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THREAT ANTICIPATION AND DECEPTIVE REASONING USING BAYESIAN BELIEF NETWORKS

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

Allgood, Glenn O; Olama, Mohammed M; Lake, Joe E

Recent events highlight the need for tools to anticipate threats posed by terrorists. Assessing these threats requires combining information from disparate data sources such as analytic models, simulations, historical data, sensor networks, and user judgments. These disparate data can be combined in a coherent, analytically defensible, and understandable manner using a Bayesian belief network (BBN). In this paper, we develop a BBN threat anticipatory model based on a deceptive reasoning algorithm using a network engineering process that treats the probability distributions of the BBN nodes within the broader context of the system development process.
Validation of the thermal challenge problem using Bayesian Belief Networks.

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

McFarland, John; Swiler, Laura Painton

The thermal challenge problem has been developed at Sandia National Laboratories as a testbed for demonstrating various types of validation approaches and prediction methods. This report discusses one particular methodology to assess the validity of a computational model given experimental data. This methodology is based on Bayesian Belief Networks (BBNs) and can incorporate uncertainty in experimental measurements, in physical quantities, and model uncertainties. The approach uses the prior and posterior distributions of model output to compute a validation metric based on Bayesian hypothesis testing (a Bayes' factor). This report discusses various aspects of the BBN, specifically in the context ofmore » the thermal challenge problem. A BBN is developed for a given set of experimental data in a particular experimental configuration. The development of the BBN and the method for ''solving'' the BBN to develop the posterior distribution of model output through Monte Carlo Markov Chain sampling is discussed in detail. The use of the BBN to compute a Bayes' factor is demonstrated.« less
Development of an Integrated Team Training Design and Assessment Architecture to Support Adaptability in Healthcare Teams

DTIC Science & Technology

2016-10-01

and implementation of embedded, adaptive feedback and performance assessment. The investigators also initiated work designing a Bayesian Belief ...training; Teamwork; Adaptive performance; Leadership; Simulation; Modeling; Bayesian belief networks (BBN) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...Trauma teams Team training Teamwork Adaptability Adaptive performance Leadership Simulation Modeling Bayesian belief networks (BBN) 6
A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.

PubMed

Nojavan A, Farnaz; Qian, Song S; Paerl, Hans W; Reckhow, Kenneth H; Albright, Elizabeth A

2014-06-15

The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Development of a Bayesian Belief Network Runway Incursion Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2014-01-01

In a previous paper, a statistical analysis of runway incursion (RI) events was conducted to ascertain their relevance to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to perhaps several of the AvSP top ten TC. That data also identified several primary causes and contributing factors for RI events that served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events. The system-level BBN model will allow NASA to generically model the causes of RI events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of RI events in particular, and to improve runway safety in general. The development, structure and assessment of that BBN for RI events by a Subject Matter Expert panel are documented in this paper.
Development of a Bayesian Belief Network Runway Incursion and Excursion Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2014-01-01

In a previous work, a statistical analysis of runway incursion (RI) event data was conducted to ascertain the relevance of this data to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to several of the AvSP top ten TC and identified numerous primary causes and contributing factors of RI events. The statistical analysis served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events, also previously reported. Through literature searches and data analysis, this RI event network has now been extended to also model runway excursion (RE) events. These RI and RE event networks have been further modified and vetted by a Subject Matter Expert (SME) panel. The combined system-level BBN model will allow NASA to generically model the causes of RI and RE events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of runway safety incidents/accidents, and to improve runway safety in general. The development and structure of the BBN for both RI and RE events are documented in this paper.
Development of a Bayesian model to estimate health care outcomes in the severely wounded

PubMed Central

Stojadinovic, Alexander; Eberhardt, John; Brown, Trevor S; Hawksworth, Jason S; Gage, Frederick; Tadaki, Douglas K; Forsberg, Jonathan A; Davis, Thomas A; Potter, Benjamin K; Dunne, James R; Elster, E A

2010-01-01

Background: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations. Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN) and step-wise logistic regression (LR). Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC) from receiver operating characteristics (ROC) curves. Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79), intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81), and wound healing (AUC: LR, 0.91; BBN, 0.72) showed strong AUC. Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold cross-validation and further confirmed through logistic regression modeling. The method warrants further development and independent validation in other, more diverse patient populations. PMID:21197361
A Bayesian Belief Network of Threat Anticipation and Terrorist Motivations

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

Olama, Mohammed M; Allgood, Glenn O; Davenport, Kristen M

Recent events highlight the need for efficient tools for anticipating the threat posed by terrorists, whether individual or groups. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, halting an event in process, and ultimately mitigating and managing the consequences of an event. To analyze such components, one must understand various aspects of threat elements like physical assets and their economic and social impacts. To this aim, we developed a three-layer Bayesian belief network (BBN) model that takes into consideration the relative threat of an attack against a particular asset (physical layer) asmore » well as the individual psychology and motivations that would induce a person to either act alone or join a terrorist group and commit terrorist acts (social and economic layers). After researching the many possible motivations to become a terrorist, the main factors are compiled and sorted into categories such as initial and personal indicators, exclusion factors, and predictive behaviors. Assessing such threats requires combining information from disparate data sources most of which involve uncertainties. BBN combines these data in a coherent, analytically defensible, and understandable manner. The developed BBN model takes into consideration the likelihood and consequence of a threat in order to draw inferences about the risk of a terrorist attack so that mitigation efforts can be optimally deployed. The model is constructed using a network engineering process that treats the probability distributions of all the BBN nodes within the broader context of the system development process.« less
[Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network].

PubMed

Noh, Wonjung; Seomun, Gyeongae

2015-06-01

This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.
Understanding Migration as an Adaptation in Deltas Using a Bayesian Network Model

NASA Astrophysics Data System (ADS)

Lázár, A. N.; Adams, H.; de Campos, R. S.; Mortreux, C. C.; Clarke, D.; Nicholls, R. J.; Amisigo, B. A.

2016-12-01

Deltas are hotspots of high population density, fertile lands and dramatic environmental and anthropogenic pressures and changes. Amongst other environmental factors, sea level rise, soil salinization, water shortages and erosion threaten people's livelihoods and wellbeing. As a result, there is a growing concern that significant environmental change induced migration might occur from these areas. Migration, however, is already happening for economic, education and other reasons (e.g. livelihood change, marriage, planned relocation, etc.). Migration hence has multiple, interlinked drivers and depending on the perspective, can be considered as a positive or negative phenomenon. The DECCMA project (Deltas, Vulnerability & Climate Change: Migration & Adaptation) studies migration as part of a suite of adaptation options available to the coastal populations in the Ganges delta in Bangladesh, the Mahanadi delta in India and the Volta delta in Ghana. It aims to develop a holistic framework of analysis that assesses the impact of climate and environmental change on the migration patterns of these areas. This assessment framework will couple environmental, socio-economics and governance dimensions in an attempt to synthesise drivers and barriers and allow testing of plausible future scenarios. One of the integrative methods of DECCMA is a Bayesian Belief Network (BBN) model describing the decision-making of a coastal household. BBN models are built on qualitative and quantitative observations/expert knowledge and describe the probability of different events/responses etc. BBN models are especially useful to capture uncertainties of large systems and engaging with stakeholders. The DECCMA BBN model is based on household survey results from delta migrant sending areas. This presentation will describe model elements (livelihood sensitivity to climate change, local and national adaptation options, household characteristics/attitude, social networks, household decision) and initial outputs on migration and in-situ adaptation. In doing so we illustrate some key causal relationships between changes in the environment, livelihoods and migration decision.
Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation.

Treesearch

B.G. Marcot; J.D. Steventon; G.D. Sutherland; R.K. McCann

2006-01-01

We provide practical guidelines for developing, testing, and revising Bayesian belief networks (BBNs). Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model...
Developing a Methodology for Eliciting Subjective Probability Estimates During Expert Evaluations of Safety Interventions: Application for Bayesian Belief Networks

NASA Technical Reports Server (NTRS)

Wiegmann, Douglas A.a

2005-01-01

The NASA Aviation Safety Program (AvSP) has defined several products that will potentially modify airline and/or ATC operations, enhance aircraft systems, and improve the identification of potential hazardous situations within the National Airspace System (NAS). Consequently, there is a need to develop methods for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the judgments to develop Bayesian Belief Networks (BBN's) that model the potential impact that specific interventions may have. Specifically, the present report summarizes methodologies for improving the elicitation of probability estimates during expert evaluations of AvSP products for use in BBN's. The work involved joint efforts between Professor James Luxhoj from Rutgers University and researchers at the University of Illinois. The Rutgers' project to develop BBN's received funding by NASA entitled "Probabilistic Decision Support for Evaluating Technology Insertion and Assessing Aviation Safety System Risk." The proposed project was funded separately but supported the existing Rutgers' program.
A Bayesian Belief Network framework to predict SOC stock change: the Veneto region (Italy) case study

NASA Astrophysics Data System (ADS)

Dal Ferro, Nicola; Quinn, Claire Helen; Morari, Francesco

2017-04-01

A key challenge for soil scientists is predicting agricultural management scenarios that combine crop productions with high standards of environmental quality. In this context, reversing the soil organic carbon (SOC) decline in croplands is required for maintaining soil fertility and contributing to mitigate GHGs emissions. Bayesian belief networks (BBN) are probabilistic models able to accommodate uncertainty and variability in the predictions of the impacts of management and environmental changes. By linking multiple qualitative and quantitative variables in a cause-and-effect relationships, BBNs can be used as a decision support system at different spatial scales to find best management strategies in the agroecosystems. In this work we built a BBN to model SOC dynamics (0-30 cm layer) in the low-lying plain of Veneto region, north-eastern Italy, and define best practices leading to SOC accumulation and GHGs (CO2-equivalent) emissions reduction. Regional pedo-climatic, land use and management information were combined with experimental and modelled data on soil C dynamics as natural and anthropic key drivers affecting SOC stock change. Moreover, utility nodes were introduced to determine optimal decisions for mitigating GHGs emissions from croplands considering also three different IPCC climate scenarios. The network was finally validated with real field data in terms of SOC stock change. Results showed that the BBN was able to model real SOC stock changes, since validation slightly overestimated SOC reduction (+5%) at the expenses of its accumulation. At regional level, probability distributions showed 50% of SOC loss, while only 17% of accumulation. However, the greatest losses (34%) were associated with low reduction rates (100-500 kg C ha-1 y-1), followed by 33% of stabilized conditions (-100 < SOC < 100 kg ha-1 y-1). Land use management (especially tillage operations and soil cover) played a primary role to affect SOC stock change, while climate conditions were only slightly involved in C regulation within the 0-30 cm layer. The proposed BBN framework was flexible to perform both field-scale validation and regional-scale predictions. Moreover, BBN provided guidelines for improved land management strategies in a perspective of climate change scenarios, although further validation, including a broader set of experimental data, is needed to strengthen the outcomes across Veneto region.
Prediction of near-term breast cancer risk using a Bayesian belief network

NASA Astrophysics Data System (ADS)

Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David

2013-03-01

Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.
COmmunications and Networking with QUantum Operationally-Secure Technology for Maritime Deployment (CONQUEST)

DTIC Science & Technology

2017-03-06

Raytheon BBN Technologies ; Dr. Saikat Guha Contractor Address: 10 Moulton Street, Cambridge, MA 02138 Title of the Project : COmmunications and...BBN Technologies 10 Moulton Street Cambridge, MA 02138 6 March 2017 US Navy Office of Naval Research One Liberty Center 875 North Randolph...Networking with QUantum operationally-Secure Technology for Maritime Deployment (CONQUEST) Contract Period of Performance: 2 September 2016 – 1
A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment

PubMed Central

Chadès, Iadine

2017-01-01

Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection. PMID:28686651
A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment.

PubMed

Nicol, Sam; Chadès, Iadine

2017-01-01

Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.
Gravitational-wave stochastic background from cosmic strings.

PubMed

Siemens, Xavier; Mandic, Vuk; Creighton, Jolien

2007-03-16

We consider the stochastic background of gravitational waves produced by a network of cosmic strings and assess their accessibility to current and planned gravitational wave detectors, as well as to big bang nucleosynthesis (BBN), cosmic microwave background (CMB), and pulsar timing constraints. We find that current data from interferometric gravitational wave detectors, such as Laser Interferometer Gravitational Wave Observatory (LIGO), are sensitive to areas of parameter space of cosmic string models complementary to those accessible to pulsar, BBN, and CMB bounds. Future more sensitive LIGO runs and interferometers such as Advanced LIGO and Laser Interferometer Space Antenna (LISA) will be able to explore substantial parts of the parameter space.
Constraining f(T) teleparallel gravity by big bang nucleosynthesis: f(T) cosmology and BBN.

PubMed

Capozziello, S; Lambiase, G; Saridakis, E N

2017-01-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f ( T ) gravity. The three most studied viable f ( T ) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f ( T ) models can successfully satisfy the BBN constraints.
A probabilistic method to diagnose faults of air handling units

NASA Astrophysics Data System (ADS)

Dey, Debashis

Air handling unit (AHU) is one of the most extensively used equipment in large commercial buildings. This device is typically customized and lacks quality system integration which can result in hardwire failures and controller errors. Air handling unit Performance Assessment Rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon sensor data and control signals that are commonly available in these systems. Although APAR has many advantages over other methods, for example no training data required and easy to implement commercially, most of the time it is unable to provide the diagnosis of the faults. For instance, a fault on temperature sensor could be fixed bias, drifting bias, inappropriate location, complete failure. Also a fault in mixing box can be return and outdoor damper leak or stuck. In addition, when multiple rules are satisfied the list of faults increases. There is no proper way to have the correct diagnosis for rule based fault detection system. To overcome this limitation we proposed Bayesian Belief Network (BBN) as a diagnostic tool. BBN can be used to simulate diagnostic thinking of FDD experts through a probabilistic way. In this study we developed a new way to detect and diagnose faults in AHU through combining APAR rules and Bayesian Belief network. Bayesian Belief Network is used as a decision support tool for rule based expert system. BBN is highly capable to prioritize faults when multiple rules are satisfied simultaneously. Also it can get information from previous AHU operating conditions and maintenance records to provide proper diagnosis. The proposed model is validated with real time measured data of a campus building at University of Texas at San Antonio (UTSA).The results show that BBN is correctly able to prioritize faults which can be verified by manual investigation.

Realistic Simulation for Body Area and Body-To-Body Networks

PubMed Central

Alam, Muhammad Mahtab; Ben Hamida, Elyes; Ben Arbia, Dhafer; Maman, Mickael; Mani, Francesco; Denis, Benoit; D’Errico, Raffaele

2016-01-01

In this paper, we present an accurate and realistic simulation for body area networks (BAN) and body-to-body networks (BBN) using deterministic and semi-deterministic approaches. First, in the semi-deterministic approach, a real-time measurement campaign is performed, which is further characterized through statistical analysis. It is able to generate link-correlated and time-varying realistic traces (i.e., with consistent mobility patterns) for on-body and body-to-body shadowing and fading, including body orientations and rotations, by means of stochastic channel models. The full deterministic approach is particularly targeted to enhance IEEE 802.15.6 proposed channel models by introducing space and time variations (i.e., dynamic distances) through biomechanical modeling. In addition, it helps to accurately model the radio link by identifying the link types and corresponding path loss factors for line of sight (LOS) and non-line of sight (NLOS). This approach is particularly important for links that vary over time due to mobility. It is also important to add that the communication and protocol stack, including the physical (PHY), medium access control (MAC) and networking models, is developed for BAN and BBN, and the IEEE 802.15.6 compliance standard is provided as a benchmark for future research works of the community. Finally, the two approaches are compared in terms of the successful packet delivery ratio, packet delay and energy efficiency. The results show that the semi-deterministic approach is the best option; however, for the diversity of the mobility patterns and scenarios applicable, biomechanical modeling and the deterministic approach are better choices. PMID:27104537
Realistic Simulation for Body Area and Body-To-Body Networks.

PubMed

Alam, Muhammad Mahtab; Ben Hamida, Elyes; Ben Arbia, Dhafer; Maman, Mickael; Mani, Francesco; Denis, Benoit; D'Errico, Raffaele

2016-04-20

In this paper, we present an accurate and realistic simulation for body area networks (BAN) and body-to-body networks (BBN) using deterministic and semi-deterministic approaches. First, in the semi-deterministic approach, a real-time measurement campaign is performed, which is further characterized through statistical analysis. It is able to generate link-correlated and time-varying realistic traces (i.e., with consistent mobility patterns) for on-body and body-to-body shadowing and fading, including body orientations and rotations, by means of stochastic channel models. The full deterministic approach is particularly targeted to enhance IEEE 802.15.6 proposed channel models by introducing space and time variations (i.e., dynamic distances) through biomechanical modeling. In addition, it helps to accurately model the radio link by identifying the link types and corresponding path loss factors for line of sight (LOS) and non-line of sight (NLOS). This approach is particularly important for links that vary over time due to mobility. It is also important to add that the communication and protocol stack, including the physical (PHY), medium access control (MAC) and networking models, is developed for BAN and BBN, and the IEEE 802.15.6 compliance standard is provided as a benchmark for future research works of the community. Finally, the two approaches are compared in terms of the successful packet delivery ratio, packet delay and energy efficiency. The results show that the semi-deterministic approach is the best option; however, for the diversity of the mobility patterns and scenarios applicable, biomechanical modeling and the deterministic approach are better choices.
Standard big bang nucleosynthesis and primordial CNO abundances after Planck

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

Coc, Alain; Uzan, Jean-Philippe; Vangioni, Elisabeth, E-mail: coc@csnsm.in2p3.fr, E-mail: uzan@iap.fr, E-mail: vangioni@iap.fr

Primordial or big bang nucleosynthesis (BBN) is one of the three historical strong evidences for the big bang model. The recent results by the Planck satellite mission have slightly changed the estimate of the baryonic density compared to the previous WMAP analysis. This article updates the BBN predictions for the light elements using the cosmological parameters determined by Planck, as well as an improvement of the nuclear network and new spectroscopic observations. There is a slight lowering of the primordial Li/H abundance, however, this lithium value still remains typically 3 times larger than its observed spectroscopic abundance in halo starsmore » of the Galaxy. According to the importance of this ''lithium problem{sup ,} we trace the small changes in its BBN calculated abundance following updates of the baryonic density, neutron lifetime and networks. In addition, for the first time, we provide confidence limits for the production of {sup 6}Li, {sup 9}Be, {sup 11}B and CNO, resulting from our extensive Monte Carlo calculation with our extended network. A specific focus is cast on CNO primordial production. Considering uncertainties on the nuclear rates around the CNO formation, we obtain CNO/H ≈ (5-30)×10{sup -15}. We further improve this estimate by analyzing correlations between yields and reaction rates and identified new influential reaction rates. These uncertain rates, if simultaneously varied could lead to a significant increase of CNO production: CNO/H∼10{sup -13}. This result is important for the study of population III star formation during the dark ages.« less
Use of Bayesian networks in predicting contamination of drinking water with E. coli in rural Vietnam.

PubMed

Hall, David C; Le, Quynh B

2017-06-01

More than 70 million Vietnamese rely on small-scale farming for some form of household income. Water on many of those farms is contaminated with waste, including animal manure, partly due to non-sustainable waste management. This increases the risk of water-related zoonotic disease transmission. The purpose of this research was to examine the impact of various demographic and management factors on the likelihood of finding Escherichia coli in drinking water sourced from wells and rainwater on farms in Vietnam. A Bayesian Belief Network (BBN) was designed to describe association between various deterministic and probabilistic variables gathered from 600 small-scale integrated (SSI) farmers in Vietnam. The variables relate to E. coli content of their drinking water sourced on-farm from wells and rainwater, and stored in on-farm large vessels, including concrete water tanks. The BBN was developed using the Netica software tool; the model was calibrated and goodness of fit examined using concordance of predictability. Sensitivity analysis of the model revealed that choice variables, including engagement in mitigation of water contamination and livestock management activities, were particularly likely to influence endpoint values, reflecting the highly variable and impactful nature of preferences, attitudes and beliefs relating to mitigation strategies. Quantitative variables including numbers of livestock (particularly chickens) and income also had a high impact. The highest concordance (62%) was achieved with the BBN reported in this paper. This BBN model of SSI farming in Vietnam is helpful in understanding the complexity of small-scale agriculture and how various factors work in concert to influence contamination of on-farm drinking water as indicated by the presence of E. coli. The model will also be useful for identifying and estimating the impact of policy options such as improved delivery of clean water management training for rural areas, particularly where such analysis is combined with other analytical and policy tools. With appropriate knowledge translation, the model results will be particularly useful in helping SSI farmers understand their options for engaging in public health mitigation strategies addressing clean water that do not significantly disrupt their agriculture-based livelihoods. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Packet Radio Temporary Note Index.

DTIC Science & Technology

1984-05-07

Dynamic Control in Carrier Sense Multiple Access 180 Cross-Radio Debugger Beeler 06/76 BBN 179 New Capabilities of the PR Gitman 05/76 NAC Simulation...Program 178 An Approximate Analytical Model for Gitman 05/76 NAC Initialization of Single Hop PRNETs 177 SPP Definition Beeler 04/76 BBN 176 PR Protocol...Sussman 03/79 BBN Labeling Process (Revision 7) 173 Interfacing Terminals to the PRN Fralick 04/76 BBN 172 Connectivity Issues in Mobile PR Gitman 03/76
Creating COMFORT: A Communication-Based Model for Breaking Bad News

ERIC Educational Resources Information Center

Villagran, Melinda; Goldsmith, Joy; Wittenberg-Lyles, Elaine; Baldwin, Paula

2010-01-01

This study builds upon existing protocols for breaking bad news (BBN), and offers an interaction-based approach to communicating comfort to patients and their families. The goal was to analyze medical students' (N = 21) videotaped standardized patient BBN interactions after completing an instructional unit on a commonly used BBN protocol, commonly…
Hydroacoustic propagation grids for the CTBT knowledge databaes BBN technical memorandum W1303

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

J. Angell

1998-05-01

The Hydroacoustic Coverage Assessment Model (HydroCAM) has been used to develop components of the hydroacoustic knowledge database required by operational monitoring systems, particularly the US National Data Center (NDC). The database, which consists of travel time, amplitude correction and travel time standard deviation grids, is planned to support source location, discrimination and estimation functions of the monitoring network. The grids will also be used under the current BBN subcontract to support an analysis of the performance of the International Monitoring System (IMS) and national sensor systems. This report describes the format and contents of the hydroacoustic knowledgebase grids, and themore » procedures and model parameters used to generate these grids. Comparisons between the knowledge grids, measured data and other modeled results are presented to illustrate the strengths and weaknesses of the current approach. A recommended approach for augmenting the knowledge database with a database of expected spectral/waveform characteristics is provided in the final section of the report.« less
A nanomaterial release model for waste shredding using a Bayesian belief network

NASA Astrophysics Data System (ADS)

Shandilya, Neeraj; Ligthart, Tom; van Voorde, Imelda; Stahlmecke, Burkhard; Clavaguera, Simon; Philippot, Cecile; Ding, Yaobo; Goede, Henk

2018-02-01

The shredding of waste of electrical and electronic equipment (WEEE) and other products, incorporated with nanomaterials, can lead to a substantial release of nanomaterials. Considering the uncertainty, complexity, and scarcity of experimental data on release, we present the development of a Bayesian belief network (BBN) model. This baseline model aims to give a first prediction of the release of nanomaterials (excluding nanofibers) during their mechanical shredding. With a focus on the description of the model development methodology, we characterize nanomaterial release in terms of number, size, mass, and composition of released particles. Through a sensitivity analysis of the model, we find the material-specific parameters like affinity of nanomaterials to the matrix of the composite and their state of dispersion inside the matrix to reduce the nanomaterial release up to 50%. The shredder-specific parameters like number of shafts in a shredder and input and output size of the material for shredding could minimize it up to 98%. The comparison with two experimental test cases shows promising outcome on the prediction capacity of the model. As additional experimental data on nanomaterial release becomes available, the model is able to further adapt and update risk forecasts. When adapting the model with additional expert beliefs, experts should be selected using criteria, e.g., substantial contribution to nanomaterial and/or particulate matter release-related scientific literature, the capacity and willingness to contribute to further development of the BBN model, and openness to accepting deviating opinions. [Figure not available: see fulltext.
Spatial Bayesian belief networks as a planning decision tool for mapping ecosystem services trade-offs on forested landscapes.

PubMed

Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro

2016-01-01

An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. Copyright © 2015 Elsevier Inc. All rights reserved.
Development and Execution of the RUNSAFE Runway Safety Bayesian Belief Network Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2015-01-01

One focus area of the National Aeronautics and Space Administration (NASA) is to improve aviation safety. Runway safety is one such thrust of investigation and research. The two primary components of this runway safety research are in runway incursion (RI) and runway excursion (RE) events. These are adverse ground-based aviation incidents that endanger crew, passengers, aircraft and perhaps other nearby people or property. A runway incursion is the incorrect presence of an aircraft, vehicle or person on the protected area of a surface designated for the landing and take-off of aircraft; one class of RI events simultaneously involves two aircraft, such as one aircraft incorrectly landing on a runway while another aircraft is taking off from the same runway. A runway excursion is an incident involving only a single aircraft defined as a veer-off or overrun off the runway surface. Within the scope of this effort at NASA Langley Research Center (LaRC), generic RI, RE and combined (RI plus RE, or RUNSAFE) event models have each been developed and implemented as a Bayesian Belief Network (BBN). Descriptions of runway safety issues from the literature searches have been used to develop the BBN models. Numerous considerations surrounding the process of developing the event models have been documented in this report. The event models were then thoroughly reviewed by a Subject Matter Expert (SME) panel through multiple knowledge elicitation sessions. Numerous improvements to the model structure (definitions, node names, node states and the connecting link topology) were made by the SME panel. Sample executions of the final RUNSAFE model have been presented herein for baseline and worst-case scenarios. Finally, a parameter sensitivity analysis for a given scenario was performed to show the risk drivers. The NASA and LaRC research in runway safety event modeling through the use of BBN technology is important for several reasons. These include: 1) providing a means to clearly understand the cause and effect patterns leading to safety issues, incidents and accidents, 2) enabling the prioritization of specialty areas needing more attention to improve aviation safety, and 3) enabling the identification of gaps within NASA's Aviation Safety funding portfolio
Molecular subtype-specific immunocompetent models of high-grade urothelial carcinoma reveal differential neoantigen expression and response to immunotherapy.

PubMed

Saito, Ryoichi; Smith, Christof C; Utsumi, Takanobu; Bixby, Lisa M; Kardos, Jordan; Wobker, Sara E; Stewart, Kyle G; Chai, Shengjie; Manocha, Ujjawal; Byrd, Kevin Matthew; Damrauer, Jeffrey S; Williams, Scott E; Vincent, Benjamin G; Kim, William Y

2018-05-21

High-grade urothelial cancer contains intrinsic molecular subtypes that exhibit differences in underlying tumor biology and can be divided into luminal-like and basal-like subtypes. We describe here the first subtype-specific murine models of bladder cancer and show that Upk3a-CreERT2; Trp53L/L; PtenL/L; Rosa26LSL-Luc (UPPL: luminal-like) and BBN (basal-like) tumors are more faithful to human bladder cancer than the widely-used MB49 cells. Following engraftment into immunocompetent C57BL/6 mice, BBN tumors were more responsive to PD-1 inhibition than UPPL tumors. Responding tumors within the BBN model showed differences in immune microenvironment composition, including increased ratios of CD8+:CD4+ and memory:regulatory T cells. Finally, we predicted and confirmed immunogenicity of tumor neoantigens in each model. These UPPL and BBN models will be a valuable resource for future studies examining bladder cancer biology and immunotherapy. Copyright ©2018, American Association for Cancer Research.
An Anticipatory and Deceptive AI Utilizing Bayesian Belief Networks

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

Lake, Joe E; Allgood, Glenn O; Olama, Mohammed M

The U.S. military defines antiterrorism as the defensive posture taken against terrorist threats. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, interdicting an event in progress, and ultimately mitigating and managing the consequences of an event. Recent events highlight the need for efficient tools for training our military and homeland security officers for anticipating threats posed by terrorists. These tools need to be easy enough so that they are readily usable without substantial training, but still maintain the complexity to allow for a level of deceptive reasoning on the part of themore » opponent. To meet this need, we propose to integrate a Bayesian Belief Network (BBN) model for threat anticipation and deceptive reasoning into training simulation environments currently utilized by several organizations within the Department of Defense (DoD). BBNs have the ability to deal with various types of uncertainties; such as identities, capabilities, target attractiveness, and the combinations of the previous. They also allow for disparate types of data to be fused in a coherent, analytically defensible, and understandable manner. A BBN has been developed by ORNL uses a network engineering process that treats the probability distributions of each node with in the broader context of the system development effort as a whole, and not in isolation. The network will be integrated into the Research Network Inc,(RNI) developed Game Distributed Interactive Simulation (GDIS) as a smart artificial intelligence module. GDIS is utilized by several DoD and civilian organizations as a distributed training tool for a multiplicity of reasons. It has garnered several awards for its realism, ease of use, and popularity. One area that it still has room to excel in, as most video training tools do, is in the area of artificial intelligence of opponent combatants. It is believed that by utilizing BBN as the backbone of the artificial intelligence code, a more realistic and helpful training experience will be available and enemy combatants that move and strategize with purpose will be obtained.« less
[The applicable study of two models used in the assessment of long-term exposure to food lead].

PubMed

Jin, Ying-liang; Zhang, Ya-fei; Liu, Pei

2013-07-01

To compare the results of observed individual means (OIM) model with beta binomial-normal (BBN) model and to apply the two models to assessment of long-term dietary lead exposure. Food consumption data were obtained from the National Nutrition and Health Survey conducted in 2002 by 24-hour recall method. Contamination data were derived from the national food contamination monitoring program from 2000 to 2006 and from monitoring data of Customs exports for agricultural products between 2005 and 2006. By multiplying the average consumption of food with the average concentration of contaminant, the OIM model calculated dietary intake per day. By correcting the within-person variation and keeping the between-person variation, the BBN model built dietary intake in the long-term.Using the example of food lead data, the results of two models were compared. The high-end percentile of OIM model was higher than the BBN model in various age groups.In the general population, the dietary intake of OIM model from 25th percentile to 99.9th percentile was between 1.167 and 7.313 µg×kg(-1)×d(-1), and the dietary intake of BBN model with the same percentile range was between 1.193 and 5.729 µg×kg(-1)×d(-1). The median of various groups was similar between the two models. The dietary intakes in the general population of two models were 1.543 and 1.579 µg×kg(-1)×d(-1). The high-end percentile of OIM model is more conservative than BBN model in the long-term dietary exposure assessment.
Heavy element production in inhomogeneous big bang nucleosynthesis

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

Matsuura, Shunji; Fujimoto, Shin-ichirou; Nishimura, Sunao

2005-12-15

We present a new astrophysical site of the big bang nucleosynthesis (BBN) that are very peculiar compared with the standard BBN. Some models of the baryogenesis suggest that very high baryon density regions were formed in the early universe. On the other hand, recent observations suggest that heavy elements already exist in high red-shifts and the origin of these elements become a big puzzle. Motivated by these, we investigate BBN in very high baryon density regions. BBN proceeds in proton-rich environment, which is known to be like the p-process. However, by taking very heavy nuclei into account, we find thatmore » BBN proceeds through both the p-process and the r-process simultaneously. P-nuclei such as {sup 92}Mo, {sup 94}Mo, {sup 96}Ru, {sup 98}Ru whose origin is not well known are also synthesized.« less
Using Inertial Fusion Implosions to Measure the T+^{3}He Fusion Cross Section at Nucleosynthesis-Relevant Energies.

PubMed

Zylstra, A B; Herrmann, H W; Johnson, M Gatu; Kim, Y H; Frenje, J A; Hale, G; Li, C K; Rubery, M; Paris, M; Bacher, A; Brune, C R; Forrest, C; Glebov, V Yu; Janezic, R; McNabb, D; Nikroo, A; Pino, J; Sangster, T C; Séguin, F H; Seka, W; Sio, H; Stoeckl, C; Petrasso, R D

2016-07-15

Light nuclei were created during big-bang nucleosynthesis (BBN). Standard BBN theory, using rates inferred from accelerator-beam data, cannot explain high levels of ^{6}Li in low-metallicity stars. Using high-energy-density plasmas we measure the T(^{3}He,γ)^{6}Li reaction rate, a candidate for anomalously high ^{6}Li production; we find that the rate is too low to explain the observations, and different than values used in common BBN models. This is the first data directly relevant to BBN, and also the first use of laboratory plasmas, at comparable conditions to astrophysical systems, to address a problem in nuclear astrophysics.
Using inertial fusion implosions to measure the T + He 3 fusion cross section at nucleosynthesis-relevant energies

DOE PAGES

Zylstra, A. B.; Herrmann, H. W.; Johnson, M. Gatu; ...

2016-07-11

Light nuclei were created during big-bang nucleosynthesis (BBN). Standard BBN theory, using rates inferred from accelerator-beam data, cannot explain high levels of 6Li in low-metallicity stars. Using high energy-density plasmas we measure the T( 3He,γ) 6Li reaction rate, a candidate for anomalously high 6Li production; we find that the rate is too low to explain the observations, and different than values used in common BBN models. In conclusion, this is the first data directly relevant to BBN, and also the first use of laboratory plasmas, at comparable conditions to astrophysical systems, to address a problem in nuclear astrophysics.
Building Process Improvement Business Cases Using Bayesian Belief Networks and Monte Carlo Simulation

DTIC Science & Technology

2009-07-01

simulation. The pilot described in this paper used this two-step approach within a Define, Measure, Analyze, Improve, and Control ( DMAIC ) framework to...networks, BBN, Monte Carlo simulation, DMAIC , Six Sigma, business case 15. NUMBER OF PAGES 35 16. PRICE CODE 17. SECURITY CLASSIFICATION OF
See, reflect, learn more: qualitative analysis of breaking bad news reflective narratives.

PubMed

Karnieli-Miller, Orit; Palombo, Michal; Meitar, Dafna

2018-05-01

Breaking bad news (BBN) is a challenge that requires multiple professional competencies. BBN teaching often includes didactic and group role-playing sessions. Both are useful and important, but exclude another critical component of students' learning: day-to-day role-model observation in the clinics. Given the importance of observation and the potential benefit of reflective writing in teaching, we have incorporated reflective writing into our BBN course. The aim of this study was to enhance our understanding of the learning potential in reflective writing about BBN encounters and the ability to identify components that inhibit this learning. This was a systematic qualitative immersion/crystallization analysis of 166 randomly selected BBN narratives written by 83 senior medical students. We analysed the narratives in an iterative consensus-building process to identify the issues discussed, the lessons learned and the enhanced understanding of BBN. Having previously been unaware of, not invited to or having avoided BBN encounters, the mandatory assignment led students to search for or ask their mentors to join them in BBN encounters. Observation and reflective writing enhanced students' awareness that 'bad news' is relative and subjective, while shedding light on patients', families', physicians' and their own experiences and needs, revealing the importance of the different components of the BBN protocol. We identified diversity among the narratives and the extent of students' learning. Narrative writing provided students with an opportunity for a deliberative learning process. This led to deeper understanding of BBN encounters, of how to apply the newly taught protocol, or of the need for it. This process connected the formal and informal or hidden curricula. To maximise learning through reflective writing, students should be encouraged to write in detail about a recent observed encounter, analyse it according to the protocol, address different participants' behaviours and emotions, and identify dilemmas and clear lessons learned. © 2018 John Wiley & Sons Ltd and The Association for the Study of Medical Education.
STANDARD BIG BANG NUCLEOSYNTHESIS UP TO CNO WITH AN IMPROVED EXTENDED NUCLEAR NETWORK

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

Coc, Alain; Goriely, Stephane; Xu, Yi

Primordial or big bang nucleosynthesis (BBN) is one of the three strong pieces of evidence for the big bang model together with the expansion of the universe and cosmic microwave background radiation. In this study, we improve the standard BBN calculations taking into account new nuclear physics analyses and enlarge the nuclear network up to sodium. This is, in particular, important to evaluate the primitive value of CNO mass fraction that could affect Population III stellar evolution. For the first time we list the complete network of more than 400 reactions with references to the origin of the rates, includingmore » Almost-Equal-To 270 reaction rates calculated using the TALYS code. Together with the cosmological light elements, we calculate the primordial beryllium, boron, carbon, nitrogen, and oxygen nuclei. We performed a sensitivity study to identify the important reactions for CNO, {sup 9}Be, and boron nucleosynthesis. We re-evaluated those important reaction rates using experimental data and/or theoretical evaluations. The results are compared with precedent calculations: a primordial beryllium abundance increase by a factor of four compared to its previous evaluation, but we note a stability for B/H and for the CNO/H abundance ratio that remains close to its previous value of 0.7 Multiplication-Sign 10{sup -15}. On the other hand, the extension of the nuclear network has not changed the {sup 7}Li value, so its abundance is still 3-4 times greater than its observed spectroscopic value.« less
Dual integrin and gastrin-releasing peptide receptor targeted tumor imaging using 18F-labeled PEGylated RGD-bombesin heterodimer 18F-FB-PEG3-Glu-RGD-BBN.

PubMed

Liu, Zhaofei; Yan, Yongjun; Chin, Frederic T; Wang, Fan; Chen, Xiaoyuan

2009-01-22

Radiolabeled RGD and bombesin peptides have been extensively investigated for tumor integrin alpha(v)beta(3) and GRPR imaging, respectively. Due to the fact that many tumors are both integrin and GRPR positive, we designed and synthesized a heterodimeric peptide Glu-RGD-BBN, which is expected to be advantageous over the monomeric peptides for dual-receptor targeting. A PEG(3) spacer was attached to the glutamate alpha-amino group of Glu-RGD-BBN to enhance the (18)F labeling yield and to improve the in vivo kinetics. PEG(3)-Glu-RGD-BBN possesses the comparable GRPR and integrin alpha(v)beta(3) receptor-binding affinities as the corresponding monomers, respectively. The dual-receptor targeting properties of (18)F-FB-PEG(3)-Glu-RGD-BBN were observed in PC-3 tumor model. (18)F-FB-PEG(3)-Glu-RGD-BBN with high tumor contrast and favorable pharmacokinetics is a promising PET tracer for dual integrin and GRPR positive tumor imaging. This heterodimer strategy may also be an applicable method to develop other molecules with improved in vitro and in vivo characterizations for tumor diagnosis and therapy.

Probabilistic Volcanic Multi-Hazard Assessment at Somma-Vesuvius (Italy): coupling Bayesian Belief Networks with a physical model for lahar propagation

NASA Astrophysics Data System (ADS)

Tierz, Pablo; Woodhouse, Mark; Phillips, Jeremy; Sandri, Laura; Selva, Jacopo; Marzocchi, Warner; Odbert, Henry

2017-04-01

Volcanoes are extremely complex physico-chemical systems where magma formed at depth breaks into the planet's surface resulting in major hazards from local to global scales. Volcano physics are dominated by non-linearities, and complicated spatio-temporal interrelationships which make volcanic hazards stochastic (i.e. not deterministic) by nature. In this context, probabilistic assessments are required to quantify the large uncertainties related to volcanic hazards. Moreover, volcanoes are typically multi-hazard environments where different hazardous processes can occur whether simultaneously or in succession. In particular, explosive volcanoes are able to accumulate, through tephra fallout and Pyroclastic Density Currents (PDCs), large amounts of pyroclastic material into the drainage basins surrounding the volcano. This addition of fresh particulate material alters the local/regional hydrogeological equilibrium and increases the frequency and magnitude of sediment-rich aqueous flows, commonly known as lahars. The initiation and volume of rain-triggered lahars may depend on: rainfall intensity and duration; antecedent rainfall; terrain slope; thickness, permeability and hydraulic diffusivity of the tephra deposit; etc. Quantifying these complex interrelationships (and their uncertainties), in a tractable manner, requires a structured but flexible probabilistic approach. A Bayesian Belief Network (BBN) is a directed acyclic graph that allows the representation of the joint probability distribution for a set of uncertain variables in a compact and efficient way, by exploiting unconditional and conditional independences between these variables. Once constructed and parametrized, the BBN uses Bayesian inference to perform causal (e.g. forecast) and/or evidential reasoning (e.g. explanation) about query variables, given some evidence. In this work, we illustrate how BBNs can be used to model the influence of several variables on the generation of rain-triggered lahars and, finally, assess the probability of occurrence of lahars of different volumes. The information utilized to parametrize the BBNs includes: (1) datasets of lahar observations; (2) numerical modelling of tephra fallout and PDCs; and (3) literature data. The BBN framework provides an opportunity to quantitatively combine these different types of evidence and use them to derive a rational approach to lahar forecasting. Lastly, we couple the BBN assessments with a shallow-water physical model for lahar propagation in order to attach probabilities to the simulated hazard footprints. We develop our methodology at Somma-Vesuvius (Italy), an explosive volcano prone to rain-triggered lahars or debris flows whether right after an eruption or during inter-eruptive periods. Accounting for the variability in tephra-fallout and dense-PDC propagation and the main geomorphological features of the catchments around Somma-Vesuvius, the areas most likely of forming medium-large lahars are the flanks of the volcano and the Sarno mountains towards the east.
Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina

USGS Publications Warehouse

Tavernia, Brian G.; Stanton, John D.; Lyons, James E.

2017-11-22

Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (1614), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.
A Bayesian Belief Network Approach to Explore Alternative Decisions for Sediment Control and water Storage Capacity at Lago Lucchetti, Puerto Rico

EPA Science Inventory

A Bayesian belief network (BBN) was developed to characterize the effects of sediment accumulation on the water storage capacity of Lago Lucchetti (located in southwest Puerto Rico) and to forecast the life expectancy (usefulness) of the reservoir under different management scena...
Using Bayesian Belief Networks and event trees for volcanic hazard assessment and decision support : reconstruction of past eruptions of La Soufrière volcano, Guadeloupe and retrospective analysis of 1975-77 unrest.

NASA Astrophysics Data System (ADS)

Komorowski, Jean-Christophe; Hincks, Thea; Sparks, Steve; Aspinall, Willy; Legendre, Yoann; Boudon, Georges

2013-04-01

Since 1992, mild but persistent seismic and fumarolic unrest at La Soufrière de Guadeloupe volcano has prompted renewed concern about hazards and risks, crisis response planning, and has rejuvenated interest in geological studies. Scientists monitoring active volcanoes frequently have to provide science-based decision support to civil authorities during such periods of unrest. In these circumstances, the Bayesian Belief Network (BBN) offers a formalized evidence analysis tool for making inferences about the state of the volcano from different strands of data, allowing associated uncertainties to be treated in a rational and auditable manner, to the extent warranted by the strength of the evidence. To illustrate the principles of the BBN approach, a retrospective analysis is undertaken of the 1975-77 crisis, providing an inferential assessment of the evolving state of the magmatic system and the probability of subsequent eruption. Conditional dependencies and parameters in the BBN are characterized quantitatively by structured expert elicitation. Revisiting data available in 1976 suggests the probability of magmatic intrusion would have been evaluated high at the time, according with subsequent thinking about the volcanological nature of the episode. The corresponding probability of a magmatic eruption therefore would have been elevated in July and August 1976; however, collective uncertainty about the future course of the crisis was great at the time, even if some individual opinions were certain. From this BBN analysis, while the more likely appraised outcome - based on observational trends at 31 August 1976 - might have been 'no eruption' (mean probability 0.5; 5-95 percentile range 0.8), an imminent magmatic eruption (or blast) could have had a probability of about 0.4, almost as substantial. Thus, there was no real scientific basis to assert one scenario was more likely than the other. This retrospective evaluation adds objective probabilistic expression to the contemporary volcanological narrative, and demonstrates that a formal evidential case could have been made to support the authorities' concerns and decision to evacuate. Revisiting the circumstances of the 1976 crisis highlights many contemporary challenges of decision-making under conditions of volcanological uncertainty. We suggest the BBN concept is a suitable framework for marshalling multiple observations, model results and interpretations - and all associated uncertainties - in a methodical manner. Base-rate eruption probabilities for Guadeloupe can be updated now with a new chronology of activity suggesting that 10 major explosive phases and 9 dome-forming phases occurred in the last 9150 years, associated with ≥ 8 flank-collapses and ≥ 6-7 high-energy pyroclastic density currents (blasts). Eruptive recurrence, magnitude and intensity place quantitative constraints on La Soufrière's event tree to elaborate credible scenarios. The current unrest offers an opportunity to update the BBN model and explore the uncertainty on inferences about the system's internal state. This probabilistic formalism would provoke key questions relating to unrest evolution: 1) is the unrest hydrothermal or magmatic? 2) what controls dyke/intrusion arrest and hence failed-magmatic eruptions like 1976? 3) what conditions could lead to significant pressurization with potential for explosive activity and edifice instability, and what monitoring signs might be manifest?
Students' experiences with a longitudinal skills training program on breaking bad news: A follow-up study.

PubMed

Brouwers, M H; Bor, H; Laan, R; van Weel, C; van Weel-Baumgarten, E

2018-05-07

Breaking bad news (BBN) should be trained, preferably early and following a helical model with multiple sessions over time, including feedback on performance. It's unclear how medical students evaluate such an approach. We gathered student opinions regarding a helical BBN training programme, the feedback and emotional support they received, and the applicability of the skills training immediately after BBN skills training (Q1) and after finishing their clinical clerkships (Q2). Students find a helical curriculum useful, but this declines on follow-up. At Q2 students report less satisfaction with the amount of feedback and emotional support they received and report that the skills training was less applicable in clinical practice compared to what they reported at Q1. A helical BBN training programme with early exposure seems to lead to a shift from students being unconsciously incompetent to consciously incompetent. Students would have appreciated more emotional support and feedback. We recommend more feedback and emotional support after BBN during clerkships. The gap between classroom and practice can be diminished by emphasizing real life role play and clinical role models should demonstrate continuity and agreement between the skills that are taught and those that are used in clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.
Integration of Enhanced Propagation, Environmental Variability, and Network Performance Models into the InfraMAP Software Toolkit

DTIC Science & Technology

2007-11-01

distribution is unlimited. Z November 2007 Li DTRA01-00-C-0063 David Norris and Robert Gibson Prepared by: BBN Technologies 1300 North 17th Street Suite...TA - CD C.AUT040WS WU - 02091 David E. Norris Robert G. Gibson 7. PERVORMS ONSAIZATIMN RAW(S) AM AURS118" L PIRU OANIZATMO ASPORT...be useful in determining the relative importance with which to treat the predictions. Support of synergy-based localization - Confidence bounds
BBN-Based Portfolio Risk Assessment for NASA Technology R&D Outcome

NASA Technical Reports Server (NTRS)

Geuther, Steven C.; Shih, Ann T.

2016-01-01

The NASA Aeronautics Research Mission Directorate (ARMD) vision falls into six strategic thrusts that are aimed to support the challenges of the Next Generation Air Transportation System (NextGen). In order to achieve the goals of the ARMD vision, the Airspace Operations and Safety Program (AOSP) is committed to developing and delivering new technologies. To meet the dual challenges of constrained resources and timely technology delivery, program portfolio risk assessment is critical for communication and decision-making. This paper describes how Bayesian Belief Network (BBN) is applied to assess the probability of a technology meeting the expected outcome. The network takes into account the different risk factors of technology development and implementation phases. The use of BBNs allows for all technologies of projects in a program portfolio to be separately examined and compared. In addition, the technology interaction effects are modeled through the application of object-oriented BBNs. The paper discusses the development of simplified project risk BBNs and presents various risk results. The results presented include the probability of project risks not meeting success criteria, the risk drivers under uncertainty via sensitivity analysis, and what-if analysis. Finally, the paper shows how program portfolio risk can be assessed using risk results from BBNs of projects in the portfolio.
Commentary on "tissue-specific mutagenesis by N-butyl-N-(4-hydroxybutyl) nitrosamine as the basis for urothelial cell carcinogenesis." He Z, Kosinska W, Zhao ZL, Wu XR, Guttenplan JB, Department of Basic Science, New York University Dental College, NY, USA.: Mutat Res 2012;742(1-2):92-5 [Epub 2011 Dec 4].

PubMed

Scherr, Douglas S

2014-02-01

Bladder cancer is one of the few cancers that have been linked to carcinogens in the environment and tobacco smoke. Of the carcinogens tested in mouse chemical carcinogenesis models, N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN) is one that reproducibly causes high-grade, invasive cancers in the urinary bladder, but not in any other tissues. However, the basis for such a high-level tissue-specificity has not been explored. Using mutagenesis in lacI (Big Blue™) mice, we show here that BBN is a potent mutagen and it causes high-level of mutagenesis specifically in the epithelial cells (urothelial) of the urinary bladder. After a 2-6-week treatment of 0.05% BBN in the drinking water, mutagenesis in urothelial cells of male and female mice was about two orders of magnitude greater than the spontaneous mutation background. In contrast, mutagenesis in smooth muscle cells of the urinary bladder was about five times lower than in urothelial tissue. No appreciable increase in mutagenesis was observed in kidney, ureter, liver or forestomach. In lacI (Big Blue™) rats, BBN mutagenesis was also elevated in urothelial cells, albeit not nearly as profoundly as in mice. This provides a potential explanation as to why rats are less prone than mice to the formation of aggressive form of bladder cancer induced by BBN. Our results suggest that the propensity to BBN-triggered mutagenesis of urothelial cells underlies its heightened susceptibility to this carcinogen and that mutagenesis induced by BBN represents a novel model for initiation of bladder carcinogenesis. Copyright © 2014 Elsevier Inc. All rights reserved.
Dark/visible parallel universes and Big Bang nucleosynthesis

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

Bertulani, C. A.; Frederico, T.; Fuqua, J.

We develop a model for visible matter-dark matter interaction based on the exchange of a massive gray boson called herein the Mulato. Our model hinges on the assumption that all known particles in the visible matter have their counterparts in the dark matter. We postulate six families of particles five of which are dark. This leads to the unavoidable postulation of six parallel worlds, the visible one and five invisible worlds. A close study of big bang nucleosynthesis (BBN), baryon asymmetries, cosmic microwave background (CMB) bounds, galaxy dynamics, together with the Standard Model assumptions, help us to set a limitmore » on the mass and width of the new gauge boson. Modification of the statistics underlying the kinetic energy distribution of particles during the BBN is also discussed. The changes in reaction rates during the BBN due to a departure from the Debye-Hueckel electron screening model is also investigated.« less
Primordial nucleosynthesis

PubMed Central

Schramm, David N.

1998-01-01

With the advent of the new extragalactic deuterium observations, Big Bang nucleosynthesis (BBN) is on the verge of undergoing a transformation. In the past, the emphasis has been on demonstrating the concordance of the BBN model with the abundances of the light isotopes extrapolated back to their primordial values by using stellar and galactic evolution theories. As a direct measure of primordial deuterium is converged upon, the nature of the field will shift to using the much more precise primordial D/H to constrain the more flexible stellar and galactic evolution models (although the question of potential systematic error in 4He abundance determinations remains open). The remarkable success of the theory to date in establishing the concordance has led to the very robust conclusion of BBN regarding the baryon density. This robustness remains even through major model variations such as an assumed first-order quark-hadron phase transition. The BBN constraints on the cosmological baryon density are reviewed and demonstrate that the bulk of the baryons are dark and also that the bulk of the matter in the universe is nonbaryonic. Comparison of baryonic density arguments from Lyman-α clouds, x-ray gas in clusters, and the microwave anisotropy are made. PMID:9419322
Primordial nucleosynthesis.

PubMed

Schramm, D N

1998-01-06

With the advent of the new extragalactic deuterium observations, Big Bang nucleosynthesis (BBN) is on the verge of undergoing a transformation. In the past, the emphasis has been on demonstrating the concordance of the BBN model with the abundances of the light isotopes extrapolated back to their primordial values by using stellar and galactic evolution theories. As a direct measure of primordial deuterium is converged upon, the nature of the field will shift to using the much more precise primordial D/H to constrain the more flexible stellar and galactic evolution models (although the question of potential systematic error in 4He abundance determinations remains open). The remarkable success of the theory to date in establishing the concordance has led to the very robust conclusion of BBN regarding the baryon density. This robustness remains even through major model variations such as an assumed first-order quark-hadron phase transition. The BBN constraints on the cosmological baryon density are reviewed and demonstrate that the bulk of the baryons are dark and also that the bulk of the matter in the universe is nonbaryonic. Comparison of baryonic density arguments from Lyman-alpha clouds, x-ray gas in clusters, and the microwave anisotropy are made.
BBN with electron-sterile neutrino oscillations — the finest leptometer

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

Kirilova, Daniela, E-mail: dani@astro.bas.bg

2012-06-01

A relic lepton asymmetry orders of magnitude bigger than the baryon one may hide in the relic neutrino background. No direct theoretical or experimental limitations on its magnitude and sign are known. Only indirect cosmological constraints exist ranging from |L| < 0.01 to L < 10. Here we discuss a Big Bang Nucleosynthesis (BBN) model with late electron-sterile neutrino oscillations. The influence of L on neutrino oscillations and on nucleons freezing in the pre-BBN epoch is numerically analyzed in the full range of the oscillation parameters of the model and for |L| ≥ 10{sup −10}. The asymmetry-oscillations interplay is studiedmore » in detail and the behavior of L for different oscillation parameters is found. L effect on the primordially produced {sup 4}He is precisely studied. It is shown that this BBN model is a fine leptometer, capable of feeling extremely small relic lepton asymmetry — |L| > 10{sup −8}. The case of oscillations generated asymmetry by late electron-sterile oscillations and its effect on the primordial {sup 4}He is also briefly discussed. The instability region of the asymmetry growth is obtained.« less
Constraining nuclear data via cosmological observations: Neutrino energy transport and big bang nucleosynthesis

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

Paris, Mark W.; Fuller, George M.; Grohs, Evan Bradley

Here, we introduce a new computational capability that moves toward a self-consistent calculation of neutrino transport and nuclear reactions for big bang nucleosynthesis (BBN). Such a self-consistent approach is needed to be able to extract detailed information about nuclear reactions and physics beyond the standard model from precision cosmological observations of primordial nuclides and the cosmic microwave background radiation. We also calculate the evolution of the early universe through the epochs of weak decoupling, weak freeze-out and big bang nucleosynthesis (BBN) by simultaneously coupling a full strong, electromagnetic, and weak nuclear reaction network with a multi-energy group Boltzmann neutrino energymore » transport scheme. The modular structure of our approach allows the dissection of the relative contributions of each process responsible for evolving the dynamics of the early universe. Such an approach allows a detailed account of the evolution of the active neutrino energy distribution functions alongside and self-consistently with the nuclear reactions and entropy/heat generation and flow between the neutrino and photon/electron/positron/baryon plasma components. Our calculations reveal nonlinear feedback in the time evolution of neutrino distribution functions and plasma thermodynamic conditions. We discuss the time development of neutrino spectral distortions and concomitant entropy production and extraction from the plasma. These effects result in changes in the computed values of the BBN deuterium and helium-4 yields that are on the order of a half-percent relative to a baseline standard BBN calculation with no neutrino transport. This is an order of magnitude larger effect than in previous estimates. For particular implementations of quantum corrections in plasma thermodynamics, our calculations show a 0.4% increase in deuterium and a 0.6% decrease in 4He over our baseline. The magnitude of these changes are on the order of uncertainties in the nuclear physics for the case of deuterium and are potentially significant for the error budget of helium in upcoming cosmological observations.« less
Constraining nuclear data via cosmological observations: Neutrino energy transport and big bang nucleosynthesis

NASA Astrophysics Data System (ADS)

Paris, Mark; Fuller, George; Grohs, Evan; Kishimoto, Chad; Vlasenko, Alexey

2017-09-01

We introduce a new computational capability that moves toward a self-consistent calculation of neutrino transport and nuclear reactions for big bang nucleosynthesis (BBN). Such a self-consistent approach is needed to be able to extract detailed information about nuclear reactions and physics beyond the standard model from precision cosmological observations of primordial nuclides and the cosmic microwave background radiation. We calculate the evolution of the early universe through the epochs of weak decoupling, weak freeze-out and big bang nucleosynthesis (BBN) by simultaneously coupling a full strong, electromagnetic, and weak nuclear reaction network with a multi-energy group Boltzmann neutrino energy transport scheme. The modular structure of our approach allows the dissection of the relative contributions of each process responsible for evolving the dynamics of the early universe. Such an approach allows a detailed account of the evolution of the active neutrino energy distribution functions alongside and self-consistently with the nuclear reactions and entropy/heat generation and 'ow between the neutrino and photon/electron/positron/baryon plasma components. Our calculations reveal nonlinear feedback in the time evolution of neutrino distribution functions and plasma thermodynamic conditions. We discuss the time development of neutrino spectral distortions and concomitant entropy production and extraction from the plasma. These e↑ects result in changes in the computed values of the BBN deuterium and helium-4 yields that are on the order of a half-percent relative to a baseline standard BBN calculation with no neutrino transport. This is an order of magnitude larger e↑ect than in previous estimates. For particular implementations of quantum corrections in plasma thermodynamics, our calculations show a 0.4% increase in deuterium and a 0.6% decrease in 4He over our baseline. The magnitude of these changes are on the order of uncertainties in the nuclear physics for the case of deuterium and are potentially signi↓cant for the error budget of helium in upcoming cosmological observations.
Constraining nuclear data via cosmological observations: Neutrino energy transport and big bang nucleosynthesis

DOE PAGES

Paris, Mark W.; Fuller, George M.; Grohs, Evan Bradley; ...

2017-09-13

Here, we introduce a new computational capability that moves toward a self-consistent calculation of neutrino transport and nuclear reactions for big bang nucleosynthesis (BBN). Such a self-consistent approach is needed to be able to extract detailed information about nuclear reactions and physics beyond the standard model from precision cosmological observations of primordial nuclides and the cosmic microwave background radiation. We also calculate the evolution of the early universe through the epochs of weak decoupling, weak freeze-out and big bang nucleosynthesis (BBN) by simultaneously coupling a full strong, electromagnetic, and weak nuclear reaction network with a multi-energy group Boltzmann neutrino energymore » transport scheme. The modular structure of our approach allows the dissection of the relative contributions of each process responsible for evolving the dynamics of the early universe. Such an approach allows a detailed account of the evolution of the active neutrino energy distribution functions alongside and self-consistently with the nuclear reactions and entropy/heat generation and flow between the neutrino and photon/electron/positron/baryon plasma components. Our calculations reveal nonlinear feedback in the time evolution of neutrino distribution functions and plasma thermodynamic conditions. We discuss the time development of neutrino spectral distortions and concomitant entropy production and extraction from the plasma. These effects result in changes in the computed values of the BBN deuterium and helium-4 yields that are on the order of a half-percent relative to a baseline standard BBN calculation with no neutrino transport. This is an order of magnitude larger effect than in previous estimates. For particular implementations of quantum corrections in plasma thermodynamics, our calculations show a 0.4% increase in deuterium and a 0.6% decrease in 4He over our baseline. The magnitude of these changes are on the order of uncertainties in the nuclear physics for the case of deuterium and are potentially significant for the error budget of helium in upcoming cosmological observations.« less
Extensible Adaptive System for STEM Learning

DTIC Science & Technology

2013-07-16

Copyright 2013 Raytheon BBN Technologies Corp. All Rights Reserved ONR STEM Grand Challenge Extensible Adaptive System for STEM Learning ...Contract # N00014-12-C-0535 Raytheon BBN Technologies Corp. (BBN) Reference # 14217 In partial fulfillment of contract deliverable item # A001...Quarterly Progress Report #2 April 7, 2013 –July 6, 2013 Submitted July 16, 2013 BBN Technical POC: John Makhoul Raytheon BBN Technologies
COmmunications and Networking with QUantum operationally Secure Technology for Maritime Deployment (CONQUEST)

DTIC Science & Technology

2016-12-02

Quantum Computing , University of Waterloo, Waterloo ON, N2L 3G1, Canada (Dated: December 1, 2016) Continuous variable (CV) quantum key distribution (QKD...Networking with QUantum operationally-Secure Technology for Maritime Deployment (CONQUEST) Contract Period of Performance: 2 September 2016 – 1 September...this letter or have any other questions. Sincerely, Raytheon BBN Technologies Kathryn Carson Program Manager Quantum Information Processing
Nuclear polarization effects in big bang nucleosynthesis

NASA Astrophysics Data System (ADS)

Voronchev, Victor T.; Nakao, Yasuyuki

2015-10-01

A standard nuclear reaction network for big bang nucleosynthesis (BBN) simulations operates with spin-averaged nuclear inputs—unpolarized reaction cross sections. At the same time, the major part of reactions controlling the abundances of light elements is spin dependent, i.e., their cross sections depend on the mutual orientation of reacting particle spins. Primordial magnetic fields in the BBN epoch may to a certain degree polarize particles and thereby affect some reactions between them, introducing uncertainties in standard BBN predictions. To clarify the points, we have examined the effects of induced polarization on key BBN reactions—p (n ,γ )d , d (d ,p )t , d (d ,n )He 3 , t (d ,n )α , He 3 (n ,p )t , He 3 (d ,p )α , Li 7 (p ,α )α , Be 7 (n ,p )Li 7 —and the abundances of elements with A ≤7 . It has been obtained that the magnetic field with the strength B0≤1012 G (at the temperature of 109 K ) has almost no effect on the reaction cross sections, and the spin polarization mechanism plays a minor role in the element production, changing the abundances at most by 0.01%. However, if the magnetic field B0 reaches 1015 G its effect on the key reactions appears and becomes appreciable at B0≳1016 G . In particular, it has been found that such a field can increase the p (n ,γ )d cross section (relevant to the starting point of BBN) by a factor of 2 and at the same time almost block the He 3 (n ,p )t reaction responsible for the interconversion of A =3 nuclei in the early Universe. This suggests that the spin polarization effects may become important in nonstandard scenarios of BBN considering the existence of local magnetic bubbles inside which the field can reach ˜1015 G .
Use of Bayesian Belief Network techniques to explore the interaction of biosecurity practices on the probability of porcine disease occurrence in Canada.

