Mouse Genome Informatics (MGI): Resources for Mining Mouse Genetic, Genomic, and Biological Data in Support of Primary and Translational Research.

PubMed

Eppig, Janan T; Smith, Cynthia L; Blake, Judith A; Ringwald, Martin; Kadin, James A; Richardson, Joel E; Bult, Carol J

2017-01-01

The Mouse Genome Informatics (MGI), resource ( www.informatics.jax.org ) has existed for over 25 years, and over this time its data content, informatics infrastructure, and user interfaces and tools have undergone dramatic changes (Eppig et al., Mamm Genome 26:272-284, 2015). Change has been driven by scientific methodological advances, rapid improvements in computational software, growth in computer hardware capacity, and the ongoing collaborative nature of the mouse genomics community in building resources and sharing data. Here we present an overview of the current data content of MGI, describe its general organization, and provide examples using simple and complex searches, and tools for mining and retrieving sets of data.

Applications of artificial neural networks (ANNs) in food science.

PubMed

Huang, Yiqun; Kangas, Lars J; Rasco, Barbara A

2007-01-01

Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.

An Overview of ANN Application in the Power Industry

NASA Technical Reports Server (NTRS)

Niebur, D.

1995-01-01

The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

Final Technical Report, Wind Generator Project (Ann Arbor)

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

Geisler, Nathan

A Final Technical Report (57 pages) describing educational exhibits and devices focused on wind energy, and related outreach activities and programs. Project partnership includes the City of Ann Arbor, MI and the Ann Arbor Hands-on Museum, along with additional sub-recipients, and U.S. Department of Energy/Office of Energy Efficiency and Renewable Energy (EERE). Report relays key milestones and sub-tasks as well as numerous graphics and images of five (5) transportable wind energy demonstration devices and five (5) wind energy exhibits designed and constructed between 2014 and 2016 for transport and use by the Ann Arbor Hands-on Museum.

iAnn: an event sharing platform for the life sciences.

PubMed

Jimenez, Rafael C; Albar, Juan P; Bhak, Jong; Blatter, Marie-Claude; Blicher, Thomas; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; van Driel, Marc A; Dunn, Michael J; Fernandes, Pedro L; van Gelder, Celia W G; Hermjakob, Henning; Ioannidis, Vassilios; Judge, David P; Kahlem, Pascal; Korpelainen, Eija; Kraus, Hans-Joachim; Loveland, Jane; Mayer, Christine; McDowall, Jennifer; Moran, Federico; Mulder, Nicola; Nyronen, Tommi; Rother, Kristian; Salazar, Gustavo A; Schneider, Reinhard; Via, Allegra; Villaveces, Jose M; Yu, Ping; Schneider, Maria V; Attwood, Teresa K; Corpas, Manuel

2013-08-01

We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available. http://iann.pro/iannviewer manuel.corpas@tgac.ac.uk.

An ANN That Applies Pragmatic Decision on Texts.

ERIC Educational Resources Information Center

Aretoulaki, Maria; Tsujii, Jun-ichi

A computer-based artificial neural network (ANN) that learns to classify sentences in a text as important or unimportant is described. The program is designed to select the sentences that are important enough to be included in composition of an abstract of the text. The ANN is embedded in a conventional symbolic environment consisting of…

Optimal conditions of LDR to protect the kidney from diabetes: exposure to 12.5 mGy X-rays for 8 weeks efficiently protects the kidney from diabetes.

PubMed

Cheng, Jie; Li, Fengsheng; Cui, Jiuwei; Guo, Weiying; Li, Cai; Li, Wei; Wang, Guixia; Xing, Xiao; Gao, Ying; Ge, Yuanyuan; Wang, Guanjun; Cai, Lu

2014-05-08

We reported the attenuation of diabetes-induced renal dysfunction by exposure to multiple low-dose radiation (LDR) at 25 mGy every other day by suppressing renal oxidative damage. We here explored the optimal conditions of LDR to protect the kidney from diabetes. Male C57BL/6J mice with type 1 diabetes were induced with multiple injections of low-dose streptozotocin. Diabetic mice received whole body X-irradiation at a dose of 12.5, 25 or 50 mGy every other day for either 4 or 8 weeks. Age-matched normal mice were similarly irradiated at the dose of 25 mGy for 4 or 8 weeks. The renal function and histopathological changes were examined at the 4th and 8th weeks of the study. Diabetes induced renal dysfunction is shown by the decreased creatinine and increased microalbumin in the urine. Renal oxidative damage, detected by protein nitration and lipid oxidation, and remodeling, reflected by increased expression of connective tissue growth factor, collagen IV and fibronectin, were significantly increased in diabetic mice. All these renal pathological and function changes in diabetic mice were significantly attenuated by exposure to LDR at all regimens, among which, however, exposure to LDR at 12.5 mGy for 8 weeks provided the best protective effect on the kidney of diabetic mice. Our results suggest that whole-body LDR at 12.5 mGy every other day for 8 weeks is the optimal condition of LDR to protect the kidney from diabetes. Copyright © 2014 Elsevier Inc. All rights reserved.

77 FR 75629 - Pramaggiore, Anne R.; Notice of Filing

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-21

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ID-6059-001] Pramaggiore, Anne R.; Notice of Filing Take notice that on December 14, 2012, Anne R. Pramaggiore submitted for filing, an application for authority to hold interlocking positions, pursuant to section 305(b) of the...

Modeling and prediction of copper removal from aqueous solutions by nZVI/rGO magnetic nanocomposites using ANN-GA and ANN-PSO.

PubMed

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Xiong, Kangning; Wei, Xionghui

2017-12-21

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) magnetic nanocomposites were prepared and then applied in the Cu(II) removal from aqueous solutions. Scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy and superconduction quantum interference device magnetometer were performed to characterize the nZVI/rGO nanocomposites. In order to reduce the number of experiments and the economic cost, response surface methodology (RSM) combined with artificial intelligence (AI) techniques, such as artificial neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), has been utilized as a major tool that can model and optimize the removal processes, because a tremendous advance has recently been made on AI that may result in extensive applications. Based on RSM, ANN-GA and ANN-PSO were employed to model the Cu(II) removal process and optimize the operating parameters, e.g., operating temperature, initial pH, initial concentration and contact time. The ANN-PSO model was proven to be an effective tool for modeling and optimizing the Cu(II) removal with a low absolute error and a high removal efficiency. Furthermore, the isotherm, kinetic, thermodynamic studies and the XPS analysis were performed to explore the mechanisms of Cu(II) removal process.

ANN modeling of DNA sequences: new strategies using DNA shape code.

PubMed

Parbhane, R V; Tambe, S S; Kulkarni, B D

2000-09-01

Two new encoding strategies, namely, wedge and twist codes, which are based on the DNA helical parameters, are introduced to represent DNA sequences in artificial neural network (ANN)-based modeling of biological systems. The performance of the new coding strategies has been evaluated by conducting three case studies involving mapping (modeling) and classification applications of ANNs. The proposed coding schemes have been compared rigorously and shown to outperform the existing coding strategies especially in situations wherein limited data are available for building the ANN models.

Using artificial neural networks (ANN) for open-loop tomography

NASA Astrophysics Data System (ADS)

Osborn, James; De Cos Juez, Francisco Javier; Guzman, Dani; Butterley, Timothy; Myers, Richard; Guesalaga, Andres; Laine, Jesus

2011-09-01

The next generation of adaptive optics (AO) systems require tomographic techniques in order to correct for atmospheric turbulence along lines of sight separated from the guide stars. Multi-object adaptive optics (MOAO) is one such technique. Here, we present a method which uses an artificial neural network (ANN) to reconstruct the target phase given off-axis references sources. This method does not require any input of the turbulence profile and is therefore less susceptible to changing conditions than some existing methods. We compare our ANN method with a standard least squares type matrix multiplication method (MVM) in simulation and find that the tomographic error is similar to the MVM method. In changing conditions the tomographic error increases for MVM but remains constant with the ANN model and no large matrix inversions are required.

Ann Eliza Young: A Nineteenth Century Champion of Women's Rights.

ERIC Educational Resources Information Center

Cullen, Jack B.

Concentrating on the efforts of such nineteenth century women's rights advocates as Susan B. Anthony and Elizabeth Cady Stanton, communication researchers have largely overlooked the contributions made to the cause by Ann Eliza Young. The nineteenth wife of Mormon leader Brigham Young, Ann Eliza Young left her husband and took to the speaker's…

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 1 2013-10-01 2013-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 1 2014-10-01 2014-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

46 CFR 7.10 - Eastport, ME to Cape Ann, MA.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Eastport, ME to Cape Ann, MA. 7.10 Section 7.10 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY PROCEDURES APPLICABLE TO THE PUBLIC BOUNDARY LINES Atlantic Coast § 7.10 Eastport, ME to Cape Ann, MA. (a) A line drawn from the easternmost extremity of Kendall...

A novel modular ANN architecture for efficient monitoring of gases/odours in real-time

NASA Astrophysics Data System (ADS)

Mishra, A.; Rajput, N. S.

2018-04-01

Data pre-processing is tremendously used for enhanced classification of gases. However, it suppresses the concentration variances of different gas samples. A classical solution of using single artificial neural network (ANN) architecture is also inefficient and renders degraded quantification. In this paper, a novel modular ANN design has been proposed to provide an efficient and scalable solution in real–time. Here, two separate ANN blocks viz. classifier block and quantifier block have been used to provide efficient and scalable gas monitoring in real—time. The classifier ANN consists of two stages. In the first stage, the Net 1-NDSRT has been trained to transform raw sensor responses into corresponding virtual multi-sensor responses using normalized difference sensor response transformation (NDSRT). These responses have been fed to the second stage (i.e., Net 2-classifier ). The Net 2-classifier has been trained to classify various gas samples to their respective class. Further, the quantifier block has parallel ANN modules, multiplexed to quantify each gas. Therefore, the classifier ANN decides class and quantifier ANN decides the exact quantity of the gas/odor present in the respective sample of that class.

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

33 CFR 80.120 - Cape Ann, MA to Marblehead Neck, MA.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Cape Ann, MA to Marblehead Neck, MA. 80.120 Section 80.120 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.120 Cape Ann, MA to...

Identification of drought in Dhalai river watershed using MCDM and ANN models

NASA Astrophysics Data System (ADS)

Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

2017-03-01

An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

A > 4 MGy radiation tolerant 8 THzOhm transimpedance amplifier with 50 dB dynamic range

NASA Astrophysics Data System (ADS)

Verbeeck, J.; Steyaert, M.; Leroux, P.

2013-02-01

A 130 nm Transimpedance Amplifier has been developed with a 255 MHz bandwidth, 90 dBΩ transimpedance gain and a dynamic input range of 1:325 or 50 dB for a photo-diode capacitance of 0.75 pF. The equivalent integrated input noise is 160 nA @ 25°C. The gain of the voltage amplifier, used in the transimpedance amplifier (TIA), degrades less than 3% over a temperature range from -40 °C up to 125 °C. The TIA and attenuator exhibit a radiation tolerance larger than 4 MGy, as evidenced by radiation assessment.

A Hybrid FEM-ANN Approach for Slope Instability Prediction

NASA Astrophysics Data System (ADS)

Verma, A. K.; Singh, T. N.; Chauhan, Nikhil Kumar; Sarkar, K.

2016-09-01

Assessment of slope stability is one of the most critical aspects for the life of a slope. In any slope vulnerability appraisal, Factor Of Safety (FOS) is the widely accepted index to understand, how close or far a slope from the failure. In this work, an attempt has been made to simulate a road cut slope in a landslide prone area in Rudrapryag, Uttarakhand, India which lies near Himalayan geodynamic mountain belt. A combination of Finite Element Method (FEM) and Artificial Neural Network (ANN) has been adopted to predict FOS of the slope. In ANN, a three layer, feed- forward back-propagation neural network with one input layer and one hidden layer with three neurons and one output layer has been considered and trained using datasets generated from numerical analysis of the slope and validated with new set of field slope data. Mean absolute percentage error estimated as 1.04 with coefficient of correlation between the FOS of FEM and ANN as 0.973, which indicates that the system is very vigorous and fast to predict FOS for any slope.

Comparison of Conventional and ANN Models for River Flow Forecasting

NASA Astrophysics Data System (ADS)

Jain, A.; Ganti, R.

2011-12-01

Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

75 FR 418 - Certificate of Alternative Compliance for the Offshore Supply Vessel KELLY ANN CANDIES

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-05

... Compliance for the Offshore Supply Vessel KELLY ANN CANDIES AGENCY: Coast Guard, DHS. ACTION: Notice. SUMMARY... supply vessel KELLY ANN CANDIES as required by 33 U.S.C. 1605(c) and 33 CFR 81.18. DATES: The Certificate... Purpose The offshore supply vessel KELLY ANN CANDIES will be used for offshore supply operations. Full...

Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

ERIC Educational Resources Information Center

Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

2011-01-01

Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

Saint Anne: A Multicultural Education Dilemma.

ERIC Educational Resources Information Center

Bruce, Bill; And Others

This 5-hour simulation is designed to give secondary- and college-level students and community persons the opportunity to deal with multicultural issues in a typical organizational and community setting. St. Anne is a fictitious town of 75,000 residents with two major ethnic neighborhoods--one German and the other Swedish. The local paper industry…

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

NASA Astrophysics Data System (ADS)

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

2011-01-01

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration

Prediction of Film Cooling Effectiveness on a Gas Turbine Blade Leading Edge Using ANN and CFD

NASA Astrophysics Data System (ADS)

Dávalos, J. O.; García, J. C.; Urquiza, G.; Huicochea, A.; De Santiago, O.

2018-05-01

In this work, the area-averaged film cooling effectiveness (AAFCE) on a gas turbine blade leading edge was predicted by employing an artificial neural network (ANN) using as input variables: hole diameter, injection angle, blowing ratio, hole and columns pitch. The database used to train the network was built using computational fluid dynamics (CFD) based on a two level full factorial design of experiments. The CFD numerical model was validated with an experimental rig, where a first stage blade of a gas turbine was represented by a cylindrical specimen. The ANN architecture was composed of three layers with four neurons in hidden layer and Levenberg-Marquardt was selected as ANN optimization algorithm. The AAFCE was successfully predicted by the ANN with a regression coefficient R2<0.99 and a root mean square error RMSE=0.0038. The ANN weight coefficients were used to estimate the relative importance of the input parameters. Blowing ratio was the most influential parameter with relative importance of 40.36 % followed by hole diameter. Additionally, by using the ANN model, the relationship between input parameters was analyzed.

Modeling and forecasting of KLCI weekly return using WT-ANN integrated model

NASA Astrophysics Data System (ADS)

Liew, Wei-Thong; Liong, Choong-Yeun; Hussain, Saiful Izzuan; Isa, Zaidi

2013-04-01

The forecasting of weekly return is one of the most challenging tasks in investment since the time series are volatile and non-stationary. In this study, an integrated model of wavelet transform and artificial neural network, WT-ANN is studied for modeling and forecasting of KLCI weekly return. First, the WT is applied to decompose the weekly return time series in order to eliminate noise. Then, a mathematical model of the time series is constructed using the ANN. The performance of the suggested model will be evaluated by root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE). The result shows that the WT-ANN model can be considered as a feasible and powerful model for time series modeling and prediction.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Thomas Tate, a third grade student at Anne Beers Elementary school, asks a question following a presentation by the crew of STS-127, Thursday, Sept. 24, 2009, in Washington. Photo Credit: (NASA/Paul E. Alers)

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

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

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actualmore » experimental observations.« less

Comparison of ANN and RKS approaches to model SCC strength

NASA Astrophysics Data System (ADS)

Prakash, Aravind J.; Sathyan, Dhanya; Anand, K. B.; Aravind, N. R.

2018-02-01

Self compacting concrete (SCC) is a high performance concrete that has high flowability and can be used in heavily reinforced concrete members with minimal compaction segregation and bleeding. The mix proportioning of SCC is highly complex and large number of trials are required to get the mix with the desired properties resulting in the wastage of materials and time. The research on SCC has been highly empirical and no theoretical relationships have been developed between the mixture proportioning and engineering properties of SCC. In this work effectiveness of artificial neural network (ANN) and random kitchen sink algorithm(RKS) with regularized least square algorithm(RLS) in predicting the split tensile strength of the SCC is analysed. Random kitchen sink algorithm is used for mapping data to higher dimension and classification of this data is done using Regularized least square algorithm. The training and testing data for the algorithm was obtained experimentally using standard test procedures and materials available. Total of 40 trials were done which were used as the training and testing data. Trials were performed by varying the amount of fine aggregate, coarse aggregate, dosage and type of super plasticizer and water. Prediction accuracy of the ANN and RKS model is checked by comparing the RMSE value of both ANN and RKS. Analysis shows that eventhough the RKS model is good for large data set, its prediction accuracy is as good as conventional prediction method like ANN so the split tensile strength model developed by RKS can be used in industries for the proportioning of SCC with tailor made property.

An Interview with Dr. Anne LaBastille.

ERIC Educational Resources Information Center

Griffin, Elizabeth

1982-01-01

Anne LaBastille, a role model for women interested in exploring the wilderness, gives hints on lessening the effects of acid rain, tells outdoor educators to encourage women to explore the wilderness and to take children outdoors to experience nature, and predicts a future economic slump for outdoor education. (LC)

Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

NASA Astrophysics Data System (ADS)

Kothari, Mahesh; Gharde, K. D.

2015-07-01

The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

Day and Night Dust Retrievals from MODIS IR Band Measurements using Artificial Neural Network (ANN) model

NASA Astrophysics Data System (ADS)

Lee, S.; Sohn, B.

2008-12-01

Artificial Neural Network (ANN) on the East Asia domain (20°N-55°N, 90°E-145°E) during the springs of 2006 and 2007 was investigated for retrieving aerosol optical thickness (AOT) of dust aerosol at both daytime and nighttime. The input data for ANN include brightness temperature, BTD (11 μm - 12 μm), spectral emissivity, surface temperature (Land: Price [1984] Equation, Ocean: The IMAPP MODIS Algorithm), relative airmass of satellite, and topography (SRTM30). The D*-parameter is adopted as dust detection algorithm which was developed by Hansell et al [2007]. The target data of the ANN is corresponding AOT at 550nm obtained from MODIS aerosol product (MYD04). After optimization and training, ANN AOT is retrieved. Among the many dust episodes during the spring of 2006, only the 8 April 2006 case was selected for the detailed analysis. Because it is one of the strongest episodes and shows a well-developed root penetrating the Korean peninsula and reaching the Japanese area. It is shown that ANN AOT coincide well with MODIS AOT having correlation coefficient of 0.8502 when the training and applying periods are the same (spring of 2006). Even a different period with training ANN AOT has a good relationship with MODIS AOT with the correlation coefficient of 0.7766 (spring 2007). This yearly difference is resulted from vegetation change and fixed IGBP land cover map. Also notable is that ANN AOT is underestimated in most IGBP types having low slope and negative mean bias. This study showed that ANN model has a good potential to retrieve AOT. More examinations and trials are needed, however, to improve this ANN algorithm using IR bands. Also this model should be extended to specify the dust aerosol property from other aerosols and clouds to assure that it has a capability during both daytime and nighttime.

New consensus multivariate models based on PLS and ANN studies of sigma-1 receptor antagonists.

PubMed

Oliveira, Aline A; Lipinski, Célio F; Pereira, Estevão B; Honorio, Kathia M; Oliveira, Patrícia R; Weber, Karen C; Romero, Roseli A F; de Sousa, Alexsandro G; da Silva, Albérico B F

2017-10-02

The treatment of neuropathic pain is very complex and there are few drugs approved for this purpose. Among the studied compounds in the literature, sigma-1 receptor antagonists have shown to be promising. In order to develop QSAR studies applied to the compounds of 1-arylpyrazole derivatives, multivariate analyses have been performed in this work using partial least square (PLS) and artificial neural network (ANN) methods. A PLS model has been obtained and validated with 45 compounds in the training set and 13 compounds in the test set (r 2 training = 0.761, q 2 = 0.656, r 2 test = 0.746, MSE test = 0.132 and MAE test = 0.258). Additionally, multi-layer perceptron ANNs (MLP-ANNs) were employed in order to propose non-linear models trained by gradient descent with momentum backpropagation function. Based on MSE test values, the best MLP-ANN models were combined in a MLP-ANN consensus model (MLP-ANN-CM; r 2 test = 0.824, MSE test = 0.088 and MAE test = 0.197). In the end, a general consensus model (GCM) has been obtained using PLS and MLP-ANN-CM models (r 2 test = 0.811, MSE test = 0.100 and MAE test = 0.218). Besides, the selected descriptors (GGI6, Mor23m, SRW06, H7m, MLOGP, and μ) revealed important features that should be considered when one is planning new compounds of the 1-arylpyrazole class. The multivariate models proposed in this work are definitely a powerful tool for the rational drug design of new compounds for neuropathic pain treatment. Graphical abstract Main scaffold of the 1-arylpyrazole derivatives and the selected descriptors.

Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS

NASA Astrophysics Data System (ADS)

Vafaeenezhad, H.; Ghanei, S.; Seyedein, S. H.; Beygi, H.; Mazinani, M.

2014-11-01

In this research, a comprehensive soft computational approach is presented for the analysis of the influencing parameters on manufacturing of dual-phase steels. A set of experimental data have been gathered to obtain the initial database used for the training and testing of both artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). The parameters used in the strategy were intercritical annealing temperature, carbon content, and holding time which gives off martensite percentage as an output. A fraction of the data set was chosen to train both ANN and ANFIS, and the rest was put into practice to authenticate the act of the trained networks while seeing unseen data. To compare the obtained results, coefficient of determination and root mean squared error indexes were chosen. Using artificial intelligence methods, it is not necessary to consider and establish a preliminary mathematical model and formulate its affecting parameters on its definition. In conclusion, the martensite percentages corresponding to the manufacturing parameters can be determined prior to a production using these controlling algorithms. Although the results acquired from both ANN and ANFIS are very encouraging, the proposed ANFIS has enhanced performance over the ANN and takes better effect on cost-reduction profit.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Students, including Marcus Pratt, left, and Ajani Young, second from left, pay close attention as the crew from STS-127 makes their presentation during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Photo Credit: (NASA/Paul E. Alers)

Novel Formulation of Adaptive MPC as EKF Using ANN Model: Multiproduct Semibatch Polymerization Reactor Case Study.

PubMed

Kamesh, Reddi; Rani, Kalipatnapu Yamuna

2017-12-01

In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon. An industrial case study for temperature control of a multiproduct semibatch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANN-EKFMPC strategy at supervisory level as a cascade control configuration along with proportional integral controller [ANN-EKFMPC with PI (ANN-EKFMPC-PI)]. The proposed approach is formulated incorporating all aspects of MPC including move suppression factor for control effort minimization and constraint-handling capability including terminal constraints. The nominal stability analysis and offset-free tracking capabilities of the proposed controller are proved. Its performance is evaluated by comparison with a standard MPC-based cascade control approach using the same adaptive ANN model. The ANN-EKFMPC-PI control configuration has shown better controller performance in terms of temperature tracking, smoother input profiles, as well as constraint-handling ability compared with the ANN-MPC with PI approach for two products in summer and winter. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.

ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

NASA Astrophysics Data System (ADS)

Chandrasekaran, Muthumari; Tamang, Santosh

2017-08-01

Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

[Nondestructive discrimination of strawberry varieties by NIR and BP-ANN].

PubMed

Niu, Xiao-ying; Shao, Li-min; Zhao, Zhi-lei; Zhang, Xiao-yu

2012-08-01

Strawberry variety is a main factor that can influence strawberry fruit quality. The use of near-infrared reflectance spectroscopy was explored discriminate among samples of strawberry of different varieties. And the significance of difference among different varieties was analyzed by comparison of the chemical composition of the different varieties samples. The performance of models established using back propagation-artificial neural networks (BP-ANN), least squares-support vector machine and discriminant analysis were evaluated on spectra range of 4545-9090 cm(-1). The optimal model was obtained by BP-ANN with a topology of 12-18-3, which correctly classified 96.68% of calibration set and 97.14% of prediction set. And the 94.95%, 97% and 98.29% classifications were given respectively for "Tianbao" (n=99), "Fengxiang" (n=100) and "Mingxing" (n=117). One-way analysis of variance was made for comparison of the mean values for soluble solids content (SSC), titratable acid (TA), pH value and SSC-TA ratio, and the statistically significant differences were found. Principal component analysis was performed on the four chemical compositions, and obvious clustering tendencies for different varieties were found. These results showed that NIR combined with BP-ANN can discriminate strawberry of different varieties effectively, and the difference in chemical compositions of different varieties strawberry might be a chemical validation for NIR results.

Intelligent MRTD testing for thermal imaging system using ANN

NASA Astrophysics Data System (ADS)

Sun, Junyue; Ma, Dongmei

2006-01-01

The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task, for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type, the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP, but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly, we use frame grabber to capture the 4-bar target image data. Then according to image gray scale, we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets, along with known target visibility, are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm, demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.

Overexpression of Arabidopsis AnnAt8 Alleviates Abiotic Stress in Transgenic Arabidopsis and Tobacco

PubMed Central

Yadav, Deepanker; Ahmed, Israr; Shukla, Pawan; Boyidi, Prasanna; Kirti, Pulugurtha Bharadwaja

2016-01-01

Abiotic stress results in massive loss of crop productivity throughout the world. Because of our limited knowledge of the plant defense mechanisms, it is very difficult to exploit the plant genetic resources for manipulation of traits that could benefit multiple stress tolerance in plants. To achieve this, we need a deeper understanding of the plant gene regulatory mechanisms involved in stress responses. Understanding the roles of different members of plant gene families involved in different stress responses, would be a step in this direction. Arabidopsis, which served as a model system for the plant research, is also the most suitable system for the functional characterization of plant gene families. Annexin family in Arabidopsis also is one gene family which has not been fully explored. Eight annexin genes have been reported in the genome of Arabidopsis thaliana. Expression studies of different Arabidopsis annexins revealed their differential regulation under various abiotic stress conditions. AnnAt8 (At5g12380), a member of this family has been shown to exhibit ~433 and ~175 fold increase in transcript levels under NaCl and dehydration stress respectively. To characterize Annexin8 (AnnAt8) further, we have generated transgenic Arabidopsis and tobacco plants constitutively expressing AnnAt8, which were evaluated under different abiotic stress conditions. AnnAt8 overexpressing transgenic plants exhibited higher seed germination rates, better plant growth, and higher chlorophyll retention when compared to wild type plants under abiotic stress treatments. Under stress conditions transgenic plants showed comparatively higher levels of proline and lower levels of malondialdehyde compared to the wild-type plants. Real-Time PCR analyses revealed that the expression of several stress-regulated genes was altered in AnnAt8 over-expressing transgenic tobacco plants, and the enhanced tolerance exhibited by the transgenic plants can be correlated with altered expressions of

How can we deal with ANN in flood forecasting? As a simulation model or updating kernel!

NASA Astrophysics Data System (ADS)

Hassan Saddagh, Mohammad; Javad Abedini, Mohammad

2010-05-01

Flood forecasting and early warning, as a non-structural measure for flood control, is often considered to be the most effective and suitable alternative to mitigate the damage and human loss caused by flood. Forecast results which are output of hydrologic, hydraulic and/or black box models should secure accuracy of flood values and timing, especially for long lead time. The application of the artificial neural network (ANN) in flood forecasting has received extensive attentions in recent years due to its capability to capture the dynamics inherent in complex processes including flood. However, results obtained from executing plain ANN as simulation model demonstrate dramatic reduction in performance indices as lead time increases. This paper is intended to monitor the performance indices as it relates to flood forecasting and early warning using two different methodologies. While the first method employs a multilayer neural network trained using back-propagation scheme to forecast output hydrograph of a hypothetical river for various forecast lead time up to 6.0 hr, the second method uses 1D hydrodynamic MIKE11 model as forecasting model and multilayer neural network as updating kernel to monitor and assess the performance indices compared to ANN alone in light of increase in lead time. Results presented in both graphical and tabular format indicate superiority of MIKE11 coupled with ANN as updating kernel compared to ANN as simulation model alone. While plain ANN produces more accurate results for short lead time, the errors increase expeditiously for longer lead time. The second methodology provides more accurate and reliable results for longer forecast lead time.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Students and teachers look on as STS-127 Commander Mark Polansky, seated left on stage talks about the mission to the International Space Station as other crew members Chris Cassidy, Doug Hurley, David Wolf, Tom Marshburn looks on during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Photo Credit: (NASA/Paul E. Alers)

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Canadian Space Agency astronaut Julie Payette, right, a mission specialist on STS-127, talks with two unidentified students during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Payette, along with the rest of the crew from STS-127, visited with students at the school Thursday. Photo Credit: (NASA/Paul E. Alers)

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

Ajani Young, a fourth grade student at Anne Beers Elementary school, at podium, introduces the crew of STS-127 during their visit, Thursday, Sept. 24, 2009, in Washington. Seated from left are crew members, Chris Cassidy, Doug Hurley, Commander Mark Polansky, David Wolf, Tom Marshburn and Canadian Space Agency astronaut Julie Payette. Photo Credit: (NASA/Paul E. Alers)

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

NASA Astrophysics Data System (ADS)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Mapping brain circuits of reward and motivation: in the footsteps of Ann Kelley.

PubMed

Richard, Jocelyn M; Castro, Daniel C; Difeliceantonio, Alexandra G; Robinson, Mike J F; Berridge, Kent C

2013-11-01

Ann Kelley was a scientific pioneer in reward neuroscience. Her many notable discoveries included demonstrations of accumbens/striatal circuitry roles in eating behavior and in food reward, explorations of limbic interactions with hypothalamic regulatory circuits, and additional interactions of motivation circuits with learning functions. Ann Kelley's accomplishments inspired other researchers to follow in her footsteps, including our own laboratory group. Here we describe results from several lines of our research that sprang in part from earlier findings by Kelley and colleagues. We describe hedonic hotspots for generating intense pleasure 'liking', separate identities of 'wanting' versus 'liking' systems, a novel role for dorsal neostriatum in generating motivation to eat, a limbic keyboard mechanism in nucleus accumbens for generating intense desire versus intense dread, and dynamic limbic transformations of learned memories into motivation. We describe how origins for each of these themes can be traced to fundamental contributions by Ann Kelley. Copyright © 2013 Elsevier Ltd. All rights reserved.

Professor Ann De Vaney and a Good Conversation.

ERIC Educational Resources Information Center

Nichols, Randall G.

The author begins this paper by explaining that in examining 10 works by Ann De Vaney his goal is to see what her writing generally reveals about her playing close attention to people-to research subjects, to subjects otherwise addressed in the works, to readers of her works. The author attempts to address each by asking basic questions: (1) What…

The Anne Frank Haven in an Israeli Kibbutz.

PubMed

Dror, Y

1995-01-01

The Anne Frank Haven, founded in 1956, in the Israeli Kibbutz Sasa provides a unique educational program for coping with muticultural and integration problems. It is a holistic, regional junior and senior high school system within the holistic community of three kibbutzim. The Haven has been the subject of much research into "Moral Development," carried out by Wolins (1969, 1971), and mainly by Kohlberg (1971), his doctoral students Reimer and Snarey and other colleagues. In the seventies and eighties they used the Kibbutz example as a model for the "Just Community" approach. In the early nineties, an Israeli group evaluated the success of the program and its rationale, taking into consideration all the "educational factors" of the community, in the Haven, and in the kibbutzim around it. This article offers a comprehensive picture of the Kohlbergian moral-developmental research at the Anne Frank Haven, including all the relevant references and evaluations of the Haven as a part of the "Just Community" approach. It concludes with a suggestion for another approach--"Community Education" research in the same Haven--as an example of present and future studies in the area of "Moral" and "Values" education.

Late-Night Shared-Ride Taxi Transit in Ann Arbor, MI

DOT National Transportation Integrated Search

1984-10-01

The Ann Arbor Transportation Authority introduced Night Ride, a late-night shared-ride taxi transit service, in mid-March 1982. The service was provided through a contract with a local taxicab company and funded through a demonstration grant from the...

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

NASA Astrophysics Data System (ADS)

Mandal, Sukomal; Rao, Subba; N., Harish; Lokesha

2012-06-01

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

STS-127 Crew Visit to Anne Beers Elementary

NASA Image and Video Library

2009-09-23

STS-127 Commander Mark Polansky, center, speaks to students during a visit to Anne Beers Elementary school, Thursday, Sept. 24, 2009, in Washington. Polansky, along with the rest of the crew from STS-127, visited with students at the school Thursday. Seated from left are Canadian Space Agency astronaut Julie Payette, Chris Cassidy, Doug Hurley, David Wolf and Tom Marshburn. Photo Credit: (NASA/Paul E. Alers)

Growth kinetics of O-polar BexMgyZn1-x-yO alloy: Role of Zn to Be and Mg flux ratio as a guide to growth at high temperature

NASA Astrophysics Data System (ADS)

Ullah, M. B.; Avrutin, V.; Nakagawara, T.; Hafiz, S.; Altuntaş, I.; Özgür, Ü.; Morkoç, H.

2017-05-01

We studied the effect of the substrate temperature, in the range from 450 °C to 500 °C, on the required Zn to (Be + Mg) flux ratio for plasma-assisted molecular beam epitaxy growth of O-polar BexMgyZn1-x-yO on (0001)-GaN/sapphire templates. Achievement of single-crystalline BexMgyZn1-x-yO with improved optical and structural qualities required relatively high substrate temperatures, which necessitated the Zn to (Be + Mg) flux ratio to be increased from 3.9 at 450 °C to 8.3 at 500 °C. This resulted in a reduction of Mg incorporation from 25% to 15% for a fixed Be content of ˜3%. With increasing Zn to (Be + Mg) ratio, 15 K photoluminescence energy for the dominant emission remained unchanged at around 3.75 eV and 3.55 eV for the samples grown at 475 °C and 500 °C, respectively. These findings readily suggest a kinetic limitation of Mg and Be incorporation into wurtzite BexMgyZn1-x-yO lattice, resulting in the formation of second phase due mainly to the enhanced surface mobility of Mg adatoms and, therefore, an increase in the probability of the formation of Mg-rich clusters. An increase in the in-plane lattice parameter, deduced from the Reflection High Energy Electron Diffraction, at the onset of the phase segregation suggests the formation of the wurtzite phase MgO rich alloy(s).

