching of natural pyrite is considered to be a bio-battery reaction, which distinguishes it from chemical oxidation reactions in ferric-ion and culture-medium (9k) solutions. The corrosion of pyrite becomes more severe over time after the long-term testing of bioleaching.

Quantitative EEG and Low-Resolution Electromagnetic Tomography (LORETA) Imaging of Patients Undergoing Methadone Treatment for Opiate Addiction.

PubMed

Wang, Grace Y; Kydd, Robert R; Russell, Bruce R

2016-07-01

Methadone maintenance treatment (MMT) has been used as a treatment for opiate dependence since the mid-1960s. Evidence suggests that methadone binds to mu opiate receptors as do other opiates and induces changes in neurophysiological function. However, little is known, about how neural activity within the higher frequency gamma band (>30 Hz) while at rest changes in those stabilized on MMT despite its association with the excitation-inhibition balance within pyramidal-interneuron networks. Our study investigated differences in resting gamma power (37-41 Hz) between patients undergoing MMT for opiate dependence, illicit opiate users, and healthy controls subjects. Electroencephalographic data were recorded from 26 sites according to the international 10-20 system. Compared with the healthy controls subjects, people either undergoing MMT (mean difference [MD] = 0.32, 95% CI = 0.09-0.55, P < .01) or currently using illicit opiates (MD = 0.31, 95% CI = 0.06-0.56, P = .01) exhibited significant increased gamma power. The sLORETA (standardized low-resolution electromagnetic tomography) between-group comparison revealed dysfunctional neuronal activity in the occipital, parietal, and frontal lobes in the patients undergoing MMT. A more severe profile of dysfunction was observed in those using illicit opiates. Our findings suggest that long-term exposure to opioids is associated with disrupted resting state network, which may be reduced after MMT. © EEG and Clinical Neuroscience Society (ECNS) 2015.

[Building epilepsy care network in Japan].

PubMed

Otsuki, Taisuke

2012-01-01

Number of epilepsy patient in Japan officially surveyed by our government in 2008 is 219,000, which is only 0.17% of the total population and less than one third of the prevalence rate reported in Western countries. Number of epilepsy surgery per year in Japan is also low and less than half of other countries such as US, UK and Korea. These numbers may suggest that epilepsy care in Japan is not sufficient to cover all hidden medical needs of people with epilepsy at present. To solve this issue, our research group funded by the government have started to build an epilepsy care network among primary care physicians, secondary care neurology specialists and tertiary care epilepsy centers by utilizing a web site: Epilepsy Care Network-Japan (http://www.ecn-japan.com/) from July 2012. We are also proposing an epilepsy care algorithm suitable for our complex medical community consisted with various neurology specialists such as pediatric and adult neurologists, neurosurgeons and psychiatrists. Building Epilepsy Care Network in Japan may facilitate better medical and social support for people with epilepsy in Japan.

Analysis of electrochemical noise (ECN) data in time and frequency domain for comparison corrosion inhibition of some azole compounds on Cu in 1.0 M H2SO4 solution

NASA Astrophysics Data System (ADS)

Ramezanzadeh, B.; Arman, S. Y.; Mehdipour, M.; Markhali, B. P.

2014-01-01

In this study, the corrosion inhibition properties of two similar heterocyclic compounds namely benzotriazole (BTA) and benzothiazole (BNS) inhibitors on copper in 1.0 M H2SO4 solution were studied by electrochemical techniques as well as surface analysis. The results showed that corrosion inhibition of copper largely depends on the molecular structure and concentration of the inhibitors. The effect of DC trend on the interpretation of electrochemical noise (ECN) results in time domain was evaluated by moving average removal (MAR) method. Accordingly, the impact of square and Hanning window functions as drift removal methods in frequency domain was studied. After DC trend removal, a good trend was observed between electrochemical noise (ECN) data and the results obtained from EIS and potentiodynamic polarization. Furthermore, the shot noise theory in frequency domain was applied to approach the charge of each electrochemical event (q) from the potential and current noise signals.

Connectivity in MEG resting-state networks increases after resective surgery for low-grade glioma and correlates with improved cognitive performance☆

PubMed Central

van Dellen, E.; de Witt Hamer, P.C.; Douw, L.; Klein, M.; Heimans, J.J.; Stam, C.J.; Reijneveld, J.C.; Hillebrand, A.

2012-01-01

Purpose Low-grade glioma (LGG) patients often have cognitive deficits. Several disease- and treatment related factors affect cognitive processing. Cognitive outcome of resective surgery is unpredictable, both for improvement and deterioration, especially for complex domains such as attention and executive functioning. MEG analysis of resting-state networks (RSNs) is a good candidate for presurgical prediction of cognitive outcome. In this study, we explore the relation between alterations in connectivity of RSNs and changes in cognitive processing after resective surgery, as a stepping stone to ultimately predict postsurgical cognitive outcome. Methods Ten patients with LGG were included, who had no adjuvant therapy. MEG recording and neuropsychological assessment were obtained before and after resective surgery. MEG data were recorded during a no-task eyes-closed condition, and projected to the anatomical space of the AAL atlas. Alterations in functional connectivity, as characterized by the phase lag index (PLI), within the default mode network (DMN), executive control network (ECN), and left- and right-sided frontoparietal networks (FPN) were compared to cognitive changes. Results Lower alpha band DMN connectivity was increased after surgery, and this increase was related to improved verbal memory functioning. Similarly, right FPN connectivity was increased after resection in the upper alpha band, which correlated with improved attention, working memory and executive functioning. Discussion Increased alpha band RSN functional connectivity in MEG recordings correlates with improved cognitive outcome after resective surgery. The mechanisms resulting in functional connectivity alterations after resection remain to be elucidated. Importantly, our findings indicate that connectivity of MEG RSNs may be used for presurgical prediction of cognitive outcome in future studies. PMID:24179752

Distinct inflammatory and cytopathic characteristics of Escherichia coli isolates from inflammatory bowel disease patients.

PubMed

Jensen, Stina Rikke; Mirsepasi-Lauridsen, Hengameh Chloé; Thysen, Anna Hammerich; Brynskov, Jørn; Krogfelt, Karen A; Petersen, Andreas Munk; Pedersen, Anders Elm; Brix, Susanne

2015-12-01

Escherichia coli (E. coli) may be implicated in the pathogenesis of inflammatory bowel disease (IBD), as implied from a higher prevalence of mucosa-associated E. coli in the gut of IBD-affected individuals. However, it is unclear whether different non-diarrheagenic E. coli spp. segregate from each other in their ability to promote intestinal inflammation. Herein we compared the inflammation-inducing properties of non-diarrheagenic LF82, 691-04A, E. coli Nissle 1917 (ECN) and eleven new intestinal isolates from different locations in five IBD patients and one healthy control. Viable E. coli were cultured with human monocyte-derived dendritic cells (moDCs) and monolayers of intestinal epithelial cells (IECs), followed by analysis of secreted cytokines, intracellular levels of reactive oxygen species and cellular death. The IBD-associated E. coli LF82 induced the same dose-dependent inflammatory cytokine profile as ECN and ten of the new E. coli isolates displayed as high level IL-12p70, IL-1β, IL-23 and TNF-α from moDCs irrespective of their site of isolation (ileum/colon/faeces), disease origin (diseased/non-diseased) or known virulence factors. Contrarily, 691-04A and one new IBD E. coli isolate induced a different cellular phenotype with enhanced killing of moDCs and IECs, coupled to elevated IL-18. The cytopathic nature of 691-04A and one other IBD E. coli isolate suggests that colonization with specific non-diarrheagenic E. coli could promote intestinal barrier leakage and profound intestinal inflammation, while LF82, ECN and the remaining non-diarrheagenic E. coli isolates hold notorious pro-inflammatory characteristics that can progress inflammation in case of intestinal barrier leakage. Copyright © 2015 Elsevier GmbH. All rights reserved.

Interleukin-8, CXCL1, and MicroRNA miR-146a Responses to Probiotic Escherichia coli Nissle 1917 and Enteropathogenic E. coli in Human Intestinal Epithelial T84 and Monocytic THP-1 Cells after Apical or Basolateral Infection.

PubMed

Sabharwal, Harshana; Cichon, Christoph; Ölschläger, Tobias A; Sonnenborn, Ulrich; Schmidt, M Alexander

2016-09-01

Bacterium-host interactions in the gut proceed via directly contacted epithelial cells, the host's immune system, and a plethora of bacterial factors. Here we characterized and compared exemplary cytokine and microRNA (miRNA) responses of human epithelial and THP-1 cells toward the prototype enteropathogenic Escherichia coli (EPEC) strain E2348/69 (O127:H6) and the probiotic strain Escherichia coli Nissle 1917 (EcN) (O6:K5:H1). Human T84 and THP-1 cells were used as cell culture-based model systems for epithelial and monocytic cells. Polarized T84 monolayers were infected apically or basolaterally. Bacterial challenges from the basolateral side resulted in more pronounced cytokine and miRNA responses than those observed for apical side infections. Interestingly, the probiotic EcN also caused a pronounced transcriptional increase of proinflammatory CXCL1 and interleukin-8 (IL-8) levels when human T84 epithelial cells were infected from the basolateral side. miR-146a, which is known to regulate adaptor molecules in Toll-like receptor (TLR)/NF-κB signaling, was found to be differentially regulated in THP-1 cells between probiotic and pathogenic bacteria. To assess the roles of flagella and flagellin, we employed several flagellin mutants of EcN. EcN flagellin mutants induced reduced IL-8 as well as CXCL1 responses in T84 cells, suggesting that flagellin is an inducer of this cytokine response. Following infection with an EPEC type 3 secretion system (T3SS) mutant, we observed increased IL-8 and CXCL1 transcription in T84 and THP-1 cells compared to that in wild-type EPEC. This study emphasizes the differential induction of miR-146a by pathogenic and probiotic E. coli strains in epithelial and immune cells as well as a loss of probiotic properties in EcN interacting with cells from the basolateral side. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Quality of Service for Real-Time Applications Over Next Generation Data Networks

NASA Technical Reports Server (NTRS)

Atiquzzaman, Mohammed; Jain, Raj

2001-01-01

This project, which started on January 1, 2000, was funded by the NASA Glenn Research Center for duration of one year. The deliverables of the project included the following tasks: (1) Study of QoS mapping between the edge and core networks envisioned in the Next Generation networks will provide us with the QoS guarantees that can be obtained from next generation networks; (2) Buffer management techniques to provide strict guarantees to real-time end-to-end applications through preferential treatment to packets belonging to real-time applications. In particular, use of ECN to help reduce the loss on high bandwidth-delay product satellite networks needs to be studied; (3) Effect of Prioritized Packet Discard to increase goodput of the network and reduce the buffering requirements in the ATM switches; (4) Provision of new IP circuit emulation services over Satellite IP backbones using MPLS will be studied; and (5) Determine the architecture and requirements for internetworking ATN and the Next Generation Internet for real-time applications. The project has been completed on time. All the objectives and deliverables of the project have been completed. Research results obtained from this project have been published in a number of papers in journals, conferences, and technical reports, included in this document.

Phenological changes of the most commonly sampled ground beetle (Coleoptera: Carabidae) species in the UK environmental change network

NASA Astrophysics Data System (ADS)

Pozsgai, Gabor; Baird, John; Littlewood, Nick A.; Pakeman, Robin J.; Young, Mark R.

2018-03-01

Despite the important roles ground beetles (Coleoptera: Carabidae) play in ecosystems, the highly valued ecosystem services they provide, and ample descriptive documentation of their phenology, the relative impact of various environmental factors on carabid phenology is not well studied. Using the long-term pitfall trap capture data from 12 terrestrial Environmental Change Network (ECN) sites from the UK, we examined how changing climate influenced the phenology of common carabids, and the role particular climate components had on phenological parameters. Of the 28 species included in the analyses, 19 showed earlier start of their activity. This advance was particularly pronounced in the spring, supporting the view that early phenophases have a greater tendency to change and these changes are more directly controlled by temperature than later ones. Autumn activity extended only a few cases, suggesting a photoperiod-driven start of hibernation. No association was found between life-history traits and the ability of species to change their phenology. Air temperatures between April and June were the most important factors determining the start of activity of each species, whilst late season precipitation hastened the cessation of activity. The balance between the advantages and disadvantages of changing phenology on various levels is likely to depend on the species and even on local environmental criteria. The substantially changing phenology of Carabidae may influence their function in ecosystems and the ecosystem services they provide.

Phenological changes of the most commonly sampled ground beetle (Coleoptera: Carabidae) species in the UK environmental change network.

PubMed

Pozsgai, Gabor; Baird, John; Littlewood, Nick A; Pakeman, Robin J; Young, Mark R

2018-06-01

Despite the important roles ground beetles (Coleoptera: Carabidae) play in ecosystems, the highly valued ecosystem services they provide, and ample descriptive documentation of their phenology, the relative impact of various environmental factors on carabid phenology is not well studied. Using the long-term pitfall trap capture data from 12 terrestrial Environmental Change Network (ECN) sites from the UK, we examined how changing climate influenced the phenology of common carabids, and the role particular climate components had on phenological parameters. Of the 28 species included in the analyses, 19 showed earlier start of their activity. This advance was particularly pronounced in the spring, supporting the view that early phenophases have a greater tendency to change and these changes are more directly controlled by temperature than later ones. Autumn activity extended only a few cases, suggesting a photoperiod-driven start of hibernation. No association was found between life-history traits and the ability of species to change their phenology. Air temperatures between April and June were the most important factors determining the start of activity of each species, whilst late season precipitation hastened the cessation of activity. The balance between the advantages and disadvantages of changing phenology on various levels is likely to depend on the species and even on local environmental criteria. The substantially changing phenology of Carabidae may influence their function in ecosystems and the ecosystem services they provide.

Phenological changes of the most commonly sampled ground beetle (Coleoptera: Carabidae) species in the UK environmental change network

NASA Astrophysics Data System (ADS)

Pozsgai, Gabor; Baird, John; Littlewood, Nick A.; Pakeman, Robin J.; Young, Mark R.

2018-06-01

Despite the important roles ground beetles (Coleoptera: Carabidae) play in ecosystems, the highly valued ecosystem services they provide, and ample descriptive documentation of their phenology, the relative impact of various environmental factors on carabid phenology is not well studied. Using the long-term pitfall trap capture data from 12 terrestrial Environmental Change Network (ECN) sites from the UK, we examined how changing climate influenced the phenology of common carabids, and the role particular climate components had on phenological parameters. Of the 28 species included in the analyses, 19 showed earlier start of their activity. This advance was particularly pronounced in the spring, supporting the view that early phenophases have a greater tendency to change and these changes are more directly controlled by temperature than later ones. Autumn activity extended only a few cases, suggesting a photoperiod-driven start of hibernation. No association was found between life-history traits and the ability of species to change their phenology. Air temperatures between April and June were the most important factors determining the start of activity of each species, whilst late season precipitation hastened the cessation of activity. The balance between the advantages and disadvantages of changing phenology on various levels is likely to depend on the species and even on local environmental criteria. The substantially changing phenology of Carabidae may influence their function in ecosystems and the ecosystem services they provide.

The entrance channel effects on the deexcitation ways of the same compound nucleus at a fixed excitation energy

NASA Astrophysics Data System (ADS)

Anastasi, A.; Mandaglio, G.; Curciarello, F.; Nasirov, A. K.; Fazio, G.; Giardina, G.

2018-05-01

The investigation of various properties of deexcitation of the same 220Th compound nucleus (CN), formed by the different mass (charge) asymmetric 16O+204Pb, 40Ar+180Hf, 82Se+138Ba and 96Zr+124Sn reactions is presented. The effective fission barrier < B fis > value, as a function of the excitation energy {E}CN* , determined for each intermediate excited nucleus reached along the deexcitation cascade of the CN obtained by the four considered reactions is strongly sensitive to the various orbital angular momentum L=ℓℏ distributions of CN formed with the same excitation energy {E}CN* by the various entrance channels. Therefore, the competition between the fission and evaporation of light particles (neutron, proton, and α-particle) processes along the deexcitation cascade of CN is dependent on the orbital angular momentum distribution of CN. In fact, the ratio between the evaporation residue cross sections obtained when also the charged particles are emitted and the ones obtained after neutron emission only for the same CN with a fixed excitation energy {E}CN* is sensitive to the mass (charge) asymmetry of the entrance channel.

The Administration of Escherichia coli Nissle 1917 Ameliorates Development of DSS-Induced Colitis in Mice

PubMed Central

Rodríguez-Nogales, Alba; Algieri, Francesca; Garrido-Mesa, José; Vezza, Teresa; Utrilla, Maria P.; Chueca, Natalia; Fernández-Caballero, Jose A.; García, Federico; Rodríguez-Cabezas, Maria E.; Gálvez, Julio

2018-01-01

The beneficial effects of probiotics on immune-based pathologies such as inflammatory bowel disease (IBD) have been well reported. However, their exact mechanisms have not been fully elucidated. Few studies have focused on the impact of probiotics on the composition of the colonic microbiota. The aim of the present study was to correlate the intestinal anti-inflammatory activity of the probiotic Escherichia coli Nissle 1917 (EcN) in the dextran sodium sulfate (DSS) model of mouse colitis with the changes induced in colonic microbiota populations. EcN prevented the DSS-induced colonic damage, as evidenced by lower disease activity index (DAI) values and colonic weight/length ratio, when compared with untreated control mice. The beneficial effects were confirmed biochemically, since the probiotic treatment improved the colonic expression of different cytokines and proteins involved in epithelial integrity. In addition, it restored the expression of different micro-RNAs (miR-143, miR-150, miR-155, miR-223, and miR-375) involved in the inflammatory response that occurs in colitic mice. Finally, the characterization of the colonic microbiota by pyrosequencing showed that the probiotic administration was able to counteract the dysbiosis associated with the intestinal inflammatory process. This effect was evidenced by an increase in bacterial diversity in comparison with untreated colitic mice. The intestinal anti-inflammatory effects of the probiotic EcN were associated with an amelioration of the altered gut microbiome in mouse experimental colitis, especially when considering bacterial diversity, which is reduced in these intestinal conditions. Moreover, this probiotic has shown an ability to modulate expression levels of miRNAs and different mediators of the immune response involved in gut inflammation. This modulation could also be of great interest to understand the mechanism of action of this probiotic in the treatment of IBD.

Volatile molecular markers of VOO Thermo-oxidation: Effect of heating processes, macronutrients composition, and olive ripeness on the new emitted aldehydic compounds.

PubMed

Oueslati, Imen; Manaï, Hédia; Madrigal-Martínez, Mónica; Martínez-Cañas, Manuel A; Sánchez-Casas, Jacinto; Zarrouk, Mokhtar; Flamini, Guido

2018-04-01

Heating operation has been applied to Chétoui extra-virgin olive oils (EVOOs) extracted from fruits with several ripening stages (RS). The studied samples, were subjected to microwave and conventional heating. Results showed that heated VOOs after 2.5 h and 7 min of conventional and microwave heating, respectively, gave rise to a drastically decrease of LOX products and allowed the detection of toxic new formed aldehydic volatiles (alkanal: nonanal, alkenals: (Z)-2-heptenal and (E)-2-decenal, and alkadienals: (E.E)-2.4-decadienal), which can be used as markers of VOO degradation. Their abundance in the VOO headspaces depends on their boiling points, the rate of their possible degradation to yield other compounds, on the heating processes and on the rate of macronutrients. The emission rate of the new synthesized volatiles during heating processes was mainly attributed to enzymatic oxidation of some fatty acids. Hexanal, (Z)-2-heptenal, (E)-2-octenal, (E)-2-nonenal, (E,E) and (E,Z)-2,4-decadienal, and (E,E)-2,4-nonadienal, derived from linoleic acid, and heptanol, octanal, nonanal, decanal, (E) and (Z)-2-decenal, (E)-2-undecenal, and (E,E)-2,4-nonadienal, are emitted after degradation of oleic acid. During thermo-oxidation, the ECN 44 (LLO, and OLnO), and the ECN 46 (OLO, and PLO + SLL) compounds decreased, whereas, the ECN 48 (OOO, and PPO), and the ECN 50 (SOO) compounds increased when temperature and heating time increased. The several variations of the studied biochemical compounds depend to the heating processes. Ripening stage of olive fruits can be used as a tool to monitor the emission rate of the aldehydic volatiles, but cannot be used for a chemometric discrimination. Copyright © 2018 Elsevier Ltd. All rights reserved.

ETF Facility evaporator skid orifice sizing design analysis

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

ELLINGSON, S.D.

1999-08-31

This document releases and records the design analysis for sizing the Orifice plate being installed on the Effluent Treatment Facility (ETF) evaporator skid per Engineering Change Notice (ECN) 651583.

Phosphatidylglycerol molecular species of photosynthetic membranes analyzed by high-performance liquid chromatography: theoretical considerations.

PubMed

Xu, Y; Siegenthaler, P A

1996-02-01

A reversed-phase high-performance liquid chromatography technique was developed to separate, identify, and quantify individual phosphatidylglycerol (PG) molecular species in thylakoid membranes isolated from higher plant leaves. PG was first separated by thin-layer chromatography; then the dinitrobenzoyl derivatives of diacylglycerols produced after phospholipase C hydrolysis of PG were separated by a C18 reversed-phase column and detected at 254 nm. A linear response of the detector was observed in the range of 0.025 to 12 nmol of PG molecular species. It was established that there was an excellent correlation (r = 0.996) between the carbon and double-bond number in the aliphatic residues and the relative retention time of dinitrobenzoyl derivatives. A new equivalent carbon number value (ECN*) which takes into consideration the number of cis-(nc) and trans-(nt) double bonds per molecular species was defined as ECN* = CN - 2nc - nt, where CN is the number of carbon atoms in the aliphatic residues. The logarithm of the retention time increased linearily as a function of ECN* value. However, in this type of correlation, it may happen that two molecular species of PG having distinct relative retention times had the same ECN* value. In this case, the two molecular species can be identified by the linear correlation (r = 1) existing between the reciprocal of the relative retention time and the number of double bonds (0 < or = n < or = 3) in the separate 18:n/delta 3-trans-hexadecenoic acid -16:1(3t)- and 18:n/16:0 molecular species series. The advantages of this method are good separation, cohort elution time, quantitative precision, and predictable retention times of PG molecular species from chloroplast membranes. The method has been used routinely to identify the ten PG molecular species of thylakoid membranes in squash, potato, lettuce, and spinach leaf: 18:3/16:1(3t), 18:3/16:0, 18:2/16:1(3t), 18:2/16:0, 18:1/16:1(3t), 18:1/16:0, 18:0/16:1(3t), 18:0/16:0, 16:0/16:1(3t), and 16:0/16:0.

ECN-23100

NASA Image and Video Library

1983-04-01

An early (1983) photograph of the AFTI F-16 team, commemorating the aircraft's 50th flight. It shows the initial configuration and paint finish of the AFTI F-16, as well as the forward mounted canards and the spin chute.

Oxidation of SiC

NASA Astrophysics Data System (ADS)

Cooper, James A.

1997-03-01

SiC is a wide band gap hexagonal anisotropic semiconductor which is attractive for use in high voltage, high temperature, or high power applications. SiC is also the only compound semiconductor that can be thermally oxidized to form SiO_2, making it possible to construct many conventional MOS devices in this material. The electrical quality of the SiO_2/SiC interface is far from ideal, however, and considerable research is presently directed to understanding and improving this interface. Electrical characterization of the SiC MOS interface is complicated by the wide band gap, since most interface states are energetically too far removed from the conduction or valence bands to respond to electrical stimulation at room temperature. Moreover, very little information is yet available on the properties of the MOS interface on the 4H polytype of SiC (preferred because of it's higher bulk electron mobility) or on interfaces on crystalline surfaces perpendicular to the basal plane (where an equal number of Si and C atoms are present). Finally, electron mobilities in inversion layers on 4H-SiC reported to date are anomolously low, especially in consideration of the relatively high bulk mobilities in this polytype. In this talk we will discuss MOS characterization techniques for wide band gap semiconductors and review the current understanding of the physics of the MOS interface on thermally oxidized SiC.

Mapping Operation and Maintenance Strategy for U.S. Offshore Wind Farms

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

Dewan, Ashish; Stehly, Tyler

This presentation provides an overview of a collaborative effort between ECN and the National Renewable Energy Laboratory that focused on an operation and maintenance study of six offshore wind power plants in the United States.

ECN-1880

NASA Image and Video Library

1969-01-09

Flight Research Center and Dryden Flight Research Center engineer R. Dale Reed has long used free-flight models to test new concepts. This photo from 1963 shows two different models of the M2-F2 (one under the Mothership) and four Hyper III shapes.

Beta Responses in Healthy Elderly and in Patients With Amnestic Mild Cognitive Impairment During a Task of Temporal Orientation of Attention.

PubMed

Caravaglios, Giuseppe; Castro, Giuseppe; Muscoso, Emma Gabriella; Crivelli, Davide; Balconi, Michela

2016-11-02

Recent studies demonstrated that beta oscillations are elicited during cognitive processes. To investigate their potential as electrophysiological markers of amnestic mild cognitive impairment (aMCI), we recorded beta EEG activity during resting and during an omitted tone task in patients and healthy elderly. Thirty participants were enrolled (15 patients, 15 healthy controls). In particular, we investigated event-related spectral perturbation and intertrial coherence indices. Analyses showed that (a) healthy elderly presented greater beta power at rest than patients with aMCI patients; (b) during the task, healthy elderly were more accurate than aMCI patients and presented greater beta power than aMCI patients; (c) both groups showed qualitatively similar spectral perturbation responses during the task, but different spatiotemporal response patterns; and (d) aMCI patients presented greater beta phase locking than healthy elderly during the task. Results indicate that beta activity in healthy elderly differs from that of patients with aMCI. Furthermore, the analysis of task-related EEG activity extends evidences obtained during resting and suggests that during the prodromal phase of Alzheimer's disease there is a reduced efficiency in information exchange by large-scale neural networks. The study for the first time shows the potential of task-related beta responses as early markers of aMCI impairments. © EEG and Clinical Neuroscience Society (ECNS) 2016.

ECN-14284

NASA Image and Video Library

1980-12-30

A close-up view of the Highly Maneuverable Aircraft Technology (HiMAT) research vehicle attached to a wing pylon on NASA’s B-52 mothership during a 1980 test flight. The HiMAT used sharply swept-back wings and a canard configuration to test possible technology for advanced fighters.

Small Supernumerary Marker Chromosome May Provide Information on Dosage-insensitive Pericentric Regions in Human.

PubMed

Al-Rikabi, Ahmed B Hamid; Pekova, Sona; Fan, Xioabo; Jančušková, Tereza; Liehr, Thomas

2018-04-01

Cytogenetically visible chromosomal imbalances in humans are deleterious and adverse in the majority of the cases. However, healthy persons living with chromosomal imbalances in the range of several megabasepairs (Mbps) in size, like carriers of small Supernumerary Marker Chromosomes (sSMCs) exist. The identification of healthy sSMC carriers with euchromatic centromere-near (ECN) imbalances led to the following proposal: ECN-regions do not contain any dosage sensitive genes. Due to own previous work, dosage-insensitive pericentric ECN-regions were already determined with an accuracy of 0.3 and 5 Mbp. Based on this data we established 43 new pericentromeric probe sets spanning about 3-5 Mbp of each euchromatic human chromosome arm starting from the known insensitive regions towards distal. Such so called pericentromeric-critical region fluorescence in situ hybridization (PeCR-FISH) probe sets were applied exemplarily and successful here in 15 sSMC cases as available from the Else Kröner-Fresenius-sSMC-cellbank . Most of the involved sSMC breakpoints could be characterized as a higher resolution than before. An unexpected result was that in 5/15 cases cryptic mosaicism was characterized. The latter is also to be considered to have potentially an influence on the clinical outcome in these so-called discontinuous sSMCs. Overall, the suitability of PeCR-FISH to characterize sSMCs was proven; the potential of this probe set to further delineate sizes of dosage insensitive pericentric regions is obvious but dependent on suited cases. Furthermore, discontinuous sSMCs can be identified by this approach and this new subtype of sSMC needs to be studied in more detail in future.

ECN-22193

NASA Image and Video Library

1982-12-22

A close-up photo of the spin chute mounted on the rear fuselage of the AFTI F-16, a safety device designed to prevent the loss of aircraft in spin conditions. Under some circumstances, pilots cannot recover from spins using normal controls. It these instances, the spin chute is deployed, thus "breaking" the spin and enabling the pilot to recover. The spin chute is held in a metal cylinder attached to the AFTI F-16 by four tubes, a structure strong enough to withstand the shock of the spin chute opening. Unlike the air probe in the last photo, spin chutes are not standard equipment on research or prototype aircraft but are commonly attached expressly for actual spin tests.

Functional eladic containing triglycerides: Synthesis, physical properties, and solution behavior

USDA-ARS?s Scientific Manuscript database

The enthalpy of fusion (Hf) for a number of symmetrical and asymmetrical triacylgylcerides as mixtures in soybean oil (TAGs) were determined by melting point data (MPD), differential scanning calorimetry (DSC), and effective carbon numbers (ECN). Pure triacylgylcerides were mixed with soybean oil an...

Wind Turbine Wake Experiment - Wieringermeer (WINTWEX-W)

NASA Astrophysics Data System (ADS)

Kumer, V. M.; Reuder, J.; Svardal, B.; Eecen, P.

2014-12-01

WINTWEX-W is a cooperative wake measurement campaign conducted by the Norwegian Centre of Offshore Wind Energy (Norcowe) and the Energy Research Centre of the Netherlands (ECN). A scanning, four static Windcubes as well as a downstream looking nacelle LiDAR were placed for half a year downstream of one of five research wind turbines in ECNs' wind turbine test farm Wieringermeer. In order to capture wake characteristics under different weather conditions we scanned a 60˚ sector at three different elevations and two vertical cross-sections every minute. Windcubes v1 measured wind profiles every second at 2, 5 and 12 rotor diameter downstream distances. Another static Windcube, a forward-looking nacelle LiDAR and three Sonics were placed upstream to measure the undisturbed approaching flow field. The aim of the campaign is a qualitative and quantitative description of single wind turbine wake propagation and persistency, as well as to improve CFD wake models by delivering a detailed data set of several real atmospheric conditions.

Distillation fraction-specific ecotoxicological evaluation of a paraffin-rich crude oil.

PubMed

Erlacher, Elisabeth; Loibner, Andreas P; Kendler, Romana; Scherr, Kerstin E

2013-03-01

Crude oil is a complex mixture of petroleum hydrocarbons (PHC) with distinct chemical, physical and toxicological properties relevant for contaminated site risk assessment. Ecotoxicological effects of crude oil distillation fractions on luminescent bacteria (Vibrio fischeri), earthworms (Dendrobaena hortensis) and invertebrates (Heterocypris incongruens) were tested using two spiked soils and their elutriates. Fraction 2 (F2) had an equivalent carbon number (ECN) range of >10 to 16, and F3 from >16 to 39. F2 showed a substantially higher ecotoxicological effect than F3 for Vibrio and Dendrobaena. In contrast, severe inhibition of Heterocypris by the poorly soluble F3 is attributed to mechanical organ blockage. Immediate sequestration of PHC to the organic matter-rich soil effected reduced toxicity for all organisms. This study indicates that a more differentiated consideration (i) of PHC mixtures based on ECN range and (ii) of model soil properties employed for ecotoxicity testing should be included into PHC-contaminated site risk assessment. Copyright © 2012 Elsevier Ltd. All rights reserved.

ECN-14280

NASA Image and Video Library

1980-12-30

The HiMAT (Highly Maneuverable Aircraft Technology) subscale research vehicle, seen here during a research flight, was flown by the NASA Dryden Flight Research Center, Edwards, California, from mid 1979 to January 1983. The aircraft demonstrated advanced fighter technologies that have been used in the development of many modern high performance military aircraft.

ECN-14273

NASA Image and Video Library

1980-12-30

The HiMAT (Highly Maneuverable Aircraft Technology) subscale research vehicle, seen here during a research flight, was flown by the NASA Dryden Flight Research Center, Edwards, California, from mid 1979 to January 1983. The aircraft demonstrated advanced fighter technologies that have been used in the development of many modern high performance military aircraft.

75 FR 3593 - Concept Release on Equity Market Structure

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-21

..., market data linkages, and undisplayed, or ``dark,'' liquidity. The Commission intends to use the public's... Centers 1. Registered Exchanges 2. ECNs 3. Dark Pools 4. Broker-Dealer Internalization B. Linkages 1... Handling Rules Release''). \\3\\ See, e.g., In the Matter of National Association of Securities Dealers, Inc...

78 FR 3058 - Self-Regulatory Organizations; National Stock Exchange, Inc.; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-15

... Organizations; National Stock Exchange, Inc.; Notice of Filing and Immediate Effectiveness of Proposed Rule... Mode provides ECNs with advertising through attributed quotations which facilitates an increasing rate... comments on the proposed rule change. III. Date of Effectiveness of the Proposed Rule Change and Timing for...

75 FR 55385 - Self-Regulatory Organizations; EDGX Exchange, Inc.; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-10

...-Regulatory Organizations; EDGX Exchange, Inc.; Notice of Filing and Immediate Effectiveness of Proposed Rule... guarantee limits the increase in a Members' execution costs associating with failing to meet the volume thresholds of other exchanges and ECNs while a Member is in the process of migrating volumes from one...