PubMed

Cox, Ruth; Revie, Crawford W; Hurnik, Daniel; Sanchez, Javier

2016-09-01

Identification and quantification of pathogen threats need to be a priority for the Canadian swine industry so that resources can be focused where they will be most effective. Here we create a tool based on a Bayesian Belief Network (BBN) to model the interaction between biosecurity practices and the probability of occurrence of four different diseases on Canadian swine farms. The benefits of using this novel approach, in comparison to other methods, is that it enables us to explore both the complex interaction and the relative importance of biosecurity practices on the probability of disease occurrence. In order to build the BBN we used two datasets. The first dataset detailed biosecurity practices employed on 218 commercial swine farms across Canada in 2010. The second dataset detailed animal health status and disease occurrence on 90 of those farms between 2010 and 2012. We used expert judgement to identify 15 biosecurity practices that were considered the most important in mitigating disease occurrence on farms. These included: proximity to other livestock holdings, the health status of purchased stock, manure disposal methods, as well as the procedures for admitting vehicles and staff. Four diseases were included in the BBN: Porcine reproductive and respiratory syndrome (PRRS), (a prevalent endemic aerosol pathogen), Swine influenza (SI) (a viral respiratory aerosol pathogen), Mycoplasma pneumonia (MP) (an endemic respiratory disease spread by close contact and aerosol) and Swine dysentery (SD) (an enteric disease which is re-emerging in North America). This model indicated that the probability of disease occurrence was influenced by a number of manageable biosecurity practices. Increased probability of PRRS and of MP were associated with spilt feed (feed that did not fall directly in a feeding trough), not being disposed of immediately and with manure being brought onto the farm premises and spread on land adjacent to the pigs. Increased probabilities of SI and SD were associated with the farm allowing access to visiting vehicles without cleaning or disinfection. SD was also more likely to occur when the health status of purchased stock was not known. Finally, we discuss how such a model can be used by the Canadian swine industry to quantify disease risks and to determine practices that may reduce the probability of disease occurrence. Copyright © 2016 Elsevier B.V. All rights reserved.
A fast tumor-targeting near-infrared fluorescent probe based on bombesin analog for in vivo tumor imaging.

PubMed

Chen, Haiyan; Wan, Shunan; Zhu, Fenxia; Wang, Chuan; Cui, Sisi; Du, Changli; Ma, Yuxiang; Gu, Yueqing

2014-01-01

Bombesin (BBN), an analog of gastrin-releasing peptide (GRP), of which the receptors are over-expressed on various tumor cells, is able to bind to GRP receptor specifically. In this study, a near-infrared fluorescent dye (MPA) and polyethylene glycol (PEG) were conjugated to BBN analog to form BBN[7-14]-MPA and BBN[7-14]-SA-PEG-MPA. The successful synthesis of the two probes was proved by the characterization via sodium dodecylsulfate-polyacrylamide gel electrophoresis, infrared and optical spectra. Cellular uptakes studies indicated that BBN-based probes were mediated by gastrin-releasing peptide receptors (GRPR) on tumor cells and the PEG modified probe had higher affinity. The dynamic distribution and clearance investigations showed that the BBN-based probes were eliminated by the liver-kidney pathway. Furthermore, both of the BBN-based probes displayed tumor-targeting ability in GRPR over-expressed tumor-bearing mice. The PEG modified probe exhibited faster and higher tumor targeting capability than BBN[7-14]-MPA. The results implied that BBN[7-14]-SA-PEG-MPA could act as an effective fluorescence probe for tumor imaging. Copyright © 2014 John Wiley & Sons, Ltd.

Decision scenario analysis for addressing sediment accumulation in Lago Lucchetti, Puerto Rico

EPA Science Inventory

A Bayesian belief network (BBN) was used to characterize the effects of sediment accumulation on water storage capacity of a reservoir (Lago Lucchetti) in southwest Puerto Rico and the potential of different management options to increase reservoir life expectancy. Water and sedi...
Saudi mothers' preferences about breaking bad news concerning newborns: a structured verbal questionnaire

PubMed Central

2011-01-01

Background Breaking bad news (BBN) to parents whose newborn has a major disease is an ethical dilemma. In Saudi Arabia, BBN about newborns is performed according to the parental preferences that have been reported from non-Arabic/non-Islamic countries. Saudi mothers' preferences about BBN have not yet been studied. Therefore, we aimed to elicit the preferences of Saudi mothers about BBN concerning newborns. Methods We selected a convenience sample of 402 Saudi mothers, aged 18-50 years, who had no previous experience with BBN. We selected them via a simple number-randomization scheme from the premises of a level III Saudi hospital between October of 2009 and January of 2011. We used a hypothetical situation (BBN about trisomy 21) to elicit their preferences about BBN concerning newborns via a structured verbal questionnaire composed of 12 multiple-choice questions. We expressed their preferences as percentages (95% confidence interval), and we used the Kendall's W test (W) to assess the degree of agreement in preferences. Results The Saudi mothers preferred that BBN be conducted with both parents together (64% [60-69]), albeit with weak levels of agreement (W = 0.29). They showed moderate agreement in their preferences that BBN should be conducted early (79% [75-83], W = 0.48), in detail (81% [77-85], W = 0.52), in person (88% [85-91], W = 0.58), and in a quiet setting (86% [83-90], W = 0.53). With extremely weak agreement, they preferred to have a known person present for support during BBN (56% [51-61], W = 0.01), to have close bodily contact with their babies (66% [61-70], W = 0.10), and to have no another patients present (64% [59-68], W = 0.08). They showed moderate levels of agreement in their desires to detail, in advance, their preferences about process of BBN by giving a reversible, written informed consent that could be utilized for guidance, if needed (80% [76-84], W = 0.36). Conclusions In our experience, Saudi mothers' preferences about BBN concerning newborns are varied, suggesting that a "one-size-fits-all" approach is inappropriate. A reversible, written informed consent detailing their preferences about BBN that would be kept in their medical records and utilized for guidance, if needed, may be the best solution, given this level of diversity. These findings merit further study. PMID:21861876
Hydroacoustic Studies Using HydroCAM - Station-centric Integration of Models and Observations Quarterly Report No.4 July 2003 - September 2003

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

Upton, Zachary, M.; Pulli, Jay, J.

2003-10-13

OAK B272 Quarterly technical report summarizing BBN's efforts to improve DOE's hydroacoustic modeling and analysis capability for nuclear explosion monitoring. BBN's work during the third quarter of 2003 was focused on preparations for and participation in the 2003 Seismic Research Review Meeting, unit testing and bug fixes to HydroCAM 4.1, data collection and analysis, and procuring high-resolution bathymetric data. In an attempt to save money, BBN scaled back its labor in the third quarter, delaying some deliverables but saving contract funding in case our next increment is delayed. We have succeeded in finding the correct Naval contact that can helpmore » us procure high-resolution bathymetry data. Although these data may require the release of a classified version of HydroCAM, we are optimistic that we will be able to acquire and integrate high-resolution bathymetric data near the Indian Ocean IMS stations. HydroCAM 4.1, which includes the ability to make blockage predictions using varying resolution bathymetric data, has completed unit testing and is now under integration (release) testing. We hope to deliver that functionality to DOE and AFTAC in November. BBN improved its database of hydroacoustic events in the Indian Ocean by including meta-data for associated arrivals. For each earthquake event, BBN is now picking the direct arrival at each station (Diego Garcia North and South, and Cape Leeuwin) and associating that arrival with the origin information that we are compiling. The data for 2001, 2002 and 2003 (to date) will be delivered to LLNL for integration into the Knowledge Base during the fourth quarter of 2003.« less
A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites

NASA Astrophysics Data System (ADS)

Thomsen, Nanna I.; Binning, Philip J.; McKnight, Ursula S.; Tuxen, Nina; Bjerg, Poul L.; Troldborg, Mads

2016-05-01

A key component in risk assessment of contaminated sites is in the formulation of a conceptual site model (CSM). A CSM is a simplified representation of reality and forms the basis for the mathematical modeling of contaminant fate and transport at the site. The CSM should therefore identify the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert opinion at different knowledge levels. The developed BBNs combine data from desktop studies and initial site investigations with expert opinion to assess which of the CSMs are more likely to reflect the actual site conditions. The method is demonstrated on a Danish field site, contaminated with chlorinated ethenes. Four different CSMs are developed by combining two contaminant source zone interpretations (presence or absence of a separate phase contamination) and two geological interpretations (fractured or unfractured clay till). The beliefs in each of the CSMs are assessed sequentially based on data from three investigation stages (a screening investigation, a more detailed investigation, and an expert consultation) to demonstrate that the belief can be updated as more information becomes available.
New effects of a long-lived negatively charged massive particle on big bang nucleosynthesis

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

Kusakabe, Motohiko; Kim, K. S.; Cheoun, Myung-Ki

Primordial {sup 7}Li abundance inferred from observations of metal-poor stars is a factor of about 3 lower than the theoretical value of standard big bang nucleosynthesis (BBN) model. One of the solutions to the Li problem is {sup 7}Be destruction during the BBN epoch caused by a long-lived negatively charged massive particle, X{sup −}. The particle can bind to nuclei, and X-bound nuclei (X-nuclei) can experience new reactions. The radiative X{sup −} capture by {sup 7}Be nuclei followed by proton capture of the bound state of {sup 7}Be and X{sup −} ({sup 7}Be{sub x}) is a possible {sup 7}Be destructionmore » reaction. Since the primordial abundance of {sup 7}Li originates mainly from {sup 7}Li produced via the electron capture of {sup 7}Be after BBN, the {sup 7}Be destruction provides a solution to the {sup 7}Li problem. We suggest a new route of {sup 7}Be{sub x} formation, that is the {sup 7}Be charge exchange at the reaction of {sup 7}Be{sup 3+} ion and X{sup −}. The formation rate depends on the ionization fraction of {sup 7}Be{sup 3+} ion, the charge exchange cross section of {sup 7}Be{sup 3+}, and the probability that excited states {sup 7}Be{sub x}* produced at the charge exchange are converted to the ground state. We find that this reaction can be equally important as or more important than ordinary radiative recombination of {sup 7}Be and X{sup −}. The effect of this new route is shown in a nuclear reaction network calculation.« less
New reaction rates for improved primordial D /H calculation and the cosmic evolution of deuterium

NASA Astrophysics Data System (ADS)

Coc, Alain; Petitjean, Patrick; Uzan, Jean-Philippe; Vangioni, Elisabeth; Descouvemont, Pierre; Iliadis, Christian; Longland, Richard

2015-12-01

Primordial or big bang nucleosynthesis (BBN) is one of the three historically strong evidences for the big bang model. Standard BBN is now a parameter-free theory, since the baryonic density of the Universe has been deduced with an unprecedented precision from observations of the anisotropies of the cosmic microwave background radiation. There is a good agreement between the primordial abundances of 4He, D, 3He, and 7Li deduced from observations and from primordial nucleosynthesis calculations. However, the 7Li calculated abundance is significantly higher than the one deduced from spectroscopic observations and remains an open problem. In addition, recent deuterium observations have drastically reduced the uncertainty on D /H , to reach a value of 1.6%. It needs to be matched by BBN predictions whose precision is now limited by thermonuclear reaction rate uncertainties. This is especially important as many attempts to reconcile Li observations with models lead to an increased D prediction. Here, we reevaluate the d (p ,γ )3He, d (d ,n ) 3H3, and d (d ,p ) 3H reaction rates that govern deuterium destruction, incorporating new experimental data and carefully accounting for systematic uncertainties. Contrary to previous evaluations, we use theoretical ab initio models for the energy dependence of the S factors. As a result, these rates increase at BBN temperatures, leading to a reduced value of D /H =(2.45 ±0.10 )×10-5 (2 σ ), in agreement with observations.
Destructions of {sup 7}Be and {sup 7}Li in Big Bang nucleosynthesis through reactions with exotic long-lived sub-strongly interacting massive particles

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

Kusakabe, Motohiko; Kawasaki, Masahiro; Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan and Institute for the Physics and Mathematics of the Universe, University of Tokyo, Kashiwa, Chiba 277-8582

An observed plateau abundance of {sup 7}Li in metal-poor halo stars indicates its primordial origin. The {sup 7}Li abundances are about a factor of three smaller than that predicted in standard big bang nucleosynthesis (BBN) model. In addition, some of the stars possibly contain {sup 6}Li in abundances larger than standard BBN prediction. Particle models sometimes include heavy longlived colored particles which are confined in exotic strongly interacting massive particles (SIMPs). We have found reactions which destroy {sup 7}Be and {sup 7}Li during BBN in the scenario of BBN affected by a long-lived sub-strongly interactingmassive particle (sub-SIMP, X). The reactionsmore » are non radiative X captures of {sup 7}Be and {sup 7}Li which can operate if the X particle interacts with nuclei strongly enough to drive {sup 7}Be destruction but not strongly enough to form a bound state with {sup 4}He of relative angular momentum L = 1. The processes can be a cause of the {sup 7}Li problem. In this paper we suggest new possible reactions for {sup 6}Li production. Especially, a {sup 6}Li production through the deuteron capture of {sup 4}He bound to X can operate in the parameter region solving the {sup 7}Li problem.« less
Doctors' stress responses and poor communication performance in simulated bad-news consultations.

PubMed

Brown, Rhonda; Dunn, Stewart; Byrnes, Karen; Morris, Richard; Heinrich, Paul; Shaw, Joanne

2009-11-01

No studies have previously evaluated factors associated with high stress levels and poor communication performance in breaking bad news (BBN) consultations. This study determined factors that were most strongly related to doctors' stress responses and poor communication performance during a simulated BBN task. In 2007, the authors recruited 24 doctors comprising 12 novices (i.e., interns/residents with 1-3 years' experience) and 12 experts (i.e., registrars, medical/radiation oncologists, or cancer surgeons, with more than 4 years' experience). Doctors participated in simulated BBN consultations and a number of control tasks. Five-minute-epoch heart rate (HR), HR variability, and communication performance were assessed in all participants. Subjects also completed a short questionnaire asking about their prior experience BBN, perceived stress, psychological distress (i.e., anxiety, depression), fatigue, and burnout. High stress responses were related to inexperience with BBN, fatigue, and giving bad versus good news. Poor communication performance in the consultation was related to high burnout and fatigue scores. These results suggest that BBN was a stressful experience for doctors even in a simulated encounter, especially for those who were inexperienced and/or fatigued. Poor communication performance was related to burnout and fatigue, but not inexperience with BBN. These results likely indicate that burnout and fatigue contributed to stress and poor work performance in some doctors during the simulated BBN task.
Imaging Primary Prostate Cancer and Bone Metastasis

DTIC Science & Technology

2007-04-01

of GRPR-posi- tive tumors. Since the native BBN peptide has a pyroglutamic acid at the N-terminus and an amidated methionine at the C-termi- nus...Lys3]bombesin ([Lys3]BBN) and aminocaproic acid - bombesin(7–14) (Aca-BBN(7–14)) with 18F for GRPR imaging of subcutaneous and orthotopic PC-3 tumor...xenografted mice. Methods: [Lys3]bombesin ([Lys3]BBN) was conjugated with 1,4,7,10-tetraazadodecane-N,N,N,N-tet- raacetic acid (DOTA) and labeled with
Breaking bad news in clinical setting - health professionals' experience and perceived competence in Southwestern Nigeria: a cross sectional study.

PubMed

Adebayo, Philip Babatunde; Abayomi, Olukayode; Johnson, Peter O; Oloyede, Taofeeq; Oyelekan, Abimbola A A

2013-01-01

Communication skills are vital in clinical settings because the manner in which bad news is delivered could be a huge determinant of responses to such news; as well as compliance with beneficial treatment option. Information on training, institutional guidelines and protocols for breaking bad news (BBN) is scarce in Nigeria. We assessed the training, experience and perceived competence of BBN among medical personnel in southwestern Nigeria. The study was a cross-sectional descriptive study conducted out among doctors and nurses in two healthcare institutions in southwestern Nigeria using an anonymous questionnaire (adapted from the survey by Horwitz et al.), which focused on the respondents training, awareness of protocols in BBN; and perceived competence (using a Five-Point Likert Scale) in five clinical scenarios. We equally asked the respondents about an instance of BBN they have recently witnessed. A total of 113 of 130 selected (response rate 86.9%) respondents were studied. Eight (7.1%) of the respondents knew of the guidelines on BBN in the hospital in which they work. Twenty-three (20.3%) respondents claimed knowledge of a protocol. The median perceived competence rating was 4 out of 5 in all the clinical scenarios. Twenty-five (22.1%) respondents have had a formal training in BBN and they generally had significant higher perceived competence rating (P = 0.003-0.021). There is poor support from fellow workers during instances of BBN. It appears that the large proportion of the respondents in this study were unconsciously incompetent in BBN in view of the low level of training and little or no knowledge of well known protocols for BBN even though self-rated competence is high. Continuous medical education in communication skills among health personnel in Nigeria is advocated.
Coastal vulnerability assessment using Fuzzy Logic and Bayesian Belief Network approaches

NASA Astrophysics Data System (ADS)

Valentini, Emiliana; Nguyen Xuan, Alessandra; Filipponi, Federico; Taramelli, Andrea

2017-04-01

Natural hazards such as sea surge are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assessment, management and planning can contribute to enhance the resilience of coastal systems. In this frame assessing current and future vulnerability is a key concern of many Systems Of Systems SOS (social, ecological, institutional) that deals with several challenges like the definition of Essential Variables (EVs) able to synthesize the required information, the assignment of different weight to be attributed to each considered variable, the selection of method for combining the relevant variables. It is widely recognized that ecosystems contribute to human wellbeing and then their conservation increases the resilience capacities and could play a key role in reducing climate related risk and thus physical and economic losses. A way to fully exploit ecosystems potential, i.e. their so called ecopotential (see H2020 EU funded project "ECOPOTENTIAL"), is the Ecosystem based Adaptation (EbA): the use of ecosystem services as part of an adaptation strategy. In order to provide insight in understanding regulating ecosystem services to surge and which variables influence them and to make the best use of available data and information (EO products, in situ data and modelling), we propose a multi-component surge vulnerability assessment, focusing on coastal sandy dunes as natural barriers. The aim is to combine together eco-geomorphological and socio-economic variables with the hazard component on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian Belief Networks (BBN). The Fuzzy Logic approach is very useful to get a spatialized information and it can easily combine variables coming from different sources. It provides information on vulnerability moving along-shore and across-shore (beach-dune transect), highlighting the variability of vulnerability conditions in the spatial dimension. According to the results using fuzzy operators, the analysis greatest weakness is the limited capacity to represent the relation among the different considered variables. The BBN approach, based on the definition of conditional probabilities, has allowed determining the trend of distributions of vulnerability along-shore, highlighting which parts of the coast are most likely to have higher or lower vulnerability than others. In BBN analysis, the greatest weakness emerge in the case of arbitrary definition of conditional probabilities (i.e. when there is a lack of information on the past hazardous events) because it is not possible to derive the individual contribution of each variable. As conclusion, the two approaches could be used together in the perspective of enhancing the multiple components in vulnerability assessment: the BBN as a preliminary assessment to provide a coarse description of the vulnerability distribution, and the Fuzzy Logic as an extended assessment to provide more space based information.
Observation of interstellar lithium in the low-metallicity Small Magellanic Cloud.

PubMed

Howk, J Christopher; Lehner, Nicolas; Fields, Brian D; Mathews, Grant J

2012-09-06

The primordial abundances of light elements produced in the standard theory of Big Bang nucleosynthesis (BBN) depend only on the cosmic ratio of baryons to photons, a quantity inferred from observations of the microwave background. The predicted primordial (7)Li abundance is four times that measured in the atmospheres of Galactic halo stars. This discrepancy could be caused by modification of surface lithium abundances during the stars' lifetimes or by physics beyond the Standard Model that affects early nucleosynthesis. The lithium abundance of low-metallicity gas provides an alternative constraint on the primordial abundance and cosmic evolution of lithium that is not susceptible to the in situ modifications that may affect stellar atmospheres. Here we report observations of interstellar (7)Li in the low-metallicity gas of the Small Magellanic Cloud, a nearby galaxy with a quarter the Sun's metallicity. The present-day (7)Li abundance of the Small Magellanic Cloud is nearly equal to the BBN predictions, severely constraining the amount of possible subsequent enrichment of the gas by stellar and cosmic-ray nucleosynthesis. Our measurements can be reconciled with standard BBN with an extremely fine-tuned depletion of stellar Li with metallicity. They are also consistent with non-standard BBN.
Using Bayesian Belief Networks to Explore the Effects of Nitrogen Inputs on Wetland Ecosystem Services

NASA Astrophysics Data System (ADS)

Spence, P. L.; Jordan, S. J.

2011-12-01

Increased reactive nitrogen (Nr) inputs to freshwater wetlands resulting from infrastructure development due to population growth along with intensive agricultural practices associated with food production can threaten regulating (i.e. climate change, water purification, and waste treatment) and supporting (i.e. nutrient cycling) ecosystem services. Wetlands generally respond both by sequestering Nr (i.e. soil accumulation and biomass assimilation) and converting Nr into inert gaseous forms via biogeochemical processes. It is important for wetlands to be efficient in removing excessive Nr inputs from polluted waters to reduce eutrophication in downstream receiving water bodies while producing negligible amounts of nitrous oxide (N2O), a potent greenhouse gas, which results from incomplete denitrification. Wetlands receiving excessive Nr lose their ability to provide a constant balance between regulating water quality and mitigating climate change. The purpose of this study is to explore the effects of Nr inputs on ecosystem services provided by wetlands using a Bayesian Belief Network (BBN). The network was developed from established relationships between a variety of wetland function indicators and biogeochemical process associated with Nr removal. Empirical data for 34 freshwater wetlands were gathered from a comprehensive review of published peer-reviewed and gray literature. The BBN was trained using 30 wetlands (88% of the freshwater wetland case file) and tested using 4 wetlands (12% of the freshwater wetland case file). Sensitivity analysis suggested that Nr removal, water quality, soil Nr accumulation and N2O emissions had the greatest influence on ecosystem service tradeoffs. The magnitude of Nr inputs did not affect ecosystem services. The network implies that Nr removal efficiency has a greater influence on final ecosystem services associated with water quality impairment and atmospheric pollution. A very low error rate, which was based on 4 wetland cases, indicated that a larger dataset is required to provide robust predictions. These findings are considered preliminary and could change as the model is updated.
Bombesin functionalized gold nanoparticles show in vitro and in vivo cancer receptor specificity.

PubMed

Chanda, Nripen; Kattumuri, Vijaya; Shukla, Ravi; Zambre, Ajit; Katti, Kavita; Upendran, Anandhi; Kulkarni, Rajesh R; Kan, Para; Fent, Genevieve M; Casteel, Stan W; Smith, C Jeffrey; Boote, Evan; Robertson, J David; Cutler, Cathy; Lever, John R; Katti, Kattesh V; Kannan, Raghuraman

2010-05-11

Development of cancer receptor-specific gold nanoparticles will allow efficient targeting/optimum retention of engineered gold nanoparticles within tumors and thus provide synergistic advantages in oncology as it relates to molecular imaging and therapy. Bombesin (BBN) peptides have demonstrated high affinity toward gastrin-releasing peptide (GRP) receptors in vivo that are overexpressed in prostate, breast, and small-cell lung carcinoma. We have synthesized a library of GRP receptor-avid nanoplatforms by conjugating gold nanoparticles (AuNPs) with BBN peptides. Cellular interactions and binding affinities (IC(50)) of AuNP-BBN conjugates toward GRP receptors on human prostate cancer cells have been investigated in detail. In vivo studies using AuNP-BBN and its radiolabeled surrogate (198)AuNP-BBN, exhibiting high binding affinity (IC(50) in microgram ranges), provide unequivocal evidence that AuNP-BBN constructs are GRP-receptor-specific showing accumulation with high selectivity in GRP-receptor-rich pancreatic acne in normal mice and also in tumors in prostate-tumor-bearing, severe combined immunodeficient mice. The i.p. mode of delivery has been found to be efficient as AuNP-BBN conjugates showed reduced RES organ uptake with concomitant increase in uptake at tumor targets. The selective uptake of this new generation of GRP-receptor-specific AuNP-BBN peptide analogs has demonstrated realistic clinical potential in molecular imaging via x-ray computed tomography techniques as the contrast numbers in prostate tumor sites are severalfold higher as compared to the pretreatment group (Hounsfield unit = 150).
Effects of the f(R) and f(G) Gravities and the Exotic Particle on Primordial Nucleosynthesis

NASA Astrophysics Data System (ADS)

Kusakabe, Motohiko; Koh, Seoktae; Kim, K. S.; Cheoun, Myung-Ki; Kajino, Toshitaka; Mathews, Grant J.

A plateau Li/H abundance of metal-poor stars is smaller than those predicted in the standard big bang nucleosynthesis (BBN) model by a factor of ˜3, for the baryon density determined from Planck. This discrepancy may be caused by a non-standard cosmic thermal history or reactions of a hypothetical particle. We consider the BBN in specific modified gravity models characterized by f(R) and f(G) terms in the gravitational actions. These models have cosmic expansion rates different from that in the standard model, and abundances of all light elements are affected. The modified gravities are constrained mainly from observational deuterium abundances. No solution is found for the Li problem because a significant modification of the expansion rate results in a large change of D abundance. This result is quite a contrast to that of a BBN model including a long-lived negatively charged massive particle X-. The 7Be nuclide is destroyed via the recombination with an X- followed by the radiative proton capture. The X- particle selectively decreases the abundance of 7Be, and the primordial abundance of 7Li originating from the electron capture of 7Be is reduced. We have an important theoretical lesson: Some physical process must have operated preferentially on 7Be nuclei.
Constraining axion dark matter with Big Bang Nucleosynthesis

DOE PAGES

Blum, Kfir; D'Agnolo, Raffaele Tito; Lisanti, Mariangela; ...

2014-08-04

We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN
Constraining axion dark matter with Big Bang Nucleosynthesis

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

Blum, Kfir; D'Agnolo, Raffaele Tito; Lisanti, Mariangela

We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN
Effectiveness of Integrating Simulation with Art-Based Teaching Strategies on Oncology Fellows' Performance Regarding Breaking Bad News.

PubMed

Yakhforoshha, Afsaneh; Emami, Seyed Amir Hossein; Shahi, Farhad; Shahsavari, Saeed; Cheraghi, Mohammadali; Mojtahedzadeh, Rita; Mahmoodi-Bakhtiari, Behrooz; Shirazi, Mandana

2018-02-21

The task of breaking bad news (BBN) may be improved by incorporating simulation with art-based teaching methods. The aim of the present study was to assess the effect of an integrating simulation with art-based teaching strategies, on fellows' performance regarding BBN, in Iran. The study was carried out using quasi-experimental methods, interrupted time series. The participants were selected from medical oncology fellows at two teaching hospitals of Tehran University of Medical Sciences (TUMS), Iran. Participants were trained through workshop, followed by engaging participants with different types of art-based teaching methods. In order to assess the effectiveness of the integrating model, fellows' performance was rated by two independent raters (standardized patients (SPs) and faculty members) using the BBN assessment checklist. This assessment tool measured seven different domains of BBN skill. Segmented regression was used to analyze the results of study. Performance of all oncology fellows (n = 19) was assessed for 228 time points during the study, by rating three time points before and three time points after the intervention by two raters. Based on SP ratings, fellows' performance scores in post-training showed significant level changes in three domains of BBN checklist (B = 1.126, F = 3.221, G = 2.241; p < 0.05). Similarly, the significant level change in fellows' score rated by faculty members in post-training was B = 1.091, F = 3.273, G = 1.724; p < 0.05. There was no significant change in trend of fellows' performance after the intervention. Our results showed that using an integrating simulation with art-based teaching strategies may help oncology fellows to improve their communication skills in different facets of BBN performance. Iranian Registry of Clinical Trials ID: IRCT2016011626039N1.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Paul-Yann; Lin, Yung-Lun; Huang, Chin-Chin

Epidemiological studies have revealed that exposure to an arsenic-contaminated environment correlates with the incidence of bladder cancer. Bladder cancer is highly recurrent after intravesical therapy, and most of the deaths from this disease are due to invasive metastasis. In our present study, the role of inorganic arsenic in bladder carcinogenesis is characterized in a mouse model. This work provides the first evidence that inorganic arsenic in drinking water promotes N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN)-induced bladder tissue damage, including the urothelium and submucosal layer. This damage to the bladder epithelium induced by BBN includes thickening of the submucosal layer, the loss of the glycosaminoglycanmore » layer and an increase in both the deoxyguanosine oxidation and cytosine methylation levels in the DNA. Further, when 10 ppm inorganic arsenic is combined with BBN, the number of bladder submucosal capillaries is increased. In addition, inorganic arsenic also increases the deoxyguanosine oxidation level, alters the cytosine methylation state, decreases the activities of glutathione reductase and glucose-6-phosphate dehydrogenase, decreases the protein expression of NAD(P)H quinone oxidoreductase-1 (NQO-1) and increases the protein expression of specific protein 1 (Sp1) in bladder tissues. In summary, our data reveal that inorganic arsenic in drinking water promotes the BBN-induced pre-neoplastic damage of bladder tissue in mice, and that the 8-hydroxy-2′-deoxyguanosine, 5-methylcytosine, NQO-1 protein and Sp1 protein levels may be pre-neoplastic markers of bladder tumors. -- Highlights: ► The role of inorganic arsenic in bladder carcinogenesis is characterized in mice. ► We examine the changes in the histology and biochemistry of bladder tissues. ► Inorganic arsenic enhances BBN-induced DNA oxidation while decreases BBN-induced DNA methylation in the mouse bladder. ► Inorganic arsenic alters the activities of the anti-oxidant enzymes in the mouse bladder. ► Inorganic arsenic increases Sp1 while decreases NQO-1 protein expression in the mouse whole bladder.« less
Bombesin Encapsulated in Long-Circulating pH-Sensitive Liposomes as a Radiotracer for Breast Tumor Identification.

PubMed

De Barros, André Luís Branco; Mota, Luciene Das Graças; Coelho, Marina Melo Antunes; Corrêa, Natássia Caroline Resende; De Góes, Alfredo Miranda; Oliveira, Mônica Cristina; Cardoso, Valbert Nascimento

2015-02-01

Bombesin (BBN) is a tetradecapeptide that binds specifically to gastrin-releasing peptide receptors in humans. These receptors are over-expressed in several forms of cancer; radiolabeled BBN could therefore be used to detect such cancers. However, the degradation of peptides is a critical issue in the development of tumor tracers. Liposomes can be used to overcome this problem and improve the uptake of tracers by tumors. Therefore, the purpose of this study was to prepare and characterize long-circulating and pH-sensitive liposomes (SpHL) containing 99mTc-HYNIC-βAla-Bombesin(7-14) (99mTc-BBN(7-14). In addition, the ability of this system to identify human breast cancer tissue was evaluated using biodistribution studies and scintigraphic images. Long-circulating and pH-sensitive liposomes (SpHL) were prepared and freeze-dried in the presence of cryoprotectants (glucose, mannitol, and trehalose). They were subsequently reconstituted with a solution of 99mTc-HYNIC-βAla-Bombesin(7-14) (99mTc-BBN(7-14)). The liposomes were evaluated for size, encapsulation percentage, radiotracer leakage, and storage stability. In addition, in vivo studies were performed in breast tumor-bearing nude mice. Liposomes in the presence of glucose (SpHLG), exhibited a mean diameter of 164.5 ± 6.5 nm and exhibited a 99mTc-BBN(7-14) encapsulation percentage of 30%. In addition, they remained highly stable for up to 120 days of storage. SpHLG- 99mTc-BBN(7-14) showed longer blood circulation than free 99mTc-BBN(7-14), did. The tumor-to-muscle and tumor-to-blood ratios for SpHLG-99mTc-BBN(7-14 were high at 4 h post-injection (9.31%ID/g and 7.93%ID/g, respectively). Furthermore, scintigraphic images revealed a strong signal in the tumor area, indicating tumor specificity of SpHLG-99mTc-BBN(7-14). In summary, SpHLG-99mTc-BBN(7-14) presented characteristics suitable for a diagnostic agent, and is a potential tool for tumor identification.

Primordial alchemy: from the Big Bang to the present universe

NASA Astrophysics Data System (ADS)

Steigman, Gary

Of the light nuclides observed in the universe today, D, 3He, 4He, and 7Li are relics from its early evolution. The primordial abundances of these relics, produced via Big Bang Nucleosynthesis (BBN) during the first half hour of the evolution of the universe provide a unique window on Physics and Cosmology at redshifts ~1010. Comparing the BBN-predicted abundances with those inferred from observational data tests the consistency of the standard cosmological model over ten orders of magnitude in redshift, constrains the baryon and other particle content of the universe, and probes both Physics and Cosmology beyond the current standard models. These lectures are intended to introduce students, both of theory and observation, to those aspects of the evolution of the universe relevant to the production and evolution of the light nuclides from the Big Bang to the present. The current observational data is reviewed and compared with the BBN predictions and the implications for cosmology (e.g., universal baryon density) and particle physics (e.g., relativistic energy density) are discussed. While this comparison reveals the stunning success of the standard model(s), there are currently some challenge which leave open the door for more theoretical and observational work with potential implications for astronomy, cosmology, and particle physics.
A human GRPr-transfected Ace-1 canine prostate cancer model in mice.

PubMed

Ding, Haiming; Kothandaraman, Shankaran; Gong, Li; Williams, Michelle M; Dirksen, Wessel P; Rosol, Thomas J; Tweedle, Michael F

2016-06-01

A versatile drug screening system was developed to simplify early targeted drug discovery in mice and then translate readily from mice to a dog prostate cancer model that more fully replicates the features of human prostate cancer. We stably transfected human cDNA of the GRPr bombesin (BBN) receptor subtype to canine Ace-1 prostate cancer cells (Ace-1(huGRPr) ). Expression was examined by (125) I-Tyr(4) -BBN competition, calcium stimulation assay, and fluorescent microscopy. A dual tumor nude mouse xenograft model was developed from Ace-1(CMV) (vector transfected Ace-1) and Ace-1(huGRPr) cells. The model was used to explore the in vivo behavior of two new IRDye800-labeled GRPr binding optical imaging agents: 800-G-Abz4-t-BBN, from a GRPr agonist peptide, and 800-G-Abz4-STAT, from a GRPr antagonist peptide, by imaging the tumor mice and dissected organs. Both agents bound Ace-1(huGRPr) and PC-3, a known GRPr-expressing human prostate cancer cell line, with 4-13 nM IC50 against (125) I-Tyr(4) -BBN, but did not bind Ace-1(CMV) cells (vector transfected). Binding was blocked by bombesin. Ca(2+) activation assays demonstrated that Ace-1(huGPRr) expressed biologically active GRPr. Both Ace-1 cell lines grew in the flanks of 100% of the nude mice and formed tumors of ∼0.5 cm diameter in 1 week. In vivo imaging of the mice at 800 nm emission showed GRPr+: GRPr- tumor signal brighter by a factor of two at 24 h post IV administration of 10 nmol of the imaging agents. Blood retention (4-8% ID at 1 h) was greater by a factor >10 and cumulative urine accumulation (28-30% at 4 h) was less by a factor 2 compared to a radioactive analog of the t-BBN containing agent, (177) LuAMBA, probably due to binding to blood albumin, which we confirmed in a mouse serum assay. The dual tumor Ace-1(CMV) /Ace-1(huGRPr) model system provides a rapid test of specific to nonspecific binding of new GRPr avid agents in a model that will extend logically to the known Ace-1 orthotopic canine prostate cancer model. Prostate 76:783-795, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Big bang nucleosynthesis: An update

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

Olive, Keith A.

An update on the standard model of big bang nucleosynthesis (BBN) is presented. With the value of the baryon-tophoton ratio determined to high precision by WMAP, standard BBN is a parameter-free theory. In this context, the theoretical prediction for the abundances of D, {sup 4}He, and {sup 7}Li is discussed and compared to their observational determination. While concordance for D and {sup 4}He is satisfactory, the prediction for {sup 7}Li exceeds the observational determination by a factor of about four. Possible solutions to this problem are discussed.
Breaking Bad News to Patients with Cancer: A Randomized Control Trial of a Brief Communication Skills Training Module Incorporating the Stories and Preferences of Actual Patients

PubMed Central

Gorniewicz, James; Floyd, Michael; Krishnan, Koyamangalath; Bishop, Thomas W.; Tudiver, Fred; Lang, Forrest

2017-01-01

Objective This study tested the effectiveness of a brief, learner-centered, breaking bad news (BBN) communication skills training module using objective evaluation measures. Methods This randomized control study (N=66) compared intervention and control groups of students (n=28) and residents' (n=38) objective structured clinical examination (OSCE) performance of communication skills using Common Ground Assessment and Breaking Bad News measures. Results Follow-up performance scores of intervention group students improved significantly regarding BBN (colon cancer (CC), p=.007, r=-.47; breast cancer (BC), p=.003, r=-.53), attention to patient responses after BBN (CC, p < .001, r=-.74; BC, p=.001, r=-.65), and addressing feelings (BC, p=.006, r=-.48). At CC follow-up assessment, performance scores of intervention group residents improved significantly regarding BBN (p=.004, r=-.43), communication related to emotions (p=.034, r=-.30), determining patient's readiness to proceed after BBN and communication preferences (p=.041, r=-.28), active listening (p=011, r=-.37), addressing feelings (p<.001, r=-.65), and global interview performance (p=.001, r=-.51). Conclusion This brief BBN training module is an effective method of improving BBN communication skills among medical students and residents. Practice Implications Implementation of this brief individualized training module within health education programs could lead to improved communication skills and patient care. PMID:27876220
Tumor control by hypoxia-specific chemotargeting of iron-oxide nanoparticle - Berberine complexes in a mouse model.

PubMed

Sreeja, S; Krishnan Nair, C K

2018-02-15

To evaluate the therapeutic efficacy of hypoxic cell-sensitizer Sanazole (SAN) -directed targeting of cytotoxic drug Berberine (BBN) and Iron-oxide nanoparticle (NP) complexes, to solid tumor in Swiss albino mice. NP-BBN-SAN complexes were characterized by FTIR, XRD, TEM and Nano-size analyzer. This complex was orally administered to mice-bearing solid tumor in hind limb. Tumor regression was analysed by measuring tumor volume. Cellular DNA damages were assessed by comet assay. Transcriptional expression of genes related to tumor hypoxia and apoptosis was evaluated by quantitative real-time PCR and morphological changes in tissues were analysed by histopathology. Also levels of antioxidants and tumor markers in tissues and serum biochemical parameters were analysed. Administration of NP-BBN-SAN complexes reduced tumor volume and studies were focussed on the underlying mechanisms. Extensive damage to cellular-DNA; down-regulated transcription of hif-1α, vegf, akt and bcl2; and up-regulated expression of bax and caspases, were observed in tumor. Results on tumor markers, antioxidant-status and serum parameters corroborated the molecular findings. Histopathology of tumor, liver and kidney revealed the therapeutic specificity of NP-BBN-SAN. Thus SAN and NP can be used for specific targeting of drugs, to hypoxic solid tumor, to improve therapeutic efficacy. Copyright © 2017. Published by Elsevier Inc.
Detection of lithium in the cool halo dwarfs Groombridge 1830 and HD 134439: Implications for internal stellar mixing and cosmology

NASA Technical Reports Server (NTRS)

Deliyannis, Constantine P.; Ryan, Sean G.; Beers, Timothy C.; Thorburn, Julie A.

1994-01-01

Lithium abundances in halo stars, when interpreted correctly, hold the key to uncovering the primordial Li abundance Li(sub p). However, whereas standard stellar evolutionary models imply consistency in standard big bang nucleosynthesis (BBN), models with rotationally induced mixing imply a higher Li(sub p), possibly implying an inconsistency in standard BBN. We report here Li detections in two cool halo dwarfs, Gmb 1830 and HD 134439. These are the coolest and lowest Li detections in halo dwarfs to date, and are consistent with the metallicity dependence of Li depletion in published models. If the recent report of a beryllium deficiency in Gmb 1830 represents a real Be depletion, then the rotational models would be favored. We propose tests to reduce critical uncertainties.
Novel 64Cu Labeled RGD2-BBN Heterotrimers for PET Imaging of Prostate Cancer.

PubMed

Lucente, Ermelinda; Liu, Hongguang; Liu, Yang; Hu, Xiang; Lacivita, Enza; Leopoldo, Marcello; Cheng, Zhen

2018-05-16

Bombesin receptor 2 (BB 2 ) and integrin α v β 3 receptor are privileged targets for molecular imaging of cancer because of their overexpression in a number of tumor tissues. The most recent developments in heterodimer-based radiopharmaceuticals concern BB 2 - and integrin α v β 3 -targeting compounds, consisting of bombesin (BBN) and cyclic arginine-glycine-aspartic acid peptides (RGD), connected through short length linkers. Molecular imaging probes based on RGD-BBN heterodimer design exhibit improved tumor targeting efficacy compared to the single-receptor targeting peptide monomers. However, their application in clinical study is restricted because of inefficient synthesis or unfavorable in vivo properties, which could depend on the short linker nature. Thus, the aim of the present study was to develop a RGD 2 -BBN heterotrimer, composed of (7-14)BBN-NH 2 peptide (BBN) linked to the E[ c(RGDyK)] 2 dimer peptide (RGD 2 ), bearing the new linker type [Pro-Gly] 12 . The heterodimer E[c(RGDyK)] 2 -PEG 3 -Glu-(Pro-Gly) 12 -BBN(7-14)-NH 2 (RGD 2 -PG 12 -BBN) was prepared through conventional solid phase synthesis, then conjugated with 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) or 1,4,7-triazacyclononane-1-glutaric acid-4,7-diacetic acid (NODA-GA). In 64 Cu labeling, the NODA-GA chelator showed superior radiochemical characteristics compared to DOTA (70% vs 40% yield, respectively). Both conjugates displayed dual targeting ability, showing good α v β 3 affinities and high BB 2 receptor affinities which, in the case of the NODA-GA conjugate, were in the same range as the best RGD-BBN heterodimer ligands reported to date ( K i = 24 nM). 64 Cu-DOTA and 64 Cu-NODA-GA probes were also found to be stable after 1 h incubation in mouse serum (>90%). In a microPET study in prostate cancer PC-3 xenograft mice, both probes showed low tumor uptake, probably due to poor pharmacokinetic properties in vivo. Overall, our study demonstrates that novel RGD-BBN heterodimer with long linker can be prepared and they preserve high binding affinities to BB 2 and integrin α v β 3 receptor binding ability. The present study represents a step forward in the design of effective heterodimer or heterotrimer probes for dual targeting.
Constraint on slepton intergenerational mixing from big-bang nucleosynthesis

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

Kohri, Kazunori; Ohta, Shingo; Sato, Joe

We find constraint on intergenerational mixing of slepton from big-bang nucleosynthesis (BBN). Today, we know that there exist lepton flavor violation (LFV) from the observation of neutrino oscillation, though there do not exist LFV in the standard model of particle physics (SM). LFV in charged lepton sector (cLFV) have also been expected to exist. From theoretical point of view, the effects of long-lived stau on BBN have been investigated and it is known that the stau can solve the cosmological 7Li problem. However, in the study so far, tau flavor is exactly conserved and it contradict with the existence ofmore » cLFV. In this study, we generalize the flavor to be violated and call the stau as slepton. Even if the violation is tiny, it drastically changes the lifetime and the evolution of relic density of the slepton. Thus we analyze the effects of the long-lived slepton on BBN, and constrain the magnitude of the cLFV.« less
Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks.

PubMed

Bashari, Hossein; Naghipour, Ali Asghar; Khajeddin, Seyed Jamaleddin; Sangoony, Hamed; Tahmasebi, Pejman

2016-09-01

Identifying areas that have a high risk of burning is a main component of fire management planning. Although the available tools can predict the fire risks, these are poor in accommodating uncertainties in their predictions. In this study, we accommodated uncertainty in wildfire prediction using Bayesian belief networks (BBNs). An influence diagram was developed to identify the factors influencing wildfire in arid and semi-arid areas of Iran, and it was populated with probabilities to produce a BBNs model. The behavior of the model was tested using scenario and sensitivity analysis. Land cover/use, mean annual rainfall, mean annual temperature, elevation, and livestock density were recognized as the main variables determining wildfire occurrence. The produced model had good accuracy as its ROC area under the curve was 0.986. The model could be applied in both predictive and diagnostic analysis for answering "what if" and "how" questions. The probabilistic relationships within the model can be updated over time using observation and monitoring data. The wildfire BBN model may be updated as new knowledge emerges; hence, it can be used to support the process of adaptive management.
Experimental challenge to the big-bang nucleosynthesis - Cosmological 7Li problem in BBN

NASA Astrophysics Data System (ADS)

Kubono, S.; Kawabata, T.; Hou, S. Q.; He, J. J.

2018-04-01

The primordial nucleosynthesis(BBN) right after the big bang (BB) is one of the key elements that basically support the BB model. The BBN is well known that it produced primarily light elements, and explains reasonably most of the elemental abundances. However, there remains an interesting and serious question. That is so called the cosmological 7Li problem in BBN. The BBN simulations using nuclear data together with the recent detailed micro-wave background measurements explain most of the light elements including D, 4He, etc, but the 7Li abundance is over predicted roughly by a factor of three. Although this problem should be investigated in all the fields relevant including physics and astronomical observations, I will concentrate my discussion on the nuclear physics side, especially the recent progress for studying the last possible major destruction process of 7Be, the 7Be(n,α)4He reaction, which would reduce the overproduction if the cross section is large. There are several efforts recently made for the 7Be(n,α)4He reaction in the world. A new theoretical estimate was made compiling all available data of the mirror reaction 7Li(p,α)4He, suggesting about one order smaller reaction rate than the ones currently being used (Wagoner rate). The n-TOF group measured some part of the s-wave components of the reaction, suggesting that the s-wave contributions are much smaller than the Wagoner rate. The p-wave component was measured clearly at RCNP, Osaka using the time-reverse reaction 4He(α,n)7Be, indicating that the p-wave contribution dominates at the effective temperature region for the BBN. However, the sum of the s-wave and p-wave contributions is about one order of magnitude smaller than the Wagoner rate. It should be of great interest to confirm by the indirect method, Trojan-Horse method to deduce cross sections at the effective temperature region, and also see the cross sections for a wider energy range systematically, which is under way by the BELICOS project by Livio Lamia and by the CRIB collaboration lead by S. Hayakawa.
Underground Study of Big Bang Nucleosynthesis in the Precision Era of Cosmology

NASA Astrophysics Data System (ADS)

Gustavino, Carlo

2017-03-01

Big Bang Nucleosinthesis (BBN) theory provides definite predictions for the abundance of light elements produced in the early universe, as far as the knowledge of the relevant nuclear processes of the BBN chain is accurate. At BBN energies (30 ≲ Ecm ≲ 300 MeV) the cross section of many BBN processes is very low because of the Coulomb repulsion between the interacting nuclei. For this reason it is convenient to perform the measurements deep underground. Presently the world's only facility operating underground is LUNA (Laboratory for Undergound Nuclear astrophysics) at LNGS ("Laboratorio Nazionale del Gran Sasso", Italy). In this presentation the BBN measurements of LUNA are briefly reviewed and discussed. It will be shown that the ongoing study of the D(p, γ)3He reaction is of primary importance to derive the baryon density of universe Ωb with high accuracy. Moreover, this study allows to constrain the existence of the so called "dark radiation", composed by undiscovered relativistic species permeating the universe, such as sterile neutrinos.
Managing the delivery of bad news: an in-depth analysis of doctors' delivery style.

PubMed

Shaw, Joanne; Dunn, Stewart; Heinrich, Paul

2012-05-01

The purpose of this study was to identify and describe the delivery styles doctors typically use when breaking bad news (BBN). Thirty one doctors were recruited to participate in two standardised BBN consultations involving a sudden death. Delivery styles were determined using time to deliver the bad news as a standardised differentiation as well as qualitative analysis of interaction content and language style. Communication performance was also assessed. Analysis of BBN interactions revealed three typical delivery styles. A blunt style characterised by doctors delivering news within the first 30 s of the interaction; Forecasting, a staged delivery of the news within the first 2 min and a stalling approach, delaying news delivery for more than 2 min. This latter avoidant style relies on the news recipient reaching a conclusion about event outcome without the doctor explicitly conveying the news. Three typical bad news delivery styles used by doctors when BBN were confirmed both semantically and operationally in the study. The relationship between delivery style and the overall quality of BBN interactions was also investigated. This research provides a new template for approaching BBN training and provides evidence for a need for greater flexibility when communicating bad news. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Breaking bad news to patients with cancer: A randomized control trial of a brief communication skills training module incorporating the stories and preferences of actual patients.

PubMed

Gorniewicz, James; Floyd, Michael; Krishnan, Koyamangalath; Bishop, Thomas W; Tudiver, Fred; Lang, Forrest

2017-04-01

This study tested the effectiveness of a brief, learner-centered, breaking bad news (BBN) communication skills training module using objective evaluation measures. This randomized control study (N=66) compared intervention and control groups of students (n=28) and residents' (n=38) objective structured clinical examination (OSCE) performance of communication skills using Common Ground Assessment and Breaking Bad News measures. Follow-up performance scores of intervention group students improved significantly regarding BBN (colon cancer (CC), p=0.007, r=-0.47; breast cancer (BC), p=0.003, r=-0.53), attention to patient responses after BBN (CC, p<0.001, r=-0.74; BC, p=0.001, r=-0.65), and addressing feelings (BC, p=0.006, r=-0.48). At CC follow-up assessment, performance scores of intervention group residents improved significantly regarding BBN (p=0.004, r=-0.43), communication related to emotions (p=0.034, r=-0.30), determining patient's readiness to proceed after BBN and communication preferences (p=0.041, r=-0.28), active listening (p=0.011, r=-0.37), addressing feelings (p<0.001, r=-0.65), and global interview performance (p=0.001, r=-0.51). This brief BBN training module is an effective method of improving BBN communication skills among medical students and residents. Implementation of this brief individualized training module within health education programs could lead to improved communication skills and patient care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Interface Message Processors for the ARPA Computer Network

DTIC Science & Technology

1975-04-01

Pluribus IMP construction and checkout; sizeable changes to the i*4P message-processing algorithms: and Satellite IMP issues. The IMP message...extremely low cost modification design. We have begun to consider changes to the MLC design which would enable the MLC to suppress continuous breaks...existing authentication mechanisms need not make these changes . 2.7 Other Topics During the first quarter BBN constructed an environmental test chamber
The BBN (Bolt Beranek and Newman) Knowledge Acquisition Project. Phase 1. Functional Description; Test Plan.

DTIC Science & Technology

1987-05-01

Computers . " Symbolics. Inc. 8. Carnegie Group. Inc KnoiledgeCraft Carnegie Group, Inc.. 1985. .- 9. Moser, Margaret, An Overviev of NIKL. Section of BBN...ORGANIZATION NAME AND ADDRESS I0. PROGRAM ELEMENT. PROJECT. TASK BBN Laboratories Inc. AREAAWoRIUNTNUMER_ 10 Moulton St. Cambridge, MA 02238 It...knowledge representation, expert systems; strategic computing , . A 20 ABSTRACT (Contnue an r rerse ide If neceaesary and Identify by block number) This
Initial construct validity evidence of a virtual human application for competency assessment in breaking bad news to a cancer patient.

PubMed

Guetterman, Timothy C; Kron, Frederick W; Campbell, Toby C; Scerbo, Mark W; Zelenski, Amy B; Cleary, James F; Fetters, Michael D

2017-01-01

Despite interest in using virtual humans (VHs) for assessing health care communication, evidence of validity is limited. We evaluated the validity of a VH application, MPathic-VR, for assessing performance-based competence in breaking bad news (BBN) to a VH patient. We used a two-group quasi-experimental design, with residents participating in a 3-hour seminar on BBN. Group A (n=15) completed the VH simulation before and after the seminar, and Group B (n=12) completed the VH simulation only after the BBN seminar to avoid the possibility that testing alone affected performance. Pre- and postseminar differences for Group A were analyzed with a paired t -test, and comparisons between Groups A and B were analyzed with an independent t -test. Compared to the preseminar result, Group A's postseminar scores improved significantly, indicating that the VH program was sensitive to differences in assessing performance-based competence in BBN. Postseminar scores of Group A and Group B were not significantly different, indicating that both groups performed similarly on the VH program. Improved pre-post scores demonstrate acquisition of skills in BBN to a VH patient. Pretest sensitization did not appear to influence posttest assessment. These results provide initial construct validity evidence that the VH program is effective for assessing BBN performance-based communication competence.
Initial construct validity evidence of a virtual human application for competency assessment in breaking bad news to a cancer patient

PubMed Central

Guetterman, Timothy C; Kron, Frederick W; Campbell, Toby C; Scerbo, Mark W; Zelenski, Amy B; Cleary, James F; Fetters, Michael D

2017-01-01

Background Despite interest in using virtual humans (VHs) for assessing health care communication, evidence of validity is limited. We evaluated the validity of a VH application, MPathic-VR, for assessing performance-based competence in breaking bad news (BBN) to a VH patient. Methods We used a two-group quasi-experimental design, with residents participating in a 3-hour seminar on BBN. Group A (n=15) completed the VH simulation before and after the seminar, and Group B (n=12) completed the VH simulation only after the BBN seminar to avoid the possibility that testing alone affected performance. Pre- and postseminar differences for Group A were analyzed with a paired t-test, and comparisons between Groups A and B were analyzed with an independent t-test. Results Compared to the preseminar result, Group A’s postseminar scores improved significantly, indicating that the VH program was sensitive to differences in assessing performance-based competence in BBN. Postseminar scores of Group A and Group B were not significantly different, indicating that both groups performed similarly on the VH program. Conclusion Improved pre–post scores demonstrate acquisition of skills in BBN to a VH patient. Pretest sensitization did not appear to influence posttest assessment. These results provide initial construct validity evidence that the VH program is effective for assessing BBN performance-based communication competence. PMID:28794664
Development of Urinary Bladder Pre-Neoplasia by Schistosoma haematobium Eggs and Chemical Carcinogen in Mice

PubMed Central

Chala, Bayissa; Choi, Min-Ho; Moon, Kyung Chul; Kim, Hyung Suk; Kwak, Cheol; Hong, Sung-Tae

2017-01-01

Schistosoma haematobium is a biocarcinogen of human urinary bladder (UB). The present study investigated developing UB cancer mouse model by injecting S. haematobium eggs into the bladder wall and introduction of chemical carcinogens. Histopathological findings showed mild hyperplasia to epithelial vacuolar change, and high grade dysplasia. Squamous metaplasia was observed in the S. haematobium eggs+NDMA group at week 12 but not in other groups. Immunohistochemistry revealed significantly high expression of Ki-67 in urothelial epithelial cells of the S. haematobium eggs+BBN group at week 20. The qRT-PCR showed high expression of p53 gene in S. haematobium eggs group at week 4 and S. haematobium eggs+BBN group at week 20. E-cadherin and vimentin showed contrasting expression in S. haematobium eggs+BBN group. Such inverse expression of E-cadherin and vimentin may indicate epithelial mesenchymal transition in the UB tissue. In conclusion, S. haematobium eggs and nitrosamines may transform UB cells into squamous metaplasia and dysplasia in correlation with increased expression of Ki-67. Marked decrease in E-cadherin and increase in p53 and vimentin expressions may support the transformation. The present study introduces a promising modified animal model for UB cancer study using S. haematobium eggs. PMID:28285503
Configuration development for ROMENET

NASA Astrophysics Data System (ADS)

Rhue, Lawrence

1989-10-01

A plan prepared by RJO Enterprises and BBN Communications Corporation (BBNCC) for the design of ROMENET, a DDN-like testbed for the Rome Air Development Center (RADC) Wide Area Networks (WAN) laboratory is presented. The ROMENET is intended to provide RADC with the ability to test and evaluate the performance and vulnerability of the Defense Data Network (DDN) technologies in support of specific Major Command programs and activities at RADC. It will also support experimentation with packet switched network technologies and includes facilities to analytically evaluate the performance of the network and its associated equipment and media. In addition, ROMENET will provide a simulation vehicle for controlled interference or jamming into the media for vulnerability assessment. Through interfaces with the RADC Battle Management Laboratory (BML), ROMENET will allow the Air Force to assess the restorative and performance characteristics of the network under stressed conditions. The closed environment of ROMENET makes it ideal for creating and testing routing algorithms and network control protocols.
Problems and Mitigation Strategies for Developing and Validating Statistical Cyber Defenses

DTIC Science & Technology

2014-04-01

Clustering Support Vector Machine (SVM) Classification Netflow Twitter Training Datasets Trained SVMs Enriched Feature State...requests. • Netflow data for TCP connections • E-mail data from SMTP logs • Chat data from XMPP logs • Microtext data (from Twitter message archives...summary data from Bro and Netflow data captured on the BBN network over the period of 1 month, plus simulated attacks WHOIS Domain name record

Web Intervention for Adolescents Affected by Disaster: Population-Based Randomized Controlled Trial

PubMed Central

Ruggiero, Kenneth J.; Price, Matthew; Adams, Zachary; Stauffacher, Kirstin; McCauley, Jenna; Danielson, Carla Kmett; Knapp, Rebecca; Hanson, Rochelle F.; Davidson, Tatiana M.; Amstadter, Ananda B.; Carpenter, Matthew J.; Saunders, Benjamin E.; Kilpatrick, Dean G.; Resnick, Heidi S.

2015-01-01

Objective To assess the efficacy of Bounce Back Now (BBN), a modular, web-based intervention for disaster-affected adolescents and their parents. Method A population-based randomized controlled trial used address-based sampling to enroll 2,000 adolescents and parents from communities affected by tornadoes in Joplin, MO, and Alabama. Data collection via baseline and follow-up semi-structured telephone interviews was completed between September 2011 and August 2013. All families were invited to access the BBN study web portal irrespective of mental health status at baseline. Families who accessed the web portal were assigned randomly to 3 groups: (1) BBN, which featured modules for adolescents and parents targeting adolescents’ mental health symptoms; (2) BBN plus additional modules targeting parents’ mental health symptoms; or (3) assessment only. The primary outcomes were adolescent symptoms of posttraumatic stress disorder (PTSD) and depression. Results Nearly 50% of families accessed the web portal. Intent-to-treat analyses revealed time × condition interactions for PTSD symptoms (B=−0.24, SE=0.08, p<.01) and depressive symptoms (B=−0.23, SE=0.09, p<.01). Post-hoc comparisons revealed fewer PTSD and depressive symptoms for adolescents in the experimental vs. control conditions at 12-month follow-up (PTSD: B=−0.36, SE=0.19, p=.06; depressive symptoms: B=−0.42, SE=0.19, p=0.03). A time × condition interaction also was found favoring the BBN vs. BBN + parent self-help condition for PTSD symptoms (B=0.30, SE=0.12, p=.02), but not depressive symptoms (B=0.12, SE=0.12, p=.33). Conclusion Results supported the feasibility and initial efficacy of BBN as a scalable disaster mental health intervention for adolescents. Technology-based solutions have tremendous potential value if found to reduce the mental health burden of disasters. PMID:26299292
Web Intervention for Adolescents Affected by Disaster: Population-Based Randomized Controlled Trial.

PubMed

Ruggiero, Kenneth J; Price, Matthew; Adams, Zachary; Stauffacher, Kirstin; McCauley, Jenna; Danielson, Carla Kmett; Knapp, Rebecca; Hanson, Rochelle F; Davidson, Tatiana M; Amstadter, Ananda B; Carpenter, Matthew J; Saunders, Benjamin E; Kilpatrick, Dean G; Resnick, Heidi S

2015-09-01

To assess the efficacy of Bounce Back Now (BBN), a modular, Web-based intervention for disaster-affected adolescents and their parents. A population-based randomized controlled trial used address-based sampling to enroll 2,000 adolescents and parents from communities affected by tornadoes in Joplin, MO, and several areas in Alabama. Data collection via baseline and follow-up semi-structured telephone interviews was completed between September 2011 and August 2013. All families were invited to access the BBN study Web portal irrespective of mental health status at baseline. Families who accessed the Web portal were assigned randomly to 1 of 3 groups: BBN, which featured modules for adolescents and parents targeting adolescents' mental health symptoms; BBN plus additional modules targeting parents' mental health symptoms; or assessment only. The primary outcomes were adolescent symptoms of posttraumatic stress disorder (PTSD) and depression. Nearly 50% of families accessed the Web portal. Intent-to-treat analyses revealed time × condition interactions for PTSD symptoms (B = -0.24, SE = 0.08, p < .01) and depressive symptoms (B = -0.23, SE = 0.09, p < .01). Post hoc comparisons revealed fewer PTSD and depressive symptoms for adolescents in the experimental versus control conditions at 12-month follow-up (PTSD: B = -0.36, SE = 0.19, p = .06; depressive symptoms: B = -0.42, SE = 0.19, p = 0.03). A time × condition interaction also was found that favored the BBN versus BBN + parent self-help condition for PTSD symptoms (B = 0.30, SE = 0.12, p = .02) but not depressive symptoms (B = 0.12, SE = 0.12, p = .33). Results supported the feasibility and initial efficacy of BBN as a scalable disaster mental health intervention for adolescents. Technology-based solutions have tremendous potential value if found to reduce the mental health burden of disasters. Web-based Intervention for Disaster-Affected Youth and Families; http://clinicaltrials.gov; NCT01606514. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. All rights reserved.
Regular Topologies for Gigabit Wide-Area Networks: Congestion Avoidance Testbed Experiments. Volume 3

NASA Technical Reports Server (NTRS)

Denny, Barbara A.; McKenney, Paul E., Sr.; Lee, Danny

1994-01-01

This document is Volume 3 of the final technical report on the work performed by SRI International (SRI) on SRI Project 8600. The document includes source listings for all software developed by SRI under this effort. Since some of our work involved the use of ST-II and the Sun Microsystems, Inc. (Sun) High-Speed Serial Interface (HSI/S) driver, we have included some of the source developed by LBL and BBN as well. In most cases, our decision to include source developed by other contractors depended on whether it was necessary to modify the original code. If we have modified the software in any way, it is included in this document. In the case of the Traffic Generator (TG), however, we have included all the ST-II software, even though BBN performed the integration, because the ST-II software is part of the standard TG release. It is important to note that all the code developed by other contractors is in the public domain, so that all software developed under this effort can be re-created from the source included here.
BBN for the LHC: Constraints on lifetimes of the Higgs portal scalars

NASA Astrophysics Data System (ADS)

Fradette, Anthony; Pospelov, Maxim

2017-10-01

LHC experiments can provide a remarkable sensitivity to exotic metastable massive particles, decaying with significant displacement from the interaction point. The best sensitivity is achieved with models where the production and decay occur due to different coupling constants, and the lifetime of exotic particles determines the probability of decay within a detector. The lifetimes of such particles can be independently limited from standard cosmology, in particular, the big bang nucleosynthesis (BBN). In this paper, we analyze the constraints on the simplest scalar model coupled through the Higgs portal, where the production occurs via h →S S , and the decay is induced by the small mixing angle of the Higgs field h and scalar S . We find that throughout most of the parameter space, 2 mμ
[Karyometry of BBN-induced precancerosis of the urothelium : An experimental analysis].