Development and Application of ANN Model for Worker Assignment into Virtual Cells of Large Sized Configurations

NASA Astrophysics Data System (ADS)

Murali, R. V.; Puri, A. B.; Fathi, Khalid

2010-10-01

This paper presents an extended version of study already undertaken on development of an artificial neural networks (ANNs) model for assigning workforce into virtual cells under virtual cellular manufacturing systems (VCMS) environments. Previously, the same authors have introduced this concept and applied it to virtual cells of two-cell configuration and the results demonstrated that ANNs could be a worth applying tool for carrying out workforce assignments. In this attempt, three-cell configurations problems are considered for worker assignment task. Virtual cells are formed under dual resource constraint (DRC) context in which the number of available workers is less than the total number of machines available. Since worker assignment tasks are quite non-linear and highly dynamic in nature under varying inputs & conditions and, in parallel, ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively, an attempt was earlier made to employ ANNs into the above task. In this paper, the multilayered perceptron with feed forward (MLP-FF) neural network model has been reused for worker assignment tasks of three-cell configurations under DRC context and its performance at different time periods has been analyzed. The previously proposed worker assignment model has been reconfigured and cell formation solutions available for three-cell configuration in the literature are used in combination to generate datasets for training ANNs framework. Finally, results of the study have been presented and discussed.

Decolonizing the Choctaws: Teaching LeAnne Howe's "Shell Shaker"

ERIC Educational Resources Information Center

Hollrah, Patrice

2004-01-01

"Shell Shaker" (2001) by LeAnne Howe (Choctaw) is a novel that gives students an opportunity to learn that the history and culture of the Choctaw Nation of Oklahoma are alive today. Winner of the Before Columbus Foundation American Book Award in 2002, the novel deals with two parallel stories that converge in the present, one about the eighteenth…

An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment

PubMed Central

de Cos Juez, Francisco J.; Lasheras, Fernando Sánchez; Roqueñí, Nieves; Osborn, James

2012-01-01

In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A). PMID:23012524

1. JoAnn SieburgBaker, Photographer, September 1977. OVERALL VIEW OF ROUNDHOUSE. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. JoAnn Sieburg-Baker, Photographer, September 1977. OVERALL VIEW OF ROUNDHOUSE. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

PubMed

Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

2016-11-01

This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

10. JoAnn SieburgBaker, Photographer, September 1977. INTERIOR VIEW OF BACK ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

10. JoAnn Sieburg-Baker, Photographer, September 1977. INTERIOR VIEW OF BACK SHOP. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Estimating SPT-N Value Based on Soil Resistivity using Hybrid ANN-PSO Algorithm

NASA Astrophysics Data System (ADS)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Standard Penetration Resistance (N value) is used in many empirical geotechnical engineering formulas. Meanwhile, soil resistivity is a measure of soil’s resistance to electrical flow. For a particular site, usually, only a limited N value data are available. In contrast, resistivity data can be obtained extensively. Moreover, previous studies showed evidence of a correlation between N value and resistivity value. Yet, no existing method is able to interpret resistivity data for estimation of N value. Thus, the aim is to develop a method for estimating N-value using resistivity data. This study proposes a hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) method to estimate N value using resistivity data. Five different ANN-PSO models based on five boreholes were developed and analyzed. The performance metrics used were the coefficient of determination, R2 and mean absolute error, MAE. Analysis of result found that this method can estimate N value (R2 best=0.85 and MAEbest=0.54) given that the constraint, Δ {\\bar{l}}ref, is satisfied. The results suggest that ANN-PSO method can be used to estimate N value with good accuracy.

Anne S. Young: Professor and Variable Star Observer Extraordinaire

NASA Astrophysics Data System (ADS)

Bracher, Katherine

2011-05-01

Anne Sewell Young (1871-1961) was one of the eight original members of the AAVSO, to which she contributed more than 6500 observations over 33 years. She also taught astronomy for 37 years at Mount Holyoke College; among her students was Helen Sawyer Hogg. This paper will look at her life and career both at Mount Holyoke and with the AAVSO.

Jo Ann Rinaudo, PhD | Division of Cancer Prevention

Cancer.gov

Dr. Jo Ann Rinaudo is a Program Director in the Cancer Biomarkers Research Group in the Division of Cancer Prevention at the National Cancer Institute. She received a doctoral degree from the University of Toronto, where she studied chemical carcinogenesis in the liver. She was in the pathology department and has a broad background in human disease. Post-graduate training

3. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF BACK SHOP ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF BACK SHOP FROM SOUTHEAST. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

7. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF OFFICES IN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF OFFICES IN BACK SHOP. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

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

Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT,more » status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.« less

Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

PubMed

Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

2017-05-01

This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

5. JoAnn SieburgBaker, Photographer, September 1977. VIEW OF ICE HOUSE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. JoAnn Sieburg-Baker, Photographer, September 1977. VIEW OF ICE HOUSE AND SURROUNDING BUILDINGS. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Lucy Maude Montgomery and Anne of Green Gables: An Early Description of Attention-Deficit/Hyperactivity Disorder.

PubMed

Edison, Jessica Katz; Clardy, Christopher

2017-07-01

Attention-deficit/hyperactivity disorder (ADHD) was added to the Diagnostic and Statistical Manual of Mental Disorders, third edition, revised in 1987. Similar disorders had appeared earlier, and many consider the first description of ADHD to be a lecture in 1902 about children with an "abnormal defect in moral control" but normal intelligence. This definition of ADHD is more alarming than the current one. Anne Shirley, the protagonist of the novel Anne of Green Gables (written by Lucy Maude Montgomery and published in 1908), shares the hyperactive and inattentive qualities that fit the current definition of ADHD. She also lacks the menacing characteristics of the 1902 description. This indicates that ADHD, by its modern definition, was probably present in the early 1900s. Furthermore, the character of Anne Shirley shares many biographical similarities with her author, suggesting that Montgomery herself may have had ADHD. Thus, looking at literature from the past not only provides insight into the timeline of ADHD, but also into the thought process of an individual with ADHD. By viewing literary classics through a medical lens, we may gain insight into other diseases as well. [Pediatr Ann. 2017; 46(7):e270-e272.]. Copyright 2017, SLACK Incorporated.

4. JoAnn SieburgBaker, Photographer, September 1977. OVERALL VIEW OF BACK ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. JoAnn Sieburg-Baker, Photographer, September 1977. OVERALL VIEW OF BACK SHOP FROM ROOF OF ROUNDHOUSE. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

Evaluation of the advanced operating system of the Ann Arbor Transit Authority

DOT National Transportation Integrated Search

1999-10-01

These reports constitute an evaluation of the intelligent transportation system deployment efforts of the Ann Arbor Transportation Authority. These efforts, collectively termed "Advanced Operating System" (AOS), represent a vision of an integrated ad...

ANN based Performance Evaluation of BDI for Condition Monitoring of Induction Motor Bearings

NASA Astrophysics Data System (ADS)

Patel, Raj Kumar; Giri, V. K.

2017-06-01

One of the critical parts in rotating machines is bearings and most of the failure arises from the defective bearings. Bearing failure leads to failure of a machine and the unpredicted productivity loss in the performance. Therefore, bearing fault detection and prognosis is an integral part of the preventive maintenance procedures. In this paper vibration signal for four conditions of a deep groove ball bearing; normal (N), inner race defect (IRD), ball defect (BD) and outer race defect (ORD) were acquired from a customized bearing test rig, under four different conditions and three different fault sizes. Two approaches have been opted for statistical feature extraction from the vibration signal. In the first approach, raw signal is used for statistical feature extraction and in the second approach statistical features extracted are based on bearing damage index (BDI). The proposed BDI technique uses wavelet packet node energy coefficients analysis method. Both the features are used as inputs to an ANN classifier to evaluate its performance. A comparison of ANN performance is made based on raw vibration data and data chosen by using BDI. The ANN performance has been found to be fairly higher when BDI based signals were used as inputs to the classifier.

Archaeological Data Recovery at the Mary Ann Cole Site

DTIC Science & Technology

1981-06-01

documents the methods and results of archaeological excavations conducted at the Mary Ann Cole Site (12Crl) near Leavenworth, Indiana. The purpose of the...the area now range from 363 feet to 953 feet above sea level (Wingard 1975). The pre-Pleistocene drainage systems differed substantially from the...defined for this report, the Wyandotte chert zone consists of different types of "chert which are often stratigraphically distinct, but also Intergrade

WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region.

PubMed

Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

2011-09-01

This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.

Modelling soil erosion in a Mediterranean watershed: Comparison between SWAT and AnnAGNPS models.

PubMed

Abdelwahab, O M M; Ricci, G F; De Girolamo, A M; Gentile, F

2018-06-20

In this study, the simulations generated by two of the most widely used hydrological basin-scale models, the Annualized Agricultural Non-Point Source (AnnAGNPS) and the Soil and Water Assessment Tool (SWAT), were compared in a Mediterranean watershed, the Carapelle (Apulia, Southern Italy). Input data requirements, time and efforts needed for input preparation, strength and weakness points of each model, ease of use and limitations were evaluated in order to give information to users. Models were calibrated and validated at monthly time scale for hydrology and sediment load using a four year period of observations (streamflow and suspended sediment concentrations). In the driest year, the specific sediment load measured at the outlet was 0.89 t ha -1 yr -1 , while the simulated values were 0.83 t ha -1 yr -1 and 1.99 t ha -1 yr -1 for SWAT and AnnAGNPS, respectively. In the wettest year, the specific measured sediment load was 7.45 t ha -1 yr -1 , and the simulated values were 8.27 t ha -1 yr -1 and 6.23 t ha -1 yr -1 for SWAT and AnnAGNPS, respectively. Both models showed from fair to a very good correlation between observed and simulated streamflow and satisfactory for sediment load. Results showed that most of the basin is under moderate (1.4-10 t ha -1 yr -1 ) and high-risk erosion (> 10 t ha -1 yr -1 ). The sediment yield predicted by the SWAT and AnnAGNPS models were compared with estimates of soil erosion simulated by models for Europe (PESERA and RUSLE2015). The average gross erosion estimated by the RUSLE2015 model (12.5 t ha -1 yr -1 ) resulted comparable with the average specific sediment yield estimated by SWAT (8.8 t ha -1 yr -1 ) and AnnAGNPS (5.6 t ha -1 yr -1 ), while it was found that the average soil erosion estimated by PESERA is lower than the other estimates (1.2 t ha -1 yr -1 ). Copyright © 2018 Elsevier Inc. All rights reserved.

Long-term solar UV radiation reconstructed by Artificial Neural Networks (ANN)

NASA Astrophysics Data System (ADS)

Feister, U.; Junk, J.; Woldt, M.

2008-01-01

Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980-1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

2. JoAnn SieburgBaker, Photographer, September 1977. SECTION SHOWING BACK OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. JoAnn Sieburg-Baker, Photographer, September 1977. SECTION SHOWING BACK OF ROUNDHOUSE AND END OF BACK SHOP WHERE CRANE WAS LOCATED. - Southern Railway Company, Spencer Shops, Salisbury Avenue between Third and Eight Streets, Spencer, Rowan County, NC

A Curve Fitting Approach Using ANN for Converting CT Number to Linear Attenuation Coefficient for CT-based PET Attenuation Correction

NASA Astrophysics Data System (ADS)

Lai, Chia-Lin; Lee, Jhih-Shian; Chen, Jyh-Cheng

2015-02-01

Energy-mapping, the conversion of linear attenuation coefficients (μ) calculated at the effective computed tomography (CT) energy to those corresponding to 511 keV, is an important step in CT-based attenuation correction (CTAC) for positron emission tomography (PET) quantification. The aim of this study was to implement energy-mapping step by using curve fitting ability of artificial neural network (ANN). Eleven digital phantoms simulated by Geant4 application for tomographic emission (GATE) and 12 physical phantoms composed of various volume concentrations of iodine contrast were used in this study to generate energy-mapping curves by acquiring average CT values and linear attenuation coefficients at 511 keV of these phantoms. The curves were built with ANN toolbox in MATLAB. To evaluate the effectiveness of the proposed method, another two digital phantoms (liver and spine-bone) and three physical phantoms (volume concentrations of 3%, 10% and 20%) were used to compare the energy-mapping curves built by ANN and bilinear transformation, and a semi-quantitative analysis was proceeded by injecting 0.5 mCi FDG into a SD rat for micro-PET scanning. The results showed that the percentage relative difference (PRD) values of digital liver and spine-bone phantom are 5.46% and 1.28% based on ANN, and 19.21% and 1.87% based on bilinear transformation. For 3%, 10% and 20% physical phantoms, the PRD values of ANN curve are 0.91%, 0.70% and 3.70%, and the PRD values of bilinear transformation are 3.80%, 1.44% and 4.30%, respectively. Both digital and physical phantoms indicated that the ANN curve can achieve better performance than bilinear transformation. The semi-quantitative analysis of rat PET images showed that the ANN curve can reduce the inaccuracy caused by attenuation effect from 13.75% to 4.43% in brain tissue, and 23.26% to 9.41% in heart tissue. On the other hand, the inaccuracy remained 6.47% and 11.51% in brain and heart tissue when the bilinear transformation

Symbolism--The Main Artistic Style of Katherine Anne Porter's Short Stories

ERIC Educational Resources Information Center

Wang, Ru

2010-01-01

The paper takes Katherine Anne Porter's two short stories: "Flowering Judas", "The Grave" as objects of study. It will try to analyze Porter's writing style through her imaginary conception, vivid psychological description and multiple symbolisms so that we can understand her studies and her attitudes to female psychological…

Application of back-propagation artificial neural network (ANN) to predict crystallite size and band gap energy of ZnO quantum dots

NASA Astrophysics Data System (ADS)

Pelicano, Christian Mark; Rapadas, Nick; Cagatan, Gerard; Magdaluyo, Eduardo

2017-12-01

Herein, the crystallite size and band gap energy of zinc oxide (ZnO) quantum dots were predicted using artificial neural network (ANN). Three input factors including reagent ratio, growth time, and growth temperature were examined with respect to crystallite size and band gap energy as response factors. The generated results from neural network model were then compared with the experimental results. Experimental crystallite size and band gap energy of ZnO quantum dots were measured from TEM images and absorbance spectra, respectively. The Levenberg-Marquardt (LM) algorithm was used as the learning algorithm for the ANN model. The performance of the ANN model was then assessed through mean square error (MSE) and regression values. Based on the results, the ANN modelling results are in good agreement with the experimental data.

Exploring QSARs of the interaction of flavonoids with GABA (A) receptor using MLR, ANN and SVM techniques.

PubMed

Deeb, Omar; Shaik, Basheerulla; Agrawal, Vijay K

2014-10-01

Quantitative Structure-Activity Relationship (QSAR) models for binding affinity constants (log Ki) of 78 flavonoid ligands towards the benzodiazepine site of GABA (A) receptor complex were calculated using the machine learning methods: artificial neural network (ANN) and support vector machine (SVM) techniques. The models obtained were compared with those obtained using multiple linear regression (MLR) analysis. The descriptor selection and model building were performed with 10-fold cross-validation using the training data set. The SVM and MLR coefficient of determination values are 0.944 and 0.879, respectively, for the training set and are higher than those of ANN models. Though the SVM model shows improvement of training set fitting, the ANN model was superior to SVM and MLR in predicting the test set. Randomization test is employed to check the suitability of the models.

Improved performance of Mg-Y alloy thin film switchable mirrors after coating with a superhydrophobic surface

NASA Astrophysics Data System (ADS)

La, Mao; Zhou, Huaijuan; Li, Ning; Xin, Yunchuan; Sha, Ren; Bao, Shanhu; Jin, Ping

2017-05-01

The magnesium based switchable mirrors can reversibly change their optical properties between the transparent and the reflective state as a result of hydrogenation and dehydrogenation. These films can potentially be applied as new energy-saving windows, by controlling the transmittance of solar radiation through the regulation of their reflective state. In this study, magnesium-yttrium (Mg-Y) alloy thin films were prepared using a DC magnetron sputtering method. However, the luminous transmittance in the transparent state and the switching durability of switchable mirrors are too poor to satisfy practical demands. In order to improve the films switching durability, luminous transmittance and the surface functionalization, polytetrafluoroethylene (PTFE) was coated with thermal vacuum deposition for use as the top layer of Mg-Y/Pd switchable mirrors. The PTFE layer had a porous network structure and exhibited a superhydrophobic surface with a water contact angle of approximately 152°. By characterization, PTFE thin films shows the excellent protection role against the oxidization of Mg, the switching durability of the films were improved 3 times, and also shows the antireflection role the luminous transmission of films was enhanced by 7% through the top covered with PTFE.

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

NASA Astrophysics Data System (ADS)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

ANN expert system screening for illicit amphetamines using molecular descriptors

NASA Astrophysics Data System (ADS)

Gosav, S.; Praisler, M.; Dorohoi, D. O.

2007-05-01

The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.

The Sally-Anne Test: An Interactional Analysis of a Dyadic Assessment

ERIC Educational Resources Information Center

Korkiakangas, Terhi; Dindar, Katja; Laitila, Aarno; Kärnä, Eija

2016-01-01

Background: The Sally-Anne test has been extensively used to examine children's theory of mind understanding. Many task-related factors have been suggested to impact children's performance on this test. Yet little is known about the interactional aspects of such dyadic assessment situations that might contribute to the ways in which children…

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

33 CFR 80.115 - Portland Head, ME to Cape Ann, MA.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Portland Head, ME to Cape Ann, MA. 80.115 Section 80.115 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY..., MA. (a) Except inside lines specifically described in this section, the 72 COLREGS shall apply on the...

Analysis of Closely Related Antioxidant Nutraceuticals Using the Green Analytical Methodology of ANN and Smart Spectrophotometric Methods.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2017-01-01

Two new, simple, and specific green analytical methods are proposed: zero-crossing first-derivative and chemometric-based spectrophotometric artificial neural network (ANN). The proposed methods were used for the simultaneous estimation of two closely related antioxidant nutraceuticals, coenzyme Q10 (Q10) and vitamin E, in their mixtures and pharmaceutical preparations. The first method is based on the handling of spectrophotometric data with the first-derivative technique, in which both nutraceuticals were determined in ethanol, each at the zero crossing of the other. The amplitudes of the first-derivative spectra for Q10 and vitamin E were recorded at 285 and 235 nm respectively, and correlated with their concentrations. The linearity ranges of Q10 and vitamin E were 10-60 and 5.6-70 μg⋅mL-1, respectively. The second method, ANN, is a multivariate calibration method and it was developed and applied for the simultaneous determination of both analytes. A training set of 90 different synthetic mixtures containing Q10 and vitamin E in the ranges of 0-100 and 0-556 μg⋅mL-1, respectively, was prepared in ethanol. The absorption spectra of the training set were recorded in the spectral region of 230-300 nm. By relating the concentration sets (x-block) with their corresponding absorption data (y-block), gradient-descent back-propagation ANN calibration could be computed. To validate the proposed network, a set of 45 synthetic mixtures of the two drugs was used. Both proposed methods were successfully applied for the assay of Q10 and vitamin E in their laboratory-prepared mixtures and in their pharmaceutical tablets with excellent recovery. These methods offer advantages over other methods because of low-cost equipment, time-saving measures, and environmentally friendly materials. In addition, no chemical separation prior to analysis was needed. The ANN method was superior to the derivative technique because ANN can determine both drugs under nonlinear experimental

Prediction of frequency for simulation of asphalt mix fatigue tests using MARS and ANN.

PubMed

Ghanizadeh, Ali Reza; Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation.

Predicting PM10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN).

PubMed

Park, Sechan; Kim, Minjeong; Kim, Minhae; Namgung, Hyeong-Gyu; Kim, Ki-Tae; Cho, Kyung Hwa; Kwon, Soon-Bark

2018-01-05

The indoor air quality of subway systems can significantly affect the health of passengers since these systems are widely used for short-distance transit in metropolitan urban areas in many countries. The particles generated by abrasion during subway operations and the vehicle-emitted pollutants flowing in from the street in particular affect the air quality in underground subway stations. Thus the continuous monitoring of particulate matter (PM) in underground station is important to evaluate the exposure level of PM to passengers. However, it is difficult to obtain indoor PM data because the measurement systems are expensive and difficult to install and operate for significant periods of time in spaces crowded with people. In this study, we predicted the indoor PM concentration using the information of outdoor PM, the number of subway trains running, and information on ventilation operation by the artificial neural network (ANN) model. As well, we investigated the relationship between ANN's performance and the depth of underground subway station. ANN model showed a high correlation between the predicted and actual measured values and it was able to predict 67∼80% of PM at 6 subway station. In addition, we found that platform shape and depth influenced the model performance. Copyright © 2017 Elsevier B.V. All rights reserved.

78 FR 65380 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... the University of Michigan, Ann Arbor, MI. The human remains were removed from Alpena, Isabella, Grand... removed from the Devil River Mound site (20AL1) in Alpena County, MI. A resident of Ossineke, MI...

Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

NASA Astrophysics Data System (ADS)

Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

2018-02-01

Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

Bethany Ann Teachman: Award for Distinguished Scientific Early Career Contributions to Psychology

ERIC Educational Resources Information Center

American Psychologist, 2012

2012-01-01

Presents a short biography of one of the winners of the American Psychological Association's Award for Distinguished Scientific Early Career Contributions to Psychology. The 2012 winner is Bethany Ann Teachman for transformative, translational research integrating social cognition, life-span, and perceptual approaches to investigating clinical…

Modelling and optimization of Mn/activate carbon nanocatalysts for NO reduction: comparison of RSM and ANN techniques.

PubMed

Mousavi, Seyed Mahdi; Niaei, Aligholi; Salari, Dariush; Panahi, Parvaneh Nakhostin; Samandari, Masoud

2013-01-01

A response surface methodology (RSM) involving a central composite design was applied to the modelling and optimization of a preparation of Mn/active carbon nanocatalysts in NH3-SCR of NO at 250 degrees C and the results were compared with the artificial neural network (ANN) predicted values. The catalyst preparation parameters, including metal loading (wt%), calcination temperature and pre-oxidization degree (v/v% HNO3) were selected as influence factors on catalyst efficiency. In the RSM model, the predicted values of NO conversion were found to be in good agreement with the experimental values. Pareto graphic analysis showed that all the chosen parameters and some of the interactions were effective on response. The optimization results showed that maximum NO conversion was achieved at the optimum conditions: 10.2 v/v% HNO3, 6.1 wt% Mn loading and calcination at 480 degrees C. The ANN model was developed by a feed-forward back propagation network with the topology 3, 8 and 1 and a Levenberg-Marquardt training algorithm. The mean square error for the ANN and RSM models were 0.339 and 1.176, respectively, and the R2 values were 0.991 and 0.972, respectively, indicating the superiority of ANN in capturing the nonlinear behaviour of the system and being accurate in estimating the values of the NO conversion.

Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

NASA Astrophysics Data System (ADS)

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

2018-02-01

This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

PubMed

Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

2018-04-25

Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

PubMed Central

Erdakov, Ivan Nikolaevich; Taha, Mohamed~Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-01-01

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness (Ra) prediction of one component in computer numerical control (CNC) turning over minimal machining time (Tm) and at prime machining costs (C). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra, Tm, and C, in relation to cutting speed, vc, depth of cut, ap, and feed per revolution, fr. For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values vc, ap, and fr. The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, Tm = 0.358 min/cm3, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed vc = 250 m/min, cutting depth ap = 1.0 mm, and feed per revolution fr = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness. PMID:29772670

Audits of Meaning: A Festschrift in Honor of Ann E. Berthoff.

ERIC Educational Resources Information Center

Smith, Louise Z., Ed.

A tribute to the work of Ann Berthoff, this book--a collection of 6 poems and 21 essays--explores issues in the philosophy and teaching of composition. Each of the five sections is introduced with a poem by Marie Ponsot. Essays and their authors consist of (1) "Genre Theory, Academic Discourse, and Writing within Disciplines" (James F.…

Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

NASA Astrophysics Data System (ADS)

Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

2018-02-01

As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm

NASA Astrophysics Data System (ADS)

Prasad, Ramendra; Deo, Ravinesh C.; Li, Yan; Maraseni, Tek

2017-11-01

Forecasting streamflow is vital for strategically planning, utilizing and redistributing water resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated with iterative input selection (IIS) algorithm (IIS-W-ANN) is evaluated for its statistical preciseness in forecasting monthly streamflow, and it is then benchmarked against M5 Tree model. To develop hybrid IIS-W-ANN model, a global predictor matrix is constructed for three local hydrological sites (Richmond, Gwydir, and Darling River) in Australia's agricultural (Murray-Darling) Basin. Model inputs comprised of statistically significant lagged combination of streamflow water level, are supplemented by meteorological data (i.e., precipitation, maximum and minimum temperature, mean solar radiation, vapor pressure and evaporation) as the potential model inputs. To establish robust forecasting models, iterative input selection (IIS) algorithm is applied to screen the best data from the predictor matrix and is integrated with the non-decimated maximum overlap discrete wavelet transform (MODWT) applied on the IIS-selected variables. This resolved the frequencies contained in predictor data while constructing a wavelet-hybrid (i.e., IIS-W-ANN and IIS-W-M5 Tree) model. Forecasting ability of IIS-W-ANN is evaluated via correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe Efficiency (ENS), root-mean-square-error (RMSE), and mean absolute error (MAE), including the percentage RMSE and MAE. While ANN models are seen to outperform M5 Tree executed for all hydrological sites, the IIS variable selector was efficient in determining the appropriate predictors, as stipulated by the better performance of the IIS coupled (ANN and M5 Tree) models relative to the models without IIS. When IIS-coupled models are integrated with MODWT, the wavelet-hybrid IIS-W-ANN and IIS-W-M5 Tree are seen to attain significantly accurate performance relative to their standalone counterparts. Importantly

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

PubMed Central

Pi, Erxu; Mantri, Nitin; Ngai, Sai Ming; Lu, Hongfei; Du, Liqun

2013-01-01

Temperature is one of the most significant environmental factors that affects germination of grass seeds. Reliable prediction of the optimal temperature for seed germination is crucial for determining the suitable regions and favorable sowing timing for turf grass cultivation. In this study, a back-propagation-artificial-neural-network-aided dual quintic equation (BP-ANN-QE) model was developed to improve the prediction of the optimal temperature for seed germination. This BP-ANN-QE model was used to determine optimal sowing times and suitable regions for three Cynodon dactylon cultivars (C. dactylon, ‘Savannah’ and ‘Princess VII’). Prediction of the optimal temperature for these seeds was based on comprehensive germination tests using 36 day/night (high/low) temperature regimes (both ranging from 5/5 to 40/40°C with 5°C increments). Seed germination data from these temperature regimes were used to construct temperature-germination correlation models for estimating germination percentage with confidence intervals. Our tests revealed that the optimal high/low temperature regimes required for all the three bermudagrass cultivars are 30/5, 30/10, 35/5, 35/10, 35/15, 35/20, 40/15 and 40/20°C; constant temperatures ranging from 5 to 40°C inhibited the germination of all three cultivars. While comparing different simulating methods, including DQEM, Bisquare ANN-QE, and BP-ANN-QE in establishing temperature based germination percentage rules, we found that the R2 values of germination prediction function could be significantly improved from about 0.6940–0.8177 (DQEM approach) to 0.9439–0.9813 (BP-ANN-QE). These results indicated that our BP-ANN-QE model has better performance than the rests of the compared models. Furthermore, data of the national temperature grids generated from monthly-average temperature for 25 years were fit into these functions and we were able to map the germination percentage of these C. dactylon cultivars in the national scale of

Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

PubMed Central

Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation. PMID:24688400

Ann O'Mara, PhD, RN, MPH | Division of Cancer Prevention

Cancer.gov

Dr. Ann O'Mara is Head of Palliative Research in the NCI Division of Cancer Prevention. She manages a portfolio of symptom management and palliative and end-of-life care research projects. The majority of these projects focus on the more common morbidities associated with cancer and its treatment, e.g., pain, chemotherapy induced neuropathy, fatigue, sleep disturbances, and

Optimization of thermal conductivity lightweight brick type AAC (Autoclaved Aerated Concrete) effect of Si & Ca composition by using Artificial Neural Network (ANN)

NASA Astrophysics Data System (ADS)

Zulkifli; Wiryawan, G. P.

2018-03-01

Lightweight brick is the most important component of building construction, therefore it is necessary to have lightweight thermal, mechanical and aqustic thermal properties that meet the standard, in this paper which is discussed is the domain of light brick thermal conductivity properties. The advantage of lightweight brick has a low density (500-650 kg/m3), more economical, can reduce the load 30-40% compared to conventional brick (clay brick). In this research, Artificial Neural Network (ANN) is used to predict the thermal conductivity of lightweight brick type Autoclaved Aerated Concrete (AAC). Based on the training and evaluation that have been done on 10 model of ANN with number of hidden node 1 to 10, obtained that ANN with 3 hidden node have the best performance. It is known from the mean value of MSE (Mean Square Error) validation for three training times of 0.003269. This ANN was further used to predict the thermal conductivity of four light brick samples. The predicted results for each of the AAC1, AAC2, AAC3 and AAC4 light brick samples were 0.243 W/m.K, respectively; 0.29 W/m.K; 0.32 W/m.K; and 0.32 W/m.K. Furthermore, ANN is used to determine the effect of silicon composition (Si), Calcium (Ca), to light brick thermal conductivity. ANN simulation results show that the thermal conductivity increases with increasing Si composition. Si content is allowed maximum of 26.57%, while the Ca content in the range 20.32% - 30.35%.

Processing RoxAnn sonar data to improve its categorization of lake bed surficial sediments

USGS Publications Warehouse

Cholwek, Gary; Bonde, John; Li, Xing; Richards, Carl; Yin, Karen

2000-01-01

To categorize spawning and nursery habitat for lake trout in Minnesota's near shore waters of Lake Superior, data was collected with a single beam echo sounder coupled with a RoxAnn bottom classification sensor. Test areas representative of different bottom surficial substrates were sampled. The collected data consisted of acoustic signals which showed both depth and substrate type. The location of the signals was tagged in real-time with a DGPS. All data was imported into a GIS database. To better interpret the output signal from the RoxAnn, several pattern classifiers were developed by multivariate statistical method. From the data a detailed and accurate map of lake bed bathymetry and surficial substrate types was produced. This map will be of great value to fishery and other natural resource managers.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs.

PubMed

Abbas, Adel Taha; Pimenov, Danil Yurievich; Erdakov, Ivan Nikolaevich; Taha, Mohamed Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-05-16

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth⁻Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness ( Ra ) prediction of one component in computer numerical control (CNC) turning over minimal machining time ( T m ) and at prime machining costs ( C ). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra , T m , and C , in relation to cutting speed, v c , depth of cut, a p , and feed per revolution, f r . For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values v c , a p , and f r . The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, T m = 0.358 min/cm³, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed v c = 250 m/min, cutting depth a p = 1.0 mm, and feed per revolution f r = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

ANN-based calibration model of FTIR used in transformer online monitoring

NASA Astrophysics Data System (ADS)

Li, Honglei; Liu, Xian-yong; Zhou, Fangjie; Tan, Kexiong

2005-02-01

Recently, chromatography column and gas sensor have been used in online monitoring device of dissolved gases in transformer oil. But some disadvantages still exist in these devices: consumption of carrier gas, requirement of calibration, etc. Since FTIR has high accuracy, consume no carrier gas and require no calibration, the researcher studied the application of FTIR in such monitoring device. Experiments of "Flow gas method" were designed, and spectrum of mixture composed of different gases was collected with A BOMEM MB104 FTIR Spectrometer. A key question in the application of FTIR is that: the absorbance spectrum of 3 fault key gases, including C2H4, CH4 and C2H6, are overlapped seriously at 2700~3400cm-1. Because Absorbance Law is no longer appropriate, a nonlinear calibration model based on BP ANN was setup to in the quantitative analysis. The height absorbance of C2H4, CH4 and C2H6 were adopted as quantitative feature, and all the data were normalized before training the ANN. Computing results show that the calibration model can effectively eliminate the cross disturbance to measurement.

Evaluation of effectiveness of wavelet based denoising schemes using ANN and SVM for bearing condition classification.

PubMed

Vijay, G S; Kumar, H S; Srinivasa Pai, P; Sriram, N S; Rao, Raj B K N

2012-01-01

The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR) and reducing the root-mean-square error (RMSE). In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN) and the Support Vector Machine (SVM), for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB) test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher's Criterion (FC). Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

Development of LC-MS determination method and back-propagation ANN pharmacokinetic model of corynoxeine in rat.