Systems Engineering 2010 Workshop | Wind | NREL

Science.gov Websites

turbine aeroelastic model, inflow turbulence model, wind plan layout and interactions, resource model, O on the approach to wind turbine design, choice, and deployment 2:40 Break Computer Science perspective) International Laboratories 3:20 Bernard Bulder, ECN Integral Wind Turbine Design with Focus-6 3

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2013-08-14

... through of the rate that Direct Edge ECN LLC (d/b/a DE Route) (``DE Route''), the Exchange's affiliated... daily basis, measured monthly, more than that MPID's December 2012 added TCV (the ``December Baseline... of Members or competing venues to maintain their competitive standing in the financial markets...

ECN-2301

NASA Image and Video Library

1969-09-10

The Hyper III was a low-cost test vehicle for an advanced lifting-body shape. Like the earlier M2-F1, it was a "homebuilt" research aircraft, i.e., built at the Flight Research Center (FRC), later redesignated the Dryden Flight Research Center. It had a steel-tube frame covered with Dacron, a fiberglass nose, sheet aluminum fins, and a wing from an HP-11 sailplane. Construction was by volunteers at the FRC. Although the Hyper III was to be flown remotely in its initial tests, it was fitted with a cockpit for a pilot. On the Hyper III's only flight, it was towed aloft attached to a Navy SH-3 helicopter by a 400-foot cable. NASA research pilot Bruce Peterson flew the SH-3. After he released the Hyper III from the cable, NASA research pilot Milt Thompson flew the vehicle by radio control until the final approach when Dick Fischer took over control using a model-airplane radio-control box. The Hyper III flared, then landed and slid to a stop on Rogers Dry Lakebed.

Computer system design description for SY-101 hydrogen mitigation test project data acquisition and control system (DACS-1)

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

Ermi, A.M.

1997-05-01

Description of the Proposed Activity/REPORTABLE OCCURRENCE or PIAB: This ECN changes the computer systems design description support document describing the computers system used to control, monitor and archive the processes and outputs associated with the Hydrogen Mitigation Test Pump installed in SY-101. There is no new activity or procedure associated with the updating of this reference document. The updating of this computer system design description maintains an agreed upon documentation program initiated within the test program and carried into operations at time of turnover to maintain configuration control as outlined by design authority practicing guidelines. There are no new crediblemore » failure modes associated with the updating of information in a support description document. The failure analysis of each change was reviewed at the time of implementation of the Systems Change Request for all the processes changed. This document simply provides a history of implementation and current system status.« less

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2013-12-26

..., written notice to FINRA Market Operations of its intention to withdraw as a Registered Reporting ADF ECN... rejection by the ADF Trading Center. As such, an incoming order that fully posts to the book of that ADF... book of that ADF Trading Center, and is subsequently cancelled, corrected, etc., the order reporting...

78 FR 27274 - Self-Regulatory Organizations; EDGX Exchange, Inc.; Notice of Filing and Immediate Effectiveness...

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2013-05-09

...' orders that yield Flag BY. When Direct Edge ECN LLC (d/b/a DE Route) (``DE Route''), the Exchange's... for removing liquidity from the BYX order book for executions by members that add a daily average... competing venues to maintain their competitive standing in the financial markets. The Exchange believes that...

Protocol Design Challenges in the Detection of Awareness in Aware Subjects Using EEG Signals.

PubMed

Henriques, J; Gabriel, D; Grigoryeva, L; Haffen, E; Moulin, T; Aubry, R; Pazart, L; Ortega, J-P

2016-10-01

Recent studies have evidenced serious difficulties in detecting covert awareness with electroencephalography-based techniques both in unresponsive patients and in healthy control subjects. This work reproduces the protocol design in two recent mental imagery studies with a larger group comprising 20 healthy volunteers. The main goal is assessing if modifications in the signal extraction techniques, training-testing/cross-validation routines, and hypotheses evoked in the statistical analysis, can provide solutions to the serious difficulties documented in the literature. The lack of robustness in the results advises for further search of alternative protocols more suitable for machine learning classification and of better performing signal treatment techniques. Specific recommendations are made using the findings in this work. © EEG and Clinical Neuroscience Society (ECNS) 2014.

78 FR 46652 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing of...

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2013-08-01

... ADF Market Maker or Registered Reporting ADF ECN that is a ``Trading Center,'' as defined in Rule 600... requirements currently in Rule 6271(b). Members who are Trading Centers, as defined in Rule 600(b)(78) of SEC... timetable as agreed to by the member and FINRA. The proposed rule change defines the ``ADF Deposit Amount...

ECN-15655

NASA Image and Video Library

1981-05-21

In this photograph, the C-140 JetStar is fitted with a model of a high-speed propeller. Three different designs were tested at NASA's Dryden Flight Research Facility in 1981-1982. Their swept-back blades were intended to increase the speed and fuel efficiency of turboprop aircraft. Speeds of Mach 0.8 were thought possible, while using 20 to 30 percent less fuel than standard jet engines.

76 FR 64147 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

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2011-10-17

..., there is no economic basis for regulating maximum prices for one of the joint products in an industry in... proprietary book data on the Internet. Second, because a single order or transaction report can appear in an... Tradebook, Island, RediBook, Attain, TracECN, BATS Trading and Direct Edge. A proliferation of dark pools...

78 FR 36006 - Self-Regulatory Organizations; EDGA Exchange, Inc.; Notice of Filing and Immediate Effectiveness...

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2013-06-14

... Flag RB. The proposed change represents a pass through of the rate that Direct Edge ECN LLC (d/b/a DE... in the financial markets. The Exchange believes that its proposal to lower the default rebate for... Change Relating to Amendments to the EDGA Exchange, Inc. Fee Schedule June 10, 2013. Pursuant to Section...

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2013-05-09

... rate that Direct Edge ECN LLC (d/b/a DE Route) (``DE Route''), the Exchange's affiliated routing broker... daily average volume of at least 50,000 shares from $0.0002 per share to $0.0005 per share). The... the financial markets. The Exchange believes that its proposal to pass through a rebate of $0.0005 per...

Nonlinear Dynamics of Formation of Drops of Non-Newtonian Liquids from Capillaries: Satellite Formation and Flow Transitions

NASA Astrophysics Data System (ADS)

Yildirim, Ozgur E.; Basaran, Osman A.

1999-11-01

Drop formation from capillaries, and the often undesired phenomenon of satellite generation, play a central role in diverse applications including ink-jet printing, biochip processors, and spray coating, where the working fluid is usually non-Newtonian. Although some work has been done in related areas, the phenomenon of formation of drops of non--Newtonian fluids from capillaries has remained largely unexplored. Here a theoretical approach is adopted to study the dripping of axisymmetric drops of non--Newtonian liquids from capillaries. The constitutive equation used accounts for both shear thinning and strain hardening. First, regular perturbation theory is utilized to reduce the spatial dimension of the governing equations to one. The computations rely on Galerkin/finite element analysis with adaptive finite differencing for time integration. The dynamics are followed beyond the first breakup to investigate conditions for occurrence of satellites. Effect of increasing flow rate is also studied to uncover transitions that occur as one moves from a regime of periodic drop formation to one of jetting.

Project W-314 acceptance test report HNF-4643 for HNF-4642 241-AN-A valve pit manifold valves and position indication for project W-314

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

HAMMERS, J.S.

1999-09-22

The purpose of the test was to verify that the AN Tank Farm Manifold Valves can be manually manipulated to the required operating position and that the electrical and visual indications accurately reflect that position. Physical locking devices were also verified to function. The Acceptance Test Procedure HNF-4642, 241-AN-A Valve Pit Manifold Valves and Position Indication was conducted between 23 June and 10 August 1999 at the 200E AN Tank Farm. The test has no open test exceptions. The test was conducted prior to final engineering ''as built'' activities being completed, this had an impact on the procedure and testmore » results, ECN 653752 was written to correct the mismatch between the procedure and actual field conditions. P&ID H-14-100941 was changed via ECN-W-314-4C-120. All components, identified in the procedure, were not found to be labeled and identified as written in the procedure, temporary tags were used for operational identification. A retest of valve ANA-WT-V 318 was required because it was removed from its installed position and modified after testing was completed.« less

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2012-05-23

... to Rule 2.11 That Establish the Authority To Cancel Orders and Describe the Operation of an Error... routing broker-dealer, Direct Edge ECN LLC d/b/a DE Route (``DE Route'') to cancel orders if and when a... Center \\5\\ that causes EDGX or DE Route to cancel orders, if the Exchange or DE Route determines that...

77 FR 30562 - Self-Regulatory Organizations; EDGA Exchange, Inc.; Order Approving a Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-23

... to Rule 2.11 That Establish the Authority To Cancel Orders and Describe the Operation of an Error... and its routing broker-dealer, Direct Edge ECN LLC d/b/a DE Route (``DE Route'') to cancel orders if... Center \\5\\ that causes EDGA or DE Route to cancel orders, if the Exchange or DE Route determines that...

Numerical simulation of internal and near-nozzle flow of a gasoline direct injection fuel injector

NASA Astrophysics Data System (ADS)

Saha, Kaushik; Som, Sibendu; Battistoni, Michele; Li, Yanheng; Quan, Shaoping; Senecal, Peter Kelly

2015-12-01

A numerical study of two-phase flow inside the nozzle holes and the issuing spray jets for a multi-hole direct injection gasoline injector has been presented in this work. The injector geometry is representative of the Spray G nozzle, an eight-hole counterbore injector, from, the Engine Combustion Network (ECN). Simulations have been carried out for the fixed needle lift. Effects of turbulence, compressibility and, non-condensable gases have been considered in this work. Standard k—ɛ turbulence model has been used to model the turbulence. Homogeneous Relaxation Model (HRM) coupled with Volume of Fluid (VOF) approach has been utilized to capture the phase change phenomena inside and outside the injector nozzle. Three different boundary conditions for the outlet domain have been imposed to examine non-flashing and evaporative, non-flashing and non-evaporative, and flashing conditions. Inside the nozzle holes mild cavitation-like and in the near-nozzle region flash boiling phenomena have been predicted in this study when liquid fuel is subjected to superheated ambiance. Noticeable hole to hole variation has been also observed in terms of mass flow rates for all the holes under both flashing and non-flashing conditions.

ECN-15662

NASA Image and Video Library

1981-05-21

The Dryden C-140 JetStar during testing of advanced propfan designs. Dryden conducted flight research in 1981-1982 on several designs. The technology was developed under the direction of the Lewis Research Center (today the Glenn Research Center, Cleveland, OH) under the Advanced Turboprop Program. Under that program, Langley Research Center in Virginia oversaw work on accoustics and noise reduction. These efforts were intended to develop a high-speed and fuel-efficient turboprop system.

ECN-14283

NASA Image and Video Library

1980-12-30

The Highly Maneuverable Aircraft Technology (HiMAT) research vehicle is shown here mated to a wing pylon on NASA’s B-52 mothership aircraft. The HiMAT was a technology demonstrator to test structures and configurations for advanced fighter concepts. Over the course of more than 40 years, the B-52 proved a valuable workhorse for NASA’s Dryden Flight Research Center (under various names), launching a wide variety of vehicles and conducting numerous other research flights.

Aircraft integrated design and analysis: A classroom experience

NASA Technical Reports Server (NTRS)

1988-01-01

AAE 451 is the capstone course required of all senior undergraduates in the School of Aeronautics and Astronautics at Purdue University. During the past year the first steps of a long evolutionary process were taken to change the content and expectations of this course. These changes are the result of the availability of advanced computational capabilities and sophisticated electronic media availability at Purdue. This presentation will describe both the long range objectives and this year's experience using the High Speed Commercial Transport (HSCT) design, the AIAA Long Duration Aircraft design and a Remotely Piloted Vehicle (RPV) design proposal as project objectives. The central goal of these efforts was to provide a user-friendly, computer-software-based, environment to supplement traditional design course methodology. The Purdue University Computer Center (PUCC), the Engineering Computer Network (ECN), and stand-alone PC's were used for this development. This year's accomplishments centered primarily on aerodynamics software obtained from the NASA Langley Research Center and its integration into the classroom. Word processor capability for oral and written work and computer graphics were also blended into the course. A total of 10 HSCT designs were generated, ranging from twin-fuselage and forward-swept wing aircraft, to the more traditional delta and double-delta wing aircraft. Four Long Duration Aircraft designs were submitted, together with one RPV design tailored for photographic surveillance. Supporting these activities were three video satellite lectures beamed from NASA/Langley to Purdue. These lectures covered diverse areas such as an overview of HSCT design, supersonic-aircraft stability and control, and optimization of aircraft performance. Plans for next year's effort will be reviewed, including dedicated computer workstation utilization, remote satellite lectures, and university/industrial cooperative efforts.

ECN-1289

NASA Image and Video Library

1966-05-27

The HL-10, seen here parked on the ramp at NASA's Flight Research Center in 1966, had a radically different shape from that of the M2-F2/F3. While the M2s were flat on top and had rounded undersides (giving them a bathtub shape), the HL-10 had a flat lower surface and a rounded top. Both shapes provided lift without wings, however. This photo was taken before the HL-10's fins were modified.

Defense Logistics Agency Computer-Aided Acquisition and Logistics Support Security Measures

DTIC Science & Technology

1989-09-29

sopisit ftre a nduate eiromensweaonsyte dt i vaiou mdi, nfrrngcls- having security features commensurate with today’s weapon system data in various media ...sections, ministrator that has completed an accredited three areas of improvement in security emphasis are APscrt orebfr htst a ecn deemed appropriate...May 1989, been in a hardcopy media and in accordance with Washington, D.C. specific contract clauses and FAR/DFAR. Through CALS, the Government shall

EDITORIAL: Instrumentation and Methods for Neutron Scattering—papers from the 4th European Conference on Neutron Scattering in Lund, Sweden, June 2007

NASA Astrophysics Data System (ADS)

Rennie, Adrian R.

2008-03-01

Neutron scattering is used as a tool to study problems in disciplines that include chemistry, materials science, biology and condensed matter physics as well as problems from neighbouring disciplines such as geology, environmental sciences and archaeology. Equipment for these studies is found at laboratories with research reactors or spallation neutron sources and there are many recent or current developments with new instruments and even entirely new facilities such as the Spallation Neutron Source at Oak Ridge, USA, the OPAL reactor at Lucas Heights, Australia and the second target station at the ISIS facility in the UK. Design and optimization of the instruments at these facilities involves work with many research laboratories and groups in universities. Every four years the European Conference on Neutron Scattering (ECNS) brings together both the specialists in neutron instrumentation and the community of users (in intervening years there are International and American conferences). In June 2007 about 700 delegates came to the 4th ECNS that was held in Lund, Sweden. There were more than 600 presentations as talks and posters. The opportunity to publish papers in Measurement Science and Technology that relate to neutron scattering instrumentation and method development was offered to the participants, and the papers that follow describe some of the recent activity in this field. Accounts of work on condensed matter science and the applications of neutron scattering appear separately in Journal of Physics: Condensed Matter. There are, of course, many features of neutron instrumentation that are specific to this particular field of measurement. However, there are also many elements of apparatus and experiment design that can usefully be shared with a broader community. It is hoped that this issue with papers from ECNS will find a broad community of interest. Apart from descriptions of overall design of diffractometers and spectrometers there are accounts of new components such as detectors, polarizers, focusing devices and sample environments. The organizers and participants are extremely grateful to numerous sponsors that helped to make the conference a great success. An equal debt of gratitude is due to the Institute of Physics and the editorial and publishing staff for agreeing to publish these papers and organizing the refereeing and editorial process efficiently and promptly in a friendly way.

A Study of Styrene-Butadiene Rubber Blends as Improved Flame Agents

DTIC Science & Technology

1976-06-01

results of air gun tests. Thus, both elasticity and viscosity must be considered when DD I JAN 7 1473 EDITION OF I NOV 63 IS OBSOLETE UNCLASSIFIED sECURITy...L.EGEND!~ 23.9’ C 0~ 1:? 100 >.80 I.. 20 ini Sha at)sc Fiue2. Prcn eoyof2-ecnSR4/0a Vaiu aisa 38 227 I LI I : hi Ilii Al 01 100 130 6n0 40- Shear Rate

ECN-2478

NASA Image and Video Library

1970-08-09

The C-140 JetStar was reconfigured as the General Purpose Airborne Simulator (GPAS) to simulate the flight characteristics of other aircraft. The JetStar was used for research for supersonic transports, general aviation aircraft, and as a training support aircraft for the Space Shuttle Approach and Landing tests at Dryden Flight Research Center (under different names) at Edwards, CA, in 1977. One of the engineers on the GPAS program was Ken Szalai, who later became Dryden's director from 1990 to August 1998.

Synergic Interaction of Rifaximin and Mutaflor (Escherichia coli Nissle 1917) in the Treatment of Acetic Acid-Induced Colitis in Rats.

PubMed

Dembiński, Artur; Warzecha, Zygmunt; Ceranowicz, Piotr; Dembiński, Marcin; Cieszkowski, Jakub; Gosiewski, Tomasz; Bulanda, Małgorzata; Kuśnierz-Cabala, Beata; Gałązka, Krystyna; Konturek, Peter Christopher

2016-01-01

Background. Inflammatory bowel disease results from the dysregulation of immune response to environmental and microbial agents in genetically susceptible individuals. The aim of the present study was to examine the effect of rifaximin and/or Mutaflor (Escherichia coli Nissle 1917, EcN) administration on the healing of acetic acid-induced colitis. Methods. Colitis was induced in male Wistar rats by rectal enema with 3.5% acetic acid solution. Rifaximin (50 mg/kg/dose) and/or Mutaflor (10(9) CFU/dose) were given intragastrically once a day. The severity of colitis was assessed at the 8th day after induction of inflammation. Results. Treatment with rifaximin significantly accelerated the healing of colonic damage. This effect was associated with significant reversion of the acetic acid-evoked decrease in mucosal blood flow and DNA synthesis. Moreover, administration of rifaximin significantly reduced concentration of proinflammatory TNF-α and activity of myeloperoxidase in colonic mucosa. Mutaflor given alone was without significant effect on activity of colitis. In contrast, Mutaflor given in combination with rifaximin significantly enhanced therapeutic effect of rifaximin. Moreover, Mutaflor led to settle of the colon by EcN and this effect was augmented by pretreatment with rifaximin. Conclusion. Rifaximin and Mutaflor exhibit synergic anti-inflammatory and therapeutic effect in acetic acid-induced colitis in rats.

Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969-2012)

NASA Astrophysics Data System (ADS)

Kumar, Naresh; Jaswal, A. K.; Mohapatra, M.; Kore, P. A.

2017-08-01

Spatial and temporal variations in summer and winter extreme temperature indices are studied by using daily maximum and minimum temperatures data from 227 surface meteorological stations well distributed over India for the period 1969-2012. For this purpose, time series for six extreme temperature indices namely, hot days (HD), very hot days (VHD), extremely hot days (EHD), cold nights (CN), very cold nights (VCN), and extremely cold nights (ECN) are calculated for all the stations. In addition, time series for mean extreme temperature indices of summer and winter seasons are also analyzed. Study reveals high variability in spatial distribution of threshold temperatures of extreme temperature indices over the country. In general, increasing trends are observed in summer hot days indices and decreasing trends in winter cold night indices over most parts of the country. The results obtained in this study indicate warming in summer maximum and winter minimum temperatures over India. Averaged over India, trends in summer hot days indices HD, VHD, and EHD are significantly increasing (+1.0, +0.64, and +0.32 days/decade, respectively) and winter cold night indices CN, VCN, and ECN are significantly decreasing (-0.93, -0.47, and -0.15 days/decade, respectively). Also, it is observed that the impact of extreme temperature is higher along the west coast for summer and east coast for winter.

Aircraft integrated design and analysis: A classroom experience

NASA Technical Reports Server (NTRS)

Weisshaar, Terrence A.

1989-01-01

AAE 451 is the capstone course required of all senior undergraduates in the School of Aeronautics and Astronautics at Purdue University. During the past year the first steps of a long evolutionary process were taken to change the content and expectations of this course. These changes are the result of the availability of advanced computational capabilities and sophisticated electronic media availability at Purdue. This presentation will describe both the long range objectives and this year's experience using the High Speed Commercial Transport design, the AIAA Long Duration Aircraft design and RPV design proposal as project objectives. The central goal of these efforts is to provide a user-friendly, computer-software-based environment to supplement traditional design course methodology. The Purdue University Computer Center (PUCC), the Engineering Computer Network (ECN) and stand-alone PC's are being used for this development. This year's accomplishments center primarily on aerodynamics software obtained from NASA/Langley and its integration into the classroom. Word processor capability for oral and written work and computer graphics were also blended into the course. A total of ten HSCT designs were generated, ranging from twin-fuselage aircraft, forward swept wing aircraft to the more traditional delta and double-delta wing aircraft. Four Long Duration Aircraft designs were submitted, together with one RPV design tailored for photographic surveillance.

Spatial and Temporal EEG-fMRI Changes During Preictal and Postictal Phases in a Patient With Posttraumatic Epilepsy.

PubMed

Storti, Silvia F; Del Felice, Alessandra; Formaggio, Emanuela; Boscolo Galazzo, Ilaria; Bongiovanni, Luigi G; Cerini, Roberto; Fiaschi, Antonio; Manganotti, Paolo

2015-07-01

The combined use of electroencephalography (EEG) and functional magnetic resonance imaging (EEG-fMRI) in epilepsy allows the noninvasive hemodynamic characterization of epileptic discharge-related neuronal activations. The aim of this study was to investigate pathophysiologic mechanisms underlying epileptic activity by exploring the spatial and temporal distribution of fMRI signal modifications during seizure in a single patient with posttraumatic epilepsy. EEG and fMRI data were acquired during two scanning sessions: a spontaneous critical episode was observed during the first, and interictal events were recorded during the second. The EEG-fMRI data were analyzed using the general linear model (GLM). Blood oxygenation level-dependent (BOLD) localization derived from the preictal and artifact-free postictal phase was concordant with the BOLD localization of the interictal epileptiform discharges identified in the second session, pointing to a left perilesional mesiofrontal area. Of note, BOLD signal modifications were already visible several seconds before seizure onset. In brief, BOLD activations from the preictal, postictal, and interictal epileptiform discharge analysis appear to be concordant with the clinically driven localization hypothesis, whereas a widespread network of activations is detected during the ictal phase in a partial seizure. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Internal and near nozzle measurements of Engine Combustion Network “Spray G” gasoline direct injectors

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

Duke, Daniel J.; Kastengren, Alan L.; Matusik, Katarzyna E.

Gasoline direct injection (GDI) sprays are complex multiphase flows. When compared to multi-hole diesel sprays, the plumes are closely spaced, and the sprays are more likely to interact. The effects of multi-jet interaction on entrainment and spray targeting can be influenced by small variations in the mass fluxes from the holes, which in turn depend on transients in the needle movement and small-scale details of the internal geometry. In this paper, we present a comprehensive overview of a multi-institutional effort to experimentally characterize the internal geometry and near-nozzle flow of the Engine Combustion Network (ECN) Spray G gasoline injector. Inmore » order to develop a complete picture of the near-nozzle flow, a standardized setup was shared between facilities. A wide range of techniques were employed, including both X-ray and visible-light diagnostics. The novel aspects of this work include both new experimental measurements, and a comparison of the results across different techniques and facilities. The breadth and depth of the data reveal phenomena which were not apparent from analysis of the individual data sets. We show that plume-to-plume variations in the mass fluxes from the holes can cause large-scale asymmetries in the entrainment field and spray structure. Both internal flow transients and small-scale geometric features can have an effect on the external flow. The sharp turning angle of the flow into the holes also causes an inward vectoring of the plumes relative to the hole drill angle, which increases with time due to entrainment of gas into a low-pressure region between the plumes. In conclusion, these factors increase the likelihood of spray collapse with longer injection durations.« less

Internal and near nozzle measurements of Engine Combustion Network “Spray G” gasoline direct injectors

DOE PAGES

Duke, Daniel J.; Kastengren, Alan L.; Matusik, Katarzyna E.; ...

2017-07-25

Gasoline direct injection (GDI) sprays are complex multiphase flows. When compared to multi-hole diesel sprays, the plumes are closely spaced, and the sprays are more likely to interact. The effects of multi-jet interaction on entrainment and spray targeting can be influenced by small variations in the mass fluxes from the holes, which in turn depend on transients in the needle movement and small-scale details of the internal geometry. In this paper, we present a comprehensive overview of a multi-institutional effort to experimentally characterize the internal geometry and near-nozzle flow of the Engine Combustion Network (ECN) Spray G gasoline injector. Inmore » order to develop a complete picture of the near-nozzle flow, a standardized setup was shared between facilities. A wide range of techniques were employed, including both X-ray and visible-light diagnostics. The novel aspects of this work include both new experimental measurements, and a comparison of the results across different techniques and facilities. The breadth and depth of the data reveal phenomena which were not apparent from analysis of the individual data sets. We show that plume-to-plume variations in the mass fluxes from the holes can cause large-scale asymmetries in the entrainment field and spray structure. Both internal flow transients and small-scale geometric features can have an effect on the external flow. The sharp turning angle of the flow into the holes also causes an inward vectoring of the plumes relative to the hole drill angle, which increases with time due to entrainment of gas into a low-pressure region between the plumes. In conclusion, these factors increase the likelihood of spray collapse with longer injection durations.« less

Supercapacitors for the energy management of electric vehicles

NASA Astrophysics Data System (ADS)

Faggioli, Eugenio; Rena, Piergeorgio; Danel, Veronique; Andrieu, X.; Mallant, Ronald; Kahlen, Hans

The integration of the on-board energy source of an electrically propelled vehicle with a supercapacitor bank (SB) as a peak power unit, can lead to substantial benefits in terms of electric vehicle performances, battery life and energy economy. Different architectures may be envisaged, to be chosen according to technical-economical trade-off. A research activity, supported by the European Community in the frame of the Joule III program and titled `Development of Supercapacitors for Electric Vehicles' (contract JOE3-CT95-0001), has been in progress since the beginning of 1996. The partners involved are SAFT (project leader), Alcatel Alsthom Research (France), Centro Ricerche Fiat (Italy), University of Kaiserslautern (Germany), Danionics (DK) and ECN (Netherlands). Its objective is to develop a SB and its electronic control and to integrate them in two different full-scale traction systems, supplied, respectively, by sealed lead traction batteries and by a fuel cell system. Through the bench tests, it will be possible to evaluate the impact of the SB on both traction systems. In this paper, a project overview will be given; the power management strategy principles, the supercapacitor's control electronic devices, the system's architecture and the supercapacitor's requirements on the base of the simulation results, will be examined.

Reinventing the PN Junction: Dimensionality Effects on Tunneling Switches

DTIC Science & Technology

2012-05-11

Figure 4.7. Finally we need to define the band tail density of states:    > < = −− Vp qVEE Vp p EEe EE ED OVp , ,1 )( /)( (4.3.10...Cn qVEE Cn n EEe EE ED OCn , ,1 )( /)( (4.3.11) Here EVp is the valence band edge on the p side and ECn is the conduction band...semiconductor will occur at the oxide semiconductor interface and is given by the boundary condition SSOXOX EE  εε = . This means that the maximum

The `advanced DIR-MCFC development' project, an overview

NASA Astrophysics Data System (ADS)

Kortbeek, P. J.; Ottervanger, R.

An overview is given of the approach and mid-term status of the joint European `Advanced DIR-MCFC Development' project, in which BCN, BG plc, GDF, ECN, Stork, Schelde and Sydkraft co-operate. Hospitals are identified as an attractive initial market for cogeneration direct internal reforming-molten carbonate fuel cell (DIR-MCFC) systems in the size of 400 kWe. Innovative system and stack design concepts are being developed for this application. The `SMARTER' system, based on DIR stacks, combines high electric efficiency and a wide operational window with optimal system simplicity and low cost.

Geautomatiseerde Verwerking van Militaire berichten Volgens ADatP-3 (Automated Processing of Military Messages According to ADatP-3)

DTIC Science & Technology

1992-06-01

ATCCIS beoogt juist dat te bereiken door te werken aan ecn informatie model en een data element dictionary. TNO-rapport Pagina 9 Binnen bet C2...en distributie 44 4.3.2 Interface met de gebruiker 45 4.3.3 Interface met dc operationcle database 46 TNO-rapport Pagina 11 4.3.3.1 Interpretatie...die bezig zijn met het ontwikkelen en implementeren van berichtformaten. Deel I van de publicatie bevat de beschrijving van FORMETS, delen 11 , I11 en

Generation and validation of oxygenated volatile organic carbon standards for the 1995 Southern Oxidants Study Nashville Intensive

NASA Astrophysics Data System (ADS)

Apel, E. C.; Calvert, J. G.; Greenberg, J. P.; Riemer, D.; Zika, R.; Kleindienst, T. E.; Lonneman, W. A.; Fung, K.; Fujita, E.

1998-09-01

Two volatile organic compound (VOC) mixtures were made available and utilized for the calibration of instruments and intercomparison exercises at the Youth, Inc. (YI) site during the Southern Oxidants Study Nashville Intensive. Cylinder 1, made by Scott-Marrin, Inc., contained 14 components (3 nonmethane hydrocarbons (NMHCs) and 11 oxygen-containing VOCs (OVOCs)) and is referred to as OVOCl. Cylinder 2, made at the National Center for Atmospheric Research (NCAR), contained 4 components (one NMHC and three OVOCs) and is referred to as OVOC2. The mixtures were not prepared by either laboratory as primary standards but significant effort was applied to validate their concentrations by several different laboratories using several different techniques. The mixtures were prepared in high-pressure cylinders in the parts per million by volume (ppmv) range using calibrated syringe methods. Gas Chromatographic (GC) and 2,4-dinitrophenylhydrazine (DNPH) cartridge/high-pressure liquid Chromatographic (HPLC) systems were utilized in the calibration of the cylinders. GC detectors included the flame ionization detector (FID) and atomic emission detector (AED). Results obtained with the GC/FID systems for OVOCs were adjusted in terms of the effective carbon number (ECN), obtained from literature values, to correct for the reduced response of the FID for compounds containing oxygen, relative to compounds containing only carbon and hydrogen. Cylinder concentrations were derived and compared based on the ECN-adjusted FID results, the AED results, and the DNPH cartridge results. The various methods employed agreed to within approximately 15%. Both cylinders were stable (±4%) over a period of 2 years.

Comparison of gas chromatography-combustion-mass spectrometry and gas chromatography-flame ionization detector for the determination of fatty acid methyl esters in biodiesel without specific standards.

PubMed

Sobrado, Laura Alonso; Freije-Carrelo, Laura; Moldovan, Mariella; Encinar, Jorge Ruiz; Alonso, J Ignacio García

2016-07-29

GC-FID has been effectively used as a universal quantification technique for volatile organic compounds for a long time. In most cases, the use of the ECN allows for quantification by GC-FID without external calibration using only the response of a single internal standard. In this paper we compare the performance characteristics of GC-FID with those of post-column (13)C Isotope Dilution GC-Combustion-MS for the absolute quantification of organic compounds without the need for individual standards. For this comparison we have selected the quantification of FAMEs in biodiesel. The selection of the right internal standard was critical for GC-FID even when ECN were considered. On the other hand, the nature of the internal standard was not relevant when GC-Combustion-MS was employed. The proposed method was validated with the analysis of the certified reference material SRM 2772 and comparative data was obtained on real biodiesel samples. The analysis of the SRM 2772 biodiesel provided recoveries in the range 100.6-103.5% and 96.4-103.6% for GC-combustion-MS and GC-FID, respectively. The detection limit for GC-combustion-MS was found to be 4.2ng compound/g of injected sample. In conclusion, the quantitative performance of GC-Combustion-MS compared satisfactorily with that of GC-FID constituting a viable alternative for the quantification of organic compounds without the need for individual standards. Copyright © 2016 Elsevier B.V. All rights reserved.

Emissions reduction scenarios in the Argentinean Energy Sector

DOE PAGES

Di Sbroiavacca, Nicolás; Nadal, Gustavo; Lallana, Francisco; ...