PubMed

Dahm, H H; Lehnen-Holtum, V; Rübben, H

2016-10-01

The morphology of experimental precancerous lesions of the urinary bladder has been interpreted quite differently by various authors. The aim of this investigation was to quantify these lesions by karyometry and, thus, to gain a more reliable understanding of the process. A total of 60 Wistar rats were fed with N‑butyl-N-(4-hydroxybutyl)nitrosamine (BBN) at a concentration of 0.05 % in their drinking water to induce preneoplastic changes of the urothelium. After the second week of BBN exposition, 6 animals were killed every 2 weeks up to week 20. Smears of the scraped off urothelium of 3 urinary bladders of each group were analyzed cytologically and karyometrically. BBN exposition led to statistically significant changes of the karyometric values using the χ 2 test to differentiate the control animals from the ones that had ingested BBN and the 2‑week groups from each other. These changes consisted mainly in significant deviations of the size of the nuclear area within the different groups. Morphological and karyometrical analysis showed that biologically relevant stages in the development of chemically induced urothelial precancerous lesions could be realized much earlier than had been assumed in recent publications. Karyometric analysis offered a valid basis to describe the early morphologic alterations of carcinogenesis.
Breaking Bad News in obstetrics: a randomized trial of simulation followed by debriefing or lecture.

PubMed

Karkowsky, Chavi Eve; Landsberger, Ellen J; Bernstein, Peter S; Dayal, Ashlesha; Goffman, Dena; Madden, Robert C; Chazotte, Cynthia

2016-11-01

Although communication skills represent an increasingly important aspect of medical care, little has been done to assess the best method of teaching these skills. Our study was designed to assess simulation-debriefing compared to lecture in teaching skills for Breaking Bad News (BBN) in obstetrics. This is a randomized prospective trial of house staff from a large academic medical center. Subjects initially underwent baseline simulation, followed by evaluation on BBN skills by themselves, a faculty observer, and the standardized patient (SP). The subjects were then immediately randomized to a debriefing session by faculty or to a lecture about BBN. Subsequently, both groups underwent a second simulation with the same three assessments, yielding post-intervention data. 35 subjects completed both simulations. Both debriefing and lecture curricula showed improvement in scores by self (p = 0.010) and faculty (p < 0.001). The debriefing group improved significantly more than the lecture group for self-evaluation; additionally, improvements were greater for the debrief group in verbal and nonverbal skills. Long-term follow-up three months after both interventions demonstrated continued improvement in BBN. Simulation training with debriefing is effective for teaching communication skills, and superior to lecture for self-perceived improvement. Long-term follow-up suggested retention of confidence in BBN skills.
Revisiting cosmological bounds on sterile neutrinos

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

Vincent, Aaron C.; Martínez, Enrique Fernández; Hernández, Pilar

2015-04-01

We employ state-of-the art cosmological observables including supernova surveys and BAO information to provide constraints on the mass and mixing angle of a non-resonantly produced sterile neutrino species, showing that cosmology can effectively rule out sterile neutrinos which decay between BBN and the present day. The decoupling of an additional heavy neutrino species can modify the time dependence of the Universe's expansion between BBN and recombination and, in extreme cases, lead to an additional matter-dominated period; while this could naively lead to a younger Universe with a larger Hubble parameter, it could later be compensated by the extra radiation expectedmore » in the form of neutrinos from sterile decay. However, recombination-era observables including the Cosmic Microwave Background (CMB), the shift parameter R{sub CMB} and the sound horizon r{sub s} from Baryon Acoustic Oscillations (BAO) severely constrain this scenario. We self-consistently include the full time-evolution of the coupled sterile neutrino and standard model sectors in an MCMC, showing that if decay occurs after BBN, the sterile neutrino is essentially bounded by the constraint sin{sup 2}θ ∼< 0.026 (m{sub s}/eV){sup −2}.« less
REVISED BIG BANG NUCLEOSYNTHESIS WITH LONG-LIVED, NEGATIVELY CHARGED MASSIVE PARTICLES: UPDATED RECOMBINATION RATES, PRIMORDIAL {sup 9}Be NUCLEOSYNTHESIS, AND IMPACT OF NEW {sup 6}Li LIMITS

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

Kusakabe, Motohiko; Kim, K. S.; Cheoun, Myung-Ki

We extensively reanalyze the effects of a long-lived, negatively charged massive particle, X {sup –}, on big bang nucleosynthesis (BBN). The BBN model with an X {sup –} particle was originally motivated by the discrepancy between the {sup 6,} {sup 7}Li abundances predicted in the standard BBN model and those inferred from observations of metal-poor stars. In this model, {sup 7}Be is destroyed via the recombination with an X {sup –} particle followed by radiative proton capture. We calculate precise rates for the radiative recombinations of {sup 7}Be, {sup 7}Li, {sup 9}Be, and {sup 4}He with X {sup –}. Inmore » nonresonant rates, we take into account respective partial waves of scattering states and respective bound states. The finite sizes of nuclear charge distributions cause deviations in wave functions from those of point-charge nuclei. For a heavy X {sup –} mass, m{sub X} ≳ 100 GeV, the d-wave → 2P transition is most important for {sup 7}Li and {sup 7,} {sup 9}Be, unlike recombination with electrons. Our new nonresonant rate of the {sup 7}Be recombination for m{sub X} = 1000 GeV is more than six times larger than the existing rate. Moreover, we suggest a new important reaction for {sup 9}Be production: the recombination of {sup 7}Li and X {sup –} followed by deuteron capture. We derive binding energies of X nuclei along with reaction rates and Q values. We then calculate BBN and find that the amount of {sup 7}Be destruction depends significantly on the charge distribution of {sup 7}Be. Finally, updated constraints on the initial abundance and the lifetime of the X {sup –} are derived in the context of revised upper limits to the primordial {sup 6}Li abundance. Parameter regions for the solution to the {sup 7}Li problem and the primordial {sup 9}Be abundances are revised.« less
DARPA DTN Phase 3 Core Engineering Support

NASA Technical Reports Server (NTRS)

Torgerson, J. Leigh; Richard Borgen, Richard; McKelvey, James; Segui, John; Tsao, Phil

2010-01-01

This report covers the initial DARPA DTN Phase 3 activities as JPL provided Core Engineering Support to the DARPA DTN Program, and then further details the culmination of the Phase 3 Program with a systematic development, integration and test of a disruption-tolerant C2 Situation Awareness (SA) system that may be transitioned to the USMC and deployed in the near future. The system developed and tested was a SPAWAR/JPL-Developed Common Operating Picture Fusion Tool called the Software Interoperability Environment (SIE), running over Disruption Tolerant Networking (DTN) protocols provided by BBN and MITRE, which effectively extends the operational range of SIE from normal fully-connected internet environments to the mobile tactical edges of the battlefield network.
Effects of sterile neutrino and extra-dimension on big bang nucleosynthesis

NASA Astrophysics Data System (ADS)

Jang, Dukjae; Kusakabe, Motohiko; Cheoun, Myung-Ki

2018-04-01

We study effects of the sterile neutrino in the five-dimensional universe on the big bang nucleosynthesis (BBN). Since the five-dimensional universe model leads to an additional term in the Friedmann equation and the energy density of the sterile neutrino increases the total energy density, this model can affect the primordial abundance via changing the cosmic expansion rate. The energy density of the sterile neutrino can be determined by a rate equation for production of the sterile neutrino. We show that not only the mixing angle and the mass of the sterile neutrino, but also a resonant effect in the oscillation between sterile and active neutrinos is important to determine a relic abundance of the sterile neutrino. In this study, we also investigate how the sterile neutrino in extra-dimensional model can affect the BBN, and constrain the parameters related to the above properties of the sterile neutrino by using the observational primordial abundances of light elements.
Downregulation of glutathione S-transferase M1 protein in N-butyl-N-(4-hydroxybutyl)nitrosamine-induced mouse bladder carcinogenesis

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

Chuang, Jing-Jing; Dai, Yuan-Chang; Lin, Yung-Lun

2014-09-15

Bladder cancer is highly recurrent following specific transurethral resection and intravesical chemotherapy, which has prompted continuing efforts to develop novel therapeutic agents and early-stage diagnostic tools. Specific changes in protein expression can provide a diagnostic marker. In our present study, we investigated changes in protein expression during urothelial carcinogenesis. The carcinogen BBN was used to induce mouse bladder tumor formation. Mouse bladder mucosa proteins were collected and analyzed by 2D electrophoresis from 6 to 20 weeks after commencing continuous BBN treatment. By histological examination, the connective layer of the submucosa showed gradual thickening and the number of submucosal capillaries graduallymore » increased after BBN treatment. At 12-weeks after the start of BBN treatment, the urothelia became moderately dysplastic and tumors arose after 20-weeks of treatment. These induced bladder lesions included carcinoma in situ and connective tissue invasive cancer. In protein 2D analysis, the sequentially downregulated proteins from 6 to 20 weeks included GSTM1, L-lactate dehydrogenase B chain, keratin 8, keratin 18 and major urinary proteins 2 and 11/8. In contrast, the sequentially upregulated proteins identified were GSTO1, keratin 15 and myosin light polypeptide 6. Western blotting confirmed that GSTM1 and NQO-1 were decreased, while GSTO1 and Sp1 were increased, after BBN treatment. In human bladder cancer cells, 5-aza-2′-deoxycytidine increased the GSTM1 mRNA and protein expression. These data suggest that the downregulation of GSTM1 in the urothelia is a biomarker of bladder carcinogenesis and that this may be mediated by DNA CpG methylation. - Highlights: • GSTM1 and NQO-1 proteins decreased in the mouse bladder mucosa after BBN treatment. • BBN induced GSTO1 and Sp1 protein expression in the mouse bladder mucosa. • 5-Aza-2′-deoxycytidine increased GSTM1 mRNA and protein in human bladder cancer cell. • GSTM1 downregulation in the urothelia may be a biomarker of bladder carcinogenesis.« less
Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society

DTIC Science & Technology

2002-01-01

6 Walter Schneider (University of Pittsburgh) A Cognitive Approach to Designing Human Error...Experiment Design and Comparison of Human and Model Data: David Diller and Yvette Tenney (BBN Technologies) An EPIC-Soar Model of Concurrent...the Roles of Design History and Affordances in the HIPE Theory of Function
Measurements of the neutron-induced reactions on 7Be with CRIB by the Trojan Horse method

NASA Astrophysics Data System (ADS)

Hayakawa, S.; Abe, K.; Beliuskina, O.; Cha, S. M.; Chae, K. Y.; Cherubini, S.; Figuera, P.; Ge, Z.; Gulino, M.; Hu, J.; Inoue, A.; Iwasa, N.; Kahl, D.; Kim, A.; Kim, D. H.; Kiss, G.; Kubono, S.; La Cognata, M.; La Commara, M.; Lamia, L.; Lattuada, M.; Lee, E. J.; Moon, J. Y.; Palmerini, S.; Parascandolo, C.; Park, S. Y.; Pierroutsakou, D.; Pizzone, R. G.; Rapisarda, G. G.; Romano, S.; Shimizu, H.; Spitaleri, C.; Tang, X. D.; Trippella, O.; Tumino, A.; , P., Vi; Yamaguchi, H.; Yang, L.; Zhang, N. T.

2018-04-01

The cosmological 7Li problem has been one of the big issues left in the standard Big-Bang nucleosynthesis (BBN) model. In order to determine the radiogenic 7Li abundance by the BBN, it is important to know the production and the destruction rate of 7Be rather than 7Li itself. We performed indirect measurements of the relevant neutron-induced reactions 7Be(n, p)7Li and 7Be(n, α)4He simultaneously by the Trojan Horse Method (THM) via the three-body reactions 7Be(d,7Lip)1H and 7Be(d, αα)1H. A 7Be radioactive-isotope (RI) beam at 3.16 MeV/u was produced at Center-for-Nuclear-Study RI Beam (CRIB) separator. The Q-value spectra shows the evidence of the three-body channels of interest. We confirmed that the THM was applicable to the present measurements by the momentum distributions of the spectator proton. Preliminary excitation functions are roughly consistent with the previous studies, moreover providing new data in the BBN energy range, and suggesting that new information about the 7Be(n, p1)7Li* contribution may be obtained by carrying out a further data analysis.
Non-extensive Statistics to the Cosmological Lithium Problem

NASA Astrophysics Data System (ADS)

Hou, S. Q.; He, J. J.; Parikh, A.; Kahl, D.; Bertulani, C. A.; Kajino, T.; Mathews, G. J.; Zhao, G.

2017-01-01

Big Bang nucleosynthesis (BBN) theory predicts the abundances of the light elements D, 3He, 4He, and 7Li produced in the early universe. The primordial abundances of D and 4He inferred from observational data are in good agreement with predictions, however, BBN theory overestimates the primordial 7Li abundance by about a factor of three. This is the so-called “cosmological lithium problem.” Solutions to this problem using conventional astrophysics and nuclear physics have not been successful over the past few decades, probably indicating the presence of new physics during the era of BBN. We have investigated the impact on BBN predictions of adopting a generalized distribution to describe the velocities of nucleons in the framework of Tsallis non-extensive statistics. This generalized velocity distribution is characterized by a parameter q, and reduces to the usually assumed Maxwell-Boltzmann distribution for q = 1. We find excellent agreement between predicted and observed primordial abundances of D, 4He, and 7Li for 1.069 ≤ q ≤ 1.082, suggesting a possible new solution to the cosmological lithium problem.
Individual training at the undergraduate level to promote competence in breaking bad news in oncology.

PubMed

Berney, Alexandre; Carrard, Valérie; Schmid Mast, Marianne; Bonvin, Raphael; Stiefel, Friedrich; Bourquin, Céline

2017-12-01

Training medical students in breaking bad news (BBN) in oncology may be key to improve patient care in an area where many physicians tend to be uncomfortable. Given the lack of evidence in the literature, this study aimed to assess empirically the impact of 2 teaching strategies to prepare students for the task of BBN in oncology: one-to-one simulated patient (SP) training with individual feedback (intervention group) vs small-group SP training with collective feedback (comparison group). Fourth-year students (N = 236) were randomly assigned to the intervention or comparison group. The SP videotaped interviews were analyzed with respect to BBN communication performance, rated using the Calgary-Cambridge checklist of teaching objectives for BBN; verbal interaction behaviors, coded with the Roter interaction analysis system; and 7 nonverbal behaviors. Students in the intervention group scored significantly higher after than before the training on the overall evaluation of the interview (P < .001) as well as on process skills (P < .001); they also obtained significantly higher scores compared to students in the comparison group on the overall evaluation of the interview (P < .001) and on process skills (P < .001). This study supports an individualized BBN teaching strategy and contributes to efforts to find the best way to train and reach the largest number of future physicians to improve communication competences in oncology. Copyright © 2017 John Wiley & Sons, Ltd.
In vivo evaluation and small-animal PET/CT of a prostate cancer mouse model using 64Cu bombesin analogs: side-by-side comparison of the CB-TE2A and DOTA chelation systems.

PubMed

Garrison, Jered C; Rold, Tammy L; Sieckman, Gary L; Figueroa, Said Daibes; Volkert, Wynn A; Jurisson, Silvia S; Hoffman, Timothy J

2007-08-01

The BB2 receptor subtype, of the bombesin family of receptors, has been shown to be highly overexpressed in a variety of human tumors, including prostate cancer. Bombesin (BBN), a 14-amino acid peptide, has been shown to target the BB2 receptor with high affinity. 64Cu (half-life = 12.7 h, beta+: 18%, E(beta+ max) = 653 keV; beta-: 37%, E(beta- max) = 578 keV) is a radioisotope that has clinical potential for application in both diagnostic imaging and radionuclide therapy. Recently, new chelation systems such as 1,4,8,11-tetraazabicyclo[6.6.2]hexadecane-4,11-diacetic acid (CB-TE2A) have been reported to significantly stabilize the 64Cu radiometal in vivo. The increased stability of the 64Cu-CB-TE2A chelate complex has been shown to significantly reduce nontarget retention compared with tetraazamacrocycles such as 1,4,7,10-tetraazacyclodoadecane-N,N',N'',N'''-tetraacetic acid (DOTA). The aim of this study was to determine whether the CB-TE2A chelation system could significantly improve the in vivo stability of 64Cu bombesin analogs. The study directly compares 64Cu bombesin analogs using the CB-TE2A and DOTA chelation systems in a prostate cancer xenograft SCID (severely compromised immunodeficient) mouse model. The CB-TE2A-8-AOC-BBN(7-14)NH2 and DOTA-8-AOC-BBN(7-14)NH2 conjugates were synthesized and radiolabeled with 64Cu. The receptor-binding affinity and internalization profile of each metallated conjugate was evaluated using PC-3 cells. Pharmacokinetic and small-animal PET/CT studies were performed using female SCID mice bearing PC-3 xenografts. In vivo BB2 receptor targeting was confirmed by tumor uptake values of 6.95 +/- 2.27 and 4.95 +/- 0.91 %ID/g (percentage injected dose per gram) at the 15-min time point for the 64Cu-CB-TE2A and 64Cu-DOTA radioconjugates, respectively. At the 24-h time point, liver uptake was substantially reduced for the 64Cu-CB-TE2A radioconjugate (0.21 +/- 0.06 %ID/g) compared with the 64Cu-DOTA radioconjugate (7.80 +/- 1.51 %ID/g). The 64Cu-CB-TE2A-8-AOC-BBN(7-14)NH2 radioconjugate demonstrated significant clearance, 98.60 +/- 0.28 %ID, from the mouse at 24 h after injection. In contrast, only 67.84 +/- 5.43 %ID of the 64Cu activity was excreted using the 64Cu-DOTA-8-AOC-BBN(7-14)NH2 radioconjugate because of nontarget retention. The pharmacokinetic and small-animal PET/CT studies demonstrate significantly improved nontarget tissue clearance for the 64Cu-CB-TE2A8-AOC-BBN(7-14)NH2. This is attributed to the improved in vivo stability of the 64Cu-CB-TE2A chelate complex as compared with the 64Cu-DOTA chelate complex.
Monooxorhenium(V) complexes with 222-N2S2 MAMA ligands for bifunctional chelator agents: Syntheses and preliminary in vivo evaluation

PubMed Central

Demoin, Dustin Wayne; Dame, Ashley N.; Minard, William D.; Gallazzi, Fabio; Seickman, Gary L.; Rold, Tammy L.; Bernskoetter, Nicole; Fassbender, Michael E.; Hoffman, Timothy J.; Deakyne, Carol A.; Jurisson, Silvia S.

2016-01-01

Introduction Targeted radiotherapy using the bifunctional chelate approach with 186/188Re(V) is challenging because of the susceptibility of monooxorhenium(V)-based complexes to oxidize in vivo at high dilution. A monoamine-monoamide dithiol (MAMA)-based bifunctional chelating agent was evaluated with both rhenium and technetium to determine its utility for in vivo applications. Methods A 222-MAMA chelator, 222-MAMA(N-6-Ahx-OEt) bifunctional chelator, and 222- MAMA(N-6-Ahx-BBN(7-14)NH2) were synthesized, complexed with rhenium, radiolabeled with 99mTc and 186Re (carrier added and no carrier added), and evaluated in initial biological distribution studies. Results An IC50 value of 2.0 ± 0.7 nM for natReO-222-MAMA(N-6-Ahx-BBN(7-14)NH2) compared to [125I]-Tyr4-BBN(NH2) was determined through competitive cell binding assays with PC-3 tumor cells. In vivo evaluation of the no-carrier added 99mTc-222-N2S2(N-6-Ahx-BBN(7-14)NH2) complex showed little gastric uptake and blockable pancreatic uptake in normal mice. Conclusions The 186ReO-222-N2S2(N-6-Ahx-BBN(7-14)NH2) complex showed stability in biological media, which indicates that the 222-N2S2 chelator is appropriate for chelating 186/188Re in radiopharmaceuticals involving peptides. Additionally, the in vitro cell studies showed that the ReO-222-N2S2(N-6-Ahx-BBN(7-14)NH2) complex (macroscopically) bound to PC3-tumor cell surface receptors with high affinity. The 99mTc analog was stable in vivo and exhibited pancreatic uptake in mice that was blockable, indicating BB2r targeting. PMID:27694058
Anticancer benefits of early versus late use of rapamycin in a rat model of urothelial carcinoma.

PubMed

Chang, C-H; Fu, Y-C; Li, J-R; Shu, K-H; Ho, H-C; Shiu, Y-N; Wu, M-J

2014-05-01

We previously reported both in vivo and in vitro effects of rapamycin on urothelial carcinoma. Clinically, the use of rapamycin could not completely prevent the recurrence of urothelial carcinoma. Therefore, we designed this study to compare the difference of efficacy between early and late use of rapamycin in a rat model of urothelial carcinoma. The rat model of urothelial carcinoma was induced by adding 0.05% N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) to the drinking water for up to 20 weeks in male Fisher-344 rats. Rapamycin was fed orally from the 1st day, 5th week, 9th week, 13th week, and 17th week. The antitumor effects of different periods of rapamycin treatment were assessed grossly and microscopically. Papillary tumors of urinary bladder were successfully induced in the BBN group. Simultaneous use of rapamycin and BBN from the 1st day of treatment significantly reduced the tumor growth in urinary bladder: 80% of the rats had no tumor and 20% had low-grade tumors. Adding rapamycin from the 5th week was associated with more tumor growth: 20% of the rats had no tumors, 20% had low-grade tumors, and 60% had high-grade tumors. Moreover, in the groups with rapamycin treatment from the 9th week, 13th week, and 17th week, all rats developed high-grade papillary tumors in urinary bladder, as did the control group that received no rapamycin. The study results suggest that the anticancer effect of rapamycin on urothelial carcinoma is stage dependent. Early use of rapamycin provides better anticancer effect, whereas late use of rapamycin fails to inhibit the cancer growth. Copyright © 2014 Elsevier Inc. All rights reserved.
Synthesis and Biological Evaluation of Copper-64 Radiolabeled [DUPA-6-Ahx-(NODAGA)-5-Ava-BBN(7-14)NH2], a Novel Bivalent Targeting Vector Having Affinity for Two Distinct Biomarkers (GRPr/PSMA) of Prostate Cancer

PubMed Central

Bandari, Rajendra Prasad; Jiang, Zongrun; Reynolds, Tamila Stott; Bernskoetter, Nicole E.; Szczodroski, Ashley F.; Bassuner, Kurt J.; Kirkpatrick, Daniel L.; Rold, Tammy L.; Sieckman, Gary L.; Hoffman, Timothy J.; Connors, James P.; Smith, Charles J.

2014-01-01

Gastrin-releasing peptide receptors (GRPr) and prostate-specific membrane antigen (PSMA) are two identifying biomarkers expressed in very high numbers on prostate cancer cells and could serve as a useful tool for molecular targeting and diagnosis of disease via positron-emission tomography (PET). The aim of this study was to produce the multipurpose, bivalent [DUPA-6-Ahx-(64Cu-NODAGA)-5-Ava-BBN(7-14)NH2] radioligand for prostate cancer imaging, where DUPA = 2-[3-(1,3-Bis-tertbutoxycarbonylpropyl)-ureido]pentanedioic acid, a small-molecule, PSMA-targeting probe, 6Ahx = 6-aminohexanoic acid, 5-Ava = 5-aminovaleric acid, NODAGA = [2-(4,7-biscarboxymethyl)-1,4,7-(triazonan-1-yl)pentanedioic acid] (a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)), and BBN(7-14)NH2 = bombesin or BBN, a GRPr-specific peptide targeting probe. Methods The PSMA/GRPr dual targeting ligand precursor [DUPA-6-Ahx-K-5-Ava-BBN(7-14)NH2], was synthesized by solid-phase and manual peptide synthesis, after which NODAGA was added via manual conjugation to the ε-amine of lysine (K). The new bivalent GRPr/PSMA targeting vector was purified by reversed-phase high performance liquid chromatography (RP-HPLC), characterized by electrospray-ionization mass spectrometry (ESI-MS), and metallated with 64CuCl2 and natCuCl2. The receptor binding affinity was evaluated in human, prostate, PC-3 (GRPr-positive) and LNCaP (PSMA-positive) cells and the tumor-targeting efficacy determined in severe combined immunodeficient (SCID) and athymic nude mice bearing PC-3 and LNCaP tumors. Whole-body maximum intensity microPET/CT images of PC-3/LNCaP tumor-bearing mice were obtained 18 h post-injection (p.i.). Results Competitive binding assays in PC-3 and LNCaP cells indicated high receptor binding affinity for the [DUPA-6-Ahx-(natCu-NODAGA)-5-Ava-BBN(7-14)NH2] conjugate. MicroPET scintigraphy in PC-3/LNCaP tumor-bearing mice indicated that xenografted tumors were visible at 18 h p.i. with collateral, background radiation also being observed in non-target tissue. Conclusions [DUPA-6-Ahx-(64Cu-NODAGA)-5-Ava-BBN(7-14)NH2] targeting vector, as described herein, is the first example of a dual GRPr-/PSMA-targeting radioligand for molecular imaging prostate tumors. Detailed in vitro studies and microPET molecular imaging investigations of [DUPA-6-Ahx-(64Cu-NODAGA)-5-Ava-BBN(7-14)NH2] in tumor-bearing mice indicates that further studies are necessary to optimize uptake and retention of tracer in GRPr- and PSMA-positive tissues. PMID:24508213
Loophole to the universal photon spectrum in electromagnetic cascades and application to the cosmological lithium problem.

PubMed

Poulin, Vivian; Serpico, Pasquale Dario

2015-03-06

The standard theory of electromagnetic cascades onto a photon background predicts a quasiuniversal shape for the resulting nonthermal photon spectrum. This has been applied to very disparate fields, including nonthermal big bang nucleosynthesis (BBN). However, once the energy of the injected photons falls below the pair-production threshold the spectral shape is much harder, a fact that has been overlooked in past literature. This loophole may have important phenomenological consequences, since it generically alters the BBN bounds on nonthermal relics; for instance, it allows us to reopen the possibility of purely electromagnetic solutions to the so-called "cosmological lithium problem," which were thought to be excluded by other cosmological constraints. We show this with a proof-of-principle example and a simple particle physics model, compared with previous literature.

NON-EXTENSIVE STATISTICS TO THE COSMOLOGICAL LITHIUM PROBLEM

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

Hou, S. Q.; He, J. J.; Parikh, A.

Big Bang nucleosynthesis (BBN) theory predicts the abundances of the light elements D, {sup 3}He, {sup 4}He, and {sup 7}Li produced in the early universe. The primordial abundances of D and {sup 4}He inferred from observational data are in good agreement with predictions, however, BBN theory overestimates the primordial {sup 7}Li abundance by about a factor of three. This is the so-called “cosmological lithium problem.” Solutions to this problem using conventional astrophysics and nuclear physics have not been successful over the past few decades, probably indicating the presence of new physics during the era of BBN. We have investigated themore » impact on BBN predictions of adopting a generalized distribution to describe the velocities of nucleons in the framework of Tsallis non-extensive statistics. This generalized velocity distribution is characterized by a parameter q , and reduces to the usually assumed Maxwell–Boltzmann distribution for q = 1. We find excellent agreement between predicted and observed primordial abundances of D, {sup 4}He, and {sup 7}Li for 1.069 ≤ q ≤ 1.082, suggesting a possible new solution to the cosmological lithium problem.« less
[Study on different responses of rats' small intestine mucous membrane and bladder transitional epithelium in the same carcinogenic urine environment].

PubMed

Wu, B; Pan, C; Song, G

2001-10-25

To preliminarily verify the tentative idea of replacement of bladder transitional epithelium with small intestine mucous membrane to prevent recurrence of carcinoma of bladder. A certain segment of small intestine was transplanted to the urinary bladder of the same body in 17 rats. Then N-butyl-N-(4-hydroxy-butyl) nitrosamine (BBN) was used to induce carcinoma of bladder. BBN was used to 11 control rats that did not undergo operation. Bladder carcinoma failed to be found in the transplanted small intestine mucous membrane in all experimental rats except one. After stimulation of BBN, carcinoma of urinary bladder occurred in all rats' bladder transitional epithelium. 1) The carcinogenic substances in the urine of rats suffering from BBN-induced bladder carcinoma are carcinogenic only to bladder transitional epithelium and have no effect on small intestine epithelium. 2) Bladder transitional epithelium may be more sensitive to the urine carcinogenic substances and easier to be cancerized than small intestine epithelium. 3) The tentative idea of substitution of small intestine mucous membrane for bladder transitional epithelium to prevent the recurrence of bladder carcinoma is worth further studying.
Medical students' reflections on emotions concerning breaking bad news.

PubMed

Toivonen, Asta Kristiina; Lindblom-Ylänne, Sari; Louhiala, Pekka; Pyörälä, Eeva

2017-10-01

To gain a deeper understanding of fourth year medical students' reflections on emotions in the context of breaking bad news (BBN). During the years 2010-2012, students reflected on their emotions concerning BBN in a learning assignment at the end of the communications skills course. The students were asked to write a description of how they felt about a BBN case. The reflections were analysed using qualitative content analysis. 351 students agreed to participate in the study. We recognized ten categories in students' reflections namely empathy, insecurity, anxiety, sadness, ambivalence, guilt, hope, frustration, gratefulness and emotional detachment. Most students expressed empathy, but there was a clear tension between feeling empathy and retaining professional distance by emotional detachment. Students experience strong and perplexing emotions during their studies, especially in challenging situations. A deeper understanding of students' emotions is valuable for supporting students' professional development and coping in their work in the future. Medical students need opportunities to reflect on emotional experiences during their education to find strategies for coping with them. Emotions should be actively discussed in studies where the issues of BBN are addressed. Teachers need education in attending emotional issues constructively. Copyright © 2017 Elsevier B.V. All rights reserved.
Effects of sterile neutrinos and an extra dimension on big bang nucleosynthesis

NASA Astrophysics Data System (ADS)

Jang, Dukjae; Kusakabe, Motohiko; Cheoun, Myung-Ki

2018-02-01

By assuming the existence of extra-dimensional sterile neutrinos in the big bang nucleosynthesis (BBN) epoch, we investigate the sterile neutrino (νs) effects on the BBN and constrain some parameters associated with the νs properties. First, for the cosmic expansion rate, we take into account effects of a five-dimensional bulk and intrinsic tension of the brane embedded in the bulk and constrain a key parameter of the extra dimension by using the observational element abundances. Second, effects of the νs traveling on or off the brane are considered. In this model, the effective mixing angle between a νs and an active neutrino depends on energy, which may give rise to a resonance effect on the mixing angle. Consequently, the reaction rate of the νs can be drastically changed during the cosmic evolution. We estimated abundances and temperature of the νs by solving the rate equation as a function of temperature until the sterile neutrino decoupling. We then find that the relic abundance of the νs is drastically enhanced by the extra dimension and maximized for a characteristic resonance energy Eres≳0.01 GeV . Finally, some constraints related to the νs, i.e., mixing angle and mass difference, are discussed in detail with the comparison of our BBN calculations corrected by the extra-dimensional νs to observational data on light element abundances.
New detectors to explore the lifetime frontier

NASA Astrophysics Data System (ADS)

Chou, John Paul; Curtin, David; Lubatti, H. J.

2017-04-01

Long-lived particles (LLPs) are a common feature in many beyond the Standard Model theories, including supersymmetry, and are generically produced in exotic Higgs decays. Unfortunately, no existing or proposed search strategy will be able to observe the decay of non-hadronic electrically neutral LLPs with masses above ∼ GeV and lifetimes near the limit set by Big Bang Nucleosynthesis (BBN), cτ ≲107-108 m. We propose the MATHUSLA surface detector concept (MAssive Timing Hodoscope for Ultra Stable neutraL pArticles), which can be implemented with existing technology and in time for the high luminosity LHC upgrade to find such ultra-long-lived particles (ULLPs), whether produced in exotic Higgs decays or more general production modes. We also advocate a dedicated LLP detector at a future 100 TeV collider, where a modestly sized underground design can discover ULLPs with lifetimes at the BBN limit produced in sub-percent level exotic Higgs decays.
Immunological and metabolic concomitants of cyclosporin prevention of diabetes in BB rats.

PubMed

Yale, J F; Grose, M; Seemayer, T A; Marliss, E B

1987-06-01

The metabolic and immunological effects of cyclosporin given to prevent diabetes in BB rats were examined. Diabetes-prone (BBdp) and normal (BBn) BB rats received either oral cyclosporin (10 mg X kg-1 X day-1 or its vehicle from age 30-150 days. Six of 21 (29%) vehicle-treated rats became glycosuric, with hyperglycemia, weight loss, and unremitting insulin requirements, and showed destruction of islet beta-cells. Five of 24 (21%) cyclosporin-treated rats became glycosuric, but none demonstrated weight loss, all required insulin only intermittently after onset, and all showed persistence of islet beta-cells. Cyclosporin induced hypoinsulinemic glucose intolerance in BBn rats. Cyclosporin inhibited the normal rise with age of peripheral blood lymphocyte cell numbers, identified with monoclonal antibodies. OX19+ (pan-T) and W3/25+ helper T-lymphocytes were affected, and there was an increase in the large W3/13+ OX19- population characteristic of BBdp rats; in addition, this subset appeared in BBn rats. Cyclosporin also caused the appearance and/or increase in both BBdp and BBn rats of W3/25+ OX19- and OX8+ OX19- subsets. Suppressor/cytotoxic (OX8+) T-lymphocytes and Ia+ cells were less affected. The incidence of hyperglycemia and glycosuria was therefore unaltered by cyclosporin, although the diabetic syndrome was milder. BBn rats receiving cyclosporin showed glucose intolerance, suggesting that in BBdp rats, the net effects of immunosuppression on beta-cell destruction may have been counterbalanced by the direct effect on the same cells. The attenuation of diabetes in BBdp rats occurred through further immunosuppression rather than by correction of its preexisting immunodeficiency.
Gastrin-releasing peptide receptor (GRPr) promotes EMT, growth, and invasion in canine prostate cancer.

PubMed

Elshafae, Said M; Hassan, Bardes B; Supsavhad, Wachiraphan; Dirksen, Wessel P; Camiener, Rachael Y; Ding, Haiming; Tweedle, Michael F; Rosol, Thomas J

2016-06-01

The gastrin-releasing peptide receptor (GRPr) is upregulated in early and late-stage human prostate cancer (PCa) and other solid tumors of the mammary gland, lung, head and neck, colon, uterus, ovary, and kidney. However, little is known about its role in prostate cancer. This study examined the effects of a heterologous GRPr agonist, bombesin (BBN), on growth, motility, morphology, gene expression, and tumor phenotype of an osteoblastic canine prostate cancer cell line (Ace-1) in vitro and in vivo. The Ace-1 cells were stably transfected with the human GRPr and tumor cells were grown in vitro and as subcutaneous and intratibial tumors in nude mice. The effect of BBN was measured on cell proliferation, cell migration, tumor growth (using bioluminescence), tumor cell morphology, bone tumor phenotype, and epithelial-mesenchymal transition (EMT) and metastasis gene expression (quantitative RT-PCR). GRPr mRNA expression was measured in primary canine prostate cancers and normal prostate glands. Bombesin (BBN) increased tumor cell proliferation and migration in vitro and tumor growth and invasion in vivo. BBN upregulated epithelial-to-mesenchymal transition (EMT) markers (TWIST, SNAIL, and SLUG mRNA) and downregulated epithelial markers (E-cadherin and β-catenin mRNA), and modified tumor cell morphology to a spindle cell phenotype. Blockade of GRPr upregulated E-cadherin and downregulated VIMENTIN and SNAIL mRNA. BBN altered the in vivo tumor phenotype in bone from an osteoblastic to osteolytic phenotype. Primary canine prostate cancers had increased GRPr mRNA expression compared to normal prostates. These data demonstrated that the GRPr is important in prostate cancer growth and progression and targeting GRPr may be a promising strategy for treatment of prostate cancer. Prostate 76:796-809, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Prevention of Chemically-Induced Urinary Bladder Cancers by Naproxen: Protocols to Reduce Gastric Toxicity in Humans Do Not Alter Preventive Efficacy

PubMed Central

Lubet, Ronald A.; Scheiman, James M.; Bode, Ann; White, Jonathan; Minasian, Lori; Juliana, M. Margaret; Boring, Daniel L.; Steele, Vernon E.; Grubbs, Clinton J.

2015-01-01

The COX inhibitors (NSAIDs/Coxibs) are a major focus for the chemoprevention of cancer. The COX-2 specific inhibitors have progressed to clinical trials, and have shown preventive efficacy in colon and skin cancers. However, they have significant adverse cardiovascular (CV) effects. Certain NSAIDs (e.g., naproxen (NPX)] have a good cardiac profile, but can cause gastric toxicity. The present studies examined protocols to reduce this toxicity of NPX. Female Fischer-344 rats were treated weekly with the urinary bladder specific carcinogen hydroxybutyl(butyl)nitrosamine (OH-BBN) for 8 weeks. Rats were dosed daily with NPX (40 mg/Kg BW/day, gavage) or with the proton pump inhibitor omeprazole (4.0 mg/Kg BW/day) either singly or in combination beginning 2 weeks after the final OH-BBN. OH-BBN treated rats, 96% developed urinary bladder cancers. While omeprazole alone was ineffective (97% cancers), NPX alone or combined with omeprazole prevented cancers; yielding 27 and 35% cancers, respectively. In a separate study, OH-BBN treated rats were administered NPX: (A) daily, (B) 1 week daily NPX/1wk vehicle, (C) 3 weeks daily NPX/3 week vehicle, or (D) daily vehicle beginning 2 weeks after last OH-BBN treatment. In the intermittent dosing study, protocol A, B, C and D resulted in palpable cancers in 27%, 22%, 19% and 96% of rats (P<0.01). Short-term NPX treatment increased apoptosis, but did not alter proliferation in the urinary bladder cancers. Two different protocols which should decrease the gastric toxicity of NSAIDs in humans did not alter chemopreventive efficacy. This should encourage the use of NSAIDs (e.g. NPX) in clinical prevention trials. PMID:25762530
Prevention of chemically induced urinary bladder cancers by naproxen: protocols to reduce gastric toxicity in humans do not alter preventive efficacy.

PubMed

Lubet, Ronald A; Scheiman, James M; Bode, Ann; White, Jonathan; Minasian, Lori; Juliana, M Margaret; Boring, Daniel L; Steele, Vernon E; Grubbs, Clinton J

2015-04-01

The COX inhibitors (NSAID/Coxibs) are a major focus for the chemoprevention of cancer. The COX-2-specific inhibitors have progressed to clinical trials and have shown preventive efficacy in colon and skin cancers. However, they have significant adverse cardiovascular effects. Certain NSAIDs (e.g., naproxen) have a good cardiac profile, but can cause gastric toxicity. The present study examined protocols to reduce this toxicity of naproxen. Female Fischer-344 rats were treated weekly with the urinary bladder-specific carcinogen hydroxybutyl(butyl)nitrosamine (OH-BBN) for 8 weeks. Rats were dosed daily with NPX (40 mg/kg body weight/day, gavage) or with the proton pump inhibitor omeprazole (4.0 mg/kg body weight/day) either singly or in combination beginning 2 weeks after the final OH-BBN. OH-BBN-treated rats, 96% developed urinary bladder cancers. While omeprazole alone was ineffective (97% cancers), naproxen alone or combined with omeprazole-prevented cancers, yielding 27 and 35% cancers, respectively. In a separate study, OH-BBN -: treated rats were administered naproxen: (A) daily, (B) 1 week daily naproxen/1week vehicle, (C) 3 weeks daily naproxen/3 week vehicle, or (D) daily vehicle beginning 2 weeks after last OH-BBN treatment. In the intermittent dosing study, protocol A, B, C, and D resulted in palpable cancers in 27%, 22%, 19%, and 96% of rats (P < 0.01). Short-term naproxen treatment increased apoptosis, but did not alter proliferation in the urinary bladder cancers. Two different protocols that should decrease the gastric toxicity of NSAIDs in humans did not alter chemopreventive efficacy. This should encourage the use of NSAIDs (e.g., naproxen) in clinical prevention trials. ©2015 American Association for Cancer Research.
Imaging Primary Prostate Cancer and Bone Metastasis

DTIC Science & Technology

2006-04-01

BBN peptide has a pyroglutamic acid at the N-terminus and an amidated methionine at the C-termi- nus, further modification and radiolabeling of this...14), where Aca refers to ε-aminocaproic acid . For both compounds, in vitro assays, metabolic stability, and microPET studies were performed to...BBN(7- 14) (■) by PC-3 cells. Data are percentage of acid - resistant (internalized) radio- activity in cells for internalization, and percentage of
First direct measurement of the 2H(α,γ)6Li cross section at big bang energies and the primordial lithium problem.

PubMed

Anders, M; Trezzi, D; Menegazzo, R; Aliotta, M; Bellini, A; Bemmerer, D; Broggini, C; Caciolli, A; Corvisiero, P; Costantini, H; Davinson, T; Elekes, Z; Erhard, M; Formicola, A; Fülöp, Zs; Gervino, G; Guglielmetti, A; Gustavino, C; Gyürky, Gy; Junker, M; Lemut, A; Marta, M; Mazzocchi, C; Prati, P; Rossi Alvarez, C; Scott, D A; Somorjai, E; Straniero, O; Szücs, T

2014-07-25

Recent observations of (6)Li in metal poor stars suggest a large production of this isotope during big bang nucleosynthesis (BBN). In standard BBN calculations, the (2)H(α,γ)(6)Li reaction dominates (6)Li production. This reaction has never been measured inside the BBN energy region because its cross section drops exponentially at low energy and because the electric dipole transition is strongly suppressed for the isoscalar particles (2)H and α at energies below the Coulomb barrier. Indirect measurements using the Coulomb dissociation of (6)Li only give upper limits owing to the dominance of nuclear breakup processes. Here, we report on the results of the first measurement of the (2)H(α,γ)(6)Li cross section at big bang energies. The experiment was performed deep underground at the LUNA 400 kV accelerator in Gran Sasso, Italy. The primordial (6)Li/(7)Li isotopic abundance ratio has been determined to be (1.5 ± 0.3) × 10(-5), from our experimental data and standard BBN theory. The much higher (6)Li/(7)Li values reported for halo stars will likely require a nonstandard physics explanation, as discussed in the literature.
Nonspecific esterase reaction in hyperplastic urinary bladder epithelium induced by administration of N-butyl-N-(4-hydroxybutyl)nitrosamine, freezing and formalin instillation in rats.

PubMed Central

Akagi, A.; Otsuka, H.

1988-01-01

Chronological changes in nonspecific esterase (NSE) activity in hyperplasia of the bladder mucosa in Wistar rats induced by the administration of 0.05% N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN) in their drinking water for up to 20 weeks and in reversible regenerative hyperplasia by freeze ulceration and 20% formalin instillation in the bladder were compared. In regenerative hyperplasia foci with strong NSE activity could not be proved throughout the experimental period, while the foci were detected in hyperplastic epithelium induced by BBN treatment for more than 3 weeks. The focus of NSE high activity persisted for 56 weeks after withdrawal of the carcinogen and the focus or area with the same NSE reaction appeared in papilloma and transitional cell carcinoma seen in weeks 7 to 20 of BBN treatment. The appearance of focal strong activity of NSE seemed to be a promising marker for the precursor lesions of bladder tumors. Short uniform, pleomorphic microvilli were observed on the cell surface of preneoplastic and carcinomatous lesions by BBN as well as on that of regenerative hyperplasia after freeze ulceration and formalin instillation. Images Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11 Fig. 12 Fig. 13 PMID:3390388
Dark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data

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

Abbott, T.M.C.; et al.

We combine Dark Energy Survey Year 1 clustering and weak lensing data with Baryon Acoustic Oscillations (BAO) and Big Bang Nucleosynthesis (BBN) experiments to constrain the Hubble constant. Assuming a flatmore » $$\\Lambda$$CDM model with minimal neutrino mass ($$\\sum m_\
Synthesis of ethylene-propylene rubber graft copolymers by borane approach

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

Chung, T.C.; Janvikul, W.; Bernard, R.

1994-01-01

This paper describes a new method to prepare graft copolymers which have an EP rubber backbone and several free radical polymerized polymers grafted thereto. The process involves hydroboration of commercial EPDM rubbers, such as poly(ethylene-co-propylene-co-1,4-hexadiene) and poly(ethylene-co-propylene-co-5-ethylidene-2-norbornene), with 9-borabicyclononane (9-BBN). The resulting secondary alkyl-9-BBN moieties in the EPDM copolymer were then exposed to oxygen in the presence of free radical polymerizable monomers. Under certain conditions, the selective autoxidation reaction of secondary alkyl-9-BBN took place to create desirable polymeric radicals which can in situ initiate free radical polymerization. High graft efficiency was observed with controllable copolymer compositions. The graft copolymer ofmore » EP-g-PMMA is used to show the chemistry as well as some of the physical properties.« less
Comparative study of 64Cu/NOTA-[D-Tyr6,βAla11,Thi13,Nle14]BBN(6-14) monomer and dimers for prostate cancer PET imaging

PubMed Central

2012-01-01

Background Gastrin-releasing peptide receptors [GRPR] are highly over-expressed in multiple cancers and have been studied as a diagnostic target. Multimeric gastrin-releasing peptides are expected to have enhanced tumor uptake and affinity for GRPR. In this study, a 64Cu-labeled 1,4,7-triazacyclononane-1,4,7-triacetic acid [NOTA]-monomer and two NOTA-dimers of [D-Tyr6,βAla11, Thi13, Nle14]bombesin(6-14) ] [BBN(6-14)] were compared. Methods Monomeric and dimeric peptides were synthesized on solid phase support and radiolabeled with 64Cu. NOTA-dimer 1 consists of asymmetrically linked BBN(6-14), while NOTA-dimer 2 has similar spacer between the two BBN(6-14) ligands and the chelator. In vitro GRPR-binding affinities were determined with competitive binding assays on PC3 human prostate cancer cells. In vivo stability and biodistribution of radiolabeled compounds were assessed in Balb/c mice. Cellular uptake and efflux were measured with radiolabeled NOTA-monomer and NOTA-dimer 2 on PC3 cells for up to 4 h. In vivo biodistribution kinetics were measured in PC3 tumor-bearing Balb/c nude mice by μ-positron emission tomography [μPET] imaging and confirmed by dissection and counting. Results NOTA-monomer, NOTA-dimers 1 and 2 were prepared with purity of 99%. The inhibition constants of the three BBN peptides were comparable and in the low nanomolar range. All 64Cu-labeled peptides were stable up to 24 h in mouse plasma and 1 h in vivo. 64Cu/NOTA-dimer 2 featuring a longer spacer between the two BBN(6-14) ligands is a more potent GRPR-targeting probe than 64Cu/NOTA-dimer 1. PC3 tumor uptake profiles are slightly different for 64Cu/NOTA-monomer and 64Cu/NOTA-dimer 2; the monomeric BBN-peptide tracer exhibited higher tumor uptake during the first 0.5 h and a fast renal clearance resulting in higher tumor-to-muscle ratio when compared to 64Cu/NOTA-dimer 2. The latter exhibited higher tumor-to-blood ratio and was retained longer at the tumor site when compared to 64Cu/NOTA-monomer. Lower ratios of tumor-to-blood and tumor-to-muscle in blocking experiments showed GRPR-dependant tumor uptake for both tracers. Conclusion Both 64Cu/NOTA-monomer and 64Cu/NOTA-dimer 2 are suitable for detecting GRPR-positive prostate cancer in vivo by PET. Tumor retention was improved in vivo with 64Cu/NOTA-dimer 2 by applying polyvalency effect and/or statistical rebinding. PMID:22333272
Comparative study of 64Cu/NOTA-[D-Tyr6,βAla11,Thi13,Nle14]BBN(6-14) monomer and dimers for prostate cancer PET imaging.

PubMed

Fournier, Patrick; Dumulon-Perreault, Véronique; Ait-Mohand, Samia; Langlois, Réjean; Bénard, François; Lecomte, Roger; Guérin, Brigitte

2012-02-14

Gastrin-releasing peptide receptors [GRPR] are highly over-expressed in multiple cancers and have been studied as a diagnostic target. Multimeric gastrin-releasing peptides are expected to have enhanced tumor uptake and affinity for GRPR. In this study, a 64Cu-labeled 1,4,7-triazacyclononane-1,4,7-triacetic acid [NOTA]-monomer and two NOTA-dimers of [D-Tyr6,βAla11, Thi13, Nle14]bombesin(6-14) ] [BBN(6-14)] were compared. Monomeric and dimeric peptides were synthesized on solid phase support and radiolabeled with 64Cu. NOTA-dimer 1 consists of asymmetrically linked BBN(6-14), while NOTA-dimer 2 has similar spacer between the two BBN(6-14) ligands and the chelator. In vitro GRPR-binding affinities were determined with competitive binding assays on PC3 human prostate cancer cells. In vivo stability and biodistribution of radiolabeled compounds were assessed in Balb/c mice. Cellular uptake and efflux were measured with radiolabeled NOTA-monomer and NOTA-dimer 2 on PC3 cells for up to 4 h. In vivo biodistribution kinetics were measured in PC3 tumor-bearing Balb/c nude mice by μ-positron emission tomography [μPET] imaging and confirmed by dissection and counting. NOTA-monomer, NOTA-dimers 1 and 2 were prepared with purity of 99%. The inhibition constants of the three BBN peptides were comparable and in the low nanomolar range. All 64Cu-labeled peptides were stable up to 24 h in mouse plasma and 1 h in vivo. 64Cu/NOTA-dimer 2 featuring a longer spacer between the two BBN(6-14) ligands is a more potent GRPR-targeting probe than 64Cu/NOTA-dimer 1. PC3 tumor uptake profiles are slightly different for 64Cu/NOTA-monomer and 64Cu/NOTA-dimer 2; the monomeric BBN-peptide tracer exhibited higher tumor uptake during the first 0.5 h and a fast renal clearance resulting in higher tumor-to-muscle ratio when compared to 64Cu/NOTA-dimer 2. The latter exhibited higher tumor-to-blood ratio and was retained longer at the tumor site when compared to 64Cu/NOTA-monomer. Lower ratios of tumor-to-blood and tumor-to-muscle in blocking experiments showed GRPR-dependant tumor uptake for both tracers. Both 64Cu/NOTA-monomer and 64Cu/NOTA-dimer 2 are suitable for detecting GRPR-positive prostate cancer in vivo by PET. Tumor retention was improved in vivo with 64Cu/NOTA-dimer 2 by applying polyvalency effect and/or statistical rebinding.
Synthesis and biological evaluation of copper-64 radiolabeled [DUPA-6-Ahx-(NODAGA)-5-Ava-BBN(7-14)NH2], a novel bivalent targeting vector having affinity for two distinct biomarkers (GRPr/PSMA) of prostate cancer.

PubMed

Bandari, Rajendra Prasad; Jiang, Zongrun; Reynolds, Tamila Stott; Bernskoetter, Nicole E; Szczodroski, Ashley F; Bassuner, Kurt J; Kirkpatrick, Daniel L; Rold, Tammy L; Sieckman, Gary L; Hoffman, Timothy J; Connors, James P; Smith, Charles J

2014-04-01

Gastrin-releasing peptide receptors (GRPr) and prostate-specific membrane antigen (PSMA) are two identifying biomarkers expressed in very high numbers on prostate cancer cells and could serve as a useful tool for molecular targeting and diagnosis of disease via positron-emission tomography (PET). The aim of this study was to produce the multipurpose, bivalent [DUPA-6-Ahx-((64)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] radioligand for prostate cancer imaging, where DUPA = (2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid), a small-molecule, PSMA-targeting probe, 6Ahx = 6-aminohexanoic acid, 5-Ava = 5-aminovaleric acid, NODAGA = [2-(4,7-biscarboxymethyl)-1,4,7-(triazonan-1-yl)pentanedioic acid] (a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)), and BBN(7-14)NH2 = bombesin, a GRPr-specific peptide targeting probe. The PSMA/GRPr dual targeting ligand precursor [DUPA-6-Ahx-K-5-Ava-BBN(7-14)NH2], was synthesized by solid-phase and manual peptide synthesis, after which NODAGA was added via manual conjugation to the ε-amine of lysine (K). The new bivalent GRPr/PSMA targeting vector was purified by reversed-phase high performance liquid chromatography (RP-HPLC), characterized by electrospray-ionization mass spectrometry (ESI-MS), and metallated with (64)CuCl2 and (nat)CuCl2. The receptor binding affinity was evaluated in human, prostate, PC-3 (GRPr-positive) and LNCaP (PSMA-positive) cells and the tumor-targeting efficacy determined in severe combined immunodeficient (SCID) and athymic nude mice bearing PC-3 and LNCaP tumors. Whole-body maximum intensity microPET/CT images of PC-3/LNCaP tumor-bearing mice were obtained 18 h post-injection (p.i.). Competitive binding assays in PC-3 and LNCaP cells indicated high receptor binding affinity for the [DUPA-6-Ahx-((nat)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] conjugate. MicroPET scintigraphy in PC-3/LNCaP tumor-bearing mice indicated that xenografted tumors were visible at 18h p.i. with collateral, background radiation also being observed in non-target tissue. DUPA-6-Ahx-((64)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] targeting vector, as described herein, is the first example of a dual GRPr-/PSMA-targeting radioligand for molecular of imaging prostate tumors. Detailed in vitro studies and microPET molecular imaging investigations of [DUPA-6-Ahx-((64)Cu-NODAGA)-5-Ava-BBN(7-14)NH2 in tumor-bearing mice indicate that further studies are necessary to optimize uptake and retention of tracer in GRPr- and PSMA-positive tissues. Published by Elsevier Inc.
Advanced distributed simulation technology: Digital Voice Gateway Reference Guide

NASA Astrophysics Data System (ADS)

Vanhook, Dan; Stadler, Ed

1994-01-01

The Digital Voice Gateway (referred to as the 'DVG' in this document) transmits and receives four full duplex encoded speech channels over the Ethernet. The information in this document applies only to DVG's running firmware of the version listed on the title page. This document, previously named Digital Voice Gateway Reference Guide, BBN Systems and Technologies Corporation, Cambridge, MA 02138, was revised for revision 2.00. This new revision changes the network protocol used by the DVG, to comply with the SINCGARS radio simulation (For SIMNET 6.6.1). Because of the extensive changes to revision 2.00 a separate document was created rather than supplying change pages.
Some nuclear physics aspects of BBN

NASA Astrophysics Data System (ADS)

Coc, Alain

2017-09-01

Primordial or big bang nucleosynthesis (BBN) is now a parameter free theory whose predictions are in good overall agreement with observations. However, the 7 Li calculated abundance is significantly higher than the one deduced from spectroscopic observations. Nuclear physics solutions to this lithium problem have been investigated by experimental means. Other solutions which were considered involve exotic sources of extra neutrons which inevitably leads to an increase of the deuterium abundance, but this seems now excluded by recent deuterium observations.
Revised thermonuclear rate of 7Be(n ,α ) 4He relevant to Big-Bang nucleosynthesis

NASA Astrophysics Data System (ADS)

Hou, S. Q.; He, J. J.; Kubono, S.; Chen, Y. S.

2015-05-01

In the standard Big-Bang nucleosynthesis (BBN) model, the primordial 7Li abundance is overestimated by about a factor of 2 to 3 compared to astronomical observations; this is the so-called pending cosmological lithium problem. The 7Be(n ,α )4He reaction was regarded as the secondary important reaction in affecting the 7Li abundance by destructing the 7Be nucleus in BBN. However, the reaction rate of 7Be(n ,α )4He has not been well studied so far. This reaction rate was first estimated by Wagoner in 1969, which has been primarily adopted in the current BBN simulations. This simple estimate involved only a direct reaction contribution, but the resonant component should also be considered according to the later experimental results. In the present work, we revised this rate based on the indirect cross-section data available for the 4He(α ,n )7Be and 4He(α ,p )7Li reactions by applying the charge symmetry and the principle of detailed balance. Our new result shows that the previous rate (acting as an upper limit) is overestimated by about a factor of ten. The BBN simulation shows that the present rate leads to a 1.2% increase in the final 7Li abundance compared with the result using the Wagoner rate and, hence, the present rate even worsens the 7Li problem. By the present estimation, the role of 7Be(n ,α )4He in destroying 7Be is weakened from the second most importance to the third and, in turn, the 7Be(d ,p )2 4He reaction becomes of secondary importance in destroying 7Be.

THM and primordial nucleosynthesis: Results and perspectives

NASA Astrophysics Data System (ADS)

Pizzone, R. G.; Spartá, R.; Bertulani, C.; Spitaleri, C.; La Cognata, M.; Lamia, L.; Tumino, A.

2017-09-01

Big Bang Nucleosynthesis (BBN) requires several nuclear physics inputs and nuclear reaction rates. An up-to-date compilation of direct cross sections of d(d,p)t, d(d,n) 3 He and 3 He(d,p) 4 He reactions is given, being these ones among the most uncertain bare-nucleus cross sections. An intense experimental effort has been carried on in the last decade to apply the Trojan Horse Method (THM) to study reactions of relevance for the BBN and measure their astrophysical S( E) -factor. The reaction rates and the relative error for the four reactions of interest are then numerically calculated in the temperature ranges of relevance for BBN ( 0.01
Leptogenesis scenarios for natural SUSY with mixed axion-higgsino dark matter

NASA Astrophysics Data System (ADS)

Bae, Kyu Jung; Baer, Howard; Serce, Hasan; Zhang, Yi-Fan

2016-01-01

Supersymmetric models with radiatively-driven electroweak naturalness require light higgsinos of mass ~ 100-300 GeV . Naturalness in the QCD sector is invoked via the Peccei-Quinn (PQ) axion leading to mixed axion-higgsino dark matter. The SUSY DFSZ axion model provides a solution to the SUSY μ problem and the Little Hierarchy μll m3/2 may emerge as a consequence of a mismatch between PQ and hidden sector mass scales. The traditional gravitino problem is now augmented by the axino and saxion problems, since these latter particles can also contribute to overproduction of WIMPs or dark radiation, or violation of BBN constraints. We compute regions of the TR vs. m3/2 plane allowed by BBN, dark matter and dark radiation constraints for various PQ scale choices fa. These regions are compared to the values needed for thermal leptogenesis, non-thermal leptogenesis, oscillating sneutrino leptogenesis and Affleck-Dine leptogenesis. The latter three are allowed in wide regions of parameter space for PQ scale fa~ 1010-1012 GeV which is also favored by naturalness: fa ~ √μMP/λμ ~ 1010-1012 GeV . These fa values correspond to axion masses somewhat above the projected ADMX search regions.
Right-handed neutrinos as the dark radiation: Status and forecasts for the LHC

NASA Astrophysics Data System (ADS)

Anchordoqui, Luis A.; Goldberg, Haim; Steigman, Gary

2013-01-01

Precision data from cosmology (probing the CMB decoupling epoch) and light-element abundances (probing the BBN epoch) have hinted at the presence of extra relativistic degrees of freedom, the so-called "dark radiation." We present a model independent study to account for the dark radiation by means of the right-handed partners of the three, left-handed, standard model neutrinos. We show that milli-weak interactions of these Dirac states (through their coupling to a TeV-scale Z‧ gauge boson) may allow the νR's to decouple much earlier, at a higher temperature, than their left-handed counterparts. If the νR's decouple during the quark-hadron crossover transition, they are considerably cooler than the νL's and contribute less than 3 extra "equivalent neutrinos" to the early Universe energy density. For decoupling in this transition region, the 3νR generate ΔNν=3(<3, extra relativistic degrees of freedom at BBN and at the CMB epochs. Consistency with present constraints on dark radiation permits us to identify the allowed region in the parameter space of Z‧ masses and couplings. Remarkably, the allowed region is within the range of discovery of LHC14.
Decline in Buprenorphine/Naloxone Prescriptions in a State Medicaid Population Following Formulary Conversion from Suboxone to Bunavail.

PubMed

Soper, Richard; Appajosyula, Sireesh; Deximo, Christina

2018-04-01

A large, statewide, fee-for-service Medicaid plan recently (October 2015) executed a complete switch from sublingual buprenorphine-naloxone [(SLBN), Suboxone ® ] to buccal buprenorphine-naloxone [(BBN), Bunavail ® ] on its preferred drug formulary. This complete formulary switch provided an opportunity to assess dynamic changes in prescribing patterns, patient/physician acceptance, and indices of potential misuse/diversion. For the period January 1, 2015 through December 31, 2016, two datasets were analyzed: prescriptions and associated costs for buprenorphine-naloxone (BN) products and urine toxicology test results for patients in the Medicaid plan. The dataset comprised 1370 unique providers ordering 643,225 prescriptions for opioid addiction therapy. Patient and order volumes, and the rate of monthly positive laboratory values for opioid molecules and cocaine were reviewed. A targeted survey of physicians treating opioid-dependent patients with state Medicaid plan coverage was also conducted. Upon plan conversion to BBN, there was a rapid increase in monthly BBN prescriptions mirrored by a rapid decrease in SLBN prescriptions. Peak in BBN prescriptions (2633 in November 2015) was approximately 60% lower than peak in SLBN prescriptions (6531 in July 2015). An unexpected finding was a 68% reduction of the overall BN market, indicating that many BN prescriptions were abandoned. The reduction was associated with quarterly cost savings to the Medicaid plan of approximately $3.5 million. Toxicology results indicated a reduction in drug positivity (defined as positivity for cocaine and/or any opioids except buprenorphine and methadone) from 13-16% in 2015 to less than 10% in 2016. Heroin positivity decreased from approximately 9% in December 2015 to an average of less than 1% during the last quarter of 2016, while positivity for norbuprenorphine, the major metabolite of buprenorphine, showed a marked increase in 2016 vs 2015. Among physicians who responded to the targeted survey most rated BBN as more difficult to abuse or misuse than SLBN. The rapid reduction in the overall BN market following a complete formulary switch from SLBN to BBN was associated with quarterly savings of $3.5 million for the state Medicaid plan. Toxicology data suggest that this cost saving was realized in the context of improved physician and patient adherence to treatment protocols. The changing market dynamics can potentially be explained by a number of contributory factors, including a reduction of diversion and illicit distribution of BN following formulary conversion. These results are considered hypothesis-generating and future research should systematically compare the propensity for diversion and abuse of BN products using various epidemiological tracking tools. BioDelivery Sciences International, Inc.
Tumor bombesin analog loaded long-circulating and pH-sensitive liposomes as tool for tumor identification.