PubMed

Ma, Jianshe; Cai, Jinzhang; Lin, Guanyang; Chen, Huilin; Wang, Xianqin; Wang, Xianchuan; Hu, Lufeng

2014-05-15

Corynoxeine(CX), isolated from the extract of Uncaria rhynchophylla, is a useful and prospective compound in the prevention and treatment for vascular diseases. A simple and selective liquid chromatography mass spectrometry (LC-MS) method was developed to determine the concentration of CX in rat plasma. The chromatographic separation was achieved on a Zorbax SB-C18 (2.1 mm × 150 mm, 5 μm) column with acetonitrile-0.1% formic acid in water as mobile phase. Selective ion monitoring (SIM) mode was used for quantification using target ions m/z 383 for CX and m/z 237 for the carbamazepine (IS). After the LC-MS method was validated, it was applied to a back-propagation artificial neural network (BP-ANN) pharmacokinetic model study of CX in rats. The results showed that after intravenous administration of CX, it was mainly distributed in blood and eliminated quickly, t1/2 was less than 1h. The predicted concentrations generated by BP-ANN model had a high correlation coefficient (R>0.99) with experimental values. The developed BP-ANN pharmacokinetic model can be used to predict the concentration of CX in rats. Copyright © 2014 Elsevier B.V. All rights reserved.

Long-term solar UV radiation reconstructed by ANN modelling with emphasis on spatial characteristics of input data

NASA Astrophysics Data System (ADS)

Feister, U.; Junk, J.; Woldt, M.; Bais, A.; Helbig, A.; Janouch, M.; Josefsson, W.; Kazantzidis, A.; Lindfors, A.; den Outer, P. N.; Slaper, H.

2008-06-01

Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Special emphasis will be given to the discussion of small-scale characteristics of input data to the ANN model. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980/1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

Simulation of CO2 Solubility in Polystyrene-b-Polybutadieneb-Polystyrene (SEBS) by artificial intelligence network (ANN) method

NASA Astrophysics Data System (ADS)

Sharudin, R. W.; AbdulBari Ali, S.; Zulkarnain, M.; Shukri, M. A.

2018-05-01

This study reports on the integration of Artificial Neural Network (ANNs) with experimental data in predicting the solubility of carbon dioxide (CO2) blowing agent in SEBS by generating highest possible value for Regression coefficient (R2). Basically, foaming of thermoplastic elastomer with CO2 is highly affected by the CO2 solubility. The ability of ANN in predicting interpolated data of CO2 solubility was investigated by comparing training results via different method of network training. Regards to the final prediction result for CO2 solubility by ANN, the prediction trend (output generate) was corroborated with the experimental results. The obtained result of different method of training showed the trend of output generated by Gradient Descent with Momentum & Adaptive LR (traingdx) required longer training time and required more accurate input to produce better output with final Regression Value of 0.88. However, it goes vice versa with Levenberg-Marquardt (trainlm) technique as it produced better output in quick detention time with final Regression Value of 0.91.

[The embroidery work of the lady at Saint-Anne Hospital].

PubMed

Thillaud, Pierre L; Postel, Jacques

2014-01-01

In July 1974, a 72 old woman had been a patient for forty years in Sainte-Anne Hospital, Ward C. As she had again a violent brawl with her neighbour patient, she revealed being a tremendous artist. She had been confined on account of dementia paralytica in the Mecca of malariotherapy, and passionately devoted herself to embroidery. Her fancy work was rather a matter for Jean Dubuffet's art through its perfect expression and deserved being known.

Childhood and Modernity: Dark Themes in Carol Ann Duffy's Poetry for Children

ERIC Educational Resources Information Center

Whitley, David

2007-01-01

Carol Ann Duffy's three volumes of children's poetry are important and interesting because they emerge from the work of a writer whose adult poetry has persistently associated childhood with dark and difficult areas of experience. This article explores what happens to such challenging material when a poet of major significance changes the focus of…

Development of experimental design approach and ANN-based models for determination of Cr(VI) ions uptake rate from aqueous solution onto the solid biodiesel waste residue.

PubMed

Shanmugaprakash, M; Sivakumar, V

2013-11-01

In the present work, the evaluation capacities of two optimization methodologies such as RSM and ANN were employed and compared for predication of Cr(VI) uptake rate using defatted pongamia oil cake (DPOC) in both batch and column mode. The influence of operating parameters was investigated through a central composite design (CCD) of RSM using Design Expert 8.0.7.1 software. The same data was fed as input in ANN to obtain a trained the multilayer feed-forward networks back-propagation algorithm using MATLAB. The performance of the developed ANN models were compared with RSM mathematical models for Cr(VI) uptake rate in terms of the coefficient of determination (R(2)), root mean square error (RMSE) and absolute average deviation (AAD). The estimated values confirm that ANN predominates RSM representing the superiority of a trained ANN models over RSM models in order to capture the non-linear behavior of the given system. Copyright © 2013 Elsevier Ltd. All rights reserved.

Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN).

PubMed

Titah, Harmin Sulistiyaning; Halmi, Mohd Izuan Effendi Bin; Abdullah, Siti Rozaimah Sheikh; Hasan, Hassimi Abu; Idris, Mushrifah; Anuar, Nurina

2018-06-07

In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg -1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R 2 (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.

Friendly Letters on the Correspondence of Helen Keller, Anne Sullivan, and Alexander Graham Bell.

ERIC Educational Resources Information Center

Blatt, Burton

1985-01-01

Excerpts from the letters between Alexander Graham Bell and Anne Sullivan and Helen Keller are given to illustrate the educational and personal growth of Helen Keller as well as the educational philosophy of Bell regarding the education of the deaf blind. (DB)

Prophecy, patriarchy, and violence in the early modern household: the revelations of Anne Wentworth.

PubMed

Johnston, Warren

2009-10-01

In 1676 the apostate Baptist prophet Anne Wentworth (1629/30-1693?) published "A True Account of Anne Wentworths Being Cruelly, Unjustly, and Unchristianly Dealt with by Some of Those People called Anabaptists," the first in a series of pamphlets that would continue to the end of the decade. Orignially a member of a London Baptist church, Wentworth left the congregation and eventually her own home after her husband used physical force to stop her writing and prophesying. Yet Wentworth persisted in her "revelations." These prophecies increasingly focused on her response to those who were trying to stop her efforts, especially within her own household. This article examines Wentworth's writings as an effort by an early modern woman, using arguments of spiritual agency, to assert ideas about proper gender roles and household responsibilities to denounce her husband and rebut those who criticized and attempted to suppress her.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : AATA Web Survey

DOT National Transportation Integrated Search

1999-01-01

During 1997, visitors to the Ann Arbor (Michigan) Transportation Authority's worldwide web site were invited to complete an electronic questionnaire about their experience with the site. Eighty surveys were collected, representing a non-scientific se...

Carbon Cycle 2.0: Mary Ann Piette: Impact of efficient buildings

ScienceCinema

Mary Ann Piette

2017-12-09

Mary Ann Piette speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

Carbon Cycle 2.0: Mary Ann Piette: Impact of efficient buildings

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

Mary Ann Piette

Mary Ann Piette speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Archives And Records

DOT National Transportation Integrated Search

1999-01-01

This study examines data regularly maintained by the AATA (Ann Arbor Transportation Authority) for evidence of AOS (Advanced Operating System) impact. These data include on-time performance, bus trips broken because of maintenance or other incidents,...

Using AnnAGNPS to Predict the Effects of Tile Drainage Control on Nutrient and Sediment Loads for a River Basin.

PubMed

Que, Z; Seidou, O; Droste, R L; Wilkes, G; Sunohara, M; Topp, E; Lapen, D R

2015-03-01

Controlled tile drainage (CTD) can reduce pollutant loading. The Annualized Agricultural Nonpoint Source model (AnnAGNPS version 5.2) was used to examine changes in growing season discharge, sediment, nitrogen, and phosphorus loads due to CTD for a ∼3900-km agriculturally dominated river basin in Ontario, Canada. Two tile drain depth scenarios were examined in detail to mimic tile drainage control for flat cropland: 600 mm depth (CTD) and 200 mm (CTD) depth below surface. Summed for five growing seasons (CTD), direct runoff, total N, and dissolved N were reduced by 6.6, 3.5, and 13.7%, respectively. However, five seasons of summed total P, dissolved P, and total suspended solid loads increased as a result of CTD by 0.96, 1.6, and 0.23%. The AnnAGNPS results were compared with mass fluxes observed from paired experimental watersheds (250, 470 ha) in the river basin. The "test" experimental watershed was dominated by CTD and the "reference" watershed by free drainage. Notwithstanding environmental/land use differences between the watersheds and basin, comparisons of seasonal observed and predicted discharge reductions were comparable in 100% of respective cases. Nutrient load comparisons were more consistent for dissolved, relative to particulate water quality endpoints. For one season under corn crop production, AnnAGNPS predicted a 55% decrease (CTD) in dissolved N from the basin. AnnAGNPS v. 5.2 treats P transport from a surface pool perspective, which is appropriate for many systems. However, for assessment of tile drainage management practices for relatively flat tile-dominated systems, AnnAGNPS may benefit from consideration of P and particulate transport in the subsurface. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Elemental Study on Auscultaiting Diagnosis Support System of Hemodialysis Shunt Stenosis by ANN

NASA Astrophysics Data System (ADS)

Suzuki, Yutaka; Fukasawa, Mizuya; Mori, Takahiro; Sakata, Osamu; Hattori, Asobu; Kato, Takaya

It is desired to detect stenosis at an early stage to use hemodailysis shunt for longer time. Stethoscope auscultation of vascular murmurs is useful noninvasive diagnostic approach, but an experienced expert operator is necessary. Some experts often say that the high-pitch murmurs exist if the shunt becomes stenosed, and some studies report that there are some features detected at high frequency by time-frequency analysis. However, some of the murmurs are difficult to detect, and the final judgment is difficult. This study proposes a new diagnosis support system to screen stenosis by using vascular murmurs. The system is performed using artificial neural networks (ANN) with the analyzed frequency data by maximum entropy method (MEM). The author recorded vascular murmurs both before percutaneous transluminal angioplasty (PTA) and after. Examining the MEM spectral characteristics of the high-pitch stenosis murmurs, three features could be classified, which covered 85 percent of stenosis vascular murmurs. The features were learnt by the ANN, and judged. As a result, a percentage of judging the classified stenosis murmurs was 100%, and that of normal was 86%.

Computer Based Language Training: A Conversation with Duane M. Rumbaugh and Mary Ann Romski.

ERIC Educational Resources Information Center

Thomas, M. Angele

1981-01-01

An interview with Duane Rumbaugh and Mary Ann Romski, researchers on the use of alternative communication systems for severely and profoundly retarded persons, focuses on applications from their primate research and the use of a computerized keyboard system to investigate language acquisition in severely retarded persons. (CL)

Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain.

PubMed

Hussain, Amjad; Syed, Muhammad Ali; Abbas, Nasir; Hanif, Sana; Arshad, Muhammad Sohail; Bukhari, Nadeem Irfan; Hussain, Khalid; Akhlaq, Muhammad; Ahmad, Zeeshan

2016-06-01

A novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN) approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release), which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN

PubMed Central

AlSharabi, Khalil; Ibrahim, Sutrisno; Alsuwailem, Abdullah

2017-01-01

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new computer aided diagnosis (CAD) of autism ‎based on electroencephalography (EEG) signal analysis is investigated. The proposed method is based on discrete wavelet transform (DWT), entropy (En), and artificial neural network (ANN). DWT is used to decompose EEG signals into approximation and details coefficients to obtain EEG subbands. The feature vector is constructed by computing Shannon entropy values from each EEG subband. ANN classifies the corresponding EEG signal into normal or autistic based on the extracted features. The experimental results show the effectiveness of the proposed method for assisting autism diagnosis. A receiver operating characteristic (ROC) curve metric is used to quantify the performance of the proposed method. The proposed method obtained promising results tested using real dataset provided by King Abdulaziz Hospital, Jeddah, Saudi Arabia. PMID:28484720

A Practically Validated Intelligent Calibration Circuit Using Optimized ANN for Flow Measurement by Venturi

NASA Astrophysics Data System (ADS)

Venkata, Santhosh Krishnan; Roy, Binoy Krishna

2016-03-01

Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 % of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.

Comparison of geology of Jurassic Norphlet Mary Ann field, Mobile Bay, Alabama, to onshore regional Norphlet trends

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

Marzono, M.; Pense, G.; Andronaco, P.

The geology of the Mary Ann field is better understood in light of regional studies, which help to establish a depositional model in terms of both facies and thickness variations. These studies also illustrate major differences between onshore and offshore Norphlet deposits concerning topics such as diagenesis, hydrocarbon trapping, and migration. The Jurassic Norphlet sandstone was deposited in an arid basin extending from east Texas to Florida by a fluvial-eolian depositional system, prior to the transgression of the Smackover Formation. Until discovery of the Mary Ann field in 1979, Norphlet production was restricted to onshore areas, mostly along the Pickens-Pollardmore » fault system in Mississippi, Alabama, and Florida. The Mary Ann field is a Norphlet dry-gas accumulation, and was the first offshore field in the Gulf of Mexico to establish economic reserves in the Jurassic. The field is located in Mobile Bay, approximately 25 mi (40 km) south of Mobile, Alabama. Formed by a deep-seated (more than 20,000 ft or 6096 m) faulted salt pillow, Mary Ann field produces from a series of stacked eolian dune sands situated near the Norphlet paleocoastline. Five lithofacies have been recognized in cores from the Mobil 76 No. 2 well. Each lithofacies has a distinct reservoir quality. Optimum reservoir faces are the dune and sheet sands. Nonreservoir facies are interdune (wet and dry), marine reworked, and evaporitic sands. Following deposition, these sediments have undergone varying amounts of diagenesis. Early cementation of well-sorted sands supported the pore system during compaction. However, late cementation by chlorite, silica, and alteration of liquid hydrocarbons to an asphaltic residue have completely occluded the pore system in parts of the reservoir.« less

Effect of DEM mesh size on AnnAGNPS simulation and slope correction.

PubMed

Wang, Xiaoyan; Lin, Q

2011-08-01

The objective of this paper is to study the impact of the mesh size of the digital elevation model (DEM) on terrain attributes within an Annualized AGricultural NonPoint Source pollution (AnnAGNPS) Model simulation at watershed scale and provide a correction of slope gradient for low resolution DEMs. The effect of different grid sizes of DEMs on terrain attributes was examined by comparing eight DEMs (30, 40, 50, 60, 70, 80, 90, and 100 m). The accuracy of the AnnAGNPS stimulation on runoff, sediments, and nutrient loads is evaluated. The results are as follows: (1) Rnoff does not vary much with decrease of DEM resolution whereas soil erosion and total nitrogen (TN) load change prominently. There is little effect on runoff simulation of AnnAGNPS modeling by the amended slope using an adjusted 50 m DEM. (2) A decrease of sediment yield and TN load is observed with an increase of DEM mesh size from 30 to 60 m; a slight decrease of sediment and TN load with the DEM mesh size bigger than 60 m. There is similar trend for total phosphorus (TP) variation, but with less range of variation, the simulation of sediment, TN, and TP increase, in which sediment increase up to 1.75 times compared to the model using unadjusted 50 m DEM. In all, the amended simulation still has a large difference relative to the results using 30 m DEM. AnnAGNPS is less reliable for sediment loading prediction in a small hilly watershed. (3) Resolution of DEM has significant impact on slope gradient. The average, minimum, maximum of slope from the various DEMs reduced obviously with the decrease of DEM precision. For the grade of 0∼15°, the slopes at lower resolution DEM are generally bigger than those at higher resolution DEM. But for the grade bigger than 15°, the slopes at lower resolution DEM are generally smaller than those at higher resolution DEM. So it is necessary to adjust the slope with a fitting equation. A cubic model is used for correction of slope gradient from lower resolution to

Master Builder of Bridges between Research and Practice: An Interview with Ann Robinson

ERIC Educational Resources Information Center

Henshon, Suzanna E.

2010-01-01

This article presents an interview with Ann Robinson, a professor of educational psychology and founding director of the Center for Gifted Education at the University of Arkansas at Little Rock. She is the president of the National Association for Gifted Children (NAGC), a former editor of the Gifted Child Quarterly (GCQ), and was the first Editor…

Development Opportunities: The Effect of UMES on the Town of Princess Anne, Maryland.

ERIC Educational Resources Information Center

Sann, David; Tervala, Victor K.

A study was done of the potential economic effect of the University of Maryland Eastern Shore (UMES) campus on the nearby town of Princess Anne, a small rural community. The study used estimates made by a UMES faculty member which projected that UMES students in 1990 spent over $7 million on goods and services unrelated to educational expenses.…

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study.

PubMed

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-06-21

Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus. The results of this study

History of psychosurgery at Sainte-Anne Hospital, Paris, France, through translational interactions between psychiatrists and neurosurgeons.

PubMed

Zanello, Marc; Pallud, Johan; Baup, Nicolas; Peeters, Sophie; Turak, Baris; Krebs, Marie Odile; Oppenheim, Catherine; Gaillard, Raphael; Devaux, Bertrand

2017-09-01

Sainte-Anne Hospital is the largest psychiatric hospital in Paris. Its long and fascinating history began in the 18th century. In 1952, it was at Sainte-Anne Hospital that Jean Delay and Pierre Deniker used the first neuroleptic, chlorpromazine, to cure psychiatric patients, putting an end to the expansion of psychosurgery. The Department of Neuro-psychosurgery was created in 1941. The works of successive heads of the Neurosurgery Department at Sainte-Anne Hospital summarized the history of psychosurgery in France. Pierre Puech defined psychosurgery as the necessary cooperation between neurosurgeons and psychiatrists to treat the conditions causing psychiatric symptoms, from brain tumors to mental health disorders. He reported the results of his series of 369 cases and underlined the necessity for proper follow-up and postoperative re-education, illustrating the relative caution of French neurosurgeons concerning psychosurgery. Marcel David and his assistants tried to follow their patients closely postoperatively; this resulted in numerous publications with significant follow-up and conclusions. As early as 1955, David reported intellectual degradation 2 years after prefrontal leucotomies. Jean Talairach, a psychiatrist who eventually trained as a neurosurgeon, was the first to describe anterior capsulotomy in 1949. He operated in several hospitals outside of Paris, including the Sarthe Psychiatric Hospital and the Public Institution of Mental Health in the Lille region. He developed stereotactic surgery, notably stereo-electroencephalography, for epilepsy surgery but also to treat psychiatric patients using stereotactic lesioning with radiofrequency ablation or radioactive seeds of yttrium-90. The evolution of functional neurosurgery has been marked by the development of deep brain stimulation, in particular for obsessive-compulsive disorder, replacing the former lesional stereotactic procedures. The history of Sainte-Anne Hospital's Neurosurgery Department sheds

A study of using smartphone to detect and identify construction workers' near-miss falls based on ANN

NASA Astrophysics Data System (ADS)

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2018-03-01

As an effective fall accident preventive method, insight into near-miss falls provides an efficient solution to find out the causes of fall accidents, classify the type of near-miss falls and control the potential hazards. In this context, the paper proposes a method to detect and identify near-miss falls that occur when a worker walks in a workplace based on artificial neural network (ANN). The energy variation generated by workers who meet with near-miss falls is measured by sensors embedded in smart phone. Two experiments were designed to train the algorithm to identify various types of near-miss falls and test the recognition accuracy, respectively. At last, a test was conducted by workers wearing smart phones as they walked around a simulated construction workplace. The motion data was collected, processed and inputted to the trained ANN to detect and identify near-miss falls. Thresholds were obtained to measure the relationship between near-miss falls and fall accidents in a quantitate way. This approach, which integrates smart phone and ANN, will help detect near-miss fall events, identify hazardous elements and vulnerable workers, providing opportunities to eliminate dangerous conditions in a construction site or to alert possible victims that need to change their behavior before the occurrence of a fall accident.

Seafloor monitoring west of Helgoland (German Bight, North Sea) using the acoustic ground discrimination system RoxAnn

NASA Astrophysics Data System (ADS)

Hass, H. Christian; Mielck, Finn; Fiorentino, Dario; Papenmeier, Svenja; Holler, Peter; Bartholomä, Alexander

2017-04-01

Marine habitats of shelf seas are in constant dynamic change and therefore need regular assessment particularly in areas of special interest. In this study, the single-beam acoustic ground discrimination system RoxAnn served to assess seafloor hardness and roughness, and combine these parameters into one variable expressed as RGB (red green blue) color code followed by k-means fuzzy cluster analysis (FCA). The data were collected at a monitoring site west of the island of Helgoland (German Bight, SE North Sea) in the course of four surveys between September 2011 and November 2014. The study area has complex characteristics varying from outcropping bedrock to sandy and muddy sectors with mostly gradual transitions. RoxAnn data enabled to discriminate all seafloor types that were suggested by ground-truth information (seafloor samples, video). The area appears to be quite stable overall; sediment import (including fluid mud) was detected only from the NW. Although hard substrates (boulders, bedrock) are clearly identified, the signal can be modified by inclination and biocover. Manually, six RoxAnn zones were identified; for the FCA, only three classes are suggested. The latter classification based on `hard' boundaries would suffice for stakeholder issues, but the former classification based on `soft' boundaries is preferred to meet state-of-the-art scientific objectives.

Analysis of the effects of geological and geomorphological factors on earthquake triggered landslides using artificial neural networks (ANN)

NASA Astrophysics Data System (ADS)

Kawabata, D.; Bandibas, J.

2007-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic and geologic features, rock types and vegetative cover are important base factors of landslide occurrence. However, determining the relationship between these factors and landslide occurrence is very difficult using conventional mathematical analysis. The use of an advanced computing technique for this kind of analysis is very important. Artificial neural network (ANN) has recently been included in the list of analytical tools for a wide range of applications in the natural sciences research fields. One of the advantages of using ANN for pattern recognition is that it can handle data at any measurement scale ranging from nominal, ordinal to linear and ratio, and any form of data distribution (Wang et al., 1995). In addition, it can easily handle qualitative variables making it widely used in integrated analysis of spatial data from multiple sources for predicting and classification. This study focuses on the definition of the relationship between geological factors and landslide occurrence using artificial neural networks. The study also focuses on the effect of the DTMs (e.g. ASTER DTM, ALSM, digitized from paper map and digital photogrammetric measurement data). The main aim of the study is to generate landslide susceptibility index map using the defined relationship using ANN. Landslide data in the Chuetsu region were used in this research. The 2004 earthquake triggered many landslides in the region. The initial results of the study showed that ANN is more accurate in defining the relationship between geological and geomorphological factors and landslide occurrence. It also determined the best combination of geological and geomorphological factors that is directly related to landslide occurrence.

Estimation of Release History of Pollutant Source and Dispersion Coefficient of Aquifer Using Trained ANN Model

NASA Astrophysics Data System (ADS)

Srivastava, R.; Ayaz, M.; Jain, A.

2013-12-01

Knowledge of the release history of a groundwater pollutant source is critical in the prediction of the future trend of the pollutant movement and in choosing an effective remediation strategy. Moreover, for source sites which have undergone an ownership change, the estimated release history can be utilized for appropriate allocation of the costs of remediation among different parties who may be responsible for the contamination. Estimation of the release history with the help of concentration data is an inverse problem that becomes ill-posed because of the irreversible nature of the dispersion process. Breakthrough curves represent the temporal variation of pollutant concentration at a particular location, and contain significant information about the source and the release history. Several methodologies have been developed to solve the inverse problem of estimating the source and/or porous medium properties using the breakthrough curves as a known input. A common problem in the use of the breakthrough curves for this purpose is that, in most field situations, we have little or no information about the time of measurement of the breakthrough curve with respect to the time when the pollutant source becomes active. We develop an Artificial Neural Network (ANN) model to estimate the release history of a groundwater pollutant source through the use of breakthrough curves. It is assumed that the source location is known but the time dependent contaminant source strength is unknown. This temporal variation of the strength of the pollutant source is the output of the ANN model that is trained using the Levenberg-Marquardt algorithm utilizing synthetically generated breakthrough curves as inputs. A single hidden layer was used in the neural network and, to utilize just sufficient information and reduce the required sampling duration, only the upper half of the curve is used as the input pattern. The second objective of this work was to identify the aquifer parameters. An

The Nation behind the Diary: Anne Frank and the Holocaust of the Dutch Jews

ERIC Educational Resources Information Center

Foray, Jennifer L.

2011-01-01

Since its first appearance in 1947, "The Diary of Anne Frank" has been translated into sixty-five different languages, including Welsh, Esperanto, and Faroese. Millions and perhaps even billions of readers, scattered throughout the globe and now spanning multiple generations, are familiar with the life and work of this young Jewish…

Quantification of phenylpropanoids in commercial Echinacea products using TLC with video densitometry as detection technique and ANN for data modelling.

PubMed

Agatonovic-Kustrin, S; Loescher, Christine M; Singh, Ragini

2013-01-01

Echinacea preparations are among the most popular herbal remedies worldwide. Although it is generally assigned immune enhancement activities, the effectiveness of Echinacea is highly dependent on the Echinacea species, part of the plant used, the age of the plant, its location and the method of extraction. The aim of this study was to investigate the capacity of an artificial neural network (ANN) to analyse thin-layer chromatography (TLC) chromatograms as fingerprint patterns for quantitative estimation of three phenylpropanoid markers (chicoric acid, chlorogenic acid and echinacoside) in commercial Echinacea products. By applying samples with different weight ratios of marker compounds to the system, a database of chromatograms was constructed. One hundred and one signal intensities in each of the TLC chromatograms were correlated to the amounts of applied echinacoside, chlorogenic acid and chicoric acid using an ANN. The developed ANN correlation was used to quantify the amounts of three marker compounds in Echinacea commercial formulations. The minimum quantifiable level of 63, 154 and 98 ng and the limit of detection of 19, 46 and 29 ng were established for echinacoside, chlorogenic acid and chicoric acid respectively. A novel method for quality control of herbal products, based on TLC separation, high-resolution digital plate imaging and ANN data analysis has been developed. The method proposed can be adopted for routine evaluation of the phytochemical variability in Echinacea formulations available in the market. Copyright © 2012 John Wiley & Sons, Ltd.

Forecasting currency circulation data of Bank Indonesia by using hybrid ARIMAX-ANN model

NASA Astrophysics Data System (ADS)

Prayoga, I. Gede Surya Adi; Suhartono, Rahayu, Santi Puteri

2017-05-01

The purpose of this study is to forecast currency inflow and outflow data of Bank Indonesia. Currency circulation in Indonesia is highly influenced by the presence of Eid al-Fitr. One way to forecast the data with Eid al-Fitr effect is using autoregressive integrated moving average with exogenous input (ARIMAX) model. However, ARIMAX is a linear model, which cannot handle nonlinear correlation structures of the data. In the field of forecasting, inaccurate predictions can be considered caused by the existence of nonlinear components that are uncaptured by the model. In this paper, we propose a hybrid model of ARIMAX and artificial neural networks (ANN) that can handle both linear and nonlinear correlation. This method was applied for 46 series of currency inflow and 46 series of currency outflow. The results showed that based on out-of-sample root mean squared error (RMSE), the hybrid models are up to10.26 and 10.65 percent better than ARIMAX for inflow and outflow series, respectively. It means that ANN performs well in modeling nonlinear correlation of the data and can increase the accuracy of linear model.

Design of a MATLAB(registered trademark) Image Comparison and Analysis Tool for Augmentation of the Results of the Ann Arbor Distortion Test

DTIC Science & Technology

2016-06-25

The equipment used in this procedure includes: Ann Arbor distortion tester with 50-line grating reticule, IQeye 720 digital video camera with 12...and import them into MATLAB. In order to digitally capture images of the distortion in an optical sample, an IQeye 720 video camera with a 12... video camera and Ann Arbor distortion tester. Figure 8. Computer interface for capturing images seen by IQeye 720 camera. Once an image was

77 FR 66547 - Approval and Promulgation of Implementation Plans; Michigan; Detroit-Ann Arbor Nonattainment Area...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-06

... 2005 Base Year Emissions Inventory AGENCY: Environmental Protection Agency (EPA). ACTION: Final rule. SUMMARY: EPA is approving the fine particulate matter (PM 2.5 ) 2005 base year emissions inventory, a... 2005 base year emissions inventory for the Detroit-Ann Arbor area. EPA did not receive any comments...

The Sally-Anne test: an interactional analysis of a dyadic assessment.

PubMed

Korkiakangas, Terhi; Dindar, Katja; Laitila, Aarno; Kärnä, Eija

2016-11-01

The Sally-Anne test has been extensively used to examine children's theory of mind understanding. Many task-related factors have been suggested to impact children's performance on this test. Yet little is known about the interactional aspects of such dyadic assessment situations that might contribute to the ways in which children respond to the test questions. To examine the interactional factors contributing to the performance of two children in the Sally-Anne test. To identify the interactional practices used by the tester administering the task and to describe how interactional features can pose challenges in the critical belief and reality questions for both the tester and the testee. The Sally-Anne test was carried out as part of a project examining children's interactions in a technology-enhanced environment. The present study uses video recordings of two children with communication disorders (one with a current diagnosis of autism spectrum disorder [ASD]) and an adult tester. We draw on a multimodal approach to conversation analysis (CA) to examine the sequential organization of the test questions and answers. The children drew on diverse resources when producing responses to the test questions: responding verbally, pointing or manually handling objects. The tester treated these responses differently depending on how they were produced. When the child pointed at an object and verbally indicated their response, the tester moved on to the next question apparently accepting the child's answer. When the child manually handled an object or produced a quiet verbal response, the tester repeated the question indicating that the child's actions did not constitute an adequate response to a test question. In response to this, both children modified or changed their previous responses. Through monitoring each other, the tester and the child produced actions highly responsive to the features of each other's conduct, which underpinned the conduct of the test itself

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

PubMed

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

Geology-based method of assessing sensitivity of streams to acidic deposition in Charles and Anne Arundel Counties, Maryland

USGS Publications Warehouse

Rice, Karen C.; Bricker, Owen P.

1991-01-01

The report describes the results of a study to assess the sensitivity of streams to acidic deposition in Charles and Anne Arundel Counties, Maryland using a geology-based method. Water samples were collected from streams in July and August 1988 when streams were at base-flow conditions. Eighteen water samples collected from streams in Charles County, and 17 water samples from streams in Anne Arundel County were analyzed in the field for pH, specific conductance, and acid-neutralizing capacity (ANC); 8 water samples from streams in Charles County were analyzed in the laboratory for chloride and sulfate concentrations. The assessment revealed that streams in these counties are sensitive to acidification by acidic deposition.

Dynamically stable associative learning: a neurobiologically based ANN and its applications

NASA Astrophysics Data System (ADS)

Vogl, Thomas P.; Blackwell, Kim L.; Barbour, Garth; Alkon, Daniel L.

1992-07-01

Most currently popular artificial neural networks (ANN) are based on conceptions of neuronal properties that date back to the 1940s and 50s, i.e., to the ideas of McCullough, Pitts, and Hebb. Dystal is an ANN based on current knowledge of neurobiology at the cellular and subcellular level. Networks based on these neurobiological insights exhibit the following advantageous properties: (1) A theoretical storage capacity of bN non-orthogonal memories, where N is the number of output neurons sharing common inputs and b is the number of distinguishable (gray shade) levels. (2) The ability to learn, store, and recall associations among noisy, arbitrary patterns. (3) A local synaptic learning rule (learning depends neither on the output of the post-synaptic neuron nor on a global error term), some of whose consequences are: (4) Feed-forward, lateral, and feed-back connections (as well as time-sensitive connections) are possible without alteration of the learning algorithm; (5) Storage allocation (patch creation) proceeds dynamically as associations are learned (self- organizing); (6) The number of training set presentations required for learning is small (< 10) and does not change with pattern size or content; and (7) The network exhibits monotonic convergence, reaching equilibrium (fully trained) values without oscillating. The performance of Dystal on pattern completion tasks such as faces with different expressions and/or corrupted by noise, and on reading hand-written digits (98% accuracy) and hand-printed Japanese Kanji (90% accuracy) is demonstrated.

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study

PubMed Central

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-01-01

Background Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis Methods The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. Results By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus

76 FR 36151 - Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-21

... of Anthropology, University of Michigan, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The Museum of Anthropology, University of Michigan, has completed an inventory... the Museum of Anthropology, University of Michigan. Repatriation of the human remains to the tribe...

Research on Mechanical Fault Prediction Algorithm for Circuit Breaker Based on Sliding Time Window and ANN

NASA Astrophysics Data System (ADS)

Wang, Xiaohua; Rong, Mingzhe; Qiu, Juan; Liu, Dingxin; Su, Biao; Wu, Yi

A new type of algorithm for predicting the mechanical faults of a vacuum circuit breaker (VCB) based on an artificial neural network (ANN) is proposed in this paper. There are two types of mechanical faults in a VCB: operation mechanism faults and tripping circuit faults. An angle displacement sensor is used to measure the main axle angle displacement which reflects the displacement of the moving contact, to obtain the state of the operation mechanism in the VCB, while a Hall current sensor is used to measure the trip coil current, which reflects the operation state of the tripping circuit. Then an ANN prediction algorithm based on a sliding time window is proposed in this paper and successfully used to predict mechanical faults in a VCB. The research results in this paper provide a theoretical basis for the realization of online monitoring and fault diagnosis of a VCB.

Bodies in Space/Bodies in Motion/Bodies in Character: Adolescents Bear Witness to Anne Frank

ERIC Educational Resources Information Center

Chisholm, James S.; Whitmore, Kathryn F.

2016-01-01

Situated at the intersection of research on Holocaust education and embodied literacies this study examines how an arts-based instructional approach engaged middle school learners in developing empathetic perspectives on the Anne Frank narrative. We addressed the research question: What can adolescents who are using their bodies to gain empathy…

76 FR 80392 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-23

...: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... Michigan officials and its Museum of Anthropology professional staff in consultation with representatives... accessioned into the Museum of Anthropology. Between 2007 and 2009 the remains were inventoried at the...

77 FR 34991 - Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-12

... DEPARTMENT OF THE INTERIOR National Park Service [NPS-WASO-NAGPRA-10375; 2200-1100-665] Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI; Correction AGENCY: National Park Service, Interior. ACTION: Notice; correction. Notice is here given in accordance with the...