2016-04-14

Here in this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO 2 emission savings of the energy sector in Argentina over the 2010-2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic costmore » of 22.8 billion US$(2005) to 2050 is expected, resulting in a 16% reduction in GHG emissions compared to a business-as-usual scenario. These measures also bring economic co-benefits, such as a reduction of energy imports improving the balance of trade. A Low CO 2 price scenario in LEAP results in the replacement of coal by nuclear and wind energy in electricity expansion. A High CO 2 price leverages additional investments in hydropower. An emission cap scenario (2050 emissions 20% lower than 2010 emissions) is feasible by including such measures as CCS and Bio CCS, but at a significant cost. By way of cross-model comparison with the TIAM-ECN and GCAM global integrated assessment models, significant variation in projected emissions reductions in the carbon price scenarios was observed, which illustrates the inherent uncertainties associated with such long-term projections. These models predict approximately 37% and 94% reductions under the High CO 2 price scenario, respectively. By comparison, the LEAP model, using an approach based on the assessment of a limited set of mitigation options, predicts a 11.3% reduction under the ‘high’ carbon tax. The main reasons for this difference are differences in assumptions about technology cost and availability, CO 2 storage capacity, and the ability to import bioenergy. In terms of technology pathways, the models agree that fossil fuels, in particular natural gas, will remain an important part of the electricity mix in the core baseline scenario. Finally, according to the models there is agreement that the introduction of a carbon price will lead to a decline in absolute and relative shares of aggregate fossil fuel generation. However, predictions vary as to the extent to which coal, nuclear and renewable energy play a role.« less

Factors Involved in the Persistence of a Shiga Toxin-Producing Escherichia coli O157:H7 Strain in Bovine Feces and Gastro-Intestinal Content

PubMed Central

Segura, Audrey; Auffret, Pauline; Bibbal, Delphine; Bertoni, Marine; Durand, Alexandra; Jubelin, Grégory; Kérourédan, Monique; Brugère, Hubert; Bertin, Yolande; Forano, Evelyne

2018-01-01

Healthy cattle are the primary reservoir for O157:H7 Shiga toxin-producing E. coli responsible for human food-borne infections. Because farm environment acts as a source of cattle contamination, it is important to better understand the factors controlling the persistence of E. coli O157:H7 outside the bovine gut. The E. coli O157:H7 strain MC2, identified as a persistent strain in French farms, possessed the characteristics required to cause human infections and genetic markers associated with clinical O157:H7 isolates. Therefore, the capacity of E. coli MC2 to survive during its transit through the bovine gastro-intestinal tract (GIT) and to respond to stresses potentially encountered in extra-intestinal environments was analyzed. E. coli MC2 survived in rumen fluids, grew in the content of posterior digestive compartments and survived in bovine feces at 15°C predicting a successful transit of the bacteria along the bovine GIT and its persistence outside the bovine intestine. E. coli MC2 possessed the genetic information encoding 14 adherence systems including adhesins with properties related to colonization of the bovine intestine (F9 fimbriae, EhaA and EspP autotransporters, HCP pilus, FdeC adhesin) reflecting the capacity of the bacteria to colonize different segments of the bovine GIT. E. coli MC2 was also a strong biofilm producer when incubated in fecal samples at low temperature and had a greater ability to form biofilms than the bovine commensal E. coli strain BG1. Furthermore, in contrast to BG1, E. coli MC2 responded to temperature stresses by inducing the genes cspA and htrA during its survival in bovine feces at 15°C. E. coli MC2 also activated genes that are part of the GhoT/GhoS, HicA/HicB and EcnB/EcnA toxin/antitoxin systems involved in the response of E. coli to nutrient starvation and chemical stresses. In summary, the large number of colonization factors known to bind to intestinal epithelium and to biotic or abiotic surfaces, the capacity to produce biofilms and to activate stress fitness genes in bovine feces could explain the persistence of E. coli MC2 in the farm environment. PMID:29593666

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

Di Sbroiavacca, Nicolás; Nadal, Gustavo; Lallana, Francisco

Here in this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO 2 emission savings of the energy sector in Argentina over the 2010-2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic costmore » of 22.8 billion US$(2005) to 2050 is expected, resulting in a 16% reduction in GHG emissions compared to a business-as-usual scenario. These measures also bring economic co-benefits, such as a reduction of energy imports improving the balance of trade. A Low CO 2 price scenario in LEAP results in the replacement of coal by nuclear and wind energy in electricity expansion. A High CO 2 price leverages additional investments in hydropower. An emission cap scenario (2050 emissions 20% lower than 2010 emissions) is feasible by including such measures as CCS and Bio CCS, but at a significant cost. By way of cross-model comparison with the TIAM-ECN and GCAM global integrated assessment models, significant variation in projected emissions reductions in the carbon price scenarios was observed, which illustrates the inherent uncertainties associated with such long-term projections. These models predict approximately 37% and 94% reductions under the High CO 2 price scenario, respectively. By comparison, the LEAP model, using an approach based on the assessment of a limited set of mitigation options, predicts a 11.3% reduction under the ‘high’ carbon tax. The main reasons for this difference are differences in assumptions about technology cost and availability, CO 2 storage capacity, and the ability to import bioenergy. In terms of technology pathways, the models agree that fossil fuels, in particular natural gas, will remain an important part of the electricity mix in the core baseline scenario. Finally, according to the models there is agreement that the introduction of a carbon price will lead to a decline in absolute and relative shares of aggregate fossil fuel generation. However, predictions vary as to the extent to which coal, nuclear and renewable energy play a role.« less

Post-Encephalitic Parkinsonism and Sleep Disorder Responsive to Immunological Treatment: A Case Report.

PubMed

Brunetti, Valerio; Testani, Elisa; Iorio, Raffaele; Frisullo, Giovanni; Luigetti, Marco; Di Giuda, Daniela; Marca, Giacomo Della

2016-10-01

We describe a 70-year-old man who, after a viral encephalitis associated with pneumonia, progressively developed a parkinsonism associated with lethargy. Encephalitis manifested with persistent hiccups, seizures and impairment of consciousness. After 2 weeks, the initial neurologic symptoms subsided and the patient progressively developed movement disorders (rigidity and bradykinesia, resistant to L-DOPA), lethargy and behavioral hypersomnia. Magnetic resonance imaging showed thalamic and hippocampal signal abnormalities, immunohistochemistry on a mouse brain substrate revealed serum autoantibodies binding to the brainstem neuropil. Polysomnographic monitoring was consistent with a very severe disruption of sleep: the sleep-wake cycle was fragmented, and the NREM-REM ultradian cycle was irregular. Intravenous immune globulin therapy resulted in the complete reversal of the movement and the sleep disorders. Our observation confirms that parkinsonism and sleep disorders may be consequences of encephalitis, that an immune-mediated pathogenesis is likely, and, consequently, that immunotherapy can be beneficial in these patients. The polysomnographic monitoring suggests that lethargia, rather than a mere hypersomnia, is the result of a combination between sleep disruption and altered motor control. © EEG and Clinical Neuroscience Society (ECNS) 2016.

Electroencephalography and Brain MRI Patterns in Encephalopathy.

PubMed

Wabulya, Angela; Lesser, Ronald P; Llinas, Rafael; Kaplan, Peter W

2016-04-01

Using electroencephalography (EEG) and histology in patients with diffuse encephalopathy, Gloor et al reported that paroxysmal synchronous discharges (PSDs) on EEG required combined cortical gray (CG) and "subcortical" gray (SCG) matter pathology, while polymorphic delta activity (PDA) occurred in patients with white matter pathology. In patients with encephalopathy, we compared EEG findings and magnetic resonance imaging (MRI) to determine if MRI reflected similar pathological EEG correlations. Retrospective case control study of 52 cases with EEG evidence of encephalopathy and 50 controls without evidence of encephalopathy. Review of clinical, EEG and MRI data acquired within 4 days of each other. The most common EEG finding in encephalopathy was background slowing, in 96.1%. We found PSDs in 0% of cases with the combination of CG and SCG abnormalities. Although 13.5% (n=7) had PSDs on EEG; 3 of these had CG and 4 had SCG abnormalities. A total of 73.1% (38/52) had white matter abnormalities-of these 28.9% (11/38) had PDA. PSDs were found with either CG or "SCG" MRI abnormalities and did not require a combination of the two. In agreement with Gloor et al, PDA occurred with white matter MRI abnormalities in the absence of gray matter abnormalities. © EEG and Clinical Neuroscience Society (ECNS) 2015.

LORETA Neurofeedback in the Precuneus: Operant Conditioning in Basic Mechanisms of Self-Regulation.

PubMed

Cannon, Rex L; Baldwin, Debora R; Diloreto, Dominic J; Phillips, Sherman T; Shaw, Tiffany L; Levy, Jacob J

2014-10-01

Low-resolution brain electomagnetic tomography (LORETA) neurofeedback provides a mechanism to influence the electrical activity of the brain in intracranial space. The aim of this study was to determine the effects of LORETA neurofeedback (LNFB) in the precuneus as a mechanism for improving self-regulation in controls and a heterogeneous diagnostic group (DX). Thirteen participants completed between 10 and 20 sessions of LNFB training in a 3-voxel cluster in the left precuneus. The participants included 5 nonclinical university students, and 8 adults with heterogeneous psychiatric diagnoses. We assessed the effects of LNFB with neurophysiological measures as well as pre- and post-Personality Assessment Inventory (PAI) subscales and selected subtests from the Delis-Kaplan Executive Function System (DKEFS). There was a significant total relative power increase at the precuneus for baseline contrasts for the control group. The DX group did not reach significant levels. All participants showed improvements in executive functions and tended to report significantly less psychopathology. The basic neural mechanisms of self-regulation are poorly understood. The data obtained in this study demonstrate that LNFB in a heterogeneous population enhances executive functions while concordantly decreasing endorsement of psychological symptoms. The alpha frequency in the brain may represent integrative functioning relative to operant efficiency and self-regulatory mechanisms. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Quantitative EEG of Rapid-Eye-Movement Sleep: A Marker of Amnestic Mild Cognitive Impairment.

PubMed

Brayet, Pauline; Petit, Dominique; Frauscher, Birgit; Gagnon, Jean-François; Gosselin, Nadia; Gagnon, Katia; Rouleau, Isabelle; Montplaisir, Jacques

2016-04-01

The basal forebrain cholinergic system, which is impaired in early Alzheimer's disease, is more crucial for the activation of rapid-eye-movement (REM) sleep electroencephalogram (EEG) than it is for wakefulness. Quantitative EEG from REM sleep might thus provide an earlier and more accurate marker of the development of Alzheimer's disease in subjects with mild cognitive impairment (MCI) subjects than that from wakefulness. To assess the superiority of the REM sleep EEG as a screening tool for preclinical Alzheimer's disease, 22 subjects with amnestic MCI (a-MCI; 63.9±7.7 years), 10 subjects with nonamnestic MCI (na-MCI; 64.1±4.5 years) and 32 controls (63.7±6.6 years) participated in the study. Spectral analyses of the waking EEG and REM sleep EEG were performed and the [(delta+theta)/(alpha+beta)] ratio was used to assess between-group differences in EEG slowing. The a-MCI subgroup showed EEG slowing in frontal lateral regions compared to both na-MCI and control groups. This EEG slowing was present in wakefulness (compared to controls) but was much more prominent in REM sleep. Moreover, the comparison between amnestic and nonamnestic subjects was found significant only for the REM sleep EEG. There was no difference in EEG power ratio between na-MCI and controls for any of the 7 cortical regions studied. These findings demonstrate the superiority of the REM sleep EEG in the discrimination between a-MCI and both na-MCI and control subjects. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Probiotic E. coli Nissle 1917 biofilms on silicone substrates for bacterial interference against pathogen colonization.

PubMed

Chen, Quan; Zhu, Zhiling; Wang, Jun; Lopez, Analette I; Li, Siheng; Kumar, Amit; Yu, Fei; Chen, Haoqing; Cai, Chengzhi; Zhang, Lijuan

2017-03-01

Bacterial interference is an alternative strategy to fight against device-associated bacterial infections. Pursuing this strategy, a non-pathogenic bacterial biofilm is used as a live, protective barrier to fence off pathogen colonization. In this work, biofilms formed by probiotic Escherichia coli strain Nissle 1917 (EcN) are investigated for their potential for long-term bacterial interference against infections associated with silicone-based urinary catheters and indwelling catheters used in the digestive system, such as feeding tubes and voice prostheses. We have shown that EcN can form stable biofilms on silicone substrates, particularly those modified with a biphenyl mannoside derivative. These biofilms greatly reduced the colonization by pathogenic Enterococcus faecalis in Lysogeny broth (LB) for 11days. Bacterial interference is an alternative strategy to fight against device-associated bacterial infections. Pursuing this strategy, we use non-pathogenic bacteria to form a biofilm that serves as a live, protective barrier against pathogen colonization. Herein, we report the first use of preformed probiotic E. coli Nissle 1917 biofilms on the mannoside-presenting silicone substrates to prevent pathogen colonization. The biofilms serve as a live, protective barrier to fence off the pathogens, whereas current antimicrobial/antifouling coatings are subjected to gradual coverage by the biomass from the rapidly growing pathogens in a high-nutrient environment. It should be noted that E. coli Nissle 1917 is commercially available and has been used in many clinical trials. We also demonstrated that this probiotic strain performed significantly better than the non-commercial, genetically modified E. coli strain that we previously reported. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Modeling of internal and near-nozzle flow for a GDI fuel injector

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

Saha, Kaushik; Som, Sibendu; Battistoni, Michele

A numerical study of two-phase flow inside the nozzle holes and the issuing spray jets for a multi-hole direct injection gasoline injector has been presented in this work. The injector geometry is representative of the Spray G nozzle, an eight-hole counterbore injector, from the Engine Combustion Network (ECN). Simulations have been carried out for a fixed needle lift. Effects of turbulence, compressibility and non-condensable gases have been considered in this work. Standard k -ε turbulence model has been used to model the turbulence. Homogeneous Relaxation Model (HRM) coupled with Volume of Fluid (VOF) approach has been utilized to capture themore » phase change phenomena inside and outside the injector nozzle. Three different boundary conditions for the outlet domain have been imposed to examine non-flashing and evaporative, non-flashing and non-evaporative and flashing conditions. Noticeable hole-to-hole variations have been observed in terms of mass flow rates for all the holes under all the operating conditions considered in this study. Inside the nozzle holes mild cavitation-like and in the near-nozzle region flash boiling phenomena have been predicted when liquid fuel is subjected to superheated ambiance. Under favorable conditions considerable flashing has been observed in the near-nozzle regions. An enormous volume is occupied by the gasoline vapor, stantial computational cost. Volume-averaging instead of mass-averaging is observed to be more effective, especially for finer mesh resolutions.« less

Alteration of Duration Mismatch Negativity Induced by Transcranial Magnetic Stimulation Over the Left Parietal Lobe.

PubMed

Oshima, Hirokazu; Shiga, Tetsuya; Niwa, Shin-Ichi; Enomoto, Hiroyuki; Ugawa, Yoshikazu; Yabe, Hirooki

2017-01-01

Mismatch negativity (MMN) is generated by a comparison between an incoming sound and the memory trace of preceding sounds stored in sensory memory without any attention to the sound. N100 (N1) is associated with the afferent response to sound onset and reflects early analysis of stimulus characteristics. MMN generators are present in the temporal and frontal lobe, and N1 generators are present in the temporal lobe. The parietal lobe is involved in MMN generation elicited by a change in duration. The anatomical network connecting these areas, lateralization, and the effect of the side of ear stimulation on MMN remain unknown. Thus, we studied the effects of low-frequency repetitive transcranial magnetic stimulation (rTMS) over the left parietal lobe on MMN and N1 in 10 healthy subjects. Low-frequency rTMS over the left parietal lobe decreased the amplitude of MMN following right ear sound stimulation, but the amplitude was unaffected with left ear sound stimulation. We observed no significant changes in the amplitude of N1 or the latency of MMN or N1. These results suggest that low-frequency rTMS over the left parietal lobe modulates the detection of early auditory changes in duration in healthy subjects. Stimulation that is contralateral to the side of the ear experiencing sound may affect the generation of duration MMN more than ipsilateral stimulation. © EEG and Clinical Neuroscience Society (ECNS) 2016.

A compact skeletal mechanism for n -dodecane with optimized semi-global low-temperature chemistry for diesel engine simulations

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

Yao, Tong; Pei, Yuanjiang; Zhong, Bei-Jing

A skeletal mechanism with 54 species and 269 reactions was developed to predict pyrolysis and oxidation of n-dodecane as a diesel fuel surrogate involving both high-temperature (high-T) and low-temperature (low-T) conditions. The skeletal mechanism was developed from a semi-detailed mechanism developed at the University of Southern California (USC). Species and reactions for high-T pyrolysis and oxidation of C5-C12 were reduced by using reaction flow analysis (RFA), isomer lumping, and then merged into a skeletal C0-C4 core to form a high-T sub-mechanism. Species and lumped semi-global reactions for low-T chemistry were then added to the high-T sub-mechanism and a 54-species skeletalmore » mechanism is obtained. The rate parameters of the low-T reactions were tuned against a detailed mechanism by the Lawrence Livermore National Laboratory (LLNL), as well as the Spray A flame experimental data, to improve the prediction of ignition delay at low-T conditions, while the high-T chemistry remained unchanged. The skeletal mechanism was validated for auto-ignition, perfectly stirred reactors (PSR), flow reactors and laminar premixed flames over a wide range of flame conditions. The skeletal mechanism was then employed to simulate three-dimensional turbulent spray flames at compression ignition engine conditions and validated against experimental data from the Engine Combustion Network (ECN).« less

Development of a reduced tri-propylene glycol monomethyl ether– n -hexadecane–poly-aromatic hydrocarbon mechanism and its application for soot prediction

DOE PAGES

Park, Seunghyun; Ra, Youngchul; Reitz, Rolf D.; ...

2016-03-01

A reduced chemical kinetic mechanism for Tri-Propylene Glycol Monomethyl Ether (TPGME) has been developed and applied to computational fluid dynamics (CFD) calculations for predicting combustion and soot formation processes. The reduced TPGME mechanism was combined with a reduced n-hexadecane mechanism and a Poly-Aromatic Hydrocarbon (PAH) mechanism to investigate the effect of fuel oxygenation on combustion and soot emissions. The final version of the TPGME-n-hexadecane-PAH mechanism consists of 144 species and 730 reactions and was validated with experiments in shock tubes as well as in a constant volume spray combustion vessel (CVCV) from the Engine Combustion Network (ECN). The effects ofmore » ambient temperature, varying oxygen content in the tested fuels on ignition delay, spray liftoff length and soot formation under diesel-like conditions were analyzed and addressed using multidimensional reacting flow simulations and the reduced mechanism. Here, the results show that the present reduced mechanism gives reliable predictions of the combustion characteristics and soot formation processes. In the CVCV simulations, two important trends were identified. First, increasing the initial temperature in the CVCV shortens the ignition delay and lift-off length, reduces the fuel-air mixing, thereby increasing the soot levels. Secondly, fuel oxygenation introduces more oxygen into the central region of a fuel jet and reduces residence times of fuel rich area in active soot forming regions, thereby reducing soot levels.« less

Development of a reduced tri-propylene glycol monomethyl ether– n -hexadecane–poly-aromatic hydrocarbon mechanism and its application for soot prediction

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

Park, Seunghyun; Ra, Youngchul; Reitz, Rolf D.

A reduced chemical kinetic mechanism for Tri-Propylene Glycol Monomethyl Ether (TPGME) has been developed and applied to computational fluid dynamics (CFD) calculations for predicting combustion and soot formation processes. The reduced TPGME mechanism was combined with a reduced n-hexadecane mechanism and a Poly-Aromatic Hydrocarbon (PAH) mechanism to investigate the effect of fuel oxygenation on combustion and soot emissions. The final version of the TPGME-n-hexadecane-PAH mechanism consists of 144 species and 730 reactions and was validated with experiments in shock tubes as well as in a constant volume spray combustion vessel (CVCV) from the Engine Combustion Network (ECN). The effects ofmore » ambient temperature, varying oxygen content in the tested fuels on ignition delay, spray liftoff length and soot formation under diesel-like conditions were analyzed and addressed using multidimensional reacting flow simulations and the reduced mechanism. Here, the results show that the present reduced mechanism gives reliable predictions of the combustion characteristics and soot formation processes. In the CVCV simulations, two important trends were identified. First, increasing the initial temperature in the CVCV shortens the ignition delay and lift-off length, reduces the fuel-air mixing, thereby increasing the soot levels. Secondly, fuel oxygenation introduces more oxygen into the central region of a fuel jet and reduces residence times of fuel rich area in active soot forming regions, thereby reducing soot levels.« less

ECN-3945

NASA Image and Video Library

1974-02-21

The General Dynamics TACT/F-111A Aardvark is seen In a banking-turn over the California Mojave desert. This photograph affords a good view of the supercritical wing airfoil shape. Starting in 1971 the NASA Flight Research Center and the Air Force undertook a major research and flight testing program, using F-111A (#63-9778), which would span almost 20 years before completion. Intense interest over the results coming from the NASA F-8 supercritical wing program spurred NASA and the Air Force to modify the General Dynamics F-111A to explore the application of supercritical wing technology to maneuverable military aircraft. This flight program was called Transonic Aircraft Technology (TACT).

ECN-5033

NASA Image and Video Library

1976-01-29

The General Dynamics TACT/F-111A (Serial #63-9778) banks over the Mojave Desert. Note the fully loaded racks of inert pratice bombs which were carried for weapon loads evaluations on the supercritical wing (SCW) that was the main feature of the Transonic Aircraft Technology F-111 research program. Intense interest in the results of the earlier F-8 SCW program spurred NASA and the U.S. Air Force to modify the number 13 F-111A for the TACT program. This aircraft participated in a major research and flight testing program that spanned nearly 20 years, beginning in 1971 at the NASA Flight Research Center at Edwards AFB, California.

P300 Amplitude in Alzheimer's Disease: A Meta-Analysis and Meta-Regression.

PubMed

Hedges, Dawson; Janis, Rebecca; Mickelson, Stephen; Keith, Cierra; Bennett, David; Brown, Bruce L

2016-01-01

Alzheimer's disease accounts for 60% of all dementia. Numerous biomarkers have been developed that can help in making an early diagnosis. The P300 is an event-related potential that may be abnormal in Alzheimer's disease. Given the possible association between P300 amplitude and Alzheimer's disease and the need for biomarkers in early Alzheimer's disease, the main purpose of this meta-analysis and meta-regression was to characterize P300 amplitude in probable Alzheimer's disease compared to healthy controls. Using online search engines, we identified peer-reviewed articles containing amplitude measures for the P300 in response to a visual or auditory oddball stimulus in subjects with Alzheimer's disease and in a healthy control group and pooled effect sizes for differences in P300 amplitude between Alzheimer's disease and control groups to obtain summary effect sizes. We also used meta-regression to determine whether age, sex, educational attainment, or dementia severity affected the association between P300 amplitude and Alzheimer's disease. Twenty articles containing a total of 646 subjects met inclusion and exclusion criteria. The overall effect size from all electrode locations was 1.079 (95% confidence interval=0.745-1.412, P<.001). The pooled effect sizes for the Cz, Fz, and Pz locations were 1.226 (P<.001), 0.724 (P=.0007), and 1.430 (P<.001), respectively. Meta-regression showed an association between amplitude and educational attainment, but no association between amplitude and age, sex, and dementia severity. In conclusion, P300 amplitude is smaller in subjects with Alzheimer's disease than in healthy controls. © EEG and Clinical Neuroscience Society (ECNS) 2014.

ECN-3931

NASA Image and Video Library

1974-01-28

This photograph shows a modified General Dynamics TACT/F-111A Aardvaark with supercritical wings installed. The aircraft, with flaps and landing gear down, is in a decending turn over Rogers Dry Lakebed at Edwards Air Force Base. Starting in 1971 the NASA Flight Research Center and the Air Force undertook a major research and flight testing program, using F-111A (#63-9778), which would span almost 20 years before completion. Intense interest over the results coming from the NASA F-8 supercritical wing program spurred NASA and the Air Force to modify the General Dynamics-Convair F-111A to explore the application of supercritical wing technology to maneuverable military aircraft. This flight program was called Transonic Aircraft Technology (TACT).

The effect of heat treatment on the corrosion resistance of 440C stainless steel in 20% HNO3 + 2.5% Na2Cr2O7 solution

NASA Astrophysics Data System (ADS)

Savas, Terence P.; Wang, Allen Yi-Lan; Earthman, James C.

2003-04-01

The effect of heat treatment on the corrosion resistance of 440C stainless steel was investigated in a 20% HNO3 + 2.5% Na2Cr2O7 solution using electrochemical noise (ECN) measurements, electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM) examinations. The noise resistance ( Rn), which has been found to be inversely related to the localized corrosion rate, was measured to be 5.7E + 08 Ω-cm2, 4.2E + 08 Ω-cm2, and 3.7E + 04 Ω-cm2 for the oil-quenched, air-quenched, and vacuum furnace cooled (VFC) samples, respectively, after 1200 s exposures. The Rn for all heat treat conditions stabilized within a range of 1.0E + 07 Ω-cm2 to 3.2E + 08 Ω-cm2 after 2 h exposures. The EIS response showed a polarization resistance ( R p) on the order of 6.6E + 04 Ω-cm2, 5.3E + 04 Ω-cm2, and 1.1E + 04 Ω-cm2 for the oil-quenched, air-quenched, and VFC samples, respectively, after 2 h exposures. The EIS data are in good agreement with ECN data and indicate that after longer exposures, general corrosion mechanisms dominate and the corrosion rates are comparable. SEM examinations of specimens subjected to 1200 s exposures revealed that severity of pitting and intergranular corrosion damage was consistent with trends in the Rn data. Specifically, the electrochemical noise data as well as SEM examinations of specimens revealed a higher localized corrosion resistance of the hardened specimens during the early stages of passivation. This greater resistance to localized corrosion can be attributed to an increased stability of the natural passive film resulting from a higher concentration of chromium atoms in solution for the martensite phase.

Comparison of Impurities in Charcoal Sorbents Found by Neutron Activation Analysis

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

Doll, Charles G.; Finn, Erin C.; Cantaloub, Michael G.

2013-01-01

Abstract: Neutron activation of gas samples in a reactor often requires a medium to retain sufficient amounts of the gas for analysis. Charcoal is commonly used to adsorb gas and hold it for activation; however, the amount of activated sodium in the charcoal after irradiation swamps most signals of interest. Neutron activation analysis (NAA) was performed on several commonly available charcoal samples in an effort to determine the activation background. The results for several elements, including the dominant sodium element, are reported. It was found that ECN charcoal had the lowest elemental background, containing sodium at 2.65 ± 0.05 ppm,more » as well as trace levels of copper and tungsten.« less

Super-Refractory Status Epilepticus: Report of a Case and Review of the Literature.

PubMed

Lapenta, Leonardo; Frisullo, Giovanni; Vollono, Catello; Brunetti, Valerio; Giannantoni, Nadia Mariagrazia; Sandroni, Claudio; Di Lella, Giuseppe; Della Marca, Giacomo

2015-10-01

Super-refractory status epilepticus (SE; ie, SE continuing or recurring despite 24 hours of general anesthesia) is a severe condition with high percentage of mortality and morbidity. Usually, this condition occurs because of serious brain damage; nevertheless, some patients develop super-refractory SE without identifiable etiology. Although not uncommonly encountered in neurointensive care, scientific data on this condition are still lacking in terms of treatment and prognosis. Herein, we report a case of super-refractory SE with recovery after 50 days, despite electroencephalographic (EEG) and magnetic resonance imaging (MRI) signs traditionally related to poor prognosis. A review of the literature on super-refractory SE is also presented. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Soot and Spectral Radiation Modeling in ECN Spray A and in Engines

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

Haworth, Daniel C; Ferreyro-Fernandez, Sebastian; Paul, Chandan

The amount of soot formed in a turbulent combustion system is determined by a complex system of coupled nonlinear chemical and physical processes. Different physical subprocesses can dominate, depending on the hydrodynamic and thermochemical environments. Similarly, the relative importance of reabsorption, spectral radiation properties, and molecular gas radiation versus soot radiation varies with thermochemical conditions, and in ways that are difficult to predict for the highly nonhomogeneous in-cylinder mixtures in engines. Here it is shown that transport and mixing play relatively more important roles as rate-determining processes in soot formation at engine-relevant conditions. It is also shown that molecular gasmore » radiation and spectral radiation properties are important for engine-relevant conditions.« less

Wake and Sleep EEG in Patients With Huntington Disease: An eLORETA Study and Review of the Literature.

PubMed

Piano, Carla; Mazzucchi, Edoardo; Bentivoglio, Anna Rita; Losurdo, Anna; Calandra Buonaura, Giovanna; Imperatori, Claudio; Cortelli, Pietro; Della Marca, Giacomo

2017-01-01

The aim of the study was to evaluate the EEG modifications in patients with Huntington disease (HD) compared with controls, by means of the exact LOw REsolution Tomography (eLORETA) software. We evaluated EEG changes during wake, non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. Moreover, we reviewed the literature concerning EEG modifications in HD. Twenty-three consecutive adult patients affected by HD were enrolled, 14 women and 9 men, mean age was 57.0 ± 12.4 years. Control subjects were healthy volunteers (mean age 58.2 ± 14.6 years). EEG and polygraphic recordings were performed during wake (before sleep) and during sleep. Sources of EEG activities were determined using the eLORETA software. In wake EEG, significant differences between patients and controls were detected in the delta frequency band (threshold T = ±4.606; P < .01) in the Brodmann areas (BAs) 3, 4, and 6 bilaterally. In NREM sleep, HD patients showed increased alpha power (T = ±4.516; P < .01) in BAs 4 and 6 bilaterally; decreased theta power (T = ±4.516; P < .01) in the BAs 23, 29, and 30; and decreased beta power (T = ±4.516; P < .01) in the left BA 30. During REM, HD patients presented decreased theta and alpha power (threshold T = ±4.640; P < .01) in the BAs 23, 29, 30, and 31 bilaterally. In conclusion, EEG data suggest a motor cortex dysfunction during wake and sleep in HD patients, which correlates with the clinical and polysomnographic evidence of increased motor activity during wake and NREM, and nearly absent motor abnormalities in REM. © EEG and Clinical Neuroscience Society (ECNS) 2016.

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

A Case of Hemiabdominal Myoclonus.

PubMed

Nociti, Viviana; Servidei, Serenella; Luigetti, Marco; Iorio, Raffaele; Lo Monaco, Mauro; Mirabella, Massimiliano; Frisullo, Giovanni; Della Marca, Giacomo

2015-10-01

Myoclonus consists of sudden, brief, involuntary jerky muscular contractions. Central and peripheral nervous system lesions are involved in the pathogenesis of this movement disorder. Symptomatic or secondary spinal myoclonus is the most common form. A 68-year-old woman was diagnosed with hemiabdominal spinal myoclonus. Occasional and very mild involuntary repetitive movements of the hemiabdomen began immediately after surgery for uterine cancer. After surgery for laparocele, secondary to the uterine cancer surgery, performed under spinal anesthesia, there was severe worsening of movements. Neuroradiological investigations failed to demonstrate spinal injury, while neurophysiological studies showed impairment of the right central somatosensory pathway. Considering the low resolution of magnetic resonance imaging in the evaluation of thoracic level, we suggest an extensive neurophysiological evaluation in patients with spinal myoclonus. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Multiple indices of soil nitrogen status and temperature regulate microbial C allocation to CO2, substrate choices, and contributions to SOM

NASA Astrophysics Data System (ADS)

Billings, S. A.; Ziegler, S. E.

2012-12-01

The response of microbial resource demand to many environmental variables, including temperature and natural organic and inorganic N variability, remains poorly understood. Furthermore, we do not understand how these variables can influence CO2 release vs. C retention in cell walls, which as microbial necromass can generate long-lived soil organic matter (SOM). We explore microbial resource demand and C retention vs. release in one temperate forest and two boreal forests along a climate gradient. We characterized SOM C:N and inorganic N, extracellular enzyme activity (E), and phospholipid fatty acid (PLFA) concentration and δ13C. Experimental warming permitted us to assess how interactions between soil N status and warming influence resource demand and C flows through microbes in the two boreal soils. For all soils, we used δ13C of respired CO2 and δ13CPLFA to generate indices of C allocation to biomass vs. to respiratory costs (Δ), useful for cross-site comparisons. Decreasing values of Δ indicate a greater proportion of 13C-enriched C allocated to respiration relative to PLFA-C; changes in Δ with warming or N status thus imply that these variables can influence the physiological mechanisms determining the fate of microbial C after it is imported into the cell. We thus were able to assess the influence of soil N status and warming on substrate decay via E, the fate of microbial C from diverse substrates via Δ, and one index of microbial composition relevant to SOM formation [PLFA]. In all soils, E often varied with N status in ways predicted by stoichiometric theory. For example, the ratio of exo-enzymes associated with labile C decay to those linked to organic N decay (EC:N) increased with inorganic N, and EC:N declined as substrate C:N increased. In contrast to measures of decay, all soils exhibited distinct responses of microbial composition and C allocation to N status and warming. In the temperate forest soils, Gram+ bacteria responded positively to organic N availability and Gram- bacteria to inorganic N, while fungi responded positively to declines in both measures of soil N status. In the more northern boreal soils, actinomycete [PLFA] increased with inorganic N, while that of more southern boreal soils increased with substrate C:N; in both boreal soils, Gram+ bacteria increased with temperature. Given that cell walls of these microbes exhibit distinct propensities for forming long-lived SOM, our work illustrates how similar variation in N status and temperature can drive divergent patterns of biomass relevant to SOM formation. Sensitivity of patterns of C allocation to these variables also contrasted between these soils. In the temperate soils, Δ did not vary with soil N status nor with E, implying that microbes' C allocation patterns were not driven N status or by the C's organic precursor. In both boreal soils, Δ declined with warming, and as EC or EC:N increased. Though N status of the boreal soils drove resource demand similarly as in the temperate forest, the fate of boreal microbial C varied with N status and temperature. Because microbial C substrate use varied with warming in the boreal soils, Δ highlights how the fate of microbial C may vary with the identity of its organic precursor, which in turn is influenced by environmental conditions like temperature and soil N status.