PubMed

de Barros, André Luís Branco; Mota, Luciene das Graças; Soares, Daniel Crístian Ferreira; Coelho, Marina Melo Antunes; Oliveira, Mônica Cristina; Cardoso, Valbert Nascimento

2011-12-15

Long-circulating and pH-sensitive liposomes trapping (99m)Tc-HYNIC-βAla-bombesin((7-14)) (aSpHL-(99m)Tc-BBN((7-14))) were successfully prepared. Biodistribution studies and scintigraphic images were performed in Ehrlich tumor-bearing Swiss mice. This system showed high accumulation in tumor tissue with high tumor-to-muscle ratio. Therefore, aSpHL-(99m)Tc-BBN((7-14)) could be considered as a potential agent for tumor diagnosis. Published by Elsevier Ltd.
Galactic fly-bys: New source of lithium production

NASA Astrophysics Data System (ADS)

Prodanović, Tijana; Bogdanović, Tamara; Urošević, Dejan

2013-05-01

Observations of low-metallicity halo stars have revealed a puzzling result: the abundance of Li7 in these stars is at least three times lower than their predicted primordial abundance. It is unclear whether the cause of this disagreement is a lack of understanding of lithium destruction mechanisms in stars or the non-standard physics behind the big bang nucleosynthesis (BBN). Uncertainties related to the destruction of lithium in stars can be circumvented if lithium abundance is measured in the “pristine” gas of the low metallicity systems. The first measurement in one such system, the small magellanic cloud (SMC), was found to be at the level of the pure expected primordial value, but is on the other hand, just barely consistent with the expected galactic abundance for the system at the SMC metallicity, where important lithium quantity was also produced in interactions of galactic cosmic rays and presents an addition to the already present primordial abundance. Because of the importance of the SMC lithium measurement for the resolution of the lithium problem, we here draw attention to the possibility of another post-BBN production channel of lithium, which could present an important addition to the observed SMC lithium abundance. Besides standard galactic cosmic rays, additional post-BBN production of lithium might come from cosmic rays accelerated in galaxy-galaxy interactions. This might be important for a system such is the SMC, which has experienced galaxy harassment in its history. Within a simplified but illustrative framework we demonstrate that large-scale tidal shocks from a few galactic fly-bys can possibly produce lithium in amounts comparable to those expected from the interactions of galactic cosmic-rays produced in supernovae over the entire history of a system. In case of the SMC, we find that only two such fly-bys could possibly account for as much lithium as the standard, galactic cosmic ray production channel. However, adding any a new mechanism for post-BBN production of lithium, like the one proposed here, would contribute to the observed SMC lithium abundance, causing this measurement to be more in tension with the primordial abundance predicted by the standard BBN.
Influence of Parallel Dark Matter Sectors on Big Bang Nucleosynthesis

NASA Astrophysics Data System (ADS)

Challa, Venkata Sai Sreeharsha

Big Bang Nucleosynthesis (BBN) is a phenomenological theory that describes the synthesis of light nuclei after a few seconds of the cosmic time in the primordial universe. The twelve nuclear reactions in the first few seconds of the cosmic history are constrained by factors such as baryon to photon ratio, number of neutrino families, and present day element abundances. The belief that the expansion of the universe must be slowed down by gravity, was defeated by the recent observation of an accelerated expansion of the universe. Friedmann equations, which describe the cosmic dynamics, need to be revised considering also the existence of dark matter, another recent astronomical observation. The effects of multiple parallel universes of dark matter (dark sectors) on the accelerated expansion of the universe are studied. Collectively, these additional effects will lead to a new cosmological model. We had developed a numerical code on BBN to address the effects of such dark sectors on the abundances of all the light elements. We have studied the effect of degrees of freedom of dark-matter in the early universe on primordial abundances of light elements. The predicted abundances of light elements are compared with observed constraints to obtain bounds on the number of dark sectors, NDM. Comparison of the obtained results with the observations during the BBN epoch shows that the number of dark matter sectors are only loosely constrained, and the dark matter sectors are colder than the ordinary matter sectors. Also, we verified that the existence of parallel dark matter sectors with colder temperatures does not affect the constraints set by observations on the number of neutrino families, Nnu .
Physicians' psychophysiological stress reaction in medical communication of bad news: A critical literature review.

PubMed

Studer, Regina Katharina; Danuser, Brigitta; Gomez, Patrick

2017-10-01

Stress is a common phenomenon in medical professions. Breaking bad news (BBN) is reported to be a particularly distressing activity for physicians. Traditionally, the stress experienced by physicians when BBN was assessed exclusively using self-reporting. Only recently, the field of difficult physician-patient communication has used physiological assessments to better understand physicians' stress reactions. This paper's goals are to (a) review current knowledge about the physicians' psychophysiological stress reactions in BBN situations, (b) discuss methodological aspects of these studies and (c) suggest directions for future research. The seven studies identified all used scenarios with simulated patients but were heterogeneous with regard to other methodological aspects, such as the psychophysiological parameters, time points and durations assessed, comparative settings, and operationalisation of the communication scenarios. Despite this heterogeneity, all the papers reported increases in psychological and/or physiological activation when breaking bad news in comparison to control conditions, such as history taking or breaking good news. Taken together, the studies reviewed support the hypothesis that BBN is a psychophysiologically arousing and stressful task for medical professionals. However, much remains to be done. We suggest several future directions to advance the field. These include (a) expanding and refining the conceptual framework, (b) extending assessments to include more diverse physiological parameters, (c) exploring the modulatory effects of physicians' personal characteristics (e.g. level of experience), (d) comparing simulated and real-life physician-patient encounters and (e) combining physiological assessment with a discourse analysis of physician-patient communication. Copyright © 2017 Elsevier B.V. All rights reserved.
Peptide conjugated polymeric nanoparticles as a carrier for targeted delivery of docetaxel.

PubMed

Kulhari, Hitesh; Pooja, Deep; Shrivastava, Shweta; V G M, Naidu; Sistla, Ramakrishna

2014-05-01

The aim of this research work was to develop Bombesin peptide (BBN) conjugated, docetaxel loaded nanocarrier for the treatment of breast cancer. Docetaxel loaded nanoparticles (DNP) were prepared by solvent evaporation method using sodium cholate as surfactant. BBN was conjugated to DNP surface through covalent bonding. Both DNP and BBN conjugated DNP (BDNP) were characterized by various techniques such as dynamic light scattering, Fourier transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC) and thermogravimetric analysis. The particle diameter and zeta potential of BDNP were 136±3.95 nm and -10.8±2.7 mV, respectively. The change in surface charge and FTIR studies confirmed the formation of amide linkage between BBN and DNP. AFM analysis showed that nanoparticles were spherical in shapes. In nanoparticles, docetaxel was present in its amorphous form as confirmed by DSC and PXRD analysis and was stable during the thermal studies. The formulations showed the sustained release of DTX over the period of 120 h. During cellular toxicity assay in gastrin releasing peptide receptor positive breast cancer cells (MDA-MB-231), BDNP were found to be 12 times more toxic than pure DTX and Taxotere. The IC50 value for DTX, Taxotere, DNP and BDNP was >375, >375, 142.23 and 35.53 ng/ml, respectively. The above studies showed that Bombesin conjugated nanocarrier system could be a promising carrier for active targeting of anticancer drugs in GRP receptor over expressing cancer cells. Copyright © 2014 Elsevier B.V. All rights reserved.
Gold nanoparticles as physiological markers of urine internalization into urothelial cells in vivo

PubMed Central

Hudoklin, Samo; Zupančič, Daša; Makovec, Darko; Kreft, Mateja Erdani; Romih, Rok

2013-01-01

Background Urothelial bladder is the reservoir of urine and the urothelium minimizes the exchange of urine constituents with this tissue. Our aim was to test 1.9 nm biocompatible gold nanoparticles as a novel marker of internalization into the urothelial cells under physiological conditions in vivo. Methods We compared normal and neoplastic mice urothelium. Neoplastic lesions were induced by 0.05% N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN) in drinking water for 10 weeks. Nanoparticles, intravenously injected into normal and BBN-treated mice, were filtered through the kidneys and became constituents of the urine within 90 minutes after injection. Results Gold nanoparticles were densely accumulated in the urine, while their internalization into urothelial cells depended on the cell differentiation stage. In the terminally differentiated superficial urothelial cells of normal animals, nanoparticles were occasionally found in the endosomes, but not in the fusiform vesicles. Regions of exfoliated cells were occasionally found in the normal urothelium. Superficial urothelial cells located next to exfoliated regions contained gold nanoparticles in the endosomes and in the cytosol beneath the apical plasma membrane. The urothelium of BBN-treated animals developed fat hyperplasia with moderate dysplasia. The superficial cells of BBN-treated animals were partially differentiated as demonstrated by the lack of fusiform vesicles. These cells contained the gold nanoparticles distributed in the endosomes and throughout their cytosol. Conclusion Gold nanoparticles are a valuable marker to study urine internalization into urothelial cells in vivo. Moreover, they can be used as a sensitive marker of differentiation and functionality of urothelial cells. PMID:24143099
Study of the 2H(p,γ)3He reaction in the BBN energy range at LUNA

NASA Astrophysics Data System (ADS)

Trezzi, Davide; LUNA Collaboration

2018-01-01

Using Big Bang Nucleosynthesis with the recent cosmological parameters obtained by the Planck collaboration, a primordial deuterium abundance value D/H = (2.65 ± 0.07) × 10-5 is obtained. This one is a little bit in tension with astronomical observations on metal- poor damped Lyman alpha systems where D/H = (2.53 ± 0.04) × 105. In order to reduce the BBN calculation uncertainty, a measurement of the 2H(p,γ)3He cross section in the energy range 10-300 keV with a 3% accuracy is thus desirable. Thanks to the low background of the underground Gran Sasso Laboratories, and to the experience accumulated in more than twenty years of scientific activity, LUNA (Laboratory for Underground Nuclear Astrophysics) planned to measure the 2H(p,γ)3He fusion cross section at the BBN energy range in 2015-2016. A feasibility test of the measurement has been recently performed at LUNA. In this paper, the results obtained will be shown. Possible cosmological outcomes from the future LUNA data will be also discussed.
Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

PubMed Central

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-01

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006
Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

PubMed

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-08

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.
Weak scale from the maximum entropy principle

NASA Astrophysics Data System (ADS)

Hamada, Yuta; Kawai, Hikaru; Kawana, Kiyoharu

2015-03-01

The theory of the multiverse and wormholes suggests that the parameters of the Standard Model (SM) are fixed in such a way that the radiation of the S3 universe at the final stage S_rad becomes maximum, which we call the maximum entropy principle. Although it is difficult to confirm this principle generally, for a few parameters of the SM, we can check whether S_rad actually becomes maximum at the observed values. In this paper, we regard S_rad at the final stage as a function of the weak scale (the Higgs expectation value) vh, and show that it becomes maximum around vh = {{O}} (300 GeV) when the dimensionless couplings in the SM, i.e., the Higgs self-coupling, the gauge couplings, and the Yukawa couplings are fixed. Roughly speaking, we find that the weak scale is given by vh ˜ T_{BBN}2 / (M_{pl}ye5), where ye is the Yukawa coupling of electron, T_BBN is the temperature at which the Big Bang nucleosynthesis starts, and M_pl is the Planck mass.
Bayesian Estimation of Thermonuclear Reaction Rates for Deuterium+Deuterium Reactions

NASA Astrophysics Data System (ADS)

Gómez Iñesta, Á.; Iliadis, C.; Coc, A.

2017-11-01

The study of d+d reactions is of major interest since their reaction rates affect the predicted abundances of D, 3He, and 7Li. In particular, recent measurements of primordial D/H ratios call for reduced uncertainties in the theoretical abundances predicted by Big Bang nucleosynthesis (BBN). Different authors have studied reactions involved in BBN by incorporating new experimental data and a careful treatment of systematic and probabilistic uncertainties. To analyze the experimental data, Coc et al. used results of ab initio models for the theoretical calculation of the energy dependence of S-factors in conjunction with traditional statistical methods based on χ 2 minimization. Bayesian methods have now spread to many scientific fields and provide numerous advantages in data analysis. Astrophysical S-factors and reaction rates using Bayesian statistics were calculated by Iliadis et al. Here we present a similar analysis for two d+d reactions, d(d, n)3He and d(d, p)3H, that has been translated into a total decrease of the predicted D/H value by 0.16%.
Amide-to-triazole switch vs. in vivo NEP-inhibition approaches to promote radiopeptide targeting of GRPR-positive tumors.

PubMed

Maina, Theodosia; Kaloudi, Aikaterini; Valverde, Ibai E; Mindt, Thomas L; Nock, Berthold A

2017-09-01

Radiolabeled bombesin (BBN)-analogs have been proposed for diagnosis and therapy of gastrin-releasing peptide receptor (GRPR)-expressing tumors, such as prostate, breast and lung cancer. Metabolic stability represents a crucial factor for the success of this approach by ensuring sufficient delivery of circulating radioligand to tumor sites. The amide-to-triazole switch on the backbone of DOTA-PEG 4 -[Nle 14 ]BBN(7-14) (1) was reported to improve the in vitro stability of resulting 177 Lu-radioligands. On the other hand, in-situ inhibition of neutral endopeptidase (NEP) by coinjection of phosphoramidon (PA) was shown to significantly improve the in vivo stability and tumor uptake of biodegradable radiopeptides. We herein compare the impact of the two methods on the bioavailability and localization of 177 Lu-DOTA-PEG 4 -[Nle 14 ]BBN(7-14) analogs in GRPR-positive tumors in mice. The 1,4-disubstituted [1-3]-triazole was used to replace one (2: Gly 11 -His 12 ; 3: Ala 9 -Val 10 ) or two (4: Ala 9 -Val 10 and Gly 11 -His 12 ) peptide bonds in 1 (reference) and all compounds were labeled with 177 Lu. Each of [ 177 Lu]1-[ 177 Lu]4 was injected without (control) or with PA in healthy mice. Blood samples collected 5min post-injection (pi) were analyzed by HPLC. Biodistribution of [ 177 Lu]1-[ 177 Lu]4 was conducted in SCID mice bearing human prostate adenocarcinoma PC-3 xenografts at 4h pi. Groups of 4 animals were injected with radioligand, alone (controls), or with coinjection of PA, or of a mixture of PA and excess and [Tyr 4 ]BBN to determine GRPR-specificity of uptake (Block). The in vivo stability of the radioligands was: [ 177 Lu]1 (25% intact), [ 177 Lu]2 (45% intact), [ 177 Lu]3 (30% intact) and [ 177 Lu]4 (40% intact). By PA-coinjection these values notably increased to 90%-93%. Moreover, treatment with PA induced an impressive and GRPR-specific uptake of all radioligands in the PC-3 xenografts at 4h pi: [ 177 Lu]1: 4.7±0.4 to 24.8±4.9%ID/g; [ 177 Lu]2: 8.3±1.2 to 26.0±1.1%ID/g; [ 177 Lu]3: 6.6±0.4 to 21.3±4.4%ID/g; and [ 177 Lu]4: 4.8±1.6 to 13.7±3.8%ID/g. This study has shown that amide-to-triazole substitutions in 177 Lu-DOTA-PEG 4 -[Nle 14 ]BBN(7-14) induced minor effects on bioavailability and tumor uptake in mice models, whereas in-situ NEP-inhibition(s) by PA impressively improved in vivo profiles. Copyright © 2017 Elsevier Inc. All rights reserved.
Refined scenario of standard Big Bang nucleosynthesis allowing for nonthermal nuclear reactions in the primordial plasma

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

Voronchev, Victor T.; Nakao, Yasuyuki; Nakamura, Makoto

The standard scenario of big bang nucleosynthesis (BBN) is generalized to take into account nonthermal nuclear reactions in the primordial plasma. These reactions are naturally triggered in the BBN epoch by fast particles generated in various exoergic processes. It is found that, although such particles can appreciably enhance the rates of some individual reactions, their influence on the whole process of element production is not significant. The nonthermal corrections to element abundances are obtained to be 0.1% ({sup 3}H), -0.03% ({sup 7}Li), and 0.34 %-0.63% (CNO group).
Resonant Production of Sterile Neutrinos in the Early Universe

NASA Astrophysics Data System (ADS)

Gilbert, Lauren; Grohs, Evan; Fuller, George M.

2016-06-01

This study examines the cosmological impacts of a light resonantly produced sterile neutrino in the early universe. Such a neutrino could be produced through lepton number-driven Mikheyev-Smirnov-Wolfenstein (MSW) conversion of active neutrinos around big bang nucleosynthesis (BBN), resulting in a non-thermal spectrum of both sterile and electron neutrinos. During BBN, the neutron-proton ratio depends sensitively on the electron neutrino flux. If electron neutrinos are being converted to sterile neutrinos, this makes the n/p ratio a probe of possible new physics. We use observations of primordial Yp and D/H to place limits on this process.
Probing the BSM physics with CMB precision cosmology: an application to supersymmetry

NASA Astrophysics Data System (ADS)

Dalianis, Ioannis; Watanabe, Yuki

2018-02-01

The cosmic history before the BBN is highly determined by the physics that operates beyond the Standard Model (BSM) of particle physics and it is poorly constrained observationally. Ongoing and future precision measurements of the CMB observables can provide us with significant information about the pre-BBN era and hence possibly test the cosmological predictions of different BSM scenarios. Supersymmetry is a particularly motivated BSM theory and it is often the case that different superymmetry breaking schemes require different cosmic histories with specific reheating temperatures or low entropy production in order to be cosmologically viable. In this paper we quantify the effects of the possible alternative cosmic histories on the n s and r CMB observables assuming a generic non-thermal stage after cosmic inflation. We analyze TeV and especially multi-TeV super-symmetry breaking schemes assuming the neutralino and gravitino dark matter scenarios. We complement our analysis considering the Starobinsky R 2 inflation model to exemplify the improved CMB predictions that a unified description of the early universe cosmic evolution yields. Our analysis underlines the importance of the CMB precision measurements that can be viewed, to some extend, as complementary to the laboratory experimental searches for supersymmetry or other BSM theories.
Gravitino dark matter and the lithium primordial abundance within a pre-BBN modified expansion

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

Bailly, Sean, E-mail: sean.bailly@lapp.in2p3.fr

2011-03-01

We present supersymmetric scenarios with gravitino LSP and stau NLSP in the case of a non-standard model of cosmology with the addition of a dark component in the pre-BBN era. In the context of the standard model of cosmology, gravitino LSP has drawn quite some attention as it is a good candidate for dark matter. It is produced in scattering processes during reheating after inflation and from the decay of the stau. With a long lifetime, the stau decays during Big Bang Nucleosynthesis. It is strongly constrained by the abundance of light elements but can however address the known ''BBNmore » lithium problem''. It requires fairly massive staus m{sub τ-tilde}∼> 1TeV and puts an upper bound on the reheating temperature T{sub R} ≅ 10{sup 7} GeV which does not satisfy the requirements for thermal leptogenesis. For the non-standard cosmological scenario, the reheating temperature bound can be strongly relaxed T{sub R} >> 10{sup 9}GeV and the lithium-7 problem solved with a stau typical mass of m{sub τ-tilde} ∼ 600–700 GeV and down to ∼ 400GeV with a very important dark component that could enable possible production and detection at the LHC.« less

Selective binding of lectins to normal and neoplastic urothelium in rat and mouse bladder carcinogenesis models.

PubMed

Zupančič, Daša; Kreft, Mateja Erdani; Romih, Rok

2014-01-01

Bladder cancer adjuvant intravesical therapy could be optimized by more selective targeting of neoplastic tissue via specific binding of lectins to plasma membrane carbohydrates. Our aim was to establish rat and mouse models of bladder carcinogenesis to investigate in vivo and ex vivo binding of selected lectins to the luminal surface of normal and neoplastic urothelium. Male rats and mice were treated with 0.05 % N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN) in drinking water and used for ex vivo and in vivo lectin binding experiments. Urinary bladder samples were also used for paraffin embedding, scanning electron microscopy and immunofluorescence labelling of uroplakins. During carcinogenesis, the structure of the urinary bladder luminal surface changed from microridges to microvilli and ropy ridges and the expression of urothelial-specific glycoproteins uroplakins was decreased. Ex vivo and in vivo lectin binding experiments gave comparable results. Jacalin (lectin from Artocarpus integrifolia) exhibited the highest selectivity for neoplastic compared to normal urothelium of rats and mice. The binding of lectin from Amaranthus caudatus decreased in rat model and increased in mouse carcinogenesis model, indicating interspecies variations of plasma membrane glycosylation. Lectin from Datura stramonium showed higher affinity for neoplastic urothelium compared to the normal in rat and mouse model. The BBN-induced animal models of bladder carcinogenesis offer a promising approach for lectin binding experiments and further lectin-mediated targeted drug delivery research. Moreover, in vivo lectin binding experiments are comparable to ex vivo experiments, which should be considered when planning and optimizing future research.
Using Machine-Learned Bayesian Belief Networks to Predict Perioperative Risk of Clostridium Difficile Infection Following Colon Surgery

PubMed Central

Bilchik, Anton; Eberhardt, John; Kalina, Philip; Nissan, Aviram; Johnson, Eric; Avital, Itzhak; Stojadinovic, Alexander

2012-01-01

Background Clostridium difficile (C-Diff) infection following colorectal resection is an increasing source of morbidity and mortality. Objective We sought to determine if machine-learned Bayesian belief networks (ml-BBNs) could preoperatively provide clinicians with postoperative estimates of C-Diff risk. Methods We performed a retrospective modeling of the Nationwide Inpatient Sample (NIS) national registry dataset with independent set validation. The NIS registries for 2005 and 2006 were used for initial model training, and the data from 2007 were used for testing and validation. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes were used to identify subjects undergoing colon resection and postoperative C-Diff development. The ml-BBNs were trained using a stepwise process. Receiver operating characteristic (ROC) curve analysis was conducted and area under the curve (AUC), positive predictive value (PPV), and negative predictive value (NPV) were calculated. Results From over 24 million admissions, 170,363 undergoing colon resection met the inclusion criteria. Overall, 1.7% developed postoperative C-Diff. Using the ml-BBN to estimate C-Diff risk, model AUC is 0.75. Using only known a priori features, AUC is 0.74. The model has two configurations: a high sensitivity and a high specificity configuration. Sensitivity, specificity, PPV, and NPV are 81.0%, 50.1%, 2.6%, and 99.4% for high sensitivity and 55.4%, 81.3%, 3.5%, and 99.1% for high specificity. C-Diff has 4 first-degree associates that influence the probability of C-Diff development: weight loss, tumor metastases, inflammation/infections, and disease severity. Conclusions Machine-learned BBNs can produce robust estimates of postoperative C-Diff infection, allowing clinicians to identify high-risk patients and potentially implement measures to reduce its incidence or morbidity. PMID:23611947
A Framework for Assessment of Aviation Safety Technology Portfolios

NASA Technical Reports Server (NTRS)

Jones, Sharon M.; Reveley, Mary S.

2014-01-01

The programs within NASA's Aeronautics Research Mission Directorate (ARMD) conduct research and development to improve the national air transportation system so that Americans can travel as safely as possible. NASA aviation safety systems analysis personnel support various levels of ARMD management in their fulfillment of system analysis and technology prioritization as defined in the agency's program and project requirements. This paper provides a framework for the assessment of aviation safety research and technology portfolios that includes metrics such as projected impact on current and future safety, technical development risk and implementation risk. The paper also contains methods for presenting portfolio analysis and aviation safety Bayesian Belief Network (BBN) output results to management using bubble charts and quantitative decision analysis techniques.
Improving Perinatology Residents' Skills in Breaking Bad News: A Randomized Intervention Study.

PubMed

Setubal, Maria Silvia Vellutini; Antonio, Maria Ângela Reis Goes Monteiro; Amaral, Eliana Martorano; Boulet, John

2018-03-01

Breaking bad news (BBN) is particularly difficult in perinatology. Previous research has shown that BBN skills can be learned and improved when taught and practiced. This project evaluated whether a structured training session would enhance perinatology residents' skills in BBN. This was a randomized controlled intervention study with year 1 to 4 Perinatology residents from a medical school in Brazil, during the 2014/15 school year. A total of 61 out of 100 (61%) eligible residents volunteered to a structured training program involving communicating a perinatal loss to a simulated patient (SP) portraying the mother followed by the SP's immediate feedback, both video recorded. Later, residents were randomly assigned to BBN training based on a setting, perception, invitation, knowledge, emotion and summary (SPIKES) strategy with video reviews (intervention) or no training (control group). All residents returned for a second simulation with the same SP blinded to the intervention and portraying a similar case. Residents' performances were then evaluated by the SP with a checklist. The statistical analysis included a repeated measures analysis of covariance (RM-ANCOVA). Complementarily, the residents provided their perceptions about the simulation with feedback activities. Fifty-eight residents completed the program. The simulations lasted on average 12 minutes, feedback 5 minutes and SPIKES training between 1h and 2h30m. There was no significant difference in the residents' performances according to the SPs' evaluations ( p = 0.55). The participants rated the simulation with feedback exercises highly. These educational activities might have offset SPIKES training impact. The SPIKES training did not significantly impact the residents' performance. The residents endorsed the simulation with feedback as a useful training modality. Further research is needed to determine which modality is more effective. Thieme Revinter Publicações Ltda Rio de Janeiro, Brazil.
A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

PubMed

Hossain, Moinul; Muromachi, Yasunori

2012-03-01

The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.
Developing a dimensional model for successful cognitive and emotional aging.

PubMed

Vahia, Ipsit V; Thompson, Wesley K; Depp, Colin A; Allison, Matthew; Jeste, Dilip V

2012-04-01

There is currently a lack of consensus on the definition of successful aging (SA) and existing implementations have omitted constructs associated with SA. We used empirical methods to develop a dimensional model of SA that incorporates a wider range of associated variables, and we examined the relationship among these components using factor analysis and Bayesian Belief Nets. We administered a successful aging questionnaire comprising several standardized measures related to SA to a sample of 1948 older women enrolled in the San Diego site of the Women's Health Initiative study. The SA-related variables we included in the model were self-rated successful aging, depression severity, physical and emotional functioning, optimism, resilience, attitude towards own aging, self-efficacy, and cognitive ability. After adjusting for age, education and income, we fitted an exploratory factor analysis model to the SA-related variables and then, in order to address relationships among these factors, we computed a Bayesian Belief Net (BBN) using rotated factor scores. The SA-related variables loaded onto five factors. Based on the loading, we labeled the factors as follows: self-rated successful aging, cognition, psychosocial protective factors, physical functioning, and emotional functioning. In the BBN, self-rated successful aging emerged as the primary downstream factor and exhibited significant partial correlations with psychosocial protective factors, physical/general status and mental/emotional status but not with cognitive ability. Our study represents a step forward in developing a dimensional model of SA. Our findings also point to a potential role for psychiatry in improving successful aging by managing depressive symptoms and developing psychosocial interventions to improve self-efficacy, resilience, and optimism.
Signatures of a hidden cosmic microwave background.

PubMed

Jaeckel, Joerg; Redondo, Javier; Ringwald, Andreas

2008-09-26

If there is a light Abelian gauge boson gamma' in the hidden sector its kinetic mixing with the photon can produce a hidden cosmic microwave background (HCMB). For meV masses, resonant oscillations gamma<-->gamma' happen after big bang nucleosynthesis (BBN) but before CMB decoupling, increasing the effective number of neutrinos Nnu(eff) and the baryon to photon ratio, and distorting the CMB blackbody spectrum. The agreement between BBN and CMB data provides new constraints. However, including Lyman-alpha data, Nnu(eff) > 3 is preferred. It is tempting to attribute this effect to the HCMB. The interesting parameter range will be tested in upcoming laboratory experiments.
Inhibition of urinary bladder tumors induced by N-butyl-N-(4-hydroxybutyl)-nitrosamine in rats by green tea.

PubMed

Sato, D

1999-02-01

Recently, the anticarcinogenic effects of green tea have been studied in sites other than the urinary tract. The present study examined the inhibition by green tea of vesical tumors induced in rats by N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN). In the first series of experiments, 0.05% BBN was added to the drinking water of rats and remained present for 5 weeks. In one experiment, six groups of animals received either tap water, green tea, matcha, hojicha, oolong tea or black tea from week 6. In a second experiment, three groups of rats received either tap water, green tea extract or powdered green tea mixed into a pellet diet from week 6. In a third experiment, five groups of rats were fed a pellet diet with addition of either 0, 0.15, 1.5 or 3.0% powdered green tea from week 6. All rats were killed and examined at 40 weeks. Green tea, particularly green tea leaves, dose-dependently inhibited the growth of BBN-induced urinary bladder tumors when given after the carcinogen. Green tea may inhibit bladder tumor growth.
Neutrino energy transport in weak decoupling and big bang nucleosynthesis

DOE PAGES

Grohs, Evan Bradley; Paris, Mark W.; Kishimoto, Chad T.; ...

2016-04-21

In this study, we calculate the evolution of the early universe through the epochs of weak decoupling, weak freeze-out and big bang nucleosynthesis (BBN) by simultaneously coupling a full strong, electromagnetic, and weak nuclear reaction network with a multienergy group Boltzmann neutrino energy transport scheme. The modular structure of our code provides the ability to dissect the relative contributions of each process responsible for evolving the dynamics of the early universe in the absence of neutrino flavor oscillations. Such an approach allows a detailed accounting of the evolution of the νe, ν¯e, νμ, ν¯μ, ντ, ν¯τ energy distribution functions alongsidemore » and self-consistently with the nuclear reactions and entropy/heat generation and flow between the neutrino and photon/electron/positron/baryon plasma components. This calculation reveals nonlinear feedback in the time evolution of neutrino distribution functions and plasma thermodynamic conditions (e.g., electron-positron pair densities), with implications for the phasing between scale factor and plasma temperature; the neutron-to-proton ratio; light-element abundance histories; and the cosmological parameter N eff. We find that our approach of following the time development of neutrino spectral distortions and concomitant entropy production and extraction from the plasma results in changes in the computed value of the BBN deuterium yield. For example, for particular implementations of quantum corrections in plasma thermodynamics, our calculations show a 0.4% increase in deuterium. These changes are potentially significant in the context of anticipated improvements in observational and nuclear physics uncertainties.« less
Neutrino energy transport in weak decoupling and big bang nucleosynthesis

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

Grohs, Evan Bradley; Paris, Mark W.; Kishimoto, Chad T.

In this study, we calculate the evolution of the early universe through the epochs of weak decoupling, weak freeze-out and big bang nucleosynthesis (BBN) by simultaneously coupling a full strong, electromagnetic, and weak nuclear reaction network with a multienergy group Boltzmann neutrino energy transport scheme. The modular structure of our code provides the ability to dissect the relative contributions of each process responsible for evolving the dynamics of the early universe in the absence of neutrino flavor oscillations. Such an approach allows a detailed accounting of the evolution of the νe, ν¯e, νμ, ν¯μ, ντ, ν¯τ energy distribution functions alongsidemore » and self-consistently with the nuclear reactions and entropy/heat generation and flow between the neutrino and photon/electron/positron/baryon plasma components. This calculation reveals nonlinear feedback in the time evolution of neutrino distribution functions and plasma thermodynamic conditions (e.g., electron-positron pair densities), with implications for the phasing between scale factor and plasma temperature; the neutron-to-proton ratio; light-element abundance histories; and the cosmological parameter N eff. We find that our approach of following the time development of neutrino spectral distortions and concomitant entropy production and extraction from the plasma results in changes in the computed value of the BBN deuterium yield. For example, for particular implementations of quantum corrections in plasma thermodynamics, our calculations show a 0.4% increase in deuterium. These changes are potentially significant in the context of anticipated improvements in observational and nuclear physics uncertainties.« less
The Primordial Deuterium Abundance of the Most Metal-poor Damped Lyman-α System

NASA Astrophysics Data System (ADS)

Cooke, Ryan J.; Pettini, Max; Nollett, Kenneth M.; Jorgenson, Regina

2016-10-01

We report the discovery and analysis of the most metal-poor damped Lyα (DLA) system currently known, which also displays the Lyman series absorption lines of neutral deuterium. The average [O/H] abundance of this system is [O/H] = -2.804 ± 0.015, which includes an absorption component with [O/H] = -3.07 ± 0.03. Despite the unfortunate blending of many weak D I absorption lines, we report a precise measurement of the deuterium abundance of this system. Using the six highest-quality and self-consistently analyzed measures of D/H in DLAs, we report tentative evidence for a subtle decrease of D/H with increasing metallicity. This trend must be confirmed with future high-precision D/H measurements spanning a range of metallicity. A weighted mean of these six independent measures provides our best estimate of the primordial abundance of deuterium, 105 (D/H)P = 2.547 ± 0.033 ({{log}}10 {{{(D/H)}}}{{P}}=-4.5940+/- 0.0056). We perform a series of detailed Monte Carlo calculations of Big Bang nucleosynthesis (BBN) that incorporate the latest determinations of several key nuclear reaction cross-sections, and propagate their associated uncertainty. Combining our measurement of (D/H)P with these BBN calculations yields an estimate of the cosmic baryon density, 100 ΩB,0 h 2(BBN) = 2.156 ± 0.020, if we adopt the most recent theoretical determination of the d{(p,γ )}3{He} reaction rate. This measure of ΩB,0 h 2 differs by ˜2.3σ from the Standard Model value estimated from the Planck observations of the cosmic microwave background. Using instead a d{(p,γ )}3{He} reaction rate that is based on the best available experimental cross-section data, we estimate 100 ΩB,0 h 2(BBN) = 2.260 ± 0.034, which is in somewhat better agreement with the Planck value. Forthcoming measurements of the crucial d{(p,γ )}3{He} cross-section may shed further light on this discrepancy. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile (VLT program ID: 093.A-0016(A)), and at the W.M. Keck Observatory which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W.M. Keck Foundation.
D-brane disformal coupling and thermal dark matter

NASA Astrophysics Data System (ADS)

Dutta, Bhaskar; Jimenez, Esteban; Zavala, Ivonne

2017-11-01

Conformal and disformal couplings between a scalar field and matter occur naturally in general scalar-tensor theories. In D-brane models of cosmology and particle physics, these couplings originate from the D-brane action describing the dynamics of its transverse (the scalar) and longitudinal (matter) fluctuations, which are thus coupled. During the post-inflationary regime and before the onset of big bang nucleosynthesis (BBN), these couplings can modify the expansion rate felt by matter, changing the predictions for the thermal relic abundance of dark matter particles and thus the annihilation rate required to satisfy the dark matter content today. We study the D-brane-like conformal and disformal couplings effect on the expansion rate of the Universe prior to BBN and its impact on the dark matter relic abundance and annihilation rate. For a purely disformal coupling, the expansion rate is always enhanced with respect to the standard one. This gives rise to larger cross sections when compared to the standard thermal prediction for a range of dark matter masses, which will be probed by future experiments. In a D-brane-like scenario, the scale at which the expansion rate enhancement occurs depends on the string coupling and the string scale.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Bae, Kyu Jung; Baer, Howard; Serce, Hasan

Supersymmetric models with radiatively-driven electroweak naturalness require light higgsinos of mass ∼ 100–300 GeV . Naturalness in the QCD sector is invoked via the Peccei-Quinn (PQ) axion leading to mixed axion-higgsino dark matter. The SUSY DFSZ axion model provides a solution to the SUSY μ problem and the Little Hierarchy μ|| m{sub 3/2} may emerge as a consequence of a mismatch between PQ and hidden sector mass scales. The traditional gravitino problem is now augmented by the axino and saxion problems, since these latter particles can also contribute to overproduction of WIMPs or dark radiation, or violation of BBN constraints. We computemore » regions of the T{sub R} vs. m{sub 3/2} plane allowed by BBN, dark matter and dark radiation constraints for various PQ scale choices f{sub a}. These regions are compared to the values needed for thermal leptogenesis, non-thermal leptogenesis, oscillating sneutrino leptogenesis and Affleck-Dine leptogenesis. The latter three are allowed in wide regions of parameter space for PQ scale f{sub a∼} 10{sup 10}–10{sup 12} GeV which is also favored by naturalness: f{sub a} ∼ √μM{sub P}/λ{sub μ} ∼ 10{sup 10}–10{sup 12} GeV . These f{sub a} values correspond to axion masses somewhat above the projected ADMX search regions.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Bae, Kyu Jung; Department of Physics, University of Tokyo,Bunkyo-ku, Tokyo 113-0033; Baer, Howard

Supersymmetric models with radiatively-driven electroweak naturalness require light higgsinos of mass ∼100–300 GeV. Naturalness in the QCD sector is invoked via the Peccei-Quinn (PQ) axion leading to mixed axion-higgsino dark matter. The SUSY DFSZ axion model provides a solution to the SUSY μ problem and the Little Hierarchy μ≪m{sub 3/2} may emerge as a consequence of a mismatch between PQ and hidden sector mass scales. The traditional gravitino problem is now augmented by the axino and saxion problems, since these latter particles can also contribute to overproduction of WIMPs or dark radiation, or violation of BBN constraints. We compute regionsmore » of the T{sub R} vs. m{sub 3/2} plane allowed by BBN, dark matter and dark radiation constraints for various PQ scale choices f{sub a}. These regions are compared to the values needed for thermal leptogenesis, non-thermal leptogenesis, oscillating sneutrino leptogenesis and Affleck-Dine leptogenesis. The latter three are allowed in wide regions of parameter space for PQ scale f{sub a}∼10{sup 10}–10{sup 12} GeV which is also favored by naturalness: f{sub a}∼√(μM{sub P}/λ{sub μ})∼10{sup 10}–10{sup 12} GeV. These f{sub a} values correspond to axion masses somewhat above the projected ADMX search regions.« less
Theranostic Prospects of Gastrin-Releasing Peptide Receptor-Radioantagonists in Oncology.

PubMed

Maina, Theodosia; Nock, Berthold A; Kulkarni, Harshad; Singh, Aviral; Baum, Richard P

2017-07-01

Gastrin-releasing peptide receptors (GRPRs) represent attractive targets for cancer diagnosis and therapy owing to their overexpression in widespread human tumors. Bombesin (BBN) analogues coupled to suitable chelators for stable radiometal binding have been proposed for diagnostic imaging and radionuclide therapy (theranostics) of GRPR-positive tumors. Recently, interest has shifted from BBN-like receptor agonists to GRPR-radioantagonists, because radioantagonists do not induce adverse effects after injection to patients and display superior pharmacokinetic in vivo profiles. Thus, they seem more advantageous for clinical use compared to agonists. Newer developments highlighting the theranostic potential of GRPR-radioantagonists in cancer patient management are presented herein. Copyright © 2017 Elsevier Inc. All rights reserved.
The Cosmological Lithium Problem and the Measurement of the 7Be(n, α) Reaction at n_TOF-CERN

NASA Astrophysics Data System (ADS)

Musumarra, Agatino; Barbagallo, Massimo

A possible explanation of the so-called "Cosmological Lithium Problem", an important unsolved problem in Nuclear Astrophysics, involves large systematic uncertainties in the cross-sections of reactions leading to the destruction of 7Be during the Big-Bang Nucleosynthesis (BBN). Among these reactions, the 7Be(n, α) is the most uncertain. So far, only a single measurement with thermal neutrons has been performed. Therefore, BBN calculations had to rely on rather uncertain theoretical extrapolations. The short half-life of 7Be (53.29 d) and the low cross section have prevented, up to now, to obtain experimental data at keV neutron energies typical for BBN studies. We have measured for the first time at n_TOF the 7Be(n, α) reaction in a wide neutron energy range, from thermal up to 10 keV. This measurement has been performed, at the new beam line (EAR2) of the Neutron-Time-Of-Flight facility n_TOF at CERN. The two α-particles, emitted back-to-back in the reaction, have been detected by mean of sandwiches of silicon detectors and, by exploiting the coincidence technique, we were able to suppress the large γ and n-induced background. The 7Be isotope production and purification has been performed by PSI-Zurich Switzerland.
BBN constraints on MeV-scale dark sectors. Part I. Sterile decays

NASA Astrophysics Data System (ADS)

Hufnagel, Marco; Schmidt-Hoberg, Kai; Wild, Sebastian

2018-02-01

We study constraints from Big Bang Nucleosynthesis on inert particles in a dark sector which contribute to the Hubble rate and therefore change the predictions of the primordial nuclear abundances. We pay special attention to the case of MeV-scale particles decaying into dark radiation, which are neither fully relativistic nor non-relativistic during all temperatures relevant to Big Bang Nucleosynthesis. As an application we discuss the implications of our general results for models of self-interacting dark matter with light mediators.
Decision Analysis Tools for Volcano Observatories

NASA Astrophysics Data System (ADS)

Hincks, T. H.; Aspinall, W.; Woo, G.

2005-12-01

Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.
Study of the possibility of solving cosmological lithium problem in an accelerator experiment

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

Bystritsky, V. M., E-mail: bystvm@jinr.ru; Varlachev, V. A.; Dudkin, G. N.

Within the standar dmodel of Big Bang Nucleosynthesis (BBN), there is a cosmological lithium problem, which consists in a substantial difference between calculated data on the abundances of the isotopes {sup 6}Li and {sup 7}Li and those that were found from observational astronomy. An attempt at measuring the cross section for the main 6Li production reaction {sup 2}H({sup 4}He, γ){sup 6}Li induced by the interaction of {sup 4}He{sup +} ions with deuterons at collision energies less than the lower boundary of the BBN energy range was made in the present study. Upper limits on the cross sections for the reactionmore » in question were set.« less
CHEMOPREVENTIVE EFFICACY OF NAPROXEN AND NO-NAPROXEN IN RODENT MODELS OF COLON, URINARY BLADDER, AND MAMMARY CANCERS

PubMed Central

Steele, Vernon E.; Rao, Chinthalapally V.; Zhang, Yuting; Patlolla, Jagan; Boring, Daniel; Kopelovich, Levy; Juliana, M. Margaret; Grubbs, Clinton J.; Lubet, Ronald A.

2009-01-01

Nonsteroidal anti-inflammatory drugs (NSAIDs) have been highly effective in preventing colon, urinary bladder, and skin cancer preclinically; and also in clinical trials of colon adenoma formation. However, certain NSAIDs cause gastrointestinal (GI) ulceration and may increase cardiovascular (CV) events. Naproxen appears to cause the lowest CV events of the common NSAIDs other than aspirin. NO-naproxen was tested based on the finding that adding a nitric oxide (NO) group to NSAIDs may help alleviate GI toxicity. In the azoxymethane (AOM)-induced rat colon aberrant crypt foci (ACF) model, naproxen administered at 200 and 400 ppm in the diet reduced mean ACFs in the colon by about 45–60%, respectively. NO-naproxen was likewise administered in the diet at roughly equimolar doses (300 and 600 ppm), and reduced total ACF by 20–40%, respectively. In the hydroxybutyl (butyl) nitrosamine (OH-BBN) rat urinary bladder cancer model, NO-naproxen was given at 183 ppm or 550 ppm in the diet, and naproxen at 128 ppm. The NO-naproxen groups had 77% and 73% decreases, respectively, in the development of large urinary bladder tumors, while the 128 ppm naproxen group also showed a strong decrease (69%). If treatments were started three months after OH-BBN, NO-naproxen (550 ppm) and naproxen (400 ppm) were also highly effective (86–94% decreases). In the methylnitrosourea (MNU)-induced mammary cancer model in rats, NO-naproxen and naproxen showed non-significant inhibitions (12 and 24%) at 550 and 400 ppm, respectively. These data show that both naproxen and NO-naproxen are effective agents against urinary bladder and colon, but not mammary, carcinogenesis. PMID:19892664

BBN technical memorandum W1291 infrasound model feasibility study

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

Farrell, T., BBN Systems and Technologies

1998-05-01

The purpose of this study is to determine the need and level of effort required to add existing atmospheric databases and infrasound propagation models to the DOE`s Hydroacoustic Coverage Assessment Model (HydroCAM) [1,2]. The rationale for the study is that the performance of the infrasound monitoring network will be an important factor for both the International Monitoring System (IMS) and US national monitoring capability. Many of the technical issues affecting the design and performance of the infrasound network are directly related to the variability of the atmosphere and the corresponding uncertainties in infrasound propagation. It is clear that the studymore » of these issues will be enhanced by the availability of software tools for easy manipulation and interfacing of various atmospheric databases and infrasound propagation models. In addition, since there are many similarities between propagation in the oceans and in the atmosphere, it is anticipated that much of the software infrastructure developed for hydroacoustic database manipulation and propagation modeling in HydroCAM will be directly extendible to an infrasound capability. The study approach was to talk to the acknowledged domain experts in the infrasound monitoring area to determine: 1. The major technical issues affecting infrasound monitoring network performance. 2. The need for an atmospheric database/infrasound propagation modeling capability similar to HydroCAM. 3. The state of existing infrasound propagation codes and atmospheric databases. 4. A recommended approach for developing the required capabilities. A list of the people who contributed information to this study is provided in Table 1. We also relied on our knowledge of oceanographic and meteorological data sources to determine the availability of atmospheric databases and the feasibility of incorporating this information into the existing HydroCAM geographic database software. This report presents a summary of the need for an integrated infrasound modeling capability in Section 2.0. Section 3.0 provides a recommended approach for developing this capability in two stages; a basic capability and an extended capability. This section includes a discussion of the available static and dynamic databases, and the various modeling tools which are available or could be developed under such a task. The conclusions and recommendations of the study are provided in Section 4.0.« less
Lack of Promoting Effects of α‐Linolenic, Linoleic or Palmitic Acid on Urinary Bladder Carcinogenesis in Rats

PubMed Central

Mori, Satoru; Chen, Tianxin; Murai, Takashi; Fukushima, Shoji

1995-01-01

Potential promoting effects of α‐linolenic, linoleic and palmitic acids were investigated in a two‐stage urinary bladder carcinogenesis model. In experiment 1, male F344 rats were given 0.05% N‐butyl‐N‐(4‐hydroxybutyl)nitrosainine (BBN) in their drinking water for 4 weeks and then basal diet containing 10%α‐linolenic, 10% linoleic or 10% palmitic acid along with 0.2% butylated hydroxyanisole (BHA) as an antioxidant for 24 weeks. The development of tumors in the urinary bladder was not increased by treatment with any of the fatty acids. In experiment 2, male F344 rats were given 10%α‐linolenic, 10% linoleic or 10% palmitic acid along with 0.2% BHA in their diet for 8 weeks without prior BBN treatment. The administration of fatty acids was not associated with any increase in the 5‐bromo‐2′‐deoxyuridine labeling index of the urinary bladder epithelium. Serum and/or urine fatty acid Ievels increased in the cases of α‐linolenic and linoleic acid treatments, but not with palmitic acid. Under the present experimental conditions neither the two polyunsaturated nor the one saturated fatty acid exerted any promoting effect on urinary bladder carcinogenesis. PMID:7622416
Trojan Horse cross section measurements and their impact on primordial nucleosynthesis

NASA Astrophysics Data System (ADS)

Pizzone, R. G.; Spartá, R.; Bertulani, C.; Spitaleri, C.; La Cognata, M.; Lamia, L.; Mukhamedzhanov, A.; Tumino, A.

2018-01-01

Big Bang Nucleosynthesis (BBN) nucleosynthesis requires several nuclear physics inputs and, among them, an important role is played by nuclear reaction rates. They are among the most important input for a quantitative description of the early Universe. An up-to-date compilation of direct cross sections of d(d,p)t, d(d,n)3He and 3He(d,p)4He reactions is given, being these ones among the most uncertain bare-nucleus cross sections. An intense experimental effort has been carried on in the last decade to apply the Trojan Horse Method (THM) to study reactions of relevance for the BBN and measure their astrophysical S(E)-factor. The result of these recent measurements is reviewed and compared with the available direct data. The reaction rates and the relative error for the four reactions of interest are then numerically calculated in the temperature ranges of relevance for BBN (0.01
Direct measurement of the 7Be(n, α)4 He reaction cross sections for the cosmological Li problem

NASA Astrophysics Data System (ADS)

Kawabata, Takahiro; Fujikawa, Yuki; Furuno, Tatsuya; Goto, Tatsuya; Hashimoto, Toshikazu; Ichikawa, Masaya; Itoh, Makoto; Iwasa, Naohito; Kanada-En'yo, Yoshiko; Koshikawa, Ami; Kubono, Shigeru; Miyawaki, Eisuke; Mizuno, Masatoshi; Mizutani, Keigo; Morimoto, Takahiro; Murata, Motoki; Nanamura, Takuya; Nishimura, Shunji; Nanamura, Takuya; Okamoto, Shintaro; Sakaguchi, Yuichi; Sakata, Itsushi; Sakaue, Akane; Sawada, Ryo; Shikata, Yuki; Takahashi, Yu; Takechi, Daiki; Takeda, Tomoya; Takimoto, Chisato; Tsumura, Miho; Watanabe, Ken; Yoshida, Sota

2017-11-01

The cross sections of the 7Be(n, α)4He reaction for p-wave neutrons were experimentally determined at Ec.m. = 0.20-0.81 MeV close to the Big Bang nucleosynthesis (BBN) energy window for the first time on the basis of the detailed balance principle by measuring the time-reverse reaction. The obtained cross sections are much larger than the cross sections for s-wave neutrons inferred from the recent measurement at the n_TOF facility in CERN, but significantly smaller than the theoretical estimation widely used in the BBN calculations. The present results suggest the 7Be(n, α)4 He reaction rate is not large enough to solve the cosmological lithium problem
Measurement of the cross section for the 4He(α, n)7Be reaction as a possible solution to the cosmological lithium problem

NASA Astrophysics Data System (ADS)

Kawabata, T.; Furuno, T.; Ichikawa, M.; Iwasa, N.; Kanada-En'yo, Y.; Koshikawa, A.; Kubono, S.; Miyawaki, E.; Morimoto, T.; Murata, M.; Nanamura, T.; Nishimura, S.; Shikata, Y.; Takahashi, Y.; Takeda, T.; Tsumura, M.; Watanabe, K.

2017-06-01

The cross section for the 4He(α,n)7Be reaction was measured at low energies between Eα = 38.50 and 39.64 MeV motivated by the cosmological lithium problem. On the basis of the detailed balance principle, the cross section for the 7Be(n,α)4He reaction was obtained at Ec.m. = 0.20-0.81 MeV close to the Big Bang nucleosynthesis (BBN) energy window for the first time. The obtained cross sections are significantly smaller than the theoretical estimation widely used in the BBN calculations. The present results suggest the 7Be(n,α)4He reaction rate is not large enough to solve the cosmological lithium problem.
Study of the 2H(p,γ)3He reaction in the Big Bang Nucleosynthesis energy range at LUNA

NASA Astrophysics Data System (ADS)

Mossa, Viviana

2018-01-01

Deuterium is the first nucleus produced in the Universe, whose accumulation marks the beginning of the so called Big Bang Nucleosynthesis (BBN). Its primordial abundance is very sensitive to some cosmological parameters like the baryon density and the number of the neutrino families. Presently the main obstacle to an accurate theoretical deuterium abundance evaluation is due to the poor knowledge of the 2H(p,γ)3He cross section at BBN energies. The aim of the present work is to describe the experimental approach proposed by the LUNA collaboration, whose goal is to measure, with unprecedented precision, the total and the differential cross section of the reaction in the 30 < Ec.m. [keV] < 300 energy range.
Primordial nucleosynthesis and neutrino physics

NASA Astrophysics Data System (ADS)

Smith, Christel Johanna

We study primordial nucleosynthesis abundance yields for assumed ranges of cosmological lepton numbers, sterile neutrino mass-squared differences and active-sterile vacuum mixing angles. We fix the baryon-to-photon ratio at the value derived from the cosmic microwave background (CMB) data and then calculate the deviation of the 2 H, 4 He, and 7 Li abundance yields from those expected in the zero lepton number(s), no-new-neutrino-physics case. We conclude that high precision (< 5% error) measurements of the primordial 2 H abundance from, e.g., QSO absorption line observations coupled with high precision (< 1% error) baryon density measurements from the CMB could have the power to either: (1) reveal or rule out the existence of a light sterile neutrino if the sign of the cosmological lepton number is known; or (2) place strong constraints on lepton numbers, sterile neutrino mixing properties and resonance sweep physics. Similar conclusions would hold if the primordial 4 He abundance could be determined to better than 10%. We have performed new Big Bang Nucleosynthesis calculations which employ arbitrarily-specified, time-dependent neutrino and antineutrino distribution functions for each of up to four neutrino flavors. We self-consistently couple these distributions to the thermodynamics, the expansion rate and scale factor-time/temperature relationship, as well as to all relevant weak, electromagnetic, and strong nuclear reaction processes in the early universe. With this approach, we can treat any scenario in which neutrino or antineutrino spectral distortion might arise. These scenarios might include, for example, decaying particles, active-sterile neutrino oscillations, and active-active neutrino oscillations in the presence of significant lepton numbers. Our calculations allow lepton numbers and sterile neutrinos to be constrained with observationally-determined primordial helium and deuterium abundances. We have modified a standard BBN code to perform these calculations and have made it available to the community. We have applied a fully relativistic Coulomb wave correction to the weak reactions in the full Kawano/Wagoner Big Bang Nucleosynthesis (BBN) code. We have also added the zero temperature radiative correction. We find that using this higher accuracy Coulomb correction results in good agreement with previous work, giving only a modest ˜ 0.04% increase in helium mass fraction over correction prescriptions applied previously in BBN calculations. We have calculated the effect of these corrections on other light element abundance yields in BBN and we have studied these yields as functions of electron neutrino lepton number. This has allowed insights into the role of the Coulomb correction in the setting of the neutron-to-proton ratio during the BBN epoch. We find that the lepton capture processes' contributions to this ratio are only second order in the Coulomb correction.
Synthesis and exploration of novel radiolabeled bombesin peptides for targeting receptor positive tumor.

PubMed

De, Kakali; Banerjee, Indranil; Sinha, Samarendu; Ganguly, Shantanu

2017-03-01

Increasing evidence of peptide receptor overexpression in various cancer cells, warrant the development of receptor specific radiolabeled peptides for molecular imaging and therapy in nuclear medicine. Gastrin-releasing-peptide (GRP) receptor, are overexpressed in a variety of human cancer cells. The present study report the synthesis and biological evaluation of new bombesin (BBN) analogs, HYNIC-Asp-[Phe 13 ]BBN(7-13)-NH-CH 2 -CH 2 -CH3:BA1, HYNIC-Pro-[Tyr 13 Met 14 ]BBN(7-14)NH 2 :BA2 as prospective tumor imaging agent with compare to BBN(7-14)NH 2 :BS as standard. The pharmacophores were radiolabeled in high yields with 99m Tc, characterized for their stability in serum and saline, cysteine/histidine and were found to be substantially stable. Internalization/externalization and receptor binding studies were assessed using MDA-MB-231 cells and showed high receptor binding-affinity and favourable internalization. Fluorescence studies revealed that BA1 changed the morphology of the cells and could localize in the nucleus more effectively than BA2/BS. Cell-viability studies displayed substantial antagonistic and nuclear-internalization effect of BA1. BA1 also exhibited antiproliferative effect on MDA-MB-231 cell by inducing apoptosis. In vivo behaviour of the radiopeptides was evaluated in GRP receptor positive tumor bearing mice. The 99m Tc-BA1/ 99m Tc-BA2 demonstrated rapid blood/urinary clearance through the renal pathway and comparatively more significant tumor uptake image and favourable tumor-to-non-target ratios provided by 99m Tc-BA1. The specificity of the in vivo uptake was confirmed by co-injection with BS. Moreover, 99m Tc-BA1 provided a much clearer tumor image in scintigraphic studies than others. Thus the combination of favourable in vitro and in vivo properties renders BA1 as more potential antagonist bombesin-peptide for targeting GRP-receptor positive tumor. These properties are encouraging to carry out further experiments for non-invasive receptor targeting potential diagnostinc and therapeutic agent for tumors. Copyright © 2017 Elsevier Inc. All rights reserved.
Fluorescent imaging of high-grade bladder cancer using a specific antagonist for chemokine receptor CXCR4.

PubMed

Nishizawa, Koji; Nishiyama, Hiroyuki; Oishi, Shinya; Tanahara, Noriko; Kotani, Hirokazu; Mikami, Yoshiki; Toda, Yoshinobu; Evans, Barry J; Peiper, Stephen C; Saito, Ryoichi; Watanabe, Jun; Fujii, Nobutaka; Ogawa, Osamu

2010-09-01

We previously reported that the expression of CXC chemokine receptor-4 (CXCR4) was upregulated in invasive bladder cancers and that the small peptide T140 was a highly sensitive antagonist for CXCR4. In this study, we identified that CXCR4 expression was induced in high-grade superficial bladder tumors, including carcinoma in situ and invasive bladder tumors. To visualize the bladder cancer cells using urinary sediments from the patients and chemically induced mouse bladder cancer model, a novel fluorescent CXCR4 antagonist TY14003 was developed, that is a T140 derivative. TY14003 could label bladder cancer cell lines expressing CXCR4, whereas negative-control fluorescent peptides did not label them. When labeling urinary sediments from patients with invasive bladder cancer, positive-stained cells were identified in all patients with bladder cancer and positive urine cytology but not in controls. Although white blood cells in urine were also labeled with TY14003, they could be easily discriminated from urothelial cells by their shape and size. Finally, intravesical instillation of TY14003 into mouse bladder, using N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN)-induced bladder cancer model, demonstrated that fluorescent signals were detected in the focal areas of bladder of all mice examined at 12 weeks of BBN drinking by confocal microscopy and fluorescent endoscopy. On the contrary, all the normal bladders were found to be negative for TY14003 staining. In conclusion, these results indicate that TY14003 is a promising diagnostic tool to visualize small or flat high-grade superficial bladder cancer.
Cosmological and supernova neutrinos

NASA Astrophysics Data System (ADS)

Kajino, T.; Aoki, W.; Balantekin, A. B.; Cheoun, M.-K.; Hayakawa, T.; Hidaka, J.; Hirai, Y.; Kusakabe, M.; Mathews, G. J.; Nakamura, K.; Pehlivan, Y.; Shibagaki, S.; Suzuki, T.

2014-06-01

The Big Bang nucleosynthesis (BBN) and the cosmic microwave background (CMB) anisotropies are the pillars of modern cosmology. It has recently been suggested that axion which is a dark matter candidate in the framework of the standard model could condensate in the early universe and induce photon cooling before the epoch of the photon last scattering. Although this may render a solution to the overproduction problem of primordial 7Li abundance, there arises another serious difficulty of overproducing D abundance. We propose a hybrid dark matter model with both axions and relic supersymmetric (SUSY) particles to solve both overproduction problems of the primordial D and 7Li abundances simultaneously. The BBN also serves to constrain the nature of neutrinos. Considering non-thermal photons produced in the decay of the heavy sterile neutrinos due to the magnetic moment, we explore the cosmological constraint on the strength of neutrino magnetic moment consistent with the observed light element abundances. Core-collapse supernovae eject huge flux of energetic neutrinos which affect explosive nucleosynthesis of rare isotopes like 7Li, 11B, 92Nb, 138La and 180Ta and r-process elements. Several isotopes depend strongly on the neutrino flavor oscillation due to the Mikheyev-Smirnov-Wolfenstein (MSW) effect. Combining the recent experimental constraints on θ13 with predicted and observed supernova-produced abundance ratio 11B/7Li encapsulated in the presolar grains from the Murchison meteorite, we show a marginal preference for an inverted neutrino mass hierarchy. We also discuss supernova relic neutrinos (SRN) that may indicate the softness of the equation of state (EoS) of nuclear matter and adiabatic conditions of the neutrino oscillation.
Risk-Based Causal Modeling of Airborne Loss of Separation

NASA Technical Reports Server (NTRS)

Geuther, Steven C.; Shih, Ann T.

2015-01-01

Maintaining safe separation between aircraft remains one of the key aviation challenges as the Next Generation Air Transportation System (NextGen) emerges. The goals of the NextGen are to increase capacity and reduce flight delays to meet the aviation demand growth through the 2025 time frame while maintaining safety and efficiency. The envisioned NextGen is expected to enable high air traffic density, diverse fleet operations in the airspace, and a decrease in separation distance. All of these factors contribute to the potential for Loss of Separation (LOS) between aircraft. LOS is a precursor to a potential mid-air collision (MAC). The NASA Airspace Operations and Safety Program (AOSP) is committed to developing aircraft separation assurance concepts and technologies to mitigate LOS instances, therefore, preventing MAC. This paper focuses on the analysis of causal and contributing factors of LOS accidents and incidents leading to MAC occurrences. Mid-air collisions among large commercial aircraft are rare in the past decade, therefore, the LOS instances in this study are for general aviation using visual flight rules in the years 2000-2010. The study includes the investigation of causal paths leading to LOS, and the development of the Airborne Loss of Separation Analysis Model (ALOSAM) using Bayesian Belief Networks (BBN) to capture the multi-dependent relations of causal factors. The ALOSAM is currently a qualitative model, although further development could lead to a quantitative model. ALOSAM could then be used to perform impact analysis of concepts and technologies in the AOSP portfolio on the reduction of LOS risk.
Trust-Based Security Level Evaluation Using Bayesian Belief Networks

NASA Astrophysics Data System (ADS)

Houmb, Siv Hilde; Ray, Indrakshi; Ray, Indrajit; Chakraborty, Sudip

Security is not merely about technical solutions and patching vulnerabilities. Security is about trade-offs and adhering to realistic security needs, employed to support core business processes. Also, modern systems are subject to a highly competitive market, often demanding rapid development cycles, short life-time, short time-to-market, and small budgets. Security evaluation standards, such as ISO 14508 Common Criteria and ISO/IEC 27002, are not adequate for evaluating the security of many modern systems for resource limitations, time-to-market, and other constraints. Towards this end, we propose an alternative time and cost effective approach for evaluating the security level of a security solution, system or part thereof. Our approach relies on collecting information from different sources, who are trusted to varying degrees, and on using a trust measure to aggregate available information when deriving security level. Our approach is quantitative and implemented as a Bayesian Belief Network (BBN) topology, allowing us to reason over uncertain information and seemingly aggregating disparate information. We illustrate our approach by deriving the security level of two alternative Denial of Service (DoS) solutions. Our approach can also be used in the context of security solution trade-off analysis.
Revisiting big-bang nucleosynthesis constraints on long-lived decaying particles

NASA Astrophysics Data System (ADS)

Kawasaki, Masahiro; Kohri, Kazunori; Moroi, Takeo; Takaesu, Yoshitaro

2018-01-01

We study the effects of long-lived massive particles, which decayed during the big-bang nucleosynthesis (BBN) epoch, on the primordial abundance of light elements. Compared to previous studies, (i) the reaction rates of standard BBN reactions are updated, (ii) the most recent observational data on the light element abundance and cosmological parameters are used, (iii) the effects of the interconversion of energetic nucleons at the time of inelastic scattering with background nuclei are considered, and (iv) the effects of the hadronic shower induced by energetic high-energy antinucleons are included. We compare the theoretical predictions on the primordial abundance of light elements with the latest observational constraints, and we derive upper bounds on the relic abundance of the decaying particle as a function of its lifetime. We also apply our analysis to an unstable gravitino, the superpartner of a graviton in supersymmetric theories, and obtain constraints on the reheating temperature after inflation.
Enhancing residents' compassionate communication to family members: A family systems breaking bad news simulation.