Modeling of biosorption of Cu(II) by alkali-modified spent tea leaves using response surface methodology (RSM) and artificial neural network (ANN)

NASA Astrophysics Data System (ADS)

Ghosh, Arpita; Das, Papita; Sinha, Keka

2015-06-01

In the present work, spent tea leaves were modified with Ca(OH)2 and used as a new, non-conventional and low-cost biosorbent for the removal of Cu(II) from aqueous solution. Response surface methodology (RSM) and artificial neural network (ANN) were used to develop predictive models for simulation and optimization of the biosorption process. The influence of process parameters (pH, biosorbent dose and reaction time) on the biosorption efficiency was investigated through a two-level three-factor (23) full factorial central composite design with the help of Design Expert. The same design was also used to obtain a training set for ANN. Finally, both modeling methodologies were statistically compared by the root mean square error and absolute average deviation based on the validation data set. Results suggest that RSM has better prediction performance as compared to ANN. The biosorption followed Langmuir adsorption isotherm and it followed pseudo-second-order kinetic. The optimum removal efficiency of the adsorbent was found as 96.12 %.

Mineral resource potential map of the Dolly Ann Roadless Area, Alleghany County, Virginia

USGS Publications Warehouse

Lesure, Frank G.; Jones, Jay G.

1983-01-01

The Dolly Ann Roadless Area comprises 7,900 acres (3,200 ha) in the George Washington National Forest in the Valley and Ridge physiographic province of west-central Virginia. The area is at the southern ·end of Warm Springs Mountain in Alleghany County just northeast of Covington, the county seat (index map). U.S. Highway 220 forms part of the western boundary, and U.S. Forest Service Road 125, which parallels Pounding Mill Creek, forms the eastern boundary. The principal streams draining the area are Pounding Mill Creek, Dry Run, and Roaring Run, all tributaries of the Jackson River. The highest point in the area is Big Knob at the north end, 4,072 ft (1241 m) above sea level; the lowest points, about 1,400 ft (427 m) above sea level, are at the south side, along Dry Run and Pounding Mill Creek. In general, the hill slopes are steep and heavily wooded with second- or third-growth hardwoods and scattered pine and hemlock. Dolly Ann Hollow near the east end of the area is a steep, boulder-strewn gorge, quite picturesque, but containing no good trails. A good trail up Dry Run connects a trail crossing the ridge between Bald Knob and Big Knob. No other trails cross the area.

ANN based Real-Time Estimation of Power Generation of Different PV Module Types

NASA Astrophysics Data System (ADS)

Syafaruddin; Karatepe, Engin; Hiyama, Takashi

Distributed generation is expected to become more important in the future generation system. Utilities need to find solutions that help manage resources more efficiently. Effective smart grid solutions have been experienced by using real-time data to help refine and pinpoint inefficiencies for maintaining secure and reliable operating conditions. This paper proposes the application of Artificial Neural Network (ANN) for the real-time estimation of the maximum power generation of PV modules of different technologies. An intelligent technique is necessary required in this case due to the relationship between the maximum power of PV modules and the open circuit voltage and temperature is nonlinear and can't be easily expressed by an analytical expression for each technology. The proposed ANN method is using input signals of open circuit voltage and cell temperature instead of irradiance and ambient temperature to determine the estimated maximum power generation of PV modules. It is important for the utility to have the capability to perform this estimation for optimal operating points and diagnostic purposes that may be an early indicator of a need for maintenance and optimal energy management. The proposed method is accurately verified through a developed real-time simulator on the daily basis of irradiance and cell temperature changes.

78 FR 67086 - Safety Zone, Submarine Cable Replacement Operations, Kent Island Narrows; Queen Anne's County, MD

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-08

... 1625-AA00 Safety Zone, Submarine Cable Replacement Operations, Kent Island Narrows; Queen Anne's County... Guard proposes to establish a temporary safety zone encompassing certain waters of Kent Island Narrows... potential safety hazards associated with the bridge project. Entry into this zone would be prohibited unless...

Tribological behaviour predictions of r-GO reinforced Mg composite using ANN coupled Taguchi approach

NASA Astrophysics Data System (ADS)

Kavimani, V.; Prakash, K. Soorya

2017-11-01

This paper deals with the fabrication of reduced graphene oxide (r-GO) reinforced Magnesium Metal Matrix Composite (MMC) through a novel solvent based powder metallurgy route. Investigations over basic and functional properties of developed MMC reveals that addition of r-GO improvises the microhardness upto 64 HV but however decrement in specific wear rate is also notified. Visualization of worn out surfaces through SEM images clearly explains for the occurrence of plastic deformation and the presence of wear debris because of ploughing out action. Taguchi coupled Artificial Neural Network (ANN) technique is adopted to arrive at optimal values of the input parameters such as load, reinforcement weight percentage, sliding distance and sliding velocity and thereby achieve minimal target output value viz. specific wear rate. Influence of any of the input parameter over specific wear rate studied through ANOVA reveals that load acting on pin has a major influence with 38.85% followed by r-GO wt. % of 25.82%. ANN model developed to predict specific wear rate value based on the variation of input parameter facilitates better predictability with R-value of 98.4% when compared with the outcomes of regression model.

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

NASA Astrophysics Data System (ADS)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

Joseph Campbell, Jung, Anne Tyler, and "The Cards": The Spiritual Journey in "Searching for Caleb."

ERIC Educational Resources Information Center

Thomson, Karen M.

Joseph Campbell, Carl Jung, and Anne Tyler have all dealt with spiritual journeys and card reading in their writings. In his book "Tarot Revelations," Joseph Campbell discusses his first association with tarot cards, dating from 1943, when he was introduced to the symoblism of playing cards by his friend and mentor, Heinrich Zimmer. Carl…

76 FR 73670 - Notice of Inventory Completion: University of Michigan Museum of Anthropology, Ann Arbor, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

...: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... Museum of Anthropology NAGPRA collections staff in consultation with representatives of the Bay Mills... Anthropology purchased the human remains from Reverend L. P. Rowland in November of 1924 as part of a larger...

78 FR 76169 - Patuxent Research Refuge, Prince George's and Anne Arundel Counties, MD; Final Comprehensive...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-16

...We, the U.S. Fish and Wildlife Service (Service), announce the availability of the final comprehensive conservation plan (CCP) and finding of no significant impact (FONSI) for Patuxent Research Refuge (Patuxent RR, refuge), located in Prince George's and Anne Arundel Counties, Maryland. In this final CCP, we describe how we will manage the refuge for the next 15 years.

Mathematical Modeling and Optimizing of in Vitro Hormonal Combination for G × N15 Vegetative Rootstock Proliferation Using Artificial Neural Network-Genetic Algorithm (ANN-GA)

PubMed Central

Arab, Mohammad M.; Yadollahi, Abbas; Ahmadi, Hamed; Eftekhari, Maliheh; Maleki, Masoud

2017-01-01

The efficiency of a hybrid systems method which combined artificial neural networks (ANNs) as a modeling tool and genetic algorithms (GAs) as an optimizing method for input variables used in ANN modeling was assessed. Hence, as a new technique, it was applied for the prediction and optimization of the plant hormones concentrations and combinations for in vitro proliferation of Garnem (G × N15) rootstock as a case study. Optimizing hormones combination was surveyed by modeling the effects of various concentrations of cytokinin–auxin, i.e., BAP, KIN, TDZ, IBA, and NAA combinations (inputs) on four growth parameters (outputs), i.e., micro-shoots number per explant, length of micro-shoots, developed callus weight (CW) and the quality index (QI) of plantlets. Calculation of statistical values such as R2 (coefficient of determination) related to the accuracy of ANN-GA models showed a considerably higher prediction accuracy for ANN models, i.e., micro-shoots number: R2 = 0.81, length of micro-shoots: R2 = 0.87, CW: R2 = 0.88, QI: R2 = 0.87. According to the results, among the input variables, BAP (19.3), KIN (9.64), and IBA (2.63) showed the highest values of variable sensitivity ratio for proliferation rate. The GA showed that media containing 1.02 mg/l BAP in combination with 0.098 mg/l IBA could lead to the optimal proliferation rate (10.53) for G × N15 rootstock. Another objective of the present study was to compare the performance of predicted and optimized cytokinin–auxin combination with the best optimized obtained concentrations of our other experiments. Considering three growth parameters (length of micro-shoots, micro-shoots number, and proliferation rate), the last treatment was found to be superior to the rest of treatments for G × N15 rootstock in vitro multiplication. Very little difference between the ANN predicted and experimental data confirmed high capability of ANN-GA method in predicting new optimized protocols for plant in vitro propagation

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Evaluation Of Automatic Vehicle Location Accuracy

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Very low-dose (0.15 mGy) chest CT protocols using the COPDGene 2 test object and a third-generation dual-source CT scanner with corresponding third-generation iterative reconstruction software.

PubMed

Newell, John D; Fuld, Matthew K; Allmendinger, Thomas; Sieren, Jered P; Chan, Kung-Sik; Guo, Junfeng; Hoffman, Eric A

2015-01-01

The purpose of this study was to evaluate the impact of ultralow radiation dose single-energy computed tomographic (CT) acquisitions with Sn prefiltration and third-generation iterative reconstruction on density-based quantitative measures of growing interest in phenotyping pulmonary disease. The effects of both decreasing dose and different body habitus on the accuracy of the mean CT attenuation measurements and the level of image noise (SD) were evaluated using the COPDGene 2 test object, containing 8 different materials of interest ranging from air to acrylic and including various density foams. A third-generation dual-source multidetector CT scanner (Siemens SOMATOM FORCE; Siemens Healthcare AG, Erlangen, Germany) running advanced modeled iterative reconstruction (ADMIRE) software (Siemens Healthcare AG) was used.We used normal and very large body habitus rings at dose levels varying from 1.5 to 0.15 mGy using a spectral-shaped (0.6-mm Sn) tube output of 100 kV(p). Three CT scans were obtained at each dose level using both rings. Regions of interest for each material in the test object scans were automatically extracted. The Hounsfield unit values of each material using weighted filtered back projection (WFBP) at 1.5 mGy was used as the reference value to evaluate shifts in CT attenuation at lower dose levels using either WFBP or ADMIRE. Statistical analysis included basic statistics, Welch t tests, multivariable covariant model using the F test to assess the significance of the explanatory (independent) variables on the response (dependent) variable, and CT mean attenuation, in the multivariable covariant model including reconstruction method. Multivariable regression analysis of the mean CT attenuation values showed a significant difference with decreasing dose between ADMIRE and WFBP. The ADMIRE has reduced noise and more stable CT attenuation compared with WFBP. There was a strong effect on the mean CT attenuation values of the scanned materials for ring

Clearance Rate and BP-ANN Model in Paraquat Poisoned Patients Treated with Hemoperfusion

PubMed Central

Hu, Lufeng; Hong, Guangliang; Ma, Jianshe; Wang, Xianqin; Lin, Guanyang; Zhang, Xiuhua; Lu, Zhongqiu

2015-01-01

In order to investigate the effect of hemoperfusion (HP) on the clearance rate of paraquat (PQ) and develop a clearance model, 41 PQ-poisoned patients who acquired acute PQ intoxication received HP treatment. PQ concentrations were determined by high performance liquid chromatography (HPLC). According to initial PQ concentration, study subjects were divided into two groups: Low-PQ group (0.05–1.0 μg/mL) and High-PQ group (1.0–10 μg/mL). After initial HP treatment, PQ concentrations decreased in both groups. However, in the High-PQ group, PQ levels remained in excess of 0.05 μg/mL and increased when the second HP treatment was initiated. Based on the PQ concentrations before and after HP treatment, the mean clearance rate of PQ calculated was 73 ± 15%. We also established a backpropagation artificial neural network (BP-ANN) model, which set PQ concentrations before HP treatment as input data and after HP treatment as output data. When it is used to predict PQ concentration after HP treatment, high prediction accuracy (R = 0.9977) can be obtained in this model. In conclusion, HP is an effective way to clear PQ from the blood, and the PQ concentration after HP treatment can be predicted by BP-ANN model. PMID:25695058

The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.

PubMed

Fiyadh, Seef Saadi; AlSaadi, Mohammed Abdulhakim; AlOmar, Mohamed Khalid; Fayaed, Sabah Saadi; Hama, Ako R; Bee, Sharifah; El-Shafie, Ahmed

2017-11-01

The main challenge in the lead removal simulation is the behaviour of non-linearity relationships between the process parameters. The conventional modelling technique usually deals with this problem by a linear method. The substitute modelling technique is an artificial neural network (ANN) system, and it is selected to reflect the non-linearity in the interaction among the variables in the function. Herein, synthesized deep eutectic solvents were used as a functionalized agent with carbon nanotubes as adsorbents of Pb 2+ . Different parameters were used in the adsorption study including pH (2.7 to 7), adsorbent dosage (5 to 20 mg), contact time (3 to 900 min) and Pb 2+ initial concentration (3 to 60 mg/l). The number of experimental trials to feed and train the system was 158 runs conveyed in laboratory scale. Two ANN types were designed in this work, the feed-forward back-propagation and layer recurrent; both methods are compared based on their predictive proficiency in terms of the mean square error (MSE), root mean square error, relative root mean square error, mean absolute percentage error and determination coefficient (R 2 ) based on the testing dataset. The ANN model of lead removal was subjected to accuracy determination and the results showed R 2 of 0.9956 with MSE of 1.66 × 10 -4 . The maximum relative error is 14.93% for the feed-forward back-propagation neural network model.

A comparison of two adaptive multivariate analysis methods (PLSR and ANN) for winter wheat yield forecasting using Landsat-8 OLI images

NASA Astrophysics Data System (ADS)

Chen, Pengfei; Jing, Qi

2017-02-01

An assumption that the non-linear method is more reasonable than the linear method when canopy reflectance is used to establish the yield prediction model was proposed and tested in this study. For this purpose, partial least squares regression (PLSR) and artificial neural networks (ANN), represented linear and non-linear analysis method, were applied and compared for wheat yield prediction. Multi-period Landsat-8 OLI images were collected at two different wheat growth stages, and a field campaign was conducted to obtain grain yields at selected sampling sites in 2014. The field data were divided into a calibration database and a testing database. Using calibration data, a cross-validation concept was introduced for the PLSR and ANN model construction to prevent over-fitting. All models were tested using the test data. The ANN yield-prediction model produced R2, RMSE and RMSE% values of 0.61, 979 kg ha-1, and 10.38%, respectively, in the testing phase, performing better than the PLSR yield-prediction model, which produced R2, RMSE, and RMSE% values of 0.39, 1211 kg ha-1, and 12.84%, respectively. Non-linear method was suggested as a better method for yield prediction.

Facteurs prédictifs de succès des étudiants en première année de médecine à l'université de Parakou

PubMed Central

Adoukonou, Thierry; Tognon-Tchegnonsi, Francis; Mensah, Emile; Allodé, Alexandre; Adovoekpe, Jean-Marie; Gandaho, Prosper; Akpona, Simon

2016-01-01

Introduction Plusieurs facteurs dont les notes obtenues au BAC peuvent influencer les performances académiques des étudiants en première année de médecine. L'objectif de cette étude était d’évaluer la relation entre les résultats des étudiants au BAC et le succès en première année de médecine. Méthodes Nous avons réalisé une étude analytique ayant inclus l'ensemble des étudiants régulièrement inscrits en première année à la Faculté de Médecine de l'université de Parakou durant l'année académique 2010-2011. Les données concernant les notes par discipline et mention obtenue au BAC ont été collectées. Une analyse multivariée utilisant la régression logistique et la régression linéaire multiple a permis d’établir les meilleurs prédicteurs du succès et de la moyenne de l’étudiant en fin d'année. Le logiciel SPSS version 17.0 a été utilisé pour l'analyse des données et un p<0,05 a été considéré comme statistiquement significatif. Résultats Parmi les 414 étudiants régulièrement inscrits les données de 407 ont pu être exploitées. Ils étaient âgés de 15 à 31 ans; 262 (64,4%) étaient de sexe masculin. 98 étaient admis avec un taux de succès de 23,7%. Le sexe masculin, la note obtenue en mathématiques, en sciences physiques, la moyenne au BAC et la mention étaient associés au succès en fin d'année mais en analyse multivariée seule une note en sciences physiques > 15/20 était associée au succès (OR: 2,8 [1,32- 6,00]). Pour la moyenne générale obtenue en fin d'année seule une mention bien obtenue au BAC était associée (coefficient de l'erreur standard: 0,130 Bêta =0,370 et p=0,00001). Conclusion Les meilleurs prédicateurs du succès en première année étaient une bonne moyenne en sciences physiques au BAC et une mention bien. La prise en compte de ces éléments dans le recrutement des étudiants en première année pourrait améliorer les résultats académiques. PMID:27313819

English for Specific Purposes: The State of the Art (An Online Interview with Ann M. Johns)

ERIC Educational Resources Information Center

Johns, Ann M.; Salmani Nodoushan, M. A.

2015-01-01

This forum paper is based on a friendly and informative interview conducted with Professor Ann M. Johns. In providing answers to the interview questions, Professor Johns suggests that all good teaching is ESP, and also distinguishes between EOP and ESP in that the former entails much more "just in time" learning while the latter may be…

The application of ANN for zone identification in a complex reservoir

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

White, A.C.; Molnar, D.; Aminian, K.

1995-12-31

Reservoir characterization plays a critical role in appraising the economic success of reservoir management and development methods. Nearly all reservoirs show some degree of heterogeneity, which invariably impacts production. As a result, the production performance of a complex reservoir cannot be realistically predicted without accurate reservoir description. Characterization of a heterogeneous reservoir is a complex problem. The difficulty stems from the fact that sufficient data to accurately predict the distribution of the formation attributes are not usually available. Generally the geophysical logs are available from a considerable number of wells in the reservoir. Therefore, a methodology for reservoir description andmore » characterization utilizing only well logs data represents a significant technical as well as economic advantage. One of the key issues in the description and characterization of heterogeneous formations is the distribution of various zones and their properties. In this study, several artificial neural networks (ANN) were successfully designed and developed for zone identification in a heterogeneous formation from geophysical well logs. Granny Creek Field in West Virginia has been selected as the study area in this paper. This field has produced oil from Big Injun Formation since the early 1900`s. The water flooding operations were initiated in the 1970`s and are currently still in progress. Well log data on a substantial number of wells in this reservoir were available and were collected. Core analysis results were also available from a few wells. The log data from 3 wells along with the various zone definitions were utilized to train the networks for zone recognition. The data from 2 other wells with previously determined zones, based on the core and log data, were then utilized to verify the developed networks predictions. The results indicated that ANN can be a useful tool for accurately identifying the zones in complex reservoirs.« less

FE-ANN based modeling of 3D Simple Reinforced Concrete Girders for Objective Structural Health Evaluation : Tech Transfer Summary

DOT National Transportation Integrated Search

2017-06-01

The objective of this study was to develop an objective, quantitative method for evaluating damage to bridge girders by using artificial neural networks (ANNs). This evaluation method, which is a supplement to visual inspection, requires only the res...

76 FR 44947 - Notice of Intent To Repatriate Cultural Items: University of Michigan Museum of Anthropology, Ann...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-27

... the appropriate Indian tribe, has determined that the items meet the definition of sacred objects and.... Representatives of any Indian tribe that believes itself to be culturally affiliated with the sacred objects may... of Anthropology, Ann Arbor, MI, that meet the definition of sacred objects under 25 U.S.C. 3001. This...

Support vector machine regression (LS-SVM)--an alternative to artificial neural networks (ANNs) for the analysis of quantum chemistry data?

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-06-28

A multilayer feed-forward artificial neural network (MLP-ANN) with a single, hidden layer that contains a finite number of neurons can be regarded as a universal non-linear approximator. Today, the ANN method and linear regression (MLR) model are widely used for quantum chemistry (QC) data analysis (e.g., thermochemistry) to improve their accuracy (e.g., Gaussian G2-G4, B3LYP/B3-LYP, X1, or W1 theoretical methods). In this study, an alternative approach based on support vector machines (SVMs) is used, the least squares support vector machine (LS-SVM) regression. It has been applied to ab initio (first principle) and density functional theory (DFT) quantum chemistry data. So, QC + SVM methodology is an alternative to QC + ANN one. The task of the study was to estimate the Møller-Plesset (MPn) or DFT (B3LYP, BLYP, BMK) energies calculated with large basis sets (e.g., 6-311G(3df,3pd)) using smaller ones (6-311G, 6-311G*, 6-311G**) plus molecular descriptors. A molecular set (BRM-208) containing a total of 208 organic molecules was constructed and used for the LS-SVM training, cross-validation, and testing. MP2, MP3, MP4(DQ), MP4(SDQ), and MP4/MP4(SDTQ) ab initio methods were tested. Hartree-Fock (HF/SCF) results were also reported for comparison. Furthermore, constitutional (CD: total number of atoms and mole fractions of different atoms) and quantum-chemical (QD: HOMO-LUMO gap, dipole moment, average polarizability, and quadrupole moment) molecular descriptors were used for the building of the LS-SVM calibration model. Prediction accuracies (MADs) of 1.62 ± 0.51 and 0.85 ± 0.24 kcal mol(-1) (1 kcal mol(-1) = 4.184 kJ mol(-1)) were reached for SVM-based approximations of ab initio and DFT energies, respectively. The LS-SVM model was more accurate than the MLR model. A comparison with the artificial neural network approach shows that the accuracy of the LS-SVM method is similar to the accuracy of ANN. The extrapolation and interpolation results show that LS-SVM is

Prediction of moving bed biofilm reactor (MBBR) performance for the treatment of aniline using artificial neural networks (ANN).

PubMed

Delnavaz, M; Ayati, B; Ganjidoust, H

2010-07-15

In this study, the results of 1-year efficiency forecasting using artificial neural networks (ANN) models of a moving bed biofilm reactor (MBBR) for a toxic and hard biodegradable aniline removal were investigated. The reactor was operated in an aerobic batch and continuous condition with 50% by volume which was filled with light expanded clay aggregate (LECA) as carrier. Efficiency evaluation of the reactors was obtained at different retention time (RT) of 8, 24, 48 and 72 h with an influent COD from 100 to 4000 mg/L. Exploratory data analysis was used to detect relationships between the data and dependent evaluated one. The appropriate architecture of the neural network models was determined using several steps of training and testing of the models. The ANN-based models were found to provide an efficient and a robust tool in predicting MBBR performance for treating aromatic amine compounds. 2010 Elsevier B.V. All rights reserved.

Prediction of coagulation and flocculation processes using ANN models and fuzzy regression.

PubMed

Zangooei, Hossein; Delnavaz, Mohammad; Asadollahfardi, Gholamreza

2016-09-01

Coagulation and flocculation are two main processes used to integrate colloidal particles into larger particles and are two main stages of primary water treatment. Coagulation and flocculation processes are only needed when colloidal particles are a significant part of the total suspended solid fraction. Our objective was to predict turbidity of water after the coagulation and flocculation process while other parameters such as types and concentrations of coagulants, pH, and influent turbidity of raw water were known. We used a multilayer perceptron (MLP), a radial basis function (RBF) of artificial neural networks (ANNs) and various kinds of fuzzy regression analysis to predict turbidity after the coagulation and flocculation processes. The coagulant used in the pilot plant, which was located in water treatment plant, was poly aluminum chloride. We used existing data, including the type and concentrations of coagulant, pH and influent turbidity, of the raw water because these types of data were available from the pilot plant for simulation and data was collected by the Tehran water authority. The results indicated that ANNs had more ability in simulating the coagulation and flocculation process and predicting turbidity removal with different experimental data than did the fuzzy regression analysis, and may have the ability to reduce the number of jar tests, which are time-consuming and expensive. The MLP neural network proved to be the best network compared to the RBF neural network and fuzzy regression analysis in this study. The MLP neural network can predict the effluent turbidity of the coagulation and the flocculation process with a coefficient of determination (R 2 ) of 0.96 and root mean square error of 0.0106.

Biosurfactant-biopolymer driven microbial enhanced oil recovery (MEOR) and its optimization by an ANN-GA hybrid technique.

PubMed

Dhanarajan, Gunaseelan; Rangarajan, Vivek; Bandi, Chandrakanth; Dixit, Abhivyakti; Das, Susmita; Ale, Kranthikiran; Sen, Ramkrishna

2017-08-20

A lipopeptide biosurfactant produced by marine Bacillus megaterium and a biopolymer produced by thermophilic Bacillus licheniformis were tested for their application potential in the enhanced oil recovery. The crude biosurfactant obtained after acid precipitation effectively reduced the surface tension of deionized water from 70.5 to 28.25mN/m and the interfacial tension between lube oil and water from 18.6 to 1.5mN/m at a concentration of 250mgL -1 . The biosurfactant exhibited a maximum emulsification activity (E 24 ) of 81.66% against lube oil. The lipopeptide micelles were stabilized by addition of Ca 2+ ions to the biosurfactant solution. The oil recovery efficiency of Ca 2+ conditioned lipopeptide solution from a sand-packed column was optimized by using artificial neural network (ANN) modelling coupled with genetic algorithm (GA) optimization. Three important parameters namely lipopeptide concentration, Ca 2+ concentration and solution pH were considered for optimization studies. In order to further improve the recovery efficiency, a water soluble biopolymer produced by Bacillus licheniformis was used as a flooding agent after biosurfactant incubation. Upon ANN-GA optimization, 45% tertiary oil recovery was achieved, when biopolymer at a concentration of 3gL -1 was used as a flooding agent. Oil recovery was only 29% at optimal conditions predicted by ANN-GA, when only water was used as flooding solution. The important characteristics of biopolymers such as its viscosity, pore plugging capabilities and bio-cementing ability have also been tested. Thus, as a result of biosurfactant incubation and biopolymer flooding under the optimal process conditions, a maximum oil recovery of 45% was achieved. Therefore, this study is novel, timely and interesting for it showed the combined influence of biosurfactant and biopolymer on solubilisation and mobilization of oil from the soil. Copyright © 2017 Elsevier B.V. All rights reserved.

Valorization of aquaculture waste in removal of cadmium from aqueous solution: optimization by kinetics and ANN analysis

NASA Astrophysics Data System (ADS)

Aditya, Gautam; Hossain, Asif

2018-05-01

Cadmium is one of the most hazardous heavy metal concerning human health and aquatic pollution. The removal of cadmium through biosorption is a feasible option for restoration of the ecosystem health of the contaminated freshwater ecosystems. In compliance with this proposition and considering the efficiency of calcium carbonate as biosorbent, the shell dust of the economically important snail Bellamya bengalensis was tested for the removal of cadmium from aqueous medium. Following use of the flesh as a cheap source of protein, the shells of B. bengalensis made up of CaCO3 are discarded as aquaculture waste. The biosorption was assessed through batch sorption studies along with studies to characterize the morphology and surface structures of waste shell dust. The data on the biosorption were subjected to the artificial neural network (ANN) model for optimization of the process. The biosorption process changed as functions of pH of the solution, concentration of heavy metal, biomass of the adsorbent and time of exposure. The kinetic process was well represented by pseudo second order ( R 2 = 0.998), and Langmuir equilibrium ( R 2 = 0.995) had better fits in the equilibrium process with 30.33 mg g-1 of maximum sorption capacity. The regression equation ( R 2 = 0.948) in the ANN model supports predicted values of Cd removal satisfactorily. The normalized importance analysis in ANN predicts Cd2+ concentration, and pH has the most influence in removal than biomass dose and time. The SEM and EDX studies show clear peaks for Cd confirming the biosorption process while the FTIR study depicts the main functional groups (-OH, C-H, C=O, C=C) responsible for the biosorption process. The study indicated that the waste shell dust can be used as an efficient, low cost, environment friendly, sustainable adsorbent for the removal of cadmium from aqueous solution.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Intelligent estimation of noise and blur variances using ANN for the restoration of ultrasound images.

PubMed

Uddin, Muhammad Shahin; Halder, Kalyan Kumar; Tahtali, Murat; Lambert, Andrew J; Pickering, Mark R; Marchese, Margaret; Stuart, Iain

2016-11-01

Ultrasound (US) imaging is a widely used clinical diagnostic tool in medical imaging techniques. It is a comparatively safe, economical, painless, portable, and noninvasive real-time tool compared to the other imaging modalities. However, the image quality of US imaging is severely affected by the presence of speckle noise and blur during the acquisition process. In order to ensure a high-quality clinical diagnosis, US images must be restored by reducing their speckle noise and blur. In general, speckle noise is modeled as a multiplicative noise following a Rayleigh distribution and blur as a Gaussian function. Hereto, we propose an intelligent estimator based on artificial neural networks (ANNs) to estimate the variances of noise and blur, which, in turn, are used to obtain an image without discernible distortions. A set of statistical features computed from the image and its complex wavelet sub-bands are used as input to the ANN. In the proposed method, we solve the inverse Rayleigh function numerically for speckle reduction and use the Richardson-Lucy algorithm for de-blurring. The performance of this method is compared with that of the traditional methods by applying them to a synthetic, physical phantom and clinical data, which confirms better restoration results by the proposed method.

An ANN-based HRV classifier for cardiac health prognosis.

PubMed

Sunkaria, Ramesh Kumar; Kumar, Vinod; Saxena, Suresh Chandra; Singhal, Achala M

2014-01-01

A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists.

The Picture of the Century with Floyd Thompsona and Ann Hitch Kilgore, Former Mayor of Hampton VA.

NASA Image and Video Library

1966-12-14

Langley Center Director Floyd Thompson shows Ann Kilgore the "picture of the century." This was the first picture of the earth taken from space. From Spaceflight Revolution: "On 23 August 1966 just as Lunar Orbiter I was about to pass behind the moon, mission controllers executed the necessary maneuvers to point the camera away from the lunar surface and toward the earth. The result was the world's first view of the earth from space. It was called "the picture of the century' and "the greatest shot taken since the invention of photography." Not even the color photos of the earth taken during the Apollo missions superseded the impact of this first image of our planet as a little island of life floating in the black and infinite sea of space." -- Published in James R. Hansen, Spaceflight Revolution: NASA Langley Research Center From Sputnik to Apollo, (Washington: NASA, 1995), pp. 345-346. Mayor Ann Kilgore was married to NASA researcher Edwin Carroll Kilgore. Mrs, Kilgore was Mayor from 1963-1971 and again from 1974-1978.

Modeling of policies for reduction of GHG emissions in energy sector using ANN: case study-Croatia (EU).

PubMed

Bolanča, Tomislav; Strahovnik, Tomislav; Ukić, Šime; Stankov, Mirjana Novak; Rogošić, Marko

2017-07-01

This study describes the development of tool for testing different policies for reduction of greenhouse gas (GHG) emissions in energy sector using artificial neural networks (ANNs). The case study of Croatia was elaborated. Two different energy consumption scenarios were used as a base for calculations and predictions of GHG emissions: the business as usual (BAU) scenario and sustainable scenario. Both of them are based on predicted energy consumption using different growth rates; the growth rates within the second scenario resulted from the implementation of corresponding energy efficiency measures in final energy consumption and increasing share of renewable energy sources. Both ANN architecture and training methodology were optimized to produce network that was able to successfully describe the existing data and to achieve reliable prediction of emissions in a forward time sense. The BAU scenario was found to produce continuously increasing emissions of all GHGs. The sustainable scenario was found to decrease the GHG emission levels of all gases with respect to BAU. The observed decrease was attributed to the group of measures termed the reduction of final energy consumption through energy efficiency measures.

A Report to the Board of Education of Anne Arundel County on the Status of the Schools.

ERIC Educational Resources Information Center

Anne Arundel County Board of Education, Annapolis, MD.

This annual report for the 1979-1980 school year summarizes and gives the status of the main objectives of the major programs within the public school system of Anne Arundel County. Project objectives for the 1981-82 school year as well as the one immediately following are also presented and explained. In his statement, the Superintendent of…

A soft computing scheme incorporating ANN and MOV energy in fault detection, classification and distance estimation of EHV transmission line with FSC.

PubMed

Khadke, Piyush; Patne, Nita; Singh, Arvind; Shinde, Gulab

2016-01-01

In this article, a novel and accurate scheme for fault detection, classification and fault distance estimation for a fixed series compensated transmission line is proposed. The proposed scheme is based on artificial neural network (ANN) and metal oxide varistor (MOV) energy, employing Levenberg-Marquardt training algorithm. The novelty of this scheme is the use of MOV energy signals of fixed series capacitors (FSC) as input to train the ANN. Such approach has never been used in any earlier fault analysis algorithms in the last few decades. Proposed scheme uses only single end measurement energy signals of MOV in all the 3 phases over one cycle duration from the occurrence of a fault. Thereafter, these MOV energy signals are fed as input to ANN for fault distance estimation. Feasibility and reliability of the proposed scheme have been evaluated for all ten types of fault in test power system model at different fault inception angles over numerous fault locations. Real transmission system parameters of 3-phase 400 kV Wardha-Aurangabad transmission line (400 km) with 40 % FSC at Power Grid Wardha Substation, India is considered for this research. Extensive simulation experiments show that the proposed scheme provides quite accurate results which demonstrate complete protection scheme with high accuracy, simplicity and robustness.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Driver And Dispatcher Perceptions Of AATA'S Advanced Operating System

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Applications of AnnAGNPS model for soil loss estimation and nutrient loading for Malaysian conditions

NASA Astrophysics Data System (ADS)

Shamshad, A.; Leow, C. S.; Ramlah, A.; Wan Hussin, W. M. A.; Sanusi, S. A. Mohd.