Controllability of flow-conservation networks

NASA Astrophysics Data System (ADS)

Zhao, Chen; Zeng, An; Jiang, Rui; Yuan, Zhengzhong; Wang, Wen-Xu

2017-07-01

The ultimate goal of exploring complex networks is to control them. As such, controllability of complex networks has been intensively investigated. Despite recent advances in studying the impact of a network's topology on its controllability, a comprehensive understanding of the synergistic impact of network topology and dynamics on controllability is still lacking. Here, we explore the controllability of flow-conservation networks, trying to identify the minimal number of driver nodes that can guide the network to any desirable state. We develop a method to analyze the controllability on flow-conservation networks based on exact controllability theory, transforming the original analysis on adjacency matrix to Laplacian matrix. With this framework, we systematically investigate the impact of some key factors of networks, including link density, link directionality, and link polarity, on the controllability of these networks. We also obtain the analytical equations by investigating the network's structural properties approximatively and design the efficient tools. Finally, we consider some real networks with flow dynamics, finding that their controllability is significantly different from that predicted by only considering the topology. These findings deepen our understanding of network controllability with flow-conservation dynamics and provide a general framework to incorporate real dynamics in the analysis of network controllability.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

PubMed

Li, Yuhong; Gong, Guanghong; Li, Ni

2018-01-01

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

Controllability of Deterministic Networks with the Identical Degree Sequence

PubMed Central

Ma, Xiujuan; Zhao, Haixing; Wang, Binghong

2015-01-01

Controlling complex network is an essential problem in network science and engineering. Recent advances indicate that the controllability of complex network is dependent on the network's topology. Liu and Barabási, et.al speculated that the degree distribution was one of the most important factors affecting controllability for arbitrary complex directed network with random link weights. In this paper, we analysed the effect of degree distribution to the controllability for the deterministic networks with unweighted and undirected. We introduce a class of deterministic networks with identical degree sequence, called (x,y)-flower. We analysed controllability of the two deterministic networks ((1, 3)-flower and (2, 2)-flower) by exact controllability theory in detail and give accurate results of the minimum number of driver nodes for the two networks. In simulation, we compare the controllability of (x,y)-flower networks. Our results show that the family of (x,y)-flower networks have the same degree sequence, but their controllability is totally different. So the degree distribution itself is not sufficient to characterize the controllability of deterministic networks with unweighted and undirected. PMID:26020920

Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder.

PubMed

Dong, Guangheng; Lin, Xiao; Hu, Yanbo; Xie, Chunming; Du, Xiaoxia

2015-03-17

Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD.

Constrained target controllability of complex networks

NASA Astrophysics Data System (ADS)

Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

2017-06-01

It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

Research on NGN network control technology

NASA Astrophysics Data System (ADS)

Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

2004-04-01

Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

A geometrical approach to control and controllability of nonlinear dynamical networks

PubMed Central

Wang, Le-Zhi; Su, Ri-Qi; Huang, Zi-Gang; Wang, Xiao; Wang, Wen-Xu; Grebogi, Celso; Lai, Ying-Cheng

2016-01-01

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control. PMID:27076273

Optimization of controllability and robustness of complex networks by edge directionality

NASA Astrophysics Data System (ADS)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

Control of Multilayer Networks

PubMed Central

Menichetti, Giulia; Dall’Asta, Luca; Bianconi, Ginestra

2016-01-01

The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on isolated networks, while the vast majority of complex systems are formed by multilayer networks. Here we build a theoretical framework for the linear controllability of multilayer networks by mapping the problem into a combinatorial matching problem. We found that correlating the external signals in the different layers can significantly reduce the multiplex network robustness to node removal, as it can be seen in conjunction with a hybrid phase transition occurring in interacting Poisson networks. Moreover we observe that multilayer networks can stabilize the fully controllable multiplex network configuration that can be stable also when the full controllability of the single network is not stable. PMID:26869210

Practical synchronization on complex dynamical networks via optimal pinning control

NASA Astrophysics Data System (ADS)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Relevance of aerodynamic modelling for load reduction control strategies of two-bladed wind turbines

NASA Astrophysics Data System (ADS)

Luhmann, B.; Cheng, P. W.

2014-06-01

A new load reduction concept is being developed for the two-bladed prototype of the Skywind 3.5MW wind turbine. Due to transport and installation advantages both offshore and in complex terrain two-bladed turbine designs are potentially more cost-effective than comparable three-bladed configurations. A disadvantage of two-bladed wind turbines is the increased fatigue loading, which is a result of asymmetrically distributed rotor forces. The innovative load reduction concept of the Skywind prototype consists of a combination of cyclic pitch control and tumbling rotor kinematics to mitigate periodic structural loading. Aerodynamic design tools must be able to model correctly the advanced dynamics of the rotor. In this paper the impact of the aerodynamic modelling approach is investigated for critical operational modes of a two-bladed wind turbine. Using a lifting line free wake vortex code (FVM) the physical limitations of the classical blade element momentum theory (BEM) can be evaluated. During regular operation vertical shear and yawed inflow are the main contributors to periodic blade load asymmetry. It is shown that the near wake interaction of the blades under such conditions is not fully captured by the correction models of BEM approach. The differing prediction of local induction causes a high fatigue load uncertainty especially for two-bladed turbines. The implementation of both cyclic pitch control and a tumbling rotor can mitigate the fatigue loading by increasing the aerodynamic and structural damping. The influence of the time and space variant vorticity distribution in the near wake is evaluated in detail for different cyclic pitch control functions and tumble dynamics respectively. It is demonstrated that dynamic inflow as well as wake blade interaction have a significant impact on the calculated blade forces and need to be accounted for by the aerodynamic modelling approach. Aeroelastic simulations are carried out using the high fidelity multi body simulation software SIMPACK. The aerodynamic loads are calculated using ECN's AeroModule and NREL's BEM code Aerodynl3.

Structural Controllability of Temporal Networks with a Single Switching Controller

PubMed Central

Yao, Peng; Hou, Bao-Yu; Pan, Yu-Jian; Li, Xiang

2017-01-01

Temporal network, whose topology evolves with time, is an important class of complex networks. Temporal trees of a temporal network describe the necessary edges sustaining the network as well as their active time points. By a switching controller which properly selects its location with time, temporal trees are used to improve the controllability of the network. Therefore, more nodes are controlled within the limited time. Several switching strategies to efficiently select the location of the controller are designed, which are verified with synthetic and empirical temporal networks to achieve better control performance. PMID:28107538

Construction quality assurance report

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

Roscha, V.

1994-09-08

This report provides a summary of the construction quality assurance (CQA) observation and test results, including: The results of the geosynthetic and soil materials conformance testing. The observation and testing results associates with the installation of the soil liners. The observation and testing results associated with the installation of the HDPE geomembrane liner systems. The observation and testing results associated with the installation of the leachate collection and removal systems. The observation and testing results associated with the installation of the working surfaces. The observation and testing results associated with in-plant manufacturing process. Summary of submittal reviews by Golder Constructionmore » Services, Inc. The submittal and certification of the piping material specifications. The observation and verification associated of the Acceptance Test Procedure results of the operational equipment functions. Summary of the ECNs which are incorporated into the project.« less

Network congestion control algorithm based on Actor-Critic reinforcement learning model

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2018-04-01

Aiming at the network congestion control problem, a congestion control algorithm based on Actor-Critic reinforcement learning model is designed. Through the genetic algorithm in the congestion control strategy, the network congestion problems can be better found and prevented. According to Actor-Critic reinforcement learning, the simulation experiment of network congestion control algorithm is designed. The simulation experiments verify that the AQM controller can predict the dynamic characteristics of the network system. Moreover, the learning strategy is adopted to optimize the network performance, and the dropping probability of packets is adaptively adjusted so as to improve the network performance and avoid congestion. Based on the above finding, it is concluded that the network congestion control algorithm based on Actor-Critic reinforcement learning model can effectively avoid the occurrence of TCP network congestion.

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

Effective augmentation of networked systems and enhancing pinning controllability

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-06-01

Controlling dynamics of networked systems to a reference state, known as pinning control, has many applications in science and engineering. In this paper, we introduce a method for effective augmentation of networked systems, while also providing high levels of pinning controllability for the final augmented network. The problem is how to connect a sub-network to an already existing network such that the pinning controllability is maximised. We consider the eigenratio of the augmented Laplacian matrix as a pinning controllability metric, and use graph perturbation theory to approximate the influence of edge addition on the eigenratio. The proposed metric can be effectively used to find the inter-network links connecting the disjoint networks. Also, an efficient link rewiring approach is proposed to further optimise the pinning controllability of the augmented network. We provide numerical simulations on synthetic networks and show that the proposed method is more effective than heuristic ones.

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Control Centrality and Hierarchical Structure in Complex Networks

PubMed Central

Liu, Yang-Yu; Slotine, Jean-Jacques; Barabási, Albert-László

2012-01-01

We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks. PMID:23028542

Multiple network interface core apparatus and method

DOEpatents

Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

2011-04-26

A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

Attack Vulnerability of Network Controllability

PubMed Central

2016-01-01

Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability. PMID:27588941

Attack Vulnerability of Network Controllability.

PubMed

Lu, Zhe-Ming; Li, Xin-Feng

2016-01-01

Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability.

Effect of edge pruning on structural controllability and observability of complex networks

PubMed Central

Mengiste, Simachew Abebe; Aertsen, Ad; Kumar, Arvind

2015-01-01

Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex systems show dynamic changes in their network connectivity, it is important to understand how perturbations in the connectivity affect the controllability of the system. To this end, we studied the control structure of different types of artificial, social and biological neuronal networks (BNN) as their connections were progressively pruned using four different pruning strategies. We show that the BNNs are more similar to scale-free networks than to small-world networks, when comparing the robustness of their control structure to structural perturbations. We introduce a new graph descriptor, ‘the cardinality curve’, to quantify the robustness of the control structure of a network to progressive edge pruning. Knowing the susceptibility of control structures to different pruning methods could help design strategies to destroy the control structures of dangerous networks such as epidemic networks. On the other hand, it could help make useful networks more resistant to edge attacks. PMID:26674854

Effect of correlations on controllability transition in network control

PubMed Central

Nie, Sen; Wang, Xu-Wen; Wang, Bing-Hong; Jiang, Luo-Luo

2016-01-01

The network control problem has recently attracted an increasing amount of attention, owing to concerns including the avoidance of cascading failures of power-grids and the management of ecological networks. It has been proven that numerical control can be achieved if the number of control inputs exceeds a certain transition point. In the present study, we investigate the effect of degree correlation on the numerical controllability in networks whose topological structures are reconstructed from both real and modeling systems, and we find that the transition point of the number of control inputs depends strongly on the degree correlation in both undirected and directed networks with moderately sparse links. More interestingly, the effect of the degree correlation on the transition point cannot be observed in dense networks for numerical controllability, which contrasts with the corresponding result for structural controllability. In particular, for directed random networks and scale-free networks, the influence of the degree correlation is determined by the types of correlations. Our approach provides an understanding of control problems in complex sparse networks. PMID:27063294

Controllability of Surface Water Networks

NASA Astrophysics Data System (ADS)

Riasi, M. Sadegh; Yeghiazarian, Lilit

2017-12-01

To sustainably manage water resources, we must understand how to control complex networked systems. In this paper, we study surface water networks from the perspective of structural controllability, a concept that integrates classical control theory with graph-theoretic formalism. We present structural controllability theory and compute four metrics: full and target controllability, control centrality and control profile (FTCP) that collectively determine the structural boundaries of the system's control space. We use these metrics to answer the following questions: How does the structure of a surface water network affect its controllability? How to efficiently control a preselected subset of the network? Which nodes have the highest control power? What types of topological structures dominate controllability? Finally, we demonstrate the structural controllability theory in the analysis of a wide range of surface water networks, such as tributary, deltaic, and braided river systems.

Control range: a controllability-based index for node significance in directed networks

NASA Astrophysics Data System (ADS)

Wang, Bingbo; Gao, Lin; Gao, Yong

2012-04-01

While a large number of methods for module detection have been developed for undirected networks, it is difficult to adapt them to handle directed networks due to the lack of consensus criteria for measuring the node significance in a directed network. In this paper, we propose a novel structural index, the control range, motivated by recent studies on the structural controllability of large-scale directed networks. The control range of a node quantifies the size of the subnetwork that the node can effectively control. A related index, called the control range similarity, is also introduced to measure the structural similarity between two nodes. When applying the index of control range to several real-world and synthetic directed networks, it is observed that the control range of the nodes is mainly influenced by the network's degree distribution and that nodes with a low degree may have a high control range. We use the index of control range similarity to detect and analyze functional modules in glossary networks and the enzyme-centric network of homo sapiens. Our results, as compared with other approaches to module detection such as modularity optimization algorithm, dynamic algorithm and clique percolation method, indicate that the proposed indices are effective and practical in depicting structural and modular characteristics of sparse directed networks.

Optimization of robustness of interdependent network controllability by redundant design

PubMed Central

2018-01-01

Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy) or DBS (degree based strategy) for node backup and HDF(high degree first) for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability. PMID:29438426

Minimizing communication cost among distributed controllers in software defined networks

NASA Astrophysics Data System (ADS)

Arlimatti, Shivaleela; Elbreiki, Walid; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

2016-08-01

Software Defined Networking (SDN) is a new paradigm to increase the flexibility of today's network by promising for a programmable network. The fundamental idea behind this new architecture is to simplify network complexity by decoupling control plane and data plane of the network devices, and by making the control plane centralized. Recently controllers have distributed to solve the problem of single point of failure, and to increase scalability and flexibility during workload distribution. Even though, controllers are flexible and scalable to accommodate more number of network switches, yet the problem of intercommunication cost between distributed controllers is still challenging issue in the Software Defined Network environment. This paper, aims to fill the gap by proposing a new mechanism, which minimizes intercommunication cost with graph partitioning algorithm, an NP hard problem. The methodology proposed in this paper is, swapping of network elements between controller domains to minimize communication cost by calculating communication gain. The swapping of elements minimizes inter and intra communication cost among network domains. We validate our work with the OMNeT++ simulation environment tool. Simulation results show that the proposed mechanism minimizes the inter domain communication cost among controllers compared to traditional distributed controllers.

Neural networks for aircraft control

NASA Technical Reports Server (NTRS)

Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Stabilization of model-based networked control systems

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

Miranda, Francisco; Instituto Politécnico de Viana do Castelo, Viana do Castelo; Abreu, Carlos

2016-06-08

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtainmore » an optimal feedback control is also presented.« less

Structural Controllability and Controlling Centrality of Temporal Networks

PubMed Central

Pan, Yujian; Li, Xiang

2014-01-01

Temporal networks are such networks where nodes and interactions may appear and disappear at various time scales. With the evidence of ubiquity of temporal networks in our economy, nature and society, it's urgent and significant to focus on its structural controllability as well as the corresponding characteristics, which nowadays is still an untouched topic. We develop graphic tools to study the structural controllability as well as its characteristics, identifying the intrinsic mechanism of the ability of individuals in controlling a dynamic and large-scale temporal network. Classifying temporal trees of a temporal network into different types, we give (both upper and lower) analytical bounds of the controlling centrality, which are verified by numerical simulations of both artificial and empirical temporal networks. We find that the positive relationship between aggregated degree and controlling centrality as well as the scale-free distribution of node's controlling centrality are virtually independent of the time scale and types of datasets, meaning the inherent robustness and heterogeneity of the controlling centrality of nodes within temporal networks. PMID:24747676

Structural controllability of unidirectional bipartite networks

NASA Astrophysics Data System (ADS)

Nacher, Jose C.; Akutsu, Tatsuya

2013-04-01

The interactions between fundamental life molecules, people and social organisations build complex architectures that often result in undesired behaviours. Despite all of the advances made in our understanding of network structures over the past decade, similar progress has not been achieved in the controllability of real-world networks. In particular, an analytical framework to address the controllability of bipartite networks is still absent. Here, we present a dominating set (DS)-based approach to bipartite network controllability that identifies the topologies that are relatively easy to control with the minimum number of driver nodes. Our theoretical calculations, assisted by computer simulations and an evaluation of real-world networks offer a promising framework to control unidirectional bipartite networks. Our analysis should open a new approach to reverting the undesired behaviours in unidirectional bipartite networks at will.

SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks

NASA Astrophysics Data System (ADS)

Lin, Likun

Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network monitoring sensors. In order to maintain signal quality while optimizing network resources, we find that it is essential to model and update estimates of the physical link impairments in real-time. In this thesis, we consider the key elements required to enable an agile optical network, with contributions as follows: • Control Framework: extended the SDN concept to include the optical transport network through extensions to the OpenFlow (OF) protocol. A unified SDN control plane is built to facilitate control and management capability across the electrical/packet-switched and optical/circuit-switched portions of the network seamlessly. The SDN control plane serves as a platform to abstract the resources of multilayer/multivendor networks. Through this platform, applications can dynamically request the network resources to meet their service requirements. • Use of In-situ Monitors: enabled real-time physical impairment sensing in the control plane using in-situ Optical Performance Monitoring (OPM) and bit error rate (BER) analyzers. OPM and BER values are used as quantitative indicators of the link status and are fed to the control plane through a high-speed data collection interface to form a closed-loop feedback system to enable adaptive resource allocation. • Predictive Network Model: used a network model embedded in the control layer to study the link status. The estimated results of network status is fed into the control decisions to precompute the network resources. The performance of the network model can be enhanced by the sensing results. • Real-Time Control Algorithms: investigated various dynamic resource allocation mechanisms supporting an agile optical network. Intelligent routing and wavelength switching for recovering from traffic impairments is achieved experimentally in the agile optical network within one second. A distance-adaptive spectrum allocation scheme to address transmission impairments caused by cascaded Wavelength Selective Switches (WSS) is proposed and evaluated for improving network spectral efficiency.

Low-Complexity Discriminative Feature Selection From EEG Before and After Short-Term Memory Task.

PubMed

Behzadfar, Neda; Firoozabadi, S Mohammad P; Badie, Kambiz

2016-10-01

A reliable and unobtrusive quantification of changes in cortical activity during short-term memory task can be used to evaluate the efficacy of interfaces and to provide real-time user-state information. In this article, we investigate changes in electroencephalogram signals in short-term memory with respect to the baseline activity. The electroencephalogram signals have been analyzed using 9 linear and nonlinear/dynamic measures. We applied statistical Wilcoxon examination and Davis-Bouldian criterion to select optimal discriminative features. The results show that among the features, the permutation entropy significantly increased in frontal lobe and the occipital second lower alpha band activity decreased during memory task. These 2 features reflect the same mental task; however, their correlation with memory task varies in different intervals. In conclusion, it is suggested that the combination of the 2 features would improve the performance of memory based neurofeedback systems. © EEG and Clinical Neuroscience Society (ECNS) 2016.

ECN-2359

NASA Image and Video Library

1969-12-18

The wingless, lifting body aircraft sitting on Rogers Dry Lake at what is now NASA's Dryden Flight Research Center, Edwards, California, from left to right are the X-24A, M2-F3 and the HL-10. The lifting body aircraft studied the feasibility of maneuvering and landing an aerodynamic craft designed for reentry from space. These lifting bodies were air launched by a B-52 mother ship, then flew powered by their own rocket engines before making an unpowered approach and landing. They helped validate the concept that a space shuttle could make accurate landings without power. The X-24A flew from April 17, 1969 to June 4, 1971. The M2-F3 flew from June 2, 1970 until December 22, 1972. The HL-10 flew from December 22, 1966 until July 17, 1970, and logged the highest and fastest records in the lifting body program.

Autonomy, responsibility and the Italian Code of Deontology for Nurses.

PubMed

Barazzetti, Gaia; Radaelli, Stefania; Sala, Roberta

2007-01-01

This article is a first assessment of the Italian Code of deontology for nurses (revised in 1999) on the basis of data collected from focus groups with nurses taking part in the Ethical Codes in Nursing (ECN) project. We illustrate the professional context in which the Code was introduced and explain why the 1999 revision was necessary in the light of changes affecting the Italian nursing profession. The most remarkable findings concern professional autonomy and responsibility, and how the Code is thought of as a set of guidelines for nursing practice. We discuss these issues, underlining that the 1999 Code represents a valuable instrument for ethical reflection and examination, a stimulus for putting the moral sense of the nursing profession into action, and that it represents a new era for professional nursing practice in Italy. The results of the analysis also deserve further qualitative study and future consideration.

ECN-2409

NASA Image and Video Library

1970-06-17

Not every moment of a test pilot's day is serious business. In a moment of levity, NASA pilots Bill Dana (left) and John A. Manke try to drag Air Force test pilot Peter Hoag away from the HL-10 lifting body while Air Force Major Jerauld R. Gentry helps from the cockpit. These four men were the principal pilots for the HL-10 program. This was not the only prank involving the HL-10 and its pilots. Once "Captain Midnight" (Gentry) and the "Midnight Skulkers" sneaked into the NASA hangar and put "U.S. Air Force" on the aircraft using stick-on letters. Later, while Gentry was making a lifting-body flight, his 1954 Ford was "borrowed" from the parking lot, painted with yellow-green zinc-chromate primer, and decorated with large stick-on flowers about one foot in diameter. After Gentry returned from the flight, he was surprised to see what had happened to his car.

Distributed controller clustering in software defined networks.

PubMed

Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

2017-01-01

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

Effect of interaction strength on robustness of controlling edge dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pang, Shao-Peng; Hao, Fei

2018-05-01

Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

Enhanced vaccine control of epidemics in adaptive networks

NASA Astrophysics Data System (ADS)

Shaw, Leah B.; Schwartz, Ira B.

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Enhanced vaccine control of epidemics in adaptive networks.

PubMed

Shaw, Leah B; Schwartz, Ira B

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Neural network-based model reference adaptive control system.

PubMed

Patino, H D; Liu, D

2000-01-01

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

The Longitudinal Effect of Self-Monitoring and Locus of Control on Social Network Position in Friendship Networks

DTIC Science & Technology

2006-03-01

equally essential to examine the antecedents that bring a person to a particular network location. The previous body of knowledge in social networks...Locus of Control on Social Network Position in Friendship Networks THESIS Gary J. Moore, Captain, USAF AFIT/GEM/ENV/06M-11 DEPARTMENT OF THE AIR...THE LONGITUDINAL EFFECTS OF SELF-MONITORING AND LOCUS OF CONTROL ON SOCIAL NETWORK POSITION IN FRIENDSHIP NETWORKS THESIS Presented to the

Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network.

PubMed

Jeng, J T; Lee, T T

2000-01-01

A Chebyshev polynomial-based unified model (CPBUM) neural network is introduced and applied to control a magnetic bearing systems. First, we show that the CPBUM neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional feedforward/recurrent neural network. It turns out that the CPBUM neural network is more suitable in the design of controller than the conventional feedforward/recurrent neural network. Second, we propose the inverse system method, based on the CPBUM neural networks, to control a magnetic bearing system. The proposed controller has two structures; namely, off-line and on-line learning structures. We derive a new learning algorithm for each proposed structure. The experimental results show that the proposed neural network architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Neural networks supporting autobiographical memory retrieval in post-traumatic stress disorder

PubMed Central

Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

2013-01-01

Post-traumatic stress disorder (PTSD) affects the functional recruitment and connectivity between neural regions during autobiographical memory (AM) retrieval that overlap with default and control networks. Whether such univariate changes relate to potential differences in the contribution of large-scale neural networks supporting cognition in PTSD is unknown. In the current functional MRI (fMRI) study we employ independent component analysis to examine the influence the engagement of neural networks during the recall of personal memories in PTSD (15 participants) compared to non-trauma exposed, healthy controls (14 participants). We found that the PTSD group recruited similar neural networks when compared to controls during AM recall, including default network subsystems and control networks, but there were group differences in the spatial and temporal characteristics of these networks. First, there were spatial differences in the contribution of the anterior and posterior midline across the networks, and with the amygdala in particular for the medial temporal subsystem of the default network. Second, there were temporal differences in the relationship of the medial prefrontal subsystem of the default network, with less temporal coupling of this network during AM retrieval in PTSD relative to controls. These findings suggest that spatial and temporal characteristics of the default and control networks potentially differ in PTSD versus healthy controls, and contribute to altered recall of personal memory. PMID:23483523

Minimum energy control and optimal-satisfactory control of Boolean control network

NASA Astrophysics Data System (ADS)

Li, Fangfei; Lu, Xiwen

2013-12-01

In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

A first packet processing subdomain cluster model based on SDN

NASA Astrophysics Data System (ADS)

Chen, Mingyong; Wu, Weimin

2017-08-01

For the current controller cluster packet processing performance bottlenecks and controller downtime problems. An SDN controller is proposed to allocate the priority of each device in the SDN (Software Defined Network) network, and the domain contains several network devices and Controller, the controller is responsible for managing the network equipment within the domain, the switch performs data delivery based on the load of the controller, processing network equipment data. The experimental results show that the model can effectively solve the risk of single point failure of the controller, and can solve the performance bottleneck of the first packet processing.

Default Network Modulation and Large-Scale Network Interactivity in Healthy Young and Old Adults

PubMed Central

Schacter, Daniel L.

2012-01-01

We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands. PMID:22128194

Network device interface for digitally interfacing data channels to a controller a via network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. In one embodiment, the bus controller transmits messages to the network device interface containing a plurality of bits having a value defined by a transition between first and second states in the bits. The network device interface determines timing of the data sequence of the message and uses the determined timing to communicate with the bus controller.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Winkelmann, Joseph P. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface is a state machine, such as an ASIC, that operates independent of a processor in communicating with the bus controller and data channels.

A microcomputer network for control of a continuous mining machine

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

Schiffbauer, W.H.

1993-12-31

This report details a microcomputer-based control and monitoring network that was developed in-house by the U.S. Bureau of Mines and installed on a continuous mining machine. The network consists of microcomputers that are connected together via a single twisted-pair cable. Each microcomputer was developed to provide a particular function in the control process. Machine-mounted microcomputers, in conjunction with the appropriate sensors, provide closed-loop control of the machine, navigation, and environmental monitoring. Off-the-machine microcomputers provide remote control of the machine, sensor status, and a connection to the network so that external computers can access network data and control the continuous miningmore » machine. Because of the network`s generic structure, it can be installed on most mining machines.« less

Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

PubMed

Jäncke, Lutz; Alahmadi, Nsreen

2016-01-01

In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical neurophysiological activation patterns might provide a helpful guide for rehabilitation strategies to treat the deficiencies in these children with LD. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

NASA Technical Reports Server (NTRS)

Wang, Shin-Ywan

2012-01-01

The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

Cell fate reprogramming by control of intracellular network dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

Pinning impulsive control algorithms for complex network

NASA Astrophysics Data System (ADS)

Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo

2014-03-01

In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.

Topology Control in Aerial Multi-Beam Directional Networks

DTIC Science & Technology

2017-04-24

underlying challenges to topology control in multi -beam direction networks. Two topology control algorithms are developed: a centralized algorithm...main beam, the gain is negligible. Thus, for topology control in a multi -beam system, two nodes that are being simultaneously transmitted to or...the network. As the network size is larger than the communication range, even the original network will require some multi -hop traffic. The second two

Application of Fuzzy-Logic Controller and Neural Networks Controller in Gas Turbine Speed Control and Overheating Control and Surge Control on Transient Performance

NASA Astrophysics Data System (ADS)

Torghabeh, A. A.; Tousi, A. M.

2007-08-01

This paper presents Fuzzy Logic and Neural Networks approach to Gas Turbine Fuel schedules. Modeling of non-linear system using feed forward artificial Neural Networks using data generated by a simulated gas turbine program is introduced. Two artificial Neural Networks are used , depicting the non-linear relationship between gas generator speed and fuel flow, and turbine inlet temperature and fuel flow respectively . Off-line fast simulations are used for engine controller design for turbojet engine based on repeated simulation. The Mamdani and Sugeno models are used to expression the Fuzzy system . The linguistic Fuzzy rules and membership functions are presents and a Fuzzy controller will be proposed to provide an Open-Loop control for the gas turbine engine during acceleration and deceleration . MATLAB Simulink was used to apply the Fuzzy Logic and Neural Networks analysis. Both systems were able to approximate functions characterizing the acceleration and deceleration schedules . Surge and Flame-out avoidance during acceleration and deceleration phases are then checked . Turbine Inlet Temperature also checked and controls by Neural Networks controller. This Fuzzy Logic and Neural Network Controllers output results are validated and evaluated by GSP software . The validation results are used to evaluate the generalization ability of these artificial Neural Networks and Fuzzy Logic controllers.

Research in Network Management Techniques for Tactical Data Communications Network.

DTIC Science & Technology

1982-09-01

the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques...contro!lers are designed to perform their limited tasks optimally. For the dynamic routing problem considered here, the local controllers are node...feedback to finding in optimum stead-o-state routing (static strategies) under non - control which can be easily implemented in real time. congested

Sex-specific effects of social networks on the prevalence, awareness, and control of hypertension among older Korean adults.

PubMed

Baek, Jiwon; Hur, Nam Wook; Kim, Hyeon Chang; Youm, Yoosik

2016-07-01

Hypertension is a common chronic disease among older adults, and is associated with medical complications and mortality. This study aimed to examine the effects of social network characteristics on the prevalence, awareness, and control of hypertension among older adults. The Korean Social Life, Health, and Aging Project (KSHAP) interviewed 814 ≥ 60-year-old residents and their spouses from a rural township between December 2011 and March 2012 (response rate: 95%). We evaluated the data from 595 participants. Multivariate logistic regression models were used to assess the effects of network characteristics on hypertension. We observed strong sex-specific network effects on the prevalence, awareness, and control of hypertension. Among older women, network density was associated with hypertension awareness [odds ratio (OR): 2.63, 95% confidence interval (CI): 1.03-5.37] and control (OR: 1.72; 95% CI: 0.94-3.13). Among older men, large networks were associated with a lower prevalence of hypertension (OR: 0.75; 95% CI: 0.58-0.96). Compared to older women, older men with coarse networks exhibited better hypertension awareness (OR: 0.37; 95% CI: 0.14-0.95) and control (OR: 0.42; 95% CI: 0.19-0.91). Network size interacted with density for hypertension control (P = 0.051), with controlled hypertension being associated with large and course networks. A large network was associated with a lower risk for hypertension, and a coarse network was associated with hypertension awareness and control among older men. Older women with dense networks were most likely to exhibit hypertension awareness and control.

Distributed controller clustering in software defined networks

PubMed Central

Gani, Abdullah; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

2017-01-01

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability. PMID:28384312

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

2005-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor); Grant, Robert L. (Inventor)

2004-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted into digital signals and transmitted back to the controller. In one embodiment, the bus controller sends commands and data a defined bit rate, and the network device interface senses this bit rate and sends data back to the bus controller using the defined bit rate.

Functional brain networks associated with cognitive control, cocaine dependence, and treatment outcome.

PubMed

Worhunsky, Patrick D; Stevens, Michael C; Carroll, Kathleen M; Rounsaville, Bruce J; Calhoun, Vince D; Pearlson, Godfrey D; Potenza, Marc N

2013-06-01

Individuals with cocaine dependence often evidence poor cognitive control. The purpose of this exploratory study was to investigate networks of functional connectivity underlying cognitive control in cocaine dependence and examine the relationship of the networks to the disorder and its treatment. Independent component analysis (ICA) was applied to fMRI data to investigate if regional activations underlying cognitive control processes operate in functional networks, and whether these networks relate to performance and treatment outcome measures in cocaine dependence. Twenty patients completed a Stroop task during fMRI prior to entering outpatient treatment and were compared to 20 control participants. ICA identified five distinct functional networks related to cognitive control interference events. Cocaine-dependent patients displayed differences in performance-related recruitment of three networks. Reduced involvement of a "top-down" fronto-cingular network contributing to conflict monitoring correlated with better treatment retention. Greater engagement of two "bottom-up" subcortical and ventral prefrontal networks related to cue-elicited motivational processing correlated with abstinence during treatment. The identification of subcortical networks linked to cocaine abstinence and cortical networks to treatment retention suggests that specific circuits may represent important, complementary targets in treatment development for cocaine dependence. 2013 APA, all rights reserved

The application of neural network PID controller to control the light gasoline etherification

NASA Astrophysics Data System (ADS)

Cheng, Huanxin; Zhang, Yimin; Kong, Lingling; Meng, Xiangyong

2017-06-01

Light gasoline etherification technology can effectively improve the quality of gasoline, which is environmental- friendly and economical. By combining BP neural network and PID control and using BP neural network self-learning ability for online parameter tuning, this method optimizes the parameters of PID controller and applies this to the Fcc gas flow control to achieve the control of the final product- heavy oil concentration. Finally, through MATLAB simulation, it is found that the PID control based on BP neural network has better controlling effect than traditional PID control.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

NASA Astrophysics Data System (ADS)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Fair and efficient network congestion control based on minority game

NASA Astrophysics Data System (ADS)

Wang, Zuxi; Wang, Wen; Hu, Hanping; Deng, Zhaozhang

2011-12-01

Low link utility, RTT unfairness and unfairness of Multi-Bottleneck network are the existing problems in the present network congestion control algorithms at large. Through the analogy of network congestion control with the "El Farol Bar" problem, we establish a congestion control model based on minority game(MG), and then present a novel network congestion control algorithm based on the model. The result of simulations indicates that the proposed algorithm can make the achievements of link utility closing to 100%, zero packet lose rate, and small of queue size. Besides, the RTT unfairness and the unfairness of Multi-Bottleneck network can be solved, to achieve the max-min fairness in Multi-Bottleneck network, while efficiently weaken the "ping-pong" oscillation caused by the overall synchronization.

Can We Control Contaminant Transport In Hydrologic Networks? Application Of Control Theory Concepts To Watershed Management

NASA Astrophysics Data System (ADS)

Yeghiazarian, L.; Riasi, M. S.

2016-12-01

Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is "what is the most efficient way to fully/partially control water quality in surface water networks?". This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in dendritic surface water networks.

Unified Lunar Control Network 2005 and Topographic Model

NASA Technical Reports Server (NTRS)

Archinal, B. A.; Rosiek, M. R.; Redding, B. L.