PubMed

Williams-Reade, Jacqueline; Lobo, Elsie; Whittemore, Abel Arvizú; Parra, Laura; Baerg, Joanne

2018-05-28

Surgical residents often need to break bad news (BBN) to patients and family members. While communication skills are a core competency in residency training, these specific skills are rarely formally taught. We piloted a simulation training to teach pediatric surgical residents how to compassionately BBN of an unexpected, traumatic pediatric death to surviving family members. This training was unique in that it was influenced by family systems theory and was a collaborative effort between our institution's surgery residency and medical family therapy (MedFT) programs. This study provides outcomes of surgery residents' communication skills, attitudes, and self-perceptions after a BBN simulation activity with standardized family members at a major academic teaching hospital. Each resident participated in two 30-min simulations and received feedback from observers. Outcome data were collected through self-assessments completed before, immediately after, and 6 months after the simulation. Participants were 15 surgery residents, and MedFT students served as simulated family members and trainers. A statistically significant change with medium to large effect sizes in participant self-reported perceptions of skill and confidence were documented and maintained over 6 months. Responses to open-ended questions supported practice changes in response to the training. This collaborative training promoted significant improvement in resident compassionate communication skills. The curriculum was highly valued by the learners and resulted in sustained application of learned skills with patients and families. Our novel approach was feasible with promising results that warrant further investigation and could be reproduced in other institutions with similar programs. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Contralateral Dpoae Suppression in Humans at Very Low Sound Intensities

NASA Astrophysics Data System (ADS)

Janssen, T.; Gehr, D. D.; Kevanishvili, Z.

2003-02-01

Different functions are attributed to the olivo-cochlear bundle system (OCBS) such as protecting the ear from acoustic injury, improving signal detection in noise, and mediating selective attention. OCBS reflex strength can be evaluated, in animals as well as in humans, by measuring the degree of suppression of an ipsilateral DPOAE by a contralateral sound. The purpose of the study was to evaluate OCBS reflex strength depending on ipsilateral stimulus level, especially at threshold, by means of extrapolated DPOAE I/O-functions. Additionally, DPOAE was measured at near-to-threshold contralateral stimulus levels when using low-level ipsilateral stimulation for investigating possible enhancement of outer hair cell motion in the presence of low-level contralateral sound. The recording of the 2f1-f2 DPOAE in the presence or absence of contralateral sound was performed in normally hearing human subjects at f2 = 2 kHz. DPOAE I/O-functions were measured in a primary tone level range from L2 = 20 to L2 = 65 dB SPL (L1 = 0.4L2 + 39, f2/f1=1.2). Broad-band noise (BBN), narrow-band noise from 1720 to 2320 Hz (NBN), and pure tones (PT) at f2, 2f1-f2, geometric mean of f1 and f2, and 0.1oct + f2 were used for contralateral stimulation. The contralateral stimulus level (Ls) was decreased from 70 down to 10 dB SPL in 10 dB steps. DPOAE suppression was highest at the lowest primary tone level and was more pronounced for BBN and NBN than for pure tones, suggesting a more diffuse than a strong tonotopic organisation of the OCBS. The contralateral stimulus level at which significant DPOAE suppression occurred (p < 0.05) was different for the different stimuli being 20, 40, and 70 dB SPL for BBN, NBN, and pure-tone (f2), respectively. Significant DPOAE suppression to BBN and NBN occurred at Ls well below audiological middle-ear reflex threshold. DPOAE time course was different for Ls below and above middle-ear reflex threshold. Thus, middle-ear muscle contraction is suggested not to be involved in DPOAE suppression at low Ls. No enhancement of DPOAE could be found. The findings suggest the OCBS to be functioning in a more protective way than for improving signal detection in noise.
Frequency Domain Fluorescent Molecular Tomography and Molecular Probes for Small Animal Imaging

NASA Astrophysics Data System (ADS)

Kujala, Naresh Gandhi

Fluorescent molecular tomography (FMT) is a noninvasive biomedical optical imaging that enables 3-dimensional quantitative determination of fluorochromes distributed in biological tissues. There are three methods for imaging large volume tissues based on different light sources: (a) using a light source of constant intensity, through a continuous or constant wave, (b) using a light source that is intensity modulated with a radio frequency (RF), and (c) using ultrafast pulses in the femtosecond range. In this study, we have developed a frequency domain fluorescent molecular tomographic system based on the heterodyne technique, using a single source and detector pair that can be used for small animal imaging. In our system, the intensity of the laser source is modulated with a RF frequency to produce a diffuse photon density wave in the tissue. The phase of the diffuse photon density wave is measured by comparing the reference signal with the signal from the tissue using a phasemeter. The data acquisition was performed by using a Labview program. The results suggest that we can measure the phase change from the heterogeneous inside tissue. Combined with fiber optics and filter sets, the system can be used to sensitively image the targeted fluorescent molecular probes, allowing the detection of cancer at an early stage. We used the system to detect the tumor-targeting molecular probe Alexa Fluor 680 and Alexa Fluor 750 bombesin peptide conjugates in phantoms as well as mouse tissues. We also developed and evaluated fluorescent Bombesin (BBN) probes to target gastrin-releasing peptide (GRP) receptors for optical molecular imaging. GRP receptors are over-expressed in several types of human cancer cells, including breast, prostate, small cell lung, and pancreatic cancers. BBN is a 14 amino acid peptide that is an analogue to human gastrin-releasing peptide that binds specifically to GRPr receptors. BBN conjugates are significant in cancer detection and therapy. The optical molecular probe AF750 BBN peptide exhibits optimal pharmacokinetic properties for targeting GRPr in mice. Fluorescent microscopic imaging of the molecular probe in PC-3 prostate and T-47D breast cancer cell lines indicated specific uptake, internalization, and receptor blocking of these probes. In vivo investigations in severely compromised immunodeficient (SCID) mice bearing xenografted PC-3 prostate and T47-D breast cancer lesions demonstrated the ability of this new molecular probe to specifically target tumor tissue with high selectively and affinity.
Topical and systemic immunoreaction triggered by intravesical chemotherapy in an N-butyl-N-(4-hydroxybutyl) nitorosamine induced bladder cancer mouse model

PubMed Central

Nakai, Yasushi; Tanaka, Nobumichi; Fujimoto, Kiyohide

2017-01-01

Intravesical bacillus Calmette-Guerin (BCG) treatment is the most common therapy to prevent progression and recurrence of non-muscle invasive bladder cancer (NMIBC). Although the immunoreaction elicited by BCG treatment is well documented, those induced by intravesical treatment with chemotherapeutic agents are much less known. We investigated the immunological profiles caused by mitomycin C, gemcitabine, adriamycin and docetaxel in the N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN)-induced orthotopic bladder cancer mouse model. Ninety mice bearing orthotopic bladder cancer induced by BBN were randomly divided into six groups and treated with chemotherapeutic agents once a week for four weeks. After last treatment, bladder and serum samples were analyzed for cell surface and immunological markers (CD4, CD8, CD56, CD204, Foxp3, and PD-L1) using immunohistochemistry staining. Serum and urine cytokine levels were evaluated by ELISA. All chemotherapeutic agents presented anti-tumor properties similar to those of BCG. These included changes in immune cells that resulted in fewer M2 macrophages and regulatory T cells around tumors. This result was compatible with those in human samples. Intravesical chemotherapy also induced systemic changes in cytokines, especially urinary interleukin (IL)-17A and granulocyte colony stimulating factor (G-CSF), as well as in the distribution of blood neutrophils, lymphocytes, and monocytes. Our findings suggest that intravesical treatment with mitomycin C and adriamycin suppresses protumoral immunity while enhancing anti-tumor immunity, possibly through the action of specific cytokines. A better understanding of the immunoreaction induced by chemotherapeutic agents can lead to improved outcomes and fewer side effects in intravesical chemotherapy against NMIBC. PMID:28406993
Suppression of ERβ signaling via ERβ knockout or antagonist protects against bladder cancer development.

PubMed

Hsu, Iawen; Chuang, Kun-Lung; Slavin, Spencer; Da, Jun; Lim, Wei-Xun; Pang, See-Tong; O'Brien, Jeanne H; Yeh, Shuyuan

2014-03-01

Epidemiological studies showed that women have a lower bladder cancer (BCa) incidence, yet higher muscle-invasive rates than men, suggesting that estrogen and the estrogen receptors, estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ), may play critical roles in BCa progression. Using in vitro cell lines and an in vivo carcinogen N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN)-induced mouse BCa model, we found that ERβ plays a positive role in promoting BCa progression. Knockdown of ERβ with ERβ-shRNA in ERβ-positive human BCa J82, 647v and T24 cell lines led to suppressed cell growth and invasion. Mice lacking ERβ have less cancer incidence with reduced expression of the proliferation marker Ki67 in BBN-induced BCa. Consistently, our results show that non-malignant urothelial cells with ERβ knockdown are more resistant to carcinogen-induced malignant transformation. Mechanism dissection found that targeting ERβ suppressed the expression of minichromosome maintenance complex component 5 (MCM5), a DNA replication licensing factor that is involved in tumor cell growth. Restoring MCM5 expression can partially reverse ERβ knockdown-mediated growth reduction. Supportively, treating cells with the ERβ-specific antagonist, 4-[2-Phenyl-5,7-bis(trifluoromethyl) pyrazolo[1,5-a]pyrimidin-3-yl]phenol (PHTPP), reduced BCa cell growth and invasion, as well as MCM5 expression. Furthermore, we provide the first evidence that BCa burden and mortality can be controlled by PHTPP treatment in the carcinogen-induced BCa model. Together, these results demonstrate that ERβ could play positive roles in promoting BCa progression via MCM5 regulation. Targeting ERβ through ERβ-shRNA, PHTPP or via downstream targets, such as MCM5, could serve as potential therapeutic approaches to battle BCa.
Holevo Capacity Achieving Joint Detection Receiver

DTIC Science & Technology

2013-12-31

DETECTION RECEIVER (75) Inventor: Saikat Guha, Everett , MA (US) (73) Assignee: Raytheon BBN Technologies Corp., Cambridge, MA (US) ( * ) Notice...tum Operations”, Oct. 18, 2011, 11 pages. Shannon, “The Bell System Technical Journal”, A Mathematical Theory of Communication, vol. XXVII, No. 3, Jul
The Gap-Startle Paradigm for Tinnitus Screening in Animal Models: Limitations and Optimization

PubMed Central

Lobarinas, Edward; Hayes, Sarah H.; Allman, Brian L.

2012-01-01

In 2006, Turner and colleagues (Behav Neurosci, 120:188–195) introduced the gap-startle paradigm as a high-throughput method for tinnitus screening in rats. Under this paradigm, gap detection ability was assessed by determining the level of inhibition of the acoustic startle reflex produced by a short silent gap inserted in an otherwise continuous background sound prior to a loud startling stimulus. Animals with tinnitus were expected to show impaired gap detection ability (i.e., lack of inhibition of the acoustic startle reflex) if the background sound containing the gap was qualitatively similar to the tinnitus pitch. Thus, for the gap-startle paradigm to be a valid tool to screen for tinnitus, a robust startle response from which to inhibit must be present. Because recent studies have demonstrated that the acoustic startle reflex could be dramatically reduced following noise exposure, we endeavored to 1) modify the gap-startle paradigm to be more resilient in the presence of hearing loss, and 2) evaluate whether a reduction in startle reactivity could confound the interpretation of gap prepulse inhibition and lead to errors in screening for tinnitus. In the first experiment, the traditional broadband noise (BBN) startle stimulus was replaced by a bandpass noise in which the sound energy was concentrated in the lower frequencies (5–10 kHz) in order to maintain audibility of the startle stimulus after unilateral high frequency noise exposure (16 kHz). However, rats still showed a 57% reduction in startle amplitude to the bandpass noise post-noise exposure. A follow-up experiment on a separate group of rats with transiently-induced conductive hearing loss revealed that startle reactivity was better preserved when the BBN startle stimulus was replaced by a rapid airpuff to the back of the rats neck. Furthermore, it was found that transient unilateral conductive hearing loss, which was not likely to induce tinnitus, caused an impairment in gap prepulse inhibition as assessed with the traditional BBN gap-startle paradigm, resulting in a false-positive screening for tinnitus. Thus, the present study identifies significant caveats of the traditional gap-startle paradigm, and describes experimental parameters using an airpuff startle stimulus which may help to limit the negative consequences of reduced startle reactivity following noise exposure, thereby allowing researchers to better screen for tinnitus in animals with hearing loss. PMID:22728305

Application Transparent HTTP Over a Disruption Tolerant Smartnet

DTIC Science & Technology

2014-09-01

American Standard Code for Information Interchange BP Bundle Protocol BPA bundle protocol agent CLA convergence layer adapters CPU central processing...forwarding them through the plugin pipeline. The initial version of the DTNInput plugin uses the BBN Spindle bundle protocol agent ( BPA ) implementation
Long-circulating, pH-sensitive liposomes versus long-circulating, non-pH-sensitive liposomes as a delivery system for tumor identification.

PubMed

de Barros, André Luís Branco; Mota, Luciene das Graças; Soares, Daniel Crístian Ferreira; de Souza, Cristina Maria; Cassali, Geovanni Dantas; Oliveira, Mônica Cristina; Cardoso, Valbert Nascimento

2013-09-01

Bombesin (BBN) is a tetradecapeptide that binds specifically to gastrin-releasing peptide receptors in humans. Several forms of cancer, including lung, prostate, breast, and colon over-express receptors for bombesin-like peptides. Therefore, radiolabeled bombesin analogs might be useful for tumor identification. Nevertheless, it is well known that higher tumor uptake can yield images in higher quality. Hence, drug delivery systems, such as liposomes, can be used to achieve a higher concentration of radiotracer in tumor site, and also improve the radiotracer stability, since peptides can suffer easily degradation in vivo by natural plasma and tissue peptides. In this paper, we prepared long-circulating, pH-sensitive liposomes and long-circulation, non-pH sensitive liposomes. Both formulations were able to encapsulate the radiolabeled bombesin derivative (99mTc-BBN(7_14)), and also showing high in vitro stability. Biodistribution studies were performed in Ehrlich tumor bearing-mice to compare the ability of pH-sensitive and non-pH sensitive liposomes to deliver 99mTc-BBN(7_14) to tumor site. Results showed higher tumor uptake (2-fold) when pH-sensitive liposomes were used, suggesting that these vesicles can facilitate the access to the tumor by releasing the diagnostic agent into the ideal area. As a result, tumor-to-muscle ratio achieved with pH-sensitive liposomes was higher than that obtained with non-pH-sensitive formulation. In addition, scintigraphic images for pH-sensitive liposomes showed evident tumor uptake, corroborating with biodistribution data. Therefore, the results presented in this paper suggest that pH-sensitive liposomes are able to deliver more efficiently the radiolabeled bombesin analog. This finding poses a new possibility to improve images quality, since the tumor-to-muscle ratio was strongly enhanced.
Effects of seven chemicals on DNA damage in the rat urinary bladder: a comet assay study.

PubMed

Wada, Kunio; Yoshida, Toshinori; Takahashi, Naofumi; Matsumoto, Kyomu

2014-07-15

The in vivo comet assay has been used for the evaluation of DNA damage and repair in various tissues of rodents. However, it can give false-positive results due to non-specific DNA damage associated with cell death. In this study, we examined whether the in vivo comet assay can distinguish between genotoxic and non-genotoxic DNA damage in urinary bladder cells, by using the following seven chemicals related to urinary bladder carcinogenesis in rodents: N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN), glycidol, 2,2-bis(bromomethyl)-1,3-propanediol (BMP), 2-nitroanisole (2-NA), benzyl isothiocyanate (BITC), uracil, and melamine. BBN, glycidol, BMP, and 2-NA are known to be Ames test-positive and they are expected to produce DNA damage in the absence of cytotoxicity. BITC, uracil, and melamine are Ames test-negative with metabolic activation but have the potential to induce non-specific DNA damage due to cytotoxicity. The test chemicals were administered orally to male Sprague-Dawley rats (five per group) for each of two consecutive days. Urinary bladders were sampled 3h after the second administration and urothelial cells were analyzed by the comet assay and subjected to histopathological examination to evaluate cytotoxicity. In the urinary bladders of rats treated with BBN, glycidol, and BMP, DNA damage was detected. In contrast, 2-NA induced neither DNA damage nor cytotoxicity. The non-genotoxic chemicals (BITC, uracil, and melamine) did not induce DNA damage in the urinary bladders under conditions where some histopathological changes were observed. The results indicate that the comet assay could distinguish between genotoxic and non-genotoxic chemicals and that no false-positive responses were obtained. Copyright © 2014 Elsevier B.V. All rights reserved.
A new, precise measurement of the primordial abundance of deuterium

NASA Astrophysics Data System (ADS)

Pettini, Max; Cooke, Ryan

2012-10-01

The metal-poor (Z ≃ 1/100 Z⊙) damped Lyman α system (DLA) at redshift zabs = 3.049 84 in the zem ≃ 3.030 QSO SDSS J1419+0829 has near-ideal properties for an accurate determination of the primordial abundance of deuterium (D/H)p. We have analysed a high-quality spectrum of this object with software specifically designed to deduce the best-fitting value of D/H and to assess comprehensively the random and systematic errors affecting this determination. We find (D/H)DLA = (2.535 ± 0.05) × 10-5, which in turn implies Ωb, 0h2 = 0.0223 ± 0.0009, in very good agreement with Ωb, 0h2(CMB) = 0.0222 ± 0.0004 deduced from the angular power spectrum of the cosmic microwave background (CMB). If the value in this DLA is indeed the true (D/H)p produced by big bang nucleosynthesis (BBN), there may be no need to invoke non-standard physics nor early astration of D to bring together Ωb, 0 h2(BBN) and Ωb, 0 h2(CMB). The scatter between most of the reported values of (D/H)p in the literature may be due largely to unaccounted systematic errors and biases. Further progress in this area will require a homogeneous set of data comparable to those reported here and analysed in a self-consistent manner. Such an endeavour, while observationally demanding, has the potential of improving our understanding of BBN physics, including the relevant nuclear reactions, and the subsequent processing of light nuclides through stars. Based on observations collected at the European Organisation for Astronomical Research in the Southern hemisphere, Chile [Very Large Telescope programme ID 085.A-0109(A)].
Big bang nucleosynthesis, the CMB, and the origin of matter and space-time

NASA Astrophysics Data System (ADS)

Mathews, Grant J.; Gangopadhyay, Mayukh; Sasankan, Nishanth; Ichiki, Kiyotomo; Kajino, Toshitaka

2018-04-01

We summarize some applications of big bang nucleosythesis (BBN) and the cosmic microwave background (CMB) to constrain the first moments of the creation of matter in the universe. We review the basic elements of BBN and how it constraints physics of the radiation-dominated epoch. In particular, how the existence of higher dimensions impacts the cosmic expansion through the projection of curvature from the higher dimension in the "dark radiation" term. We summarize current constraints from BBN and the CMB on this brane-world dark radiation term. At the same time, the existence of extra dimensions during the earlier inflation impacts the tensor to scalar ratio and the running spectral index as measured in the CMB. We summarize how the constraints on inflation shift when embedded in higher dimensions. Finally, one expects that the universe was born out of a complicated multiverse landscape near the Planck time. In these moments the energy scale of superstrings was obtainable during the early moments of chaotic inflation. We summarize the quest for cosmological evidence of the birth of space-time out of the string theory landscape. We will explore the possibility that a superstring excitations may have made itself known via a coupling to the field of inflation. This may have left an imprint of "dips" in the power spectrum of temperature fluctuations in the cosmic microwave background. The identification of this particle as a superstring is possible because there may be evidence for different oscillator states of the same superstring that appear on different scales on the sky. It will be shown that from this imprint one can deduce the mass, number of oscillations, and coupling constant for the superstring. Although the evidence is marginal, this may constitute the first observation of a superstring in Nature.
Precision Higgs Physics, Effective Field Theory, and Dark Matter

NASA Astrophysics Data System (ADS)

Henning, Brian Quinn

The recent discovery of the Higgs boson calls for detailed studies of its properties. As precision measurements are indirect probes of new physics, the appropriate theoretical framework is effective field theory. In the first part of this thesis, we present a practical three-step procedure of using the Standard Model effective field theory (SM EFT) to connect ultraviolet (UV) models of new physics with weak scale precision observables. With this procedure, one can interpret precision measurements as constraints on the UV model concerned. We give a detailed explanation for calculating the effective action up to one-loop order in a manifestly gauge covariant fashion. The covariant derivative expansion dramatically simplifies the process of matching a UV model with the SM EFT, and also makes available a universal formalism that is easy to use for a variety of UV models. A few general aspects of renormalization group running effects and choosing operator bases are discussed. Finally, we provide mapping results between the bosonic sector of the SM EFT and a complete set of precision electroweak and Higgs observables to which present and near future experiments are sensitive. With a detailed understanding of how to use the SM EFT, we then turn to applications and study in detail two well-motivated test cases. The first is singlet scalar field that enables the first-order electroweak phase transition for baryogenesis; the second example is due to scalar tops in the MSSM. We find both Higgs and electroweak measurements are sensitive probes of these cases. The second part of this thesis centers around dark matter, and consists of two studies. In the first, we examine the effects of relic dark matter annihilations on big bang nucleosynthesis (BBN). The magnitude of these effects scale simply with the dark matter mass and annihilation cross-section, which we derive. Estimates based on these scaling behaviors indicate that BBN severely constrains hadronic and radiative dark matter annihilation channels in the previously unconsidered dark matter mass region MeV <˜ m x <˜ 10 GeV. Interestingly, we find that BBN constraints on hadronic annihilation channels are competitive with similar bounds derived from the cosmic microwave background. Our second study of dark matter concerns a possible connection with supersymmetry and the keV scale. Various theoretical and experimental considerations motivate models with high scale supersymmetry breaking. While such models may be difficult to test in colliders, we propose looking for signatures at much lower energies. We show that a keV line in the X-ray spectrum of galaxy clusters (such as the recently disputed 3.5 keV observation) can have its origin in a universal string axion coupled to a hidden supersymmetry breaking sector. A linear combination of the string axion and an additional axion in the hidden sector remains light, obtaining a mass of order 10 keV through supersymmetry breaking dynamics. In order to explain the X-ray line, the scale of supersymmetry breaking must be about 1011-12 GeV. This motivates high scale supersymmetry as in pure gravity mediation or minimal split supersymmetry and is consistent with all current limits. Since the axion mass is controlled by a dynamical mass scale, this mass can be much higher during inflation, avoiding isocurvature (and domain wall) problems associated with high scale inflation. In an appendix E we present a mechanism for dilaton stabilization that additionally leads to O(1) modifications of the gaugino mass from anomaly mediation.
The medial olivocochlear reflex in children during active listening.

PubMed

Smith, Spencer B; Cone, Barbara

2015-08-01

To determine if active listening modulates the strength of the medial olivocochlear (MOC) reflex in children. Click-evoked otoacoustic emissions (CEOAEs) were recorded from the right ear in quiet and in four test conditions: one with contralateral broadband noise (BBN) only, and three with active listening tasks wherein attention was directed to speech embedded in contralateral BBN. Fifteen typically-developing children (ranging in age from 8 to14 years) with normal hearing. CEOAE levels were reduced in every condition with contralateral acoustic stimulus (CAS) when compared to preceding quiet conditions. There was an additional systematic decrease in CEOAE level with increased listening task difficulty, although this effect was very small. These CEOAE level differences were most apparent in the 8-18 ms region after click onset. Active listening may change the strength of the MOC reflex in children, although the effects reported here are very subtle. Further studies are needed to verify that task difficulty modulates the activity of the MOC reflex in children.
The medial olivocochlear reflex in children during active listening

PubMed Central

Smith, Spencer B.; Cone, Barbara

2015-01-01

Objective To determine if active listening modulates the strength of the medial olivocochlear (MOC) reflex in children. Design Click-evoked otoacoustic emissions (CEOAEs) were recorded from the right ear in quiet and in four test conditions: one with contralateral broadband noise (BBN) only, and three with active listening tasks wherein attention was directed to speech embedded in contralateral BBN. Study sample Fifteen typically-developing children (ranging in age from 8 to 14 years) with normal hearing. Results CEOAE levels were reduced in every condition with contralateral acoustic stimulus (CAS) when compared to preceding quiet conditions. There was an additional systematic decrease in CEOAE level with increased listening task difficulty, although this effect was very small. These CEOAE level differences were most apparent in the 8–18 ms region after click onset. Conclusions Active listening may change the strength of the MOC reflex in children, although the effects reported here are very subtle. Further studies are needed to verify that task difficulty modulates the activity of the MOC reflex in children. PMID:25735203
Increasing Neff with particles in thermal equilibrium with neutrinos

NASA Astrophysics Data System (ADS)

hm, Céline Bœ; Dolan, Matthew J.; McCabe, Christopher

2012-12-01

Recent work on increasing the effective number of neutrino species (Neff) in the early universe has focussed on introducing extra relativistic species ('dark radiation'). We draw attention to another possibility: a new particle of mass lesssim10 MeV that remains in thermal equilibrium with neutrinos until it becomes non-relativistic increases the neutrino temperature relative to the photons. We demonstrate that this leads to a value of Neff that is greater than three and that Neff at CMB formation is larger than at BBN. We investigate the constraints on such particles from the primordial abundance of helium and deuterium created during BBN and from the CMB power spectrum measured by ACT and SPT and find that they are presently relatively unconstrained. We forecast the sensitivity of the Planck satellite to this scenario: in addition to dramatically improving constraints on the particle mass, in some regions of parameter space it can discriminate between the new particle being a real or complex scalar.
Time-Reversal Measurement of the p -Wave Cross Sections of the 7Be (n ,α )4He Reaction for the Cosmological Li Problem

NASA Astrophysics Data System (ADS)

Kawabata, T.; Fujikawa, Y.; Furuno, T.; Goto, T.; Hashimoto, T.; Ichikawa, M.; Itoh, M.; Iwasa, N.; Kanada-En'yo, Y.; Koshikawa, A.; Kubono, S.; Miyawaki, E.; Mizuno, M.; Mizutani, K.; Morimoto, T.; Murata, M.; Nanamura, T.; Nishimura, S.; Okamoto, S.; Sakaguchi, Y.; Sakata, I.; Sakaue, A.; Sawada, R.; Shikata, Y.; Takahashi, Y.; Takechi, D.; Takeda, T.; Takimoto, C.; Tsumura, M.; Watanabe, K.; Yoshida, S.

2017-02-01

The cross sections of the 7Be (n ,α )4He reaction for p -wave neutrons were experimentally determined at Ec .m .=0.20 - 0.81 MeV slightly above the big bang nucleosynthesis (BBN) energy window for the first time on the basis of the detailed balance principle by measuring the time-reverse reaction. The obtained cross sections are much larger than the cross sections for s -wave neutrons inferred from the recent measurement at the n_TOF facility in CERN, but significantly smaller than the theoretical estimation widely used in the BBN calculations. The present results suggest the 7Be (n ,α )4He reaction rate is not large enough to solve the cosmological lithium problem, and this conclusion agrees with the recent result from the direct measurement of the s -wave cross sections using a low-energy neutron beam and the evaluated nuclear data library ENDF/B-VII.1.
New cosmic microwave background constraint to primordial gravitational waves.

PubMed

Smith, Tristan L; Pierpaoli, Elena; Kamionkowski, Marc

2006-07-14

Primordial gravitational waves (GWs) with frequencies > or approximately equal to 10(-15) Hz contribute to the radiation density of the Universe at the time of decoupling of the cosmic microwave background (CMB). This affects the CMB and matter power spectra in a manner identical to massless neutrinos, unless the initial density perturbation for the GWs is nonadiabatic, as may occur if such GWs are produced during inflation or some post-inflation phase transition. In either case, current observations provide a constraint to the GW amplitude that competes with that from big-bang nucleosynthesis (BBN), although it extends to much lower frequencies (approximately 10(-15) Hz rather than the approximately 10(-10) Hz from BBN): at 95% confidence level, omega(gw)h(2)
Research and Development in Natural Language Understanding as Part of the Strategic Computing Program.

DTIC Science & Technology

1987-04-01

facilities. BBN is developing a series of increasingly sophisticated natural language understanding systems which will serve as an integrated interface...Haas, A.R. A Syntactic Theory of Belief and Action. Artificial Intelligence. 1986. Forthcoming. [6] Hinrichs, E. Temporale Anaphora im Englischen
Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

NASA Technical Reports Server (NTRS)

Shih, Ann T.; Ancel, Ersin; Jones, Sharon Monica; Reveley, Mary S.; Luxhoj, James T.

2012-01-01

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Hong, Jeong-Pyong; Kawasaki, Masahiro; Kavli IPMU

We consider nearly equal number of gauge mediation type charged (anti-) Q-balls with charge of ±α{sup −1}≃±137 well before the BBN epoch and discussed how they evolve in time. We found that ion-like objects with electric charges of +O(1) are likely to become relics in the present universe, which we expect to be the dark matter. These are constrained by MICA experiment, where the trail of heavy atom-like or ion-like object in 10{sup 9} years old ancient mica crystals is not observed. We found that the allowed region for gauge mediation model parameter and reheating temperature have to be smallermore » than the case of the neutral Q-ball dark matter.« less
Cosmological signals of a mirror twin Higgs

DOE PAGES

Craig, Nathaniel; Koren, Seth; Trott, Timothy

2017-05-08

We investigate the cosmology of the minimal model of neutral naturalness, the mirror Twin Higgs. The softly-broken mirror symmetry relating the Standard Model to its twin counterpart leads to significant dark radiation in tension with BBN and CMB observations. We quantify this tension and illustrate how it can be mitigated in several simple scenarios that alter the relative energy densities of the two sectors while respecting the softly-broken mirror symmetry. In particular, we consider both the out-of-equilibrium decay of a new scalar as well as reheating in a toy model of twinned inflation, Twinflation. In both cases the dilution ofmore » energy density in the twin sector does not merely reconcile the existence of a mirror Twin Higgs with cosmological constraints, but predicts contributions to cosmological observables that may be probed in current and future CMB experiments. This raises the prospect of discovering evidence of neutral naturalness through cosmology rather than colliders.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Craig, Nathaniel; Koren, Seth; Trott, Timothy

We investigate the cosmology of the minimal model of neutral naturalness, the mirror Twin Higgs. The softly-broken mirror symmetry relating the Standard Model to its twin counterpart leads to significant dark radiation in tension with BBN and CMB observations. We quantify this tension and illustrate how it can be mitigated in several simple scenarios that alter the relative energy densities of the two sectors while respecting the softly-broken mirror symmetry. In particular, we consider both the out-of-equilibrium decay of a new scalar as well as reheating in a toy model of twinned inflation, Twinflation. In both cases the dilution ofmore » energy density in the twin sector does not merely reconcile the existence of a mirror Twin Higgs with cosmological constraints, but predicts contributions to cosmological observables that may be probed in current and future CMB experiments. This raises the prospect of discovering evidence of neutral naturalness through cosmology rather than colliders.« less
A Hybrid Methodology for Modeling Risk of Adverse Events in Complex Health-Care Settings.

PubMed

Kazemi, Reza; Mosleh, Ali; Dierks, Meghan

2017-03-01

In spite of increased attention to quality and efforts to provide safe medical care, adverse events (AEs) are still frequent in clinical practice. Reports from various sources indicate that a substantial number of hospitalized patients suffer treatment-caused injuries while in the hospital. While risk cannot be entirely eliminated from health-care activities, an important goal is to develop effective and durable mitigation strategies to render the system "safer." In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the health-care domain, this can be extremely challenging due to the wide variability in the way that health-care processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study, we have developed a generic methodology for evaluating dynamic changes in AE risk in acute care hospitals as a function of organizational and nonorganizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational-level and policy-level contributions to risk evolve over time, and how policies and decisions may affect the general system-level contribution to AE risk. It also captures the feedback of organizational factors and decisions over time and the nonlinearities in these feedback effects. SD is a popular approach to understanding the behavior of complex social and economic systems. It is a simulation-based, differential equation modeling tool that is widely used in situations where the formal model is complex and an analytical solution is very difficult to obtain. Second, a Bayesian belief network (BBN) framework is used to represent patient-level factors and also physician-level decisions and factors in the management of an individual patient, which contribute to the risk of hospital-acquired AE. BBNs are networks of probabilities that can capture probabilistic relations between variables and contain historical information about their relationship, and are powerful tools for modeling causes and effects in many domains. The model is intended to support hospital decisions with regard to staffing, length of stay, and investments in safety, which evolve dynamically over time. The methodology has been applied in modeling the two types of common AEs: pressure ulcers and vascular-catheter-associated infection, and the models have been validated with eight years of clinical data and use of expert opinion. © 2017 Society for Risk Analysis.
Bayesian Safety Risk Modeling of Human-Flightdeck Automation Interaction

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2015-01-01

Usage of automatic systems in airliners has increased fuel efficiency, added extra capabilities, enhanced safety and reliability, as well as provide improved passenger comfort since its introduction in the late 80's. However, original automation benefits, including reduced flight crew workload, human errors or training requirements, were not achieved as originally expected. Instead, automation introduced new failure modes, redistributed, and sometimes increased workload, brought in new cognitive and attention demands, and increased training requirements. Modern airliners have numerous flight modes, providing more flexibility (and inherently more complexity) to the flight crew. However, the price to pay for the increased flexibility is the need for increased mode awareness, as well as the need to supervise, understand, and predict automated system behavior. Also, over-reliance on automation is linked to manual flight skill degradation and complacency in commercial pilots. As a result, recent accidents involving human errors are often caused by the interactions between humans and the automated systems (e.g., the breakdown in man-machine coordination), deteriorated manual flying skills, and/or loss of situational awareness due to heavy dependence on automated systems. This paper describes the development of the increased complexity and reliance on automation baseline model, named FLAP for FLightdeck Automation Problems. The model development process starts with a comprehensive literature review followed by the construction of a framework comprised of high-level causal factors leading to an automation-related flight anomaly. The framework was then converted into a Bayesian Belief Network (BBN) using the Hugin Software v7.8. The effects of automation on flight crew are incorporated into the model, including flight skill degradation, increased cognitive demand and training requirements along with their interactions. Besides flight crew deficiencies, automation system failures and anomalies of avionic systems are also incorporated. The resultant model helps simulate the emergence of automation-related issues in today's modern airliners from a top-down, generalized approach, which serves as a platform to evaluate NASA developed technologies
Contralateral Effects and Binaural Interactions in Dorsal Cochlear Nucleus

PubMed Central

2005-01-01

The dorsal cochlear nucleus (DCN) receives afferent input from the auditory nerve and is thus usually thought of as a monaural nucleus, but it also receives inputs from the contralateral cochlear nucleus as well as descending projections from binaural nuclei. Evidence suggests that some of these commissural and efferent projections are excitatory, whereas others are inhibitory. The goals of this study were to investigate the nature and effects of these inputs in the DCN by measuring DCN principal cell (type IV unit) responses to a variety of contralateral monaural and binaural stimuli. As expected, the results of contralateral stimulation demonstrate a mixture of excitatory and inhibitory influences, although inhibitory effects predominate. Most type IV units are weakly, if at all, inhibited by tones but are strongly inhibited by broadband noise (BBN). The inhibition evoked by BBN is also low threshold and short latency. This inhibition is abolished and excitation is revealed when strychnine, a glycine-receptor antagonist, is applied to the DCN; application of bicuculline, a GABAA-receptor antagonist, has similar effects but does not block the onset of inhibition. Manipulations of discrete fiber bundles suggest that the inhibitory, but not excitatory, inputs to DCN principal cells enter the DCN via its output pathway, and that the short latency inhibition is carried by commissural axons. Consistent with their respective monaural effects, responses to binaural tones as a function of interaural level difference are essentially the same as responses to ipsilateral tones, whereas binaural BBN responses decrease with increasing contralateral level. In comparison to monaural responses, binaural responses to virtual space stimuli show enhanced sensitivity to the elevation of a sound source in ipsilateral space but reduced sensitivity in contralateral space. These results show that the contralateral inputs to the DCN are functionally relevant in natural listening conditions, and that one role of these inputs is to enhance DCN processing of spectral sound localization cues produced by the pinna. PMID:16075189
In Vitro Mouse and Human Serum Stability of a Heterobivalent Dual-Target Probe That Has Strong Affinity to Gastrin-Releasing Peptide and Neuropeptide Y1 Receptors on Tumor Cells.

PubMed

Ghosh, Arijit; Raju, Natarajan; Tweedle, Michael; Kumar, Krishan

2017-02-01

Receptor-targeting radiolabeled molecular probes with high affinity and specificity are useful in studying and monitoring biological processes and responses. Dual- or multiple-targeting probes, using radiolabeled metal chelates conjugated to peptides, have potential advantages over single-targeting probes as they can recognize multiple targets leading to better sensitivity for imaging and radiotherapy when target heterogeneity is present. Two natural hormone peptide receptors, gastrin-releasing peptide (GRP) and Y1, are specifically interesting as their expression is upregulated in most breast and prostate cancers. One of our goals has been to develop a dual-target probe that can bind both GRP and Y1 receptors. Consequently, a heterobivalent dual-target probe, t-BBN/BVD15-DO3A (where a GRP targeting ligand J-G-Abz4-QWAVGHLM-NH 2 and Y1 targeting ligand INP-K [ɛ-J-(α-DO3A-ɛ-DGa)-K] YRLRY-NH 2 were coupled), that recognizes both GRP and Y1 receptors was synthesized, purified, and characterized in the past. Competitive displacement cell binding assay studies with the probe demonstrated strong affinity (IC 50 values given in parentheses) for GRP receptors in T-47D cells (18 ± 0.7 nM) and for Y1 receptors in MCF7 cells (80 ± 11 nM). As a further evaluation of the heterobivalent dual-target probe t-BBN/BVD15-DO3A, the objective of this study was to determine its mouse and human serum stability at 37°C. The in vitro metabolic degradation of the dual-target probe in mouse and human serum was studied by using a 153 Gd-labeled t-BBN/BVD15-DO3A and a high-performance liquid chromatography/radioisotope detector analytical method. The half-life (t 1/2 ) of degradation of the dual-target probe in mouse serum was calculated as 7 hours and only ∼20% degradation was seen after 6 hours incubation in human serum. The slow in vitro metabolic degradation of the dual-target probe can be compared with the degradation t 1/2 of the corresponding monomeric probes, BVD15-DO3A and AMBA: 15, and ∼40 minutes for BVD15-DO3A and 3.1 and 38.8 hours for AMBA in mouse and human serum, respectively. A possible pathway for in vitro metabolic degradation of the t-BBN/BVD15-DO3A in mouse serum is proposed based on the chromatographic retention times of the intact probe and its degradants.

Acoustic stapedial reflexes in healthy neonates: normative data and test-retest reliability.

PubMed

Kei, Joseph

2012-01-01

The acoustic stapedial reflex (ASR) test provides useful information about the function of the auditory system. While it is frequently used with adults and children in a clinical setting, its use with young infants is limited. Presently, there are few data for neonates and inadequate research into the test-retest reliability of the ASR test. This study aimed to establish normative data and evaluate the test-retest reliability of the ASR test in healthy neonates. A cross-sectional experimental design was used to establish ASR normative data and assess the test-retest reliability of ASR thresholds obtained from healthy neonates. Sixty-eight full-term neonates with mean chronological age of 2.5 days (SD = 1.8 day), who passed the automated auditory brainstem response, transient evoked otoacoustic emission, and high frequency (1 kHz) tympanometry (HFT) tests. One randomly selected ear from each neonate was tested using TEOAE (transient evoked otoacoustic emission), HFT, and ASR tests using a 1 kHz probe tone. ASR thresholds were elicited by presenting pure tones of 0.5, 2, and 4 kHz and broadband noise (BBN) separately to the test ear in an ipsilateral stimulation mode. The ASR procedure was repeated to acquire retest data within the same testing session. Descriptive statistics, χ2, and analysis of variance with repeated measures tests were used to analyze ASR data. All neonates exhibited ASR when stimulated by tonal stimuli or BBN. The mean ASRTs (acoustic stapedial reflex thresholds) for the 0.5, 2, and 4 kHz tones were 81.6 ± 7.9, 71.3 ± 7.9, and 65.4 ± 8.7 dB HL, respectively. The mean ASRT for the BBN was estimated to be smaller than 57.2 dB HL, given the limitation of the equipment. The 95th percentiles of the ASRT were 95, 85, 80, and 75 dB HL for the 0.5, 2, and 4 kHz and BBN, respectively. The test-retest reliability of the ASR test for all stimuli was high, with no significant difference in mean ASRTs across the test and retest conditions. Test-retest differences were within 10 dB for more than 91% of ASRT data across all stimuli. There was a slight trend of ASRTs being more repeatable in the medium ASRT range than in the higher or lower range. This study demonstrated that ASRTs obtained from healthy neonates were highly repeatable across test and retest sessions. Given the availability of normative data and the high test-retest reliability, the ASR test will be useful as a diagnostic tool in a battery of tests to evaluate the auditory function of neonates. American Academy of Audiology.
Insights into neutrino decoupling gleaned from considerations of the role of electron mass

NASA Astrophysics Data System (ADS)

Grohs, E.; Fuller, George M.

2017-10-01

We present calculations showing how electron rest mass influences entropy flow, neutrino decoupling, and Big Bang Nucleosynthesis (BBN) in the early universe. To elucidate this physics and especially the sensitivity of BBN and related epochs to electron mass, we consider a parameter space of rest mass values larger and smaller than the accepted vacuum value. Electromagnetic equilibrium, coupled with the high entropy of the early universe, guarantees that significant numbers of electron-positron pairs are present, and dominate over the number of ionization electrons to temperatures much lower than the vacuum electron rest mass. Scattering between the electrons-positrons and the neutrinos largely controls the flow of entropy from the plasma into the neutrino seas. Moreover, the number density of electron-positron-pair targets can be exponentially sensitive to the effective in-medium electron mass. This entropy flow influences the phasing of scale factor and temperature, the charged current weak-interaction-determined neutron-to-proton ratio, and the spectral distortions in the relic neutrino energy spectra. Our calculations show the sensitivity of the physics of this epoch to three separate effects: finite electron mass, finite-temperature quantum electrodynamic (QED) effects on the plasma equation of state, and Boltzmann neutrino energy transport. The ratio of neutrino to plasma-component energy scales manifests in Cosmic Microwave Background (CMB) observables, namely the baryon density and the radiation energy density, along with the primordial helium and deuterium abundances. Our results demonstrate how the treatment of in-medium electron mass (i.e., QED effects) could translate into an important source of uncertainty in extracting neutrino and beyond-standard-model physics limits from future high-precision CMB data.
First-in-human study of PET and optical dual-modality image-guided surgery in glioblastoma using 68Ga-IRDye800CW-BBN.

PubMed

Li, Deling; Zhang, Jingjing; Chi, Chongwei; Xiao, Xiong; Wang, Junmei; Lang, Lixin; Ali, Iqbal; Niu, Gang; Zhang, Liwei; Tian, Jie; Ji, Nan; Zhu, Zhaohui; Chen, Xiaoyuan

2018-01-01

Purpose : Despite the use of fluorescence-guided surgery (FGS), maximum safe resection of glioblastoma multiforme (GBM) remains a major challenge. It has restricted surgeons between preoperative diagnosis and intraoperative treatment. Currently, an integrated approach combining preoperative assessment with intraoperative guidance would be a significant step in this direction. Experimental design : We developed a novel 68 Ga-IRDye800CW-BBN PET/near-infrared fluorescence (NIRF) dual-modality imaging probe targeting gastrin-releasing peptide receptor (GRPR) in GBM. The preclinical in vivo tumor imaging and FGS were first evaluated using an orthotopic U87MG glioma xenograft model. Subsequently, the first-in-human prospective cohort study (NCT 02910804) of GBM patients were conducted with preoperative PET assessment and intraoperative FGS. Results : The orthotopic tumors in mice could be precisely resected using the near-infrared intraoperative system. Translational cohort research in 14 GBM patients demonstrated an excellent correlation between preoperative positive PET uptake and intraoperative NIRF signal. The tumor fluorescence signals were significantly higher than those from adjacent brain tissue in vivo and ex vivo (p < 0.0001). Compared with pathology, the sensitivity and specificity of fluorescence using 42 loci of fluorescence-guided sampling were 93.9% (95% CI 79.8%-99.3%) and 100% (95% CI 66.4%-100%), respectively. The tracer was safe and the extent of resection was satisfactory without newly developed neurologic deficits. Progression-free survival (PFS) at 6 months was 80% and two newly diagnosed patients achieved long PFS. Conclusions: This initial study has demonstrated that the novel dual-modality imaging technique is feasible for integrated pre- and intraoperative targeted imaging via the same molecular receptor and improved intraoperative GBM visualization and maximum safe resection.
Charged Q-ball dark matter from B and L direction

NASA Astrophysics Data System (ADS)

Hong, Jeong-Pyong; Kawasaki, Masahiro; Yamada, Masaki

2016-08-01

We consider nearly equal number of gauge mediation type charged (anti-) Q-balls with charge of ±α-1 simeq ±137 well before the BBN epoch and discussed how they evolve in time. We found that ion-like objects with electric charges of +O(1) are likely to become relics in the present universe, which we expect to be the dark matter. These are constrained by MICA experiment, where the trail of heavy atom-like or ion-like object in 109 years old ancient mica crystals is not observed. We found that the allowed region for gauge mediation model parameter and reheating temperature have to be smaller than the case of the neutral Q-ball dark matter.
Expert Approaches to Analysis

DTIC Science & Technology

1999-03-01

of epistemic forms and games , which can form the basis for building a tool to support expert analyses. 15. SUBJECT TERMS Expert analysis Epistemic...forms Epistemic games SECURITY CLASSIFICATION OF 16. REPORT Unclassified 17. ABSTRACT Unclassified 18. THIS PAGE Unclassified 19. LIMITATION OF...1998 Principal Investigators: Allan Collins & William Ferguson BBN Technologies Introduction 1 Prior Work 2 Structural-Analysis Games 2 Functional
Was the Universe actually radiation dominated prior to nucleosynthesis?

NASA Astrophysics Data System (ADS)

Giblin, John T.; Kane, Gordon; Nesbit, Eva; Watson, Scott; Zhao, Yue

2017-08-01

Maybe not. String theory approaches to both beyond the Standard Model and inflationary model building generically predict the existence of scalars (moduli) that are light compared to the scale of quantum gravity. These moduli become displaced from their low energy minima in the early Universe and lead to a prolonged matter-dominated epoch prior to big bang nucleosynthesis (BBN). In this paper, we examine whether nonperturbative effects such as parametric resonance or tachyonic instabilities can shorten, or even eliminate, the moduli condensate and matter-dominated epoch. Such effects depend crucially on the strength of the couplings, and we find that unless the moduli become strongly coupled, the matter-dominated epoch is unavoidable. In particular, we find that in string and M-theory compactifications where the lightest moduli are near the TeV scale, a matter-dominated epoch will persist until the time of big bang nucleosynthesis.
Flexible Coordination in Resource-Constrained Domains

DTIC Science & Technology

1994-07-01

Experiments (TIEs) with planning technologies developed at both BBN (FMERG) and SRI ( SOCAP ). We have also exported scheduling support capabilities provided by...SRI’s SOCAP course of action (COA) plan generator. "* Development and demonstration of distributed, multi-level deployment scheduling - Through analysis...scheduler was adapted for integration with the SOCAP planning system to provide feedback on transportation feasibility during generation of the
Solutions for Coding Societal Events

DTIC Science & Technology

2016-12-01

develop a prototype system for civil unrest event extraction, and (3) engineer BBN ACCENT (ACCurate Events from Natural Text ) to support broad use by...56 iv List of Tables Table 1: Features in similarity metric. Abbreviations are as follows. TG: text graph...extraction of a stream of events (e.g. protests, attacks, etc.) from unstructured text (e.g. news, social media). This technical report presents results
My 65 years in acoustics

NASA Astrophysics Data System (ADS)

Beranek, Leo L.

2004-05-01

My entry into acoustics began as research assistant to Professor F. V. Hunt at Harvard University. I received my doctorate in 1940 and directed the Electro-Acoustic Laboratory at Harvard from October 1940 until September 1945. In 1947, I became a tenured associate professor at MIT, and, with Richard H. Bolt, formed the consulting firm Bolt and Beranek, that later included Robert B. Newman, becoming BBN. My most significant contributions before 1970 were design of wedge-lined anechoic chambers, systemization of noise reduction in ventilation systems, design of the world's largest muffler for the testing of supersonic jet engines at NASA's Lewis Laboratory in Cleveland, speech interference level, NC noise criterion curves, heading New York Port Authority's noise study that resulted in mufflers on jet aircraft, and steep aircraft climb procedures, and publishing books titled, Acoustical Measurements, Acoustics, Noise Reduction, Noise and Vibration Control, and Music, Acoustics and Architecture. As President of BBN, I supervised the formation of the group that built and operated the ARPANET (1969), which, when split in two (using TCP/IP protocol) became the INTERNET (1984). Since then, I have written two books on Concert Halls and Opera Houses and have consulted on four concert halls and an opera house.
Individual Supervision to Enhance Reflexivity and the Practice of Patient-Centered Care: Experience at the Undergraduate Level.

PubMed

Berney, Alexandre; Bourquin, Céline

2017-12-22

This article reports on what is at work during individual supervision of medical students in the context of teaching breaking bad news (BBN). Surprisingly, there is a relative lack of research and report on the topic of supervision, even though it is regularly used in medical training. Building on our research and teaching experience on BBN at the undergraduate level, as well as interviews of supervisors, the following key elements have been identified: learning objectives (e.g., raising student awareness of structural elements of the interview, emotion (patients and students) handling), pedagogical approach (being centered on student's needs and supportive to promote already existing competences), essentials (e.g., discussing skills and examples from the clinical practice), and enhancing reflexivity while discussing specific issues (e.g., confusion between the needs of the patient and those of the student). Individual supervision has been identified as crucial and most satisfactory by students to provide guidance and to foster a reflexive stance enabling them to critically apprehend their communication style. Ultimately, the challenge is to teach medical students to not only connect with the patient but also with themselves.
Universes without the weak force: Astrophysical processes with stable neutrons

NASA Astrophysics Data System (ADS)

Grohs, E.; Howe, Alex R.; Adams, Fred C.

2018-02-01

We investigate a class of universes in which the weak interaction is not in operation. We consider how astrophysical processes are altered in the absence of weak forces, including big bang nucleosynthesis (BBN), galaxy formation, molecular cloud assembly, star formation, and stellar evolution. Without weak interactions, neutrons no longer decay, and the universe emerges from its early epochs with a mixture of protons, neutrons, deuterium, and helium. The baryon-to-photon ratio must be smaller than the canonical value in our Universe to allow free nucleons to survive the BBN epoch without being incorporated into heavier nuclei. At later times, the free neutrons readily combine with protons to make deuterium in sufficiently dense parts of the interstellar medium, and provide a power source before they are incorporated into stars. Almost all of the neutrons are incorporated into deuterium nuclei before stars are formed. As a result, stellar evolution proceeds primarily through strong interactions, with deuterium first burning into helium, and then helium fusing into carbon. Low-mass deuterium-burning stars can be long-lived, and higher-mass stars can synthesize the heavier elements necessary for life. Although somewhat different from our own, such universes remain potentially habitable.
Neutrino cosmology after WMAP 7-year data and LHC first Z' bounds.

PubMed

Anchordoqui, Luis Alfredo; Goldberg, Haim

2012-02-24

The gauge-extended U(1)(C)×SU(2)(L)×U(1)(I(R))×U(1)(L) model elevates the global symmetries of the standard model (baryon number B and lepton number L) to local gauge symmetries. The U(1)(L) symmetry leads to three superweakly interacting right-handed neutrinos. This also renders a B-L symmetry nonanomalous. The superweak interactions of these Dirac states permit ν(R) decoupling just above the QCD phase transition: 175 is < or approximately equal to T(ν(R))(dec)/MeV is < or approximately equal to 250. In this transitional region, the residual temperature ratio between ν(L) and ν(R) generates extra relativistic degrees of freedom at BBN and at the CMB epochs. Consistency with both WMAP 7-year data and recent estimates of the primordial 4He mass fraction is achieved for 3
Gravitational wave signals and cosmological consequences of gravitational reheating

NASA Astrophysics Data System (ADS)

Artymowski, Michał; Czerwińska, Olga; Lalak, Zygmunt; Lewicki, Marek

2018-04-01

Reheating after inflation can proceed even if the inflaton couples to Standard Model (SM) particles only gravitationally. However, particle production during the transition between de-Sitter expansion and a decelerating Universe is rather inefficient and the necessity to recover the visible Universe leads to a non-standard cosmological evolution initially dominated by remnants of the inflaton field. We remain agnostic to the specific dynamics of the inflaton field and discuss a generic scenario in which its remnants behave as a perfect fluid with a general barotropic parameter w. Using CMB and BBN constraints we derive the allowed range of inflationary scales. We also show that this scenario results in a characteristic primordial Gravitational Wave (GW) spectrum which gives hope for observation in upcoming runs of LIGO as well as in other planned experiments.
Stakeholder perceptions of soil managements in the Canyoles watershed. A Bayesian Belief Network approach

NASA Astrophysics Data System (ADS)

Burguet Marimón, Maria; Quinn, Claire; Stringer, Lindsay; Cerdà, Artemi

2017-04-01

The fate of the management and use of land is the result of economic, social and political factors (Tengberg et al., 2016). Stakeholder perceptions are relevant in understanding land management (Marques et al., 2015; Teshome et al., 2016) as perceptions can shape behaviours and actions. In the Canyoles River watershed (Eastern Spain), rainfed agriculture has been replaced by traditional irrigation systems at its valley bottom, and by drip irrigation on its slopes. The new irrigation systems in hilly citrus orchards, along with intensive farming, use of herbicides and high fertilization, are causing high erosion and land degradation rates due to the lack of vegetation cover, soil compaction and the loss of organic matter. Bayesian Belief Networks (BBN) are defined as a 'graphical tool for building decision support systems to help make decisions under uncertain conditions' (Cain, 2001). In this work, BBNs were used to incorporate the issues and objectives identified by stakeholders during interviews about their perceptions of different soil management practices in the Canyoles watershed. BBNs are appropriate for the modeling of geospatial data which can contain different kinds of uncertainties due to positional error, feature classification error, resolution, attribute error, data completeness, currency, and logical consistency, and can integrate qualitative and quantitative data. Our stakeholders were farmers, politicians (especially the mayors of the nearby towns), managers, farm employees and technicians. The questions asked to the stakeholders were related to their concern in keeping the farm active and profitable, the changes in the price of the farm products, the price of the fertilizers and tractors and if soil erosion is a key issue in their farms Preliminary results from the interviews performed with the stakeholders suggest that there is still a strong refusal to the use of different cover crops, as well as to the change in the tillage systems. Farmers do not fight against these problems as, on the one hand, they do not realize that non-sustainable soil erosion rates reduce soil fertility, and, on the other hand, there are several cultural issues that guide them towards bare soil as they find this as a tidy way to keep their properties. However, more research needs to be done on the BBN approach in order to be able to have a holistic approach regarding the vision of the farmers concerning the use of the different soil conservation strategies. Acknowledgements. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 603498 (RECARE project). References Cain, J. 2001. Planning improvements in natural resources management: Guidelines for using Bayesian networks to support the planning and management of development programmes in the water sector and beyond. Centre for Ecology & Hydrology, Wallingford, UK. Marques, M. J., R. Bienes, J. Cuadrado, M. Ruiz-Colmenero, C. Barbero-Sierra, and A. Velasco. 2015. Analysing Perceptions Attitudes and Responses of Winegrowers about Sustainable Land Management in Central Spain. Land Degradation and Development 26 (5): 458-467. doi:10.1002/ldr.2355. Tengberg, A., F. Radstake, K. Zhang, and B. Dunn. 2016. Scaling Up of Sustainable Land Management in the Western People's Republic of China: Evaluation of a 10-Year Partnership. Land Degradation and Development 27 (2): 134-144. doi:10.1002/ldr.2270. Teshome, A., J. de Graaff, C. Ritsema, and M. Kassie. 2016. Farmers' Perceptions about the Influence of Land Quality, Land Fragmentation and Tenure Systems on Sustainable Land Management in the North Western Ethiopian Highlands. Land Degradation and Development 27 (4): 884-898. doi:10.1002/ldr.2298.
Semantic and Syntactic Bases of Text Comprehension.

DTIC Science & Technology

1985-07-25

processing . Psychological Review, 82, 407-428. Craik , F. & Lockhart , R. (1972). Levels of processing : A framework for memory research. Journal of...development, 55, 2083-2093. 56 BBN Laboratories Incorporated Perfetti. C. (1979). Levels of language and levels of processing . In L. Cermak & F. Craik ... processing cycle. Thus, the activation level of those representations that are used in ongoing cycles of integration (e.g. those related to the central
Distributed Computation and TENEX-Related Activities

DTIC Science & Technology

1975-02-01

A new echo rr ode, viz., echo non -wakeup characters and do not echo wakeup characters, was defined; and the assignments of four control characters...operations and, with certain controllers e.g. 3339 equivalent , simultaneous rotational positioning. Prior to installing tnis feature, BBN’s lyscem C... Control and Accounting System 3 B. RSEXEC Program Execution Environment 5 C. Management of Distributed Data Bases 6 III. TENEX RELATED ACTIVITIES
Breaking Be: a sterile neutrino solution to the cosmological lithium problem

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

Salvati, L.; Melchiorri, A.; Pagano, L.