2008-09-01

The study evaluated the performance and suitability of AnnAGNPS model in assessing runoff, sediment loading and nutrient loading under Malaysian conditions. The watershed of River Kuala Tasik in Malaysia, a combination of two sub-watersheds, was selected as the area of study. The data for the year 2004 was used to calibrate the model and the data for the year 2005 was used for validation purposes. Several input parameters were computed using methods suggested by other researchers and studies carried out in Malaysia. The study shows that runoff was predicted well with an overall R2 value of 0.90 and E value of 0.70. Sediment loading was able to produce a moderate result of R2 = 0.66 and E = 0.49, nitrogen loading predictions were slightly better with R2 = 0.68 and E = 0.53, and phosphorus loading performance was slightly poor with an R2 = 0.63 and E = 0.33. The erosion map developed was in agreement with the erosion risk map produced by the Department of Agriculture, Malaysia. Rubber estates and urban areas were found to be the main contributors to soil erosion. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for planning and management of watersheds under Malaysian conditions.

Effect of hydrogen fluoride on pollen germination and pollen tube growth in Prunus avium L. cv. Royal Ann

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

Facteau, T.J.; Wang, S.Y.; Rowe, K.E.

1973-05-01

Increased fluoride (F) fumigation levels resulted in decrease in percent Royal Ann pollen germination and pollen tube growth. As dose (hour x concentration in ..mu.. gF/m/sup 3/) increased, Van pollen tube growth in vivo decreased. A linear relationship between increased dose and fluoride residue in the flowers was shown. 14 references, 5 figures.

"Anne of Green Gables": A One-Act Musical Based on Lucy Maud Montgomery's Novel. Cue Sheet for Teachers.

ERIC Educational Resources Information Center

Flynn, Rosalind

This performance guide is designed for teachers to use with students before and after a performance of the one-act musical based on Lucy Maud Montgomery's novel, "Anne of Green Gables," with music by Richard DeRosa and book and lyrics by Greg Gunning. The guide is designed to help teachers foster students' appreciation of theatre, dance,…

Meeting report for Odd Pols 2016: Ann Arbor 2.0.

PubMed

Roy-Engel, Astrid M

2017-05-15

The Tenth International Conference on Transcription by RNA Polymerases I, III, IV and V (the 'Odd Pols') was held June 24-28, 2016 at the University of Michigan, Ann Arbor, USA and organized by David Engelke, Deborah Johnson, Richard Maraia, Lawrence Rothblum, David Schneider, Andrzej Wierzbicki and Astrid Engel. The organizers are grateful for the support from the Rackham Graduate School of the University of Michigan for providing the meeting venue. The environment provided a great background with unexpected encounters with fireflies, free live music and a festive fireworks display. The meeting was composed of eleven oral sessions and a poster session. The keynote speaker, Dave Engelke, opened the meeting with his presentation entitled "A personal history of pol III transcription - how we got here from the 'good old days'." The meeting drew attendees from sixteen countries that shared their research discoveries. Here we present some of the highlights from the meeting using summaries provided by the participants. Copyright © 2016 Elsevier B.V. All rights reserved.

Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for

NASA Technical Reports Server (NTRS)

1993-01-01

Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for pictures in the NASA Magazine aritcle 'How it Feels to be a Human Test Subject' as they prepare for a bed rest study to simulate the efects of microgravity on the human body.

Two Different Approaches to Teaching Final-Year Projects for Mechanical Engineers and Biotechnologists at Ngee Ann Polytechnic--Case Studies Approach.

ERIC Educational Resources Information Center

Walsh, Kath; Rebaczonok-Padulo, Michael

1993-01-01

Ngee Ann Polytechnic, a leading postsecondary technical institution in Singapore, offers English for academic and occupational purposes to prepare students for writing their final year projects. This article discusses the approaches used in Mechanical Engineering and Biotechnology projects. A sample exercise is appended. (Contains two references.)…

Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed in Navarre (Spain)

USDA-ARS?s Scientific Manuscript database

AnnAGNPS (Annualized Agricultural Non-Point Source Pollution Model) is a system of computer models developed to predict non-point source pollutant loadings within agricultural watersheds. It contains a daily time step distributed parameter continuous simulation surface runoff model designed to assis...

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction

PubMed Central

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results. PMID:28125609

Determining degree of roasting in cocoa beans by artificial neural network (ANN)-based electronic nose system and gas chromatography/mass spectrometry (GC/MS).

PubMed

Tan, Juzhong; Kerr, William L

2018-08-01

Roasting is a critical step in chocolate processing, where moisture content is decreased and unique flavors and texture are developed. The determination of the degree of roasting in cocoa beans is important to ensure the quality of chocolate. Determining the degree of roasting relies on human specialists or sophisticated chemical analyses that are inaccessible to small manufacturers and farmers. In this study, an electronic nose system was constructed consisting of an array of gas sensors and used to detect volatiles emanating from cocoa beans roasted for 0, 20, 30 and 40 min. The several signals were used to train a three-layer artificial neural network (ANN). Headspace samples were also analyzed by gas chromatography/mass spectrometry (GC/MS), with 23 select volatiles used to train a separate ANN. Both ANNs were used to predict the degree of roasting of cocoa beans. The electronic nose had a prediction accuracy of 94.4% using signals from sensors TGS 813, 826, 822, 830, 830, 2620, 2602 and 2610. In comparison, the GC/MS predicted the degree of roasting with an accuracy of 95.8%. The electronic nose system is able to predict the extent of roasting, as well as a more sophisticated approach using GC/MS. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction.

PubMed

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results.

The adventures of Ann: A case study of a kindergarten teacher and her beliefs as she explored integrating science into her literacy curriculum

NASA Astrophysics Data System (ADS)

Potter, Gregory Ralph

Science education is an often neglected portion of the curriculum in elementary school, particularly in the primary grades. While early childhood educators have many choices in their curricula, two constants remain, literacy and math education. Ideally, young children need science along with literacy and mathematics. This study investigated how one kindergarten teacher used science to enhance her literacy program and how this use of science in her classroom affected her teaching beliefs. The case study took place in a publicly funded early childhood education center devoted to teaching kindergarten children in the small town of Summers in rural northern California. "Ann" was a master kindergarten teacher who historically used developmentally appropriate activities to support her literacy instruction. She was posed with the suggestion of infusing science into her literacy program and over the course of one school year, she was observed planning, implementing, and reflecting on six integrated science and literacy units. Ann's general teaching beliefs as well as her beliefs about teaching literacy and science were explored in order to investigate whether her experience with the integrated science and literacy units had altered her teaching beliefs. It was discovered that not only had Ann significantly changed the way she taught science, her beliefs about teaching science had changed and had moved towards mimicking her pro-active and positive beliefs about teaching literacy.

Design of an Experiment to Measure ann Using 3H(γ, pn)n at HIγS★

NASA Astrophysics Data System (ADS)

Friesen, F. Q. L.; Ahmed, M. W.; Crowe, B. J.; Crowell, A. S.; Cumberbatch, L. C.; Fallin, B.; Han, Z.; Howell, C. R.; Malone, R. M.; Markoff, D.; Tornow, W.; Witała, H.

2016-03-01

We provide an update on the development of an experiment at TUNL for determining the 1S0 neutron-neutron (nn) scattering length (ann) from differential cross-section measurements of three-body photodisintegration of the triton. The experiment will be conducted using a linearly polarized gamma-ray beam at the High Intensity Gamma-ray Source (HIγS) and tritium gas contained in thin-walled cells. The main components of the planned experiment are a 230 Ci gas target system, a set of wire chambers and silicon strip detectors on each side of the beam axis, and an array of neutron detectors on each side beyond the silicon detectors. The protons emitted in the reaction are tracked in the wire chambers and their energy and position are measured in silicon strip detectors. The first iteration of the experiment will be simplified, making use of a collimator system, and silicon detectors to interrogate the main region of interest near 90° in the polar angle. Monte-Carlo simulations based on rigorous 3N calculations have been conducted to validate the sensitivity of the experimental setup to ann. This research supported in part by the DOE Office of Nuclear Physics Grant Number DE-FG02-97ER41033

Ali, Cunich: Halley's Churches: Halley and the London Queen Anne Churches

NASA Astrophysics Data System (ADS)

Ali, Jason R.; Cunich, Peter

2005-04-01

Edmond Halley's enormous contribution to science has received much attention. New research adds an intriguing chapter to his story and concerns his hitherto unexplored association with the baroque architectural visionary Nicholas Hawksmoor, and some important Temple-inspired churches that were built in London in the early 1700s. We argue that Christchurch Spitalfields and St Anne's Limehouse, which were both started in the summer of 1714, were aligned exactly eastwards using ``corrected'' magnetic-compass bearings and that Halley influenced or aided Hawksmoor. By this time the men had probably known each other for 30 years and had recently worked together on the Clarendon Building in Oxford. Despite there being more than 1500 years of Chinese and about 500 years of Western compass technology at the time, these probably represent the first constructions planned using a modern-day ``scientific'' technique. The research also throws light on Halley's contended religious position.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

PubMed

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

Two Different Approaches to Teaching Final-Year Projects for Mechanical Engineers and Biotechnologists at Ngee Ann Polytechnic: Case Studies Approach.

ERIC Educational Resources Information Center

Walsh, Kath; Rebaczonok-Padulo, Michael

The Oral and Written Communication (OWC) course at Ngee Ann Polytechnic was originally intended to equip students with occupational skills (e.g., report- and letter-writing, public speaking) but has expanded to be a course aimed at helping third-year mechanical engineering students to develop third-year project reports. This has been done through…

Modeling and Investigation of the Wear Resistance of Salt Bath Nitrided Aisi 4140 via ANN

NASA Astrophysics Data System (ADS)

Ekinci, Şerafettin; Akdemir, Ahmet; Kahramanli, Humar

2013-05-01

Nitriding is usually used to improve the surface properties of steel materials. In this way, the wear resistance of steels is improved. We conducted a series of studies in order to investigate the microstructural, mechanical and tribological properties of salt bath nitrided AISI 4140 steel. The present study has two parts. For the first phase, the tribological behavior of the AISI 4140 steel which was nitrided in sulfinuz salt bath (SBN) was compared to the behavior of the same steel which was untreated. After surface characterization using metallography, microhardness and sliding wear tests were performed on a block-on-cylinder machine in which carbonized AISI 52100 steel discs were used as the counter face. For the examined AISI 4140 steel samples with and without surface treatment, the evolution of both the friction coefficient and of the wear behavior were determined under various loads, at different sliding velocities and a total sliding distance of 1000 m. The test results showed that wear resistance increased with the nitriding process, friction coefficient decreased due to the sulfur in salt bath and friction coefficient depended systematically on surface hardness. For the second part of this study, four artificial neural network (ANN) models were designed to predict the weight loss and friction coefficient of the nitrided and unnitrided AISI 4140 steel. Load, velocity and sliding distance were used as input. Back-propagation algorithm was chosen for training the ANN. Statistical measurements of R2, MAE and RMSE were employed to evaluate the success of the systems. The results showed that all the systems produced successful results.

Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

PubMed

Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

2015-05-01

The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of GWL with the help of GRACE TWS for unevenly spaced time series data in India : Analysis of comparative performances of SVR, ANN and LRM

NASA Astrophysics Data System (ADS)

Mukherjee, Amritendu; Ramachandran, Parthasarathy

2018-03-01

Prediction of Ground Water Level (GWL) is extremely important for sustainable use and management of ground water resource. The motivations for this work is to understand the relationship between Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water change (ΔTWS) data and GWL, so that ΔTWS could be used as a proxy measurement for GWL. In our study, we have selected five observation wells from different geographic regions in India. The datasets are unevenly spaced time series data which restricts us from applying standard time series methodologies and therefore in order to model and predict GWL with the help of ΔTWS, we have built Linear Regression Model (LRM), Support Vector Regression (SVR) and Artificial Neural Network (ANN). Comparative performances of LRM, SVR and ANN have been evaluated with the help of correlation coefficient (ρ) and Root Mean Square Error (RMSE) between the actual and fitted (for training dataset) or predicted (for test dataset) values of GWL. It has been observed in our study that ΔTWS is highly significant variable to model GWL and the amount of total variations in GWL that could be explained with the help of ΔTWS varies from 36.48% to 74.28% (0.3648 ⩽R2 ⩽ 0.7428) . We have found that for the model GWL ∼ Δ TWS, for both training and test dataset, performances of SVR and ANN are better than that of LRM in terms of ρ and RMSE. It also has been found in our study that with the inclusion of meteorological variables along with ΔTWS as input parameters to model GWL, the performance of SVR improves and it performs better than ANN. These results imply that for modelling irregular time series GWL data, ΔTWS could be very useful.

Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

NASA Astrophysics Data System (ADS)

Rahmati, Mehdi

2017-08-01

Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

Applying of the Artificial Neural Networks (ANN) to Identify and Characterize Sweet Spots in Shale Gas Formations

NASA Astrophysics Data System (ADS)

Puskarczyk, Edyta

2018-03-01

The main goal of the study was to enhance and improve information about the Ordovician and Silurian gas-saturated shale formations. Author focused on: firstly, identification of the shale gas formations, especially the sweet spots horizons, secondly, classification and thirdly, the accurate characterization of divisional intervals. Data set comprised of standard well logs from the selected well. Shale formations are represented mainly by claystones, siltstones, and mudstones. The formations are also partially rich in organic matter. During the calculations, information about lithology of stratigraphy weren't taken into account. In the analysis, selforganizing neural network - Kohonen Algorithm (ANN) was used for sweet spots identification. Different networks and different software were tested and the best network was used for application and interpretation. As a results of Kohonen networks, groups corresponding to the gas-bearing intervals were found. The analysis showed diversification between gas-bearing formations and surrounding beds. It is also shown that internal diversification in sweet spots is present. Kohonen algorithm was also used for geological interpretation of well log data and electrofacies prediction. Reliable characteristic into groups shows that Ja Mb and Sa Fm which are usually treated as potential sweet spots only partially have good reservoir conditions. It is concluded that ANN appears to be useful and quick tool for preliminary classification of members and sweet spots identification.

Workshop on Surface Science and Technology Held in Ann Arbor, Michigan on 7-9 November 1990

DTIC Science & Technology

1992-03-01

assess the state of the art of surface science and technology as well as to identify new research opportunities essential for the understanding and control...The objective of this workshop was to review and assess the state of the art of surface science and technology as well as to identify new research...AD-A253 566 ’ # 4 - m~~i n~nl lInIir ~~ na Ri1 ?epoi’rt: EN 1Workshop on Surface Science and Technology DTIC ft , L-CTE I OUG0 3192 Ann Arbor

Evaluation of a non-point source pollution model, AnnAGNPS, in a tropical watershed

USGS Publications Warehouse

Polyakov, V.; Fares, A.; Kubo, D.; Jacobi, J.; Smith, C.

2007-01-01

Impaired water quality caused by human activity and the spread of invasive plant and animal species has been identified as a major factor of degradation of coastal ecosystems in the tropics. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized Non-Point Source Pollution Model), in simulating runoff and soil erosion in a 48 km2 watershed located on the Island of Kauai, Hawaii. The model was calibrated and validated using 2 years of observed stream flow and sediment load data. Alternative scenarios of spatial rainfall distribution and canopy interception were evaluated. Monthly runoff volumes predicted by AnnAGNPS compared well with the measured data (R2 = 0.90, P < 0.05); however, up to 60% difference between the actual and simulated runoff were observed during the driest months (May and July). Prediction of daily runoff was less accurate (R2 = 0.55, P < 0.05). Predicted and observed sediment yield on a daily basis was poorly correlated (R2 = 0.5, P < 0.05). For the events of small magnitude, the model generally overestimated sediment yield, while the opposite was true for larger events. Total monthly sediment yield varied within 50% of the observed values, except for May 2004. Among the input parameters the model was most sensitive to the values of ground residue cover and canopy cover. It was found that approximately one third of the watershed area had low sediment yield (0-1 t ha-1 y-1), and presented limited erosion threat. However, 5% of the area had sediment yields in excess of 5 t ha-1 y-1. Overall, the model performed reasonably well, and it can be used as a management tool on tropical watersheds to estimate and compare sediment loads, and identify "hot spots" on the landscape. ?? 2007 Elsevier Ltd. All rights reserved.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Cost Study : Before, During And After AOS Implementation (October 1996-May 1999)

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority (AATA) began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such te...

Proceedings of Workshop on Priority Great Lakes Environmental Research Initiatives (Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan, October 10-11, 1974).

ERIC Educational Resources Information Center

Pinsak, Arthur P., Ed.

This publication contains the proceedings of a workshop held in Ann Arbor, Michigan to identify the priority Great Lakes environmental research initiatives. The five major objectives of the workshop include the determination of research initiatives, opportunities for university research communities to discuss and recommend future research…

The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data

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

Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.

2010-08-15

The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output.more » (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)« less

An Experimental Investigation into the Optimal Processing Conditions for the CO2 Laser Cladding of 20 MnCr5 Steel Using Taguchi Method and ANN

NASA Astrophysics Data System (ADS)

Mondal, Subrata; Bandyopadhyay, Asish.; Pal, Pradip Kumar

2010-10-01

This paper presents the prediction and evaluation of laser clad profile formed by means of CO2 laser applying Taguchi method and the artificial neural network (ANN). Laser cladding is one of the surface modifying technologies in which the desired surface characteristics of any component can be achieved such as good corrosion resistance, wear resistance and hardness etc. Laser is used as a heat source to melt the anti-corrosive powder of Inconel-625 (Super Alloy) to give a coating on 20 MnCr5 substrate. The parametric study of this technique is also attempted here. The data obtained from experiments have been used to develop the linear regression equation and then to develop the neural network model. Moreover, the data obtained from regression equations have also been used as supporting data to train the neural network. The artificial neural network (ANN) is used to establish the relationship between the input/output parameters of the process. The established ANN model is then indirectly integrated with the optimization technique. It has been seen that the developed neural network model shows a good degree of approximation with experimental data. In order to obtain the combination of process parameters such as laser power, scan speed and powder feed rate for which the output parameters become optimum, the experimental data have been used to develop the response surfaces.

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.

PubMed

Leng, Xiang'zi; Wang, Jinhua; Ji, Haibo; Wang, Qin'geng; Li, Huiming; Qian, Xin; Li, Fengying; Yang, Meng

2017-08-01

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM 2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m 3 . Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of ANN and SVM for classification of eye movements in EOG signals

NASA Astrophysics Data System (ADS)

Qi, Lim Jia; Alias, Norma

2018-03-01

Nowadays, electrooculogram is regarded as one of the most important biomedical signal in measuring and analyzing eye movement patterns. Thus, it is helpful in designing EOG-based Human Computer Interface (HCI). In this research, electrooculography (EOG) data was obtained from five volunteers. The (EOG) data was then preprocessed before feature extraction methods were employed to further reduce the dimensionality of data. Three feature extraction approaches were put forward, namely statistical parameters, autoregressive (AR) coefficients using Burg method, and power spectral density (PSD) using Yule-Walker method. These features would then become input to both artificial neural network (ANN) and support vector machine (SVM). The performance of the combination of different feature extraction methods and classifiers was presented and analyzed. It was found that statistical parameters + SVM achieved the highest classification accuracy of 69.75%.

An Emotional ANN (EANN) approach to modeling rainfall-runoff process

NASA Astrophysics Data System (ADS)

Nourani, Vahid

2017-01-01

This paper presents the first hydrological implementation of Emotional Artificial Neural Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall-runoff (r-r) modeling of the watersheds. Inspired by neurophysiological form of brain, in addition to conventional weights and bias, an EANN includes simulated emotional parameters aimed at improving the network learning process. EANN trained by a modified version of back-propagation (BP) algorithm was applied to single and multi-step-ahead runoff forecasting of two watersheds with two distinct climatic conditions. Also to evaluate the ability of EANN trained by smaller training data set, three data division strategies with different number of training samples were considered for the training purpose. The overall comparison of the obtained results of the r-r modeling indicates that the EANN could outperform the conventional feed forward neural network (FFNN) model up to 13% and 34% in terms of training and verification efficiency criteria, respectively. The superiority of EANN over classic ANN is due to its ability to recognize and distinguish dry (rainless days) and wet (rainy days) situations using hormonal parameters of the artificial emotional system.

An experimental study of interstitial lung tissue classification in HRCT images using ANN and role of cost functions

NASA Astrophysics Data System (ADS)

Dash, Jatindra K.; Kale, Mandar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan; Prabhakar, Nidhi; Garg, Mandeep; Kalra, Naveen

2017-03-01

In this paper, we investigate the effect of the error criteria used during a training phase of the artificial neural network (ANN) on the accuracy of the classifier for classification of lung tissues affected with Interstitial Lung Diseases (ILD). Mean square error (MSE) and the cross-entropy (CE) criteria are chosen being most popular choice in state-of-the-art implementations. The classification experiment performed on the six interstitial lung disease (ILD) patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Micronodules, Fibrosis and Healthy from MedGIFT database. The texture features from an arbitrary region of interest (AROI) are extracted using Gabor filter. Two different neural networks are trained with the scaled conjugate gradient back propagation algorithm with MSE and CE error criteria function respectively for weight updation. Performance is evaluated in terms of average accuracy of these classifiers using 4 fold cross-validation. Each network is trained for five times for each fold with randomly initialized weight vectors and accuracies are computed. Significant improvement in classification accuracy is observed when ANN is trained by using CE (67.27%) as error function compared to MSE (63.60%). Moreover, standard deviation of the classification accuracy for the network trained with CE (6.69) error criteria is found less as compared to network trained with MSE (10.32) criteria.

[Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

PubMed

Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

2010-01-01

Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

Optimization of Monocrystalline MgxCd1-xTe/MgyCd1-yTe Double-Heterostructure Solar Cells

NASA Astrophysics Data System (ADS)

Becker, Jacob J.

Polycrystalline CdS/CdTe solar cells continue to dominate the thin-film photovoltaics industry with an achieved record efficiency of over 22% demonstrated by First Solar, yet monocrystalline CdTe devices have received considerably less attention over the years. Monocrystalline CdTe double-heterostructure solar cells show great promise with respect to addressing the problem of low Voc with the passing of the 1 V benchmark. Rapid progress has been made in driving the efficiency in these devices ever closer to the record presently held by polycrystalline thin-films. This achievement is primarily due to the utilization of a remote p-n heterojunction in which the heavily doped contact materials, which are so problematic in terms of increasing non-radiative recombination inside the absorber, are moved outside of the CdTe double heterostructure with two MgyCd1-yTe barrier layers to provide confinement and passivation at the CdTe surfaces. Using this design, the pursuit and demonstration of efficiencies beyond 20% in CdTe solar cells is reported through the study and optimization of the structure barriers, contacts layers, and optical design. Further development of a wider bandgap MgxCd1-xTe solar cell based on the same design is included with the intention of applying this knowledge to the development of a tandem solar cell constructed on a silicon subcell. The exploration of different hole-contact materials--ZnTe, CuZnS, and a-Si:H--and their optimization is presented throughout the work. Devices utilizing a-Si:H hole contacts exhibit open-circuit voltages of up to 1.11 V, a maximum total-area efficiency of 18.5% measured under AM1.5G, and an active-area efficiency of 20.3% for CdTe absorber based devices. The achievement of voltages beyond 1.1V while still maintaining relatively high fill factors with no rollover, either before or after open-circuit, is a promising indicator that this approach can result in devices surpassing the 22% record set by polycrystalline

Constitutive Equations and ANN Approach to Predict the Flow Stress of Ti-6Al-4V Alloy Based on ABI Tests

NASA Astrophysics Data System (ADS)

Wang, Fuzeng; Zhao, Jun; Zhu, Ningbo

2016-11-01

The flow behavior of Ti-6Al-4V alloy was studied by automated ball indentation (ABI) tests in a wide range of temperatures (293, 493, 693, and 873 K) and strain rates (10-6, 10-5, and 10-4 s-1). Based on the experimental true stress-plastic strain data derived from the ABI tests, the Johnson-Cook (JC), Khan-Huang-Liang (KHL) and modified Zerilli-Armstrong (ZA) constitutive models, as well as artificial neural network (ANN) methods, were employed to predict the flow behavior of Ti-6Al-4V. A comparative study was made on the reliability of the four models, and their predictability was evaluated in terms of correlation coefficient ( R) and mean absolute percentage error. It is found that the flow stresses of Ti-6Al-4V alloy are more sensitive to temperature than strain rate under current experimental conditions. The predicted flow stresses obtained from JC model and KHL model show much better agreement with the experimental results than modified ZA model. Moreover, the ANN model is much more efficient and shows a higher accuracy in predicting the flow behavior of Ti-6Al-4V alloy than the constitutive equations.

The heart of Blessed Anne-Madeleine Remuzat: a biomedical approach of "miraculous" heart conservation.

PubMed

Charlier, Philippe; Huynh-Charlier, Isabelle; Poupon, Joël; Fox, Carles Lalueza; Keyser, Christine; Mougniot, Christian; Popescu, Spéranta-Maria; Brun, Luc; Pietri, Sylvia; Thévenard, Frédéric; Laquay, Laëtitia; Hurel, Agathe; Ellul, Jean-Pierre; Hervé, Christian

2014-01-01

We present here the results of our inter-disciplinary examination of the mummified heart of Blessed Anne-Madeleine Remuzat (1696-1730). This organ has been examined in the context of a canonization process. This analysis is related to important aspects of the early history of anatomy in Europe, that of "Holy autopsies", and to the relationship between anatomical investigations, Catholic theology, and religious/medical customs. According to anatomical, genetic, toxicological, and palynological analyses, it has been shown that this organ has not been naturally ("miraculously") conserved but embalmed using myrtle, honey, and lime. Moreover, a right ventricle dilatation has been diagnosed, that may represent a post-tuberculosis condition and may have played a role in the cause of death of this religious figure. Copyright © 2014 Elsevier Inc. All rights reserved.

[The utility boiler low NOx combustion optimization based on ANN and simulated annealing algorithm].

PubMed

Zhou, Hao; Qian, Xinping; Zheng, Ligang; Weng, Anxin; Cen, Kefa

2003-11-01

With the developing restrict environmental protection demand, more attention was paid on the low NOx combustion optimizing technology for its cheap and easy property. In this work, field experiments on the NOx emissions characteristics of a 600 MW coal-fired boiler were carried out, on the base of the artificial neural network (ANN) modeling, the simulated annealing (SA) algorithm was employed to optimize the boiler combustion to achieve a low NOx emissions concentration, and the combustion scheme was obtained. Two sets of SA parameters were adopted to find a better SA scheme, the result show that the parameters of T0 = 50 K, alpha = 0.6 can lead to a better optimizing process. This work can give the foundation of the boiler low NOx combustion on-line control technology.

Optimization of delignification of two Pennisetum grass species by NaOH pretreatment using Taguchi and ANN statistical approach.

PubMed

Mohaptra, Sonali; Dash, Preeti Krishna; Behera, Sudhanshu Shekar; Thatoi, Hrudayanath

2016-01-01

In the bioconversion of lignocelluloses for bioethanol, pretreatment seems to be the most important step which improves the elimination of the lignin and hemicelluloses content, exposing cellulose to further hydrolysis. The present study discusses the application of dynamic statistical techniques like the Taguchi method and artificial neural network (ANN) in the optimization of pretreatment of lignocellulosic biomasses such as Hybrid Napier grass (HNG) (Pennisetum purpureum) and Denanath grass (DG) (Pennisetum pedicellatum), using alkali sodium hydroxide. This study analysed and determined a parameter combination with a low number of experiments by using the Taguchi method in which both the substrates can be efficiently pretreated. The optimized parameters obtained from the L16 orthogonal array are soaking time (18 and 26 h), temperature (60°C and 55°C), and alkali concentration (1%) for HNG and DG, respectively. High performance liquid chromatography analysis of the optimized pretreated grass varieties confirmed the presence of glucan (47.94% and 46.50%), xylan (9.35% and 7.95%), arabinan (2.15% and 2.2%), and galactan/mannan (1.44% and 1.52%) for HNG and DG, respectively. Physicochemical characterization studies of native and alkali-pretreated grasses were carried out by scanning electron microscopy and Fourier transformation Infrared spectroscopy which revealed some morphological differences between the native and optimized pretreated samples. Model validation by ANN showed a good agreement between experimental results and the predicted responses.

Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Transfer And On-Time Performance Study : Before And After AOS Implementation, October 1996 - May 1999

DOT National Transportation Integrated Search

1999-01-01

In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

Correlation between electrical and mechanical properties in La1-xSrxGa1-yMgyO3-δ ceramics used as electrolytes for solid oxide fuel cells

NASA Astrophysics Data System (ADS)

Morales, M.; Roa, J. J.; Perez-Falcón, J. M.; Moure, A.; Tartaj, J.; Espiell, F.; Segarra, M.

2014-01-01

The relation between the electrical and the mechanical properties in Sr and Mg doped LaGaO3 ceramics, which can be used as electrolyte for solid oxide fuel cells, was investigated in terms of hardness and ionic conductivity. For this purpose, ceramic materials corresponding to the compositions of La1-xSrxGa1-yMgyO3-δ (LSGM), with x = 0.1 and y = 0.2, and x = 0.15 and y = 0.2, were prepared. LSGM powders synthesized by the ethylene glycol complex solution method were shaped into disks by isostatic pressing method. The variation in the microstructure of samples was achieved by varying the sintering temperature between 1300 and 1450 °C. While the effect of the different microstructures on the electrical properties of the LSGM electrolytes was determined by impedance spectroscopy, the influence of the hardness was extracted by instrumented indentation technique. The results showed a linear correlation between the hardness and total ionic conductivity within the temperature range of 500-660 °C, thus indicating that both properties were strongly influenced on the relative density and purity of the samples. It has a potential practical implication: by measuring the LSGM hardness at room temperature, one can achieve an approach to the ionic conductivity within the studied temperature range.

Tell it to someone who cares. The health care industry wants more information--and Anne Arundel Health Care Systems is giving it to them.

PubMed

Appleby, C

1995-10-20

The way to succeed in the health care industry these days is to stay ahead of the information curve. With a lot of ingenuity and a stern eye on the bottom line, Anne Arundel Health Care Systems in Maryland is doing just that. Here's how and why they did it, and how much they paid.

The use of artificial neural network (ANN) for the prediction and simulation of oil degradation in wastewater by AOP.

PubMed

Mustafa, Yasmen A; Jaid, Ghydaa M; Alwared, Abeer I; Ebrahim, Mothana

2014-06-01

The application of advanced oxidation process (AOP) in the treatment of wastewater contaminated with oil was investigated in this study. The AOP investigated is the homogeneous photo-Fenton (UV/H2O2/Fe(+2)) process. The reaction is influenced by the input concentration of hydrogen peroxide H2O2, amount of the iron catalyst Fe(+2), pH, temperature, irradiation time, and concentration of oil in the wastewater. The removal efficiency for the used system at the optimal operational parameters (H2O2 = 400 mg/L, Fe(+2) = 40 mg/L, pH = 3, irradiation time = 150 min, and temperature = 30 °C) for 1,000 mg/L oil load was found to be 72%. The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of oil degradation in aqueous solution by photo-Fenton process. The multilayered feed-forward networks were trained by using a backpropagation algorithm; a three-layer network with 22 neurons in the hidden layer gave optimal results. The results show that the ANN model can predict the experimental results with high correlation coefficient (R (2) = 0.9949). The sensitivity analysis showed that all studied variables (H2O2, Fe(+2), pH, irradiation time, temperature, and oil concentration) have strong effect on the oil degradation. The pH was found to be the most influential parameter with relative importance of 20.6%.

As-Deposited (La1-xSrx)(Ga1-y-zMgyCoz)O3-(x+y+z)/2 Crystallized Thin Films Prepared by Pulsed Laser Deposition for Application to Solid Oxide Fuel Cell Electrolyte

NASA Astrophysics Data System (ADS)

Mitsugi, Fumiaki; Kanazawa, Seiji; Ohkubo, Toshikazu; Nomoto, Yukiharu; Ishihara, Tatsumi; Takita, Yusaku

2004-01-01

Doped lanthanum gallate (La1-xSrx)(Ga1-y-zMgyCoz)O3-(x+y+z)/2 (LSGMCO) perovskite oxide films were deposited on a quartz glass, LaAlO3 single-crystal substrate and porous anode electrode of a solid oxide fuel cell (SOFC) by pulsed laser deposition. It was necessary to increase the substrate temperature up to 800°C for a crystallization of the LSGMCO films. The film deposited on the LaAlO3 single-crystal substrate grew along the c-axis. The as-deposited LSGMCO thick film fabricated on the porous substrate at 800°C and at an oxygen pressure of 20Pa was formed from polycrystal columns and showed a high conductivity of 0.7S/cm at a measurement temperature of 800°C. The activation energies were 0.72 eV at 600-800°C and 1.05 eV at 400-600°C.

Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

Women's translations of scientific texts in the 18th century: a case study of Marie-Anne Lavoisier.

PubMed

Kawashima, Keiko

2011-01-01

In the 18th century, many outstanding translations of scientific texts were done by women. These women were important mediators of science. However, I would like to raise the issue that the 'selection,' which is the process by which intellectual women chose to conduct translation works, and those 'selections' made by male translators, would not be made at the same level. For example, Émilie du Châtelet (1706-1749), the only French translator of Newton's "Principia," admitted her role as participating in important work, but, still, she was not perfectly satisfied with the position. For du Châtelet, the role as a translator was only an option under the current conditions that a female was denied the right to be a creator by society. In the case of Marie-Anne Lavoisier (1743-1794), like du Châtelet, we find an acute feeling in her mind that translation was not the work of creators. Because of her respect toward creative geniuses and her knowledge about the practical situation and concrete results of scientific studies, the translation works done by Marie-Anne Lavoisier were excellent. At the same time, the source of this excellence appears paradoxical at a glance: this excellence of translation was related closely with her low self-estimation in the field of science. Hence, we should not forget the gender problem that is behind such translations of scientific works done by women in that era. Such a possibility was a ray of light that was grasped by females, the sign of a gender that was eliminated from the center of scientific study due to social systems and norms and one of the few valuable opportunities to let people know of her own existence in the field of science.

Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Chen, Long; Sun, Yangbo; Bai, Yu; Huang, Bisheng; Chen, Keli

2018-03-01

Near-infrared (NIR) spectroscopy has been widely used in the analysis fields of traditional Chinese medicine. It has the advantages of fast analysis, no damage to samples and no pollution. In this research, a fast quantitative model for zinc oxide (ZnO) content in mineral medicine calamine was explored based on NIR spectroscopy. NIR spectra of 57 batches of calamine samples were collected and the first derivative (FD) method was adopted for conducting spectral pretreatment. The content of ZnO in calamine sample was determined using ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy. 57 batches of calamine samples were categorized into calibration and prediction set using the Kennard-Stone (K-S) algorithm. Firstly, in the calibration set, to calculate the correlation coefficient (r) between the absorbance value and the ZnO content of corresponding samples at each wave number. Next, according to the square correlation coefficient (r2) value to obtain the top 50 wave numbers to compose the characteristic spectral bands (4081.8-4096.3, 4188.9-4274.7, 4335.4, 4763.6,4794.4-4802.1, 4809.9, 4817.6-4875.4 cm- 1), which were used to establish the quantitative model of ZnO content using back propagation artificial neural network (BP-ANN) algorithm. Then, the 50 wave numbers were operated by the mean impact value (MIV) algorithm to choose wave numbers whose absolute value of MIV greater than or equal to 25, to obtain the optimal characteristic spectral bands (4875.4-4836.9, 4223.6-4080.9 cm- 1). And then, both internal cross and external validation were used to screen the number of hidden layer nodes of BP-ANN. Finally, the number 4 of hidden layer nodes was chosen as the best. At last, the BP-ANN model was found to enjoy a high accuracy and strong forecasting capacity for analyzing ZnO content in calamine samples ranging within 42.05-69.98%, with relative mean square error of cross validation (RMSECV) of 1.66% and coefficient of

A frequency-domain approach to improve ANNs generalization quality via proper initialization.

PubMed

Chaari, Majdi; Fekih, Afef; Seibi, Abdennour C; Hmida, Jalel Ben

2018-08-01

The ability to train a network without memorizing the input/output data, thereby allowing a good predictive performance when applied to unseen data, is paramount in ANN applications. In this paper, we propose a frequency-domain approach to evaluate the network initialization in terms of quality of training, i.e., generalization capabilities. As an alternative to the conventional time-domain methods, the proposed approach eliminates the approximate nature of network validation using an excess of unseen data. The benefits of the proposed approach are demonstrated using two numerical examples, where two trained networks performed similarly on the training and the validation data sets, yet they revealed a significant difference in prediction accuracy when tested using a different data set. This observation is of utmost importance in modeling applications requiring a high degree of accuracy. The efficiency of the proposed approach is further demonstrated on a real-world problem, where unlike other initialization methods, a more conclusive assessment of generalization is achieved. On the practical front, subtle methodological and implementational facets are addressed to ensure reproducibility and pinpoint the limitations of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

NASA Astrophysics Data System (ADS)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

Specific considerations for obtaining appropriate La1-xSrxGa1-yMgyO3-δ thin films using pulsed-laser deposition and its influence on the performance of solid-oxide fuel cells

NASA Astrophysics Data System (ADS)

Hwang, Jaeyeon; Lee, Heon; Lee, Jong-Ho; Yoon, Kyung Joong; Kim, Hyoungchul; Hong, Jongsup; Son, Ji-Won

2015-01-01

To obtain La1-xSrxGa1-yMgyO3-δ (LSGM) thin films with the appropriate properties, pulsed-laser deposition (PLD) is employed, and specific considerations regarding control of the deposition parameters is investigated. It is demonstrated that with a target of stoichiometric composition, appropriate LSGM thin films cannot be produced because of the deviation of the composition from the target to the thin film. Only after adjusting the target composition an LSGM thin film with an appropriate composition and phase can be obtained. The optimized LSGM thin film possesses an electrical conductivity close to that of the bulk LSGM. In contrast, non-optimized thin films do not yield any measurable electrical conductivity. The impact of the optimization of the LSGM thin-film electrolyte on the cell performance is quite significant, in that a solid-oxide fuel cell (SOFC) with an optimized LSGM thin-film electrolyte produces a maximum power density of 1.1 W cm-2 at 600 °C, whereas an SOFC with a non-optimal LSGM thin-film electrolyte is not operable.

Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells.

PubMed

Yetilmezsoy, Kaan; Demirel, Sevgi

2008-05-30

A three-layer artificial neural network (ANN) model was developed to predict the efficiency of Pb(II) ions removal from aqueous solution by Antep pistachio (Pistacia Vera L.) shells based on 66 experimental sets obtained in a laboratory batch study. The effect of operational parameters such as adsorbent dosage, initial concentration of Pb(II) ions, initial pH, operating temperature, and contact time were studied to optimise the conditions for maximum removal of Pb(II) ions. On the basis of batch test results, optimal operating conditions were determined to be an initial pH of 5.5, an adsorbent dosage of 1.0 g, an initial Pb(II) concentration of 30 ppm, and a temperature of 30 degrees C. Experimental results showed that a contact time of 45 min was generally sufficient to achieve equilibrium. After backpropagation (BP) training combined with principal component analysis (PCA), the ANN model was able to predict adsorption efficiency with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and a linear transfer function (purelin) at output layer. The Levenberg-Marquardt algorithm (LMA) was found as the best of 11 BP algorithms with a minimum mean squared error (MSE) of 0.000227875. The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of about 0.936 for five model variables used in this study.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

PubMed

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-09-02

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

PubMed Central

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-01-01

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds. PMID:26364642

Application of Particle Swarm Optimization Algorithm for Optimizing ANN Model in Recognizing Ripeness of Citrus

NASA Astrophysics Data System (ADS)

Diyana Rosli, Anis; Adenan, Nur Sabrina; Hashim, Hadzli; Ezan Abdullah, Noor; Sulaiman, Suhaimi; Baharudin, Rohaiza

2018-03-01

This paper shows findings of the application of Particle Swarm Optimization (PSO) algorithm in optimizing an Artificial Neural Network that could categorize between ripeness and unripeness stage of citrus suhuensis. The algorithm would adjust the network connections weights and adapt its values during training for best results at the output. Initially, citrus suhuensis fruit’s skin is measured using optically non-destructive method via spectrometer. The spectrometer would transmit VIS (visible spectrum) photonic light radiation to the surface (skin of citrus) of the sample. The reflected light from the sample’s surface would be received and measured by the same spectrometer in terms of reflectance percentage based on VIS range. These measured data are used to train and test the best optimized ANN model. The accuracy is based on receiver operating characteristic (ROC) performance. The result outcomes from this investigation have shown that the achieved accuracy for the optimized is 70.5% with a sensitivity and specificity of 60.1% and 80.0% respectively.

Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA)

PubMed Central

Shi, Xuedan; Ruan, Wenqian; Hu, Jiwei; Fan, Mingyi; Cao, Rensheng; Wei, Xionghui

2017-01-01

Rhodamine B (Rh B) is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, N2-sorption, and X-ray photoelectron spectroscopy (XPS) analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time) on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA). The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0%) was determined using the ANN-GA model, which was compatible with the experimental value (86.4%). Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model. PMID:28587196

Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA).

PubMed

Shi, Xuedan; Ruan, Wenqian; Hu, Jiwei; Fan, Mingyi; Cao, Rensheng; Wei, Xionghui

2017-06-03

Rhodamine B (Rh B) is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, N₂-sorption, and X-ray photoelectron spectroscopy (XPS) analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time) on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA). The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0%) was determined using the ANN-GA model, which was compatible with the experimental value (86.4%). Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model.

Estimation of runoff and sediment yield in the Redrock Creek watershed using AnnAGNPS and GIS

USGS Publications Warehouse

Tsou, Ming‐shu; Zhan, X.-Y.

2004-01-01

Sediment has been identified as a significant threat to water quality and channel clogging that in turn may lead to river flooding. With the increasing awareness of the impairment from sediment to water bodies in a watershed, identifying the locations of the major sediment sources and reducing the sediment through management practices will be important for an effective watershed management. The annualized agricultural non-point source pollution (AnnAGNPS) model and newly developed GIS interface for it were applied in a small agricultural watershed, Redrock Creek watershed, Kansas, in this pilot study for exploring the effectiveness of using this model as a management tool. The calibrated model appropriately simulated monthly runoff and sediment yield through the practices in this study and potentially suggested the ways of sediment reduction through evaluating the changes of land use and field operation in the model for the purpose of watershed management.

Ultralow-dose CT of the craniofacial bone for navigated surgery using adaptive statistical iterative reconstruction and model-based iterative reconstruction: 2D and 3D image quality.

PubMed

Widmann, Gerlig; Schullian, Peter; Gassner, Eva-Maria; Hoermann, Romed; Bale, Reto; Puelacher, Wolfgang

2015-03-01

OBJECTIVE. The purpose of this article is to evaluate 2D and 3D image quality of high-resolution ultralow-dose CT images of the craniofacial bone for navigated surgery using adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) in comparison with standard filtered backprojection (FBP). MATERIALS AND METHODS. A formalin-fixed human cadaver head was scanned using a clinical reference protocol at a CT dose index volume of 30.48 mGy and a series of five ultralow-dose protocols at 3.48, 2.19, 0.82, 0.44, and 0.22 mGy using FBP and ASIR at 50% (ASIR-50), ASIR at 100% (ASIR-100), and MBIR. Blinded 2D axial and 3D volume-rendered images were compared with each other by three readers using top-down scoring. Scores were analyzed per protocol or dose and reconstruction. All images were compared with the FBP reference at 30.48 mGy. A nonparametric Mann-Whitney U test was used. Statistical significance was set at p < 0.05. RESULTS. For 2D images, the FBP reference at 30.48 mGy did not statistically significantly differ from ASIR-100 at 3.48 mGy, ASIR-100 at 2.19 mGy, and MBIR at 0.82 mGy. MBIR at 2.19 and 3.48 mGy scored statistically significantly better than the FBP reference (p = 0.032 and 0.001, respectively). For 3D images, the FBP reference at 30.48 mGy did not statistically significantly differ from all reconstructions at 3.48 mGy; FBP and ASIR-100 at 2.19 mGy; FBP, ASIR-100, and MBIR at 0.82 mGy; MBIR at 0.44 mGy; and MBIR at 0.22 mGy. CONCLUSION. MBIR (2D and 3D) and ASIR-100 (2D) may significantly improve subjective image quality of ultralow-dose images and may allow more than 90% dose reductions.

A comparison RSM and ANN surface roughness models in thin-wall machining of Ti6Al4V using vegetable oils under MQL-condition

NASA Astrophysics Data System (ADS)

Mohruni, Amrifan Saladin; Yanis, Muhammad; Sharif, Safian; Yani, Irsyadi; Yuliwati, Erna; Ismail, Ahmad Fauzi; Shayfull, Zamree

2017-09-01

Thin-wall components as usually applied in the structural parts of aeronautical industry require significant challenges in machining. Unacceptable surface roughness can occur during machining of thin-wall. Titanium product such Ti6Al4V is mostly applied to get the appropriate surface texture in thin wall designed requirements. In this study, the comparison of the accuracy between Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) in the prediction of surface roughness was conducted. Furthermore, the machining tests were carried out under Minimum Quantity Lubrication (MQL) using AlCrN-coated carbide tools. The use of Coconut oil as cutting fluids was also chosen in order to evaluate its performance when involved in end milling. This selection of cutting fluids is based on the better performance of oxidative stability than that of other vegetable based cutting fluids. The cutting speed, feed rate, radial and axial depth of cut were used as independent variables, while surface roughness is evaluated as the dependent variable or output. The results showed that the feed rate is the most significant factors in increasing the surface roughness value followed by the radial depth of cut and lastly the axial depth of cut. In contrary, the surface becomes smoother with increasing the cutting speed. From a comparison of both methods, the ANN model delivered a better accuracy than the RSM model.

The educational challenge of Paediatric Virology: An interview with Professor of Neonatology Anne Greenough.

PubMed

Mammas, Ioannis N; Spandidos, Demetrios A

2017-10-01

According to Professor Anne Greenough, Professor of Neonatology and Clinical Respiratory Physiology at the King's College London (London, UK), Paediatric Virology is indeed a rapidly increasing educational challenge. Professor Greenough, who in 1992 wrote her book on congenital, perinatal and neonatal infections, believes that during the past 3 decades, paediatric health professionals are becoming increasingly involved in specialised care and follow-up of paediatric patients with viral diseases, who require advanced medical care and innovative technological services. Moreover, she highlights the expected role of new vaccines and antiviral agents that are currently under investigation, as well as the impact of emerging viral diseases that require novel prevention strategies and therapeutic protocols. However, she notes that the number of Paediatric Virologists in any one country is likely to be small; hence, a separate paediatric subspecialty needs to be considered carefully. In the context of the 3rd Workshop on Paediatric Virology, which will be held in Athens, Greece, on October 7th, 2017, Professor Greenough will give her plenary lecture on the impact of viral infections on the long term outcomes of prematurely born infants.

The educational challenge of Paediatric Virology: An interview with Professor of Neonatology Anne Greenough

PubMed Central

Mammas, Ioannis N.; Spandidos, Demetrios A.

2017-01-01

According to Professor Anne Greenough, Professor of Neonatology and Clinical Respiratory Physiology at the King's College London (London, UK), Paediatric Virology is indeed a rapidly increasing educational challenge. Professor Greenough, who in 1992 wrote her book on congenital, perinatal and neonatal infections, believes that during the past 3 decades, paediatric health professionals are becoming increasingly involved in specialised care and follow-up of paediatric patients with viral diseases, who require advanced medical care and innovative technological services. Moreover, she highlights the expected role of new vaccines and antiviral agents that are currently under investigation, as well as the impact of emerging viral diseases that require novel prevention strategies and therapeutic protocols. However, she notes that the number of Paediatric Virologists in any one country is likely to be small; hence, a separate paediatric subspecialty needs to be considered carefully. In the context of the 3rd Workshop on Paediatric Virology, which will be held in Athens, Greece, on October 7th, 2017, Professor Greenough will give her plenary lecture on the impact of viral infections on the long term outcomes of prematurely born infants. PMID:29042914

Biosorption of chromium (VI) from aqueous solutions and ANN modelling.

PubMed

Nag, Soma; Mondal, Abhijit; Bar, Nirjhar; Das, Sudip Kumar

2017-08-01

The use of sustainable, green and biodegradable natural wastes for Cr(VI) detoxification from the contaminated wastewater is considered as a challenging issue. The present research is aimed to assess the effectiveness of seven different natural biomaterials, such as jackfruit leaf, mango leaf, onion peel, garlic peel, bamboo leaf, acid treated rubber leaf and coconut shell powder, for Cr(VI) eradication from aqueous solution by biosorption process. Characterizations were conducted using SEM, BET and FTIR spectroscopy. The effects of operating parameters, viz., pH, initial Cr(VI) ion concentration, adsorbent dosages, contact time and temperature on metal removal efficiency, were studied. The biosorption mechanism was described by the pseudo-second-order model and Langmuir isotherm model. The biosorption process was exothermic, spontaneous and chemical (except garlic peel) in nature. The sequence of adsorption capacity was mango leaf > jackfruit leaf > acid treated rubber leaf > onion peel > bamboo leaf > garlic peel > coconut shell with maximum Langmuir adsorption capacity of 35.7 mg g -1 for mango leaf. The treated effluent can be reused. Desorption study suggested effective reuse of the adsorbents up to three cycles, and safe disposal method of the used adsorbents suggested biodegradability and sustainability of the process by reapplication of the spent adsorbent and ultimately leading towards zero wastages. The performances of the adsorbents were verified with wastewater from electroplating industry. The scale-up study reported for industrial applications. ANN modelling using multilayer perception with gradient descent (GD) and Levenberg-Marquart (LM) algorithm had been successfully used for prediction of Cr(VI) removal efficiency. The study explores the undiscovered potential of the natural waste materials for sustainable existence of small and medium sector industries, especially in the third world countries by protecting the environment by eco-innovation.

Optimizing the balance between radiation dose and image quality in pediatric head CT: findings before and after intensive radiologic staff training.

PubMed

Paolicchi, Fabio; Faggioni, Lorenzo; Bastiani, Luca; Molinaro, Sabrina; Puglioli, Michele; Caramella, Davide; Bartolozzi, Carlo

2014-06-01

The purpose of this study was to assess the radiation dose and image quality of pediatric head CT examinations before and after radiologic staff training. Outpatients 1 month to 14 years old underwent 215 unenhanced head CT examinations before and after intensive training of staff radiologists and technologists in optimization of CT technique. Patients were divided into three age groups (0-4, 5-9, and 10-14 years), and CT dose index, dose-length product, tube voltage, and tube current-rotation time product values before and after training were retrieved from the hospital PACS. Gray matter conspicuity and contrast-to-noise ratio before and after training were calculated, and subjective image quality in terms of artifacts, gray-white matter differentiation, noise, visualization of posterior fossa structures, and need for repeat CT examination was visually evaluated by three neuroradiologists. The median CT dose index and dose-length product values were significantly lower after than before training in all age groups (27 mGy and 338 mGy ∙ cm vs 107 mGy and 1444 mGy ∙ cm in the 0- to 4-year-old group, 41 mGy and 483 mGy ∙ cm vs 68 mGy and 976 mGy ∙ cm in the 5- to 9-year-old group, and 51 mGy and 679 mGy ∙ cm vs 107 mGy and 1480 mGy ∙ cm in the 10- to 14-year-old group; p < 0.001). The tube voltage and tube current-time values after training were significantly lower than the levels before training (p < 0.001). Subjective posttraining image quality was not inferior to pretraining levels for any item except noise (p < 0.05), which, however, was never diagnostically unacceptable. Radiologic staff training can be effective in reducing radiation dose while preserving diagnostic image quality in pediatric head CT examinations.

Occupational and patient exposure in coronary angiography procedures

NASA Astrophysics Data System (ADS)

Sulieman, A.; Alzimami, K.; Gafar, R.; Babikir, E.; Alsafi, K.; Suliman, I. I.

2014-11-01

Cardiac catheterization is the gold standard in the diagnosis and management of coronary artery diseases. The objectives of this study were to evaluate the radiation dose of patients and staff during cardiology procedures. Staff was monitored using thermoluminescence dosimeter (TLD) chips for 86 procedures. The mean patient dose was 2813.6 μGy m2 and the mean fluoroscopic time was 4.8 min. The mean radiation doses for cardiologists were 0.9 mGy for the forehead, 0.92 mGy for the thyroid, 1.38 mGy for the chest, 1.28 mGy for the waist and 1.41 mGy for the hand. The mean radiation doses for assistants were 0.72 mGy for the chest, 0.82 mGy for the hand. High patient and staff exposure is due to lack of experience and protective equipment, exacerbated by a high workload. Interventional procedures remain operator dependent; therefore, continuous training is crucial.

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

PubMed

Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

2018-01-01

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

Niche partitioning of marine group I Crenarchaeota in the euphotic and upper mesopelagic zones of the East China Sea.

PubMed

Hu, Anyi; Jiao, Nianzhi; Zhang, Rui; Yang, Zao

2011-11-01

Marine group I Crenarchaeota (MGI) represents a ubiquitous and numerically predominant microbial population in marine environments. An understanding of the spatial dynamics of MGI and its controlling mechanisms is essential for an understanding of the role of MGI in energy and element cycling in the ocean. In the present study, we investigated the diversity and abundance of MGI in the East China Sea (ECS) by analysis of crenarchaeal 16S rRNA gene, the ammonia monooxygenase gene amoA, and the biotin carboxylase gene accA. Quantitative PCR analyses revealed that these genes were higher in abundance in the mesopelagic than in the euphotic zone. In addition, the crenarchaeal amoA gene was positively correlated with the copy number of the MGI 16S rRNA gene, suggesting that most of the MGI in the ECS are nitrifiers. Furthermore, the ratios of crenarchaeal accA to amoA or to MGI 16S rRNA genes increased from the euphotic to the mesopelagic zone, suggesting that the role of MGI in carbon cycling may change from the epipelagic to the mesopelagic zones. Denaturing gradient gel electrophoretic profiling of the 16S rRNA genes revealed depth partitioning in MGI community structures. Clone libraries of the crenarchaeal amoA and accA genes showed both "shallow" and "deep" groups, and their relative abundances varied in the water column. Ecotype simulation analysis revealed that MGI in the upper ocean could diverge into special ecotypes associated with depth to adapt to the light gradient across the water column. Overall, our results showed niche partitioning of the MGI population and suggested a shift in their ecological functions between the euphotic and mesopelagic zones of the ECS.

Breast Radiation Dose With CESM Compared With 2D FFDM and 3D Tomosynthesis Mammography.

PubMed

James, Judy R; Pavlicek, William; Hanson, James A; Boltz, Thomas F; Patel, Bhavika K

2017-02-01

We aimed to compare radiation dose received during contrast-enhanced spectral mammography (CESM) using high- and low-energy projections with radiation dose received during 2D full field digital mammography (FFDM) and 3D tomosynthesis on phantoms and patients with varying breast thickness and density. A single left craniocaudal projection was chosen to determine the doses for 6214 patients who underwent 2D FFDM, 3662 patients who underwent 3D tomosynthesis, and 173 patients who underwent CESM in this retrospective study. Dose measurements were also collected in phantoms with composition mimicking nondense and dense breast tissue. Average glandular dose (AGD) ± SD was 3.0 ± 1.1 mGy for CESM exposures at a mean breast thickness of 63 mm. At this thickness, the dose was 2.1 mGy from 2D FFDM and 2.5 mGy from 3D tomosynthesis. The nondense phantom had a mean AGD of 1.0 mGy with 2D FFDM, 1.3 mGy with 3D tomosynthesis, and 1.6 mGy with CESM. The dense breast phantom had a mean AGD of 1.3 mGy with 2D FFDM, 1.4 mGy with 3D tomosynthesis, and 2.1 mGy with CESM. At a compressed thickness of 4.5 cm, radiation exposure from CESM was approximately 25% higher in dense breast phantoms than in nondense breast phantoms. The dose in the dense phantom at a compressed thickness of 6 cm was approximately 42% higher than the dose in the nondense phantom at a compressed thickness of 4.5 cm. CESM was found to increase AGD at a mean breast thickness of 63 mm by approximately 0.9 mGy and 0.5 mGy compared with 2D FFDM and 3D tomosynthesis, respectively. Of note, CESM provides a standard image (similar to 2D FFDM) that is obtained using the low-energy projection. Overall, the AGD from CESM falls below the dose limit of 3 mGy set by Mammography Quality Standards Act regulations.

Altered cellular magnesium responsiveness to hyperglycemia in hypertensive subjects.

PubMed

Barbagallo, M; Dominguez, L J; Bardicef, O; Resnick, L M

2001-09-01

Previous studies by our group have identified ionic aspects of insulin resistance in hypertension, in which cellular responses to insulin were influenced by the basal intracellular ionic environment-the lower the cytosolic free magnesium (Mg(i)), the less Mg(i) increased following insulin stimulation. To investigate whether this ionic insulin resistance represents a more general abnormality of cellular responsiveness in hypertension, we studied Mg(i) responses to nonhormonal signals such as hyperglycemia (15 mmol/L) and used (31)P-nuclear magnetic resonance (NMR) spectroscopy to measure Mg(i) in erythrocytes from normal (NL, n=14) and hypertensive (HTN, n=12) subjects before and 30, 60, 120, and 180 minutes after in vitro glucose incubations. Basal Mg(i) levels were significantly lower in HTN subjects than in NL subjects (169+/-10 versus 205+/-8 micromol.L(-1), P<0.01). In NL cells, hyperglycemia significantly lowered Mg(i), from 205+/-8 micromol.L(-1) (basal, T=0) to 181+/-8, 162+/-6, 152+/-7, and 175+/-9 micromol.L(-1) (T=30, 60, 120, and 180, respectively; P<0.005 versus T=0 at all times). In HTN cells, maximal Mg(i) responses to hyperglycemia were blunted, from 169+/-10 micromol.L(-1) (basal, T=0) to 170+/-11, 179+/-12, 181+/-14, and 173+/-15 micromol.L(-1) (T=30, 60, 120, and 180, respectively; P=NS versus T=0 at all times). For all subjects, Mg(i) responses to hyperglycemia were closely related to basal Mg(i) levels: the higher the Mg(i), the greater the response (n=26, r=0.620, P<0.001). Thus, (1) erythrocytes from hypertensive vis-à-vis normotensive subjects are resistant to the ionic effects of extracellular hyperglycemia on Mg(i) levels, and (2) cellular ionic responses to glucose depend on the basal Mg(i) environment. Altogether, these data support a role for altered extracellular glucose levels in regulating cellular magnesium metabolism and also suggest the importance of ionic factors in determining cellular responsiveness to nonhormonal as well as

Application of FrontPage 98 to the Development of Web Sites for the Science Division and the Center for the Advancement of Learning and Teaching (CALT) at Anne Arundel Community College.

ERIC Educational Resources Information Center

Bird, Bruce

This paper discusses the development of two World Wide Web sites at Anne Arundel Community College (Maryland). The criteria for the selection of hardware and software for Web site development that led to the decision to use Microsoft FrontPage 98 are described along with its major components and features. The discussion of the Science Division Web…

Optimum coagulant forecasting by modeling jar test experiments using ANNs

NASA Astrophysics Data System (ADS)

Haghiri, Sadaf; Daghighi, Amin; Moharramzadeh, Sina

2018-01-01

Currently, the proper utilization of water treatment plants and optimizing their use is of particular importance. Coagulation and flocculation in water treatment are the common ways through which the use of coagulants leads to instability of particles and the formation of larger and heavier particles, resulting in improvement of sedimentation and filtration processes. Determination of the optimum dose of such a coagulant is of particular significance. A high dose, in addition to adding costs, can cause the sediment to remain in the filtrate, a dangerous condition according to the standards, while a sub-adequate dose of coagulants can result in the reducing the required quality and acceptable performance of the coagulation process. Although jar tests are used for testing coagulants, such experiments face many constraints with respect to evaluating the results produced by sudden changes in input water because of their significant costs, long time requirements, and complex relationships among the many factors (turbidity, temperature, pH, alkalinity, etc.) that can influence the efficiency of coagulant and test results. Modeling can be used to overcome these limitations; in this research study, an artificial neural network (ANN) multi-layer perceptron (MLP) with one hidden layer has been used for modeling the jar test to determine the dosage level of used coagulant in water treatment processes. The data contained in this research have been obtained from the drinking water treatment plant located in Ardabil province in Iran. To evaluate the performance of the model, the mean squared error (MSE) and correlation coefficient (R2) parameters have been used. The obtained values are within an acceptable range that demonstrates the high accuracy of the models with respect to the estimation of water-quality characteristics and the optimal dosages of coagulants; so using these models will allow operators to not only reduce costs and time taken to perform experimental jar tests

Evaluation of radiation dose during the percutaneous angioplasty for arteriovenous shunt assembling

NASA Astrophysics Data System (ADS)

Ting, Chien-Yi; Wu, Wen-Shiann; Tang, Kuo-Ting; Wang, Hsin-Ell; Lin, Chun-Chih

2017-11-01

Percutaneous angioplasty (PTA) for dysfunctional hemodialysis is usually performed by radiologists, but not cardiologists, in Taiwan, so that the radiation dose in patients and physicians are usually unknown and related studies are rare. In this study, we are pioneering an investigation into the radiation dose in percutaneous angioplasty for arteriovenous shunt assembling and the effect of RADPAD device, a lead-free surgical drape containing Bi and Ba, on the decrease of a radiation dose in the non-targeted organs of the patient and also the operator. The radiation dose in a typical digital subtraction angiography (DSA) by the PTA protocol under a fixed field of view (FOV), was measured with optically simulated luminescent dosimeters arranged in a PIXY RS-102 anthropomorphic phantom. The results indicate that there is a significant dose reduction at the hands (0.022±0.002 mGy before treatment vs. 0.014±0.001 mGy after treatment; P=0.021), but not at the lens (0.027±0.003 mGy before treatment vs. 0.018±0.001 mGy after treatment; P=0.058), and the gonads (0.026±0.003 mGy before treatment vs. 0.020±0.001 mGy after treatment; P=0.058), of the cardiologist/operator after treatment with the RADPAD drape. At the patient's abdomen, the dose significantly decreased from 1.597±0.104 mGy to 0.031±0.002 mGy (P<0.001) after treated with the RADPAD shield. For the chest, lens and thyroid in the patient, the doses were respectively 0.154±0.100 mGy (compared to 0.049±0.001 mGy after treated with the RADPAD drape; P=0.0002), 0.066±0.001 mGy (compared to 0.021±0.001 mGy after the RADPAD treatment; P=0.009), and 0.208±0.002 mGy (compared to 0.042±0.003 mGy after shielded with the RADPAD drape; P<0.0001), which represents an apparent reduction in dose. However, no significant difference was found in the dose-area product between before (179.9±0.1mGy.cm2) and after (177.4±0.1mGy.cm2) the treatment (P=0.38). In conclusion, the RADPAD drape significantly reduced radiation

Influence of low versus moderate glycemic index of diet on substrate oxidation and energy expenditure during incremental exercise in endurance athletes: a randomized counterbalanced cross-over trial.

PubMed

Durkalec-Michalski, Krzysztof; Zawieja, Emilia Ewa; Zawieja, Bogna Ewa; Podgórski, Tomasz; Jurkowska, Dominika; Jeszka, Jan

2017-12-18

The study was aimed at assessing the influence of 3-week low glycemic index (LGI) versus moderate glycemic index (MGI) diet on substrate oxidation during incremental exercise. 17 runners completed two 3-week trials of either LGI or MGI diet in a randomised counterbalanced manner. Before and after each trial the incremental cycling test was performed. Metabolic alternations were observed only within tested diets and no significant differences in fat and carbohydrate (CHO) oxidation were found between MGI and LGI diets. Following MGI diet CHO oxidation rate increased. The AUC of fat oxidation decreased after both diets. Percent contribution of fat to energy yield declined, whereas contribution of CHO was augmented following MGI diet. This study indicates that the 3-week MGI diet increased the rate of carbohydrate oxidation during incremental cycling test and improved performance in acute intense exercise test, while both high-carbohydrate diets downregulated fat oxidation rate.

Electron spin resonance analysis of tooth enamel does not indicate exposures to large radiation doses in a large proportion of distally-exposed A-bomb survivors.

PubMed

Hirai, Yuko; Kodama, Yoshiaki; Cullings, Harry M; Miyazawa, Chuzo; Nakamura, Nori

2011-01-01

The atomic bombs in Hiroshima and Nagasaki led to two different types of radiation exposure; one was direct and brief and the other was indirect and persistent. The latter (so-called exposure to residual radiation) resulted from the presence of neutron activation products in the soil, or from fission products present in the fallout. Compared with the doses from direct exposures, estimations of individual doses from residual radiation have been much more complicated, and estimates vary widely among researchers. The present report bases its conclusions on radiation doses recorded in tooth enamel from survivors in Hiroshima. Those survivors were present at distances of about 3 km or greater from the hypocenter at the time of the explosion, and have DS02 estimated doses (direct exposure doses) of less than 5 mGy (and are regarded as control subjects). Individual doses were estimated by measuring CO(2)(-) radicals in tooth enamel with the electron spin resonance (ESR; or electron paramagnetic resonance, EPR) method. The results from 56 molars donated by 49 survivors provided estimated doses which vary from -200 mGy to 500 mGy, and the median dose was 17 mGy (25% and 75% quartiles are -54 mGy and 137 mGy, respectively) for the buccal parts and 13 mGy (25% and 75% quartiles: -49 mGy and 87 mGy, respectively) for the lingual parts of the molars. Three molars had ESR-estimated doses of 300 to 400 mGy for both the buccal and lingual parts, which indicates possible exposures to excess doses of penetrating radiation, although the origin of such radiation remains to be determined. The results did not support claims that a large fraction of distally-exposed survivors received large doses (e.g. 1 Gy) of external penetrating radiation resulting from residual radiation.

Absorbed dose thresholds and absorbed dose rate limitations for studies of electron radiation effects on polyetherimides

NASA Technical Reports Server (NTRS)

Long, Edward R., Jr.; Long, Sheila Ann T.; Gray, Stephanie L.; Collins, William D.

1989-01-01

The threshold values of total absorbed dose for causing changes in tensile properties of a polyetherimide film and the limitations of the absorbed dose rate for accelerated-exposure evaluation of the effects of electron radiation in geosynchronous orbit were studied. Total absorbed doses from 1 kGy to 100 MGy and absorbed dose rates from 0.01 MGy/hr to 100 MGy/hr were investigated, where 1 Gy equals 100 rads. Total doses less than 2.5 MGy did not significantly change the tensile properties of the film whereas doses higher than 2.5 MGy significantly reduced elongation-to-failure. There was no measurable effect of the dose rate on the tensile properties for accelerated electron exposures.

Gaydar, Marriage, and Rip-Roaring Homosexuals: Discourses About Homosexuality in Dear Abby and Ann Landers Advice Columns, 1967-1982.

PubMed

Johnson, Patrick M; Holmes, Kwame A

2017-12-04

Over the past 70 years, the history of acceptance of the lesbian, gay and bisexual (LGB) community within the United States has seen much change and fluctuation. One of the places that this dialogue has been preserved is through the syndicated advice columns of Dear Abby and Ann Landers, in which individuals in the United States were writing in for advice to deal with their anxiety over a newly emerging and highly visible new community of individuals once considered to be mentally ill and dangerous. Using discourse analysis, this article traces the evolution of public and scientific opinions about the LGBT community during the years leading up to the Stonewall riots all the way to right before the AIDs epidemic. This analysis sheds light on several moral panics that emerged regarding this newly visible population, especially in regard to disturbances within the domestic sphere and a stigmatization of bisexuality.