2005-01-01

There are currently two generally accepted lunar control networks. These are the Unified Lunar Control Network (ULCN) and the Clementine Lunar Control Network (CLCN), both derived by M. Davies and T. Colvin at RAND. We address here our efforts to merge and improve these networks into a new ULCN. The ULCN was described in the last major publication about a lunar control network. The statistics on this and the other networks discussed here. Images for this network are from the Apollo, Mariner 10, and Galileo missions, and Earth-based photographs. The importance of this network is that its accuracy is relatively well quantified and published information on the network is available. The CLCN includes measurements on 43,871 Clementine 750-nm images - the largest planetary control network ever computed. This purpose of this network was to determine the geometry for the Clementine Basemap Mosiac (CBM). The geometry of that mosaic was used to produce the Clementine UVVIS digital image model and the Near-Infrared Global Multispectral Map of the Moon from Clementine. Through the extensive use of these products, they and the underlying CLCN in effect define the generally accepted current coordinate system for reporting and describing the location of lunar coordinates. However, no publication describes the CLCN itself.

Predictive Control of Networked Multiagent Systems via Cloud Computing.

PubMed

Liu, Guo-Ping

2017-01-18

This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.

PubMed

Wan, Ying; Cao, Jinde; Wen, Guanghui

In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.

Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

NASA Technical Reports Server (NTRS)

Scott, Robert C.

2000-01-01

NASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.

Controllability of structural brain networks

NASA Astrophysics Data System (ADS)

Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

2015-10-01

Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.

Interorganizational relationships within state tobacco control networks: a social network analysis.

PubMed

Krauss, Melissa; Mueller, Nancy; Luke, Douglas

2004-10-01

State tobacco control programs are implemented by networks of public and private agencies with a common goal to reduce tobacco use. The degree of a program's comprehensiveness depends on the scope of its activities and the variety of agencies involved in the network. Structural aspects of these networks could help describe the process of implementing a state's tobacco control program, but have not yet been examined. Social network analysis was used to examine the structure of five state tobacco control networks. Semi-structured interviews with key agencies collected quantitative and qualitative data on frequency of contact among network partners, money flow, relationship productivity, level of network effectiveness, and methods for improvement. Most states had hierarchical communication structures in which partner agencies had frequent contact with one or two central agencies. Lead agencies had the highest control over network communication. Networks with denser communication structures had denser productivity structures. Lead agencies had the highest financial influence within the networks, while statewide coalitions were financially influenced by others. Lead agencies had highly productive relationships with others, while agencies with narrow roles had fewer productive relationships. Statewide coalitions that received Robert Wood Johnson Foundation funding had more highly productive relationships than coalitions that did not receive the funding. Results suggest that frequent communication among network partners is related to more highly productive relationships. Results also highlight the importance of lead agencies and statewide coalitions in implementing a comprehensive state tobacco control program. Network analysis could be useful in developing process indicators for state tobacco control programs.

A Study of the Effects of Fieldbus Network Induced Delays on Control Systems

ERIC Educational Resources Information Center

Mainoo, Joseph

2012-01-01

Fieldbus networks are all-digital, two-way, multi-drop communication systems that are used to connect field devices such as sensors and actuators, and controllers. These fieldbus network systems are also called networked control systems (NCS). Although, there are different varieties of fieldbus networks such as Foundation Field Bus, DeviceNet, and…

Bio-inspired spiking neural network for nonlinear systems control.

PubMed

Pérez, Javier; Cabrera, Juan A; Castillo, Juan J; Velasco, Juan M

2018-08-01

Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more complex computation. As demonstrated by biological organisms, they are a potentially good approach to designing controllers for highly nonlinear dynamic systems in which the performance of controllers developed by conventional techniques is not satisfactory or difficult to implement. SNN-based controllers exploit their ability for online learning and self-adaptation to evolve when transferred from simulations to the real world. SNN's inherent binary and temporary way of information codification facilitates their hardware implementation compared to analog neurons. Biological neural networks often require a lower number of neurons compared to other controllers based on artificial neural networks. In this work, these neuronal systems are imitated to perform the control of non-linear dynamic systems. For this purpose, a control structure based on spiking neural networks has been designed. Particular attention has been paid to optimizing the structure and size of the neural network. The proposed structure is able to control dynamic systems with a reduced number of neurons and connections. A supervised learning process using evolutionary algorithms has been carried out to perform controller training. The efficiency of the proposed network has been verified in two examples of dynamic systems control. Simulations show that the proposed control based on SNN exhibits superior performance compared to other approaches based on Neural Networks and SNNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Multicomponent Blend as a Diesel Fuel Surrogate for Compression Ignition Engine Applications

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

Pei, Yuanjiang; Mehl, Marco; Liu, Wei

A mixture of n-dodecane and m-xylene is investigated as a diesel fuel surrogate for compression ignition engine applications. Compared to neat n-dodecane, this binary mixture is more representative of diesel fuel because it contains an alkyl-benzene which represents an important chemical class present in diesel fuels. A detailed multi-component mechanism for n-dodecane and m-xylene was developed by combining a previously developed n-dodecane mechanism with a recently developed mechanism for xylenes. The xylene mechanism is shown to reproduce experimental ignition data from a rapid compression machine and shock tube, speciation data from the jet stirred reactor and flame speed data. Thismore » combined mechanism was validated by comparing predictions from the model with experimental data for ignition in shock tubes and for reactivity in a flow reactor. The combined mechanism, consisting of 2885 species and 11754 reactions, was reduced to a skeletal mechanism consisting 163 species and 887 reactions for 3D diesel engine simulations. The mechanism reduction was performed using directed relation graph (DRG) with expert knowledge (DRG-X) and DRG-aided sensitivity analysis (DRGASA) at a fixed fuel composition of 77% of n-dodecane and 23% m-xylene by volume. The sample space for the reduction covered pressure of 1 – 80 bar, equivalence ratio of 0.5 – 2.0, and initial temperature of 700 – 1600 K for ignition. The skeletal mechanism was compared with the detailed mechanism for ignition and flow reactor predictions. Finally, the skeletal mechanism was validated against a spray flame dataset under diesel engine conditions documented on the Engine Combustion Network (ECN) website. These multi-dimensional simulations were performed using a Representative Interactive Flame (RIF) turbulent combustion model. Encouraging results were obtained compared to the experiments with regards to the predictions of ignition delay and lift-off length at different ambient temperatures.« less

Visual Evoked Potentials in Infants With Diffuse Periventricular Leukomalacia.

PubMed

Carbajal-Valenzuela, Cintli Carolina; Santiago-Rodríguez, Efraín; Harmony, Thalía; Fernández-Bouzas, Antonio

2014-10-01

Periventricular leukomalacia (PVL) is characterized by necrosis of the cerebral white matter in the dorsolateral portions of the lateral ventricles. PVL causes motor, sensory, and cognitive deficits. The aim of this study was to analyze the conduction characteristics of the visual pathway in infants with diffuse PVL using visual evoked potentials (VEPs). We studied 11 healthy infants (mean age 3.3 ± 1.3 months) and 17 with diffuse PVL (mean age 2.9 ± 0.8 months and mean gestational age 31.9 ± 3.1 weeks). The N75, P100, and N135 wave latencies; the interwave N75-P100 and P100-N135 latencies; and the N75-P100 and P100-N135 amplitudes were measured in the occipital leads. VEPs were recorded during binocular stimulation at an angle of 120' from the Fz-Oz lead. Healthy children had mean N75, P100, and N135 wave latencies of 84.4 ± 5.8, 143.4 ± 30.6 and 222.9 ± 40.4 ms, respectively. The mean interwave N75-P100 and P100-N135 latencies were 59.0 ± 28.6 and 79.5 ± 13.6 ms, respectively. Compared with the healthy group, infants with PVL had longer N75 and N135 latencies at 92.3 ± 15.3 (P = .05) and 265.0 ms ± 60.3 (P = .05), respectively. The interwave latency P100-N135 (105.5 ± 29.1 ms; P = .017) was longer in children with PVL than in healthy infants. Infants with diffuse PVL had mild alterations in their N75, P100 and, particularly, their N135 latencies. These increases in P100-N135 interwave latencies could be because of damage to the geniculocortical pathways and V2-V3 networks. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease.

PubMed

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian; Zhou, Juan

2017-11-01

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer's disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer's disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer's disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks-the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer's disease patients with and without cerebrovascular disease. Alzheimer's disease patients without cerebrovascular disease, but not Alzheimer's disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer's disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer's disease patients with and without cerebrovascular disease. Across Alzheimer's disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer's disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer's disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer's disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer's disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer's disease network degeneration phenotype. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Neural networks for self-learning control systems

NASA Technical Reports Server (NTRS)

Nguyen, Derrick H.; Widrow, Bernard

1990-01-01

It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.

The Contribution of Network Organization and Integration to the Development of Cognitive Control

PubMed Central

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N.; Luna, Beatriz

2015-01-01

Abstract Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10–26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control. PMID:26713863

The Contribution of Network Organization and Integration to the Development of Cognitive Control.

PubMed

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

2015-12-01

Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks

PubMed Central

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the “immune system” of mental health recently developed in relation to flexible hub theory. PMID:28736535

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

PubMed

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the "immune system" of mental health recently developed in relation to flexible hub theory.

Global Efficiency of Structural Networks Mediates Cognitive Control in Mild Cognitive Impairment

PubMed Central

Berlot, Rok; Metzler-Baddeley, Claudia; Ikram, M. Arfan; Jones, Derek K.; O’Sullivan, Michael J.

2016-01-01

Background: Cognitive control has been linked to both the microstructure of individual tracts and the structure of whole-brain networks, but their relative contributions in health and disease remain unclear. Objective: To determine the contribution of both localized white matter tract damage and disruption of global network architecture to cognitive control, in older age and Mild Cognitive Impairment (MCI). Materials and Methods: Twenty-five patients with MCI and 20 age, sex, and intelligence-matched healthy volunteers were investigated with 3 Tesla structural magnetic resonance imaging (MRI). Cognitive control and episodic memory were evaluated with established tests. Structural network graphs were constructed from diffusion MRI-based whole-brain tractography. Their global measures were calculated using graph theory. Regression models utilized both global network metrics and microstructure of specific connections, known to be critical for each domain, to predict cognitive scores. Results: Global efficiency and the mean clustering coefficient of networks were reduced in MCI. Cognitive control was associated with global network topology. Episodic memory, in contrast, correlated with individual temporal tracts only. Relationships between cognitive control and network topology were attenuated by addition of single tract measures to regression models, consistent with a partial mediation effect. The mediation effect was stronger in MCI than healthy volunteers, explaining 23-36% of the effect of cingulum microstructure on cognitive control performance. Network clustering was a significant mediator in the relationship between tract microstructure and cognitive control in both groups. Conclusion: The status of critical connections and large-scale network topology are both important for maintenance of cognitive control in MCI. Mediation via large-scale networks is more important in patients with MCI than healthy volunteers. This effect is domain-specific, and true for cognitive control but not for episodic memory. Interventions to improve cognitive control will need to address both dysfunction of local circuitry and global network architecture to be maximally effective. PMID:28018208

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

Kim, Jason Z; Soffer, Jonathan M; Kahn, Ari E; Vettel, Jean M; Pasqualetti, Fabio; Bassett, Danielle S

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Role of graph architecture in controlling dynamical networks with applications to neural systems

NASA Astrophysics Data System (ADS)

Kim, Jason Z.; Soffer, Jonathan M.; Kahn, Ari E.; Vettel, Jean M.; Pasqualetti, Fabio; Bassett, Danielle S.

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviours such as synchronization. Although descriptions of these behaviours are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behaviour. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behaviour in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Cell Fate Reprogramming by Control of Intracellular Network Dynamics

PubMed Central

Zañudo, Jorge G. T.; Albert, Réka

2015-01-01

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method’s potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. PMID:25849586

Development of a decentralized multi-axis synchronous control approach for real-time networks.

PubMed

Xu, Xiong; Gu, Guo-Ying; Xiong, Zhenhua; Sheng, Xinjun; Zhu, Xiangyang

2017-05-01

The message scheduling and the network-induced delays of real-time networks, together with the different inertias and disturbances in different axes, make the synchronous control of the real-time network-based systems quite challenging. To address this challenge, a decentralized multi-axis synchronous control approach is developed in this paper. Due to the limitations of message scheduling and network bandwidth, error of the position synchronization is firstly defined in the proposed control approach as a subset of preceding-axis pairs. Then, a motion message estimator is designed to reduce the effect of network delays. It is proven that position and synchronization errors asymptotically converge to zero in the proposed controller with the delay compensation. Finally, simulation and experimental results show that the developed control approach can achieve the good position synchronization performance for the multi-axis motion over the real-time network. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor)

2007-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. In some embodiments, network device interfaces associated with different data channels coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

On the Control of Consensus Networks: Theory and Applications

NASA Astrophysics Data System (ADS)

Hudoba de Badyn, Mathias

Signed networks allow the study of positive and negative interactions between agents. In this thesis, three papers are presented that address controllability of networked dynamics. First, controllability of signed consensus networks is approached from a symmetry perspective, for both linear and nonlinear consensus protocols. It is shown that the graph-theoretic property of signed networks known as structural balance renders the consensus protocol uncontrollable when coupled with a certain type of symmetry. Stabilizability and output controllability of signed linear consensus is also examined, as well as a data-driven approach to finding bipartite consensus stemming from structural balance for signed nonlinear consensus. Second, an algorithm is constructed that allows one to grow a network while preserving controllability, and some generalizations of this algorithm are presented. Submodular optimization is used to analyze a second algorithm that adds nodes to a network to maximize the network connectivity.

Closed-Loop Control of Complex Networks: A Trade-Off between Time and Energy

NASA Astrophysics Data System (ADS)

Sun, Yong-Zheng; Leng, Si-Yang; Lai, Ying-Cheng; Grebogi, Celso; Lin, Wei

2017-11-01

Controlling complex nonlinear networks is largely an unsolved problem at the present. Existing works focus either on open-loop control strategies and their energy consumptions or on closed-loop control schemes with an infinite-time duration. We articulate a finite-time, closed-loop controller with an eye toward the physical and mathematical underpinnings of the trade-off between the control time and energy as well as their dependence on the network parameters and structure. The closed-loop controller is tested on a large number of real systems including stem cell differentiation, food webs, random ecosystems, and spiking neuronal networks. Our results represent a step forward in developing a rigorous and general framework to control nonlinear dynamical networks with a complex topology.

Connecting Core Percolation and Controllability of Complex Networks

PubMed Central

Jia, Tao; Pósfai, Márton

2014-01-01

Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks. PMID:24946797

Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

PubMed Central

Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

2016-01-01

Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease

PubMed Central

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian

2017-01-01

Abstract Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype. PMID:29053778

Abnormal functional network connectivity among resting-state networks in children with frontal lobe epilepsy.

PubMed

Widjaja, E; Zamyadi, M; Raybaud, C; Snead, O C; Smith, M L

2013-12-01

Epilepsy is considered a disorder of neural networks. The aims of this study were to assess functional connectivity within resting-state networks and functional network connectivity across resting-state networks by use of resting-state fMRI in children with frontal lobe epilepsy and to relate changes in resting-state networks with neuropsychological function. Fifteen patients with frontal lobe epilepsy and normal MR imaging and 14 healthy control subjects were recruited. Spatial independent component analysis was used to identify the resting-state networks, including frontal, attention, default mode network, sensorimotor, visual, and auditory networks. The Z-maps of resting-state networks were compared between patients and control subjects. The relation between abnormal connectivity and neuropsychological function was assessed. Correlations from all pair-wise combinations of independent components were performed for each group and compared between groups. The frontal network was the only network that showed reduced connectivity in patients relative to control subjects. The remaining 5 networks demonstrated both reduced and increased functional connectivity within resting-state networks in patients. There was a weak association between connectivity in frontal network and executive function (P = .029) and a significant association between sensorimotor network and fine motor function (P = .004). Control subjects had 79 pair-wise independent components that showed significant temporal coherence across all resting-state networks except for default mode network-auditory network. Patients had 66 pairs of independent components that showed significant temporal coherence across all resting-state networks. Group comparison showed reduced functional network connectivity between default mode network-attention, frontal-sensorimotor, and frontal-visual networks and increased functional network connectivity between frontal-attention, default mode network-sensorimotor, and frontal-visual networks in patients relative to control subjects. We found abnormal functional connectivity within and across resting-state networks in children with frontal lobe epilepsy. Impairment in functional connectivity was associated with impaired neuropsychological function.

Software defined network architecture based research on load balancing strategy

NASA Astrophysics Data System (ADS)

You, Xiaoqian; Wu, Yang

2018-05-01

As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.

Development of distinct control networks through segregation and integration

PubMed Central

Fair, Damien A.; Dosenbach, Nico U. F.; Church, Jessica A.; Cohen, Alexander L.; Brahmbhatt, Shefali; Miezin, Francis M.; Barch, Deanna M.; Raichle, Marcus E.; Petersen, Steven E.; Schlaggar, Bradley L.

2007-01-01

Human attentional control is unrivaled. We recently proposed that adults depend on distinct frontoparietal and cinguloopercular networks for adaptive online task control versus more stable set control, respectively. During development, both experience-dependent evoked activity and spontaneous waves of synchronized cortical activity are thought to support the formation and maintenance of neural networks. Such mechanisms may encourage tighter “integration” of some regions into networks over time while “segregating” other sets of regions into separate networks. Here we use resting state functional connectivity MRI, which measures correlations in spontaneous blood oxygenation level-dependent signal fluctuations between brain regions to compare previously identified control networks between children and adults. We find that development of the proposed adult control networks involves both segregation (i.e., decreased short-range connections) and integration (i.e., increased long-range connections) of the brain regions that comprise them. Delay/disruption in the developmental processes of segregation and integration may play a role in disorders of control, such as autism, attention deficit hyperactivity disorder, and Tourette's syndrome. PMID:17679691

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Network Upgrade for the SLC: PEP II Network

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

Crane, M.; Call, M.; Clark, S.

2011-09-09

The PEP-II control system required a new network to support the system functions. This network, called CTLnet, is an FDDI/Ethernet based network using only TCP/IP protocols. An upgrade of the SLC Control System micro communications to use TCP/IP and SLCNET would allow all PEP-II control system nodes to use TCP/IP. CTLnet is private and separate from the SLAC public network. Access to nodes and control system functions is provided by multi-homed application servers with connections to both the private CTLnet and the SLAC public network. Monitoring and diagnostics are provided using a dedicated system. Future plans and current status informationmore » is included.« less

Multiple-Ring Digital Communication Network

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1992-01-01

Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

Selective impairment of attention networks during propofol anesthesia after gynecological surgery in middle-aged women.

PubMed

Chen, Chen; Xu, Guang-hong; Li, Yuan-hai; Tang, Wei-xiang; Wang, Kai

2016-04-15

Postoperative cognitive dysfunction is a common complication of anesthesia and surgery. Attention networks are essential components of cognitive function and are subject to impairment after anesthesia and surgery. It is not known whether such impairment represents a global attention deficit or relates to a specific attention network. We used an Attention Network Task (ANT) to examine the efficiency of the alerting, orienting, and executive control attention networks in middle-aged women (40-60 years) undergoing gynecologic surgery. A matched group of medical inpatients were recruited as a control. Fifty female patients undergoing gynecologic surgery (observation group) and 50 female medical inpatients (control group) participated in this study. Preoperatively patients were administered a mini-mental state examination as a screening method. The preoperative efficiencies of three attention networks in an attention network test were compared to the 1st and 5th post-operative days. The control group did not have any significant attention network impairments. On the 1st postoperative day, significant impairment was shown in the alerting (p=0.003 vs. control group, p=0.015 vs. baseline), orienting (p<0.001 vs. both baseline level and control group), and executive control networks (p=0.007 vs. control group, p=0.002 vs. baseline) of the observation group. By the 5th postoperative day, the alerting network efficiency had recovered to preoperative levels (p=0.464 vs. baseline) and the orienting network efficiency had recovered partially (p=0.031 vs. 1st post-operative day), but not to preoperative levels (p=0.01 vs. baseline). The executive control network did not recover by the 5th postoperative day (p=0.001 vs. baseline, p=0.680 vs. 1st post-operative day). Attention networks of middle-aged women show a varying degree of significant impairment and differing levels of recovery after surgery and propofol anesthetic. Copyright © 2016 Elsevier B.V. All rights reserved.

A robust fractional-order PID controller design based on active queue management for TCP network

NASA Astrophysics Data System (ADS)

Hamidian, Hamideh; Beheshti, Mohammad T. H.

2018-01-01

In this paper, a robust fractional-order controller is designed to control the congestion in transmission control protocol (TCP) networks with time-varying parameters. Fractional controllers can increase the stability and robustness. Regardless of advantages of fractional controllers, they are still not common in congestion control in TCP networks. The network parameters are time-varying, so the robust stability is important in congestion controller design. Therefore, we focused on the robust controller design. The fractional PID controller is developed based on active queue management (AQM). D-partition technique is used. The most important property of designed controller is the robustness to the time-varying parameters of the TCP network. The vertex quasi-polynomials of the closed-loop characteristic equation are obtained, and the stability boundaries are calculated for each vertex quasi-polynomial. The intersection of all stability regions is insensitive to network parameter variations, and results in robust stability of TCP/AQM system. NS-2 simulations show that the proposed algorithm provides a stable queue length. Moreover, simulations show smaller oscillations of the queue length and less packet drop probability for FPID compared to PI and PID controllers. We can conclude from NS-2 simulations that the average packet loss probability variations are negligible when the network parameters change.

State feedback controller design for the synchronization of Boolean networks with time delays

NASA Astrophysics Data System (ADS)

Li, Fangfei; Li, Jianning; Shen, Lijuan

2018-01-01

State feedback control design to make the response Boolean network synchronize with the drive Boolean network is far from being solved in the literature. Motivated by this, this paper studies the feedback control design for the complete synchronization of two coupled Boolean networks with time delays. A necessary condition for the existence of a state feedback controller is derived first. Then the feedback control design procedure for the complete synchronization of two coupled Boolean networks is provided based on the necessary condition. Finally, an example is given to illustrate the proposed design procedure.

The application of immune genetic algorithm in main steam temperature of PID control of BP network

NASA Astrophysics Data System (ADS)

Li, Han; Zhen-yu, Zhang

In order to overcome the uncertainties, large delay, large inertia and nonlinear property of the main steam temperature controlled object in the power plant, a neural network intelligent PID control system based on immune genetic algorithm and BP neural network is designed. Using the immune genetic algorithm global search optimization ability and good convergence, optimize the weights of the neural network, meanwhile adjusting PID parameters using BP network. The simulation result shows that the system is superior to conventional PID control system in the control of quality and robustness.

Controlling Contagion Processes in Activity Driven Networks

NASA Astrophysics Data System (ADS)

Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro

2014-03-01

The vast majority of strategies aimed at controlling contagion processes on networks consider the connectivity pattern of the system either quenched or annealed. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently with the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for a class of time-varying networks, namely activity-driven networks. We develop a block variable mean-field approach that allows the derivation of the equations describing the coevolution of the contagion process and the network dynamic. We derive the critical immunization threshold and assess the effectiveness of three different control strategies. Finally, we validate the theoretical picture by simulating numerically the spreading process and control strategies in both synthetic networks and a large-scale, real-world, mobile telephone call data set.

Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control.

PubMed

Wen, Shiping; Zeng, Zhigang; Chen, Michael Z Q; Huang, Tingwen

2017-10-01

This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

Observability and Controllability of Networks: Symmetry in Representations of Brains and Controllers for Epidemics

NASA Astrophysics Data System (ADS)

Schiff, Steven

Observability and controllability are essential concepts to the design of predictive observer models and feedback controllers of networked systems. We present a numerical and group representational framework, to quantify the observability and controllability of nonlinear networks with explicit symmetries that shows the connection between symmetries and nonlinear measures of observability and controllability. In addition to the topology of brain networks, we have advanced our ability to represent network nodes within the brain using conservation principles and more accurate biophysics that unifies the dynamics of spikes, seizures, and spreading depression. Lastly, we show how symmetries in controller design can be applied to infectious disease epidemics. NIH Grants 1R01EB014641, 1DP1HD086071.

Transport Protocols for Wireless Mesh Networks

NASA Astrophysics Data System (ADS)

Eddie Law, K. L.

Transmission control protocol (TCP) provides reliable connection-oriented services between any two end systems on the Internet. With TCP congestion control algorithm, multiple TCP connections can share network and link resources simultaneously. These TCP congestion control mechanisms have been operating effectively in wired networks. However, performance of TCP connections degrades rapidly in wireless and lossy networks. To sustain the throughput performance of TCP connections in wireless networks, design modifications may be required accordingly in the TCP flow control algorithm, and potentially, in association with other protocols in other layers for proper adaptations. In this chapter, we explain the limitations of the latest TCP congestion control algorithm, and then review some popular designs for TCP connections to operate effectively in wireless mesh network infrastructure.

Robust pinning control of heterogeneous complex networks with jointly connected topologies and time-varying parametric uncertainty

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2018-05-01

The pinning/leader control problems provide the design of the leader or pinning controller in order to guide a complex network to a desired trajectory or target (synchronisation or consensus). Let a time-invariant complex network, pinning/leader control problems include the design of the leader or pinning controller gain and number of nodes to pin in order to guide a network to a desired trajectory (synchronization or consensus). Usually, lower is the number of pinned nodes larger is the pinning gain required to assess network synchronisation. On the other side, realistic application scenario of complex networks is characterised by switching topologies, time-varying node coupling strength and link weight that make hard to solve the pinning/leader control problem. Additionally, the system dynamics at nodes can be heterogeneous. In this paper, we derive robust stabilisation conditions of time-varying heterogeneous complex networks with jointly connected topologies when coupling strength and link weight interactions are affected by time-varying uncertainties. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, we formulate low computationally demanding stabilisability conditions to design a pinning/leader control gain for robust network synchronisation. The effectiveness of the proposed approach is shown by several design examples applied to a paradigmatic well-known complex network composed of heterogeneous Chua's circuits.

Network Access Control List Situation Awareness

ERIC Educational Resources Information Center

Reifers, Andrew

2010-01-01

Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…

The evolutions of medical building network structure for emerging infectious disease protection and control.

PubMed

Liu, Nan; Zhang, Hongzhe; Zhang, Shanshan

2014-12-01

Emerging infectious disease is one of the most minatory threats in modern society. A perfect medical building network system need to be established to protect and control emerging infectious disease. Although in China a preliminary medical building network is already set up with disease control center, the infectious disease hospital, infectious diseases department in general hospital and basic medical institutions, there are still many defects in this system, such as simple structural model, weak interoperability among subsystems, and poor capability of the medical building to adapt to outbreaks of infectious disease. Based on the characteristics of infectious diseases, the whole process of its prevention and control and the comprehensive influence factors, three-dimensional medical architecture network system is proposed as an inevitable trend. In this conception of medical architecture network structure, the evolutions are mentioned, such as from simple network system to multilayer space network system, from static network to dynamic network, and from mechanical network to sustainable network. Ultimately, a more adaptable and corresponsive medical building network system will be established and argued in this paper.

Communications and control for electric power systems: Power system stability applications of artificial neural networks

NASA Technical Reports Server (NTRS)

Toomarian, N.; Kirkham, Harold

1994-01-01

This report investigates the application of artificial neural networks to the problem of power system stability. The field of artificial intelligence, expert systems, and neural networks is reviewed. Power system operation is discussed with emphasis on stability considerations. Real-time system control has only recently been considered as applicable to stability, using conventional control methods. The report considers the use of artificial neural networks to improve the stability of the power system. The networks are considered as adjuncts and as replacements for existing controllers. The optimal kind of network to use as an adjunct to a generator exciter is discussed.

Resting State Synchrony in Short-Term versus Long-Term Abstinent Alcoholics

PubMed Central

Camchong, Jazmin; Stenger, Victor Andrew; Fein, George

2012-01-01

BACKGROUND We previously reported that when compared to controls, long-term abstinent alcoholics (LTAA) have increased resting state synchrony (RSS) of the inhibitory control network and reduced synchrony of the appetitive drive network, and hypothesized that these levels of synchrony are adaptive, and support the behavioral changes required to maintain abstinence. In the current study, we investigate whether these RSS patterns can be identified in short-term abstinent alcoholics. METHODS Resting state functional magnetic resonance imaging data were collected from 27 short-term abstinent alcoholics (STAA), 23 LTAA and 23 non-substance abusing controls (NSAC). We examined baseline RSS using seed-based measures. RESULTS We found ordered RSS effects from NSAC to STAA and then to LTAA within both the appetitive drive and executive control networks: increasing RSS of the executive control network, and decreasing RSS of the reward processing network. Finally, we found significant correlations between strength of RSS in these networks and (a) cognitive flexibility and (b) current antisocial behavior. DISCUSSION Findings are consistent with an adaptive progression of RSS from short- to long-term abstinence so that, compared to normal controls, the synchrony (a) within the reward network progressively decreases and (b) within the executive control network progressively increases. PMID:23421812

Coactivation of cognitive control networks during task switching.

PubMed

Yin, Shouhang; Deák, Gedeon; Chen, Antao

2018-01-01

The ability to flexibly switch between tasks is considered an important component of cognitive control that involves frontal and parietal cortical areas. The present study was designed to characterize network dynamics across multiple brain regions during task switching. Functional magnetic resonance images (fMRI) were captured during a standard rule-switching task to identify switching-related brain regions. Multiregional psychophysiological interaction (PPI) analysis was used to examine effective connectivity between these regions. During switching trials, behavioral performance declined and activation of a generic cognitive control network increased. Concurrently, task-related connectivity increased within and between cingulo-opercular and fronto-parietal cognitive control networks. Notably, the left inferior frontal junction (IFJ) was most consistently coactivated with the 2 cognitive control networks. Furthermore, switching-dependent effective connectivity was negatively correlated with behavioral switch costs. The strength of effective connectivity between left IFJ and other regions in the networks predicted individual differences in switch costs. Task switching was supported by coactivated connections within cognitive control networks, with left IFJ potentially acting as a key hub between the fronto-parietal and cingulo-opercular networks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Fast packet switching algorithms for dynamic resource control over ATM networks

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

Tsang, R.P.; Keattihananant, P.; Chang, T.

1996-12-01

Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less

Complexity, Robustness, and Multistability in Network Systems with Switching Topologies: A Hierarchical Hybrid Control Approach

DTIC Science & Technology

2015-05-22

sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor

A Hybrid Authentication and Authorization Process for Control System Networks

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

Manz, David O.; Edgar, Thomas W.; Fink, Glenn A.

2010-08-25

Convergence of control system and IT networks require that security, privacy, and trust be addressed. Trust management continues to plague traditional IT managers and is even more complex when extended into control system networks, with potentially millions of entities, a mission that requires 100% availability. Yet these very networks necessitate a trusted secure environment where controllers and managers can be assured that the systems are secure and functioning properly. We propose a hybrid authentication management protocol that addresses the unique issues inherent within control system networks, while leveraging the considerable research and momentum in existing IT authentication schemes. Our hybridmore » authentication protocol for control systems provides end device to end device authentication within a remote station and between remote stations and control centers. Additionally, the hybrid protocol is failsafe and will not interrupt communication or control of vital systems in a network partition or device failure. Finally, the hybrid protocol is resilient to transitory link loss and can operate in an island mode until connectivity is reestablished.« less

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

NASA Astrophysics Data System (ADS)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

Neural-tree call admission controller for ATM networks

NASA Astrophysics Data System (ADS)

Rughooputh, Harry C. S.

1999-03-01

Asynchronous Transfer Mode (ATM) has been recommended by ITU-T as the transport method for broadband integrated services digital networks. In high-speed ATM networks different types of multimedia traffic streams with widely varying traffic characteristics and Quality of Service (QoS) are asynchronously multiplexed on transmission links and switched without window flow control as found in X.25. In such an environment, a traffic control scheme is required to manage the required QoS of each class individually. To meet the QoS requirements, Bandwidth Allocation and Call Admission Control (CAC) in ATM networks must be able to adapt gracefully to the dynamic behavior of traffic and the time-varying nature of the network condition. In this paper, a Neural Network approach for CAC is proposed. The call admission problem is addressed by designing controllers based on Neural Tree Networks. Simulations reveal that the proposed scheme is not only simple but it also offers faster response than conventional neural/neuro-fuzzy controllers.

Interaction Control to Synchronize Non-synchronizable Networks.

PubMed

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-11-17

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks' exact interaction topology and consequently have implications for biological and self-organizing technical systems.

Realizing actual feedback control of complex network

NASA Astrophysics Data System (ADS)

Tu, Chengyi; Cheng, Yuhua

2014-06-01

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

PubMed

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

DOT National Transportation Integrated Search

1996-01-01

An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

Method for neural network control of motion using real-time environmental feedback

NASA Technical Reports Server (NTRS)

Buckley, Theresa M. (Inventor)

1997-01-01

A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Williams-Hayes, Peggy; Kaneshige, John T.; Stachowiak, Susan J.

2006-01-01

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Williams-Hayes, Peggy; Karneshige, J. T.; Stachowiak, Susan J.

2006-01-01

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

A security architecture for health information networks.

PubMed

Kailar, Rajashekar; Muralidhar, Vinod

2007-10-11

Health information network security needs to balance exacting security controls with practicality, and ease of implementation in today's healthcare enterprise. Recent work on 'nationwide health information network' architectures has sought to share highly confidential data over insecure networks such as the Internet. Using basic patterns of health network data flow and trust models to support secure communication between network nodes, we abstract network security requirements to a core set to enable secure inter-network data sharing. We propose a minimum set of security controls that can be implemented without needing major new technologies, but yet realize network security and privacy goals of confidentiality, integrity and availability. This framework combines a set of technology mechanisms with environmental controls, and is shown to be sufficient to counter commonly encountered network security threats adequately.