2016-08-01

The possibility that the so-called ''lithium problem'', i.e., the disagreement between the theoretical abundance predicted for primordial {sup 7}Li assuming standard nucleosynthesis and the value inferred from astrophysical measurements, can be solved through a non-thermal Big Bang Nucleosynthesis (BBN) mechanism has been investigated by several authors. In particular, it has been shown that the decay of a MeV-mass particle, like, e.g., a sterile neutrino, decaying after BBN not only solves the lithium problem, but also satisfies cosmological and laboratory bounds, making such a scenario worth to be investigated in further detail. In this paper, we constrain the parameters of themore » model with the combination of current data, including Planck 2015 measurements of temperature and polarization anisotropies of the Cosmic Microwave Background (CMB), FIRAS limits on CMB spectral distortions, astrophysical measurements of primordial abundances and laboratory constraints. We find that a sterile neutrino with mass M {sub S} = 4.35{sub -0.17}{sup +0.13} MeV (at 95% c.l.), a decay time τ {sub S} = 1.8{sub -1.3}{sup +2.5} · 10{sup 5} s (at 95% c.l.) and an initial density n-bar {sub S} / n-bar {sub cmb} = 1.7{sub -0.6}{sup +3.5} · 10{sup -4} (at 95% c.l.) in units of the number density of CMB photons, perfectly accounts for the difference between predicted and observed {sup 7}Li primordial abundance. This model also predicts an increase of the effective number of relativistic degrees of freedom at the time of CMB decoupling Δ N {sub eff}{sup cmb} ≡ N {sub eff}{sup cmb} -3.046 = 0.34{sub -0.14}{sup +0.16} at 95% c.l.. The required abundance of sterile neutrinos is incompatible with the standard thermal history of the Universe, but could be realized in a low reheating temperature scenario. We also provide forecasts for future experiments finding that the combination of measurements from the COrE+ and PIXIE missions will allow to significantly reduce the permitted region for the sterile lifetime and density.« less
Stochastic Drought Risk Analysis and Projection Methods For Thermoelectric Power Systems

NASA Astrophysics Data System (ADS)

Bekera, Behailu Belamo

Combined effects of socio-economic, environmental, technological and political factors impact fresh cooling water availability, which is among the most important elements of thermoelectric power plant site selection and evaluation criteria. With increased variability and changes in hydrologic statistical stationarity, one concern is the increased occurrence of extreme drought events that may be attributable to climatic changes. As hydrological systems are altered, operators of thermoelectric power plants need to ensure a reliable supply of water for cooling and generation requirements. The effects of climate change are expected to influence hydrological systems at multiple scales, possibly leading to reduced efficiency of thermoelectric power plants. This study models and analyzes drought characteristics from a thermoelectric systems operational and regulation perspective. A systematic approach to characterize a stream environment in relation to extreme drought occurrence, duration and deficit-volume is proposed and demonstrated. More specifically, the objective of this research is to propose a stochastic water supply risk analysis and projection methods from thermoelectric power systems operation and management perspectives. The study defines thermoelectric drought as a shortage of cooling water due to stressed supply or beyond operable water temperature limits for an extended period of time requiring power plants to reduce production or completely shut down. It presents a thermoelectric drought risk characterization framework that considers heat content and water quantity facets of adequate water availability for uninterrupted operation of such plants and safety of its surroundings. In addition, it outlines mechanisms to identify rate of occurrences of the said droughts and stochastically quantify subsequent potential losses to the sector. This mechanism is enabled through a model based on compound Nonhomogeneous Poisson Process. This study also demonstrates how the systematic approach can be used for better understanding of pertinent vulnerabilities by providing risk-based information to stakeholders in the power sector. Vulnerabilities as well as our understanding of their extent and likelihood change over time. Keeping up with the changes and making informed decisions demands a time-dependent method that incorporates new evidence into risk assessment framework. This study presents a statistical time-dependent risk analysis approach, which allows for life cycle drought risk assessment of thermoelectric power systems. Also, a Bayesian Belief Network (BBN) extension to the proposed framework is developed. The BBN allows for incorporating new evidence, such as observing power curtailments due to extreme heat or lowflow situations, and updating our knowledge and understanding of the pertinent risk. In sum, the proposed approach can help improve adaptive capacity of the electric power infrastructure, thereby enhancing its resilience to events potentially threatening grid reliability and economic stability. The proposed drought characterization methodology is applied on a daily streamflow series obtained from three United States Geological Survey (USGS) water gauges on the Tennessee River basin. The stochastic water supply risk assessment and projection methods are demonstrated for two power plants on the White River, Indiana: Frank E. Ratts and Petersburg, using water temperature and streamflow time series data obtained from a nearby USGS gauge.
Syntax, Semantics, and Speech

DTIC Science & Technology

1975-04-01

D.R. Reddy (ed.), Academic Press (1975). \\h \\ i: LJ r- I. I. 0 i bbN Heport No. 3067 bolt Beranek and Newman Ine S. mm he directi...context is tne type ^ at trie ielt -nanu gie nonterrainai nonempty string pe 3 grammars, more restricted u in generative cnaracterized by 1...Collins, A. (eds.) Academic Press, (in press [23] wewell , A. et al . ( 1973) Speech Understanoing Systems: tlinal heport of a Study Group. North
Some Issues in Programming Multi-Mini-Processors

DTIC Science & Technology

1975-01-01

Hardware ^nd software are to be combined optimally to perform that specialized task. This in essence is the stategy followed by the BBN group in...large memory is directly addressable. MIXED SOLUTIONS The most promising approach appears to involve mixing several of the previous solutions...mini- or micro-computers. Possibly the problem will be solved by avoiding it. Some new minis are appearing on the market now with large physical

Natural Communication with Computers. Volume 1. Speech Understanding Research at BBN

DTIC Science & Technology

1974-12-01

Signal Processing Concurrently with the incremental simulation experiments used to develop insights into the organization of the control component and...us to seek an alternative organization for our phonemic dictionary. There is also the potential problem of new words being used to name new places... organize the lexicon for maximization of efficient retrieval by taking advantage of phonetic, syntactic and semantic relationsnips. Work has already
Observational constraints on secret neutrino interactions from big bang nucleosynthesis

NASA Astrophysics Data System (ADS)

Huang, Guo-yuan; Ohlsson, Tommy; Zhou, Shun

2018-04-01

We investigate possible interactions between neutrinos and massive scalar bosons via gϕν ¯ν ϕ (or massive vector bosons via gVν ¯γμν Vμ) and explore the allowed parameter space of the coupling constant gϕ (or gV) and the scalar (or vector) boson mass mϕ (or mV) by requiring that these secret neutrino interactions (SNIs) should not spoil the success of big bang nucleosynthesis (BBN). Incorporating the SNIs into the evolution of the early Universe in the BBN era, we numerically solve the Boltzmann equations and compare the predictions for the abundances of light elements with observations. It turns out that the constraint on gϕ and mϕ in the scalar-boson case is rather weak, due to a small number of degrees of freedom (d.o.f.). However, in the vector-boson case, the most stringent bound on the coupling gV≲6 ×10-10 at 95% confidence level is obtained for mV≃1 MeV , while the bound becomes much weaker gV≲8 ×10-6 for smaller masses mV≲10-4 MeV . Moreover, we discuss in some detail how the SNIs affect the cosmological evolution and the abundances of the lightest elements.
Hardware for dynamic quantum computing experiments: Part I

NASA Astrophysics Data System (ADS)

Johnson, Blake; Ryan, Colm; Riste, Diego; Donovan, Brian; Ohki, Thomas

Static, pre-defined control sequences routinely achieve high-fidelity operation on superconducting quantum processors. Efforts toward dynamic experiments depending on real-time information have mostly proceeded through hardware duplication and triggers, requiring a combinatorial explosion in the number of channels. We provide a hardware efficient solution to dynamic control with a complete platform of specialized FPGA-based control and readout electronics; these components enable arbitrary control flow, low-latency feedback and/or feedforward, and scale far beyond single-qubit control and measurement. We will introduce the BBN Arbitrary Pulse Sequencer 2 (APS2) control system and the X6 QDSP readout platform. The BBN APS2 features: a sequencer built around implementing short quantum gates, a sequence cache to allow long sequences with branching structures, subroutines for code re-use, and a trigger distribution module to capture and distribute steering information. The X6 QDSP features a single-stage DSP pipeline that combines demodulation with arbitrary integration kernels, and multiple taps to inspect data flow for debugging and calibration. We will show system performance when putting it all together, including a latency budget for feedforward operations. This research was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), through the Army Research Office Contract No. W911NF-10-1-0324.
A definitive signal of multiple supersymmetry breaking

NASA Astrophysics Data System (ADS)

Cheung, Clifford; Mardon, Jeremy; Nomura, Yasunori; Thaler, Jesse

2010-07-01

If the lightest observable-sector supersymmetric particle (LOSP) is charged and long-lived, then it may be possible to indirectly measure the Planck mass at the LHC and provide a spectacular confirmation of supergravity as a symmetry of nature. Unfortunately, this proposal is only feasible if the gravitino is heavy enough to be measured at colliders, and this condition is in direct conflict with constraints from big bang nucleosynthesis (BBN). In this work, we show that the BBN bound can be naturally evaded in the presence of multiple sectors which independently break supersymmetry, since there is a new decay channel of the LOSP to a goldstino. Certain regions of parameter space allow for a direct measurement of LOSP decays into both the goldstino and the gravitino at the LHC. If the goldstino/gravitino mass ratio is measured to be 2, as suggested by theory, then this would provide dramatic verification of the existence of multiple supersymmetry breaking and sequestering. A variety of consistent cosmological scenarios are obtained within this framework. In particular, if an R symmetry is imposed, then the gauge-gaugino-goldstino interaction vertices can be forbidden. In this case, there is no bound on the reheating temperature from goldstino overproduction, and thermal lepto genesis can be accommodated consistently with gravitino dark matter.
Do joint CMB and HST data support a scale invariant spectrum?

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

Benetti, Micol; Graef, Leila L.; Alcaniz, Jailson S., E-mail: micolbenetti@on.br, E-mail: leilagraef@on.br, E-mail: alcaniz@on.br

We combine current measurements of the local expansion rate, H {sub 0}, and Big Bang Nucleosynthesis (BBN) estimates of helium abundance with the latest cosmic microwave background (CMB) data from the Planck Collaboration to discuss the observational viability of the scale invariant Harrison-Zeldovch-Peebles (HZP) spectrum. We also analyze some of its extensions, namely, HZP + Y {sub P} and HZP + N {sub eff}, where Y {sub P} is the primordial helium mass fraction and N {sub eff} is the effective number of relativistic degrees of freedom. We perform a Bayesian analysis and show that the latter model is favoredmore » with respect to the standard cosmology for values of N {sub eff} lying in the interval 3.70 ± 0.13 (1σ), which is currently allowed by some independent analyses.« less
Isorhapontigenin (ISO) Inhibits Invasive Bladder Cancer Formation In Vivo and Human Bladder Cancer Invasion In Vitro by Targeting STAT1/FOXO1 Axis.

PubMed

Jiang, Guosong; Wu, Amy D; Huang, Chao; Gu, Jiayan; Zhang, Liping; Huang, Haishan; Liao, Xin; Li, Jingxia; Zhang, Dongyun; Zeng, Xingruo; Jin, Honglei; Huang, Haojie; Huang, Chuanshu

2016-07-01

Although our most recent studies have identified Isorhapontigenin (ISO), a novel derivative of stilbene that isolated from a Chinese herb Gnetum cleistostachyum, for its inhibition of human bladder cancer growth, nothing is known whether ISO possesses an inhibitory effect on bladder cancer invasion. Thus, we addressed this important question in current study and discovered that ISO treatment could inhibit mouse-invasive bladder cancer development following bladder carcinogen N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) exposure in vivo We also found that ISO suppressed human bladder cancer cell invasion accompanied by upregulation of the forkhead box class O 1 (FOXO1) mRNA transcription in vitro Accordingly, FOXO1 was profoundly downregulated in human bladder cancer tissues and was negatively correlated with bladder cancer invasion. Forced expression of FOXO1 specifically suppressed high-grade human bladder cancer cell invasion, whereas knockdown of FOXO1 promoted noninvasive bladder cancer cells becoming invasive bladder cancer cells. Moreover, knockout of FOXO1 significantly increased bladder cancer cell invasion and abolished the ISO inhibition of invasion in human bladder cancer cells. Further studies showed that the inhibition of Signal transducer and activator of transcription 1 (STAT1) phosphorylation at Tyr701 was crucial for ISO upregulation of FOXO1 transcription. Furthermore, this study revealed that metalloproteinase-2 (MMP-2) was a FOXO1 downstream effector, which was also supported by data obtained from mouse model of ISO inhibition BBN-induced mouse-invasive bladder cancer formation. These findings not only provide a novel insight into the understanding of mechanism of bladder cancer's propensity to invasion, but also identify a new role and mechanisms underlying the natural compound ISO that specifically suppresses such bladder cancer invasion through targeting the STAT1-FOXO1-MMP-2 axis. Cancer Prev Res; 9(7); 567-80. ©2016 AACR. ©2016 American Association for Cancer Research.
Implication of the Proton-Deuteron Radiative Capture for Big Bang Nucleosynthesis.

PubMed

Marcucci, L E; Mangano, G; Kievsky, A; Viviani, M

2016-03-11

The astrophysical S factor for the radiative capture d(p,γ)^{3}He in the energy range of interest for big bang nucleosynthesis (BBN) is calculated using an ab initio approach. The nuclear Hamiltonian retains both two- and three-nucleon interactions-the Argonne v_{18} and the Urbana IX, respectively. Both one- and many-body contributions to the nuclear current operator are included. The former retain for the first time, besides the 1/m leading order contribution (m is the nucleon mass), also the next-to-leading order term, proportional to 1/m^{3}. The many-body currents are constructed in order to satisfy the current conservation relation with the adopted Hamiltonian model. The hyperspherical harmonics technique is applied to solve the A=3 bound and scattering states. Particular attention is paid in this second case in order to obtain, in the energy range of BBN, an uncertainty on the astrophysical S factor of the order or below ∼1%. Then, in this energy range, the S factor is found to be ∼10% larger than the currently adopted values. Part of this increase (1%-3%) is due to the 1/m^{3} one-body operator, while the remaining is due to the new more accurate scattering wave functions. We have studied the implication of this new determination for the d(p,γ)^{3}He S factor on the deuterium primordial abundance. We find that the predicted theoretical value for ^{2}H/H is in excellent agreement with its experimental determination, using the most recent determination of the baryon density of the Planck experiment, and with a standard number of relativistic degrees of freedom N_{eff}=3.046 during primordial nucleosynthesis. This calls for a more accurate measurement of the astrophysical S factor in order to confirm the present predictions.
The BBN Knowledge Acquisition Project

DTIC Science & Technology

1988-09-01

Optation 17 S . Large-Scale Revisions of Knowledge Bases 19 5.1 The Macro and Structure Editor 19 5.2 Developing Macro Editing Procedre 20 5.2.1 Macro...consistency checking foreach style of representaton easier and mote efficient, so that knowledge engineers and subject matter expert s can work together to... s ~Ta OIM-iJC ~Va Coetnin: MILECSXCT 8.1.3.1 Local Comumand Menus Anytime ICREM ais~laying a view of a particular kind of knowledge , the State Winsdow
User-Computer Interactions: Some Problems for Human Factors Research

DTIC Science & Technology

1981-09-01

accessibility from the work place or home of R. information stored in major repositories. o Two-way real-time communication between broadcasting - facilities...Miller, and R.W. Pew (BBN Inc.) MDA 903-80-C-0551 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT, TASK AREA & WORK UNIT NUMBERS...average U.S. home has gone from about 10 in 1940 to about 100 in 1960 to a few thousand in 1930. Collectively, these trends represent an enormous
The NYU System for MUC-6 or Where’s the Syntax?

DTIC Science & Technology

1995-01-01

34 and only in the face of compelling syntactic or semantic evidence, in a (nearly) deterministic manner . Speed was particularly an issue for MUC-6...thank BBN Systems and Technologies for providing us with this tagger. 168 Name Recognitio n The input stage is followed by several stages of pattern...Group Recognitio n The third stage of pattern matching recognizes verb groups : simple tensed verbs ("sleeps"), and verbs with auxiliaries ("will sleep
Cosmological moduli and the post-inflationary universe: A critical review

NASA Astrophysics Data System (ADS)

Kane, Gordon; Sinha, Kuver; Watson, Scott

2015-06-01

We critically review the role of cosmological moduli in determining the post-inflationary history of the universe. Moduli are ubiquitous in string and M-theory constructions of beyond the Standard Model physics, where they parametrize the geometry of the compactification manifold. For those with masses determined by supersymmetry (SUSY) breaking this leads to their eventual decay slightly before Big Bang nucleosynthesis (BBN) (without spoiling its predictions). This results in a matter dominated phase shortly after inflation ends, which can influence baryon and dark matter genesis, as well as observations of the cosmic microwave background (CMB) and the growth of large-scale structure. Given progress within fundamental theory, and guidance from dark matter and collider experiments, nonthermal histories have emerged as a robust and theoretically well-motivated alternative to a strictly thermal one. We review this approach to the early universe and discuss both the theoretical challenges and the observational implications.
3He(α, γ)7Be cross section in a wide energy range

NASA Astrophysics Data System (ADS)

Szücs, Tamás; Gyürky, György; Halász, Zoltán; Kiss, Gábor Gy.; Fülöp, Zsolt

2018-01-01

The reaction rate of the 3He(α,γ)7 Be reaction is important both in the Big Bang Nucleosynthesis (BBN) and in the Solar hydrogen burning. There have been a lot of experimental and theoretical efforts to determine this reaction rate with high precision. Some long standing issues have been solved by the more precise investigations, like the different S(0) values predicted by the activation and in-beam measurement. However, the recent, more detailed astrophysical model predictions require the reaction rate with even higher precision to unravel new issues like the Solar composition. One way to increase the precision is to provide a comprehensive dataset in a wide energy range, extending the experimental cross section database of this reaction. This paper presents a new cross section measurement between Ecm = 2.5 - 4.4 MeV, in an energy range which extends above the 7Be proton separation threshold.
^{7}Be(n,α)^{4}He Reaction and the Cosmological Lithium Problem: Measurement of the Cross Section in a Wide Energy Range at n_TOF at CERN.

PubMed

Barbagallo, M; Musumarra, A; Cosentino, L; Maugeri, E; Heinitz, S; Mengoni, A; Dressler, R; Schumann, D; Käppeler, F; Colonna, N; Finocchiaro, P; Ayranov, M; Damone, L; Kivel, N; Aberle, O; Altstadt, S; Andrzejewski, J; Audouin, L; Bacak, M; Balibrea-Correa, J; Barros, S; Bécares, V; Bečvář, F; Beinrucker, C; Berthoumieux, E; Billowes, J; Bosnar, D; Brugger, M; Caamaño, M; Calviani, M; Calviño, F; Cano-Ott, D; Cardella, R; Casanovas, A; Castelluccio, D M; Cerutti, F; Chen, Y H; Chiaveri, E; Cortés, G; Cortés-Giraldo, M A; Cristallo, S; Diakaki, M; Domingo-Pardo, C; Dupont, E; Duran, I; Fernandez-Dominguez, B; Ferrari, A; Ferreira, P; Furman, W; Ganesan, S; García-Rios, A; Gawlik, A; Glodariu, T; Göbel, K; Gonçalves, I F; González-Romero, E; Griesmayer, E; Guerrero, C; Gunsing, F; Harada, H; Heftrich, T; Heyse, J; Jenkins, D G; Jericha, E; Katabuchi, T; Kavrigin, P; Kimura, A; Kokkoris, M; Krtička, M; Leal-Cidoncha, E; Lerendegui, J; Lederer, C; Leeb, H; Lo Meo, S; Lonsdale, S J; Losito, R; Macina, D; Marganiec, J; Martínez, T; Massimi, C; Mastinu, P; Mastromarco, M; Mazzone, A; Mendoza, E; Milazzo, P M; Mingrone, F; Mirea, M; Montesano, S; Nolte, R; Oprea, A; Pappalardo, A; Patronis, N; Pavlik, A; Perkowski, J; Piscopo, M; Plompen, A; Porras, I; Praena, J; Quesada, J; Rajeev, K; Rauscher, T; Reifarth, R; Riego-Perez, A; Rout, P; Rubbia, C; Ryan, J; Sabate-Gilarte, M; Saxena, A; Schillebeeckx, P; Schmidt, S; Sedyshev, P; Smith, A G; Stamatopoulos, A; Tagliente, G; Tain, J L; Tarifeño-Saldivia, A; Tassan-Got, L; Tsinganis, A; Valenta, S; Vannini, G; Variale, V; Vaz, P; Ventura, A; Vlachoudis, V; Vlastou, R; Vollaire, J; Wallner, A; Warren, S; Weigand, M; Weiß, C; Wolf, C; Woods, P J; Wright, T; Žugec, P

2016-10-07

The energy-dependent cross section of the ^{7}Be(n,α)^{4}He reaction, of interest for the so-called cosmological lithium problem in big bang nucleosynthesis, has been measured for the first time from 10 meV to 10 keV neutron energy. The challenges posed by the short half-life of ^{7}Be and by the low reaction cross section have been overcome at n_TOF thanks to an unprecedented combination of the extremely high luminosity and good resolution of the neutron beam in the new experimental area (EAR2) of the n_TOF facility at CERN, the availability of a sufficient amount of chemically pure ^{7}Be, and a specifically designed experimental setup. Coincidences between the two alpha particles have been recorded in two Si-^{7}Be-Si arrays placed directly in the neutron beam. The present results are consistent, at thermal neutron energy, with the only previous measurement performed in the 1960s at a nuclear reactor. The energy dependence reported here clearly indicates the inadequacy of the cross section estimates currently used in BBN calculations. Although new measurements at higher neutron energy may still be needed, the n_TOF results hint at a minor role of this reaction in BBN, leaving the long-standing cosmological lithium problem unsolved.
Distributed Computation and TENEX-Related Activities

DTIC Science & Technology

1978-01-01

IPCF) which provides the inter-job communication functions required by MSG. MSG will be modified to use the IPCF primitives when running under TOPS...mmummi iiiwnrnrtnr’in i^WMBi. ■a^j.i.aiAj.k ■*"-’"’’"— •’ ’■■ BBN Report No. 3752 Bolt Beranek and Newman Inc. . . - . *. - primitive (e.g...from a process to MSG when a communication primitive is executed, and from MSG to a process when a pending event (e.g., outstanding receive operation
A Linked-Cell Domain Decomposition Method for Molecular Dynamics Simulation on a Scalable Multiprocessor

DOE PAGES

Yang, L. H.; Brooks III, E. D.; Belak, J.

1992-01-01

A molecular dynamics algorithm for performing large-scale simulations using the Parallel C Preprocessor (PCP) programming paradigm on the BBN TC2000, a massively parallel computer, is discussed. The algorithm uses a linked-cell data structure to obtain the near neighbors of each atom as time evoles. Each processor is assigned to a geometric domain containing many subcells and the storage for that domain is private to the processor. Within this scheme, the interdomain (i.e., interprocessor) communication is minimized.
BBN: Description of the PLUM System as Used for MUC-4

DTIC Science & Technology

1992-01-01

in the MUC-4 corpus’ . Here are the 8 parse fragments generated by FPP for the first sentence of TST2- MUC4 -0048 : ("SALVADORAN PRESIDENT-ELECT ALFREDO...extensive patterns for fragment combination . Figure 2 shows a graphical version of the semantics generated for the first fragment of S1 in TST2- MUC4 ...trigger. Following is the discourse event structure for the first event in TST2- MUC4 -0048 : Event MURDER Trigger fragments: "SALVADORAN PRESIDENT
Cognitive Support for Transportation Planners: A Collaborative Course of Action Exploration Tool

DTIC Science & Technology

2011-06-01

smaller problem . We chose to work with MIDAS , for the pragmatic reason that MIDAS developers were at Raytheon BBN Technologies, and were accessible to...overall framework we built up to let the planner interact with MIDAS . In [Scott, 2009b], the problem under discussion is the design of a “Joint...previously been used for and what we now want to use it for - we are using MIDAS for a set of problems for which it has not previously been used. It
Strongly self-interacting vector dark matter via freeze-in

NASA Astrophysics Data System (ADS)

Duch, Mateusz; Grzadkowski, Bohdan; Huang, Da

2018-01-01

We study a vector dark matter (VDM) model in which the dark sector couples to the Standard Model sector via a Higgs portal. If the portal coupling is small enough the VDM can be produced via the freeze-in mechanism. It turns out that the electroweak phase transition have a substantial impact on the prediction of the VDM relic density. We further assume that the dark Higgs boson which gives the VDM mass is so light that it can induce strong VDM self-interactions and solve the small-scale structure problems of the Universe. As illustrated by the latest LUX data, the extreme smallness of the Higgs portal coupling required by the freeze-in mechanism implies that the dark matter direct detection bounds are easily satisfied. However, the model is well constrained by the indirect detections of VDM from BBN, CMB, AMS-02, and diffuse γ/X-rays. Consequently, only when the dark Higgs boson mass is at most of O (keV) does there exist a parameter region which leads to a right amount of VDM relic abundance and an appropriate VDM self-scattering while satisfying all other constraints simultaneously.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Audren, Benjamin; Lesgourgues, Julien; Benabed, Karim

Models for the latest stages of the cosmological evolution rely on a less solid theoretical and observational ground than the description of earlier stages like BBN and recombination. As suggested in a previous work by Vonlanthen et al., it is possible to tweak the analysis of CMB data in such way to avoid making assumptions on the late evolution, and obtain robust constraints on ''early cosmology parameters''. We extend this method in order to marginalise the results over CMB lensing contamination, and present updated results based on recent CMB data. Our constraints on the minimal early cosmology model are weakermore » than in a standard ΛCDM analysis, but do not conflict with this model. Besides, we obtain conservative bounds on the effective neutrino number and neutrino mass, showing no hints for extra relativistic degrees of freedom, and proving in a robust way that neutrinos experienced their non-relativistic transition after the time of photon decoupling. This analysis is also an occasion to describe the main features of the new parameter inference code MONTE PYTHON, that we release together with this paper. MONTE PYTHON is a user-friendly alternative to other public codes like COSMOMC, interfaced with the Boltzmann code CLASS.« less
Biodecolorization of a food azo dye by the deep sea Dermacoccus abyssi MT1.1(T) strain from the Mariana Trench.

PubMed

Lang, Weeranuch; Sirisansaneeyakul, Sarote; Martins, Lígia O; Ngiwsara, Lukana; Sakairi, Nobuo; Pathom-aree, Wasu; Okuyama, Masayuki; Mori, Haruhide; Kimura, Atsuo

2014-01-01

This study reports the characterization of the ability of Dermacoccus spp. isolated from the deepest point of the world's oceans for azo dye decolorization. A detailed investigation of Dermacoccus abyssi MT1.1(T) with respect to the azoreductase activity and enzymatic mechanism as well as the potential role of the bacterial strain for biocleaning of industrial dye baths is reported. Resting cells with oxygen-insensitive azoreductase resulted in the rapid decolorization of the polysulfonated dye Brilliant Black BN (BBN) which is a common food colorant. The highest specific decolorization rate (vs) was found at 50 °C with a moderately thermal tolerance for over 1 h. Kinetic analysis showed the high rates and strong affinity of the enzymatic system for the dye with a Vmax = 137 mg/g cell/h and a Km = 19 mg/L. The degradation of BBN produces an initial orange intermediate, 8-amino-5-((4-sulfonatophenyl)diazenyl)naphthalene-2-sulfonic acid, identified by mass spectrometry which is later converted to 4-aminobenzene sulfonic acid. Nearly 80% of the maximum vs is possible achieved in resting cell treatment with the salinity increased up to 5.0% NaCl in reaction media. Therefore, this bacterial system has potential for dye decolorization bioprocesses occurring at high temperature and salt concentrations e.g. for cleaning dye-containing saline wastewaters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Big Bang 6Li nucleosynthesis studied deep underground (LUNA collaboration)

NASA Astrophysics Data System (ADS)

Trezzi, D.; Anders, M.; Aliotta, M.; Bellini, A.; Bemmerer, D.; Boeltzig, A.; Broggini, C.; Bruno, C. G.; Caciolli, A.; Cavanna, F.; Corvisiero, P.; Costantini, H.; Davinson, T.; Depalo, R.; Elekes, Z.; Erhard, M.; Ferraro, F.; Formicola, A.; Fülop, Zs.; Gervino, G.; Guglielmetti, A.; Gustavino, C.; Gyürky, Gy.; Junker, M.; Lemut, A.; Marta, M.; Mazzocchi, C.; Menegazzo, R.; Mossa, V.; Pantaleo, F.; Prati, P.; Rossi Alvarez, C.; Scott, D. A.; Somorjai, E.; Straniero, O.; Szücs, T.; Takacs, M.

2017-03-01

The correct prediction of the abundances of the light nuclides produced during the epoch of Big Bang Nucleosynthesis (BBN) is one of the main topics of modern cosmology. For many of the nuclear reactions that are relevant for this epoch, direct experimental cross section data are available, ushering the so-called "age of precision". The present work addresses an exception to this current status: the 2H(α,γ)6Li reaction that controls 6Li production in the Big Bang. Recent controversial observations of 6Li in metal-poor stars have heightened the interest in understanding primordial 6Li production. If confirmed, these observations would lead to a second cosmological lithium problem, in addition to the well-known 7Li problem. In the present work, the direct experimental cross section data on 2H(α,γ)6Li in the BBN energy range are reported. The measurement has been performed deep underground at the LUNA (Laboratory for Underground Nuclear Astrophysics) 400 kV accelerator in the Laboratori Nazionali del Gran Sasso, Italy. The cross section has been directly measured at the energies of interest for Big Bang Nucleosynthesis for the first time, at Ecm = 80, 93, 120, and 133 keV. Based on the new data, the 2H(α,γ)6Li thermonuclear reaction rate has been derived. Our rate is even lower than previously reported, thus increasing the discrepancy between predicted Big Bang 6Li abundance and the amount of primordial 6Li inferred from observations.
Exploring nuclear reactions relevant to Stellar and Big-Bang Nucleosynthesis using High-Energy-Density plasmas at OMEGA and the NIF

NASA Astrophysics Data System (ADS)

Gatu Johnson, M.

2017-10-01

Thermonuclear reaction rates and nuclear processes have been explored traditionally by means of accelerator experiments, which are difficult to execute at conditions relevant to Stellar Nucleosynthesis (SN) and Big Bang Nucleosynthesis (BBN). High-Energy-Density (HED) plasmas closely mimic astrophysical environments and are an excellent complement to accelerator experiments in exploring SN and BBN-relevant nuclear reactions. To date, our work using HED plasmas at OMEGA and NIF has focused on the complementary 3He+3He, T+3He and T +T reactions. First studies of the T +T reaction indicated the significance of the 5He ground-state resonance in the T +T neutron spectrum. Subsequent T +T experiments showed that the strength of this resonance varies with center-of-mass (c-m) energy in the range of 16-50 keV, a variation that is not fundamentally understood. Studies of the 3He+3He and T+3He reactions have also been conducted at OMEGA at c-m energies of 165 keV and 80 keV, respectively, and the results revealed three things. First, a large cross section for the T+3He- γ branch can be ruled out as an explanation for the anomalously high abundance of 6Li in primordial material. Second, the results contrasted to theoretical modeling indicate that the mirror-symmetry assumption is not enough to capture the differences between T +T and 3He+3He reactions. Third, the elliptical spectrum assumed in the analysis of 3He+3He data obtained in accelerator experiments is incorrect. Preliminary data from recent experiments at the NIF exploring the 3He+3He reaction at c-m energies of 60 keV and 100 keV also indicate that the underlying physics changes with c-m energy. In this talk, we describe these findings and future directions for exploring light-ion reactions at OMEGA and the NIF. The work was supported in part by the US DOE, LLE, and LLNL.
Continuous Solvothermal Synthesis and Surface Treatment for Improved and Scalable Processing of Ultra High Temperature Ceramic (UHTC) Nanopowders

DTIC Science & Technology

2017-06-13

with homogeneous nonagglomerated nanoparticles,20 smudge- and stain -resistant coatings, antibody bonding to phosphor particles, and more. A series...2 BBn + 11.0 Na (in benzene) --- ZrB2 + 4 NaCl + 6 NaBr (1) (2) In a typical experiment, the reactor is charged with 5 grams of anhydrous ZrCl4...21.5 mmol), 0.471 grams of boron (43.5 mmol), 2.35 grams of sodium metal (102.3 mmol) and 100 ml of anhydrous benzene in a controlled atmosphere
Long-lived stop at the LHC with or without R-parity

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

Covi, L.; Dradi, F., E-mail: laura.covi@theorie.physik.uni-goettingen.de, E-mail: federico.dradi@theorie.physik.uni-goettingen.de

2014-10-01

We consider scenarios of gravitino LSP and DM with stop NLSP both within R-parity conserving and R-parity violating supersymmetry (RPC and RPV SUSY, respectively). We discuss cosmological bounds from Big Bang Nucleosynthesis (BBN) and the gravitino abundance and then concentrate on the signals of long-lived stops at the LHC as displaced vertices or metastable particles. Finally we discuss how to distinguish R-parity conserving and R-parity breaking stop decays if they happen within the detector and how to suppress SM backgrounds.
Voice technology and BBN

NASA Technical Reports Server (NTRS)

Wolf, Jared J.

1977-01-01

The following research was discussed: (1) speech signal processing; (2) automatic speech recognition; (3) continuous speech understanding; (4) speaker recognition; (5) speech compression; (6) subjective and objective evaluation of speech communication system; (7) measurement of the intelligibility and quality of speech when degraded by noise or other masking stimuli; (8) speech synthesis; (9) instructional aids for second-language learning and for training of the deaf; and (10) investigation of speech correlates of psychological stress. Experimental psychology, control systems, and human factors engineering, which are often relevant to the proper design and operation of speech systems are described.
On the Determination of the 7Be(n, α)4He Reaction Cross Section at BBN Energies

NASA Astrophysics Data System (ADS)

Lamia, L.; Spitaleri, C.; Bertulani, C. A.; Hou, S. Q.; La Cognata, M.; Pizzone, R. G.; Romano, S.; Sergi, M. L.; Tumino, A.

2017-12-01

7Be destruction channels are currently a matter of study because of their influence on the 7Li cosmological abundances. Here, we determine the cross section of the (n, α) reaction by using Trojan Horse experimental data for the 7Li(p, α)4He reaction and correcting for Coulomb effects. The deduced 7Be(n, α)4He data overlap with the Big Bang nucleosynthesis energies and the deduced reaction rate allows us to evaluate the corresponding cosmological implications.
No Promoting Effect of Ethyl Tertiary-butyl Ether (ETBE) on Rat Urinary Bladder Carcinogenesis Initiated with N-Butyl-N-(4-hydroxybutyl)nitrosamine

PubMed Central

Hagiwara, Akihiro; Imai, Norio; Doi, Yuko; Suguro, Mayuko; Kawabe, Mayumi; Furukawa, Fumio; Nagano, Kasuke; Fukushima, Shoji

2013-01-01

The effects of ethyl tertiary-butyl ether (ETBE) on two-stage urinary bladder carcinogenesis in male F344 rats initiated with N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN) were investigated at various dose levels with regard to possible promoting activity. Groups of 30 rats were given drinking water containing 500 ppm BBN, as an initiator, for 4 weeks and starting one week thereafter received ETBE by gavage (daily, 7 days/week) at dose levels of 0 (control), 100, 300, 500 or 1000 mg/kg/day until experimental week 36. No statistically significant differences in incidences of preneoplastic lesions, papillomas, and carcinomas of the urinary bladder were evident in rats treated with 100–1000 mg/kg/day ETBE as compared with control values. Furthermore, the average numbers of preneoplastic or neoplastic lesions per unit length of basement membrane in rats given 100–1000 mg/kg/day ETBE were also comparable to control values. However, papillomatosis of the urinary bladder was found in 4 out of 30 rats (13%) in the group given 1000 mg/kg/day ETBE, and soft stones in the urinary bladder were found in 3 out of these 4 rats. The results thus demonstrated that ETBE did not exert promotional activity on urinary bladder carcinogenesis. However, papillomatosis of the urinary bladder developed in small numbers of the rats given ETBE at 1000 mg/kg/day but not in rats given 500 mg/kg/day or lower doses. PMID:24526807
Summary of Recent Developments in Primordial Nucleosynthesis.

PubMed

Schramm, D N

1993-06-01

This paper summarizes the recent observational and theoretical results on Big Bang Nucleosynthesis. In particular, it is shown that the new Pop II (6)Li results strongly support the argument that the Spite Plateau lithium is a good estimate of the primordial value. The (6)Li is consistent with the Be and Be found in Pop II stars, assuming those elements are cosmic ray produced. The HST (2)D value tightens the (2)D arguments and the observation of the (3)He in planetary nebula strengthens the (3)He +(2)D argument as a lower bound on Ωb. The new low metalicity (4)He determinations slightly raise the best primordial (4)He number and thus make a better fit and avoid a potential problem. The quark-hadron inspired inhomogeneous calculations now unanimously agree that only relatively small variations in Ωb are possible vis-à-vis the homogeneous model; hence, the robustness of Ωb∼ 0.05 is now apparent. A comparison with the ROSAT cluster data is also shown to be consistent with the standard BBN model. Ωb∼ 1 seems to be definitely excluded, so, if Ω= 1, as some recent observations may hint, then non-baryonic dark matter is required.
First Evidence of Running Cosmic Vacuum: Challenging the Concordance Model

NASA Astrophysics Data System (ADS)

Solà, Joan; Gómez-Valent, Adrià; de Cruz Pérez, Javier

2017-02-01

Despite the fact that a rigid {{Λ }}-term is a fundamental building block of the concordance ΛCDM model, we show that a large class of cosmological scenarios with dynamical vacuum energy density {ρ }{{Λ }} together with a dynamical gravitational coupling G or a possible non-conservation of matter, are capable of seriously challenging the traditional phenomenological success of the ΛCDM. In this paper, we discuss these “running vacuum models” (RVMs), in which {ρ }{{Λ }}={ρ }{{Λ }}(H) consists of a nonvanishing constant term and a series of powers of the Hubble rate. Such generic structure is potentially linked to the quantum field theoretical description of the expanding universe. By performing an overall fit to the cosmological observables SN Ia+BAO+H(z)+LSS+BBN+CMB (in which the WMAP9, Planck 2013, and Planck 2015 data are taken into account), we find that the class of RVMs appears significantly more favored than the ΛCDM, namely, at an unprecedented level of ≳ 4.2σ . Furthermore, the Akaike and Bayesian information criteria confirm that the dynamical RVMs are strongly preferred compared to the conventional rigid {{Λ }}-picture of the cosmic evolution.
PET Using a GRPR Antagonist 68Ga-RM26 in Healthy Volunteers and Prostate Cancer Patients.

PubMed

Zhang, Jingjing; Niu, Gang; Fan, Xinrong; Lang, Lixin; Hou, Guozhu; Chen, Libo; Wu, Huanwen; Zhu, Zhaohui; Li, Fang; Chen, Xiaoyuan

2018-06-01

This study was designed to analyze the safety, biodistribution, and radiation dosimetry of a gastrin-releasing peptide receptor (GRPR) antagonist PET tracer, 68 Ga-RM26; to assess its clinical diagnostic value in prostate cancer patients; and to perform a direct comparison between GRPR antagonist 68 Ga-RM26 and agonist 68 Ga-BBN. Methods: Five healthy volunteers were enrolled to validate the safety of 68 Ga-RM26 and calculate dosimetry. A total of 28 patients with prostate cancer (17 newly diagnosed and 11 posttherapy) were recruited and provided written informed consent. All the cancer patients underwent PET/CT at 15-30 min after intravenous injection of 1.85 MBq (0.05 mCi) per kilogram of body weight of 68 Ga-RM26. Among them, 22 patients (11 newly diagnosed and 11 posttherapy) underwent 68 Ga-BBN PET/CT for comparison within 1 wk. 99m Tc-MDP (methylene diphosphonate) bone scans were obtained within 2 wk for comparison. GRPR immunohistochemical staining of tumor samples was performed. Results: The administration of 68 Ga-M26 was well tolerated by all subjects, with no adverse symptoms being noticed or reported during the procedure and at 2-wk follow-up. The total effective dose equivalent and effective dose were 0.0912 ± 0.0140 and 0.0657 ± 0.0124 mSv/MBq, respectively. In the 17 patients with newly diagnosed prostate cancer, 68 Ga-RM26 PET/CT showed positive prostate-confined findings in 15 tumors with an SUV max of 6.49 ± 2.37. In the 11 patients who underwent prostatectomy or brachytherapy with or without androgen deprivation therapy, 68 Ga-RM26 PET/CT detected 8 metastatic lymph nodes in 3 patients with an SUV max of 4.28 ± 1.25 and 21 bone lesions in 8 patients with an SUV max of 3.90 ± 3.07. Compared with 68 Ga-RM26 PET/CT, GRPR agonist 68 Ga-BBN PET/CT detected fewer primary lesions and lymph node metastases as well as demonstrated lower tracer accumulation. There was a significant positive correlation between SUV derived from 68 Ga-RM26 PET and the expression level of GRPR ( P < 0.001). Conclusion: This study indicates the safety and significant efficiency of GRPR antagonist 68 Ga-RM26. 68 Ga-RM26 PET/CT would have remarkable value in detecting both primary prostate cancer and metastasis. 68 Ga-RM26 is also expected to be better than GRPR agonist as an imaging marker to evaluate GRPR expression in prostate cancer. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.
Fan Noise Prediction System Development: Source/Radiation Field Coupling and Workstation Conversion for the Acoustic Radiation Code

NASA Technical Reports Server (NTRS)

Meyer, H. D.

1993-01-01

The Acoustic Radiation Code (ARC) is a finite element program used on the IBM mainframe to predict far-field acoustic radiation from a turbofan engine inlet. In this report, requirements for developers of internal aerodynamic codes regarding use of their program output an input for the ARC are discussed. More specifically, the particular input needed from the Bolt, Beranek and Newman/Pratt and Whitney (turbofan source noise generation) Code (BBN/PWC) is described. In a separate analysis, a method of coupling the source and radiation models, that recognizes waves crossing the interface in both directions, has been derived. A preliminary version of the coupled code has been developed and used for initial evaluation of coupling issues. Results thus far have shown that reflection from the inlet is sufficient to indicate that full coupling of the source and radiation fields is needed for accurate noise predictions ' Also, for this contract, the ARC has been modified for use on the Sun and Silicon Graphics Iris UNIX workstations. Changes and additions involved in this effort are described in an appendix.
Coupled Boltzmann computation of mixed axion neutralino dark matter in the SUSY DFSZ axion model

NASA Astrophysics Data System (ADS)

Bae, Kyu Jung; Baer, Howard; Lessa, Andre; Serce, Hasan

2014-10-01

The supersymmetrized DFSZ axion model is highly motivated not only because it offers solutions to both the gauge hierarchy and strong CP problems, but also because it provides a solution to the SUSY μ-problem which naturally allows for a Little Hierarchy. We compute the expected mixed axion-neutralino dark matter abundance for the SUSY DFSZ axion model in two benchmark cases—a natural SUSY model with a standard neutralino underabundance (SUA) and an mSUGRA/CMSSM model with a standard overabundance (SOA). Our computation implements coupled Boltzmann equations which track the radiation density along with neutralino, axion, axion CO (produced via coherent oscillations), saxion, saxion CO, axino and gravitino densities. In the SUSY DFSZ model, axions, axinos and saxions go through the process of freeze-in—in contrast to freeze-out or out-of-equilibrium production as in the SUSY KSVZ model—resulting in thermal yields which are largely independent of the re-heat temperature. We find the SUA case with suppressed saxion-axion couplings (ξ=0) only admits solutions for PQ breaking scale falesssim 6× 1012 GeV where the bulk of parameter space tends to be axion-dominated. For SUA with allowed saxion-axion couplings (ξ =1), then fa values up to ~ 1014 GeV are allowed. For the SOA case, almost all of SUSY DFSZ parameter space is disallowed by a combination of overproduction of dark matter, overproduction of dark radiation or violation of BBN constraints. An exception occurs at very large fa~ 1015-1016 GeV where large entropy dilution from CO-produced saxions leads to allowed models.
Trials for the cosmological 7Li problem with 7Be beams at CRIB and collaborating studies

NASA Astrophysics Data System (ADS)

Hayakawa, S.

2017-09-01

For many years, the cosmological ^7 Li problem has been tackled from various aspects. The nuclear reaction data have also been improved, but still there remains some ambiguities. We review our experimental plans to measure the cross sections of three key reactions which act to destroy ^7 Be during the Big-Bang Nucleosynthesis (BBN). These experiments are all based on ^7 Be beams produced at Center-for-Nuclear-Study Radioactive Ion Beam separator (CRIB) in collaborations mainly with research groups from INFN-LNS and RCNP. The preliminary result of the previous experiment and the future plan are discussed.
RS/1 in the Clinical Environment

PubMed Central

Kush, Thomas

1980-01-01

This paper describes the design of RS/1,™ the Research System, and its use in clinical patient studies. RS/1 is an interactive computer software system developed by the Medical Systems Group at BBN. Investigators and technicians who have never before used computers can learn RS/1 with a few hours of training. It uses familiar and intuitive concepts for data handling and data analysis, such as the “automated notebook” format of data storage, the direct use of graphs in curve-fitting, and a simple command language. Its versatility has made RS/1 useful in clinical research contexts, especially for studies involving patient care data.
Running vacuum in the Universe and the time variation of the fundamental constants of Nature

NASA Astrophysics Data System (ADS)

Fritzsch, Harald; Solà, Joan; Nunes, Rafael C.

2017-03-01

We compute the time variation of the fundamental constants (such as the ratio of the proton mass to the electron mass, the strong coupling constant, the fine-structure constant and Newton's constant) within the context of the so-called running vacuum models (RVMs) of the cosmic evolution. Recently, compelling evidence has been provided that these models are able to fit the main cosmological data (SNIa+BAO+H(z)+LSS+BBN+CMB) significantly better than the concordance Λ CDM model. Specifically, the vacuum parameters of the RVM (i.e. those responsible for the dynamics of the vacuum energy) prove to be nonzero at a confidence level ≳ 3σ . Here we use such remarkable status of the RVMs to make definite predictions on the cosmic time variation of the fundamental constants. It turns out that the predicted variations are close to the present observational limits. Furthermore, we find that the time evolution of the dark matter particle masses should be crucially involved in the total mass variation of our Universe. A positive measurement of this kind of effects could be interpreted as strong support to the "micro-macro connection" (viz. the dynamical feedback between the evolution of the cosmological parameters and the time variation of the fundamental constants of the microscopic world), previously proposed by two of us (HF and JS).
DOE Office of Scientific and Technical Information (OSTI.GOV)

Hochberg, Yonit; Pyle, Matt; Zhao, Yue

We examine in greater detail the recent proposal of using superconductors for detecting dark matter as light as the warm dark matter limit of O(keV). Detection of suc light dark matter is possible if the entire kinetic energy of the dark matter is extracted in the scattering, and if the experiment is sensitive to O(meV) energy depositions. This is the case for Fermi-degenerate materials in which the Fermi velocity exceeds the dark matter velocity dispersion in the Milky Way of ~10 –3. We focus on a concrete experimental proposal using a superconducting target with a transition edge sensor in ordermore » to detect the small energy deposits from the dark matter scatterings. Considering a wide variety of constraints, from dark matter self-interactions to the cosmic microwave background, we show that models consistent with cosmological/astrophysical and terrestrial constraints are observable with such detectors. A wider range of viable models with dark matter mass below an MeV is available if dark matter or mediator properties (such as couplings or masses) differ at BBN epoch or in stellar interiors from those in superconductors. We also show that metal targets pay a strong in-medium suppression for kinetically mixed mediators; this suppression is alleviated with insulating targets.« less
Detecting superlight dark matter with Fermi-degenerate materials

DOE PAGES

Hochberg, Yonit; Pyle, Matt; Zhao, Yue; ...

2016-08-08

We examine in greater detail the recent proposal of using superconductors for detecting dark matter as light as the warm dark matter limit of O(keV). Detection of suc light dark matter is possible if the entire kinetic energy of the dark matter is extracted in the scattering, and if the experiment is sensitive to O(meV) energy depositions. This is the case for Fermi-degenerate materials in which the Fermi velocity exceeds the dark matter velocity dispersion in the Milky Way of ~10 –3. We focus on a concrete experimental proposal using a superconducting target with a transition edge sensor in ordermore » to detect the small energy deposits from the dark matter scatterings. Considering a wide variety of constraints, from dark matter self-interactions to the cosmic microwave background, we show that models consistent with cosmological/astrophysical and terrestrial constraints are observable with such detectors. A wider range of viable models with dark matter mass below an MeV is available if dark matter or mediator properties (such as couplings or masses) differ at BBN epoch or in stellar interiors from those in superconductors. We also show that metal targets pay a strong in-medium suppression for kinetically mixed mediators; this suppression is alleviated with insulating targets.« less
Dark matter candidates: a ten-point test

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

Taoso, Marco; Masiero, Antonio; Bertone, Gianfranco, E-mail: taoso@pd.infn.it, E-mail: bertone@iap.fr, E-mail: antonio.masiero@pd.infn.it

An extraordinarily rich zoo of non-baryonic dark matter candidates has been proposed over the last three decades. Here we present a ten-point test that a new particle has to pass in order to be considered a viable DM candidate. (I) Does it match the appropriate relic density? (II) Is it cold? (III) Is it neutral? (IV) Is it consistent with BBN? (V) Does it leave stellar evolution unchanged? (VI) Is it compatible with constraints on self-interactions? (VII) Is it consistent with direct DM searches? (VIII) Is it compatible with gamma-ray constraints? (IX) Is it compatible with other astrophysical bounds? (X)more » Can it be probed experimentally?.« less
Precision Measures of the Primordial Abundance of Deuterium

NASA Astrophysics Data System (ADS)

Cooke, Ryan J.; Pettini, Max; Jorgenson, Regina A.; Murphy, Michael T.; Steidel, Charles C.

2014-01-01

We report the discovery of deuterium absorption in the very metal-poor ([Fe/H] = -2.88) damped Lyα system at z abs = 3.06726 toward the QSO SDSS J1358+6522. On the basis of 13 resolved D I absorption lines and the damping wings of the H I Lyα transition, we have obtained a new, precise measure of the primordial abundance of deuterium. Furthermore, to bolster the present statistics of precision D/H measures, we have reanalyzed all of the known deuterium absorption-line systems that satisfy a set of strict criteria. We have adopted a blind analysis strategy (to remove human bias) and developed a software package that is specifically designed for precision D/H abundance measurements. For this reanalyzed sample of systems, we obtain a weighted mean of (D/H)p = (2.53 ± 0.04) × 10-5, corresponding to a universal baryon density 100 Ωb, 0 h 2 = 2.202 ± 0.046 for the standard model of big bang nucleosynthesis (BBN). By combining our measure of (D/H)p with observations of the cosmic microwave background (CMB), we derive the effective number of light fermion species, N eff = 3.28 ± 0.28. We therefore rule out the existence of an additional (sterile) neutrino (i.e., N eff = 4.046) at 99.3% confidence (2.7σ), provided that the values of N eff and of the baryon-to-photon ratio (η10) did not change between BBN and recombination. We also place a strong bound on the neutrino degeneracy parameter, independent of the 4He primordial mass fraction, Y P: ξD = +0.05 ± 0.13 based only on the CMB+(D/H)p observations. Combining this value of ξD with the current best literature measure of Y P, we find a 2σ upper bound on the neutrino degeneracy parameter, |ξ| <= +0.062. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile (VLT program IDs: 68.B-0115(A), 70.A-0425(C), 078.A-0185(A), 085.A-0109(A)), and at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. Keck telescope time was partially granted by NOAO, through the Telescope System Instrumentation Program (TSIP). TSIP is funded by NSF.
One Percent Determination of the Primordial Deuterium Abundance

NASA Astrophysics Data System (ADS)

Cooke, Ryan J.; Pettini, Max; Steidel, Charles C.

2018-03-01

We report a reanalysis of a near-pristine absorption system, located at a redshift {z}abs}=2.52564 toward the quasar Q1243+307, based on the combination of archival and new data obtained with the HIRES echelle spectrograph on the Keck telescope. This absorption system, which has an oxygen abundance [O/H] = ‑2.769 ± 0.028 (≃1/600 of the solar abundance), is among the lowest metallicity systems currently known where a precise measurement of the deuterium abundance is afforded. Our detailed analysis of this system concludes, on the basis of eight D I absorption lines, that the deuterium abundance of this gas cloud is {log}}10({{D}}/{{H}})=-4.622+/- 0.015, which is in very good agreement with the results previously reported by Kirkman et al., but with an improvement on the precision of this single measurement by a factor of ∼3.5. Combining this new estimate with our previous sample of six high precision and homogeneously analyzed D/H measurements, we deduce that the primordial deuterium abundance is {log}}10{({{D}}/{{H}})}{{P}}=-4.5974+/- 0.0052 or, expressed as a linear quantity, {10}5{({{D}}/{{H}})}{{P}}=2.527+/- 0.030; this value corresponds to a one percent determination of the primordial deuterium abundance. Combining our result with a big bang nucleosynthesis (BBN) calculation that uses the latest nuclear physics input, we find that the baryon density derived from BBN agrees to within 2σ of the latest results from the Planck cosmic microwave background data. Based on observations collected at the W.M. Keck Observatory which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W.M. Keck Foundation.

Gallium compounds for the design of (nano)radiophamarceuticals

NASA Astrophysics Data System (ADS)

Silva, Francisco Franca A. C.

The work presented in this thesis focus on the design of targeted nanosized and molecular tools, for the design of gallium radiopharmaceuticals with potential application in cancer theranostics. The first part describes gold nanoparticles (AuNPs) stabilized with thiolated derivatives of acyclic and macrocyclic chelators, and functionalized with bioactive peptides for specific targeting of Gastrin Releasing Peptide (GRP) and Epidermal Growth Factor (EGF) receptors. For GRPr targeting, the AuNPs were decorated with a bombesin (BBN) analog and stabilized with derivatives of diethylene triamine pentaacetic acid (DTPA) or 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelators for 67Ga complexation. From the evaluated radiolabeled nanoconstructs, the ones containing a dithioctic derivative of BBN and a thiolated DOTA chelator is the most promising one for the design of 67Ga (nano)radiopharmaceuticals, due to its high in vitro/in vivo stability, high cellular internalization in GRPr-positive PC3 cells, and significant tumor uptake in prostate cancer tumor xenografts. For EGFr targeting, the AuNPs were decorated with GE-11 peptide that was incorporated in a thiolated DOTA derivative. The resulting AuNPs were labeled with 67Ga using pre- and post-labeling approaches. Those obtained based on the pre-labeling approach showed an enhanced in vitro stability towards release of 67Ga while maintaining a high cellular internalization in A431 cells overexpressing EGFr. The second part describes new N4O2-donor acyclic chelators of the Schiff base type and the respective reduced amines, which contain pyridyl or pyrazolyl coordinating units at the central nitrogen atom of diethylenetriamine and phenol groups introduced at the terminal amines. The Schiff bases undergo decomposition reactions, while the corresponding amine derivatives give well defined monocationic Ga(III) complexes. However, only a pyridyl-containing amine derivative was able to effectively coordinate 67Ga. Biodistribution studies in mice showed that the corresponding radiocomplex displays a high in vivo stability and favourable pharmacokinetics, being a good candidate for further evaluation in radiopharmaceutical research.
Neutrino mixing, oscillations and decoherence in astrophysics and cosmology

NASA Astrophysics Data System (ADS)

Ho, Chiu Man

2007-08-01

This thesis focuses on a finite-temperature field-theoretical treatment of neutrino oscillations in hot and dense media. By implementing the methods of real-time non-equilibrium field theory, we study the dynamics of neutrino mixing, oscillations, decoherence and relaxation in astrophysical and cosmological environments. We first study neutrino oscillations in the early universe in the temperature regime prior to the epoch of Big Bang Nucleosynthesis (BBN). The dispersion relations and mixing angles in the medium are found to be helicity-dependent, and a resonance like the Mikheyev-Smirnov- Wolfenstein (MSW) effect is realized. The oscillation time scales are found to be longer near a resonance and shorter for off-resonance high-energy neutrinos. We then investigate the space-time propagation of neutrino wave-packets just before BBN. A phenomenon of " frozen coherence " is found to occur if the longitudinal dispersion catches up with the progressive separation between the mass eigenstates, before the coherence time limit has been reached. However, the transverse dispersion occurs at a much shorter scale than all other possible time scales in the medium, resulting in a large suppression in the transition probabilities from electron-neutrino to muon-neutrino. We also explore the possibility of charged lepton mixing as a consequence of neutrino mixing in the early Universe. We find that charged leptons, like electrons and muons, can mix and oscillate resonantly if there is a large lepton asymmetry in the neutrino sector. We study sterile neutrino production in the early Universe via active-sterile oscillations. We provide a quantum field theoretical reassessment of the quantum Zeno suppression on the active-to-sterile transition probability and its time average. We determine the complete conditions for quantum Zeno suppression. Finally, we examine the interplay between neutrino mixing, oscillations and equilibration in a thermal medium, and the corresponding non-equilibrium dynamics. The equilibrium density matrix is found to be nearly diagonal in the basis of eigenstates of an effective Hamiltonian that includes self-energy corrections in the medium.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Bae, Kyu Jung; Baer, Howard; Serce, Hasan

The supersymmetrized DFSZ axion model is highly motivated not only because it offers solutions to both the gauge hierarchy and strong CP problems, but also because it provides a solution to the SUSY μ-problem which naturally allows for a Little Hierarchy. We compute the expected mixed axion-neutralino dark matter abundance for the SUSY DFSZ axion model in two benchmark cases—a natural SUSY model with a standard neutralino underabundance (SUA) and an mSUGRA/CMSSM model with a standard overabundance (SOA). Our computation implements coupled Boltzmann equations which track the radiation density along with neutralino, axion, axion CO (produced via coherent oscillations), saxion,more » saxion CO, axino and gravitino densities. In the SUSY DFSZ model, axions, axinos and saxions go through the process of freeze-in—in contrast to freeze-out or out-of-equilibrium production as in the SUSY KSVZ model—resulting in thermal yields which are largely independent of the re-heat temperature. We find the SUA case with suppressed saxion-axion couplings (ξ=0) only admits solutions for PQ breaking scale f{sub a}∼< 6× 10{sup 12} GeV where the bulk of parameter space tends to be axion-dominated. For SUA with allowed saxion-axion couplings (ξ =1), then f{sub a} values up to ∼ 10{sup 14} GeV are allowed. For the SOA case, almost all of SUSY DFSZ parameter space is disallowed by a combination of overproduction of dark matter, overproduction of dark radiation or violation of BBN constraints. An exception occurs at very large f{sub a}∼ 10{sup 15}–10{sup 16} GeV where large entropy dilution from CO-produced saxions leads to allowed models.« less
Vacuum dynamics in the Universe versus a rigid Λ=const.

NASA Astrophysics Data System (ADS)

Solà, Joan; Gómez-Valent, Adrià; de Cruz Pérez, Javier

2017-07-01

In this year, in which we celebrate 100 years of the cosmological term, Λ, in Einstein’s gravitational field equations, we are still facing the crucial question whether Λ is truly a fundamental constant or a mildly evolving dynamical variable. After many theoretical attempts to understand the meaning of Λ, and in view of the enhanced accuracy of the cosmological observations, it seems now mandatory that this issue should be first settled empirically before further theoretical speculations on its ultimate nature. In this review, we summarize the situation of some of these studies. Devoted analyses made recently show that the Λ = const. hypothesis, despite being the simplest, may well not be the most favored one. The overall fit to the cosmological observables SNIa+BAO+H(z)+LSS+BBN+CMB single out the class of “running” vacuum models (RVMs), in which Λ = Λ(H) is an affine power-law function of the Hubble rate. It turns out that the performance of the RVM as compared to the “concordance” ΛCDM model (with Λ = const.) is much better. The evidence in support of the RVM may reach ˜ 4σ c.l., and is bolstered with Akaike and Bayesian criteria providing strong evidence in favor of the RVM option. We also address the implications of this framework on the tension between the CMB and local measurements of the current Hubble parameter.
Quark mass variations of nuclear forces, BBN, and all that

NASA Astrophysics Data System (ADS)

Meissner, Ulf-G.

2014-03-01

In this talk, I discuss the modifications of the nuclear forces due to variations of the light quark masses and of the fine structure constant. This is based on the chiral nuclear effective field theory, that successfully describes a large body of data. The generation of the light elements in the Big Bang Nucleosynthesis provides important constraints on these modifications. In addition, I discuss the role of the anthropic principle in the triple-alpha process that underlies carbon and oxygen generation in hot stars. It appears that a fine-tuning of the quark masses and the fine structure constant within 2 to 3 per cent is required to make life on Earth viable. Supported in part by DFG, HGF and the BMBF.
Prediction of drilling site-specific interaction of industrial acoustic stimuli and endangered whales: Beaufort Sea (1985). Final report, July 1985-March 1986

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

Miles, P.R.; Malme, C.I.; Shepard, G.W.

1986-10-01

Research was performed during the first year (1985) of the two-year project investigating potential responsiveness of bowhead and gray whales to underwater sounds associated with offshore oil-drilling sites in the Alaskan Beaufort Sea. The underwater acoustic environment and sound propagation characteristics of five offshore sites were determined. Estimates of industrial noise levels versus distance from those sites are provided. LGL Ltd. (bowhead) and BBN (gray whale) jointly present zones of responsiveness of these whales to typical underwater sounds (drillship, dredge, tugs, drilling at gravel island). An annotated bibliography regarding the potential effects of offshore industrial noise on bowhead whales inmore » the Beaufort Sea is included.« less
Ambiphilic Frustrated Lewis Pair Exhibiting High Robustness and Reversible Water Activation: Towards the Metal-Free Hydrogenation of Carbon Dioxide.

PubMed

Rochette, Étienne; Courtemanche, Marc-André; Pulis, Alexander P; Bi, Wenhua; Fontaine, Frédéric-Georges

2015-06-29

The synthesis and structural characterization of a phenylene-bridged Frustrated Lewis Pair (FLP) having a 2,2,6,6‑tetramethylpiperidine (TMP) as the Lewis base and a 9-borabicyclo[3.3.1]nonane (BBN) as the Lewis acid is reported. This FLP exhibits unique robustness towards the products of carbon dioxide hydrogenation. The compound shows reversible splitting of water, formic acid and methanol while no reaction is observed in the presence of excess formaldehyde. The molecule is incredibly robust, showing little sign of degradation after heating at 80 °C in benzene with 10 equiv. of formic acid for 24 h. The robustness of the system could be exploited in the design of metal-free catalysts for the hydrogenation of carbon dioxide.
N-Heterocyclic Olefins as Robust Organocatalyst for the Chemical Conversion of Carbon Dioxide to Value-Added Chemicals.

PubMed

Saptal, Vitthal B; Bhanage, Bhalchandra M

2016-08-09

In this report, the activity of N-heterocyclic olefins (NHOs) as a newly emerging class of organocatalyst is investigated for the chemical fixation of carbon dioxide through reactions with aziridines to form oxazolidinones and the N-formylation of amines with polymethylhydrosiloxane (PMHS) or 9-borabicyclo[3.3.1]nonane (9-BBN) as the reducing agent under mild conditions. The exocyclic carbon atoms of NHOs are highly nucleophilic owing to the electron-donating ability of the two nitrogen atoms. This high nucleophilicity of the NHOs activates CO2 molecules to form zwitterionic NHO-carboxylate (NHO-CO2 ) adducts, which are active in formylation reactions as well as the carboxylation of aziridines to oxazolidinones. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A heterodimeric [RGD-Glu-[(64)Cu-NO2A]-6-Ahx-RM2] αvβ3/GRPr-targeting antagonist radiotracer for PET imaging of prostate tumors.

PubMed

Durkan, Kubra; Jiang, Zongrun; Rold, Tammy L; Sieckman, Gary L; Hoffman, Timothy J; Bandari, Rajendra Prasad; Szczodroski, Ashley F; Liu, Liqin; Miao, Yubin; Reynolds, Tamila Stott; Smith, Charles J

2014-02-01

In the present study, we describe a (64)Cu-radiolabeled heterodimeric peptide conjugate for dual αvβ3/GRPr (αvβ3 integrin/gastrin releasing peptide receptor) targeting of the form [RGD-Glu-[(64)Cu-NO2A]-6-Ahx-RM2] (RGD: the amino acid sequence [Arg-Gly-Asp], a nonregulatory peptide used for αvβ3 integrin receptor targeting; Glu: glutamic acid; NO2A: 1,4,7-triazacyclononane-1,4-diacetic acid; 6-Ahx: 6-amino hexanoic acid; and RM2: (D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH2), an antagonist analogue of bombesin (BBN) peptide used for GRPr targeting). RGD-Glu-6Ahx-RM2] was conjugated to a NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid) complexing agent to produce [RGD-Glu-[NO2A]-6-Ahx-RM2], which was purified by reversed-phase high-performance liquid chromatography (RP-HPLC) and characterized by electrospray ionization-mass spectrometry (ESI-MS). Radiolabeling of the conjugate with (64)Cu produced [RGD-Glu-[(64)Cu-NO2A]-6-Ahx-RM2 in high radiochemical yield (≥95%). In vivo behavior of the radiolabeled peptide conjugate was investigated in normal CF-1 mice and in the PC-3 human prostate cancer experimental model. A competitive displacement receptor binding assay in human prostate PC-3 cells using (125)I-[Tyr(4)]BBN as the radioligand showed high binding affinity of [RGD-Glu-[(nat)Cu-NO2A]-6-Ahx-RM2] conjugate for the GRPr (3.09±0.34 nM). A similar assay in human, glioblastoma U87-MG cells using (125)I-Echistatin as the radioligand indicated a moderate receptor-binding affinity for the αvβ3 integrin (518±37.5 nM). In vivo studies of [RGD-Glu-[(64)Cu-NO2A]-6-Ahx-RM2] showed high accumulation (4.86±1.01 %ID/g, 1h post-intravenous injection (p.i.)) and prolonged retention (4.26±1.23 %ID/g, 24h p.i.) of tracer in PC-3 tumor-bearing mice. Micro-positron emission tomography (microPET) molecular imaging studies produced high-quality, high contrast images in PC-3 tumor-bearing mice at 4h p.i. The favorable pharmacokinetics and enhanced tumor uptake of (64)Cu-NOTA-RGD-Glu-6Ahx-RM2 warrant further investigations for dual integrin and GRPr-positive tumor imaging and possible radiotherapy. Copyright © 2014 Elsevier Inc. All rights reserved.
Challenging the cosmological constant

NASA Astrophysics Data System (ADS)

Kaloper, Nemanja

2007-09-01

We outline a dynamical dark energy scenario whose signatures may be simultaneously tested by astronomical observations and laboratory experiments. The dark energy is a field with slightly sub-gravitational couplings to matter, a logarithmic self-interaction potential with a scale tuned to ˜10 eV, as is usual in quintessence models, and an effective mass m influenced by the environmental energy density. Its forces may be suppressed just below the current bounds by the chameleon-like mimicry, whereby only outer layers of mass distributions, of thickness 1/m, give off appreciable long range forces. After inflation and reheating, the field is relativistic, and attains a Planckian expectation value before Hubble friction freezes it. This can make gravity in space slightly stronger than on Earth. During the matter era, interactions with nonrelativistic matter dig a minimum close to the Planck scale. However, due to its sub-gravitational matter couplings the field will linger away from this minimum until the matter energy density dips below ˜10 eV. Then it starts to roll to the minimum, driving a period of cosmic acceleration. Among the signatures of this scenario may be dark energy equation of state w≠-1, stronger gravity in dilute mediums, that may influence BBN and appear as an excess of dark matter, and sub-millimeter corrections to Newton's law, close to the present laboratory limits.
Theranostic Perspectives in Prostate Cancer with the Gastrin-Releasing Peptide Receptor Antagonist NeoBOMB1: Preclinical and First Clinical Results.