Bulgarian experience in the establishment of reference dose levels and implementation of a quality control system in diagnostic radiology.

PubMed

Vassileva, J; Dimov, A; Slavchev, A; Karadjov, A

2005-01-01

Results from a Bulgarian patient dose survey in diagnostic radiology are presented. Reference levels for entrance surface dose (ESD) were 0.9 mGy for chest radiography (PA), 30 mGy for lumbar spine (Lat), 10 mGy for pelvis, 5 mGy for skull (AP), 3 mGy for skull (Lat) and 13 mGy for mammography. Quality control (QC) programmes were proposed for various areas of diagnostic radiology. Film processing QC warranted special attention. Proposed QC programmes included parameters to be tested, level of expertise needed and two action levels: remedial and suspension. Programmes were tested under clinical conditions to assess initial results and draw conclusions for further QC system development. On the basis of international experience, measurement protocols were developed for all parameters tested. QC equipment was provided as part of the PHARE project. A future problem for QC programme implementation may be the small number of medical physics experts in diagnostic radiology.

Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study.

PubMed

Maghsoudi, M; Ghaedi, M; Zinali, A; Ghaedi, A M; Habibi, M H

2015-01-05

In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R(2)) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation. Copyright © 2014 Elsevier B.V. All rights reserved.

Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study

NASA Astrophysics Data System (ADS)

Maghsoudi, M.; Ghaedi, M.; Zinali, A.; Ghaedi, A. M.; Habibi, M. H.

2015-01-01

In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R2) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation.

DNA alterations and effects on growth and reproduction in Daphnia magna during chronic exposure to gamma radiation over three successive generations.

PubMed

Parisot, Florian; Bourdineaud, Jean-Paul; Plaire, Delphine; Adam-Guillermin, Christelle; Alonzo, Frédéric

2015-06-01

This study examined chronic effects of external Cs-137 gamma radiation on Daphnia magna exposed over three successive generations (F0, F1 and F2) to environmentally relevant dose rates (ranging from 0.007 to 35.4 mGy h(-1)). Investigated endpoints included survival, growth, reproduction and DNA alterations quantified using random-amplified polymorphic DNA polymerase chain reaction (RAPD-PCR). Results demonstrated that radiation effects on survival, growth and reproduction increased in severity from generation F0 to generation F2. Mortality after 21 days at 35.4 mGy h(-1) increased from 20% in F0 to 30% in F2. Growth was affected by a slight reduction in maximum length at 35.4 mGy h(-1) in F0 and by reductions of 5 and 13% in growth rate, respectively, at 4.70 and 35.4 mGy h(-1) in F2. Reproduction was affected by a reduction of 19% in 21 day-fecundity at 35.4 mGy h(-1) in F0 and by a delay of 1.9 days in brood release as low as 0.070 mGy h(-1) in F2. In parallel, DNA alterations became significant at decreasing dose rates over the course of F0 (from 4.70 mGy h(-1) at hatching to 0.007 mGy h(-1) after ∼21 days) and from F0 to F2 (0.070 mGy h(-1) at hatching to 0.007 mGy h(-1) after ∼21 days), demonstrating their rapid accumulation in F0 daphnids and their transmission to offspring generations. Transiently more efficient DNA repair leading to some recovery at the organism level was suggested in F1, with no effect on survival, a slight reduction of 12% in 21 day-fecundity at 35.4 mGy h(-1) and DNA alterations significant at highest dose rates only. The study improved our understanding of long term responses to low doses of radiation at the molecular and organismic levels in a non-human species for a better radioprotection of aquatic ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.

SU-E-I-28: Evaluating the Organ Dose From Computed Tomography Using Monte Carlo Calculations

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

Ono, T; Araki, F

Purpose: To evaluate organ doses from computed tomography (CT) using Monte Carlo (MC) calculations. Methods: A Philips Brilliance CT scanner (64 slice) was simulated using the GMctdospp (IMPS, Germany) based on the EGSnrc user code. The X-ray spectra and a bowtie filter for MC simulations were determined to coincide with measurements of half-value layer (HVL) and off-center ratio (OCR) profile in air. The MC dose was calibrated from absorbed dose measurements using a Farmer chamber and a cylindrical water phantom. The dose distribution from CT was calculated using patient CT images and organ doses were evaluated from dose volume histograms.more » Results: The HVLs of Al at 80, 100, and 120 kV were 6.3, 7.7, and 8.7 mm, respectively. The calculated HVLs agreed with measurements within 0.3%. The calculated and measured OCR profiles agreed within 3%. For adult head scans (CTDIvol) =51.4 mGy), mean doses for brain stem, eye, and eye lens were 23.2, 34.2, and 37.6 mGy, respectively. For pediatric head scans (CTDIvol =35.6 mGy), mean doses for brain stem, eye, and eye lens were 19.3, 24.5, and 26.8 mGy, respectively. For adult chest scans (CTDIvol=19.0 mGy), mean doses for lung, heart, and spinal cord were 21.1, 22.0, and 15.5 mGy, respectively. For adult abdominal scans (CTDIvol=14.4 mGy), the mean doses for kidney, liver, pancreas, spleen, and spinal cord were 17.4, 16.5, 16.8, 16.8, and 13.1 mGy, respectively. For pediatric abdominal scans (CTDIvol=6.76 mGy), mean doses for kidney, liver, pancreas, spleen, and spinal cord were 8.24, 8.90, 8.17, 8.31, and 6.73 mGy, respectively. In head scan, organ doses were considerably different from CTDIvol values. Conclusion: MC dose distributions calculated by using patient CT images are useful to evaluate organ doses absorbed to individual patients.« less

SU-F-207-14: Low Contrast Detectability (LCD) at Different Diagnostic Reference Levels for Adult Abdominal CT Procedures

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

Mahmood, U; Erdi, Y

2015-06-15

Purpose Using diagnostic reference levels (DRL) to optimize CT protocols has potential to reduce radiation dose and meet regulatory requirements. However, DRL’s tend to be misconstrued as dose limits, are typically designed for specific patient populations, and are assumed to have acceptable image quality (AIQ) associated with them. To determine the image quality that is associated with established DRL’s for adult abdominal CT studies, a LCD phantom study was employed. Methods: A CT phantom (CIRS) containing three columns of 7 spherical targets, ranging from 10mm to 2.4 mm, that are 5, 10, and 20 HU below the background (HUBB) matrixmore » was scanned with a GE HD750 64 slice scanner. The phantom was scanned at the NEXT 2006 25th CTDIvol of 12 mGy, the NCRP 172 achievable dose (AD) CTDIvol of 17 mGy and 75th CTDIvol of 25 mGy and at the ACR recommended CTDIvol of 25 mGy. It was also scanned at a CTDIvol 20% greater than the AD at 20 mGy and the ACR maximum threshold of 30 mGy. Results: At the NEXT 2006 25th percentile CTDIvol of 12 mGy, a 6.3 mm low contrast lesion was detectable in the 20 HUBB; 6.3 mm in the 10 HUBB and 10 mm in the 5 HUBB column. Increasing the CTDIvol to the NCRP 172 AD of 17 mGy, an additional 4.8 mm lesion was visualized in the 20 HUBB column. At 20 mGy, an additional 4.8 mm lesion was detectable in the 10 HUBB column. No further lesions were visible between 20 and 30 mGy. However, conspicuity of all lesions increased with each additional step up in CTDI. Conclusion: Optimizing radiation dose to achieve AIQ is a critical aspect of any dose optimization committee. Hence, judicious monitoring of radiation exposure to patients has to be balanced with diagnostic image quality.« less

A novel and generalized approach in the inversion of geoelectrical resistivity data using Artificial Neural Networks (ANN)

NASA Astrophysics Data System (ADS)

Raj, A. Stanley; Srinivas, Y.; Oliver, D. Hudson; Muthuraj, D.

2014-03-01

The non-linear apparent resistivity problem in the subsurface study of the earth takes into account the model parameters in terms of resistivity and thickness of individual subsurface layers using the trained synthetic data by means of Artificial Neural Networks (ANN). Here we used a single layer feed-forward neural network with fast back propagation learning algorithm. So on proper training of back propagation networks it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data with reference to the synthetic data trained in the appropriate network. During training, the weights and biases of the network are iteratively adjusted to make network performance function level more efficient. On adequate training, errors are minimized and the best result is obtained using the artificial neural networks. The network is trained with more number of VES data and this trained network is demonstrated by the field data. The accuracy of inversion depends upon the number of data trained. In this novel and specially designed algorithm, the interpretation of the vertical electrical sounding has been done successfully with the more accurate layer model.

The Anne Frank Haven: A case of an alternative educational program in an integrative Kibbutz setting

NASA Astrophysics Data System (ADS)

Ben-Peretz, Miriam; Giladi, Moshe; Dror, Yuval

1992-01-01

The essential features of the programme of the Anne Frank Haven are the complete integration of children from low SES and different cultural backgrounds with Kibbutz children; a holistic approach to education; and the involvement of the whole community in an "open" residential school. After 33 years, it is argued that the experiment has proved successful in absorbing city-born youth in the Kibbutz, enabling at-risk populations to reach significant academic achievements, and ensuring their continued participation in the dominant culture. The basic integration model consists of "layers" of concentric circles, in dynamic interaction. The innermost circle is the class, the learning community. The Kibbutz community and the foster parents form a supportive, enveloping circle, which enables students to become part of the outer community and to intervene in it. A kind of meta-environment, the inter-Kibbutz partnership and the Israeli educational system, influence the program through decision making and guidance. Some of the principles of the Haven — integration, community involvement, a year's induction for all new students, and open residential settings — could be useful for cultures and societies outside the Kibbutz. The real "secret" of success of an alternative educational program is the dedicated, motivated and highly trained staff.

Hourly predictive Levenberg-Marquardt ANN and multi linear regression models for predicting of dew point temperature

NASA Astrophysics Data System (ADS)

Zounemat-Kermani, Mohammad

2012-08-01

In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.

Effect of filter on average glandular dose and image quality in digital mammography

NASA Astrophysics Data System (ADS)

Songsaeng, C.; Krisanachinda, A.; Theerakul, K.

2016-03-01

To determine the average glandular dose and entrance surface air kerma in both phantoms and patients to assess image quality for different target-filters (W/Rh and W/Ag) in digital mammography system. The compressed breast thickness, compression force, average glandular dose, entrance surface air kerma, peak kilovoltage and tube current time were recorded and compared between W/Rh and W/Ag target filter. The CNR and the figure of merit were used to determine the effect of target filter on image quality. The mean AGD of the W/Rh target filter was 1.75 mGy, the mean ESAK was 6.67 mGy, the mean CBT was 54.1 mm, the mean CF was 14 1bs. The mean AGD of W/Ag target filter was 2.7 mGy, the mean ESAK was 12.6 mGy, the mean CBT was 75.5 mm, the mean CF was 15 1bs. In phantom study, the AGD was 1.2 mGy at 4 cm, 3.3 mGy at 6 cm and 3.83 mGy at 7 cm thickness. The FOM was 24.6, CNR was 9.02 at thickness 6 cm. The FOM was 18.4, CNR was 8.6 at thickness 7 cm. The AGD from Digital Mammogram system with W/Rh of thinner CBT was lower than the AGD from W/Ag target filter.

Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

PubMed

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. Copyright © 2014 Elsevier Inc. All rights reserved.

3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

NASA Astrophysics Data System (ADS)

Saeed, R. A.; Galybin, A. N.; Popov, V.

2013-01-01

This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

Entrance radiation doses during paediatric cardiac catheterisations performed for diagnosis or the treatment of congenital heart disease.

PubMed

Papadopoulou, D; Yakoumakis, Em; Sandilos, P; Thanopoulos, V; Makri, Tr; Gialousis, G; Houndas, D; Yakoumakis, N; Georgiou, Ev

2005-01-01

The purpose of this study was to estimate the radiation exposure of children, during cardiac catheterisations for the diagnosis or treatment of congenital heart disease. Radiation doses were estimated for 45 children aged from 1 d to 13 y old. Thermoluminescent dosemeters (TLDs) were used to estimate the posterior entrance dose (DP), the lateral entrance dose (DLAT), the thyroid dose and the gonads dose. A dose-area product (DAP) meter was also attached externally to the tube of the angiographic system and gave a direct value in mGy cm2 for each procedure. Posterior and lateral entrance dose values during cardiac catheterisations ranged from 1 to 197 mGy and from 1.1 to 250.3 mGy, respectively. Radiation exposure to the thyroid and the gonads ranged from 0.3 to 8.4 mGy to 0.1 and 0.7 mGy, respectively. Finally, the DAP meter values ranged between 360 and 33,200 mGy cm2. Radiation doses measured in this study are comparable with those reported to previous studies. Moreover, strong correlation was found between the DAP values and the entrance radiation dose measured with TLDs.

SU-F-I-46: Optimizing Dose Reduction in Adult Head CT Protocols While Maintaining Image Quality in Postmortem Head Scans

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

Lipnharski, I; Carranza, C; Quails, N

Purpose: To optimize adult head CT protocol by reducing dose to an appropriate level while providing CT images of diagnostic quality. Methods: Five cadavers were scanned from the skull base to the vertex using a routine adult head CT protocol (120 kVp, 270 mA, 0.75 s rotation, 0.5 mm × 32 detectors, 70.8 mGy CTDIvol) followed by seven reduced-dose protocols with varying combinations of reduced tube current, reduced rotation time, and increased detectors with CTDIvol ranging from 38.2 to 65.6 mGy. Organ doses were directly measured with 21 OSL dosimeters placed on the surface and implanted in the head bymore » a neurosurgeon. Two neuroradiologists assessed grey-white matter differentiation, fluid space, ventricular size, midline shift, brain mass, edema, ischemia, and skull fractures on a three point scale: (1) Unacceptable, (2) Borderline Acceptable, and (3) Acceptable. Results: For the standard scan, doses to the skin, lens of the eye, salivary glands, thyroid, and brain were 37.55 mGy, 49.65 mGy, 40.67 mGy, 4.63 mGy, and 27.33 mGy, respectively. Two cadavers had cerebral edema due to changing dynamics of postmortem effects, causing the grey-white matter differentiation to appear less distinct. Two cadavers with preserved grey-white matter received acceptable scores for all image quality features for the protocol with a CTDIvol of 57.3 mGy, allowing organ dose savings ranging from 34% to 45%. One cadaver allowed for greater dose reduction for the protocol with a CTDIvol of 42 mGy. Conclusion: Efforts to optimize scan protocol should consider both dose and clinical image quality. This is made possible with postmortem subjects, whose brains are similar to patients, allowing for an investigation of ideal scan parameters. Radiologists at our institution accepted scan protocols acquired with lower scan parameters, with CTDIvol values closer to the American College of Radiology’s (ACR) Achievable Dose level of 57 mGy.« less

Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

NASA Astrophysics Data System (ADS)

Harun, R.

2013-05-01

This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the

Atrazine is primarily responsible for the toxicity of long-term exposure to a combination of atrazine and inorganic arsenic in the nigrostriatal system of the albino rat.

PubMed

Bardullas, Ulises; Giordano, Magda; Rodríguez, Verónica Mireya

2013-01-01

Chronic and simultaneous exposure to a variety of chemicals present in the environment is an unavoidable fact. However, given the complexity of studying chemical mixtures, most toxicological studies have focused on the effects of short-term exposure to single substances. The aim of this study was to evaluate the effects on the nigrostriatal system of the chronic, simultaneous exposure to two widely distributed substances that have been identified as potential dopaminergic system toxicants, inorganic arsenic (iAs) and atrazine (ATR). Six groups of rats were treated daily for one year with atrazine (10mg ATR/kg), inorganic arsenic (0.5 or 50mgiAs/L of drinking water), or a combination of ATR+0.5mgiAs/L or ATR+50mgiAs/L. The 50mgiAs/L group showed locomotor hypoactivity, while all treatments decreased motor coordination in contrast no effects of treatment were found on the place and response learning tasks. Regarding markers for liver and muscle damage, there were no differences between groups in creatine kinase (CK) or aspartate transaminase (AST) activities, while decreases in lactate dehydrogenase (LDH) levels were found in some exposed groups. The striatal DA content was significantly reduced in ATR, 0.5mgiAs/L, ATR+0.5mgiAs/L, and ATR+50mgiAs/L groups, in comparison to the control group. The number of mesencephalic tyrosine hydroxylase positive cells decreased in the ATR and ATR+0.5mgiAs/L groups compared to the control. In contrast, immunoreactivity to cytochrome oxidase was reduced compared to the control in all treated groups, except for the group treated with 0.5iAsmg alone. Our results indicate that ATR has deleterious effects on dopaminergic neurons and that the combination of ATR and iAs does not exacerbate these effects. © 2013 Elsevier Inc. All rights reserved.

Maps and seismic profiles showing geology of the inner continental shelf, Cape Ann, Massachusetts to New Hampshire

USGS Publications Warehouse

Oldale, R.N.; Wommack, L.E.

1987-01-01

Early studies in the western Gulf of Maine have outlined the general geology and geologic history of the region. Seismic-reflection data have defined the major stratigraphic units and unconformities (Oldale and Uchupi, 1970; Ballard and Uchupi, 1972; Oldale and others, 1973). Two long cores provided information on the glacial and postglacial sediments in the deep offshore basins (Tucholke and Hollister, 1973). Generalized bottom-sediment type and distribution were determined by Schlee and others (1973) and by Folger and others (1975). Investigations on land, which have provided information on the late Quaternary history of the offshore area, include descriptions of ice retreat and marine submergence (Bloom, 1963; Smith, 1982; Stone and Peper, 1982; Thompson, 1982). Radiocarbon dates from coastal marsh peats have established the middle to late Holocene sea-level-rise history (McIntire and Morgan, 1964; Keene, 1971). Submarine moraincs that recently were recognized off Cape Ann provide additional information on the nature and chronology of ice retreat (Oldale, 1985a). A submerged delta of the Merrimack River and a submerged barrier spit have been used to establish an early IIolocene lowstand of 588 level of about 50 meters (m) below present sea level (Oldale and others, 1983; Oldale, 1985b).

Investigation of LiF, Mg and Ti (TLD-100) Reproducibility.

PubMed

Sadeghi, M; Sina, S; Faghihi, R

2015-12-01

LiF, Mg and Ti cubical TLD chips (known as TLD-100) are widely used for dosimetry purposes. The repeatability of TL dosimetry is investigated by exposing them to doses of (81, 162 and 40.5 mGy) with 662keV photons of Cs-137. A group of 40 cubical TLD chips was randomly selected from a batch and the values of Element Correction Coefficient (ECC) were obtained 4 times by irradiating them to doses of 81 mGy (two times), 162mGy and 40.5mGy. Results of this study indicate that the average reproducibility of ECC calculation for 40 TLDs is 1.5%, while these values for all chips do not exceed 5%.

Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

PubMed

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Effects of Chronic Low-Dose Radiation on Human Neural Progenitor Cells

NASA Astrophysics Data System (ADS)

Katsura, Mari; Cyou-Nakamine, Hiromasa; Zen, Qin; Zen, Yang; Nansai, Hiroko; Amagasa, Shota; Kanki, Yasuharu; Inoue, Tsuyoshi; Kaneki, Kiyomi; Taguchi, Akashi; Kobayashi, Mika; Kaji, Toshiyuki; Kodama, Tatsuhiko; Miyagawa, Kiyoshi; Wada, Youichiro; Akimitsu, Nobuyoshi; Sone, Hideko

2016-01-01

The effects of chronic low-dose radiation on human health have not been well established. Recent studies have revealed that neural progenitor cells are present not only in the fetal brain but also in the adult brain. Since immature cells are generally more radiosensitive, here we investigated the effects of chronic low-dose radiation on cultured human neural progenitor cells (hNPCs) derived from embryonic stem cells. Radiation at low doses of 31, 124 and 496 mGy per 72 h was administered to hNPCs. The effects were estimated by gene expression profiling with microarray analysis as well as morphological analysis. Gene expression was dose-dependently changed by radiation. By thirty-one mGy of radiation, inflammatory pathways involving interferon signaling and cell junctions were altered. DNA repair and cell adhesion molecules were affected by 124 mGy of radiation while DNA synthesis, apoptosis, metabolism, and neural differentiation were all affected by 496 mGy of radiation. These in vitro results suggest that 496 mGy radiation affects the development of neuronal progenitor cells while altered gene expression was observed at a radiation dose lower than 100 mGy. This study would contribute to the elucidation of the clinical and subclinical phenotypes of impaired neuronal development induced by chronic low-dose radiation.

National reference doses for dental cephalometric radiography.

PubMed

Holroyd, J R

2011-12-01

Diagnostic reference levels (DRLs) are an important tool in the optimisation of clinical radiography. Although national DRLs are provided for many diagnostic procedures including dental intra-oral radiography, there are currently no national DRLs set for cephalometric radiography. In the absence of formal national DRLs, the Health Protection Agency (HPA) has previously published National Reference Doses (NRDs) covering a wide range of diagnostic X-ray examinations. The aim of this study was to determine provisional NRDs for cephalometric radiography. Measurements made by the Dental X-ray Protection Service (DXPS) of the HPA, as part of the cephalometric X-ray equipment testing service provided to dentists and dental trade companies throughout the UK, were used to derive provisional NRDs. Dose-area product measurements were made on 42 X-ray sets. Third quartile dose-area product values for adult and child lateral cephalometric radiography were found to be 41 mGy cm² and 25 mGy cm², respectively, with individual measurements ranging from 3 mGy cm² to 108 mGy cm². This report proposes provisional NRDs of 40 mGy cm² and 25 mGy cm² for adult and child lateral cephalometric radiographs, respectively; these doses could be considered by employers when establishing their local DRLs.

Radiation exposure of contrast-enhanced spectral mammography compared with full-field digital mammography.

PubMed

Jeukens, Cécile R L P N; Lalji, Ulrich C; Meijer, Eduard; Bakija, Betina; Theunissen, Robin; Wildberger, Joachim E; Lobbes, Marc B I

2014-10-01

Contrast-enhanced spectral mammography (CESM) shows promising initial results but comes at the cost of increased dose as compared with full-field digital mammography (FFDM). We aimed to quantitatively assess the dose increase of CESM in comparison with FFDM. Radiation exposure-related data (such as kilovoltage, compressed breast thickness, glandularity, entrance skin air kerma (ESAK), and average glandular dose (AGD) were retrieved for 47 CESM and 715 FFDM patients. All examinations were performed on 1 mammography unit. Radiation dose values reported by the unit were validated by phantom measurements. Descriptive statistics of the patient data were generated using a statistical software package. Dose values reported by the mammography unit were in good qualitative agreement with those of phantom measurements. Mean ESAK was 10.5 mGy for a CESM exposure and 7.46 mGy for an FFDM exposure. Mean AGD for a CESM exposure was 2.80 mGy and 1.55 mGy for an FFDM exposure. Compared with our institutional FFDM, the AGD of a single CESM exposure is increased by 1.25 mGy (+81%), whereas ESAK is increased by 3.07 mGy (+41%). Dose values of both techniques meet the recommendations for maximum dose in mammography.

Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh.

PubMed

Rahman, M Tauhid Ur; Tabassum, Faheemah; Rasheduzzaman, Md; Saba, Humayra; Sarkar, Lina; Ferdous, Jannatul; Uddin, Syed Zia; Zahedul Islam, A Z M

2017-10-17

Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. "Bare lands" decreased by 21% being occupied by other land uses, especially by "shrimp farms." Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in "settlement" area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy

Quantitative assessment of the cataractogenic potential of very low doses of neutrons

NASA Technical Reports Server (NTRS)

Worgul, B. V.; Medvedovsky, C.; Huang, Y.; Marino, S. A.; Randers-Pehrson, G.; Brenner, D. J.

1996-01-01

We report on the prevalence and relative biological effectiveness (RBE) for various stages of lens opacification in rats induced by very low doses (2 to 250 mGy) of medium-energy (440 keV) neutrons, compared to those for X rays. Neutron doses were delivered either in a single fraction or in four separate fractions and the irradiated animals were followed for over 100 weeks. At the highest observed dose (250 mGy) and at early observation times, there was evidence of an inverse dose-rate effect; i.e., a fractionated exposure was more potent than a single exposure. Neutron RBEs relative to X rays were estimated using a non-parametric technique. The results were only weakly dependent on time postirradiation. At 30 weeks, for example, 80% confidence intervals for the RBE of acutely delivered neutrons relative to X rays were 8-16 at 250 mGy, 10-20 at 50 mGy, 50-100 at 10 mGy and 250-500 at 2 mGy. The results are consistent with the estimated neutron RBEs in Japanese A-bomb survivors, though broad confidence bounds are present in the Japanese results. Our findings are also consistent with data reported earlier for cataractogenesis induced by heavy ions in rats, mice, and rabbits. We conclude from these results that, at very low doses (<10 mGy), the RBE for neutron-induced cataractogenesis is considerably larger than the RBE of 20 commonly used, and use of a significantly larger value for calculating equivalent dose would be prudent.

Kilovoltage cone-beam CT imaging dose during breast radiotherapy: A dose comparison between a left and right breast setup

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

Quinn, Alexandra, E-mail: Alexandra.quinn@health.nsw.gov.au; Centre for Medical Radiation Physics, University of Wollongong, NSW; Liverpool and Macarthur Cancer Therapy Centres, NSW

2014-07-01

The purpose of this study was to investigate the delivered dose from a kilovoltage cone-beam computed tomography (kV-CBCT) acquired in breast treatment position for a left and right breast setup. The dose was measured with thermoluminescent dosimeters positioned within a female anthropomorphic phantom at organ locations. Imaging was performed on an Elekta Synergy XVI system with the phantom setup on a breast board. The image protocol involved 120 kVp, 140 mAs, and a 270° arc rotation clockwise 0° to 270° for the left breast setup and 270° to 180° for the right breast setup (maximum arc rotations possible). The dosemore » delivered to the left breast, right breast, and heart was 5.1 mGy, 3.9 mGy, and 4.0 mGy for the left breast setup kV-CBCT, and 6.4 mGy, 6.0 mGy, and 4.8 mGy for the right breast setup kV-CBCT, respectively. The rotation arc of the kV-CBCT influenced the dose delivered, with the right breast setup kV-CBCT found to deliver a dose of up to 4 mGy or 105% higher to the treated breast′s surface in comparison with the left breast setup. This is attributed to the kV-CBCT source being more proximal to the anterior of the phantom for a right breast setup, whereas the source is more proximal to the posterior of the patient for a left-side scan.« less

Investigation of LiF, Mg and Ti (TLD-100) Reproducibility

PubMed Central

Sadeghi, M.; Sina, S.; Faghihi, R.

2015-01-01

LiF, Mg and Ti cubical TLD chips (known as TLD-100) are widely used for dosimetry purposes. The repeatability of TL dosimetry is investigated by exposing them to doses of (81, 162 and 40.5 mGy) with 662keV photons of Cs-137. A group of 40 cubical TLD chips was randomly selected from a batch and the values of Element Correction Coefficient (ECC) were obtained 4 times by irradiating them to doses of 81 mGy (two times), 162mGy and 40.5mGy. Results of this study indicate that the average reproducibility of ECC calculation for 40 TLDs is 1.5%, while these values for all chips do not exceed 5%. PMID:26688801

Cultural differences in postnatal quality of life among German-speaking women - a prospective survey in two countries.

PubMed

Grylka-Baeschlin, Susanne; van Teijlingen, Edwin; Gross, Mechthild M

2014-08-15

Assessment of quality of life after childbirth is an important health-outcome measurement for new mothers and is of special interest in midwifery. The Mother-Generated Index (MGI) is a validated instrument to assess postnatal quality of life. The tool has not been applied for making a cross-cultural comparison before. This study investigated (a) responses to the MGI in German-speaking women in Germany and Switzerland; and (b) associations between MGI scores on the one hand and maternity and midwifery care on the other. A two-stage survey was conducted in two rural hospitals 10 km apart, on opposite sides of the German-Swiss border. The questionnaires included the MGI and questions on socio-demographics, physical and mental health and maternity care, and were distributed during the first days after birth and six weeks postpartum. Parametric and non-parametric tests were computed with the statistical programme SPSS. A total of 129 questionnaires were returned an average of three days after birth and 83 in the follow-up after seven weeks. There were no statistically significant differences in the MGI scores between the German and the Swiss women (p = 0.22). Significantly more favourable MGI scores were found associated with more adequate information during pregnancy (p = 0.02), a more satisfactory birth experience (p < .01), epidural anaesthesia (p < 0.01), more information (p = 0.01) and better support (p = 0.02) during the time in hospital and less disturbed sleep (p < 0.01). Significantly lower MGI scores were associated with the presence of a private doctor during birth (p = 0.01) and with exclusive breastfeeding during the first postnatal days (p = 0.04). The MGI scores of these German-speaking women were higher than those in other studies reported previously. Thus the tool may be able to detect differences in postnatal quality of life among women with substantially divergent cultural backgrounds. Shortcomings in maternity and midwifery care were detected, as for

AI-based (ANN and SVM) statistical downscaling methods for precipitation estimation under climate change scenarios

NASA Astrophysics Data System (ADS)

Mehrvand, Masoud; Baghanam, Aida Hosseini; Razzaghzadeh, Zahra; Nourani, Vahid

2017-04-01

Since statistical downscaling methods are the most largely used models to study hydrologic impact studies under climate change scenarios, nonlinear regression models known as Artificial Intelligence (AI)-based models such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used to spatially downscale the precipitation outputs of Global Climate Models (GCMs). The study has been carried out using GCM and station data over GCM grid points located around the Peace-Tampa Bay watershed weather stations. Before downscaling with AI-based model, correlation coefficient values have been computed between a few selected large-scale predictor variables and local scale predictands to select the most effective predictors. The selected predictors are then assessed considering grid location for the site in question. In order to increase AI-based downscaling model accuracy pre-processing has been developed on precipitation time series. In this way, the precipitation data derived from various GCM data analyzed thoroughly to find the highest value of correlation coefficient between GCM-based historical data and station precipitation data. Both GCM and station precipitation time series have been assessed by comparing mean and variances over specific intervals. Results indicated that there is similar trend between GCM and station precipitation data; however station data has non-stationary time series while GCM data does not. Finally AI-based downscaling model have been applied to several GCMs with selected predictors by targeting local precipitation time series as predictand. The consequences of recent step have been used to produce multiple ensembles of downscaled AI-based models.

Biotreatment of zinc-containing wastewater in a sulfidogenic CSTR: Performance and artificial neural network (ANN) modelling studies.

PubMed

Sahinkaya, Erkan

2009-05-15

Sulfidogenic treatment of sulfate (2-10g/L) and zinc (65-677mg/L) containing simulated wastewater was studied in a mesophilic (35 degrees C) CSTR. Ethanol was supplemented (COD/sulfate=0.67) as carbon and energy source for sulfate-reducing bacteria (SRB). The robustness of the system was studied by increasing Zn, COD and sulfate loadings. Sulfate removal efficiency, which was 70% at 2g/L feed sulfate concentration, steadily decreased with increasing feed sulfate concentration and reached 40% at 10g/L. Over 99% Zn removal was attained due to the formation of zinc-sulfide precipitate. COD removal efficiency at 2g/L feed sulfate concentration was over 94%, whereas, it steadily decreased due to the accumulation of acetate at higher loadings. Alkalinity produced from acetate oxidation increased wastewater pH remarkably when feed sulfate concentration was 5g/L or lower. Electron flow from carbon oxidation to sulfate reduction averaged 83+/-13%. The rest of the electrons were most likely coupled with fermentative reactions as the amount of methane production was insignificant. The developed ANN model was very successful as an excellent to reasonable match was obtained between the measured and the predicted concentrations of sulfate (R=0.998), COD (R=0.993), acetate (R=0.976) and zinc (R=0.827) in the CSTR effluent.