Distinct brain networks for adaptive and stable task control in humans

PubMed Central

Dosenbach, Nico U. F.; Fair, Damien A.; Miezin, Francis M.; Cohen, Alexander L.; Wenger, Kristin K.; Dosenbach, Ronny A. T.; Fox, Michael D.; Snyder, Abraham Z.; Vincent, Justin L.; Raichle, Marcus E.; Schlaggar, Bradley L.; Petersen, Steven E.

2007-01-01

Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms. PMID:17576922

Neural Networks for Modeling and Control of Particle Accelerators

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

Edelen, A. L.; Biedron, S. G.; Chase, B. E.

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Neural Networks for Modeling and Control of Particle Accelerators

NASA Astrophysics Data System (ADS)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

2016-04-01

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Neural Networks for Modeling and Control of Particle Accelerators

DOE PAGES

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

2016-04-01

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

PubMed

Chen, Gang; Song, Yongduan; Guan, Yanfeng

2018-03-01

This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.

Neural network based automatic limit prediction and avoidance system and method

NASA Technical Reports Server (NTRS)

Calise, Anthony J. (Inventor); Prasad, Jonnalagadda V. R. (Inventor); Horn, Joseph F. (Inventor)

2001-01-01

A method for performance envelope boundary cueing for a vehicle control system comprises the steps of formulating a prediction system for a neural network and training the neural network to predict values of limited parameters as a function of current control positions and current vehicle operating conditions. The method further comprises the steps of applying the neural network to the control system of the vehicle, where the vehicle has capability for measuring current control positions and current vehicle operating conditions. The neural network generates a map of current control positions and vehicle operating conditions versus the limited parameters in a pre-determined vehicle operating condition. The method estimates critical control deflections from the current control positions required to drive the vehicle to a performance envelope boundary. Finally, the method comprises the steps of communicating the critical control deflection to the vehicle control system; and driving the vehicle control system to provide a tactile cue to an operator of the vehicle as the control positions approach the critical control deflections.

Interdependent networks: the fragility of control

PubMed Central

Morris, Richard G.; Barthelemy, Marc

2013-01-01

Recent work in the area of interdependent networks has focused on interactions between two systems of the same type. However, an important and ubiquitous class of systems are those involving monitoring and control, an example of interdependence between processes that are very different. In this Article, we introduce a framework for modelling ‘distributed supervisory control' in the guise of an electrical network supervised by a distributed system of control devices. The system is characterised by degrees of freedom salient to real-world systems— namely, the number of control devices, their inherent reliability, and the topology of the control network. Surprisingly, the behavior of the system depends crucially on the reliability of control devices. When devices are completely reliable, cascade sizes are percolation controlled; the number of devices being the relevant parameter. For unreliable devices, the topology of the control network is important and can dramatically reduce the resilience of the system. PMID:24067404

Reliable and Fault-Tolerant Software-Defined Network Operations Scheme for Remote 3D Printing

NASA Astrophysics Data System (ADS)

Kim, Dongkyun; Gil, Joon-Min

2015-03-01

The recent wide expansion of applicable three-dimensional (3D) printing and software-defined networking (SDN) technologies has led to a great deal of attention being focused on efficient remote control of manufacturing processes. SDN is a renowned paradigm for network softwarization, which has helped facilitate remote manufacturing in association with high network performance, since SDN is designed to control network paths and traffic flows, guaranteeing improved quality of services by obtaining network requests from end-applications on demand through the separated SDN controller or control plane. However, current SDN approaches are generally focused on the controls and automation of the networks, which indicates that there is a lack of management plane development designed for a reliable and fault-tolerant SDN environment. Therefore, in addition to the inherent advantage of SDN, this paper proposes a new software-defined network operations center (SD-NOC) architecture to strengthen the reliability and fault-tolerance of SDN in terms of network operations and management in particular. The cooperation and orchestration between SDN and SD-NOC are also introduced for the SDN failover processes based on four principal SDN breakdown scenarios derived from the failures of the controller, SDN nodes, and connected links. The abovementioned SDN troubles significantly reduce the network reachability to remote devices (e.g., 3D printers, super high-definition cameras, etc.) and the reliability of relevant control processes. Our performance consideration and analysis results show that the proposed scheme can shrink operations and management overheads of SDN, which leads to the enhancement of responsiveness and reliability of SDN for remote 3D printing and control processes.

OXC management and control system architecture with scalability, maintenance, and distributed managing environment

NASA Astrophysics Data System (ADS)

Park, Soomyung; Joo, Seong-Soon; Yae, Byung-Ho; Lee, Jong-Hyun

2002-07-01

In this paper, we present the Optical Cross-Connect (OXC) Management Control System Architecture, which has the scalability and robust maintenance and provides the distributed managing environment in the optical transport network. The OXC system we are developing, which is divided into the hardware and the internal and external software for the OXC system, is made up the OXC subsystem with the Optical Transport Network (OTN) sub layers-hardware and the optical switch control system, the signaling control protocol subsystem performing the User-to-Network Interface (UNI) and Network-to-Network Interface (NNI) signaling control, the Operation Administration Maintenance & Provisioning (OAM&P) subsystem, and the network management subsystem. And the OXC management control system has the features that can support the flexible expansion of the optical transport network, provide the connectivity to heterogeneous external network elements, be added or deleted without interrupting OAM&P services, be remotely operated, provide the global view and detail information for network planner and operator, and have Common Object Request Broker Architecture (CORBA) based the open system architecture adding and deleting the intelligent service networking functions easily in future. To meet these considerations, we adopt the object oriented development method in the whole developing steps of the system analysis, design, and implementation to build the OXC management control system with the scalability, the maintenance, and the distributed managing environment. As a consequently, the componentification for the OXC operation management functions of each subsystem makes the robust maintenance, and increases code reusability. Also, the component based OXC management control system architecture will have the flexibility and scalability in nature.

Evolutionary transitions in controls reconcile adaptation with continuity of evolution.

PubMed

Badyaev, Alexander V

2018-05-19

Evolution proceeds by accumulating functional solutions, necessarily forming an uninterrupted lineage from past solutions of ancestors to the current design of extant forms. At the population level, this process requires an organismal architecture in which the maintenance of local adaptation does not preclude the ability to innovate in the same traits and their continuous evolution. Representing complex traits as networks enables us to visualize a fundamental principle that resolves tension between adaptation and continuous evolution: phenotypic states encompassing adaptations traverse the continuous multi-layered landscape of past physical, developmental and functional associations among traits. The key concept that captures such traversing is network controllability - the ability to move a network from one state into another while maintaining its functionality (reflecting evolvability) and to efficiently propagate information or products through the network within a phenotypic state (maintaining its robustness). Here I suggest that transitions in network controllability - specifically in the topology of controls - help to explain how robustness and evolvability are balanced during evolution. I will focus on evolutionary transitions in degeneracy of metabolic networks - a ubiquitous property of phenotypic robustness where distinct pathways achieve the same end product - to suggest that associated changes in network controls is a common rule underlying phenomena as distinct as phenotypic plasticity, organismal accommodation of novelties, genetic assimilation, and macroevolutionary diversification. Capitalizing on well understood principles by which network structure translates into function of control nodes, I show that accumulating redundancy in one type of network controls inevitably leads to the emergence of another type of controls, forming evolutionary cycles of network controllability that, ultimately, reconcile local adaptation with continuity of evolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Top-Down Network Effective Connectivity in Abstinent Substance Dependent Individuals

PubMed Central

Regner, Michael F.; Saenz, Naomi; Maharajh, Keeran; Yamamoto, Dorothy J.; Mohl, Brianne; Wylie, Korey; Tregellas, Jason; Tanabe, Jody

2016-01-01

Objective We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. Methods 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI. fMRI results were analyzed using group independent component analysis; 14 networks-of-interest (NOI) were selected using template matching to a canonical set of resting state networks. The number, direction, and strength of connections between NOI were analyzed with Granger Causality. Within-group thresholds were p<0.005 using a bootstrap permutation. Between group thresholds were p<0.05, FDR-corrected for multiple comparisons. NOI were correlated with behavioral measures, and group-level graph theory measures were compared. Results Compared to controls, SDI showed significantly greater Granger causal connectivity from right executive control network (RECN) to dorsal default mode network (dDMN) and from dDMN to basal ganglia network (BGN). RECN was negatively correlated with impulsivity, behavioral approach, and negative affect; dDMN was positively correlated with impulsivity. Among the 14 NOI, SDI showed greater bidirectional connectivity; controls showed more unidirectional connectivity. SDI demonstrated greater global efficiency and lower local efficiency. Conclusions Increased effective connectivity in long-term abstinent drug users may reflect improved cognitive control over habit and reward processes. Higher global and lower local efficiency across all networks in SDI compared to controls may reflect connectivity changes associated with drug dependence or remission and requires future, longitudinal studies to confirm. PMID:27776135

Functional resting-state networks are differentially affected in schizophrenia

PubMed Central

Woodward, Neil D.; Rogers, Baxter; Heckers, Stephan

2011-01-01

Neurobiological theories posit that schizophrenia relates to disturbances in connectivity between brain regions. Resting-state functional magnetic resonance imaging is a powerful tool for examining functional connectivity and has revealed several canonical brain networks, including the default mode, dorsal attention, executive control, and salience networks. The purpose of this study was to examine changes in these networks in schizophrenia. 42 patients with schizophrenia and 61 healthy subjects completed a RS-fMRI scanning session. Seed-based region-of-interest correlation analysis was used to identify the default mode, dorsal attention, executive control, and salience networks. Compared to healthy subjects, individuals with schizophrenia demonstrated greater connectivity between the posterior cingulate cortex, a key hub of the default mode, and the left inferior gyrus, left middle frontal gyrus, and left middle temporal gyrus. Interestingly, these regions were more strongly connected to the executive control network in healthy control subjects. In contrast to the default mode, patients demonstrated less connectivity in the executive control and dorsal attention networks. No differences were observed in the salience network. The results indicate that resting-state networks are differentially affected in schizophrenia. The alterations are characterized by reduced segregation between the default mode and executive control networks in the prefrontal cortex and temporal lobe, and reduced connectivity in the dorsal attention and executive control networks. The changes suggest that the process of functional specialization is altered in schizophrenia. Further work is needed to determine if the alterations are related to disturbances in white matter connectivity, neurodevelopmental abnormalities, and genetic risk for schizophrenia. PMID:21458238

NIC atomic operation unit with caching and bandwidth mitigation

DOEpatents

Hemmert, Karl Scott; Underwood, Keith D.; Levenhagen, Michael J.

2016-03-01

A network interface controller atomic operation unit and a network interface control method comprising, in an atomic operation unit of a network interface controller, using a write-through cache and employing a rate-limiting functional unit.

The Weight-control Information Network (WIN) | NIH MedlinePlus the Magazine

MedlinePlus

... Javascript on. Feature: Reducing Childhood Obesity The Weight-control Information Network (WIN) Past Issues / Spring - Summer 2010 ... overweight children, here are tips from the Weight-control Information Network (WIN), an information service of the ...

Neural joint control for Space Shuttle Remote Manipulator System

NASA Technical Reports Server (NTRS)

Atkins, Mark A.; Cox, Chadwick J.; Lothers, Michael D.; Pap, Robert M.; Thomas, Charles R.

1992-01-01

Neural networks are being used to control a robot arm in a telerobotic operation. The concept uses neural networks for both joint and inverse kinematics in a robotic control application. An upper level neural network is trained to learn inverse kinematic mappings. The output, a trajectory, is then fed to the Decentralized Adaptive Joint Controllers. This neural network implementation has shown that the controlled arm recovers from unexpected payload changes while following the reference trajectory. The neural network-based decentralized joint controller is faster, more robust and efficient than conventional approaches. Implementations of this architecture are discussed that would relax assumptions about dynamics, obstacles, and heavy loads. This system is being developed to use with the Space Shuttle Remote Manipulator System.

Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1997-01-01

A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

Robustness of Controllability for Networks Based on Edge-Attack

PubMed Central

Nie, Sen; Wang, Xuwen; Zhang, Haifeng; Li, Qilang; Wang, Binghong

2014-01-01

We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdős-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components. PMID:24586507

Robustness of controllability for networks based on edge-attack.

PubMed

Nie, Sen; Wang, Xuwen; Zhang, Haifeng; Li, Qilang; Wang, Binghong

2014-01-01

We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdős-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components.

Optimal control of epidemic information dissemination over networks.

PubMed

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor); Konz, Daniel W. (Inventor)

2009-01-01

A communications system and method are provided for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. Network device interfaces associated with different data channels can coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

Distributed intelligent control and status networking

NASA Technical Reports Server (NTRS)

Fortin, Andre; Patel, Manoj

1993-01-01

Over the past two years, the Network Control Systems Branch (Code 532) has been investigating control and status networking technologies. These emerging technologies use distributed processing over a network to accomplish a particular custom task. These networks consist of small intelligent 'nodes' that perform simple tasks. Containing simple, inexpensive hardware and software, these nodes can be easily developed and maintained. Once networked, the nodes can perform a complex operation without a central host. This type of system provides an alternative to more complex control and status systems which require a central computer. This paper will provide some background and discuss some applications of this technology. It will also demonstrate the suitability of one particular technology for the Space Network (SN) and discuss the prototyping activities of Code 532 utilizing this technology.

Thermoelastic steam turbine rotor control based on neural network

NASA Astrophysics Data System (ADS)

Rzadkowski, Romuald; Dominiczak, Krzysztof; Radulski, Wojciech; Szczepanik, R.

2015-12-01

Considered here are Nonlinear Auto-Regressive neural networks with eXogenous inputs (NARX) as a mathematical model of a steam turbine rotor for controlling steam turbine stress on-line. In order to obtain neural networks that locate critical stress and temperature points in the steam turbine during transient states, an FE rotor model was built. This model was used to train the neural networks on the basis of steam turbine transient operating data. The training included nonlinearity related to steam turbine expansion, heat exchange and rotor material properties during transients. Simultaneous neural networks are algorithms which can be implemented on PLC controllers. This allows for the application neural networks to control steam turbine stress in industrial power plants.

Stochastic Characterization of Communication Network Latency for Wide Area Grid Control Applications.

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

Ameme, Dan Selorm Kwami; Guttromson, Ross

This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selectionmore » within the simulated network.« less

Warnings and caveats in brain controllability.

PubMed

Tu, Chengyi; Rocha, Rodrigo P; Corbetta, Maurizio; Zampieri, Sandro; Zorzi, Marco; Suweis, S

2018-08-01

A recent article by Gu et al. (Nat. Commun. 6, 2015) proposed to characterize brain networks, quantified using anatomical diffusion imaging, in terms of their "controllability", drawing on concepts and methods of control theory. They reported that brain activity is controllable from a single node, and that the topology of brain networks provides an explanation for the types of control roles that different regions play in the brain. In this work, we first briefly review the framework of control theory applied to complex networks. We then show contrasting results on brain controllability through the analysis of five different datasets and numerical simulations. We find that brain networks are not controllable (in a statistical significant way) by one single region. Additionally, we show that random null models, with no biological resemblance to brain network architecture, produce the same type of relationship observed by Gu et al. between the average/modal controllability and weighted degree. Finally, we find that resting state networks defined with fMRI cannot be attributed specific control roles. In summary, our study highlights some warning and caveats in the brain controllability framework. Copyright © 2018 Elsevier Inc. All rights reserved.

The deep space network, volume 18. [Deep Space Instrumentation Facility, Ground Communication Facility, and Network Control System

NASA Technical Reports Server (NTRS)

1973-01-01

The objectives, functions, and organization of the Deep Space Network are summarized. The Deep Space Instrumentation Facility, the Ground Communications Facility, and the Network Control System are described.

Network Monitor and Control of Disruption-Tolerant Networks

NASA Technical Reports Server (NTRS)

Torgerson, J. Leigh

2014-01-01

For nearly a decade, NASA and many researchers in the international community have been developing Internet-like protocols that allow for automated network operations in networks where the individual links between nodes are only sporadically connected. A family of Disruption-Tolerant Networking (DTN) protocols has been developed, and many are reaching CCSDS Blue Book status. A NASA version of DTN known as the Interplanetary Overlay Network (ION) has been flight-tested on the EPOXI spacecraft and ION is currently being tested on the International Space Station. Experience has shown that in order for a DTN service-provider to set up a large scale multi-node network, a number of network monitor and control technologies need to be fielded as well as the basic DTN protocols. The NASA DTN program is developing a standardized means of querying a DTN node to ascertain its operational status, known as the DTN Management Protocol (DTNMP), and the program has developed some prototypes of DTNMP software. While DTNMP is a necessary component, it is not sufficient to accomplish Network Monitor and Control of a DTN network. JPL is developing a suite of tools that provide for network visualization, performance monitoring and ION node control software. This suite of network monitor and control tools complements the GSFC and APL-developed DTN MP software, and the combined package can form the basis for flight operations using DTN.

Reconfigurable Control Design with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

The viewgraphs present background information about reconfiguration control design, design methods used for paper, control failure survivability results, and results and time histories of tests. Topics examined include control reconfiguration, general information about adaptive controllers, model reference adaptive control (MRAC), the utility of neural networks, radial basis functions (RBF) neural network outputs, neurons, and results of investigations of failures.

Altered resting-state frontoparietal control network in children with attention-deficit/hyperactivity disorder.

PubMed

Lin, Hsiang-Yuan; Tseng, Wen-Yih Isaac; Lai, Meng-Chuan; Matsuo, Kayako; Gau, Susan Shur-Fen

2015-04-01

The frontoparietal control network, anatomically and functionally interposed between the dorsal attention network and default mode network, underpins executive control functions. Individuals with attention-deficit/hyperactivity disorder (ADHD) commonly exhibit deficits in executive functions, which are mainly mediated by the frontoparietal control network. Involvement of the frontoparietal control network based on the anterior prefrontal cortex in neurobiological mechanisms of ADHD has yet to be tested. We used resting-state functional MRI and seed-based correlation analyses to investigate functional connectivity of the frontoparietal control network in a sample of 25 children with ADHD (7-14 years; mean 9.94 ± 1.77 years; 20 males), and 25 age-, sex-, and performance IQ-matched typically developing (TD) children. All participants had limited in-scanner head motion. Spearman's rank correlations were used to test the associations between altered patterns of functional connectivity with clinical symptoms and executive functions, measured by the Conners' Continuous Performance Test and Spatial Span in the Cambridge Neuropsychological Test Automated Battery. Compared with TD children, children with ADHD demonstrated weaker connectivity between the right anterior prefrontal cortex (PFC) and the right ventrolateral PFC, and between the left anterior PFC and the right inferior parietal lobule. Furthermore, this aberrant connectivity of the frontoparietal control network in ADHD was associated with symptoms of impulsivity and opposition-defiance, as well as impaired response inhibition and attentional control. The findings support potential integration of the disconnection model and the executive dysfunction model for ADHD. Atypical frontoparietal control network may play a pivotal role in the pathophysiology of ADHD.

A network architecture for International Business Satellite communications

NASA Astrophysics Data System (ADS)

Takahata, Fumio; Nohara, Mitsuo; Takeuchi, Yoshio

Demand Assignment (DA) control is expected to be introduced in the International Business Satellte communications (IBS) network in order to cope with a growing international business traffic. The paper discusses the DA/IBS network from the viewpoints of network configuration, satellite channel configuration and DA control. The network configuration proposed here consists of one Central Station with network management function and several Network Coordination Stations with user management function. A satellite channel configuration is also presented along with a tradeoff study on transmission bit rate, high power amplifier output power requirement, and service quality. The DA control flow and protocol based on CCITT Signalling System No. 7 are also proposed.

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

NASA Astrophysics Data System (ADS)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

Main control computer security model of closed network systems protection against cyber attacks

NASA Astrophysics Data System (ADS)

Seymen, Bilal

2014-06-01

The model that brings the data input/output under control in closed network systems, that maintains the system securely, and that controls the flow of information through the Main Control Computer which also brings the network traffic under control against cyber-attacks. The network, which can be controlled single-handedly thanks to the system designed to enable the network users to make data entry into the system or to extract data from the system securely, intends to minimize the security gaps. Moreover, data input/output record can be kept by means of the user account assigned for each user, and it is also possible to carry out retroactive tracking, if requested. Because the measures that need to be taken for each computer on the network regarding cyber security, do require high cost; it has been intended to provide a cost-effective working environment with this model, only if the Main Control Computer has the updated hardware.

Neural networks for function approximation in nonlinear control

NASA Technical Reports Server (NTRS)

Linse, Dennis J.; Stengel, Robert F.

1990-01-01

Two neural network architectures are compared with a classical spline interpolation technique for the approximation of functions useful in a nonlinear control system. A standard back-propagation feedforward neural network and a cerebellar model articulation controller (CMAC) neural network are presented, and their results are compared with a B-spline interpolation procedure that is updated using recursive least-squares parameter identification. Each method is able to accurately represent a one-dimensional test function. Tradeoffs between size requirements, speed of operation, and speed of learning indicate that neural networks may be practical for identification and adaptation in a nonlinear control environment.

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Network Controllability in the Inferior Frontal Gyrus Relates to Controlled Language Variability and Susceptibility to TMS.

PubMed

Medaglia, John D; Harvey, Denise Y; White, Nicole; Kelkar, Apoorva; Zimmerman, Jared; Bassett, Danielle S; Hamilton, Roy H

2018-06-08

In language production, humans are confronted with considerable word selection demands. Often, we must select a word from among similar, acceptable, and competing alternative words in order to construct a sentence that conveys an intended meaning. In recent years, the left inferior frontal gyrus (LIFG) has been identified as critical to this ability. Despite a recent emphasis on network approaches to understanding language, how the LIFG interacts with the brain's complex networks to facilitate controlled language performance remains unknown. Here, we take a novel approach to understand word selection as a network control process in the brain. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we computed network controllability underlying the site of transcranial magnetic stimulation in the LIFG between administrations of language tasks that vary in response (cognitive control) demands: open-response (word generation) vs. closed-response (number naming) tasks. We find that a statistic that quantifies the LIFG's theoretically predicted control of communication across modules in the human connectome explains TMS-induced changes in open-response language task performance only. Moreover, we find that a statistic that quantifies the LIFG's theoretically predicted control of difficult-to-reach states explains vulnerability to TMS in the closed-ended (but not open-ended) response task. These findings establish a link between network controllability, cognitive function, and TMS effects. SIGNIFICANCE STATEMENT This work illustrates that network control statistics applied to anatomical connectivity data demonstrate relationships with cognitive variability during controlled language tasks and TMS effects. Copyright © 2018 the authors.

Performance analysis of SS7 congestion controls under sustained overload

NASA Astrophysics Data System (ADS)

Manfield, David R.; Millsteed, Gregory K.; Zukerman, Moshe

1994-04-01

Congestion controls are a key factor in achieving the robust performance required of common channel signaling (CCS) networks in the face of partial network failures and extreme traffic loads, especially as networks become large and carry high traffic volume. The CCITT recommendations define a number of types of congestion control, and the parameters of the controls must be well set in order to ensure their efficacy under transient and sustained signalling network overload. The objective of this paper is to present a modeling approach to the determination of the network parameters that govern the performance of the SS7 congestion controls under sustained overload. Results of the investigation by simulation are presented and discussed.

Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays.

PubMed

Tang, Xiaoming; Qu, Hongchun; Wang, Ping; Zhao, Meng

2015-03-01

This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S-A) and controller to actuator (C-A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A Security Architecture for Health Information Networks

PubMed Central

Kailar, Rajashekar

2007-01-01

Health information network security needs to balance exacting security controls with practicality, and ease of implementation in today’s healthcare enterprise. Recent work on ‘nationwide health information network’ architectures has sought to share highly confidential data over insecure networks such as the Internet. Using basic patterns of health network data flow and trust models to support secure communication between network nodes, we abstract network security requirements to a core set to enable secure inter-network data sharing. We propose a minimum set of security controls that can be implemented without needing major new technologies, but yet realize network security and privacy goals of confidentiality, integrity and availability. This framework combines a set of technology mechanisms with environmental controls, and is shown to be sufficient to counter commonly encountered network security threats adequately. PMID:18693862

An intelligent control system for failure detection and controller reconfiguration

NASA Technical Reports Server (NTRS)

Biswas, Saroj K.

1994-01-01

We present an architecture of an intelligent restructurable control system to automatically detect failure of system components, assess its impact on system performance and safety, and reconfigure the controller for performance recovery. Fault detection is based on neural network associative memories and pattern classifiers, and is implemented using a multilayer feedforward network. Details of the fault detection network along with simulation results on health monitoring of a dc motor have been presented. Conceptual developments for fault assessment using an expert system and controller reconfiguration using a neural network are outlined.

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-19

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-01

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. PMID:26797616

An Artificial Neural Network Control System for Spacecraft Attitude Stabilization

DTIC Science & Technology

1990-06-01

NAVAL POSTGRADUATE SCHOOL Monterey, California ’-DTIC 0 ELECT f NMARO 5 191 N S, U, THESIS B . AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR...NO. NO. NO ACCESSION NO 11. TITLE (Include Security Classification) AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR SPACECRAFT ATTITUDE STABILIZATION...obsolete a U.S. G v pi.. iim n P.. oiice! toog-eo.5s43 i Approved for public release; distribution is unlimited. AN ARTIFICIAL NEURAL NETWORK CONTROL

Congestion control and routing over satellite networks

NASA Astrophysics Data System (ADS)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE) method and then develop a novel on-demand routing system named Cross Entropy Accelerated Ant Routing System (CEAARS) for regular constellation LEO satellite networks. By implementing simulations on an Iridium-like satellite network, we compare the proposed CEAARS algorithm with the two approaches to adaptive routing protocols on the Internet: distance-vector (DV) and link-state (LS), as well as with the original Cross Entropy Ant Routing System (CEARS). DV algorithms are based on distributed Bellman Ford algorithm, and LS algorithms are implementation of Dijkstras single source shortest path. The results show that CEAARS not only remarkably improves the convergence speed of achieving optimal or suboptimal paths, but also reduces the number of overhead ants (management packets).

Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

PubMed Central

Ehrens, Daniel; Sritharan, Duluxan; Sarma, Sridevi V.

2015-01-01

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the unstable mode from using the firing rate of the most fragile node in the network (which is the output of the HMM). When the unstable mode is detected, a state-feedback gain is applied to generate a control input to the fragile node bringing the network back to the stable mode. Finally, when the network is detected as stable again, the feedback control input is switched off. High performance was achieved for the stability detector, and feedback control suppressed seizures within 2 s after onset. PMID:25784851

Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions.

PubMed

Li, Shuhui; Fairbank, Michael; Johnson, Cameron; Wunsch, Donald C; Alonso, Eduardo; Proaño, Julio L

2014-04-01

Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using back-propagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

Synchronization criteria for generalized reaction-diffusion neural networks via periodically intermittent control.

PubMed

Gan, Qintao; Lv, Tianshi; Fu, Zhenhua

2016-04-01

In this paper, the synchronization problem for a class of generalized neural networks with time-varying delays and reaction-diffusion terms is investigated concerning Neumann boundary conditions in terms of p-norm. The proposed generalized neural networks model includes reaction-diffusion local field neural networks and reaction-diffusion static neural networks as its special cases. By establishing a new inequality, some simple and useful conditions are obtained analytically to guarantee the global exponential synchronization of the addressed neural networks under the periodically intermittent control. According to the theoretical results, the influences of diffusion coefficients, diffusion space, and control rate on synchronization are analyzed. Finally, the feasibility and effectiveness of the proposed methods are shown by simulation examples, and by choosing different diffusion coefficients, diffusion spaces, and control rates, different controlled synchronization states can be obtained.

A Network Scheduling Model for Distributed Control Simulation

NASA Technical Reports Server (NTRS)

Culley, Dennis; Thomas, George; Aretskin-Hariton, Eliot

2016-01-01

Distributed engine control is a hardware technology that radically alters the architecture for aircraft engine control systems. Of its own accord, it does not change the function of control, rather it seeks to address the implementation issues for weight-constrained vehicles that can limit overall system performance and increase life-cycle cost. However, an inherent feature of this technology, digital communication networks, alters the flow of information between critical elements of the closed-loop control. Whereas control information has been available continuously in conventional centralized control architectures through virtue of analog signaling, moving forward, it will be transmitted digitally in serial fashion over the network(s) in distributed control architectures. An underlying effect is that all of the control information arrives asynchronously and may not be available every loop interval of the controller, therefore it must be scheduled. This paper proposes a methodology for modeling the nominal data flow over these networks and examines the resulting impact for an aero turbine engine system simulation.

Usefulness of Neuro-Fuzzy Models' Application for Tobacco Control

NASA Astrophysics Data System (ADS)

Petrovic-Lazarevic, Sonja; Zhang, Jian Ying

2007-12-01

The paper presents neuro-fuzzy models' application appropriate for tobacco control: the fuzzy control model, Adaptive Network Based Fuzzy Inference System, Evolving Fuzzy Neural Network models, and EVOlving POLicies. We propose further the use of Fuzzy Casual Networks to help tobacco control decision makers develop policies and measure their impact on social regulation.

Passivity and Dissipativity as Design and Analysis Tools for Networked Control Systems

ERIC Educational Resources Information Center

Yu, Han

2012-01-01

In this dissertation, several control problems are studied that arise when passive or dissipative systems are interconnected and controlled over a communication network. Since communication networks can impact the systems' stability and performance, there is a need to extend the results on control of passive or dissipative systems to networked…

Distributed synchronization control of complex networks with communication constraints.

PubMed

Xu, Zhenhua; Zhang, Dan; Song, Hongbo

2016-11-01

This paper is concerned with the distributed synchronization control of complex networks with communication constraints. In this work, the controllers communicate with each other through the wireless network, acting as a controller network. Due to the constrained transmission power, techniques such as the packet size reduction and transmission rate reduction schemes are proposed which could help reduce communication load of the controller network. The packet dropout problem is also considered in the controller design since it is often encountered in networked control systems. We show that the closed-loop system can be modeled as a switched system with uncertainties and random variables. By resorting to the switched system approach and some stochastic system analysis method, a new sufficient condition is firstly proposed such that the exponential synchronization is guaranteed in the mean-square sense. The controller gains are determined by using the well-known cone complementarity linearization (CCL) algorithm. Finally, a simulation study is performed, which demonstrates the effectiveness of the proposed design algorithm. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamical behaviours and control measures of rumour-spreading model with consideration of network topology

NASA Astrophysics Data System (ADS)

Zhu, Linhe; Zhao, Hongyong

2017-07-01

A series of online rumours have seriously influenced the normal production and living of people. This paper aims to study the combined impact of psychological factor, propagation delay, network topology and control strategy on rumour diffusion over the online social networks. Based on an online social network, which is seen as a scale-free network, we model the spread of rumours by using a delayed SIS (Susceptible and Infected) epidemic-like model with consideration of psychological factor and network topology. First, through theoretical analysis, we illustrate the boundedness of the density of rumour-susceptible individuals and rumour-infected individuals. Second, we obtain the basic reproduction number R0 and prove the stability of the non-rumour equilibrium point and the rumour-spreading equilibrium point. Third, control strategies, such as uniform immunisation control, proportional immunisation control, targeted immunisation control and optimum control, are put forward to restrain rumour diffusion. Meanwhile, we have compared the differences of these control strategies. Finally, some representative numerical simulations are performed to verify the theoretical analysis results.

Planning assistance for the NASA 30/20 GHz program. Network control architecture study.

NASA Technical Reports Server (NTRS)

Inukai, T.; Bonnelycke, B.; Strickland, S.

1982-01-01

Network Control Architecture for a 30/20 GHz flight experiment system operating in the Time Division Multiple Access (TDMA) was studied. Architecture development, identification of processing functions, and performance requirements for the Master Control Station (MCS), diversity trunking stations, and Customer Premises Service (CPS) stations are covered. Preliminary hardware and software processing requirements as well as budgetary cost estimates for the network control system are given. For the trunking system control, areas covered include on board SS-TDMA switch organization, frame structure, acquisition and synchronization, channel assignment, fade detection and adaptive power control, on board oscillator control, and terrestrial network timing. For the CPS control, they include on board processing and adaptive forward error correction control.

Fuzzy and neural control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Control of autonomous robot using neural networks

NASA Astrophysics Data System (ADS)

Barton, Adam; Volna, Eva

2017-07-01

The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

Epigenetics and Why Biological Networks are More Controllable than Expected

NASA Astrophysics Data System (ADS)

Motter, Adilson

2013-03-01

A fundamental property of networks is that perturbations to one node can affect other nodes, potentially causing the entire system to change behavior or fail. In this talk, I will show that it is possible to exploit this same principle to control network behavior. This approach takes advantage of the nonlinear dynamics inherent to real networks, and allows bringing the system to a desired target state even when this state is not directly accessible or the linear counterpart is not controllable. Applications show that this framework permits both reprogramming a network to a desired task as well as rescuing networks from the brink of failure, which I will illustrate through various biological problems. I will also briefly review the progress our group has made over the past 5 years on related control of complex networks in non-biological domains.

Neural network for control of rearrangeable Clos networks.

PubMed

Park, Y K; Cherkassky, V

1994-09-01

Rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. The multistage crossbar networks have always been attractive to switch designers. In this paper a neural network approach to controlling a three-stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections, with a minimum length of rearrangement sequence so that a new blocked call request can be accommodated. The proposed neural network controller uses Paull's rearrangement algorithm, along with the special (least used) switch selection rule in order to minimize the length of rearrangement sequences. The functional behavior of our model is verified by simulations and it is shown that the convergence time required for finding an optimal solution is constant, regardless of the switching network size. The performance is evaluated for random traffic with various traffic loads. Simulation results show that applying the least used switch selection rule increases the efficiency in switch rearrangements, reducing the network convergence time. The implementation aspects are also discussed to show the feasibility of the proposed approach.