PubMed

Nock, Berthold A; Kaloudi, Aikaterini; Lymperis, Emmanouil; Giarika, Athina; Kulkarni, Harshad R; Klette, Ingo; Singh, Aviral; Krenning, Eric P; de Jong, Marion; Maina, Theodosia; Baum, Richard P

2017-01-01

We recently introduced the potent gastrin-releasing peptide receptor (GRPR) antagonist 68 Ga-SB3 ( 68 Ga-DOTA-p-aminomethylaniline-diglycolic acid-DPhe-Gln-Trp-Ala-Val-Gly-His-Leu-NHEt), showing excellent tumor localizing efficacy in animal models and in patients. By replacement of the C-terminal Leu 13 -Met 14 -NH 2 dipeptide of SB3 by Sta 13 -Leu 14 -NH 2 , the novel GRPR antagonist NeoBOMB1 was generated and labeled with different radiometals for theranostic use. We herein report on the biologic profile of resulting 67/68 Ga-, 111 In-, and 177 Lu-NeoBOMB1 radioligands in GRPR-expressing cells and mouse models. The first evidence of prostate cancer lesion visualization in men using 68 Ga-NeoBOMB1 and PET/CT is also presented. NeoBOMB1 was radiolabeled with 67/68 Ga, 111 In, and 177 Lu according to published protocols. The respective metalated species nat Ga-, nat In-, and nat Lu-NeoBOMB1 were also synthesized and used in competition binding experiments against [ 125 I-Tyr 4 ]BBN in GRPR-positive PC-3 cell membranes. Internalization of 67 Ga-, 111 In-, and 177 Lu-NeoBOMB1 radioligands was studied in PC-3 cells at 37°C, and their metabolic stability in peripheral mouse blood was determined by high-performance liquid chromatography analysis of blood samples. Biodistribution was performed by injecting a 67 Ga-, 111 In-, or 177 Lu-NeoBOMB1 bolus (74, 74, or 370 kBq, respectively, 100 μL, 10 pmol total peptide ± 40 nmol Tyr 4 -BBN: for in vivo GRPR blockade) in severe combined immunodeficiency mice bearing PC-3 xenografts. PET/CT images with 68 Ga-NeoBOMB1 were acquired in prostate cancer patients. NeoBOMB1 and nat Ga-, nat In-, and nat Lu-NeoBOMB1 bound to GRPR with high affinity (half maximal inhibitory concentration, 1-2 nM). 67 Ga-, 111 In-, and 177 Lu-NeoBOMB1 specifically and strongly bound on the cell membrane of PC-3 cells displaying low internalization, as expected for receptor antagonists. They showed excellent metabolic stability in peripheral mouse blood (>95% intact at 5 min after injection). After injection in mice, all 3 ( 67 Ga-, 111 In-, and 177 Lu-NeoBOMB1) showed comparably high and GRPR-specific uptake in the PC-3 xenografts (e.g., 30.6 ± 3.9, 28.6 ± 6.0, and >35 percentage injected dose per gram at 4 h after injection, respectively), clearing from background predominantly via the kidneys. During a translational study in prostate cancer patients, 68 Ga-NeoBOMB1 rapidly localized in pathologic lesions, achieving high-contrast imaging. The GRPR antagonist radioligands 67 Ga-, 111 In-, and 177 Lu-NeoBOMB1, independent of the radiometal applied, have shown comparable behavior in prostate cancer models, in favor of future theranostic use in GRPR-positive cancer patients. Such translational prospects were further supported by the successful visualization of prostate cancer lesions in men using 68 Ga-NeoBOMB1 and PET/CT. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.
Experimental setup and procedure for the measurement of the 7Be(n,p)7Li reaction at n_TOF

NASA Astrophysics Data System (ADS)

Barbagallo, M.; Andrzejewski, J.; Mastromarco, M.; Perkowski, J.; Damone, L. A.; Gawlik, A.; Cosentino, L.; Finocchiaro, P.; Maugeri, E. A.; Mazzone, A.; Dressler, R.; Heinitz, S.; Kivel, N.; Schumann, D.; Colonna, N.; Aberle, O.; Amaducci, S.; Audouin, L.; Bacak, M.; Balibrea, J.; Bečvář, F.; Bellia, G.; Berthoumieux, E.; Billowes, J.; Bosnar, D.; Brown, A.; Caamaño, M.; Calviño, F.; Calviani, M.; Cano-Ott, D.; Cardella, R.; Casanovas, A.; Cerutti, F.; Chen, Y. H.; Chiaveri, E.; Cortés, G.; Cortés-Giraldo, M. A.; Cristallo, S.; Diakaki, M.; Dietz, M.; Domingo-Pardo, C.; Dupont, E.; Durán, I.; Fernández-Domínguez, B.; Ferrari, A.; Ferreira, P.; Furman, V.; Göbel, K.; García, A. R.; Gilardoni, S.; Glodariu, T.; Gonçalves, I. F.; González-Romero, E.; Griesmayer, E.; Guerrero, C.; Gunsing, F.; Harada, H.; Heyse, J.; Jenkins, D. G.; Jericha, E.; Johnston, K.; Käppeler, F.; Kadi, Y.; Kalamara, A.; Kavrigin, P.; Kimura, A.; Kokkoris, M.; Krtička, M.; Kurtulgil, D.; Leal-Cidoncha, E.; Lederer, C.; Leeb, H.; Lerendegui-Marco, J.; Lo Meo, S.; Lonsdale, S. J.; Macina, D.; Manna, A.; Marganiec, J.; Martínez, T.; Martins-Correia, J. G.; Masi, A.; Massimi, C.; Mastinu, P.; Mendoza, E.; Mengoni, A.; Milazzo, P. M.; Mingrone, F.; Musumarra, A.; Negret, A.; Nolte, R.; Oprea, A.; Pappalardo, A. D.; Patronis, N.; Pavlik, A.; Piscopo, M.; Porras, I.; Praena, J.; Quesada, J. M.; Radeck, D.; Rauscher, T.; Reifarth, R.; Robles, M. S.; Rubbia, C.; Ryan, J. A.; Sabaté-Gilarte, M.; Saxena, A.; Schell, J.; Schillebeeckx, P.; Sedyshev, P.; Smith, A. G.; Sosnin, N. V.; Stamatopoulos, A.; Tagliente, G.; Tain, J. L.; Tarifeño-Saldivia, A.; Tassan-Got, L.; Valenta, S.; Vannini, G.; Variale, V.; Vaz, P.; Ventura, A.; Vlachoudis, V.; Vlastou, R.; Wallner, A.; Warren, S.; Weiss, C.; Woods, P. J.; Wright, T.; Žugec, P.

2018-04-01

Following the completion of the second neutron beam line and the related experimental area (EAR2) at the n_TOF spallation neutron source at CERN, several experiments were planned and performed. The high instantaneous neutron flux available in EAR2 allows to investigate neutron induced reactions with charged particles in the exit channel even employing targets made out of small amounts of short-lived radioactive isotopes. After the successful measurement of the 7Be(n, α) α cross section, the 7Be(n,p)7Li reaction was studied in order to provide still missing cross section data of relevance for Big Bang Nucleosynthesis (BBN), in an attempt to find a solution to the cosmological Lithium abundance problem. This paper describes the experimental setup employed in such a measurement and its characterization.
Parallel consistent labeling algorithms

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

Samal, A.; Henderson, T.

Mackworth and Freuder have analyzed the time complexity of several constraint satisfaction algorithms. Mohr and Henderson have given new algorithms, AC-4 and PC-3, for arc and path consistency, respectively, and have shown that the arc consistency algorithm is optimal in time complexity and of the same order space complexity as the earlier algorithms. In this paper, they give parallel algorithms for solving node and arc consistency. They show that any parallel algorithm for enforcing arc consistency in the worst case must have O(na) sequential steps, where n is number of nodes, and a is the number of labels per node.more » They give several parallel algorithms to do arc consistency. It is also shown that they all have optimal time complexity. The results of running the parallel algorithms on a BBN Butterfly multiprocessor are also presented.« less
Supergravity models with 50-100 TeV scalars, supersymmetry discovery at the LHC, and gravitino decay constraints

NASA Astrophysics Data System (ADS)

Aboubrahim, Amin; Nath, Pran

2017-10-01

We investigate the possibility of testing supergravity unified models with scalar masses in the range 50-100 TeV and much lighter gaugino masses at the Large Hadron Collider. The analysis is carried out under the constraints that models produce the Higgs boson mass consistent with experiment and also produce dark matter consistent with WMAP and PLANCK experiments. A set of benchmarks in the supergravity parameter space are investigated using a combination of signal regions which are optimized for the model set. It is found that some of the models with scalar masses in the 50-100 TeV mass range are discoverable with as little as 100 fb-1 of integrated luminosity and should be accessible at the LHC RUN II. The remaining benchmark models are found to be discoverable with less than 1000 fb-1 of integrated luminosity and thus testable in the high luminosity era of the LHC, i.e., at HL-LHC. It is shown that scalar masses in the 50-100 TeV range but gaugino masses much lower in mass produce unification of gauge coupling constants, consistent with experimental data at low scale, with as good an accuracy (and sometimes even better) as models with low [O (1 ) TeV ] weak scale supersymmetry. Decay of the gravitinos for the supergravity model benchmarks are investigated and it is shown that they decay before the big bang nucleosynthesis (BBN). Further, we investigate the nonthermal production of neutralinos from gravitino decay and it is found that the nonthermal contribution to the dark matter relic density is negligible relative to that from the thermal production of neutralinos for reheat temperature after inflation up to 1 09 GeV . An analysis of the direct detection of dark matter for supergravity grand unified models (SUGRA) with high scalar masses is also discussed. SUGRA models with scalar masses in the range 50-100 TeV have several other attractive features such as they help alleviate the supersymmetric C P problem and help suppress proton decay from baryon and lepton number violating dimension five operators.
Innovative patient-centered skills training addressing challenging issues in cancer communications: Using patient's stories that teach.

PubMed

Bishop, Thomas W; Gorniewicz, James; Floyd, Michael; Tudiver, Fred; Odom, Amy; Zoppi, Kathy

2016-05-01

This workshop demonstrated the utility of a patient-centered web-based/digital Breaking Bad News communication training module designed to educate learners of various levels and disciplines. This training module is designed for independent, self-directed learning as well as group instruction. These interactive educational interventions are based upon video-recorded patient stories. Curriculum development was the result of an interdisciplinary, collaborative effort involving faculty from the East Tennessee State University (ETSU) Graduate Storytelling Program and the departments of Family and Internal Medicine at the James H. Quillen College of Medicine. The specific goals of the BBN training module are to assist learners in: (1) understanding a five-step patient-centered model that is based upon needs, preferences, and expectations of patients with cancer and (2) individualizing communication that is consistent with patient preferences in discussing emotions, informational detail, prognosis and timeline, and whether or not to discuss end-of-life issues. The pedagogical approach to the training module is to cycle through Emotional Engagement, Data, Modeled Practices, Adaptation Opportunities, and Feedback. The communication skills addressed are rooted in concepts found within the Reaching Common Ground communication training. A randomized control study investigating the effectiveness of the Breaking Bad News module found that medical students as well as resident physicians improved their communication skills as measured by an Objective Structured Clinical Examination. Four other similarly designed modules were also created: Living Through Treatment, Transitions: From Curable to Treatable/From Treatable to End-of-Life, Spirituality, and Family. © The Author(s) 2016.
Inhibition of angiogenesis by leflunomide via targeting the soluble ephrin-A1/EphA2 system in bladder cancer.

PubMed

Chu, Maolin; Zhang, Chunying

2018-01-24

Angiogenesis plays an important role in bladder cancer (BCa). The immunosuppressive drug leflunomide has attracted worldwide attention. However, the effects of leflunomide on angiogenesis in cancer remain unclear. Here, we report the increased expression of soluble ephrin-A1 (sEphrin-A1) in supernatants of BCa cell lines (RT4, T24, and TCCSUP) co-cultured with human umbilical vein endothelial cells (HUVECs) compared with that in immortalized uroepithelial cells (SV-HUC-1) co-cultured with HUVECs. sEphrin-A1 is released from BCa cells as a monomeric protein that is a functional form of the ligand. The co-culture supernatants containing sEphrin-A1 caused the internalization and down-regulation of EphA2 on endothelial cells and dramatic functional activation of HUVECs. This sEphrin-A1/EphA2 system is mainly functional in regulating angiogenesis in BCa tissue. We showed that leflunomide (LEF) inhibited angiogenesis in a N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN)-induced bladder carcinogenesis model and a tumor xenograft model, as well as in BCa cell and HUVEC co-culture systems, via significant inhibition of the sEphrin-A1/EphA2 system. Ephrin-A1 overexpression could partially reverse LEF-induced suppression of angiogenesis and subsequent tumor growth inhibition. Thus, LEF has a significant anti-angiogenesis effect on BCa cells and BCa tissue via its inhibition of the functional angiogenic sEphrin-A1/EphA2 system and may have potential for treating BCa beyond immunosuppressive therapy.
Saxion cosmology for thermalized gravitino dark matter

DOE PAGES

Co, Raymond T.; D’Eramo, Francesco; Hall, Lawrence J.; ...

2017-07-26

In all supersymmetric theories, gravitinos, with mass suppressed by the Planck scale, are an obvious candidate for dark matter; but if gravitinos ever reached thermal equilibrium, such dark matter is apparently either too abundant or too hot, and is excluded. However, in theories with an axion, a saxion condensate is generated during an early era of cosmological history and its late decay dilutes dark matter. We show that such dilution allows previously thermalized gravitinos to account for the observed dark matter over very wide ranges of gravitino mass, keV < m 3/2 < TeV, axion decay constant, 10 9 GeVmore » < f a < 10 16 GeV, and saxion mass, 10 MeV < m s < 100 TeV. Constraints on this parameter space are studied from BBN, supersymmetry breaking, gravitino and axino production from freeze-in and saxion decay, and from axion production from both misalignment and parametric resonance mechanisms. Large allowed regions of (m 3/2, f a, m s) remain, but differ for DFSZ and KSVZ theories. Superpartner production at colliders may lead to events with displaced vertices and kinks, and may contain saxions decaying to (WW, ZZ, hh), gg, γγ or a pair of Standard Model fermions. In conclusion, freeze-in may lead to a sub-dominant warm component of gravitino dark matter, and saxion decay to axions may lead to dark radiation.« less
Saxion cosmology for thermalized gravitino dark matter

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

Co, Raymond T.; D’Eramo, Francesco; Hall, Lawrence J.

In all supersymmetric theories, gravitinos, with mass suppressed by the Planck scale, are an obvious candidate for dark matter; but if gravitinos ever reached thermal equilibrium, such dark matter is apparently either too abundant or too hot, and is excluded. However, in theories with an axion, a saxion condensate is generated during an early era of cosmological history and its late decay dilutes dark matter. We show that such dilution allows previously thermalized gravitinos to account for the observed dark matter over very wide ranges of gravitino mass, keV < m 3/2 < TeV, axion decay constant, 10 9 GeVmore » < f a < 10 16 GeV, and saxion mass, 10 MeV < m s < 100 TeV. Constraints on this parameter space are studied from BBN, supersymmetry breaking, gravitino and axino production from freeze-in and saxion decay, and from axion production from both misalignment and parametric resonance mechanisms. Large allowed regions of (m 3/2, f a, m s) remain, but differ for DFSZ and KSVZ theories. Superpartner production at colliders may lead to events with displaced vertices and kinks, and may contain saxions decaying to (WW, ZZ, hh), gg, γγ or a pair of Standard Model fermions. In conclusion, freeze-in may lead to a sub-dominant warm component of gravitino dark matter, and saxion decay to axions may lead to dark radiation.« less
Origin of ΔN{sub eff} as a result of an interaction between dark radiation and dark matter

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

Bjaelde, Ole Eggers; Das, Subinoy; Moss, Adam, E-mail: oeb@phys.au.dk, E-mail: subinoy@physik.rwth-aachen.de, E-mail: Adam.Moss@nottingham.ac.uk

2012-10-01

Results from the Wilkinson Microwave Anisotropy Probe (WMAP), Atacama Cosmology Telescope (ACT) and recently from the South Pole Telescope (SPT) have indicated the possible existence of an extra radiation component in addition to the well known three neutrino species predicted by the Standard Model of particle physics. In this paper, we explore the possibility of the apparent extra dark radiation being linked directly to the physics of cold dark matter (CDM). In particular, we consider a generic scenario where dark radiation, as a result of an interaction, is produced directly by a fraction of the dark matter density effectively decayingmore » into dark radiation. At an early epoch when the dark matter density is negligible, as an obvious consequence, the density of dark radiation is also very small. As the Universe approaches matter radiation equality, the dark matter density starts to dominate thereby increasing the content of dark radiation and changing the expansion rate of the Universe. As this increase in dark radiation content happens naturally after Big Bang Nucleosynthesis (BBN), it can relax the possible tension with lower values of radiation degrees of freedom measured from light element abundances compared to that of the CMB. We numerically confront this scenario with WMAP+ACT and WMAP+SPT data and derive an upper limit on the allowed fraction of dark matter decaying into dark radiation.« less
Reciprocity-based experimental determination of dynamic forces and moments: A feasibility study

NASA Technical Reports Server (NTRS)

Ver, Istvan L.; Howe, Michael S.

1994-01-01

BBN Systems and Technologies has been tasked by the Georgia Tech Research Center to carry Task Assignment No. 7 for the NASA Langley Research Center to explore the feasibility of 'In-Situ Experimental Evaluation of the Source Strength of Complex Vibration Sources Utilizing Reciprocity.' The task was carried out under NASA Contract No. NAS1-19061. In flight it is not feasible to connect the vibration sources to their mounting points on the fuselage through force gauges to measure dynamic forces and moments directly. However, it is possible to measure the interior sound field or vibration response caused by these structureborne sound sources at many locations and invoke principle of reciprocity to predict the dynamic forces and moments. The work carried out in the framework of Task 7 was directed to explore the feasibility of reciprocity-based measurements of vibration forces and moments.

Boric ester-type molten salt via dehydrocoupling reaction.

PubMed

Matsumi, Noriyoshi; Toyota, Yoshiyuki; Joshi, Prerna; Puneet, Puhup; Vedarajan, Raman; Takekawa, Toshihiro

2014-11-14

Novel boric ester-type molten salt was prepared using 1-(2-hydroxyethyl)-3-methylimidazolium chloride as a key starting material. After an ion exchange reaction of 1-(2-hydroxyethyl)-3-methylimidazolium chloride with lithium (bis-(trifluoromethanesulfonyl) imide) (LiNTf2), the resulting 1-(2-hydroxyethyl)-3-methylimidazolium NTf2 was reacted with 9-borabicyclo[3.3.1]nonane (9-BBN) to give the desired boric ester-type molten salt in a moderate yield. The structure of the boric ester-type molten salt was supported by 1H-, 13C-, 11B- and 19F-NMR spectra. In the presence of two different kinds of lithium salts, the matrices showed an ionic conductivity in the range of 1.1 × 10⁻⁴-1.6 × 10⁻⁵ S cm⁻¹ at 51 °C. This was higher than other organoboron molten salts ever reported.
Boric Ester-Type Molten Salt via Dehydrocoupling Reaction

PubMed Central

Matsumi, Noriyoshi; Toyota, Yoshiyuki; Joshi, Prerna; Puneet, Puhup; Vedarajan, Raman; Takekawa, Toshihiro

2014-01-01

Novel boric ester-type molten salt was prepared using 1-(2-hydroxyethyl)-3-methylimidazolium chloride as a key starting material. After an ion exchange reaction of 1-(2-hydroxyethyl)-3-methylimidazolium chloride with lithium (bis-(trifluoromethanesulfonyl) imide) (LiNTf2), the resulting 1-(2-hydroxyethyl)-3-methylimidazolium NTf2 was reacted with 9-borabicyclo[3.3.1]nonane (9-BBN) to give the desired boric ester-type molten salt in a moderate yield. The structure of the boric ester-type molten salt was supported by 1H-, 13C-, 11B- and 19F-NMR spectra. In the presence of two different kinds of lithium salts, the matrices showed an ionic conductivity in the range of 1.1 × 10−4–1.6 × 10−5 S cm−1 at 51 °C. This was higher than other organoboron molten salts ever reported. PMID:25405738
Hardware for dynamic quantum computing.

PubMed

Ryan, Colm A; Johnson, Blake R; Ristè, Diego; Donovan, Brian; Ohki, Thomas A

2017-10-01

We describe the hardware, gateware, and software developed at Raytheon BBN Technologies for dynamic quantum information processing experiments on superconducting qubits. In dynamic experiments, real-time qubit state information is fed back or fed forward within a fraction of the qubits' coherence time to dynamically change the implemented sequence. The hardware presented here covers both control and readout of superconducting qubits. For readout, we created a custom signal processing gateware and software stack on commercial hardware to convert pulses in a heterodyne receiver into qubit state assignments with minimal latency, alongside data taking capability. For control, we developed custom hardware with gateware and software for pulse sequencing and steering information distribution that is capable of arbitrary control flow in a fraction of superconducting qubit coherence times. Both readout and control platforms make extensive use of field programmable gate arrays to enable tailored qubit control systems in a reconfigurable fabric suitable for iterative development.
Impact analysis of two kinds of failure strategies in Beijing road transportation network

NASA Astrophysics Data System (ADS)

Zhang, Zundong; Xu, Xiaoyang; Zhang, Zhaoran; Zhou, Huijuan

The Beijing road transportation network (BRTN), as a large-scale technological network, exhibits very complex and complicate features during daily periods. And it has been widely highlighted that how statistical characteristics (i.e. average path length and global network efficiency) change while the network evolves. In this paper, by using different modeling concepts, three kinds of network models of BRTN namely the abstract network model, the static network model with road mileage as weights and the dynamic network model with travel time as weights — are constructed, respectively, according to the topological data and the real detected flow data. The degree distribution of the three kinds of network models are analyzed, which proves that the urban road infrastructure network and the dynamic network behavior like scale-free networks. By analyzing and comparing the important statistical characteristics of three models under random attacks and intentional attacks, it shows that the urban road infrastructure network and the dynamic network of BRTN are both robust and vulnerable.
A Complex Network Approach to Distributional Semantic Models

PubMed Central

Utsumi, Akira

2015-01-01

A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940
A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

PubMed Central

Rolls, David A.; Wang, Peng; McBryde, Emma; Pattison, Philippa; Robins, Garry

2015-01-01

We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure. PMID:26555701
Modeling the Citation Network by Network Cosmology

PubMed Central

Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

2015-01-01

Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well. PMID:25807397
Modeling the citation network by network cosmology.

PubMed

Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

2015-01-01

Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.
Engineering technology for networks

NASA Technical Reports Server (NTRS)

Paul, Arthur S.; Benjamin, Norman

1991-01-01

Space Network (SN) modeling and evaluation are presented. The following tasks are included: Network Modeling (developing measures and metrics for SN, modeling of the Network Control Center (NCC), using knowledge acquired from the NCC to model the SNC, and modeling the SN); and Space Network Resource scheduling.
A random spatial network model based on elementary postulates

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.
Classification of complex networks based on similarity of topological network features

NASA Astrophysics Data System (ADS)

Attar, Niousha; Aliakbary, Sadegh

2017-09-01

Over the past few decades, networks have been widely used to model real-world phenomena. Real-world networks exhibit nontrivial topological characteristics and therefore, many network models are proposed in the literature for generating graphs that are similar to real networks. Network models reproduce nontrivial properties such as long-tail degree distributions or high clustering coefficients. In this context, we encounter the problem of selecting the network model that best fits a given real-world network. The need for a model selection method reveals the network classification problem, in which a target-network is classified into one of the candidate network models. In this paper, we propose a novel network classification method which is independent of the network size and employs an alignment-free metric of network comparison. The proposed method is based on supervised machine learning algorithms and utilizes the topological similarities of networks for the classification task. The experiments show that the proposed method outperforms state-of-the-art methods with respect to classification accuracy, time efficiency, and robustness to noise.
The early universe as a probe of new physics

NASA Astrophysics Data System (ADS)

Bird, Christopher Shane

The Standard Model of Particle Physics has been verified to unprecedented precision in the last few decades. However there are still phenomena in nature which cannot be explained, and as such new theories will be required. Since terrestrial experiments are limited in both the energy and precision that can be probed, new methods are required to search for signs of physics beyond the Standard Model. In this dissertation, I demonstrate how these theories can be probed by searching for remnants of their effects in the early Universe. In particular I focus on three possible extensions of the Standard Model: the addition of massive neutral particles as dark matter, the addition of charged massive particles, and the existence of higher dimensions. For each new model, I review the existing experimental bounds and the potential for discovering new physics in the next generation of experiments. For dark matter, I introduce six simple models which I have developed, and which involve a minimum amount of new physics, as well as reviewing one existing model of dark matter. For each model I calculate the latest constraints from astrophysics experiments, nuclear recoil experiments, and collider experiments. I also provide motivations for studying sub-GeV mass dark matter, and propose the possibility of searching for light WIMPs in the decay of B-mesons and other heavy particles. For charged massive relics, I introduce and review the recently proposed model of catalyzed Big Bang nucleosynthesis. In particular I review the production of 6Li by this mechanism, and calculate the abundance of 7Li after destruction of 7Be by charged relics. The result is that for certain natural relics CBBN is capable of removing tensions between the predicted and observed 6Li and 7Li abundances which are present in the standard model of BBN. For extra dimensions, I review the constraints on the ADD model from both astrophysics and collider experiments. I then calculate the constraints on this model from Big Bang nucleosynthesis in the early Universe. I also calculate the bounds on this model from Kaluza-Klein gravitons trapped in the galaxy which decay to electron-positron pairs, using the measured 511 keV gamma-ray flux. For each example of new physics, I find that remnants of the early Universe provide constraints on the models which are complementary to the existing constraints from colliders and other terrestrial experiments.
A simple model clarifies the complicated relationships of complex networks

PubMed Central

Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi

2014-01-01

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506
Random graph models of social networks.

PubMed

Newman, M E J; Watts, D J; Strogatz, S H

2002-02-19

We describe some new exactly solvable models of the structure of social networks, based on random graphs with arbitrary degree distributions. We give models both for simple unipartite networks, such as acquaintance networks, and bipartite networks, such as affiliation networks. We compare the predictions of our models to data for a number of real-world social networks and find that in some cases, the models are in remarkable agreement with the data, whereas in others the agreement is poorer, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph.
Studies on the population dynamics of a rumor-spreading model in online social networks

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.
Network structure exploration in networks with node attributes

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

2016-05-01

Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.
Precise Network Modeling of Systems Genetics Data Using the Bayesian Network Webserver.

PubMed

Ziebarth, Jesse D; Cui, Yan

2017-01-01

The Bayesian Network Webserver (BNW, http://compbio.uthsc.edu/BNW ) is an integrated platform for Bayesian network modeling of biological datasets. It provides a web-based network modeling environment that seamlessly integrates advanced algorithms for probabilistic causal modeling and reasoning with Bayesian networks. BNW is designed for precise modeling of relatively small networks that contain less than 20 nodes. The structure learning algorithms used by BNW guarantee the discovery of the best (most probable) network structure given the data. To facilitate network modeling across multiple biological levels, BNW provides a very flexible interface that allows users to assign network nodes into different tiers and define the relationships between and within the tiers. This function is particularly useful for modeling systems genetics datasets that often consist of multiscalar heterogeneous genotype-to-phenotype data. BNW enables users to, within seconds or minutes, go from having a simply formatted input file containing a dataset to using a network model to make predictions about the interactions between variables and the potential effects of experimental interventions. In this chapter, we will introduce the functions of BNW and show how to model systems genetics datasets with BNW.
Human Behavior Modeling in Network Science

DTIC Science & Technology

2010-03-01

in Network Science bringing three distinct research areas together, communication networks, information networks, and social /cognitive networks. The...researchers. A critical part of the social /cognitive network effort is the modeling of human behavior. The modeling efforts range from organizational...behavior to social cognitive trust to explore and refine the theoretical and applied network relationships between and among the human
Generative model selection using a scalable and size-independent complex network classifier

NASA Astrophysics Data System (ADS)

Motallebi, Sadegh; Aliakbary, Sadegh; Habibi, Jafar

2013-12-01

Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree for model selection. Our proposed method, which is named "Generative Model Selection for Complex Networks," outperforms existing methods with respect to accuracy, scalability, and size-independence.
Network traffic behaviour near phase transition point

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-03-01

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.

A general stochastic model for studying time evolution of transition networks

NASA Astrophysics Data System (ADS)

Zhan, Choujun; Tse, Chi K.; Small, Michael

2016-12-01

We consider a class of complex networks whose nodes assume one of several possible states at any time and may change their states from time to time. Such networks represent practical networks of rumor spreading, disease spreading, language evolution, and so on. Here, we derive a model describing the dynamics of this kind of network and a simulation algorithm for studying the network evolutionary behavior. This model, derived at a microscopic level, can reveal the transition dynamics of every node. A numerical simulation is taken as an ;experiment; or ;realization; of the model. We use this model to study the disease propagation dynamics in four different prototypical networks, namely, the regular nearest-neighbor (RN) network, the classical Erdös-Renyí (ER) random graph, the Watts-Strogátz small-world (SW) network, and the Barabási-Albert (BA) scalefree network. We find that the disease propagation dynamics in these four networks generally have different properties but they do share some common features. Furthermore, we utilize the transition network model to predict user growth in the Facebook network. Simulation shows that our model agrees with the historical data. The study can provide a useful tool for a more thorough understanding of the dynamics networks.
A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

2005-01-01

This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.
Inferring general relations between network characteristics from specific network ensembles.

PubMed

Cardanobile, Stefano; Pernice, Volker; Deger, Moritz; Rotter, Stefan

2012-01-01

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their ability to generate networks with large structural variability. In particular, we consider the statistical constraints which the respective construction scheme imposes on the generated networks. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This makes it possible to infer global features from local ones using regression models trained on networks with high generalization power. Our results confirm and extend previous findings regarding the synchronization properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks in good approximation. Finally, we demonstrate on three different data sets (C. elegans neuronal network, R. prowazekii metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models.
Vulnerability of complex networks

NASA Astrophysics Data System (ADS)

Mishkovski, Igor; Biey, Mario; Kocarev, Ljupco

2011-01-01

We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős-Rényi (ER) random networks, Barabási-Albert (BA) model of scale-free networks, Watts-Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.
Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578
Capacity of Heterogeneous Mobile Wireless Networks with D-Delay Transmission Strategy.

PubMed

Wu, Feng; Zhu, Jiang; Xi, Zhipeng; Gao, Kai

2016-03-25

This paper investigates the capacity problem of heterogeneous wireless networks in mobility scenarios. A heterogeneous network model which consists of n normal nodes and m helping nodes is proposed. Moreover, we propose a D-delay transmission strategy to ensure that every packet can be delivered to its destination nodes with limited delay. Different from most existing network schemes, our network model has a novel two-tier architecture. The existence of helping nodes greatly improves the network capacity. Four types of mobile networks are studied in this paper: i.i.d. fast mobility model and slow mobility model in two-dimensional space, i.i.d. fast mobility model and slow mobility model in three-dimensional space. Using the virtual channel model, we present an intuitive analysis of the capacity of two-dimensional mobile networks and three-dimensional mobile networks, respectively. Given a delay constraint D, we derive the asymptotic expressions for the capacity of the four types of mobile networks. Furthermore, the impact of D and m to the capacity of the whole network is analyzed. Our findings provide great guidance for the future design of the next generation of networks.
Modeling online social signed networks

NASA Astrophysics Data System (ADS)

Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

2018-04-01

People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.
Reliable Communication Models in Interdependent Critical Infrastructure Networks

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

Lee, Sangkeun; Chinthavali, Supriya; Shankar, Mallikarjun

Modern critical infrastructure networks are becoming increasingly interdependent where the failures in one network may cascade to other dependent networks, causing severe widespread national-scale failures. A number of previous efforts have been made to analyze the resiliency and robustness of interdependent networks based on different models. However, communication network, which plays an important role in today's infrastructures to detect and handle failures, has attracted little attention in the interdependency studies, and no previous models have captured enough practical features in the critical infrastructure networks. In this paper, we study the interdependencies between communication network and other kinds of critical infrastructuremore » networks with an aim to identify vulnerable components and design resilient communication networks. We propose several interdependency models that systematically capture various features and dynamics of failures spreading in critical infrastructure networks. We also discuss several research challenges in building reliable communication solutions to handle failures in these models.« less
Generative model selection using a scalable and size-independent complex network classifier

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

Motallebi, Sadegh, E-mail: motallebi@ce.sharif.edu; Aliakbary, Sadegh, E-mail: aliakbary@ce.sharif.edu; Habibi, Jafar, E-mail: jhabibi@sharif.edu

2013-12-15

Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree formore » model selection. Our proposed method, which is named “Generative Model Selection for Complex Networks,” outperforms existing methods with respect to accuracy, scalability, and size-independence.« less
Dense power-law networks and simplicial complexes

NASA Astrophysics Data System (ADS)

Courtney, Owen T.; Bianconi, Ginestra

2018-05-01

There is increasing evidence that dense networks occur in on-line social networks, recommendation networks and in the brain. In addition to being dense, these networks are often also scale-free, i.e., their degree distributions follow P (k ) ∝k-γ with γ ∈(1 ,2 ] . Models of growing networks have been successfully employed to produce scale-free networks using preferential attachment, however these models can only produce sparse networks as the numbers of links and nodes being added at each time step is constant. Here we present a modeling framework which produces networks that are both dense and scale-free. The mechanism by which the networks grow in this model is based on the Pitman-Yor process. Variations on the model are able to produce undirected scale-free networks with exponent γ =2 or directed networks with power-law out-degree distribution with tunable exponent γ ∈(1 ,2 ) . We also extend the model to that of directed two-dimensional simplicial complexes. Simplicial complexes are generalization of networks that can encode the many body interactions between the parts of a complex system and as such are becoming increasingly popular to characterize different data sets ranging from social interacting systems to the brain. Our model produces dense directed simplicial complexes with power-law distribution of the generalized out-degrees of the nodes.
Generative models for network neuroscience: prospects and promise

PubMed Central

Betzel, Richard F.

2017-01-01

Network neuroscience is the emerging discipline concerned with investigating the complex patterns of interconnections found in neural systems, and identifying principles with which to understand them. Within this discipline, one particularly powerful approach is network generative modelling, in which wiring rules are algorithmically implemented to produce synthetic network architectures with the same properties as observed in empirical network data. Successful models can highlight the principles by which a network is organized and potentially uncover the mechanisms by which it grows and develops. Here, we review the prospects and promise of generative models for network neuroscience. We begin with a primer on network generative models, with a discussion of compressibility and predictability, and utility in intuiting mechanisms, followed by a short history on their use in network science, broadly. We then discuss generative models in practice and application, paying particular attention to the critical need for cross-validation. Next, we review generative models of biological neural networks, both at the cellular and large-scale level, and across a variety of species including Caenorhabditis elegans, Drosophila, mouse, rat, cat, macaque and human. We offer a careful treatment of a few relevant distinctions, including differences between generative models and null models, sufficiency and redundancy, inferring and claiming mechanism, and functional and structural connectivity. We close with a discussion of future directions, outlining exciting frontiers both in empirical data collection efforts as well as in method and theory development that, together, further the utility of the generative network modelling approach for network neuroscience. PMID:29187640
Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks

PubMed Central

Lähdesmäki, Harri; Hautaniemi, Sampsa; Shmulevich, Ilya; Yli-Harja, Olli

2006-01-01

A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interactions of Boolean networks into the stochastic setting. Dynamic Bayesian networks (DBNs) is a general and versatile model class that is able to represent complex temporal stochastic processes and has also been proposed as a model for gene regulatory systems. In this paper, we concentrate on these two model classes and demonstrate that PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables. The major benefit of introducing the relationships between the models is that it opens up the possibility of applying the standard tools of DBNs to PBNs and vice versa. Hence, the standard learning tools of DBNs can be applied in the context of PBNs, and the inference methods give a natural way of handling the missing values in PBNs which are often present in gene expression measurements. Conversely, the tools for controlling the stationary behavior of the networks, tools for projecting networks onto sub-networks, and efficient learning schemes can be used for DBNs. In other words, the introduced relationships between the models extend the collection of analysis tools for both model classes. PMID:17415411
Oxidative stress as a mechanism of diabetes in diabetic BB prone rats: effect of secoisolariciresinol diglucoside (SDG).

PubMed

Prasad, K

2000-06-01

Secoisolariciresinol diglucoside (SDG) isolated from flaxseed has antioxidant activity and has been shown to prevent hypercholesterolemic atherosclerosis. An investigation was made of the effects of SDG on the development of diabetes in diabetic prone BioBreeding rats (BBdp rats), a model of human type I diabetes [insulin dependent diabetes mellitus (IDDM)] to determine if this type of diabetes is due to oxidative stress and if SDG can prevent the incidence of diabetes. The rats were divided into three groups: Group I, BioBreeding normal rats (BBn rats) (n = 10); group II, BBdp untreated (n = 11); and group III, BBdp treated with SDG 22 mg/kg body wt, orally) (n = 14). Oxidative stress was determined by measuring lipid peroxidation product malondialdehyde (MDA) an index of level of reactive oxygen species in blood and pancreas; and pancreatic chemiluminescence (Pancreatic-CL), a measure of antioxidant reserve. Incidence of diabetes was 72.7% in untreated and 21.4% in SDG-treated group as determined by glycosuria and hyperglycemia. SDG prevented the development of diabetes by approximately 71%. Development of diabetes was associated with an increase in serum and pancreatic MDA and a decrease in antioxidant reserve. Prevention in development of diabetes by SDG was associated with a decrease in serum and pancreatic-MDA and an increase in antioxidant reserve. These results suggest that IDDM is mediated through oxidative stress and that SDG prevents the development of diabetes.
The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.
The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.
QSAR modelling using combined simple competitive learning networks and RBF neural networks.

PubMed

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.
Spatiotemporal Bayesian networks for malaria prediction.

PubMed

Haddawy, Peter; Hasan, A H M Imrul; Kasantikul, Rangwan; Lawpoolsri, Saranath; Sa-Angchai, Patiwat; Kaewkungwal, Jaranit; Singhasivanon, Pratap

2018-01-01

Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating village level models with weekly temporal resolution for Tha Song Yang district in northern Thailand. The networks are learned using data on cases and environmental covariates. Three types of networks are explored: networks for numeric prediction, networks for outbreak prediction, and networks that incorporate spatial autocorrelation. Evaluation of the numeric prediction network shows that the Bayes net has prediction accuracy in terms of mean absolute error of about 1.4 cases for 1 week prediction and 1.7 cases for 6 week prediction. The network for outbreak prediction has an ROC AUC above 0.9 for all prediction horizons. Comparison of prediction accuracy of both Bayes nets against several traditional modeling approaches shows the Bayes nets to outperform the other models for longer time horizon prediction of high incidence transmission. To model spread of malaria over space, we elaborate the models with links between the village networks. This results in some very large models which would be far too laborious to build by hand. So we represent the models as collections of probability logic rules and automatically generate the networks. Evaluation of the models shows that the autocorrelation links significantly improve prediction accuracy for some villages in regions of high incidence. We conclude that spatiotemporal Bayesian networks are a highly promising modeling alternative for prediction of malaria and other vector-borne diseases. Copyright © 2017 Elsevier B.V. All rights reserved.
Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.
Structure-preserving model reduction of large-scale logistics networks. Applications for supply chains

NASA Astrophysics Data System (ADS)

Scholz-Reiter, B.; Wirth, F.; Dashkovskiy, S.; Makuschewitz, T.; Schönlein, M.; Kosmykov, M.

2011-12-01

We investigate the problem of model reduction with a view to large-scale logistics networks, specifically supply chains. Such networks are modeled by means of graphs, which describe the structure of material flow. An aim of the proposed model reduction procedure is to preserve important features within the network. As a new methodology we introduce the LogRank as a measure for the importance of locations, which is based on the structure of the flows within the network. We argue that these properties reflect relative importance of locations. Based on the LogRank we identify subgraphs of the network that can be neglected or aggregated. The effect of this is discussed for a few motifs. Using this approach we present a meta algorithm for structure-preserving model reduction that can be adapted to different mathematical modeling frameworks. The capabilities of the approach are demonstrated with a test case, where a logistics network is modeled as a Jackson network, i.e., a particular type of queueing network.
A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

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.
Polynomial algebra of discrete models in systems biology.

PubMed

Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2010-07-01

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.
Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately
Toward a model of school inspections in a polycentric system.

PubMed

Janssens, Frans J G; Ehren, Melanie C M

2016-06-01

Many education systems are developing towards more lateral structures where schools collaborate in networks to improve and provide (inclusive) education. These structures call for bottom-up models of network evaluation and accountability instead of the current hierarchical arrangements where single schools are evaluated by a central agency. This paper builds on available research about network effectiveness to present evolving models of network evaluation. Network effectiveness can be defined as the achievement of positive network level outcomes that cannot be attained by individual organizational participants acting alone. Models of network evaluation need to take into account the relations between network members, the structure of the network, its processes and its internal mechanism to enforce norms in order to understand the achievement and outcomes of the network and how these may evolve over time. A range of suitable evaluation models are presented in this paper, as well as a tentative school inspection framework which is inspired by these models. The final section will present examples from Inspectorates of Education in Northern Ireland and Scotland who have developed newer inspection models to evaluate the effectiveness of a range of different networks. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling the resilience of critical infrastructure: the role of network dependencies.

PubMed

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2016-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities' well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.
Modeling the resilience of critical infrastructure: the role of network dependencies

PubMed Central

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2017-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities’ well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure. PMID:28825037
Turing instability in reaction-diffusion models on complex networks

NASA Astrophysics Data System (ADS)

Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya

2016-09-01

In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.
An adaptable neural-network model for recursive nonlinear traffic prediction and modeling of MPEG video sources.

PubMed

Doulamis, A D; Doulamis, N D; Kollias, S D

2003-01-01

Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.
Investigation of membrane mechanics using spring networks: application to red-blood-cell modelling.

PubMed

Chen, Mingzhu; Boyle, Fergal J

2014-10-01

In recent years a number of red-blood-cell (RBC) models have been proposed using spring networks to represent the RBC membrane. Some results predicted by these models agree well with experimental measurements. However, the suitability of these membrane models has been questioned. The RBC membrane, like a continuum membrane, is mechanically isotropic throughout its surface, but the mechanical properties of a spring network vary on the network surface and change with deformation. In this work spring-network mechanics are investigated in large deformation for the first time via an assessment of the effect of network parameters, i.e. network mesh, spring type and surface constraint. It is found that a spring network is conditionally equivalent to a continuum membrane. In addition, spring networks are employed for RBC modelling to replicate the optical tweezers test. It is found that a spring network is sufficient for modelling the RBC membrane but strain-hardening springs are required. Moreover, the deformation profile of a spring network is presented for the first time via the degree of shear. It is found that spring-network deformation approaches continuous as the mesh density increases. Copyright © 2014 Elsevier B.V. All rights reserved.
A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.
Equity venture capital platform model based on complex network

NASA Astrophysics Data System (ADS)

Guo, Dongwei; Zhang, Lanshu; Liu, Miao

2018-05-01

This paper uses the small-world network and the random-network to simulate the relationship among the investors, construct the network model of the equity venture capital platform to explore the impact of the fraud rate and the bankruptcy rate on the robustness of the network model while observing the impact of the average path length and the average agglomeration coefficient of the investor relationship network on the income of the network model. The study found that the fraud rate and bankruptcy rate exceeded a certain threshold will lead to network collapse; The bankruptcy rate has a great influence on the income of the platform; The risk premium exists, and the average return is better under a certain range of bankruptcy risk; The structure of the investor relationship network has no effect on the income of the investment model.
Modeling geomagnetic induced currents in Australian power networks

NASA Astrophysics Data System (ADS)

Marshall, R. A.; Kelly, A.; Van Der Walt, T.; Honecker, A.; Ong, C.; Mikkelsen, D.; Spierings, A.; Ivanovich, G.; Yoshikawa, A.

2017-07-01

Geomagnetic induced currents (GICs) have been considered an issue for high-latitude power networks for some decades. More recently, GICs have been observed and studied in power networks located in lower latitude regions. This paper presents the results of a model aimed at predicting and understanding the impact of geomagnetic storms on power networks in Australia, with particular focus on the Queensland and Tasmanian networks. The model incorporates a "geoelectric field" determined using a plane wave magnetic field incident on a uniform conducting Earth, and the network model developed by Lehtinen and Pirjola (1985). Model results for two intense geomagnetic storms of solar cycle 24 are compared with transformer neutral monitors at three locations within the Queensland network and one location within the Tasmanian network. The model is then used to assess the impacts of the superintense geomagnetic storm of 29-31 October 2003 on the flow of GICs within these networks. The model results show good correlation with the observations with coefficients ranging from 0.73 to 0.96 across the observing sites. For Queensland, modeled GIC magnitudes during the superstorm of 29-31 October 2003 exceed 40 A with the larger GICs occurring in the south-east section of the network. Modeled GICs in Tasmania for the same storm do not exceed 30 A. The larger distance spans and general east-west alignment of the southern section of the Queensland network, in conjunction with some relatively low branch resistance values, result in larger modeled GICs despite Queensland being a lower latitude network than Tasmania.
Directly executable formal models of middleware for MANET and Cloud Networking and Computing

NASA Astrophysics Data System (ADS)

Pashchenko, D. V.; Sadeq Jaafar, Mustafa; Zinkin, S. A.; Trokoz, D. A.; Pashchenko, T. U.; Sinev, M. P.

2016-04-01

The article considers some “directly executable” formal models that are suitable for the specification of computing and networking in the cloud environment and other networks which are similar to wireless networks MANET. These models can be easily programmed and implemented on computer networks.
A study of the security technology and a new security model for WiFi network

NASA Astrophysics Data System (ADS)

Huang, Jing

2013-07-01

The WiFi network is one of the most rapidly developing wireless communication networks, which makes wireless office and wireless life possible and greatly expands the application form and scope of the internet. At the same time, the WiFi network security has received wide attention, and this is also the key factor of WiFi network development. This paper makes a systematic introduction to the WiFi network and WiFi network security problems, and the WiFi network security technology are reviewed and compared. In order to solve the security problems in WiFi network, this paper presents a new WiFi network security model and the key exchange algorithm. Experiments are performed to test the performance of the model, the results show that the new security model can withstand external network attack and ensure stable and safe operation of WiFi network.
Deterministic ripple-spreading model for complex networks.

PubMed

Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel

2011-04-01

This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.
Resolving Structural Variability in Network Models and the Brain

PubMed Central

Klimm, Florian; Bassett, Danielle S.; Carlson, Jean M.; Mucha, Peter J.

2014-01-01

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling—in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data. PMID:24675546
A Novel BA Complex Network Model on Color Template Matching

PubMed Central

Han, Risheng; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching. PMID:25243235
A novel BA complex network model on color template matching.

PubMed

Han, Risheng; Shen, Shigen; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching.
Modeling and Performance Simulation of the Mass Storage Network Environment

NASA Technical Reports Server (NTRS)

Kim, Chan M.; Sang, Janche

2000-01-01

This paper describes the application of modeling and simulation in evaluating and predicting the performance of the mass storage network environment. Network traffic is generated to mimic the realistic pattern of file transfer, electronic mail, and web browsing. The behavior and performance of the mass storage network and a typical client-server Local Area Network (LAN) are investigated by modeling and simulation. Performance characteristics in throughput and delay demonstrate the important role of modeling and simulation in network engineering and capacity planning.
Esterase reactions in acute myelomonocytic leukemia.

PubMed

Kass, L

1977-05-01

Specific and nonspecific esterase reactions of bone marrow cells from 14 patients with untreated acute myelomonocytic leukemia and six patients with acute histiomonocytic leukemia were examined. The technic for esterase determination permitted simultaneous visualization of both esterases on the same glass coverslip containing the marrow cells. In cases of acute histiomonocytic leukemia, monocytes, monocytoid hemohistioblasts and undifferentiated blasts stained intensely positive for nonspecific esterase, using alpha-naphthyl acetate as the substrate. No evidence of specific esterase activity using naphthol ASD-chloroacetate as the substrate and fast blue BBN as the dye coupler was apparent in these cells. In all of the cases of acute myelomonocytic leukemia, both specific and nonspecific esterases were visualized within monocytes, monocytoid cells, and granulocytic cells that had monocytoid-type nuclei. Nonspecific esterase activity was not observed in polymorphonuclear leukocytes in cases of myelomonocytic leukemia. The results support a current viewpoint that acute myelomonocytic leukemia may be a variant of acute myeloblastic leukemia, and that cytochemically, many of the leukemic cells in myelomonocytic leukemia share properties of both granulocytes and monocytes.

Coupling of 3,8-Dibromo-1,10-Phenanthroline With 3,5-Diethynylheptyloxybenzene: A Suzuki/Miyaura Versus a Sonogashira Perspective

NASA Technical Reports Server (NTRS)

Yang, Jinhua; Oh, Woon Su; Elder, Ian A.; Leventis, Nicholas; Sotiriou-Leventis, Chariklia

2003-01-01

We report a new application of the Suzuki-Miyaura reaction whereas two bifunctional reactants, 3,8-dibromo-1,10-phenanthroline and 3,5-diethynylheptyloxylbenzene (9), yield 3,8-bis (3-ethynyl-5-heptyloxyphenylethynyl)-1,10-phenanthroline (2) efficiently (74% yield) without polymerization. This was achieved by reacting a stoichiometric amount of 9 and (Me3Si)2NLi to obtain quantitatively the monoacetylide anion of 9 (10). The latter was activated with B-methoxy-9-BBN and reacted in analogy to the alkynyl copper complex of a Sonogashira route. However, in the Sonogashira reaction, the alkynyl copper complex is present in small equilibrium concentrations and polymerization takes place even when reagents are mixed slowly. Actually the Sonogashira route gave no desired product 2, as the latter polymerizes easily via homo-coupling in the presence of air and Cu(I). Sonogashira coupling involves the palladium(0) catalyzed reaction of terminal alkynes.
'Breaking Good News': Neurologists' experiences of discussing SUDEP with patients in Scotland.

PubMed

Nisbet, Tom; Turbull, Sue; Mulhern, Sharon; Razvi, Saif

2017-05-01

Since the findings of a Fatal Accident Inquiry (FAI) in 2010, clinicians working in Scotland have been advised to discuss the risk of Sudden Unexpected Death in Epilepsy (SUDEP) with patients immediately or soon after a diagnosis of epilepsy is made. A thematic analysis was used to describe the experiences discussing SUDEP of 10 clinicians (six Consultant Neurologists and four Neurology Registrars) working in Scotland. Contrary to previous research, clinicians appear to be routinely discussing SUDEP in a standardized fashion with newly diagnosed patients and the FAI appears to have instigated this change in practice. Clinicians are ambivalent about the practice and whether this is a Breaking Bad News (BBN) experience. Clinicians appear to anticipate that patients will be anxious or distressed discussing SUDEP, despite their experiences that patients do not react this way. There are further concerns that the pressure to discuss SUDEP, as a result of the FAI, hinders effective communication of the SUDEP message. Implications for guideline development are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.
A Measurement of the Interaction of Neutrons With 7Be at Cosmological Energies

NASA Astrophysics Data System (ADS)

Kading, E. E.; Gai, M.; Palchan, T.; Paul, M.; Tessler, M.; Weiss, A.; Berkovits, D.; Halfon, Sh.; Kijel, D.; Kreisel, A.; Shor, A.; Silverman, I.; Weissman, L.; Dressler, R.; Heinitz, S.; Maugeri, E. A.; Schumann, D.; Hass, M.; Mukul, I.; Shachar, Y.; Seiffert, Ch,; Stora, Th.; Ticehurst, D.; Howell, C. R.; Kivel, N.

2016-09-01

We exposed the 4.4 GBq electroplated 7Be target prepared at the Paul Scherrer Institute in Switzerland to the high neutrons flux of 5x1010 /sec/cm2 generated by the LiLiT at the Soreq Applied Research Accelerator Facility (SARAF) in Israel. The so produced quasi-Maxwelian neutron spectrum with an equivalent kT = 49.2 keV simulate directly BBN conditions with T = 700 - 500 MK (kT = 60 - 43 keV), allowing the first measurement at Big Bang energies. The measured alpha-particles emanating from all possible 8Be states populated in the 7Be(n, α) and 7Be(n, γα) reaction, detected with a CR39 plastic track detectors, will be shown and discussed. This material is based upon work supported by the U.S - Israel Binational Science Foundation, under Award Number 2012098 and the US. Department of Energy, Office of Science, Office of Nuclear Physics, under Award Number DE-FG02-94ER40870.
Dispersive Readout of a Superconducting Flux Qubit Using a Microstrip SQUID Amplifier

NASA Astrophysics Data System (ADS)

Johnson, J. E.; Hoskinson, E. M.; Macklin, C.; Siddiqi, I.; Clarke, John

2011-03-01

Dispersive techniques for the readout of superconducting qubits offer the possibility of high repetition-rate, quantum non-demolition measurement by avoiding dissipation close to the qubit. To achieve dispersive readout, we couple our three-junction aluminum flux qubit inductively to a 1-2 GHz non-linear oscillator formed by a capacitively shunted DC SQUID. The frequency of this resonator is modulated by the state of the qubit via the flux-dependent inductance of the SQUID. Readout is performed by probing the resonator in the linear (weak drive) regime with a microwave tone and monitoring the phase of the reflected signal. A microstrip SQUID amplifier (MSA) is used to increase the sensitivity of the measurement over that of a HEMT (high electron mobility transistor) amplifier. We report measurements of the performance of our amplification chain. Increased fidelity and reduced measurement backaction resulting from the implementation of the MSA will also be discussed. This work was funded in part by the U.S. Government and by BBN Technologies.
A local structure model for network analysis

DOE PAGES

Casleton, Emily; Nordman, Daniel; Kaiser, Mark

2017-04-01

The statistical analysis of networks is a popular research topic with ever widening applications. Exponential random graph models (ERGMs), which specify a model through interpretable, global network features, are common for this purpose. In this study we introduce a new class of models for network analysis, called local structure graph models (LSGMs). In contrast to an ERGM, a LSGM specifies a network model through local features and allows for an interpretable and controllable local dependence structure. In particular, LSGMs are formulated by a set of full conditional distributions for each network edge, e.g., the probability of edge presence/absence, depending onmore » neighborhoods of other edges. Additional model features are introduced to aid in specification and to help alleviate a common issue (occurring also with ERGMs) of model degeneracy. Finally, the proposed models are demonstrated on a network of tornadoes in Arkansas where a LSGM is shown to perform significantly better than a model without local dependence.« less
A local structure model for network analysis

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

Casleton, Emily; Nordman, Daniel; Kaiser, Mark

The statistical analysis of networks is a popular research topic with ever widening applications. Exponential random graph models (ERGMs), which specify a model through interpretable, global network features, are common for this purpose. In this study we introduce a new class of models for network analysis, called local structure graph models (LSGMs). In contrast to an ERGM, a LSGM specifies a network model through local features and allows for an interpretable and controllable local dependence structure. In particular, LSGMs are formulated by a set of full conditional distributions for each network edge, e.g., the probability of edge presence/absence, depending onmore » neighborhoods of other edges. Additional model features are introduced to aid in specification and to help alleviate a common issue (occurring also with ERGMs) of model degeneracy. Finally, the proposed models are demonstrated on a network of tornadoes in Arkansas where a LSGM is shown to perform significantly better than a model without local dependence.« less
Coevolutionary, coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2013-07-01

Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner’s dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents’ strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents’ enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society.
Use of model calibration to achieve high accuracy in analysis of computer networks

DOEpatents

Frogner, Bjorn; Guarro, Sergio; Scharf, Guy

2004-05-11

A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.
Switching performance of OBS network model under prefetched real traffic

NASA Astrophysics Data System (ADS)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.
Measuring, Understanding, and Responding to Covert Social Networks: Passive and Active Tomography

DTIC Science & Technology

2017-11-11

practical algorithms for sociologically principled detection of small sub- networks. To detect “foreground” networks, we need two competing models...understanding of how to model “background” network clutter, leading to principled approaches to “foreground” sub-network detection. Before the MURI...no frameworks existed for network detection theory or goodness-of-fit, nor were models and algorithms coupled to sound sociological principles
A biologically inspired network design model.

PubMed

Zhang, Xiaoge; Adamatzky, Andrew; Chan, Felix T S; Deng, Yong; Yang, Hai; Yang, Xin-She; Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Mahadevan, Sankaran

2015-06-04

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach.
A Biologically Inspired Network Design Model

PubMed Central

Zhang, Xiaoge; Adamatzky, Andrew; Chan, Felix T.S.; Deng, Yong; Yang, Hai; Yang, Xin-She; Tsompanas, Michail-Antisthenis I.; Sirakoulis, Georgios Ch.; Mahadevan, Sankaran

2015-01-01

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach. PMID:26041508
Creating, documenting and sharing network models.

PubMed

Crook, Sharon M; Bednar, James A; Berger, Sandra; Cannon, Robert; Davison, Andrew P; Djurfeldt, Mikael; Eppler, Jochen; Kriener, Birgit; Furber, Steve; Graham, Bruce; Plesser, Hans E; Schwabe, Lars; Smith, Leslie; Steuber, Volker; van Albada, Sacha

2012-01-01

As computational neuroscience matures, many simulation environments are available that are useful for neuronal network modeling. However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. Here we briefly review existing software and applications for network model creation, documentation and exchange. Then we discuss a few of the larger issues facing the field of computational neuroscience regarding network modeling and suggest solutions to some of these problems, concentrating in particular on standardized network model terminology, notation, and descriptions and explicit documentation of model scaling. We hope this will enable and encourage computational neuroscientists to share their models more systematically in the future.
Model of community emergence in weighted social networks

NASA Astrophysics Data System (ADS)

Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

2009-04-01

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.
A Feasibility Study of Synthesizing Subsurfaces Modeled with Computational Neural Networks

NASA Technical Reports Server (NTRS)

Wang, John T.; Housner, Jerrold M.; Szewczyk, Z. Peter

1998-01-01

This paper investigates the feasibility of synthesizing substructures modeled with computational neural networks. Substructures are modeled individually with computational neural networks and the response of the assembled structure is predicted by synthesizing the neural networks. A superposition approach is applied to synthesize models for statically determinate substructures while an interface displacement collocation approach is used to synthesize statically indeterminate substructure models. Beam and plate substructures along with components of a complicated Next Generation Space Telescope (NGST) model are used in this feasibility study. In this paper, the limitations and difficulties of synthesizing substructures modeled with neural networks are also discussed.
A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks.

PubMed

Petrovskaya, Olga V; Petrovskiy, Evgeny D; Lavrik, Inna N; Ivanisenko, Vladimir A

2017-04-01

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.
Bayesian Network Webserver: a comprehensive tool for biological network modeling.

PubMed

Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

2013-11-01

The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.
Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty.

PubMed

Fathollah Bayati, Mohsen; Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model.
Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty

PubMed Central

Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model. PMID:28953900
Models and algorithm of optimization launch and deployment of virtual network functions in the virtual data center

NASA Astrophysics Data System (ADS)

Bolodurina, I. P.; Parfenov, D. I.

2017-10-01

The goal of our investigation is optimization of network work in virtual data center. The advantage of modern infrastructure virtualization lies in the possibility to use software-defined networks. However, the existing optimization of algorithmic solutions does not take into account specific features working with multiple classes of virtual network functions. The current paper describes models characterizing the basic structures of object of virtual data center. They including: a level distribution model of software-defined infrastructure virtual data center, a generalized model of a virtual network function, a neural network model of the identification of virtual network functions. We also developed an efficient algorithm for the optimization technology of containerization of virtual network functions in virtual data center. We propose an efficient algorithm for placing virtual network functions. In our investigation we also generalize the well renowned heuristic and deterministic algorithms of Karmakar-Karp.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.
Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.