Thalamocortical functional connectivity in Lennox-Gastaut syndrome is abnormally enhanced in executive-control and default-mode networks.

PubMed

Warren, Aaron E L; Abbott, David F; Jackson, Graeme D; Archer, John S

2017-12-01

To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that the mediodorsal and ventrolateral thalamus may be candidate targets for modulating abnormal network behavior underlying LGS, potentially via emerging thalamic neurostimulation therapies. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

Newly developed double neural network concept for reliable fast plasma position control

NASA Astrophysics Data System (ADS)

Jeon, Young-Mu; Na, Yong-Su; Kim, Myung-Rak; Hwang, Y. S.

2001-01-01

Neural network is considered as a parameter estimation tool in plasma controls for next generation tokamak such as ITER. The neural network has been reported to be so accurate and fast for plasma equilibrium identification that it may be applied to the control of complex tokamak plasmas. For this application, the reliability of the conventional neural network needs to be improved. In this study, a new idea of double neural network is developed to achieve this. The new idea has been applied to simple plasma position identification of KSTAR tokamak for feasibility test. Characteristics of the concept show higher reliability and fault tolerance even in severe faulty conditions, which may make neural network applicable to plasma control reliably and widely in future tokamaks.

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

PubMed Central

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

Quality of service policy control in virtual private networks

NASA Astrophysics Data System (ADS)

Yu, Yiqing; Wang, Hongbin; Zhou, Zhi; Zhou, Dongru

2004-04-01

This paper studies the QoS of VPN in an environment where the public network prices connection-oriented services based on source, destination and grade of service, and advertises these prices to its VPN customers (users). As different QoS technologies can produce different QoS, there are according different traffic classification rules and priority rules. The internet service provider (ISP) may need to build complex mechanisms separately for each node. In order to reduce the burden of network configuration, we need to design policy control technologies. We considers mainly directory server, policy server, policy manager and policy enforcers. Policy decision point (PDP) decide its control according to policy rules. In network, policy enforce point (PEP) decide its network controlled unit. For InterServ and DiffServ, we will adopt different policy control methods as following: (1) In InterServ, traffic uses resource reservation protocol (RSVP) to guarantee the network resource. (2) In DiffServ, policy server controls the DiffServ code points and per hop behavior (PHB), its PDP distributes information to each network node. Policy server will function as following: information searching; decision mechanism; decision delivering; auto-configuration. In order to prove the effectiveness of QoS policy control, we make the corrective simulation.

EFG Ribbon Technology

NASA Astrophysics Data System (ADS)

Schwirtlich, I. A.

Since the beginning of solar cell development based on crystalline silicon, there have been efforts to produce wafers directly from the melt instead of through crystallization of ingots. Ingots require slicing into the blocs and wafers which form the basis of solar cells. In the last 30 years, several dozen processes have been published that describe a variety of concepts. Only few of these processes could be developed to an acceptable degree of technical maturity. Among those successful technologies are the Dendritic Web process, the Edge Supported Pulling (ESP) process and the Edge-Defined-Film-Fed-Growth (EFG) process. The EFG Process was originally developed by Mobil Solar and, since the mid-1990s, belongs to SCHOTT Solar GmbH and its predecessors, respectively. The Ribbon Growth on Substrate (RGS) process was originally developed by Bayer AG and is now in a pilot project at the ECN, Petten. Considering the past 20 to 30 years, the EFG process has reached the most advanced state in terms of industrialization.

Critical Characteristics of Radiation Detection System Components to be Dedicated for use in Safety Class and Safety Significant System

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

DAVIS, S.J.

2000-05-25

This document identifies critical characteristics of components to be dedicated for use in Safety Class (SC) or Safety Significant (SS) Systems, Structures, or Components (SSCs). This document identifies the requirements for the components of the common radiation area monitor alarm in the WESF pool cell. These are procured as Commercial Grade Items (CGI), with the qualification testing and formal dedication to be performed at the Waste Encapsulation Storage Facility (WESF), in safety class, safety significant systems. System modifications are to be performed in accordance with the instructions provided on ECN 658230. Components for this change are commercially available and interchangeablemore » with the existing alarm configuration This document focuses on the operational requirements for alarm, declaration of the safety classification, identification of critical characteristics, and interpretation of requirements for procurement. Critical characteristics are identified herein and must be verified, followed by formal dedication, prior to the components being used in safety related applications.« less

IEA Wind Task 26. Wind Technology, Cost and Performance Trends in Denmark, Germany, Ireland, Norway, the European Union, and the United States. 2007 - 2012

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

Vitina, Aisma; Luers, Silke; Wallasch, Anna-Kathrin

This report builds from a similar previous analysis (Schwabe et al., 2011) exploring the differences in cost of wind energy in 2008 among countries participating in IEA Wind Task 26 at that time. The levelized cost of energy (LCOE) is a widely recognized metric for understanding how technology, capital investment, operations, and financing impact the life-cycle cost of building and operating a wind plant. Schwabe et al. (2011) apply a spreadsheet-based cash flow model developed by the Energy Research Centre of the Netherlands (ECN) to estimate LCOE. This model is a detailed, discounted cash flow model used to represent themore » various cost structures in each of the participating countries from the perspective of a financial investor in a domestic wind energy project. This model is used for the present analysis as well, and comparisons are made for those countries who contributed to both reports, Denmark, Germany, and the United States.« less

Artificial bee colony algorithm for single-trial electroencephalogram analysis.

PubMed

Hsu, Wei-Yen; Hu, Ya-Ping

2015-04-01

In this study, we propose an analysis system combined with feature selection to further improve the classification accuracy of single-trial electroencephalogram (EEG) data. Acquiring event-related brain potential data from the sensorimotor cortices, the system comprises artifact and background noise removal, feature extraction, feature selection, and feature classification. First, the artifacts and background noise are removed automatically by means of independent component analysis and surface Laplacian filter, respectively. Several potential features, such as band power, autoregressive model, and coherence and phase-locking value, are then extracted for subsequent classification. Next, artificial bee colony (ABC) algorithm is used to select features from the aforementioned feature combination. Finally, selected subfeatures are classified by support vector machine. Comparing with and without artifact removal and feature selection, using a genetic algorithm on single-trial EEG data for 6 subjects, the results indicate that the proposed system is promising and suitable for brain-computer interface applications. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Quantitative EEG and Current Source Density Analysis of Combined Antiepileptic Drugs and Dopaminergic Agents in Genetic Epilepsy: Two Case Studies.

PubMed

Emory, Hamlin; Wells, Christopher; Mizrahi, Neptune

2015-07-01

Two adolescent females with absence epilepsy were classified, one as attention deficit and the other as bipolar disorder. Physical and cognitive exams identified hypotension, bradycardia, and cognitive dysfunction. Their initial electroencephalograms (EEGs) were considered slightly slow, but within normal limits. Quantitative EEG (QEEG) data included relative theta excess and low alpha mean frequencies. A combined treatment of antiepileptic drugs with a catecholamine agonist/reuptake inhibitor was sequentially used. Both patients' physical and cognitive functions improved and they have remained seizure free. The clinical outcomes were correlated with statistically significant changes in QEEG measures toward normal Z-scores in both anterior and posterior regions. In addition, low resolution electromagnetic tomography (LORETA) Z-scored source correlation analyses of the initial and treated QEEG data showed normalized patterns, supporting a neuroanatomic resolution. This study presents preliminary evidence for a neurophysiologic approach to patients with absence epilepsy and comorbid disorders and may provide a method for further research. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Interaction Control to Synchronize Non-synchronizable Networks

PubMed Central

Schröder, Malte; Chakraborty, Sagar; Witthaut, Dirk; Nagler, Jan; Timme, Marc

2016-01-01

Synchronization constitutes one of the most fundamental collective dynamics across networked systems and often underlies their function. Whether a system may synchronize depends on the internal unit dynamics as well as the topology and strength of their interactions. For chaotic units with certain interaction topologies synchronization might be impossible across all interaction strengths, meaning that these networks are non-synchronizable. Here we propose the concept of interaction control, generalizing transient uncoupling, to induce desired collective dynamics in complex networks and apply it to synchronize even such non-synchronizable systems. After highlighting that non-synchronizability prevails for a wide range of networks of arbitrary size, we explain how a simple binary control may localize interactions in state space and thereby synchronize networks. Intriguingly, localizing interactions by a fixed control scheme enables stable synchronization across all connected networks regardless of topological constraints. Interaction control may thus ease the design of desired collective dynamics even without knowledge of the networks’ exact interaction topology and consequently have implications for biological and self-organizing technical systems. PMID:27853266

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot; Thomas, George; Culley, Dennis; Kratz, Jonathan

2017-01-01

Distributed engine control (DEC) systems alter aircraft engine design constraints because of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Design and Benchmarking of a Network-In-the-Loop Simulation for Use in a Hardware-In-the-Loop System

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Thomas, George Lindsey; Culley, Dennis E.; Kratz, Jonathan L.

2017-01-01

Distributed engine control (DEC) systems alter aircraft engine design constraints be- cause of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.

Compliance and Functional Testing of IEEE 1451.1 for NCAP-to-NCAP Communications in a Sensor Network

NASA Technical Reports Server (NTRS)

Figueroa, Jorge; Gurkan, Deniz; Yuan, X.; Benhaddou, D.; Liu, H.; Singla, A.; Franzl, R.; Ma, H.; Bhatt, S.; Morris, J.;

Resource Allocation and Cross Layer Control in Wireless Networks

DTIC Science & Technology

2006-08-25

arrival rates lies within the capacity region of the network. The notion of controlling the system to maximize its stability region and the following...optimization problem (4.5) that must be solved at the beginning of 48 Dynamic Control for Network Stability each time slot requires in general knowledge...Dynamic Control for Network Stability ~ (c) ab (t) those of any other feasible algorithm, then for any time t 0; X ic U (c) i (t) "X b ~ (c) ab (t) X

Self-teaching neural network learns difficult reactor control problem

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

Jouse, W.C.

1989-01-01

A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits.

Functional Characterization of the Cingulo-Opercular Network in the Maintenance of Tonic Alertness

PubMed Central

Sadaghiani, Sepideh; D'Esposito, Mark

2015-01-01

The complex processing architecture underlying attentional control requires delineation of the functional role of different control-related brain networks. A key component is the cingulo-opercular (CO) network composed of anterior insula/operculum, dorsal anterior cingulate cortex, and thalamus. Its function has been particularly difficult to characterize due to the network's pervasive activity and frequent co-activation with other control-related networks. We previously suggested this network to underlie intrinsically maintained tonic alertness. Here, we tested this hypothesis by separately manipulating the demand for selective attention and for tonic alertness in a two-factorial, continuous pitch discrimination paradigm. The 2 factors had independent behavioral effects. Functional imaging revealed that activity as well as functional connectivity in the CO network increased when the task required more tonic alertness. Conversely, heightened selective attention to pitch increased activity in the dorsal attention (DAT) network but not in the CO network. Across participants, performance accuracy showed dissociable correlation patterns with activity in the CO, DAT, and fronto-parietal (FP) control networks. These results support tonic alertness as a fundamental function of the CO network. They further the characterization of this function as the effortful process of maintaining cognitive faculties available for current processing requirements. PMID:24770711

Programmable multi-node quantum network design and simulation

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

2016-05-01

Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

Identification of control targets in Boolean molecular network models via computational algebra.

PubMed

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

Network influences on dissemination of evidence-based guidelines in state tobacco control programs.

PubMed

Luke, Douglas A; Wald, Lana M; Carothers, Bobbi J; Bach, Laura E; Harris, Jenine K

2013-10-01

Little is known regarding the social network relationships that influence dissemination of evidence-based public health practices and policies. In public health, it is critical that evidence-based guidelines, such as the Centers for Disease Control and Prevention's Best Practices for Comprehensive Tobacco Control Programs, are effectively and efficiently disseminated to intended stakeholders. To determine the organizational and network predictors of dissemination among state tobacco control programs, interviews with members of tobacco control networks across eight states were conducted between August 2009 and September 2010. Measures included partner attributes (e.g., agency type) and relationships among network members (frequency of contact, extent of collaboration, and dissemination of Best Practices). Exponential random graph modeling was used to examine attribute and structural predictors of collaboration and dissemination among partners in each network. Although density and centralization of dissemination ties varied across states, network analyses revealed a consistent prediction pattern across all eight states. State tobacco control dissemination networks were less dense but more centralized compared with organizational contact and collaboration networks. Tobacco control partners in each state were more likely to disseminate the Best Practices guidelines if they also had existing contact and collaboration relationships with one another. Evidence-based guidelines in public health need to be efficiently and broadly disseminated if we hope to translate science into practice. This study suggests that funders, advocacy groups, and public health agencies can take advantage of existing public health organizational relationships to support the communication and dissemination of evidence-based practices and policies.

Design of Distributed Engine Control Systems with Uncertain Delay.

PubMed

Liu, Xiaofeng; Li, Yanxi; Sun, Xu

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

Design of Distributed Engine Control Systems with Uncertain Delay

PubMed Central

Li, Yanxi; Sun, Xu

2016-01-01

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

Stability of Control Networks in Autonomous Homeostatic Regulation of Stem Cell Lineages.

PubMed

Komarova, Natalia L; van den Driessche, P

2018-05-01

Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages. We focus on "minimal" networks that are those that have the smallest possible numbers of controls. For such minimal networks, the number of controls must be equal to the number of compartments, and the reducibility/irreducibility of the network (whether or not it can be split into smaller independent sub-networks) is defined by a matrix comprised of the cell number increments induced by each of the controlled processes in each of the compartments. Using the formalism of digraphs, we show that in two-compartment lineages, reducible systems must contain two 1-cycles, and irreducible systems one 1-cycle and one 2-cycle; stability follows from the signs of the controls and does not require magnitude restrictions. In three-compartment systems, irreducible digraphs have a tree structure or have one 3-cycle and at least two more shorter cycles, at least one of which is a 1-cycle. With further work and proper biological validation, our results may serve as a first step toward an understanding of ways in which these networks become dysregulated in cancer.

Effects of iterative learning based signal control strategies on macroscopic fundamental diagrams of urban road networks

NASA Astrophysics Data System (ADS)

Yan, Fei; Tian, Fuli; Shi, Zhongke

2016-10-01

Urban traffic flows are inherently repeated on a daily or weekly basis. This repeatability can help improve the traffic conditions if it is used properly by the control system. In this paper, we propose a novel iterative learning control (ILC) strategy for traffic signals of urban road networks using the repeatability feature of traffic flow. To improve the control robustness, the ILC strategy is further integrated with an error feedback control law in a complementary manner. Theoretical analysis indicates that the ILC-based traffic signal control methods can guarantee the asymptotic learning convergence, despite the presence of modeling uncertainties and exogenous disturbances. Finally, the impacts of the ILC-based signal control strategies on the network macroscopic fundamental diagram (MFD) are examined. The results show that the proposed ILC-based control strategies can homogenously distribute the network accumulation by controlling the vehicle numbers in each link to the desired levels under different traffic demands, which can result in the network with high capacity and mobility.

Effects of Edge Directions on the Structural Controllability of Complex Networks.

PubMed

Xiao, Yandong; Lao, Songyang; Hou, Lvlin; Small, Michael; Bai, Liang

2015-01-01

Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain "inappropriate" edge directions. However, the existence of multiple sets of "inappropriate" edge directions suggests that different edges have different effects on optimal controllability-that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions-utilizing only local information-which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks.

Nonlinear adaptive inverse control via the unified model neural network

NASA Astrophysics Data System (ADS)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

On neural networks in identification and control of dynamic systems

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Hyland, David C.

1993-01-01

This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

Autonomous Congestion Control in Delay-Tolerant Networks

NASA Technical Reports Server (NTRS)

Burleigh, Scott; Jennings, Esther; Schoolcraft, Joshua

2006-01-01

Congestion control is an important feature that directly affects network performance. Network congestion may cause loss of data or long delays. Although this problem has been studied extensively in the Internet, the solutions for Internet congestion control do not apply readily to challenged network environments such as Delay Tolerant Networks (DTN) where end-to-end connectivity may not exist continuously and latency can be high. In DTN, end-to-end rate control is not feasible. This calls for congestion control mechanisms where the decisions can be made autonomously with local information only. We use an economic pricing model and propose a rule-based congestion control mechanism where each router can autonomously decide on whether to accept a bundle (data) based on local information such as available storage and the value and risk of accepting the bundle (derived from historical statistics). Preliminary experimental results show that this congestion control mechanism can protect routers from resource depletion without loss of data.

Measured results of polarization crosstalk cancellation using LMS control. [Least Mean Square

NASA Technical Reports Server (NTRS)

Baird, C. A.; Rassweiler, G. G.

1977-01-01

This paper discusses the use of wideband decoupling networks for the cancellation of polarization crosstalk in dual-polarized communication links. Measured cancellation performance for an all-electronic IF network and an RF electro-mechanical waveguide network are presented. Each of these networks utilizes LMS-type adaptive control techniques to adjust the cancellation network.

Resting-state functional connectivity in multiple sclerosis: an examination of group differences and individual differences.

PubMed

Janssen, Alisha L; Boster, Aaron; Patterson, Beth A; Abduljalil, Amir; Prakash, Ruchika Shaurya

2013-11-01

Multiple sclerosis (MS) is a neurodegenerative, inflammatory disease of the central nervous system, resulting in physical and cognitive disturbances. The goal of the current study was to examine the association between network integrity and composite measures of cognition and disease severity in individuals with relapsing-remitting MS (RRMS), relative to healthy controls. All participants underwent a neuropsychological and neuroimaging session, where resting-state data was collected. Independent component analysis and dual regression were employed to examine network integrity in individuals with MS, relative to healthy controls. The MS sample exhibited less connectivity in the motor and visual networks, relative to healthy controls, after controlling for group differences in gray matter volume. However, no alterations were observed in the frontoparietal, executive control, or default-mode networks, despite previous evidence of altered neuronal patterns during tasks of exogenous processing. Whole-brain, voxel-wise regression analyses with disease severity and processing speed composites were also performed to elucidate the brain-behavior relationship with neuronal network integrity. Individuals with higher levels of disease severity demonstrated reduced intra-network connectivity of the motor network, and the executive control network, while higher disease burden was associated with greater inter-network connectivity between the medial visual network and areas involved in visuomotor learning. Our findings underscore the importance of examining resting-state oscillations in this population, both as a biomarker of disease progression and a potential target for therapeutic intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Performance evaluation of power control algorithms in wireless cellular networks

NASA Astrophysics Data System (ADS)

Temaneh-Nyah, C.; Iita, V.

2014-10-01

Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.

Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

2016-09-01

A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

Microcomputer network for control of a continuous mining machine. Information circular/1993

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

Schiffbauer, W.H.

1993-01-01

The paper details a microcomputer-based control and monitoring network that was developed in-house by the U.S. Bureau of Mines, and installed on a Joy 14 continuous mining machine. The network consists of microcomputers that are connected together via a single twisted pair cable. Each microcomputer was developed to provide a particular function in the control process. Machine-mounted microcomputers in conjunction with the appropriate sensors provide closed-loop control of the machine, navigation, and environmental monitoring. Off-the-machine microcomputers provide remote control of the machine, sensor status, and a connection to the network so that external computers can access network data and controlmore » the continuous mining machine. Although the network was installed on a Joy 14 continuous mining machine, its use extends beyond it. Its generic structure lends itself to installation onto most mining machine types.« less

Control of coupled oscillator networks with application to microgrid technologies.

PubMed

Skardal, Per Sebastian; Arenas, Alex

2015-08-01

The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

Control of coupled oscillator networks with application to microgrid technologies

PubMed Central

Skardal, Per Sebastian; Arenas, Alex

2015-01-01

The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions—a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself. PMID:26601231

Selective pinning control of the average disease transmissibility in an HIV contact network

NASA Astrophysics Data System (ADS)

du Toit, E. F.; Craig, I. K.

2015-07-01

Medication is applied to the HIV-infected nodes of high-risk contact networks with the aim of controlling the spread of disease to a predetermined maximum level. This intervention, known as pinning control, is performed both selectively and randomly in the network. These strategies are applied to 300 independent realizations per reference level of incidence on connected undirectional networks without isolated components and varying in size from 100 to 10 000 nodes per network. It is shown that a selective on-off pinning control strategy can control the networks studied with limited steady-state error and, comparing the medians of the doses from both strategies, uses 51.3% less medication than random pinning of all infected nodes. Selective pinning could possibly be used by public health specialists to identify the maximum level of HIV incidence in a population that can be achieved in a constrained funding environment.

Control of coupled oscillator networks with application to microgrid technologies

NASA Astrophysics Data System (ADS)

Arenas, Alex

The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable syn- chronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

Smart home design for electronic devices monitoring based wireless gateway network using cisco packet tracer

NASA Astrophysics Data System (ADS)

Sihombing, Oloan; Zendrato, Niskarto; Laia, Yonata; Nababan, Marlince; Sitanggang, Delima; Purba, Windania; Batubara, Diarmansyah; Aisyah, Siti; Indra, Evta; Siregar, Saut

2018-04-01

In the era of technological development today, the technology has become the need for the life of today's society. One is needed to create a smart home in turning on and off electronic devices via smartphone. So far in turning off and turning the home electronic device is done by pressing the switch or remote button, so in control of electronic device control less effective. The home smart design is done by simulation concept by testing system, network configuration, and wireless home gateway computer network equipment required by a smart home network on cisco packet tracer using Internet Thing (IoT) control. In testing the IoT home network wireless network gateway system, multiple electronic devices can be controlled and monitored via smartphone based on predefined configuration conditions. With the Smart Ho me can potentially increase energy efficiency, decrease energy usage costs, control electronics and change the role of residents.

Hypersonic Vehicle Trajectory Optimization and Control

NASA Technical Reports Server (NTRS)

Balakrishnan, S. N.; Shen, J.; Grohs, J. R.

1997-01-01

Two classes of neural networks have been developed for the study of hypersonic vehicle trajectory optimization and control. The first one is called an 'adaptive critic'. The uniqueness and main features of this approach are that: (1) they need no external training; (2) they allow variability of initial conditions; and (3) they can serve as feedback control. This is used to solve a 'free final time' two-point boundary value problem that maximizes the mass at the rocket burn-out while satisfying the pre-specified burn-out conditions in velocity, flightpath angle, and altitude. The second neural network is a recurrent network. An interesting feature of this network formulation is that when its inputs are the coefficients of the dynamics and control matrices, the network outputs are the Kalman sequences (with a quadratic cost function); the same network is also used for identifying the coefficients of the dynamics and control matrices. Consequently, we can use it to control a system whose parameters are uncertain. Numerical results are presented which illustrate the potential of these methods.

Adaptive Suspicious Prevention for Defending DoS Attacks in SDN-Based Convergent Networks

PubMed Central

Dao, Nhu-Ngoc; Kim, Joongheon; Park, Minho; Cho, Sungrae

2016-01-01

The convergent communication network will play an important role as a single platform to unify heterogeneous networks and integrate emerging technologies and existing legacy networks. Although there have been proposed many feasible solutions, they could not become convergent frameworks since they mainly focused on converting functions between various protocols and interfaces in edge networks, and handling functions for multiple services in core networks, e.g., the Multi-protocol Label Switching (MPLS) technique. Software-defined networking (SDN), on the other hand, is expected to be the ideal future for the convergent network since it can provide a controllable, dynamic, and cost-effective network. However, SDN has an original structural vulnerability behind a lot of advantages, which is the centralized control plane. As the brains of the network, a controller manages the whole network, which is attractive to attackers. In this context, we proposes a novel solution called adaptive suspicious prevention (ASP) mechanism to protect the controller from the Denial of Service (DoS) attacks that could incapacitate an SDN. The ASP is integrated with OpenFlow protocol to detect and prevent DoS attacks effectively. Our comprehensive experimental results show that the ASP enhances the resilience of an SDN network against DoS attacks by up to 38%. PMID:27494411

Adaptive Suspicious Prevention for Defending DoS Attacks in SDN-Based Convergent Networks.

PubMed

Dao, Nhu-Ngoc; Kim, Joongheon; Park, Minho; Cho, Sungrae

2016-01-01

The convergent communication network will play an important role as a single platform to unify heterogeneous networks and integrate emerging technologies and existing legacy networks. Although there have been proposed many feasible solutions, they could not become convergent frameworks since they mainly focused on converting functions between various protocols and interfaces in edge networks, and handling functions for multiple services in core networks, e.g., the Multi-protocol Label Switching (MPLS) technique. Software-defined networking (SDN), on the other hand, is expected to be the ideal future for the convergent network since it can provide a controllable, dynamic, and cost-effective network. However, SDN has an original structural vulnerability behind a lot of advantages, which is the centralized control plane. As the brains of the network, a controller manages the whole network, which is attractive to attackers. In this context, we proposes a novel solution called adaptive suspicious prevention (ASP) mechanism to protect the controller from the Denial of Service (DoS) attacks that could incapacitate an SDN. The ASP is integrated with OpenFlow protocol to detect and prevent DoS attacks effectively. Our comprehensive experimental results show that the ASP enhances the resilience of an SDN network against DoS attacks by up to 38%.

PeerShield: determining control and resilience criticality of collaborative cyber assets in networks

NASA Astrophysics Data System (ADS)

Cam, Hasan

2012-06-01

As attackers get more coordinated and advanced in cyber attacks, cyber assets are required to have much more resilience, control effectiveness, and collaboration in networks. Such a requirement makes it essential to take a comprehensive and objective approach for measuring the individual and relative performances of cyber security assets in network nodes. To this end, this paper presents four techniques as to how the relative importance of cyber assets can be measured more comprehensively and objectively by considering together the main variables of risk assessment (e.g., threats, vulnerabilities), multiple attributes (e.g., resilience, control, and influence), network connectivity and controllability among collaborative cyber assets in networks. In the first technique, a Bayesian network is used to include the random variables for control, recovery, and resilience attributes of nodes, in addition to the random variables of threats, vulnerabilities, and risk. The second technique shows how graph matching and coloring can be utilized to form collaborative pairs of nodes to shield together against threats and vulnerabilities. The third technique ranks the security assets of nodes by incorporating multiple weights and thresholds of attributes into a decision-making algorithm. In the fourth technique, the hierarchically well-separated tree is enhanced to first identify critical nodes of a network with respect to their attributes and network connectivity, and then selecting some nodes as driver nodes for network controllability.

Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

PubMed

Heydari, Ali; Balakrishnan, Sivasubramanya N

2013-01-01

To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.

Neural network-based sliding mode control for atmospheric-actuated spacecraft formation using switching strategy

NASA Astrophysics Data System (ADS)

Sun, Ran; Wang, Jihe; Zhang, Dexin; Shao, Xiaowei

2018-02-01

This paper presents an adaptive neural networks-based control method for spacecraft formation with coupled translational and rotational dynamics using only aerodynamic forces. It is assumed that each spacecraft is equipped with several large flat plates. A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators. For this model, a neural network-based adaptive sliding mode controller is implemented, accounting for system uncertainties and external perturbations. To avoid invalidation of the neural networks destroying stability of the system, a switching control strategy is proposed which combines an adaptive neural networks controller dominating in its active region and an adaptive sliding mode controller outside the neural active region. An optimal process is developed to determine the control commands for the plates system. The stability of the closed-loop system is proved by a Lyapunov-based method. Comparative results through numerical simulations illustrate the effectiveness of executing attitude control while maintaining the relative motion, and higher control accuracy can be achieved by using the proposed neural-based switching control scheme than using only adaptive sliding mode controller.

GMPLS-based control plane for optical networks: early implementation experience

NASA Astrophysics Data System (ADS)

Liu, Hang; Pendarakis, Dimitrios; Komaee, Nooshin; Saha, Debanjan

2002-07-01

Generalized Multi-Protocol Label Switching (GMPLS) extends MPLS signaling and Internet routing protocols to provide a scalable, interoperable, distributed control plane, which is applicable to multiple network technologies such as optical cross connects (OXCs), photonic switches, IP routers, ATM switches, SONET and DWDM systems. It is intended to facilitate automatic service provisioning and dynamic neighbor and topology discovery across multi-vendor intelligent transport networks, as well as their clients. Efforts to standardize such a distributed common control plane have reached various stages in several bodies such as the IETF, ITU and OIF. This paper describes the design considerations and architecture of a GMPLS-based control plane that we have prototyped for core optical networks. Functional components of GMPLS signaling and routing are integrated in this architecture with an application layer controller module. Various requirements including bandwidth, network protection and survivability, traffic engineering, optimal utilization of network resources, and etc. are taken into consideration during path computation and provisioning. Initial experiments with our prototype demonstrate the feasibility and main benefits of GMPLS as a distributed control plane for core optical networks. In addition to such feasibility results, actual adoption and deployment of GMPLS as a common control plane for intelligent transport networks will depend on the successful completion of relevant standardization activities, extensive interoperability testing as well as the strengthening of appropriate business drivers.

Flight control with adaptive critic neural network

NASA Astrophysics Data System (ADS)

Han, Dongchen

2001-10-01

In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

Designing communication and remote controlling of virtual instrument network system

NASA Astrophysics Data System (ADS)

Lei, Lin; Wang, Houjun; Zhou, Xue; Zhou, Wenjian

2005-01-01

In this paper, a virtual instrument network through the LAN and finally remote control of virtual instruments is realized based on virtual instrument and LabWindows/CVI software platform. The virtual instrument network system is made up of three subsystems. There are server subsystem, telnet client subsystem and local instrument control subsystem. This paper introduced virtual instrument network structure in detail based on LabWindows. Application procedure design of virtual instrument network communication, the Client/the programming mode of the server, remote PC and server communication far realizing, the control power of the workstation is transmitted, server program and so on essential technical were introduced. And virtual instruments network may connect to entire Internet on. Above-mentioned technology, through measuring the application in the electronic measurement virtual instrument network that is already built up, has verified the actual using value of the technology. Experiment and application validate that this design is resultful.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, D.B.

1996-12-31

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor to a plurality of slave processors to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor`s status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

NCC simulation model. Phase 2: Simulating the operations of the Network Control Center and NCC message manual

NASA Technical Reports Server (NTRS)

Benjamin, Norman M.; Gill, Tepper; Charles, Mary

1994-01-01

The network control center (NCC) provides scheduling, monitoring, and control of services to the NASA space network. The space network provides tracking and data acquisition services to many low-earth orbiting spacecraft. This report describes the second phase in the development of simulation models for the FCC. Phase one concentrated on the computer systems and interconnecting network.Phase two focuses on the implementation of the network message dialogs and the resources controlled by the NCC. Performance measures were developed along with selected indicators of the NCC's operational effectiveness.The NCC performance indicators were defined in terms of the following: (1) transfer rate, (2) network delay, (3) channel establishment time, (4) line turn around time, (5) availability, (6) reliability, (7) accuracy, (8) maintainability, and (9) security. An NCC internal and external message manual is appended to this report.

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Autonomous Congestion Control in Delay-Tolerant Networks

NASA Technical Reports Server (NTRS)

Burleigh, Scott C.; Jennings, Esther H.

2005-01-01

Congestion control is an important feature that directly affects network performance. Network congestion may cause loss of data or long delays. Although this problem has been studied extensively in the Internet, the solutions for Internet congestion control do not apply readily to challenged network environments such as Delay Tolerant Networks (DTN) where end-to-end connectivity may not exist continuously and latency can be high. In DTN, end-to-end rate control is not feasible. This calls for congestion control mechanisms where the decisions can be made autonomously with local information only. We use an economic pricing model and propose a rule-based congestion control mechanism where each router can autonomously decide on whether to accept a bundle (data) based on local information such as available storage and the value and risk of accepting the bundle (derived from historical statistics).

Real-time networked control of an industrial robot manipulator via discrete-time second-order sliding modes

NASA Astrophysics Data System (ADS)

Massimiliano Capisani, Luca; Facchinetti, Tullio; Ferrara, Antonella

2010-08-01

This article presents the networked control of a robotic anthropomorphic manipulator based on a second-order sliding mode technique, where the control objective is to track a desired trajectory for the manipulator. The adopted control scheme allows an easy and effective distribution of the control algorithm over two networked machines. While the predictability of real-time tasks execution is achieved by the Soft Hard Real-Time Kernel (S.Ha.R.K.) real-time operating system, the communication is established via a standard Ethernet network. The performances of the control system are evaluated under different experimental system configurations using, to perform the experiments, a COMAU SMART3-S2 industrial robot, and the results are analysed to put into evidence the robustness of the proposed approach against possible network delays, packet losses and unmodelled effects.

Receiver-Assisted Congestion Control to Achieve High Throughput in Lossy Wireless Networks

NASA Astrophysics Data System (ADS)

Shi, Kai; Shu, Yantai; Yang, Oliver; Luo, Jiarong

2010-04-01

Many applications would require fast data transfer in high-speed wireless networks nowadays. However, due to its conservative congestion control algorithm, Transmission Control Protocol (TCP) cannot effectively utilize the network capacity in lossy wireless networks. In this paper, we propose a receiver-assisted congestion control mechanism (RACC) in which the sender performs loss-based control, while the receiver is performing delay-based control. The receiver measures the network bandwidth based on the packet interarrival interval and uses it to compute a congestion window size deemed appropriate for the sender. After receiving the advertised value feedback from the receiver, the sender then uses the additive increase and multiplicative decrease (AIMD) mechanism to compute the correct congestion window size to be used. By integrating the loss-based and the delay-based congestion controls, our mechanism can mitigate the effect of wireless losses, alleviate the timeout effect, and therefore make better use of network bandwidth. Simulation and experiment results in various scenarios show that our mechanism can outperform conventional TCP in high-speed and lossy wireless environments.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

NASDA knowledge-based network planning system

NASA Technical Reports Server (NTRS)

Yamaya, K.; Fujiwara, M.; Kosugi, S.; Yambe, M.; Ohmori, M.

1993-01-01

One of the SODS (space operation and data system) sub-systems, NP (network planning) was the first expert system used by NASDA (national space development agency of Japan) for tracking and control of satellite. The major responsibilities of the NP system are: first, the allocation of network and satellite control resources and, second, the generation of the network operation plan data (NOP) used in automated control of the stations and control center facilities. Up to now, the first task of network resource scheduling was done by network operators. NP system automatically generates schedules using its knowledge base, which contains information on satellite orbits, station availability, which computer is dedicated to which satellite, and how many stations must be available for a particular satellite pass or a certain time period. The NP system is introduced.

Optical burst switching based satellite backbone network

NASA Astrophysics Data System (ADS)

Li, Tingting; Guo, Hongxiang; Wang, Cen; Wu, Jian

2018-02-01

We propose a novel time slot based optical burst switching (OBS) architecture for GEO/LEO based satellite backbone network. This architecture can provide high speed data transmission rate and high switching capacity . Furthermore, we design the control plane of this optical satellite backbone network. The software defined network (SDN) and network slice (NS) technologies are introduced. Under the properly designed control mechanism, this backbone network is flexible to support various services with diverse transmission requirements. Additionally, the LEO access and handoff management in this network is also discussed.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Experimental demonstration of OpenFlow-enabled media ecosystem architecture for high-end applications over metro and core networks.

PubMed

Ntofon, Okung-Dike; Channegowda, Mayur P; Efstathiou, Nikolaos; Rashidi Fard, Mehdi; Nejabati, Reza; Hunter, David K; Simeonidou, Dimitra

2013-02-25

In this paper, a novel Software-Defined Networking (SDN) architecture is proposed for high-end Ultra High Definition (UHD) media applications. UHD media applications require huge amounts of bandwidth that can only be met with high-capacity optical networks. In addition, there are requirements for control frameworks capable of delivering effective application performance with efficient network utilization. A novel SDN-based Controller that tightly integrates application-awareness with network control and management is proposed for such applications. An OpenFlow-enabled test-bed demonstrator is reported with performance evaluations of advanced online and offline media- and network-aware schedulers.

An Architecture for SCADA Network Forensics

NASA Astrophysics Data System (ADS)

Kilpatrick, Tim; Gonzalez, Jesus; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet

Supervisory control and data acquisition (SCADA) systems are widely used in industrial control and automation. Modern SCADA protocols often employ TCP/IP to transport sensor data and control signals. Meanwhile, corporate IT infrastructures are interconnecting with previously isolated SCADA networks. The use of TCP/IP as a carrier protocol and the interconnection of IT and SCADA networks raise serious security issues. This paper describes an architecture for SCADA network forensics. In addition to supporting forensic investigations of SCADA network incidents, the architecture incorporates mechanisms for monitoring process behavior, analyzing trends and optimizing plant performance.

A neural-network approach to robotic control

NASA Technical Reports Server (NTRS)

Graham, D. P. W.; Deleuterio, G. M. T.

1993-01-01

An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

Security and SCADA protocols

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

Igure, V. M.; Williams, R. D.

2006-07-01

Supervisory control and data acquisition (SCADA) networks have replaced discrete wiring for many industrial processes, and the efficiency of the network alternative suggests a trend toward more SCADA networks in the future. This paper broadly considers SCADA to include distributed control systems (DCS) and digital control systems. These networks offer many advantages, but they also introduce potential vulnerabilities that can be exploited by adversaries. Inter-connectivity exposes SCADA networks to many of the same threats that face the public internet and many of the established defenses therefore show promise if adapted to the SCADA differences. This paper provides an overview ofmore » security issues in SCADA networks and ongoing efforts to improve the security of these networks. Initially, a few samples from the range of threats to SCADA network security are offered. Next, attention is focused on security assessment of SCADA communication protocols. Three challenges must be addressed to strengthen SCADA networks. Access control mechanisms need to be introduced or strengthened, improvements are needed inside of the network to enhance security and network monitoring, and SCADA security management improvements and policies are needed. This paper discusses each of these challenges. This paper uses the Profibus protocol as an example to illustrate some of the vulnerabilities that arise within SCADA networks. The example Profibus security assessment establishes a network model and an attacker model before proceeding to a list of example attacks. (authors)« less

Effects of Edge Directions on the Structural Controllability of Complex Networks

PubMed Central

Xiao, Yandong; Lao, Songyang; Hou, Lvlin; Small, Michael; Bai, Liang

2015-01-01

Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain “inappropriate” edge directions. However, the existence of multiple sets of “inappropriate” edge directions suggests that different edges have different effects on optimal controllability—that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions—utilizing only local information—which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks. PMID:26281042

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

PubMed

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Allen, Michael J.; Dibley, Ryan P.

2003-01-01

Neural networks were used to model wing bending-moment loads, torsion loads, and control surface hinge-moments of the Active Aeroelastic Wing (AAW) aircraft. Accurate loads models are required for the development of control laws designed to increase roll performance through wing twist while not exceeding load limits. Inputs to the model include aircraft rates, accelerations, and control surface positions. Neural networks were chosen to model aircraft loads because they can account for uncharacterized nonlinear effects while retaining the capability to generalize. The accuracy of the neural network models was improved by first developing linear loads models to use as starting points for network training. Neural networks were then trained with flight data for rolls, loaded reversals, wind-up-turns, and individual control surface doublets for load excitation. Generalization was improved by using gain weighting and early stopping. Results are presented for neural network loads models of four wing loads and four control surface hinge moments at Mach 0.90 and an altitude of 15,000 ft. An average model prediction error reduction of 18.6 percent was calculated for the neural network models when compared to the linear models. This paper documents the input data conditioning, input parameter selection, structure, training, and validation of the neural network models.

Neuroplasticity in Human Alcoholism

PubMed Central

Fein, George; Cardenas, Valerie A.

2015-01-01

Alcoholism is characterized by a lack of control over excessive alcohol consumption despite significant negative consequences. This impulsive and compulsive behavior may be related to functional abnormalities within networks of brain regions responsible for how we make decisions. The abnormalities may result in strengthened networks related to appetitive drive—or the need to fulfill desires—and simultaneously weakened networks that exercise control over behaviors. Studies using functional magnetic resonance imaging (fMRI) in abstinent alcoholics suggest that abstinence is associated with changes in the tone of such networks, decreasing resting tone in appetitive drive networks, and increasing resting tone in inhibitory control networks to support continued abstinence. Identifying electroencephalographic (EEG) measures of resting tone in these networks initially identified using fMRI, and establishing in longitudinal studies that these abstinence-related changes in network tone are progressive would motivate treatment initiatives to facilitate these changes in network tone, thereby supporting successful ongoing abstinence. PMID:26259093

Exponential Synchronization of Networked Chaotic Delayed Neural Network by a Hybrid Event Trigger Scheme.

PubMed

Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun; Zhongyang Fei; Chaoxu Guan; Huijun Gao; Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun

2018-06-01

This paper is concerned with the exponential synchronization for master-slave chaotic delayed neural network with event trigger control scheme. The model is established on a network control framework, where both external disturbance and network-induced delay are taken into consideration. The desired aim is to synchronize the master and slave systems with limited communication capacity and network bandwidth. In order to save the network resource, we adopt a hybrid event trigger approach, which not only reduces the data package sending out, but also gets rid of the Zeno phenomenon. By using an appropriate Lyapunov functional, a sufficient criterion for the stability is proposed for the error system with extended ( , , )-dissipativity performance index. Moreover, hybrid event trigger scheme and controller are codesigned for network-based delayed neural network to guarantee the exponential synchronization between the master and slave systems. The effectiveness and potential of the proposed results are demonstrated through a numerical example.

Complex Dynamical Networks Constructed with Fully Controllable Nonlinear Nanomechanical Oscillators.

PubMed

Fon, Warren; Matheny, Matthew H; Li, Jarvis; Krayzman, Lev; Cross, Michael C; D'Souza, Raissa M; Crutchfield, James P; Roukes, Michael L

2017-10-11

Control of the global parameters of complex networks has been explored experimentally in a variety of contexts. Yet, the more difficult prospect of realizing arbitrary network architectures, especially analog physical networks that provide dynamical control of individual nodes and edges, has remained elusive. Given the vast hierarchy of time scales involved, it also proves challenging to measure a complex network's full internal dynamics. These span from the fastest nodal dynamics to very slow epochs over which emergent global phenomena, including network synchronization and the manifestation of exotic steady states, eventually emerge. Here, we demonstrate an experimental system that satisfies these requirements. It is based upon modular, fully controllable, nonlinear radio frequency nanomechanical oscillators, designed to form the nodes of complex dynamical networks with edges of arbitrary topology. The dynamics of these oscillators and their surrounding network are analog and continuous-valued and can be fully interrogated in real time. They comprise a piezoelectric nanomechanical membrane resonator, which serves as the frequency-determining element within an electrical feedback circuit. This embodiment permits network interconnections entirely within the electrical domain and provides unprecedented node and edge control over a vast region of parameter space. Continuous measurement of the instantaneous amplitudes and phases of every constituent oscillator node are enabled, yielding full and detailed network data without reliance upon statistical quantities. We demonstrate the operation of this platform through the real-time capture of the dynamics of a three-node ring network as it evolves from the uncoupled state to full synchronization.

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

System Identification for Nonlinear Control Using Neural Networks

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Linse, Dennis J.

1990-01-01

An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.

Digital Signal Processing and Control for the Study of Gene Networks

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun

2016-04-01

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

Digital Signal Processing and Control for the Study of Gene Networks.

PubMed

Shin, Yong-Jun

2016-04-22

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

Digital Signal Processing and Control for the Study of Gene Networks

PubMed Central

Shin, Yong-Jun

2016-01-01

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks. PMID:27102828

Energy scaling and reduction in controlling complex networks

PubMed Central

Chen, Yu-Zhong; Wang, Le-Zhi; Wang, Wen-Xu; Lai, Ying-Cheng

2016-01-01

Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks. PMID:27152220

Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

NASA Technical Reports Server (NTRS)

Burken, John J.

2005-01-01

This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

NASA Astrophysics Data System (ADS)

Aguado, Alejandro; Hugues-Salas, Emilio; Haigh, Paul Anthony; Marhuenda, Jaume; Price, Alasdair B.; Sibson, Philip; Kennard, Jake E.; Erven, Chris; Rarity, John G.; Thompson, Mark Gerard; Lord, Andrew; Nejabati, Reza; Simeonidou, Dimitra

2017-04-01

We demonstrate, for the first time, a secure optical network architecture that combines NFV orchestration and SDN control with quantum key distribution (QKD) technology. A novel time-shared QKD network design is presented as a cost-effective solution for practical networks.

Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

PubMed

Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea

2014-03-01

In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Detecting Anomalies in Process Control Networks

NASA Astrophysics Data System (ADS)

Rrushi, Julian; Kang, Kyoung-Don

This paper presents the estimation-inspection algorithm, a statistical algorithm for anomaly detection in process control networks. The algorithm determines if the payload of a network packet that is about to be processed by a control system is normal or abnormal based on the effect that the packet will have on a variable stored in control system memory. The estimation part of the algorithm uses logistic regression integrated with maximum likelihood estimation in an inductive machine learning process to estimate a series of statistical parameters; these parameters are used in conjunction with logistic regression formulas to form a probability mass function for each variable stored in control system memory. The inspection part of the algorithm uses the probability mass functions to estimate the normalcy probability of a specific value that a network packet writes to a variable. Experimental results demonstrate that the algorithm is very effective at detecting anomalies in process control networks.

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

NASA Technical Reports Server (NTRS)

Gupta, Pramod; Loparo, Kenneth; Mackall, Dale; Schumann, Johann; Soares, Fola

2004-01-01

Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.

Resilient distributed control in the presence of misbehaving agents in networked control systems.

PubMed

Zeng, Wente; Chow, Mo-Yuen

2014-11-01

In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.

Research on Environmental Adjustment of Cloud Ranch Based on BP Neural Network PID Control

NASA Astrophysics Data System (ADS)

Ren, Jinzhi; Xiang, Wei; Zhao, Lin; Wu, Jianbo; Huang, Lianzhen; Tu, Qinggang; Zhao, Heming

2018-01-01

In order to make the intelligent ranch management mode replace the traditional artificial one gradually, this paper proposes a pasture environment control system based on cloud server, and puts forward the PID control algorithm based on BP neural network to control temperature and humidity better in the pasture environment. First, to model the temperature and humidity (controlled object) of the pasture, we can get the transfer function. Then the traditional PID control algorithm and the PID one based on BP neural network are applied to the transfer function. The obtained step tracking curves can be seen that the PID controller based on BP neural network has obvious superiority in adjusting time and error, etc. This algorithm, calculating reasonable control parameters of the temperature and humidity to control environment, can be better used in the cloud service platform.

Vibration control of building structures using self-organizing and self-learning neural networks

NASA Astrophysics Data System (ADS)

Madan, Alok

2005-11-01

Past research in artificial intelligence establishes that artificial neural networks (ANN) are effective and efficient computational processors for performing a variety of tasks including pattern recognition, classification, associative recall, combinatorial problem solving, adaptive control, multi-sensor data fusion, noise filtering and data compression, modelling and forecasting. The paper presents a potentially feasible approach for training ANN in active control of earthquake-induced vibrations in building structures without the aid of teacher signals (i.e. target control forces). A counter-propagation neural network is trained to output the control forces that are required to reduce the structural vibrations in the absence of any feedback on the correctness of the output control forces (i.e. without any information on the errors in output activations of the network). The present study shows that, in principle, the counter-propagation network (CPN) can learn from the control environment to compute the required control forces without the supervision of a teacher (unsupervised learning). Simulated case studies are presented to demonstrate the feasibility of implementing the unsupervised learning approach in ANN for effective vibration control of structures under the influence of earthquake ground motions. The proposed learning methodology obviates the need for developing a mathematical model of structural dynamics or training a separate neural network to emulate the structural response for implementation in practice.

Integration and segregation of large-scale brain networks during short-term task automatization

PubMed Central

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F.; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-01-01

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes. PMID:27808095

Flight Test of an Intelligent Flight-Control System

NASA Technical Reports Server (NTRS)

Davidson, Ron; Bosworth, John T.; Jacobson, Steven R.; Thomson, Michael Pl; Jorgensen, Charles C.

2003-01-01

The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.

Identification of critical regulatory genes in cancer signaling network using controllability analysis

NASA Astrophysics Data System (ADS)

Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

2017-05-01

Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

Control of collective network chaos.

PubMed

Wagemakers, Alexandre; Barreto, Ernest; Sanjuán, Miguel A F; So, Paul

2014-06-01

Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of "reduced" ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

Adaptive Flow Control for Enabling Quality of Service in Tactical Ad Hoc Wireless Networks

DTIC Science & Technology

2010-12-01

environment in wireless networks , we use sensors in the network routers to detect and respond to congestion. We use backpressure techniques... wireless mesh network . In the current approach, we used OLSR as the routing scheme. However, B.A.T.M.A.N. offers the significant advantage of being based...Control and QoS Routing in Multi-Channel Wireless Mesh Networks ,” 68-77. ACM International Symposium on Mobile Ad Hoc Networking &

Molecular inspired models for prediction and control of directional FSO/RF wireless networks

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Milner, Stuart D.; Davis, Christopher C.

2010-08-01

Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a framework based on the definition of a potential energy function to characterize robustness in communication networks and the study of first and second order variations of the potential energy to provide prediction and control strategies for network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in the eigenvalues of the Hessian of the network potential and network degradation.

A neural network controller for automated composite manufacturing

NASA Technical Reports Server (NTRS)

Lichtenwalner, Peter F.

1994-01-01

At McDonnell Douglas Aerospace (MDA), an artificial neural network based control system has been developed and implemented to control laser heating for the fiber placement composite manufacturing process. This neurocontroller learns an approximate inverse model of the process on-line to provide performance that improves with experience and exceeds that of conventional feedback control techniques. When untrained, the control system behaves as a proportional plus integral (PI) controller. However after learning from experience, the neural network feedforward control module provides control signals that greatly improve temperature tracking performance. Faster convergence to new temperature set points and reduced temperature deviation due to changing feed rate have been demonstrated on the machine. A Cerebellar Model Articulation Controller (CMAC) network is used for inverse modeling because of its rapid learning performance. This control system is implemented in an IBM compatible 386 PC with an A/D board interface to the machine.

Using a CLIPS expert system to automatically manage TCP/IP networks and their components

NASA Technical Reports Server (NTRS)

Faul, Ben M.

1991-01-01

A expert system that can directly manage networks components on a Transmission Control Protocol/Internet Protocol (TCP/IP) network is described. Previous expert systems for managing networks have focused on managing network faults after they occur. However, this proactive expert system can monitor and control network components in near real time. The ability to directly manage network elements from the C Language Integrated Production System (CLIPS) is accomplished by the integration of the Simple Network Management Protocol (SNMP) and a Abstract Syntax Notation (ASN) parser into the CLIPS artificial intelligence language.

Experiments in Neural-Network Control of a Free-Flying Space Robot

NASA Technical Reports Server (NTRS)

Wilson, Edward

1995-01-01

Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype. The first issue concerns the importance of true system level design of the control system. A new hybrid strategy is developed here, in depth, for the beneficial integration of neural networks into the total control system. A second important issue in neural network control concerns incorporating a priori knowledge into the neural network. In many applications, it is possible to get a reasonably accurate controller using conventional means. If this prior information is used purposefully to provide a starting point for the optimizing capabilities of the neural network, it can provide much faster initial learning. In a step towards addressing this issue, a new generic Fully Connected Architecture (FCA) is developed for use with backpropagation. A third issue is that neural networks are commonly trained using a gradient based optimization method such as backpropagation; but many real world systems have Discrete Valued Functions (DVFs) that do not permit gradient based optimization. One example is the on-off thrusters that are common on spacecraft. A new technique is developed here that now extends backpropagation learning for use with DVFs. The fourth issue is that the speed of adaptation is often a limiting factor in the implementation of a neural network control system. This issue has been strongly resolved in the research by drawing on the above new contributions.

T-SDN architecture for space and ground integrated optical transport network

NASA Astrophysics Data System (ADS)

Nie, Kunkun; Hu, Wenjing; Gao, Shenghua; Chang, Chengwu

2015-11-01

Integrated optical transport network is the development trend of the future space information backbone network. The space and ground integrated optical transport network(SGIOTN) may contain a variety of equipment and systems. Changing the network or meeting some innovation missions in the network will be an expensive implement. Software Defined Network(SDN) provides a good solution to flexibly adding process logic, timely control states and resources of the whole network, as well as shielding the differences of heterogeneous equipment and so on. According to the characteristics of SGIOTN, we propose an transport SDN architecture for it, with hierarchical control plane and data plane composed of packet networks and optical transport networks.

Connected Dominating Set Based Topology Control in Wireless Sensor Networks

ERIC Educational Resources Information Center

He, Jing

2012-01-01

Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

PubMed

Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

2016-12-08

This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

Salience network dynamics underlying successful resistance of temptation

PubMed Central

Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q

2017-01-01

Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582

Microcomputer Applications with PC LAN (Local Area Network) in Battleships.

DTIC Science & Technology

1988-12-01

NETWORKS 5 C. TRANSMISSION TECHNIQUES 6 D. MEDIUM ACCESS CONTROL METHODS 6 1. CSMA CD 6 2. Control Token 7 3. Slotted Ring 7 E...network model in the Turkish Battleships will employ the broadband technique. D. MEDIUM ACCESS CONTROL METHODS The access method is one of the most...better performance at heavier loads. 3. Slotted Ring This method is used with a ring network. The ring is initialized to contain a fixed number of

Inferring Network Controls from Topology Using the Chomp Database

DTIC Science & Technology

2015-12-03

AFRL-AFOSR-VA-TR-2016-0033 INFERRING NETWORK CONTROLS FROM TOPOLOGY USING THE CHOMP DATABASE John Harer DUKE UNIVERSITY Final Report 12/03/2015...INFERRING NETWORK CONTROLS FROM TOPOLOGY USING THE CHOMP DATABASE 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-10-1-0436 5c. PROGRAM ELEMENT NUMBER 6...area of Topological Data Analysis (TDA) and it’s application to dynamical systems. The role of this work in the Complex Networks program is based on

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

This paper describes the performance of a simplified dynamic inversion controller with neural network supplementation. This 6 DOF (Degree-of-Freedom) simulation study focuses on the results with and without adaptation of neural networks using a simulation of the NASA modified F-15 which has canards. One area of interest is the performance of a simulated surface failure while attempting to minimize the inertial cross coupling effect of a [B] matrix failure (a control derivative anomaly associated with a jammed or missing control surface). Another area of interest and presented is simulated aerodynamic failures ([A] matrix) such as a canard failure. The controller uses explicit models to produce desired angular rate commands. The dynamic inversion calculates the necessary surface commands to achieve the desired rates. The simplified dynamic inversion uses approximate short period and roll axis dynamics. Initial results indicated that the transient response for a [B] matrix failure using a Neural Network (NN) improved the control behavior when compared to not using a neural network for a given failure, However, further evaluation of the controller was comparable, with objections io the cross coupling effects (after changes were made to the controller). This paper describes the methods employed to reduce the cross coupling effect and maintain adequate tracking errors. The IA] matrix failure results show that control of the aircraft without adaptation is more difficult [leas damped) than with active neural networks, Simulation results show Neural Network augmentation of the controller improves performance in terms of backing error and cross coupling reduction and improved performance with aerodynamic-type failures.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE PAGES

Shen, Yiwen; Hattink, Maarten; Samadi, Payman; ...

2018-04-13

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

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

Shen, Yiwen; Hattink, Maarten; Samadi, Payman

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Increasingly diverse brain dynamics in the developmental arc: using Pareto-optimization to infer a mechanism

NASA Astrophysics Data System (ADS)

Tang, Evelyn; Giusti, Chad; Baum, Graham; Gu, Shi; Pollock, Eli; Kahn, Ari; Roalf, David; Moore, Tyler; Ruparel, Kosha; Gur, Ruben; Gur, Raquel; Satterthwaite, Theodore; Bassett, Danielle

Motivated by a recent demonstration that the network architecture of white matter supports emerging control of diverse neural dynamics as children mature into adults, we seek to investigate structural mechanisms that support these changes. Beginning from a network representation of diffusion imaging data, we simulate network evolution with a set of simple growth rules built on principles of network control. Notably, the optimal evolutionary trajectory displays a striking correspondence to the progression of child to adult brain, suggesting that network control is a driver of development. More generally, and in comparison to the complete set of available models, we demonstrate that all brain networks from child to adult are structured in a manner highly optimized for the control of diverse neural dynamics. Within this near-optimality, we observe differences in the predicted control mechanisms of the child and adult brains, suggesting that the white matter architecture in children has a greater potential to increasingly support brain state transitions, potentially underlying cognitive switching.

Resting-State Functional Connectivity in Individuals with Down Syndrome and Williams Syndrome Compared with Typically Developing Controls.

PubMed

Vega, Jennifer N; Hohman, Timothy J; Pryweller, Jennifer R; Dykens, Elisabeth M; Thornton-Wells, Tricia A

2015-10-01

The emergence of resting-state functional connectivity (rsFC) analysis, which examines temporal correlations of low-frequency (<0.1 Hz) blood oxygen level-dependent signal fluctuations between brain regions, has dramatically improved our understanding of the functional architecture of the typically developing (TD) human brain. This study examined rsFC in Down syndrome (DS) compared with another neurodevelopmental disorder, Williams syndrome (WS), and TD. Ten subjects with DS, 18 subjects with WS, and 40 subjects with TD each participated in a 3-Tesla MRI scan. We tested for group differences (DS vs. TD, DS vs. WS, and WS vs. TD) in between- and within-network rsFC connectivity for seven functional networks. For the DS group, we also examined associations between rsFC and other cognitive and genetic risk factors. In DS compared with TD, we observed higher levels of between-network connectivity in 6 out 21 network pairs but no differences in within-network connectivity. Participants with WS showed lower levels of within-network connectivity and no significant differences in between-network connectivity relative to DS. Finally, our comparison between WS and TD controls revealed lower within-network connectivity in multiple networks and higher between-network connectivity in one network pair relative to TD controls. While preliminary due to modest sample sizes, our findings suggest a global difference in between-network connectivity in individuals with neurodevelopmental disorders compared with controls and that such a difference is exacerbated across many brain regions in DS. However, this alteration in DS does not appear to extend to within-network connections, and therefore, the altered between-network connectivity must be interpreted within the framework of an intact intra-network pattern of activity. In contrast, WS shows markedly lower levels of within-network connectivity in the default mode network and somatomotor network relative to controls. These findings warrant further investigation using a task-based procedure that may help disentangle the relationship between brain function and cognitive performance across the spectrum of neurodevelopmental disorders.

NATO IST 124 Experimentation Instructions

DTIC Science & Technology

2016-11-10

more reliable and predictable network performance through adaptive and efficient control schemes . This report provides guidance and instructions for...tactical heterogeneous networks for more reliable and predictable network performance through adaptive and efficient control schemes . This report

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

PubMed Central

Albattat, Ali; Gruenwald, Benjamin C.; Yucelen, Tansel

2016-01-01

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches. PMID:27537894

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

PubMed

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Exponential H(infinity) synchronization of general discrete-time chaotic neural networks with or without time delays.

PubMed

Qi, Donglian; Liu, Meiqin; Qiu, Meikang; Zhang, Senlin

2010-08-01

This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.

Enhancing synchronization stability in a multi-area power grid

PubMed Central

Wang, Bing; Suzuki, Hideyuki; Aihara, Kazuyuki

2016-01-01

Maintaining a synchronous state of generators is of central importance to the normal operation of power grids, in which many networks are generally interconnected. In order to understand the condition under which the stability can be optimized, it is important to relate network stability with feedback control strategies as well as network structure. Here, we present a stability analysis on a multi-area power grid by relating it with several control strategies and topological design of network structure. We clarify the minimal feedback gain in the self-feedback control, and build the optimal communication network for the local and global control strategies. Finally, we consider relationship between the interconnection pattern and the synchronization stability; by optimizing the network interlinks, the obtained network shows better synchronization stability than the original network does, in particular, at a high power demand. Our analysis shows that interlinks between spatially distant nodes will improve the synchronization stability. The results seem unfeasible to be implemented in real systems but provide a potential guide for the design of stable power systems. PMID:27225708

Approximate reasoning-based learning and control for proximity operations and docking in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Jani, Yashvant; Lea, Robert N.

1991-01-01

A recently proposed hybrid-neutral-network and fuzzy-logic-control architecture is applied to a fuzzy logic controller developed for attitude control of the Space Shuttle. A model using reinforcement learning and learning from past experience for fine-tuning its knowledge base is proposed. Two main components of this approximate reasoning-based intelligent control (ARIC) model - an action-state evaluation network and action selection network are described as well as the Space Shuttle attitude controller. An ARIC model for the controller is presented, and it is noted that the input layer in each network includes three nodes representing the angle error, angle error rate, and bias node. Preliminary results indicate that the controller can hold the pitch rate within its desired deadband and starts to use the jets at about 500 sec in the run.

On controlling networks of limit-cycle oscillators

NASA Astrophysics Data System (ADS)

Skardal, Per Sebastian; Arenas, Alex

2016-09-01

The control of network-coupled nonlinear dynamical systems is an active area of research in the nonlinear science community. Coupled oscillator networks represent a particularly important family of nonlinear systems, with applications ranging from the power grid to cardiac excitation. Here, we study the control of network-coupled limit cycle oscillators, extending the previous work that focused on phase oscillators. Based on stabilizing a target fixed point, our method aims to attain complete frequency synchronization, i.e., consensus, by applying control to as few oscillators as possible. We develop two types of controls. The first type directs oscillators towards larger amplitudes, while the second does not. We present numerical examples of both control types and comment on the potential failures of the method.

Neural Network Control of a Magnetically Suspended Rotor System

NASA Technical Reports Server (NTRS)

Choi, Benjamin; Brown, Gerald; Johnson, Dexter

1997-01-01

Abstract Magnetic bearings offer significant advantages because of their noncontact operation, which can reduce maintenance. Higher speeds, no friction, no lubrication, weight reduction, precise position control, and active damping make them far superior to conventional contact bearings. However, there are technical barriers that limit the application of this technology in industry. One of them is the need for a nonlinear controller that can overcome the system nonlinearity and uncertainty inherent in magnetic bearings. This paper discusses the use of a neural network as a nonlinear controller that circumvents system nonlinearity. A neural network controller was well trained and successfully demonstrated on a small magnetic bearing rig. This work demonstrated the feasibility of using a neural network to control nonlinear magnetic bearings and systems with unknown dynamics.

Wireless Control of Miniaturized Mobile Vehicle for Indoor Surveillance

NASA Astrophysics Data System (ADS)

Taha Saquib, Syed M.; Hameed, Sarmad; Usman Ali, Syed M.; Jafri, Raza; Amin, Imran

2013-12-01

This work is based upon electronic automation and Smart Control techniques, which constitute the basis of Control Area Network (CAN) and Personal Area Network (PAN). Bluetooth technology has been interfaced with a programmable controller to provide multi-dimensional vehicle control. A network is proposed which contains a remote, mobile host controller and an android operating system based mobile set (Client). The client communicates with a host controller through a Bluetooth device. The system incorporates duplex communication after successful confirmation between the host and the client; the android based mobile unit controls the vehicle through the Bluetooth module.

Space Network Control Conference on Resource Allocation Concepts and Approaches

NASA Technical Reports Server (NTRS)

Moe, Karen L. (Editor)

1991-01-01

The results are presented of the Space Network Control (SNC) Conference. In the late 1990s, when the Advanced Tracking and Data Relay Satellite System is operational, Space Network communication services will be supported and controlled by the SNC. The goals of the conference were to survey existing resource allocation concepts and approaches, to identify solutions applicable to the Space Network, and to identify avenues of study in support of the SNC development. The conference was divided into three sessions: (1) Concepts for Space Network Allocation; (2) SNC and User Payload Operations Control Center (POCC) Human-Computer Interface Concepts; and (3) Resource Allocation Tools, Technology, and Algorithms. Key recommendations addressed approaches to achieving higher levels of automation in the scheduling process.

NASA Integrated Network Monitor and Control Software Architecture

NASA Technical Reports Server (NTRS)

Shames, Peter; Anderson, Michael; Kowal, Steve; Levesque, Michael; Sindiy, Oleg; Donahue, Kenneth; Barnes, Patrick

2012-01-01

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation office (SCaN) has commissioned a series of trade studies to define a new architecture intended to integrate the three existing networks that it operates, the Deep Space Network (DSN), Space Network (SN), and Near Earth Network (NEN), into one integrated network that offers users a set of common, standardized, services and interfaces. The integrated monitor and control architecture utilizes common software and common operator interfaces that can be deployed at all three network elements. This software uses state-of-the-art concepts such as a pool of re-programmable equipment that acts like a configurable software radio, distributed hierarchical control, and centralized management of the whole SCaN integrated network. For this trade space study a model-based approach using SysML was adopted to describe and analyze several possible options for the integrated network monitor and control architecture. This model was used to refine the design and to drive the costing of the four different software options. This trade study modeled the three existing self standing network elements at point of departure, and then described how to integrate them using variations of new and existing monitor and control system components for the different proposed deployments under consideration. This paper will describe the trade space explored, the selected system architecture, the modeling and trade study methods, and some observations on useful approaches to implementing such model based trade space representation and analysis.

Stationary and structural control in gene regulatory networks: basic concepts

NASA Astrophysics Data System (ADS)

Dougherty, Edward R.; Pal, Ranadip; Qian, Xiaoning; Bittner, Michael L.; Datta, Aniruddha

2010-01-01

A major reason for constructing gene regulatory networks is to use them as models for determining therapeutic intervention strategies by deriving ways of altering their long-run dynamics in such a way as to reduce the likelihood of entering undesirable states. In general, two paradigms have been taken for gene network intervention: (1) stationary external control is based on optimally altering the status of a control gene (or genes) over time to drive network dynamics; and (2) structural intervention involves an optimal one-time change of the network structure (wiring) to beneficially alter the long-run behaviour of the network. These intervention approaches have mainly been developed within the context of the probabilistic Boolean network model for gene regulation. This article reviews both types of intervention and applies them to reducing the metastatic competence of cells via intervention in a melanoma-related network.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

PubMed

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

Social Network Resources and Management of Hypertension*

PubMed Central

Cornwell, Erin York; Waite, Linda J.

2013-01-01

Hypertension is one of the most prevalent chronic diseases among older adults, but rates of blood pressure control are low. In this paper, we explore the role of social network ties and network-based resources (e.g., information and support) in hypertension diagnosis and management. We use data from the National Social Life, Health, and Aging Project (NSHAP) to identify older adults with undiagnosed or uncontrolled hypertension. We find that network characteristics and emotional support are associated with hypertension diagnosis and control. Importantly, the risks of undiagnosed and uncontrolled hypertension are lower among those with larger social networks -- if they discuss health issues with their network members. When these lines of communication are closed, network size is associated with greater risk of undiagnosed and uncontrolled hypertension. Health care utilization partially mediates associations with diagnosis, but the benefits of network resources for hypertension control do not seem to stem from health-related behaviors. PMID:22660826