PubMed

Sauser Zachrison, Kori; Iwashyna, Theodore J; Gebremariam, Achamyeleh; Hutchins, Meghan; Lee, Joyce M

2016-12-28

Connected individuals (or nodes) in a network are more likely to be similar than two randomly selected nodes due to homophily and/or network influence. Distinguishing between these two influences is an important goal in network analysis, and generalized estimating equation (GEE) analyses of longitudinal dyadic network data are an attractive approach. It is not known to what extent such regressions can accurately extract underlying data generating processes. Therefore our primary objective is to determine to what extent, and under what conditions, does the GEE-approach recreate the actual dynamics in an agent-based model. We generated simulated cohorts with pre-specified network characteristics and attachments in both static and dynamic networks, and we varied the presence of homophily and network influence. We then used statistical regression and examined the GEE model performance in each cohort to determine whether the model was able to detect the presence of homophily and network influence. In cohorts with both static and dynamic networks, we find that the GEE models have excellent sensitivity and reasonable specificity for determining the presence or absence of network influence, but little ability to distinguish whether or not homophily is present. The GEE models are a valuable tool to examine for the presence of network influence in longitudinal data, but are quite limited with respect to homophily.
Trainable Gene Regulation Networks with Applications to Drosophila Pattern Formation

NASA Technical Reports Server (NTRS)

Mjolsness, Eric

2000-01-01

This chapter will very briefly introduce and review some computational experiments in using trainable gene regulation network models to simulate and understand selected episodes in the development of the fruit fly, Drosophila melanogaster. For details the reader is referred to the papers introduced below. It will then introduce a new gene regulation network model which can describe promoter-level substructure in gene regulation. As described in chapter 2, gene regulation may be thought of as a combination of cis-acting regulation by the extended promoter of a gene (including all regulatory sequences) by way of the transcription complex, and of trans-acting regulation by the transcription factor products of other genes. If we simplify the cis-action by using a phenomenological model which can be tuned to data, such as a unit or other small portion of an artificial neural network, then the full transacting interaction between multiple genes during development can be modelled as a larger network which can again be tuned or trained to data. The larger network will in general need to have recurrent (feedback) connections since at least some real gene regulation networks do. This is the basic modeling approach taken, which describes how a set of recurrent neural networks can be used as a modeling language for multiple developmental processes including gene regulation within a single cell, cell-cell communication, and cell division. Such network models have been called "gene circuits", "gene regulation networks", or "genetic regulatory networks", sometimes without distinguishing the models from the actual modeled systems.
Gossip spread in social network Models

NASA Astrophysics Data System (ADS)

Johansson, Tobias

2017-04-01

Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.
Thinking outside the channel: Modeling nitrogen cycling in networked river ecosystems

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

Helton, Ashley; Poole, Geoffrey C.; Meyer, Judy

2011-01-01

Agricultural and urban development alters nitrogen and other biogeochemical cycles in rivers worldwide. Because such biogeochemical processes cannot be measured empirically across whole river networks, simulation models are critical tools for understanding river-network biogeochemistry. However, limitations inherent in current models restrict our ability to simulate biogeochemical dynamics among diverse river networks. We illustrate these limitations using a river-network model to scale up in situ measures of nitrogen cycling in eight catchments spanning various geophysical and land-use conditions. Our model results provide evidence that catchment characteristics typically excluded from models may control river-network biogeochemistry. Based on our findings, we identify importantmore » components of a revised strategy for simulating biogeochemical dynamics in river networks, including approaches to modeling terrestrial-aquatic linkages, hydrologic exchanges between the channel, floodplain/riparian complex, and subsurface waters, and interactions between coupled biogeochemical cycles.« less
Revisiting node-based SIR models in complex networks with degree correlations

NASA Astrophysics Data System (ADS)

Wang, Yi; Cao, Jinde; Alofi, Abdulaziz; AL-Mazrooei, Abdullah; Elaiw, Ahmed

2015-11-01

In this paper, we consider two growing networks which will lead to the degree-degree correlations between two nearest neighbors in the network. When the network grows to some certain size, we introduce an SIR-like disease such as pandemic influenza H1N1/09 to the population. Due to its rapid spread, the population size changes slowly, and thus the disease spreads on correlated networks with approximately fixed size. To predict the disease evolution on correlated networks, we first review two node-based SIR models incorporating degree correlations and an edge-based SIR model without considering degree correlation, and then compare the predictions of these models with stochastic SIR simulations, respectively. We find that the edge-based model, even without considering degree correlations, agrees much better than the node-based models incorporating degree correlations with stochastic SIR simulations in many respects. Moreover, simulation results show that for networks with positive correlation, the edge-based model provides a better upper bound of the cumulative incidence than the node-based SIR models, whereas for networks with negative correlation, it provides a lower bound of the cumulative incidence.
GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.
Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273
A last updating evolution model for online social networks

NASA Astrophysics Data System (ADS)

Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

2013-05-01

As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.
Temporal efficiency evaluation and small-worldness characterization in temporal networks

PubMed Central

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-01-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks. PMID:27682314
Temporal efficiency evaluation and small-worldness characterization in temporal networks

NASA Astrophysics Data System (ADS)

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-09-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks.
Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.

PubMed

Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen

2016-05-01

Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed.
Search for Directed Networks by Different Random Walk Strategies

NASA Astrophysics Data System (ADS)

Zhu, Zi-Qi; Jin, Xiao-Ling; Huang, Zhi-Long

2012-03-01

A comparative study is carried out on the efficiency of five different random walk strategies searching on directed networks constructed based on several typical complex networks. Due to the difference in search efficiency of the strategies rooted in network clustering, the clustering coefficient in a random walker's eye on directed networks is defined and computed to be half of the corresponding undirected networks. The search processes are performed on the directed networks based on Erdös—Rényi model, Watts—Strogatz model, Barabási—Albert model and clustered scale-free network model. It is found that self-avoiding random walk strategy is the best search strategy for such directed networks. Compared to unrestricted random walk strategy, path-iteration-avoiding random walks can also make the search process much more efficient. However, no-triangle-loop and no-quadrangle-loop random walks do not improve the search efficiency as expected, which is different from those on undirected networks since the clustering coefficient of directed networks are smaller than that of undirected networks.
SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

2017-10-01

Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028
Neural network modelling of the influence of channelopathies on reflex visual attention.

PubMed

Gravier, Alexandre; Quek, Chai; Duch, Włodzisław; Wahab, Abdul; Gravier-Rymaszewska, Joanna

2016-02-01

This paper introduces a model of Emergent Visual Attention in presence of calcium channelopathy (EVAC). By modelling channelopathy, EVAC constitutes an effort towards identifying the possible causes of autism. The network structure embodies the dual pathways model of cortical processing of visual input, with reflex attention as an emergent property of neural interactions. EVAC extends existing work by introducing attention shift in a larger-scale network and applying a phenomenological model of channelopathy. In presence of a distractor, the channelopathic network's rate of failure to shift attention is lower than the control network's, but overall, the control network exhibits a lower classification error rate. The simulation results also show differences in task-relative reaction times between control and channelopathic networks. The attention shift timings inferred from the model are consistent with studies of attention shift in autistic children.
[Study on the automatic parameters identification of water pipe network model].

PubMed

Jia, Hai-Feng; Zhao, Qi-Feng

2010-01-01

Based on the problems analysis on development and application of water pipe network model, the model parameters automatic identification is regarded as a kernel bottleneck of model's application in water supply enterprise. The methodology of water pipe network model parameters automatic identification based on GIS and SCADA database is proposed. Then the kernel algorithm of model parameters automatic identification is studied, RSA (Regionalized Sensitivity Analysis) is used for automatic recognition of sensitive parameters, and MCS (Monte-Carlo Sampling) is used for automatic identification of parameters, the detail technical route based on RSA and MCS is presented. The module of water pipe network model parameters automatic identification is developed. At last, selected a typical water pipe network as a case, the case study on water pipe network model parameters automatic identification is conducted and the satisfied results are achieved.
Towards Reproducible Descriptions of Neuronal Network Models

PubMed Central

Nordlie, Eilen; Gewaltig, Marc-Oliver; Plesser, Hans Ekkehard

2009-01-01

Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing—and thinking about—complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain. PMID:19662159
Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber.

PubMed

Koch, Ina; Junker, Björn H; Heiner, Monika

2005-04-01

Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood. We provide an approach for model validation of metabolic networks using Petri net theory, which we demonstrate for the sucrose breakdown pathway in the potato tuber. We start with hierarchical modelling of the metabolic network as a Petri net and continue with the analysis of qualitative properties of the network. The results characterize the net structure and give insights into the complex net behaviour.
Prediction of relative and absolute permeabilities for gas and water from soil water retention curves using a pore-scale network model

NASA Astrophysics Data System (ADS)

Fischer, Ulrich; Celia, Michael A.

1999-04-01

Functional relationships for unsaturated flow in soils, including those between capillary pressure, saturation, and relative permeabilities, are often described using analytical models based on the bundle-of-tubes concept. These models are often limited by, for example, inherent difficulties in prediction of absolute permeabilities, and in incorporation of a discontinuous nonwetting phase. To overcome these difficulties, an alternative approach may be formulated using pore-scale network models. In this approach, the pore space of the network model is adjusted to match retention data, and absolute and relative permeabilities are then calculated. A new approach that allows more general assignments of pore sizes within the network model provides for greater flexibility to match measured data. This additional flexibility is especially important for simultaneous modeling of main imbibition and drainage branches. Through comparisons between the network model results, analytical model results, and measured data for a variety of both undisturbed and repacked soils, the network model is seen to match capillary pressure-saturation data nearly as well as the analytical model, to predict water phase relative permeabilities equally well, and to predict gas phase relative permeabilities significantly better than the analytical model. The network model also provides very good estimates for intrinsic permeability and thus for absolute permeabilities. Both the network model and the analytical model lost accuracy in predicting relative water permeabilities for soils characterized by a van Genuchten exponent n≲3. Overall, the computational results indicate that reliable predictions of both relative and absolute permeabilities are obtained with the network model when the model matches the capillary pressure-saturation data well. The results also indicate that measured imbibition data are crucial to good predictions of the complete hysteresis loop.
Trust recovery model of Ad Hoc network based on identity authentication scheme

NASA Astrophysics Data System (ADS)

Liu, Jie; Huan, Shuiyuan

2017-05-01

Mobile Ad Hoc network trust model is widely used to solve mobile Ad Hoc network security issues. Aiming at the problem of reducing the network availability caused by the processing of malicious nodes and selfish nodes in mobile Ad Hoc network routing based on trust model, an authentication mechanism based on identity authentication mobile Ad Hoc network is proposed, which uses identity authentication to identify malicious nodes, And trust the recovery of selfish nodes in order to achieve the purpose of reducing network congestion and improving network quality. The simulation results show that the implementation of the mechanism can effectively improve the network availability and security.

Network model of bilateral power markets based on complex networks

NASA Astrophysics Data System (ADS)

Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li

2014-06-01

The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.
Modeling and control of magnetorheological fluid dampers using neural networks

NASA Astrophysics Data System (ADS)

Wang, D. H.; Liao, W. H.

2005-02-01

Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.
Earth-Mars Telecommunications and Information Management System (TIMS): Antenna Visibility Determination, Network Simulation, and Management Models

NASA Technical Reports Server (NTRS)

Odubiyi, Jide; Kocur, David; Pino, Nino; Chu, Don

1996-01-01

This report presents the results of our research on Earth-Mars Telecommunications and Information Management System (TIMS) network modeling and unattended network operations. The primary focus of our research is to investigate the feasibility of the TIMS architecture, which links the Earth-based Mars Operations Control Center, Science Data Processing Facility, Mars Network Management Center, and the Deep Space Network of antennae to the relay satellites and other communication network elements based in the Mars region. The investigation was enhanced by developing Build 3 of the TIMS network modeling and simulation model. The results of several 'what-if' scenarios are reported along with reports on upgraded antenna visibility determination software and unattended network management prototype.
Network structure, topology, and dynamics in generalized models of synchronization

NASA Astrophysics Data System (ADS)

Lerman, Kristina; Ghosh, Rumi

2012-08-01

Network structure is a product of both its topology and interactions between its nodes. We explore this claim using the paradigm of distributed synchronization in a network of coupled oscillators. As the network evolves to a global steady state, nodes synchronize in stages, revealing the network's underlying community structure. Traditional models of synchronization assume that interactions between nodes are mediated by a conservative process similar to diffusion. However, social and biological processes are often nonconservative. We propose a model of synchronization in a network of oscillators coupled via nonconservative processes. We study the dynamics of synchronization of a synthetic and real-world networks and show that the traditional and nonconservative models of synchronization reveal different structures within the same network.
Wayfinding in Social Networks

NASA Astrophysics Data System (ADS)

Liben-Nowell, David

With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.
Automatic decomposition of kinetic models of signaling networks minimizing the retroactivity among modules.

PubMed

Saez-Rodriguez, Julio; Gayer, Stefan; Ginkel, Martin; Gilles, Ernst Dieter

2008-08-15

The modularity of biochemical networks in general, and signaling networks in particular, has been extensively studied over the past few years. It has been proposed to be a useful property to analyze signaling networks: by decomposing the network into subsystems, more manageable units are obtained that are easier to analyze. While many powerful algorithms are available to identify modules in protein interaction networks, less attention has been paid to signaling networks de.ned as chemical systems. Such a decomposition would be very useful as most quantitative models are de.ned using the latter, more detailed formalism. Here, we introduce a novel method to decompose biochemical networks into modules so that the bidirectional (retroactive) couplings among the modules are minimized. Our approach adapts a method to detect community structures, and applies it to the so-called retroactivity matrix that characterizes the couplings of the network. Only the structure of the network, e.g. in SBML format, is required. Furthermore, the modularized models can be loaded into ProMoT, a modeling tool which supports modular modeling. This allows visualization of the models, exploiting their modularity and easy generation of models of one or several modules for further analysis. The method is applied to several relevant cases, including an entangled model of the EGF-induced MAPK cascade and a comprehensive model of EGF signaling, demonstrating its ability to uncover meaningful modules. Our approach can thus help to analyze large networks, especially when little a priori knowledge on the structure of the network is available. The decomposition algorithms implemented in MATLAB (Mathworks, Inc.) are freely available upon request. ProMoT is freely available at http://www.mpi-magdeburg.mpg.de/projects/promot. Supplementary data are available at Bioinformatics online.
Development of a pore network simulation model to study nonaqueous phase liquid dissolution

USGS Publications Warehouse

Dillard, Leslie A.; Blunt, Martin J.

2000-01-01

A pore network simulation model was developed to investigate the fundamental physics of nonequilibrium nonaqueous phase liquid (NAPL) dissolution. The network model is a lattice of cubic chambers and rectangular tubes that represent pore bodies and pore throats, respectively. Experimental data obtained by Powers [1992] were used to develop and validate the model. To ensure the network model was representative of a real porous medium, the pore size distribution of the network was calibrated by matching simulated and experimental drainage and imbibition capillary pressure‐saturation curves. The predicted network residual styrene blob‐size distribution was nearly identical to the observed distribution. The network model reproduced the observed hydraulic conductivity and produced relative permeability curves that were representative of a poorly consolidated sand. Aqueous‐phase transport was represented by applying the equation for solute flux to the network tubes and solving for solute concentrations in the network chambers. Complete mixing was found to be an appropriate approximation for calculation of chamber concentrations. Mass transfer from NAPL blobs was represented using a corner diffusion model. Predicted results of solute concentration versus Peclet number and of modified Sherwood number versus Peclet number for the network model compare favorably with experimental data for the case in which NAPL blob dissolution was negligible. Predicted results of normalized effluent concentration versus pore volume for the network were similar to the experimental data for the case in which NAPL blob dissolution occurred with time.
Deep hierarchical attention network for video description

NASA Astrophysics Data System (ADS)

Li, Shuohao; Tang, Min; Zhang, Jun

2018-03-01

Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.
Modeling fluctuations in default-mode brain network using a spiking neural network.

PubMed

Yamanishi, Teruya; Liu, Jian-Qin; Nishimura, Haruhiko

2012-08-01

Recently, numerous attempts have been made to understand the dynamic behavior of complex brain systems using neural network models. The fluctuations in blood-oxygen-level-dependent (BOLD) brain signals at less than 0.1 Hz have been observed by functional magnetic resonance imaging (fMRI) for subjects in a resting state. This phenomenon is referred to as a "default-mode brain network." In this study, we model the default-mode brain network by functionally connecting neural communities composed of spiking neurons in a complex network. Through computational simulations of the model, including transmission delays and complex connectivity, the network dynamics of the neural system and its behavior are discussed. The results show that the power spectrum of the modeled fluctuations in the neuron firing patterns is consistent with the default-mode brain network's BOLD signals when transmission delays, a characteristic property of the brain, have finite values in a given range.
Graph modeling systems and methods

DOEpatents

Neergaard, Mike

2015-10-13

An apparatus and a method for vulnerability and reliability modeling are provided. The method generally includes constructing a graph model of a physical network using a computer, the graph model including a plurality of terminating vertices to represent nodes in the physical network, a plurality of edges to represent transmission paths in the physical network, and a non-terminating vertex to represent a non-nodal vulnerability along a transmission path in the physical network. The method additionally includes evaluating the vulnerability and reliability of the physical network using the constructed graph model, wherein the vulnerability and reliability evaluation includes a determination of whether each terminating and non-terminating vertex represents a critical point of failure. The method can be utilized to evaluate wide variety of networks, including power grid infrastructures, communication network topologies, and fluid distribution systems.
Epidemic spreading on complex networks with community structures

PubMed Central

Stegehuis, Clara; van der Hofstad, Remco; van Leeuwaarden, Johan S. H.

2016-01-01

Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities. PMID:27440176
Unified Approach to Modeling and Simulation of Space Communication Networks and Systems

NASA Technical Reports Server (NTRS)

Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth

2010-01-01

Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks
Assessing the Increase in Specific Surface Area for Electrospun Fibrous Network due to Pore Induction.

PubMed

Katsogiannis, Konstantinos Alexandros G; Vladisavljević, Goran T; Georgiadou, Stella; Rahmani, Ramin

2016-10-26

The effect of pore induction on increasing electrospun fibrous network specific surface area was investigated in this study. Theoretical models based on the available surface area of the fibrous network and exclusion of the surface area lost due to fiber-to-fiber contacts were developed. The models for calculation of the excluded area are based on Hertzian, Derjaguin-Muller-Toporov (DMT), and Johnson-Kendall-Roberts (JKR) contact models. Overall, the theoretical models correlated the network specific surface area to the material properties including density, surface tension, Young's modulus, Poisson's ratio, as well as network physical properties, such as density and geometrical characteristics including fiber radius, fiber aspect ratio and network thickness. Pore induction proved to increase the network specific surface area up to 52%, compared to the maximum surface area that could be achieved by nonporous fiber network with the same physical properties and geometrical characteristics. The model based on Johnson-Kendall-Roberts contact model describes accurately the fiber-to-fiber contact area under the experimental conditions used for pore generation. The experimental results and the theoretical model based on Johnson-Kendall-Roberts contact model show that the increase in network surface area due to pore induction can reach to up to 58%.
Learning Data Set Influence on Identification Accuracy of Gas Turbine Neural Network Model

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Makaryants, G. M.

2018-01-01

There are many gas turbine engine identification researches via dynamic neural network models. It should minimize errors between model and real object during identification process. Questions about training data set processing of neural networks are usually missed. This article presents a study about influence of data set type on gas turbine neural network model accuracy. The identification object is thermodynamic model of micro gas turbine engine. The thermodynamic model input signal is the fuel consumption and output signal is the engine rotor rotation frequency. Four types input signals was used for creating training and testing data sets of dynamic neural network models - step, fast, slow and mixed. Four dynamic neural networks were created based on these types of training data sets. Each neural network was tested via four types test data sets. In the result 16 transition processes from four neural networks and four test data sets from analogous solving results of thermodynamic model were compared. The errors comparison was made between all neural network errors in each test data set. In the comparison result it was shown error value ranges of each test data set. It is shown that error values ranges is small therefore the influence of data set types on identification accuracy is low.
Using RDF to Model the Structure and Process of Systems

NASA Astrophysics Data System (ADS)

Rodriguez, Marko A.; Watkins, Jennifer H.; Bollen, Johan; Gershenson, Carlos

Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network models. First, the Resource Description Framework (RDF) offers a standardized semantic network data model that can be further formalized by ontology modeling languages such as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent introduction of highly performant triple-stores (i.e. semantic network databases) allows semantic network models on the order of 109 edges to be efficiently stored and manipulated. RDF and its related technologies are currently used extensively in the domains of computer science, digital library science, and the biological sciences. This article will provide an introduction to RDF/RDFS/OWL and an examination of its suitability to model discrete element complex systems.
Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512
A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

PubMed Central

2018-01-01

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients' survival independent of clinicopathological variables. Five networks were significantly associated with patients' survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients' survival in two test sets and training set (p < 0.00001, p < 0.0001 and p = 0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients' prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction. PMID:29581968
Semi-Automated Curation Allows Causal Network Model Building for the Quantification of Age-Dependent Plaque Progression in ApoE-/- Mouse.

PubMed

Szostak, Justyna; Martin, Florian; Talikka, Marja; Peitsch, Manuel C; Hoeng, Julia

2016-01-01

The cellular and molecular mechanisms behind the process of atherosclerotic plaque destabilization are complex, and molecular data from aortic plaques are difficult to interpret. Biological network models may overcome these difficulties and precisely quantify the molecular mechanisms impacted during disease progression. The atherosclerosis plaque destabilization biological network model was constructed with the semiautomated curation pipeline, BELIEF. Cellular and molecular mechanisms promoting plaque destabilization or rupture were captured in the network model. Public transcriptomic data sets were used to demonstrate the specificity of the network model and to capture the different mechanisms that were impacted in ApoE -/- mouse aorta at 6 and 32 weeks. We concluded that network models combined with the network perturbation amplitude algorithm provide a sensitive, quantitative method to follow disease progression at the molecular level. This approach can be used to investigate and quantify molecular mechanisms during plaque progression.
Mixture models with entropy regularization for community detection in networks

NASA Astrophysics Data System (ADS)

Chang, Zhenhai; Yin, Xianjun; Jia, Caiyan; Wang, Xiaoyang

2018-04-01

Community detection is a key exploratory tool in network analysis and has received much attention in recent years. NMM (Newman's mixture model) is one of the best models for exploring a range of network structures including community structure, bipartite and core-periphery structures, etc. However, NMM needs to know the number of communities in advance. Therefore, in this study, we have proposed an entropy regularized mixture model (called EMM), which is capable of inferring the number of communities and identifying network structure contained in a network, simultaneously. In the model, by minimizing the entropy of mixing coefficients of NMM using EM (expectation-maximization) solution, the small clusters contained little information can be discarded step by step. The empirical study on both synthetic networks and real networks has shown that the proposed model EMM is superior to the state-of-the-art methods.
Network bandwidth utilization forecast model on high bandwidth networks

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

Yoo, Wuchert; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology,more » our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.« less

Network Bandwidth Utilization Forecast Model on High Bandwidth Network

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

Yoo, Wucherl; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology,more » our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.« less
Bifurcations of large networks of two-dimensional integrate and fire neurons.

PubMed

Nicola, Wilten; Campbell, Sue Ann

2013-08-01

Recently, a class of two-dimensional integrate and fire models has been used to faithfully model spiking neurons. This class includes the Izhikevich model, the adaptive exponential integrate and fire model, and the quartic integrate and fire model. The bifurcation types for the individual neurons have been thoroughly analyzed by Touboul (SIAM J Appl Math 68(4):1045-1079, 2008). However, when the models are coupled together to form networks, the networks can display bifurcations that an uncoupled oscillator cannot. For example, the networks can transition from firing with a constant rate to burst firing. This paper introduces a technique to reduce a full network of this class of neurons to a mean field model, in the form of a system of switching ordinary differential equations. The reduction uses population density methods and a quasi-steady state approximation to arrive at the mean field system. Reduced models are derived for networks with different topologies and different model neurons with biologically derived parameters. The mean field equations are able to qualitatively and quantitatively describe the bifurcations that the full networks display. Extensions and higher order approximations are discussed.
Predicting Employee Turnover from Communication Networks.

ERIC Educational Resources Information Center

Feeley, Thomas H.; Barnett, George A.

1997-01-01

Investigates three social network models of employee turnover: a structural equivalence model, a social influence model, and an erosion model. Administers a communication network questionnaire to all 170 employees of an organization. Finds support for all three models of turnover, with the erosion model explaining more of the variance than do the…
Social network models predict movement and connectivity in ecological landscapes

USGS Publications Warehouse

Fletcher, R.J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, W.M.

2011-01-01

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.
Estimating standard errors in feature network models.

PubMed

Frank, Laurence E; Heiser, Willem J

2007-05-01

Feature network models are graphical structures that represent proximity data in a discrete space while using the same formalism that is the basis of least squares methods employed in multidimensional scaling. Existing methods to derive a network model from empirical data only give the best-fitting network and yield no standard errors for the parameter estimates. The additivity properties of networks make it possible to consider the model as a univariate (multiple) linear regression problem with positivity restrictions on the parameters. In the present study, both theoretical and empirical standard errors are obtained for the constrained regression parameters of a network model with known features. The performance of both types of standard error is evaluated using Monte Carlo techniques.
A growth model for directed complex networks with power-law shape in the out-degree distribution

PubMed Central

Esquivel-Gómez, J.; Stevens-Navarro, E.; Pineda-Rico, U.; Acosta-Elias, J.

2015-01-01

Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1. PMID:25567141
Software-Enabled Distributed Network Governance: The PopMedNet Experience.

PubMed

Davies, Melanie; Erickson, Kyle; Wyner, Zachary; Malenfant, Jessica; Rosen, Rob; Brown, Jeffrey

2016-01-01

The expanded availability of electronic health information has led to increased interest in distributed health data research networks. The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Four case studies describe how PopMedNet is used to enforce network governance models. Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders.
Weighted Networks at the Polish Market

NASA Astrophysics Data System (ADS)

Chmiel, A. M.; Sienkiewicz, J.; Suchecki, K.; Hołyst, J. A.

During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed.
NetFlow Dynamics

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

Corbet Jr., Thomas F; Beyeler, Walter E; Vanwestrienen, Dirk

NetFlow Dynamics is a web-accessible analysis environment for simulating dynamic flows of materials on model networks. Performing a simulation requires both the NetFlow Dynamics application and a network model which is a description of the structure of the nodes and edges of a network including the flow capacity of each edge and the storage capacity of each node, and the sources and sinks of the material flowing on the network. NetFlow Dynamics consists of databases for storing network models, algorithms to calculate flows on networks, and a GIS-based graphical interface for performing simulations and viewing simulation results. Simulated flows aremore » dynamic in the sense that flows on each edge of the network and inventories at each node change with time and can be out of equilibrium with boundary conditions. Any number of network models could be simulated using Net Flow Dynamics. To date, the models simulated have been models of petroleum infrastructure. The main model has been the National Transportation Fuels Model (NTFM), a network of U.S. oil fields, transmission pipelines, rail lines, refineries, tank farms, and distribution terminals. NetFlow Dynamics supports two different flow algorithms, the Gradient Flow algorithm and the Inventory Control algorithm, that were developed specifically for the NetFlow Dynamics application. The intent is to add additional algorithms in the future as needed. The ability to select from multiple algorithms is desirable because a single algorithm never covers all analysis needs. The current algorithms use a demand-driven capacity-constrained formulation which means that the algorithms strive to use all available capacity and stored inventory to meet desired flows to sinks, subject to the capacity constraints of each network component. The current flow algorithms are best suited for problems in which a material flows on a capacity-constrained network representing a supply chain in which the material supplied can be stored at each node of the network. In the petroleum models, the flowing materials are crude oil and refined products that can be stored at tank farms, refineries, or terminals (i.e. the nodes of the network). Examples of other network models that could be simulated are currency flowing in a financial network, agricultural products moving to market, or natural gas flowing on a pipeline network.« less
3-way Networks: Application of Hypergraphs for Modelling Increased Complexity in Comparative Genomics

DOE PAGES

Weighill, Deborah A.; Jacobson, Daniel A.

2015-03-27

Herein we present and develop the theory of 3-way networks, a type of hypergraph in which each edge models relationships between triplets of objects as opposed to pairs of objects as done by standard network models. We explore approaches of how to prune these 3-way networks, illustrate their utility in comparative genomics and demonstrate how they find relationships which would be missed by standard 2-way network models using a phylogenomic dataset of 211 bacterial genomes.
Modeling of Relation between Transaction Network and Production Activity for Firms

NASA Astrophysics Data System (ADS)

Iino, T.; Iyetomi, H.

Bak et al. [Ricerche Economiche 47 (1993), 3] proposed a self-organizing model for production activity of interacting firms to illustrate how large fluctuations can be triggered by small independent shocks in aggregate economy. This paper develops the original transaction model based on a regular network with layered order flow to accommodate more realistic networks. Simulations in the generalized model so obtained are then carried out for various networks to examine the influence caused by change of the network structure.
3-way Networks: Application of Hypergraphs for Modelling Increased Complexity in Comparative Genomics

PubMed Central

Weighill, Deborah A; Jacobson, Daniel A

2015-01-01

We present and develop the theory of 3-way networks, a type of hypergraph in which each edge models relationships between triplets of objects as opposed to pairs of objects as done by standard network models. We explore approaches of how to prune these 3-way networks, illustrate their utility in comparative genomics and demonstrate how they find relationships which would be missed by standard 2-way network models using a phylogenomic dataset of 211 bacterial genomes. PMID:25815802
Tensor Basis Neural Network v. 1.0 (beta)

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

Ling, Julia; Templeton, Jeremy

This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.
An approximation method for improving dynamic network model fitting.

PubMed

Carnegie, Nicole Bohme; Krivitsky, Pavel N; Hunter, David R; Goodreau, Steven M

There has been a great deal of interest recently in the modeling and simulation of dynamic networks, i.e., networks that change over time. One promising model is the separable temporal exponential-family random graph model (ERGM) of Krivitsky and Handcock, which treats the formation and dissolution of ties in parallel at each time step as independent ERGMs. However, the computational cost of fitting these models can be substantial, particularly for large, sparse networks. Fitting cross-sectional models for observations of a network at a single point in time, while still a non-negligible computational burden, is much easier. This paper examines model fitting when the available data consist of independent measures of cross-sectional network structure and the duration of relationships under the assumption of stationarity. We introduce a simple approximation to the dynamic parameters for sparse networks with relationships of moderate or long duration and show that the approximation method works best in precisely those cases where parameter estimation is most likely to fail-networks with very little change at each time step. We consider a variety of cases: Bernoulli formation and dissolution of ties, independent-tie formation and Bernoulli dissolution, independent-tie formation and dissolution, and dependent-tie formation models.
Hidden Markov models and neural networks for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.
Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

NASA Astrophysics Data System (ADS)

Anderson, Thomas S.

2016-05-01

The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.
Steady state analysis of Boolean molecular network models via model reduction and computational algebra.

PubMed

Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard

2014-06-26

A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem.
Steady state analysis of Boolean molecular network models via model reduction and computational algebra

PubMed Central

2014-01-01

Background A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. Results This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. Conclusions The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem. PMID:24965213
Applications of flow-networks to opinion-dynamics

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Kurths, Jürgen

2015-04-01

Networks were successfully applied to describe complex systems, such as brain, climate, processes in society. Recently a socio-physical problem of opinion-dynamics was studied using network techniques. We present the toy-model of opinion-formation based on the physical model of advection-diffusion. We consider spreading of the opinion on the fixed subject, assuming that opinion on society is binary: if person has opinion then the state of the node in the society-network equals 1, if the person doesn't have opinion state of the node equals 0. Opinion can be spread from one person to another if they know each other, or in the network-terminology, if the nodes are connected. We include into the system governed by advection-diffusion equation the external field to model such effects as for instance influence from media. The assumptions for our model can be formulated as the following: 1.the node-states are influenced by the network structure in such a way, that opinion can be spread only between adjacent nodes (the advective term of the opinion-dynamics), 2.the network evolution can have two scenarios: -network topology is not changing with time; -additional links can appear or disappear each time-step with fixed probability which requires adaptive networks properties. Considering these assumptions for our system we obtain the system of equations describing our model-dynamics which corresponds well to other socio-physics models, for instance, the model of the social cohesion and the famous voter-model. We investigate the behavior of the suggested model studying "waiting time" of the system, time to get to the stable state, stability of the model regimes for different values of model parameters and network topology.
A fault-tolerant small world topology control model in ad hoc networks for search and rescue

NASA Astrophysics Data System (ADS)

Tan, Mian; Fang, Ling; Wu, Yue; Zhang, Bo; Chang, Bowen; Holme, Petter; Zhao, Jing

2018-02-01

Due to their self-organized, multi-hop and distributed characteristics, ad hoc networks are useful in search and rescue. Topology control models need to be designed for energy-efficient, robust and fast communication in ad hoc networks. This paper proposes a topology control model which specializes for search and rescue-Compensation Small World-Repeated Game (CSWRG)-which integrates mobility models, constructing small world networks and a game-theoretic approach to the allocation of resources. Simulation results show that our mobility models can enhance the communication performance of the constructed small-world networks. Our strategy, based on repeated game, can suppress selfish behavior and compensate agents that encounter selfish or faulty neighbors. This model could be useful for the design of ad hoc communication networks.

Model Diagnostics for Bayesian Networks

ERIC Educational Resources Information Center

Sinharay, Sandip

2006-01-01

Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…
Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses

NASA Astrophysics Data System (ADS)

Lezon, Timothy R.; Shrivastava, Indira H.; Yang, Zheng; Bahar, Ivet

The following sections are included: * Introduction * Theory and Assumptions * Statistical mechanical foundations * Anisotropic network models * Gaussian network model * Rigid block models * Treatment of perturbations * Langevin dynamics * Applications * Membrane proteins * Viruses * Conclusion * References
Non-consensus Opinion Models on Complex Networks

NASA Astrophysics Data System (ADS)

Li, Qian; Braunstein, Lidia A.; Wang, Huijuan; Shao, Jia; Stanley, H. Eugene; Havlin, Shlomo

2013-04-01

Social dynamic opinion models have been widely studied to understand how interactions among individuals cause opinions to evolve. Most opinion models that utilize spin interaction models usually produce a consensus steady state in which only one opinion exists. Because in reality different opinions usually coexist, we focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao et al. (Phys. Rev. Lett. 103:01870, 2009). The NCO model in random networks displays a second order phase transition that belongs to regular mean field percolation and is characterized by the appearance (above a certain threshold) of a large spanning cluster of the minority opinion. We generalize the NCO model by adding a weight factor W to each individual's original opinion when determining their future opinion (NCO W model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction than in the NCO model. We also revisit another non-consensus opinion model based on the NCO model, the inflexible contrarian opinion (ICO) model (Li et al. in Phys. Rev. E 84:066101, 2011), which introduces inflexible contrarians to model the competition between two opinions in a steady state. Inflexible contrarians are individuals that never change their original opinion but may influence the opinions of others. To place the inflexible contrarians in the ICO model we use two different strategies, random placement and one in which high-degree nodes are targeted. The inflexible contrarians effectively decrease the size of the largest rival-opinion cluster in both strategies, but the effect is more pronounced under the targeted method. All of the above models have previously been explored in terms of a single network, but human communities are usually interconnected, not isolated. Because opinions propagate not only within single networks but also between networks, and because the rules of opinion formation within a network may differ from those between networks, we study here the opinion dynamics in coupled networks. Each network represents a social group or community and the interdependent links joining individuals from different networks may be social ties that are unusually strong, e.g., married couples. We apply the non-consensus opinion (NCO) rule on each individual network and the global majority rule on interdependent pairs such that two interdependent agents with different opinions will, due to the influence of mass media, follow the majority opinion of the entire population. The opinion interactions within each network and the interdependent links across networks interlace periodically until a steady state is reached. We find that the interdependent links effectively force the system from a second order phase transition, which is characteristic of the NCO model on a single network, to a hybrid phase transition, i.e., a mix of second-order and abrupt jump-like transitions that ultimately becomes, as we increase the percentage of interdependent agents, a pure abrupt transition. We conclude that for the NCO model on coupled networks, interactions through interdependent links could push the non-consensus opinion model to a consensus opinion model, which mimics the reality that increased mass communication causes people to hold opinions that are increasingly similar. We also find that the effect of interdependent links is more pronounced in interdependent scale free networks than in interdependent Erdős Rényi networks.
Optimized planning methodologies of ASON implementation

NASA Astrophysics Data System (ADS)

Zhou, Michael M.; Tamil, Lakshman S.

2005-02-01

Advanced network planning concerns effective network-resource allocation for dynamic and open business environment. Planning methodologies of ASON implementation based on qualitative analysis and mathematical modeling are presented in this paper. The methodology includes method of rationalizing technology and architecture, building network and nodal models, and developing dynamic programming for multi-period deployment. The multi-layered nodal architecture proposed here can accommodate various nodal configurations for a multi-plane optical network and the network modeling presented here computes the required network elements for optimizing resource allocation.
Social inheritance can explain the structure of animal social networks

PubMed Central

Ilany, Amiyaal; Akçay, Erol

2016-01-01

The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101
Dynamic Modeling of Systemic Risk in Financial Networks

NASA Astrophysics Data System (ADS)

Avakian, Adam

Modern financial networks are complicated structures that can contain multiple types of nodes and connections between those nodes. Banks, governments and even individual people weave into an intricate network of debt, risk correlations and many other forms of interconnectedness. We explore multiple types of financial network models with a focus on understanding the dynamics and causes of cascading failures in such systems. In particular, we apply real-world data from multiple sources to these models to better understand real-world financial networks. We use the results of the Federal Reserve "Banking Organization Systemic Risk Report" (FR Y-15), which surveys the largest US banks on their level of interconnectedness, to find relationships between various measures of network connectivity and systemic risk in the US financial sector. This network model is then stress-tested under a number of scenarios to determine systemic risks inherent in the various network structures. We also use detailed historical balance sheet data from the Venezuelan banking system to build a bipartite network model and find relationships between the changing network structure over time and the response of the system to various shocks. We find that the relationship between interconnectedness and systemic risk is highly dependent on the system and model but that it is always a significant one. These models are useful tools that add value to regulators in creating new measurements of systemic risk in financial networks. These models could be used as macroprudential tools for monitoring the health of the entire banking system as a whole rather than only of individual banks.
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.
Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

PubMed

Francis, Andrew; Moulton, Vincent

2018-06-07

Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.
Advanced Performance Modeling with Combined Passive and Active Monitoring

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

Dovrolis, Constantine; Sim, Alex

2015-04-15

To improve the efficiency of resource utilization and scheduling of scientific data transfers on high-speed networks, the "Advanced Performance Modeling with combined passive and active monitoring" (APM) project investigates and models a general-purpose, reusable and expandable network performance estimation framework. The predictive estimation model and the framework will be helpful in optimizing the performance and utilization of networks as well as sharing resources with predictable performance for scientific collaborations, especially in data intensive applications. Our prediction model utilizes historical network performance information from various network activity logs as well as live streaming measurements from network peering devices. Historical network performancemore » information is used without putting extra load on the resources by active measurement collection. Performance measurements collected by active probing is used judiciously for improving the accuracy of predictions.« less
Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases.

PubMed

Masías, Víctor Hugo; Valle, Mauricio; Morselli, Carlo; Crespo, Fernando; Vargas, Augusto; Laengle, Sigifredo

2016-01-01

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers-Logistic Regression, Naïve Bayes and Random Forest-with a range of social network measures and the necessary databases to model the verdicts in two real-world cases: the U.S. Watergate Conspiracy of the 1970's and the now-defunct Canada-based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures.
A hybrid modeling approach for option pricing

NASA Astrophysics Data System (ADS)

Hajizadeh, Ehsan; Seifi, Abbas

2011-11-01

The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.
A new model of the spinal locomotor networks of a salamander and its properties.

PubMed

Liu, Qiang; Yang, Huizhen; Zhang, Jinxue; Wang, Jingzhuo

2018-05-22

A salamander is an ideal animal for studying the spinal locomotor network mechanism of vertebrates from an evolutionary perspective since it represents the transition from an aquatic to a terrestrial animal. However, little is known about the spinal locomotor network of a salamander. A spinal locomotor network model is a useful tool for exploring the working mechanism of the spinal networks of salamanders. A new spinal locomotor network model for a salamander is built for a three-dimensional (3D) biomechanical model of the salamander using a novel locomotion-controlled neural network model. Based on recent experimental data on the spinal circuitry and observational results of gaits of vertebrates, we assume that different interneuron sets recruited for mediating the frequency of spinal circuits are also related to the generation of different gaits. The spinal locomotor networks of salamanders are divided into low-frequency networks for walking and high-frequency networks for swimming. Additionally, a new topological structure between the body networks and limb networks is built, which only uses the body networks to coordinate the motion of limbs. There are no direct synaptic connections among limb networks. These techniques differ from existing salamander spinal locomotor network models. A simulation is performed and analyzed to validate the properties of the new spinal locomotor networks of salamanders. The simulation results show that the new spinal locomotor networks can generate a forward walking gait, a backward walking gait, a swimming gait, and a turning gait during swimming and walking. These gaits can be switched smoothly by changing external inputs from the brainstem. These properties are consistent with those of a real salamander. However, it is still difficult for the new spinal locomotor networks to generate highly efficient turning during walking, 3D swimming, nonrhythmic movements, and so on. New experimental data are required for further validation.
Shaping Neuronal Network Activity by Presynaptic Mechanisms

PubMed Central

Ashery, Uri

2015-01-01

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048
A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

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

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less
A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less
Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

PubMed

Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

2016-12-01

With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.
Developing an Effective Plan for Smart Sanctions: A Network Analysis Approach

DTIC Science & Technology

2012-10-31

data and a network model that realistically simulates the Iranian nuclear development program. We then utilize several network analysis techniques...the Iran Watch (iranwatch.org) watchdog website. Using this data, which at first glance seems obtuse and unwieldy, we constructed network models in... model is created, nodes were evaluated using several measures of centrality. The team then analyzed this network utilizing four of the most common
Modeling, Evaluation and Detection of Jamming Attacks in Time-Critical Wireless Applications

DTIC Science & Technology

2014-08-01

computing, modeling and analysis of wireless networks , network topol- ogy, and architecture design. Dr. Wang has been a Member of the Association for...important, yet open research question is how to model and detect jamming attacks in such wireless networks , where communication traffic is more time...against time-critical wireless networks with applications to the smart grid. In contrast to communication networks where packets-oriented metrics
Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

PubMed

Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina

2015-01-01

Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

DSGRN: Examining the Dynamics of Families of Logical Models.

PubMed

Cummins, Bree; Gedeon, Tomas; Harker, Shaun; Mischaikow, Konstantin

2018-01-01

We present a computational tool DSGRN for exploring the dynamics of a network by computing summaries of the dynamics of switching models compatible with the network across all parameters. The network can arise directly from a biological problem, or indirectly as the interaction graph of a Boolean model. This tool computes a finite decomposition of parameter space such that for each region, the state transition graph that describes the coarse dynamical behavior of a network is the same. Each of these parameter regions corresponds to a different logical description of the network dynamics. The comparison of dynamics across parameters with experimental data allows the rejection of parameter regimes or entire networks as viable models for representing the underlying regulatory mechanisms. This in turn allows a search through the space of perturbations of a given network for networks that robustly fit the data. These are the first steps toward discovering a network that optimally matches the observed dynamics by searching through the space of networks.
Packet Traffic Dynamics Near Onset of Congestion in Data Communication Network Model

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-05-01

The dominant technology of data communication networks is the Packet Switching Network (PSN). It is a complex technology organized as various hierarchical layers according to the International Standard Organization (ISO) Open Systems Interconnect (OSI) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for delivering packets from their sources to their destinations and for dealing with congestion if it arises in a network. Thus, we focus on this layer and present an abstraction of the Network Layer of the ISO OSI Reference Model. Using this abstraction we investigate how onset of traffic congestion is affected for various routing algorithms by changes in network connection topology. We study how aggregate measures of network performance depend on network connection topology and routing. We explore packets traffic spatio-temporal dynamics near the phase transition point from free flow to congestion for various network connection topologies and routing algorithms. We consider static and adaptive routings. We present selected simulation results.
Modeling and optimization of Quality of Service routing in Mobile Ad hoc Networks

NASA Astrophysics Data System (ADS)

Rafsanjani, Marjan Kuchaki; Fatemidokht, Hamideh; Balas, Valentina Emilia

2016-01-01

Mobile ad hoc networks (MANETs) are a group of mobile nodes that are connected without using a fixed infrastructure. In these networks, nodes communicate with each other by forming a single-hop or multi-hop network. To design effective mobile ad hoc networks, it is important to evaluate the performance of multi-hop paths. In this paper, we present a mathematical model for a routing protocol under energy consumption and packet delivery ratio of multi-hop paths. In this model, we use geometric random graphs rather than random graphs. Our proposed model finds effective paths that minimize the energy consumption and maximizes the packet delivery ratio of the network. Validation of the mathematical model is performed through simulation.
Modeling the propagation of mobile malware on complex networks

NASA Astrophysics Data System (ADS)

Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue

2016-08-01

In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.
An artificial neural network improves prediction of observed survival in patients with laryngeal squamous carcinoma.

PubMed

Jones, Andrew S; Taktak, Azzam G F; Helliwell, Timothy R; Fenton, John E; Birchall, Martin A; Husband, David J; Fisher, Anthony C

2006-06-01

The accepted method of modelling and predicting failure/survival, Cox's proportional hazards model, is theoretically inferior to neural network derived models for analysing highly complex systems with large datasets. A blinded comparison of the neural network versus the Cox's model in predicting survival utilising data from 873 treated patients with laryngeal cancer. These were divided randomly and equally into a training set and a study set and Cox's and neural network models applied in turn. Data were then divided into seven sets of binary covariates and the analysis repeated. Overall survival was not significantly different on Kaplan-Meier plot, or with either test model. Although the network produced qualitatively similar results to Cox's model it was significantly more sensitive to differences in survival curves for age and N stage. We propose that neural networks are capable of prediction in systems involving complex interactions between variables and non-linearity.
Modelling temporal networks of human face-to-face contacts with public activity and individual reachability

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qing; Cui, Jing; Zhang, Shu-Min; Zhang, Qi; Li, Xiang

2016-02-01

Modelling temporal networks of human face-to-face contacts is vital both for understanding the spread of airborne pathogens and word-of-mouth spreading of information. Although many efforts have been devoted to model these temporal networks, there are still two important social features, public activity and individual reachability, have been ignored in these models. Here we present a simple model that captures these two features and other typical properties of empirical face-to-face contact networks. The model describes agents which are characterized by an attractiveness to slow down the motion of nearby people, have event-triggered active probability and perform an activity-dependent biased random walk in a square box with periodic boundary. The model quantitatively reproduces two empirical temporal networks of human face-to-face contacts which are testified by their network properties and the epidemic spread dynamics on them.
An information model for a virtual private optical network (OVPN) using virtual routers (VRs)

NASA Astrophysics Data System (ADS)

Vo, Viet Minh Nhat

2002-05-01

This paper describes a virtual private optical network architecture (Optical VPN - OVPN) based on virtual router (VR). It improves over architectures suggested for virtual private networks by using virtual routers with optical networks. The new things in this architecture are necessary changes to adapt to devices and protocols used in optical networks. This paper also presents information models for the OVPN: at the architecture level and at the service level. These are extensions to the DEN (directory enable network) and CIM (Common Information Model) for OVPNs using VRs. The goal is to propose a common management model using policies.
Random graph models for dynamic networks

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Moore, Cristopher; Newman, Mark E. J.

2017-10-01

Recent theoretical work on the modeling of network structure has focused primarily on networks that are static and unchanging, but many real-world networks change their structure over time. There exist natural generalizations to the dynamic case of many static network models, including the classic random graph, the configuration model, and the stochastic block model, where one assumes that the appearance and disappearance of edges are governed by continuous-time Markov processes with rate parameters that can depend on properties of the nodes. Here we give an introduction to this class of models, showing for instance how one can compute their equilibrium properties. We also demonstrate their use in data analysis and statistical inference, giving efficient algorithms for fitting them to observed network data using the method of maximum likelihood. This allows us, for example, to estimate the time constants of network evolution or infer community structure from temporal network data using cues embedded both in the probabilities over time that node pairs are connected by edges and in the characteristic dynamics of edge appearance and disappearance. We illustrate these methods with a selection of applications, both to computer-generated test networks and real-world examples.
Enhanced storage capacity with errors in scale-free Hopfield neural networks: An analytical study.

PubMed

Kim, Do-Hyun; Park, Jinha; Kahng, Byungnam

2017-01-01

The Hopfield model is a pioneering neural network model with associative memory retrieval. The analytical solution of the model in mean field limit revealed that memories can be retrieved without any error up to a finite storage capacity of O(N), where N is the system size. Beyond the threshold, they are completely lost. Since the introduction of the Hopfield model, the theory of neural networks has been further developed toward realistic neural networks using analog neurons, spiking neurons, etc. Nevertheless, those advances are based on fully connected networks, which are inconsistent with recent experimental discovery that the number of connections of each neuron seems to be heterogeneous, following a heavy-tailed distribution. Motivated by this observation, we consider the Hopfield model on scale-free networks and obtain a different pattern of associative memory retrieval from that obtained on the fully connected network: the storage capacity becomes tremendously enhanced but with some error in the memory retrieval, which appears as the heterogeneity of the connections is increased. Moreover, the error rates are also obtained on several real neural networks and are indeed similar to that on scale-free model networks.
Statistical modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.
Modeling Diagnostic Assessments with Bayesian Networks

ERIC Educational Resources Information Center

Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego

2007-01-01

This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Towards a Framework for Evolvable Network Design

NASA Astrophysics Data System (ADS)

Hassan, Hoda; Eltarras, Ramy; Eltoweissy, Mohamed

The layered Internet architecture that had long guided network design and protocol engineering was an “interconnection architecture” defining a framework for interconnecting networks rather than a model for generic network structuring and engineering. We claim that the approach of abstracting the network in terms of an internetwork hinders the thorough understanding of the network salient characteristics and emergent behavior resulting in impeding design evolution required to address extreme scale, heterogeneity, and complexity. This paper reports on our work in progress that aims to: 1) Investigate the problem space in terms of the factors and decisions that influenced the design and development of computer networks; 2) Sketch the core principles for designing complex computer networks; and 3) Propose a model and related framework for building evolvable, adaptable and self organizing networks We will adopt a bottom up strategy primarily focusing on the building unit of the network model, which we call the “network cell”. The model is inspired by natural complex systems. A network cell is intrinsically capable of specialization, adaptation and evolution. Subsequently, we propose CellNet; a framework for evolvable network design. We outline scenarios for using the CellNet framework to enhance legacy Internet protocol stack.
Synergistic effects in threshold models on networks.

PubMed

Juul, Jonas S; Porter, Mason A

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can-depending on a parameter-either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.
Synergistic effects in threshold models on networks

NASA Astrophysics Data System (ADS)

Juul, Jonas S.; Porter, Mason A.

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.
Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

PubMed Central

Lange, Stefan; Donges, Jonathan F.; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation. Building on a recent study by Feldhoff et al. [1] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system. Three types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed. PMID:25856374
Local difference measures between complex networks for dynamical system model evaluation.

PubMed

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed.
Generalized Adaptive Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1993-01-01

Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.
Time Series Neural Network Model for Part-of-Speech Tagging Indonesian Language

NASA Astrophysics Data System (ADS)

Tanadi, Theo

2018-03-01

Part-of-speech tagging (POS tagging) is an important part in natural language processing. Many methods have been used to do this task, including neural network. This paper models a neural network that attempts to do POS tagging. A time series neural network is modelled to solve the problems that a basic neural network faces when attempting to do POS tagging. In order to enable the neural network to have text data input, the text data will get clustered first using Brown Clustering, resulting a binary dictionary that the neural network can use. To further the accuracy of the neural network, other features such as the POS tag, suffix, and affix of previous words would also be fed to the neural network.
On Connectivity of Wireless Sensor Networks with Directional Antennas

PubMed Central

Wang, Qiu; Dai, Hong-Ning; Zheng, Zibin; Imran, Muhammad; Vasilakos, Athanasios V.

2017-01-01

In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models. PMID:28085081
Spatial Epidemic Modelling in Social Networks

NASA Astrophysics Data System (ADS)

Simoes, Joana Margarida

2005-06-01

The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

Modeling of workflow-engaged networks on radiology transfers across a metro network.

PubMed

Camorlinga, Sergio; Schofield, Bruce

2006-04-01

Radiology metro networks bear the challenging proposition of interconnecting several hospitals in a region to provide a comprehensive diagnostic imaging service. Consequences of a poorly designed and implemented metro network could cause delays or no access at all when health care providers try to retrieve medical cases across the network. This could translate into limited diagnostic services to patients, resulting in negative impacts to the patients' medical treatment. A workflow-engaged network (WEN) is a new network paradigm. A WEN appreciates radiology workflows and priorities in using the network. A WEN greatly improves the network performance by guaranteeing that critical image transfers experience minimal delay. It adjusts network settings to ensure the application's requirements are met. This means that high-priority image transfers will have guaranteed and known delay times, whereas lower-priority traffic will have increased delays. This paper introduces a modeling to understand the benefits that WEN brings to a radiology metro network. The modeling uses actual data patterns and flows found in a hospital metro region. The workflows considered are based on the Integrating the Healthcare Enterprise profiles. This modeling has been applied to metropolitan workflows of a health region. The modeling helps identify the kind of metro network that supports data patterns and flows in a metro area. The results of the modeling show that a 155-Mb/s metropolitan area network (MAN) with WEN operates virtually equal to a normal 622-Mb/s MAN without WEN, with potential cost savings for leased line services measured in the millions of dollars per year.
Epidemic threshold of the susceptible-infected-susceptible model on complex networks

NASA Astrophysics Data System (ADS)

Lee, Hyun Keun; Shim, Pyoung-Seop; Noh, Jae Dong

2013-06-01

We demonstrate that the susceptible-infected-susceptible (SIS) model on complex networks can have an inactive Griffiths phase characterized by a slow relaxation dynamics. It contrasts with the mean-field theoretical prediction that the SIS model on complex networks is active at any nonzero infection rate. The dynamic fluctuation of infected nodes, ignored in the mean field approach, is responsible for the inactive phase. It is proposed that the question whether the epidemic threshold of the SIS model on complex networks is zero or not can be resolved by the percolation threshold in a model where nodes are occupied in degree-descending order. Our arguments are supported by the numerical studies on scale-free network models.
Plant Growth Models Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Bubenheim, David

1997-01-01

In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.
Tracking trade transactions in water resource systems: A node-arc optimization formulation

NASA Astrophysics Data System (ADS)

Erfani, Tohid; Huskova, Ivana; Harou, Julien J.

2013-05-01

We formulate and apply a multicommodity network flow node-arc optimization model capable of tracking trade transactions in complex water resource systems. The model uses a simple node to node network connectivity matrix and does not require preprocessing of all possible flow paths in the network. We compare the proposed node-arc formulation with an existing arc-path (flow path) formulation and explain the advantages and difficulties of both approaches. We verify the proposed formulation model on a hypothetical water distribution network. Results indicate the arc-path model solves the problem with fewer constraints, but the proposed formulation allows using a simple network connectivity matrix which simplifies modeling large or complex networks. The proposed algorithm allows converting existing node-arc hydroeconomic models that broadly represent water trading to ones that also track individual supplier-receiver relationships (trade transactions).
A game theory-based trust measurement model for social networks.

PubMed

Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

2016-01-01

In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.
Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.
Testing a model of facilitated reflection on network feedback: a mixed method study on integration of rural mental healthcare services for older people.

PubMed

Fuller, Jeffrey; Oster, Candice; Muir Cochrane, Eimear; Dawson, Suzanne; Lawn, Sharon; Henderson, Julie; O'Kane, Deb; Gerace, Adam; McPhail, Ruth; Sparkes, Deb; Fuller, Michelle; Reed, Richard L

2015-11-11

To test a management model of facilitated reflection on network feedback as a means to engage services in problem solving the delivery of integrated primary mental healthcare to older people. Participatory mixed methods case study evaluating the impact of a network management model using organisational network feedback (through social network analysis, key informant interviews and policy review). A model of facilitated network reflection using network theory and methods. A rural community in South Australia. 32 staff from 24 services and 12 senior service managers from mental health, primary care and social care services. Health and social care organisations identified that they operated in clustered self-managed networks within sectors, with no overarching purposive older people's mental healthcare network. The model of facilitated reflection revealed service goal and role conflicts. These discussions helped local services to identify as a network, and begin the problem-solving communication and referral links. A Governance Group assisted this process. Barriers to integrated servicing through a network included service funding tied to performance of direct care tasks and the lack of a clear lead network administration organisation. A model of facilitated reflection helped organisations to identify as a network, but revealed sensitivity about organisational roles and goals, which demonstrated that conflict should be expected. Networked servicing needed a neutral network administration organisation with cross-sectoral credibility, a mandate and the resources to monitor the network, to deal with conflict, negotiate commitment among the service managers, and provide opportunities for different sectors to meet and problem solve. This requires consistency and sustained intersectoral policies that include strategies and funding to facilitate and maintain health and social care networks in rural communities. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Cyber threat model for tactical radio networks

NASA Astrophysics Data System (ADS)

Kurdziel, Michael T.

2014-05-01

The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.
Innovative research of AD HOC network mobility model

NASA Astrophysics Data System (ADS)

Chen, Xin

2017-08-01

It is difficult for researchers of AD HOC network to conduct actual deployment during experimental stage as the network topology is changeable and location of nodes is unfixed. Thus simulation still remains the main research method of the network. Mobility model is an important component of AD HOC network simulation. It is used to describe the movement pattern of nodes in AD HOC network (including location and velocity, etc.) and decides the movement trail of nodes, playing as the abstraction of the movement modes of nodes. Therefore, mobility model which simulates node movement is an important foundation for simulation research. In AD HOC network research, mobility model shall reflect the movement law of nodes as truly as possible. In this paper, node generally refers to the wireless equipment people carry. The main research contents include how nodes avoid obstacles during movement process and the impacts of obstacles on the mutual relation among nodes, based on which a Node Self Avoiding Obstacle, i.e. NASO model is established in AD HOC network.
A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.
Multilayer Brain Networks

NASA Astrophysics Data System (ADS)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.
LavaNet—Neural network development environment in a general mine planning package

NASA Astrophysics Data System (ADS)

Kapageridis, Ioannis Konstantinou; Triantafyllou, A. G.

2011-04-01

LavaNet is a series of scripts written in Perl that gives access to a neural network simulation environment inside a general mine planning package. A well known and a very popular neural network development environment, the Stuttgart Neural Network Simulator, is used as the base for the development of neural networks. LavaNet runs inside VULCAN™—a complete mine planning package with advanced database, modelling and visualisation capabilities. LavaNet is taking advantage of VULCAN's Perl based scripting environment, Lava, to bring all the benefits of neural network development and application to geologists, mining engineers and other users of the specific mine planning package. LavaNet enables easy development of neural network training data sets using information from any of the data and model structures available, such as block models and drillhole databases. Neural networks can be trained inside VULCAN™ and the results be used to generate new models that can be visualised in 3D. Direct comparison of developed neural network models with conventional and geostatistical techniques is now possible within the same mine planning software package. LavaNet supports Radial Basis Function networks, Multi-Layer Perceptrons and Self-Organised Maps.
Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

PubMed

Ehret, Phillip J; Monroe, Brian M; Read, Stephen J

2015-05-01

We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory. © 2014 by the Society for Personality and Social Psychology, Inc.
Neural network submodel as an abstraction tool: relating network performance to combat outcome

NASA Astrophysics Data System (ADS)

Jablunovsky, Greg; Dorman, Clark; Yaworsky, Paul S.

2000-06-01

Simulation of Command and Control (C2) networks has historically emphasized individual system performance with little architectural context or credible linkage to `bottom- line' measures of combat outcomes. Renewed interest in modeling C2 effects and relationships stems from emerging network intensive operational concepts. This demands improved methods to span the analytical hierarchy between C2 system performance models and theater-level models. Neural network technology offers a modeling approach that can abstract the essential behavior of higher resolution C2 models within a campaign simulation. The proposed methodology uses off-line learning of the relationships between network state and campaign-impacting performance of a complex C2 architecture and then approximation of that performance as a time-varying parameter in an aggregated simulation. Ultimately, this abstraction tool offers an increased fidelity of C2 system simulation that captures dynamic network dependencies within a campaign context.
Communications network design and costing model technical manual

NASA Technical Reports Server (NTRS)

Logan, K. P.; Somes, S. S.; Clark, C. A.

1983-01-01

This computer model provides the capability for analyzing long-haul trunking networks comprising a set of user-defined cities, traffic conditions, and tariff rates. Networks may consist of all terrestrial connectivity, all satellite connectivity, or a combination of terrestrial and satellite connectivity. Network solutions provide the least-cost routes between all cities, the least-cost network routing configuration, and terrestrial and satellite service cost totals. The CNDC model allows analyses involving three specific FCC-approved tariffs, which are uniquely structured and representative of most existing service connectivity and pricing philosophies. User-defined tariffs that can be variations of these three tariffs are accepted as input to the model and allow considerable flexibility in network problem specification. The resulting model extends the domain of network analysis from traditional fixed link cost (distance-sensitive) problems to more complex problems involving combinations of distance and traffic-sensitive tariffs.
Deformable complex network for refining low-resolution X-ray structures

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

Zhang, Chong; Wang, Qinghua; Ma, Jianpeng, E-mail: jpma@bcm.edu

2015-10-27

A new refinement algorithm called the deformable complex network that combines a novel angular network-based restraint with a deformable elastic network model in the target function has been developed to aid in structural refinement in macromolecular X-ray crystallography. In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint withmore » the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.« less
Complex networks under dynamic repair model

NASA Astrophysics Data System (ADS)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.
From calls to communities: a model for time-varying social networks

NASA Astrophysics Data System (ADS)

Laurent, Guillaume; Saramäki, Jari; Karsai, Márton

2015-11-01

Social interactions vary in time and appear to be driven by intrinsic mechanisms that shape the emergent structure of social networks. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model integrates key mechanisms that drive the formation of social ties - social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and small-world connectedness in social networks. We compare the proposed model with a real-world time-varying network of mobile phone communication, and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, including the role of weak ties.
Markov State Models of gene regulatory networks.

PubMed

Chu, Brian K; Tse, Margaret J; Sato, Royce R; Read, Elizabeth L

2017-02-06

Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models. Application of transition path theory to the constructed Markov State Model decomposes global dynamics into a set of dominant transition paths and associated relative probabilities for stochastic state-switching. In this proof-of-concept study, we found that the Markov State Model provides a general framework for analyzing and visualizing stochastic multistability and state-transitions in gene networks. Our results suggest that this framework-adopted from the field of atomistic Molecular Dynamics-can be a useful tool for quantitative Systems Biology at the network scale.
Associative memory in phasing neuron networks

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

Nair, Niketh S; Bochove, Erik J.; Braiman, Yehuda

2014-01-01

We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

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