SU-E-I-32: Benchmarking Head CT Doses: A Pooled Vs. Protocol Specific Analysis of Radiation Doses in Adult Head CT Examinations

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

Fujii, K; UCLA School of Medicine, Los Angeles, CA; Bostani, M

Purpose: The aim of this study was to collect CT dose index data from adult head exams to establish benchmarks based on either: (a) values pooled from all head exams or (b) values for specific protocols. One part of this was to investigate differences in scan frequency and CT dose index data for inpatients versus outpatients. Methods: We collected CT dose index data (CTDIvol) from adult head CT examinations performed at our medical facilities from Jan 1st to Dec 31th, 2014. Four of these scanners were used for inpatients, the other five were used for outpatients. All scanners used Tubemore » Current Modulation. We used X-ray dose management software to mine dose index data and evaluate CTDIvol for 15807 inpatients and 4263 outpatients undergoing Routine Brain, Sinus, Facial/Mandible, Temporal Bone, CTA Brain and CTA Brain-Neck protocols, and combined across all protocols. Results: For inpatients, Routine Brain series represented 84% of total scans performed. For outpatients, Sinus scans represented the largest fraction (36%). The CTDIvol (mean ± SD) across all head protocols was 39 ± 30 mGy (min-max: 3.3–540 mGy). The CTDIvol for Routine Brain was 51 ± 6.2 mGy (min-max: 36–84 mGy). The values for Sinus were 24 ± 3.2 mGy (min-max: 13–44 mGy) and for Facial/Mandible were 22 ± 4.3 mGy (min-max: 14–46 mGy). The mean CTDIvol for inpatients and outpatients was similar across protocols with one exception (CTA Brain-Neck). Conclusion: There is substantial dose variation when results from all protocols are pooled together; this is primarily a function of the differences in technical factors of the protocols themselves. When protocols are analyzed separately, there is much less variability. While analyzing pooled data affords some utility, reviewing protocols segregated by clinical indication provides greater opportunity for optimization and establishing useful benchmarks.« less

TH-AB-207A-03: Skin Dose to Patients Receiving Multiple CTA and CT Exams of the Head

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

Nawfel, RD; Young, G

Purpose: To measure patient skin dose from CT angiography (CTA) and CT exams of the head, and determine if patients having multiple exams could receive cumulative doses that approach or exceed deterministic thresholds. Methods: This study was HIPAA compliant and conducted with IRB approval. Patient skin doses were measured over a 4 month period using nanoDot OSL dosimeters placed on the head of 52 patients for two CT scanners. On each scanner, 26 patients received CT exams (scanner 1: 10 females, 16 males, mean age 64.2 years; scanner 2: 18 females, 8 males, mean age 61.2 years). CT exam dosemore » metrics, CTDIvol and dose-length product (DLP) were recorded for each exam. Additionally, skin dose was measured on an acrylic skull phantom in each scanner and on a neuro-interventional imaging system using clinical protocols. Measured dose data was used to estimate peak skin dose (PSD) for 4 patients receiving multiple exams including CTA, head CT, and cerebral angiography. Results: For scanner 1, the mean PSD for CTA exams (98.9 ± 5.3 mGy) and for routine head CT exams (39.2 ± 3.7 mGy) agreed reasonably well with the PSD measured on the phantom, 105.4 mGy and 40.0 mGy, respectively. Similarly for scanner 2, the mean PSD for CTA exams (98.8 ± 7.4 mGy) and for routine head CT exams (42.9 ± 9.4 mGy) compared well with phantom measurements, 95.2 mGy and 37.6 mGy, respectively. In addition, the mean PSD was comparable between scanners for corresponding patient exams, CTA and routine head CT respectively. PSD estimates ranged from 1.9 – 4.5 Gy among 4 patients receiving multiple exams. Conclusion: Patients having several exams including both CTA and routine head CT may receive cumulative doses approaching or exceeding the threshold for single dose deterministic effects.« less

[Dose and image quality in intraoral radiography].

PubMed

Hjardemaal, O

1991-11-01

The technique factors when performing intraoral X-ray exposures must be selected in such a way that sufficient diagnostic information is obtained at a reasonable patient dose. The Danish National Institute of Radiation Hygiene has performed a study comprising 32 dental X-ray sets. The mean value of the skin dose for a maxillary molar was 9.6 mGy and the value for the dental colleges 7.0 mGy. For a mandibular incisor the corresponding doses were 7.7 mGy and 3.6 mGy. After the conclusion of the mentioned study it has been part of the institute's inspection procedure for dental X-ray sets to measure patient skin doses. 243 measurements were performed and the mean value of the entrance skin dose was 6.5 mGy and the dose interval was 0.7-57 mGy. All doses are normalised to speed class D film. At 16% of the inspected sets films of speed class E were used. The remainder used class D films. The spread in doses cannot be explained by variation in equipment parameters alone but is to a high degree due to a combination of inappropriate film processing and exposure time. Interviews with staff in dental clinics confirm that films are frequently processed until the desired density is obtained by visual estimation. It is shown that the skin dose when using film of speed class D can be kept below 7 mGy for a mandibular incisor. Concluding is stated that film processing shall be performed in accordance with specifications from the manufacturer of the developer. Film of speed class E must be used. Finally must the exposure time be graduated according to the object exposed.

Surface radiation dose comparison of a dedicated extremity cone beam computed tomography (CBCT) device and a multidetector computed tomography (MDCT) machine in pediatric ankle and wrist phantoms

PubMed Central

Nagy, Eszter; Apfaltrer, Georg; Riccabona, Michael; Singer, Georg; Stücklschweiger, Georg; Guss, Helmuth; Sorantin, Erich

2017-01-01

Objectives To evaluate and compare surface doses of a cone beam computed tomography (CBCT) and a multidetector computed tomography (MDCT) device in pediatric ankle and wrist phantoms. Methods Thermoluminescent dosimeters (TLD) were used to measure and compare surface doses between CBCT and MDCT in a left ankle and a right wrist pediatric phantom. In both modalities adapted pediatric dose protocols were utilized to achieve realistic imaging conditions. All measurements were repeated three times to prove test-retest reliability. Additionally, objective and subjective image quality parameters were assessed. Results Average surface doses were 3.8 ±2.1 mGy for the ankle, and 2.2 ±1.3 mGy for the wrist in CBCT. The corresponding surface doses in optimized MDCT were 4.5 ±1.3 mGy for the ankle, and 3.4 ±0.7 mGy for the wrist. Overall, mean surface dose was significantly lower in CBCT (3.0 ±1.9 mGy vs. 3.9 ±1.2 mGy, p<0.001). Subjectively rated general image quality was not significantly different between the study protocols (p = 0.421), whereas objectively measured image quality parameters were in favor of CBCT (p<0.001). Conclusions Adapted extremity CBCT imaging protocols have the potential to fall below optimized pediatric ankle and wrist MDCT doses at comparable image qualities. These possible dose savings warrant further development and research in pediatric extremity CBCT applications. PMID:28570626

Impact of Adaptive Statistical Iterative Reconstruction (ASIR) on radiation dose and image quality in aortic dissection studies: a qualitative and quantitative analysis.

PubMed

Cornfeld, Daniel; Israel, Gary; Detroy, Ezra; Bokhari, Jamal; Mojibian, Hamid

2011-03-01

The purpose of the study was to quantify the radiation dose reduction achieved when imaging the aorta using Adaptive Statistical Iterative Reconstruction (ASIR) and to determine if this has an effect on image quality. We retrospectively reviewed 31 CT angiography examinations of the thoracic and abdominal aorta performed with ASIR and 32 consecutive similar examinations performed without ASIR. Volume CT dose index (CTDI(vol)), dose-length product (DLP), aortic enhancement at multiple levels, aorta-to-muscle contrast-to-noise ratio at multiple levels, and subjective image quality were compared between the two groups. The mean CTDI(vol) and DLP were significantly lower for the studies performed with ASIR versus studies without ASIR (15.6 vs 21.5 mGy, with an average difference of 5.8 mGy [95% CI 2.3-9.4 mGy] and 818 vs 1075 mGy × cm with an average difference of -257 mGy × cm [54-460 mGy × cm], respectively). Aortic enhancement, aortic signal-to-noise ratio, and aortic to muscle contrast-to-noise ratio were not different between the two groups. Subjectively, one reviewer preferred the non-ASIR images and one found the images equivalent. Both reviewers believed the images were of diagnostic quality. A 29% decrease in CTDI(vol) and a 20% decrease in DLP were obtained in scans with ASIR compared with scans without ASIR, without a quantitative loss of image quality.

Evaluation of external and internal irradiation on uranium mining enterprise staff by tooth enamel EPR spectroscopy

NASA Astrophysics Data System (ADS)

Zhumadilov, Kassym; Ivannikov, Alexander; Khailov, Artem; Orlenko, Sergei; Skvortsov, Valeriy; Stepanenko, Valeriy; Kuterbekov, Kairat; Toyoda, Shin; Kazymbet, Polat; Hoshi, Masaharu

2017-11-01

In order to estimate radiation effects on uranium enterprise staff and population teeth samples were collected for EPR tooth enamel dosimetry from population of Stepnogorsk city and staff of uranium mining enterprise in Shantobe settlment (Akmola region, North of Kazakhstan). By measurements of tooth enamel EPR spectra, the total absorbed dose in the enamel samples and added doses after subtraction of the contribution of natural background radiation are determined. For the population of Stepnogorsk city average added dose value of 4 +/- 11 mGy with variation of 51 mGy was obtained. For the staff of uranium mining enterprise in Shantobe settlment average value of added dose 95 +/- 20 mGy, with 85 mGy variation was obtained. Higher doses and the average value and a large variation for the staff, probably is due to the contribution of occupational exposure.

Research Update: The materials genome initiative: Data sharing and the impact of collaborative ab initio databases

DOE PAGES

Jain, Anubhav; Persson, Kristin A.; Ceder, Gerbrand

2016-03-24

Materials innovations enable new technological capabilities and drive major societal advancements but have historically required long and costly development cycles. The Materials Genome Initiative (MGI) aims to greatly reduce this time and cost. Here, we focus on data reuse in the MGI and, in particular, discuss the impact of three different computational databases based on density functional theory methods to the research community. Finally, we discuss and provide recommendations on technical aspects of data reuse, outline remaining fundamental challenges, and present an outlook on the future of MGI's vision of data sharing.

Investigation of an HMM/ANN hybrid structure in pattern recognition application using cepstral analysis of dysarthric (distorted) speech signals.

PubMed

Polur, Prasad D; Miller, Gerald E

2006-10-01

Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients requires a robust technique that can handle conditions of very high variability and limited training data. In this study, application of a 10 state ergodic hidden Markov model (HMM)/artificial neural network (ANN) hybrid structure for a dysarthric speech (isolated word) recognition system, intended to act as an assistive tool, was investigated. A small size vocabulary spoken by three cerebral palsy subjects was chosen. The effect of such a structure on the recognition rate of the system was investigated by comparing it with an ergodic hidden Markov model as a control tool. This was done in order to determine if this modified technique contributed to enhanced recognition of dysarthric speech. The speech was sampled at 11 kHz. Mel frequency cepstral coefficients were extracted from them using 15 ms frames and served as training input to the hybrid model setup. The subsequent results demonstrated that the hybrid model structure was quite robust in its ability to handle the large variability and non-conformity of dysarthric speech. The level of variability in input dysarthric speech patterns sometimes limits the reliability of the system. However, its application as a rehabilitation/control tool to assist dysarthric motor impaired individuals holds sufficient promise.

Photon hormesis deactivates alpha-particle induced bystander effects between zebrafish embryos

NASA Astrophysics Data System (ADS)

Ng, C. Y. P.; Cheng, S. H.; Yu, K. N.

2017-04-01

In the present work, we studied the effects of low-dose X-ray photons on the alpha-particle induced bystander effects between embryos of the zebrafish, Danio rerio. The effects on the naive whole embryos were studied through quantification of apoptotic signals (amounts of cells undergoing apoptosis) at 24 h post fertilization (hpf) using vital dye acridine orange staining, followed by counting the stained cells under a fluorescent microscope. We report data showing that embryos at 5 hpf subjected to a 4.4 mGy alpha-particle irradiation could release a stress signal into the medium, which could induce bystander effect in partnered naive embryos sharing the same medium. We also report that the bystander effect was deactivated when the irradiated embryos were subjected to a concomitant irradiation of 10 or 14 mGy of X-rays, but no such deactivation was achieved if the concomitant X-ray dose dropped to 2.5 or 5 mGy. In the present study, the significant drop in the amount of apoptotic signals on the embryos having received 4.4 mGy alpha particles together X-rays irradiation from 2.5 or 5 mGy to 10 or 14 mGy, together with the deactivation of RIBE with concomitant irradiation of 10 or 14 mGy of X-rays supported the participation of photon hormesis with an onset dose between 5 and 10 mGy, which might lead to removal of aberrant cells through early apoptosis or induction of high-fidelity DNA repair. As we found that photons and alpha particles could have opposite biological effects when these were simultaneously irradiated onto living organisms, these ionizing radiations could be viewed as two different environmental stressors, and the resultant effects could be regarded as multiple stressor effects. The present work presented the first study on a multiple stressor effect which occurred on bystander organisms. In other words, this was a non-targeted multiple stressor effect. The photon hormesis could also explain some failed attempts to observe neutron-induced bystander

SU-E-P-08: Establishment of Local Diagnostic Reference Levels of Routine Abdomen Exam in Computed Tomography According to Body Weight

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

Wang, H; Wang, Y; Weng, H

Purpose: The national diagnostic reference levels (NDRLs) is an efficient, concise and powerful standard for optimizing radiation protection of a patient. However, for each hospital the dose-reducing potential of focusing on establishment of local DRLs (LDRLs). A lot of study reported that Computed tomography exam contributed majority radiation dose in different medical modalities, therefore, routine abdomen CT exam was choose in initial pilot study in our study. Besides the mAs of routine abdomen CT exam was decided automatic exposure control by linear attenuation is relate to body shape of patient. In this study we would like to establish the localmore » diagnostic reference levels of routine abdomen exam in computed tomography according to body weight of patient. Methods and Materials: There are two clinical CT scanners (a Toshiba Aquilion and a Siemens Sensation) were performed in this study. For CT examinations the basic recommended dosimetric quantity is the Computed Tomography Dose Index (CTDI). The patient sample involved 82 adult patients of both sexes and divided into three groups by their body weight (50–60 kg, 60–70 kg, 70–80 kg).Carried out the routine abdomen examinations, and all exposure parameters have been collected and the corresponding CTDIv and DLP values have been determined. The average values were compared with the European DRLs. Results: The majority of patients (75%) were between 50–70 Kg of body weight, the numbers of patient in each group of weight were 40–50:7; 50–60:29; 60–70:33; 70–80:13. The LDRLs in each group were 10.81mGy, 14.46mGy, 20.27mGy and 21.04mGy, respectively. The DLP were 477mGy, 630mGy, 887mGy and 959mGy, respectively. No matter which group the LDRLs were lower than European DRLs. Conclusions: We would like to state that this was a pioneer work in local hospital in Chiayi. We hope that this may lead the way to further developments in Taiwan.« less

ITER Disruption Mitigation System Design

NASA Astrophysics Data System (ADS)

Rasmussen, David; Lyttle, M. S.; Baylor, L. R.; Carmichael, J. R.; Caughman, J. B. O.; Combs, S. K.; Ericson, N. M.; Bull-Ezell, N. D.; Fehling, D. T.; Fisher, P. W.; Foust, C. R.; Ha, T.; Meitner, S. J.; Nycz, A.; Shoulders, J. M.; Smith, S. F.; Warmack, R. J.; Coburn, J. D.; Gebhart, T. E.; Fisher, J. T.; Reed, J. R.; Younkin, T. R.

2015-11-01

The disruption mitigation system for ITER is under design and will require injection of up to 10 kPa-m3 of deuterium, helium, neon, or argon material for thermal mitigation and up to 100 kPa-m3 of material for suppression of runaway electrons. A hybrid unit compatible with the ITER nuclear, thermal and magnetic field environment is being developed. The unit incorporates a fast gas valve for massive gas injection (MGI) and a shattered pellet injector (SPI) to inject a massive spray of small particles, and can be operated as an SPI with a frozen pellet or an MGI without a pellet. Three ITER upper port locations will have three SPI/MGI units with a common delivery tube. One equatorial port location has space for sixteen similar SPI/MGI units. Supported by US DOE under DE-AC05-00OR22725.

Safety, immunogencity, and efficacy of a cold-adapted A/Ann Arbor/6/60 (H2N2) vaccine in mice and ferrets

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

Chen, Grace L., E-mail: chengra@niaid.nih.go; Lamirande, Elaine W., E-mail: elamirande@niaid.nih.go; Jin Hong, E-mail: jinh@medimmune.co

We studied the attenuation, immunogenicity and efficacy of the cold-adapted A/Ann Arbor/6/60 (AA ca) (H2N2) virus in mice and ferrets to evaluate its use in the event of an H2 influenza pandemic. The AA ca virus was restricted in replication in the respiratory tract of mice and ferrets. In mice, 2 doses of vaccine elicited a > 4-fold rise in hemagglutination-inhibition (HAI) titer and resulted in complete inhibition of viral replication following lethal homologous wild-type virus challenge. In ferrets, a single dose of the vaccine elicited a > 4-fold rise in HAI titer and conferred complete protection against homologous wild-typemore » virus challenge in the upper respiratory tract. In both mice and ferrets, the AA ca virus provided significant protection from challenge with heterologous H2 virus challenge in the respiratory tract. The AA ca vaccine is safe, immunogenic, and efficacious against homologous and heterologous challenge in mice and ferrets, supporting the evaluation of this vaccine in clinical trials.« less

[Comparison of Organ Dose Calculation Using Monte Carlo Simulation and In-phantom Dosimetry in CT Examination].

PubMed

Iriuchijima, Akiko; Fukushima, Yasuhiro; Ogura, Akio

Direct measurement of each patient organ dose from computed tomography (CT) is not possible. Most methods to estimate patient organ dose is using Monte Carlo simulation with dedicated software. However, the method and the relative differences between organ dose simulation and measurement is unclear. The purpose of this study was to compare organ doses evaluated by Monte Carlo simulation with doses evaluated by in-phantom dosimetry. The simulation software Radimetrics (Bayer) was used for the calculation of organ dose. Measurement was performed with radio-photoluminescence glass dosimeter (RPLD) set at various organ positions within RANDO phantom. To evaluate difference of CT scanner, two different CT scanners were used in this study. Angular dependence of RPLD and measurement of effective energy were performed for each scanner. The comparison of simulation and measurement was evaluated by relative differences. In the results, angular dependence of RPLD at two scanners was 31.6±0.45 mGy for SOMATOM Definition Flash and 29.2±0.18 mGy for LightSpeed VCT. The organ dose was 42.2 mGy (range, 29.9-52.7 mGy) by measurements and 37.7 mGy (range, 27.9-48.1 mGy) by simulations. The relative differences of organ dose between measurement and simulation were 13%, excluding of breast's 42%. We found that organ dose by simulation was lower than by measurement. In conclusion, the results of relative differences will be useful for evaluating organ doses for individual patients by simulation software Radimetrics.

Assessment of Regional Pediatric Computed Tomography Dose Indices in Tamil Nadu

PubMed Central

Saravanakumar, A.; Vaideki, K.; Govindarajan, K. N.; Jayakumar, S.; Devanand, B.

2017-01-01

The aim of this article is to assess Tamil Nadu pediatric computed tomography (CT) diagnostic reference levels (DRLs) by collecting radiation dose data for the most commonly performed CT examinations. This work was performed for thirty CT scanners installed in various parts of the Tamil Nadu region. The patient cohort was divided into two age groups: <1 year, and 1–5 years. CT dose indices were measured using a 10 cm3 pencil ion chamber with pediatric head and body polymethyl methacrylate phantoms. Dose data such as volumetric CT dose index (CTDIv) and dose length product (DLP) on a minimum of twenty average-sized pediatric patients in each category were recorded to calculate a mean site CTDIv and DLP value. The rounded 75th percentile was used to calculate a pediatric DRL for each hospital, and then region by compiling all results. Data were collected for 3600 pediatric patients. Pediatric CT DRL for two age groups: <1 year (CTDIv and DLP of head [20 mGy, 352 mGy.cm], chest [7 mGy, 120 mGy.cm] and abdomen [12 mGy, 252 mGy.cm]), and 1–5 years (CTDIv and DLP of head [38 mGy, 505 mGy.cm], chest [8 mGy, 132 mGy.cm] and abdomen [14 mGy, 270 mGy.cm]) for select procedures have been calculated. Proposed pediatric DRLs of CTDIv and DLP for head procedure were lower, and for chest and abdomen procedures were higher than European pediatric DRLs for both age groups. PMID:28405108

Assessment of Regional Pediatric Computed Tomography Dose Indices in Tamil Nadu.

PubMed

Saravanakumar, A; Vaideki, K; Govindarajan, K N; Jayakumar, S; Devanand, B

2017-01-01

The aim of this article is to assess Tamil Nadu pediatric computed tomography (CT) diagnostic reference levels (DRLs) by collecting radiation dose data for the most commonly performed CT examinations. This work was performed for thirty CT scanners installed in various parts of the Tamil Nadu region. The patient cohort was divided into two age groups: <1 year, and 1-5 years. CT dose indices were measured using a 10 cm 3 pencil ion chamber with pediatric head and body polymethyl methacrylate phantoms. Dose data such as volumetric CT dose index (CTDI v ) and dose length product (DLP) on a minimum of twenty average-sized pediatric patients in each category were recorded to calculate a mean site CTDI v and DLP value. The rounded 75 th percentile was used to calculate a pediatric DRL for each hospital, and then region by compiling all results. Data were collected for 3600 pediatric patients. Pediatric CT DRL for two age groups: <1 year (CTDI v and DLP of head [20 mGy, 352 mGy.cm], chest [7 mGy, 120 mGy.cm] and abdomen [12 mGy, 252 mGy.cm]), and 1-5 years (CTDI v and DLP of head [38 mGy, 505 mGy.cm], chest [8 mGy, 132 mGy.cm] and abdomen [14 mGy, 270 mGy.cm]) for select procedures have been calculated. Proposed pediatric DRLs of CTDI v and DLP for head procedure were lower, and for chest and abdomen procedures were higher than European pediatric DRLs for both age groups.

Intracellular magnesium concentrations in dogs with gastric dilatation-volvulus.

PubMed

Bebchuk, T N; Hauptman, J G; Braselton, W E; Walshaw, R

2000-11-01

To quantify and compare intracellular magnesium concentrations (Mgi) in clinically normal dogs (control dogs) and dogs that have gastric dilatation-volvulus (GDV dogs) and to determine whether there is a difference in Mgi and serum magnesium concentrations (Mgs) between GDV dogs with and without cardiac arrhythmias. 41 control dogs and 21 GDV dogs. Rectus abdominis muscle specimens were obtained from control and GDV dogs for determination of Mgi. Blood samples were obtained from GDV dogs for determination of Mgs, and dogs were monitored for 48 hours for cardiac arrhythmias. Muscle specimens were frozen at -40 C, oven dried at 95 C, and digested with concentrated nitric acid. Multielemental analyses were performed by simultaneous/sequential inductively coupled plasma-atomic emission spectroscopy with fixed-cross flow nebulization. The Mg, was standardized to sulfur content to correct for the amount of fat and fascia in the muscle specimen. Mean (+/- SEM) values were recorded in parts per million (ppm). Results-There were no significant differences in Mgi between control (627 +/- 11.1 ppm) and GDV (597 +/- 20.5 ppm) dogs, in Mgi between GDV dogs with (590 +/- 34 ppm) and without (584 +/- 29 ppm) cardiac arrhythmias, and in Mgs between GDV dogs with (1.77 +/- 0.26 ppm) and without (1.51 +/- 0.09 ppm) cardiac arrhythmias. There was no correlation between Mgs and Mgi (R2 = 0.0001). Results indicate that Mg depletion is not pathophysiologically important in dogs with GDV and does not play a role in the cardiac arrhythmias detected in these patients.

[Radiation exposure during spiral-CT of the paranasal sinuses].

PubMed

Dammann, F; Momino-Traserra, E; Remy, C; Pereira, P L; Baumann, I; Koitschev, A; Claussen, C D

2000-03-01

Determination of the radiation doses in spiral CT of the paranasal sinuses using a variety of mAs values and scan protocols. CT examinations of the paranasal sinuses were performed using an Alderson-Rando phantom. Radiation dose was determined by LiF-TLD at the level of high risk organs in the head and neck region for combinations of different scan parameters (2/3, 3/3, 3/4 mm) and decreasing charges (200, 150, 100, 50, 25 mAs) on a spiral CT. Additional measurements were performed on three other CT scanners using the 2/3 mm protocol at 50 mAs, and a single slice technique (5/5 mm) on one scanner. The lowest dose values found were 1.88 mGy for the eye lenses, 1.35 mGy for the parotid gland, 0.03 mGy for the thyroid gland and 0.1 mGy for the medulla oblongata using 2 mm collimation and 3 mm table feed at 25 mAs. Maximal dose values resulted using the 3/3 mm protocol at 200 mAs (31.00 mGy for the eye lense, 0.65 mGy for the thyroid gland). There were no significant differences found between the different CT scanners. Using up-to-date CT scanners, radiation exposure may be reduced by a factor of 15-20 compared to that of conventional CT technique. Thus, the exposure of the eye lens comes to only a thousandth of the value supposedly inducing a cataract, as published by the ICRP.

Investigation of the Entrance Surface Dose and Dose to Different Organs in Lumbar Spine Imaging

PubMed Central

Sina, S; Zeinali, B; Karimipoorfard, M; Lotfalizadeh, F; Sadeghi, M; Zamani, E; Faghihi, R

2014-01-01

Background: Dose assessment using proper dosimeters is especially important in radiation protection optimization and imaging justification in diagnostic radiology. Objective: The aim of this study is to obtain the Entrance Skin Dose (ESD) of patients undergoing lumbar spine imaging using two thermoluminescence dosimeters TLD-100 (LiF: Mg, Ti) and GR-200 (LiF: Mg, Cu, P) and also to obtain the absorbed dose to different organs in lumbar spine imaging with several views. Methods: To measure the ESD values of the patients undergoing lumbar spine imaging, the two TLD types were put on their skin surface. The ESD values for different views of lumbar spine imaging were also measured by putting the TLDs at the surface of the Rando phantom. Several TLD chips were inserted inside different organs of Rando phantom to measure the absorbed dose to different organs in lumbar spine imaging. Results: The results indicate that there is a close agreement between the results of the two dosimeters. Based on the results of this experiment, the ESD dose of the 16 patients included in this study varied between 2.71 mGy and 26.29 mGy with the average of 11.89 mGy for TLD-100, and between 2.55 mGy and 27.41 mGy with the average of 12.32 mGy for GR-200 measurements. The ESDs obtained by putting the two types of TLDs at the surface of Rando phantom are in close agreement. Conclusion: According to the results, the GR200 has greater sensitivity than the TLD-100. PMID:25599058

Performance degradation of ferrofluidic feedthroughs in a mixed irradiation field

DOE PAGES

Simos, Nikolaos; Fernandes, S.; Mittig, Wolfgang; ...

2016-10-06

We present ferrofluidic feedthrough (FF) rotary seals containing either NdFeB or SmCo-type permanent magnets that have been considered for use in the target and beam dump systems of the Facility for Rare Isotope Beams (FRIB). To evaluate their performance under irradiation three FF seals were irradiated in a mixed field consisting of fast neutrons, protons and γ-rays to an average absorbed dose of 0.2, 2.0, and 20.0 MGy at the Brookhaven Linac Isotope Producer facility (BLIP). The radiation types and energy profiles mimic those expected at the FRIB facility. Degradation of the operational performance of these devices due to irradiationmore » is expected to be the result of the de-magnetization of the permanent magnets contained within the seal and the changes in the ferrofluid properties. Post-irradiation performance was evaluated by determining the ferrofluidic seal vacuum tightness and torque under static and dynamic conditions. The study revealed that the ferrofluidic feedthrough seal irradiated to a dose of 0.2 MGy maintained its vacuum tightness under both static and rotational condition while the one irradiated to a dose of 2.0 MGy exhibited signs of ferrofluid damage but no overall performance loss. Lastly, at 20 MGy dose the effects of irradiation on the ferrofluid properties (viscosity and particle agglomeration) were shown to be severe. Furthermore, limited de-magnetization of the annular shaped Nd 2Fe 14B and Sm 2Co 17 magnets located within the irradiated FFs was observed for doses of 0.2 MGy and 20 MGy respectively.« less

Performance degradation of ferrofluidic feedthroughs in a mixed irradiation field

NASA Astrophysics Data System (ADS)

Simos, Nikolaos; Fernandes, S.; Mittig, Wolfgang; Pellemoine, Frederique; Avilov, M.; Kostin, M.; Mausner, L.; Ronningen, R.; Schein, M.; Bollen, G.

2017-01-01

Ferrofluidic feedthrough (FF) rotary seals containing either NdFeB or SmCo-type permanent magnets have been considered for use in the target and beam dump systems of the Facility for Rare Isotope Beams (FRIB). To evaluate their performance under irradiation three FF seals were irradiated in a mixed field consisting of fast neutrons, protons and γ-rays to an average absorbed dose of 0.2, 2.0, and 20.0 MGy at the Brookhaven Linac Isotope Producer facility (BLIP). The radiation types and energy profiles mimic those expected at the FRIB facility. Degradation of the operational performance of these devices due to irradiation is expected to be the result of the de-magnetization of the permanent magnets contained within the seal and the changes in the ferrofluid properties. Post-irradiation performance was evaluated by determining the ferrofluidic seal vacuum tightness and torque under static and dynamic conditions. The study revealed that the ferrofluidic feedthrough seal irradiated to a dose of 0.2 MGy maintained its vacuum tightness under both static and rotational condition while the one irradiated to a dose of 2.0 MGy exhibited signs of ferrofluid damage but no overall performance loss. At 20 MGy dose the effects of irradiation on the ferrofluid properties (viscosity and particle agglomeration) were shown to be severe. Furthermore, limited de-magnetization of the annular shaped Nd2Fe14B and Sm2Co17 magnets located within the irradiated FFs was observed for doses of 0.2 MGy and 20 MGy respectively.

The cold adapted and temperature sensitive influenza A/Ann Arbor/6/60 virus, the master donor virus for live attenuated influenza vaccines, has multiple defects in replication at the restrictive temperature

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

Chan, Winnie; Zhou, Helen; Kemble, George

2008-10-25

We have previously determined that the temperature sensitive (ts) and attenuated (att) phenotypes of the cold adapted influenza A/Ann Arbor/6/60 strain (MDV-A), the master donor virus for the live attenuated influenza A vaccines (FluMist), are specified by the five amino acids in the PB1, PB2 and NP gene segments. To understand how these loci control the ts phenotype of MDV-A, replication of MDV-A at the non-permissive temperature (39 deg. C) was compared with recombinant wild-type A/Ann Arbor/6/60 (rWt). The mRNA and protein synthesis of MDV-A in the infected MDCK cells were not significantly reduced at 39 deg. C during amore » single-step replication, however, vRNA synthesis was reduced and the nuclear-cytoplasmic export of viral RNP (vRNP) was blocked. In addition, the virions released from MDV-A infected cells at 39 deg. C exhibited irregular morphology and had a greatly reduced amount of the M1 protein incorporated. The reduced M1 protein incorporation and vRNP export blockage correlated well with the virus ts phenotype because these defects could be partially alleviated by removing the three ts loci from the PB1 gene. The virions and vRNPs isolated from the MDV-A infected cells contained a higher level of heat shock protein 70 (Hsp70) than those of rWt, however, whether Hsp70 is involved in thermal inhibition of MDV-A replication remains to be determined. Our studies demonstrate that restrictive replication of MDV-A at the non-permissive temperature occurs in multiple steps of the virus replication cycle.« less

Increased apoptosis and DNA double-strand breaks in the embryonic mouse brain in response to very low-dose X-rays but not 50 Hz magnetic fields.

PubMed

Saha, Shreya; Woodbine, Lisa; Haines, Jackie; Coster, Margaret; Ricket, Nicole; Barazzuol, Lara; Ainsbury, Elizabeth; Sienkiewicz, Zenon; Jeggo, Penny

2014-11-06

The use of X-rays for medical diagnosis is enhancing exposure to low radiation doses. Exposure to extremely low-frequency electromagnetic or magnetic fields is also increasing. Epidemiological studies show consistent associations of childhood leukaemia with exposure to magnetic fields but any causal relationship is unclear. A limitation in assessing the consequence of such exposure is the availability of sensitive assays. The embryonic neuronal stem and progenitor cell compartments are radiosensitive tissues. Using sensitive assays, we report a statistically significant increase in DNA double-strand break (DSB) formation and apoptosis in the embryonic neuronal stem cell compartment following in utero exposure to 10-200 mGy X-rays. Both endpoints show a linear response. We also show that DSB repair is delayed following exposure to doses below 50 mGy compared with 100 mGy. Thus, we demonstrate in vivo consequences of low-dose radiation. In contrast to these impacts, we did not observe any significant induction of DSBs or apoptosis following exposure to 50 Hz magnetic fields (100 or 300 µT). We conclude that any DSB induction by treatment with magnetic fields is lower than following exposure to 10 mGy X-rays. For comparison, certain procedures involving computed tomography scanning are equivalent to 1-5 mGy X-rays.

Trusting families: Responding to Mary Ann Meeker, "Responsive care management: family decision makers in advanced cancer".

PubMed

Nelson, James Lindemann

2011-01-01

Mary Ann Meeker's article admirably reminds readers that family members are involved in--or "responsively manage"--the care of relatives with severe illness in ways that run considerably beyond the stereotypes at play in many bioethical discussions of advance directives. Her observations thus make thinking about the role of families in healthcare provision more adequate to the facts, and this is an important contribution. There's reason to be worried, however, that one explicit aim of the article--to ease the standing anxieties that many clinicians and ethicists have about the reliability of family members as proxy decision makers--will be frustrated by its very success. Those already inclined to suspicion may tend to think that the more intricate and pervasive the ways in which families influence the healthcare decision making of their sick, the more chances they have for altering the connection between patients' interests and the actions of professional providers. To determine whether and when such alterations are something to be concerned about, we'll need to supplement a better grasp of the pertinent facts with a deeper sense of how human agency works and why we value it. We may also need some reminders about the defensibility of diverse moral understandings. Although both professionals and family members may profess an ethic that sets patients' interests above those of non-patients--as Meeker's own results suggest--any strict allegiance to such a framework may be more notional than normative--as her findings also hint. The actual working norms (among professionals, as well as within families) will likely be more complex, but not necessarily any the less defensible for that.

Radiation dose to the eyes and parotids during CT of the sinuses.

PubMed

Bassim, Marc K; Ebert, Charles S; Sit, Roger C; Senior, Brent A

2005-10-01

To measure the radiation dose to the lens and parotid during high-resolution computed tomography scan of the sinuses. Nine cadaver heads were scanned in the axial plane by means of a fine-cut (0.75 mm) protocol. Images were then reconstructed in the coronal and sagittal planes for use with the image guidance software. Thermoluminescent dosimeters were taped over the eyes and parotids and used to measure the radiation dose absorbed by these organs. Doses obtained were 29.5 mGy for the lens and around 30 mGy for the parotid. The measured doses are lower than the reported acute thresholds of 500-2000 mGy for lens opacities and well below the threshold of 2500 mGy for damage to the parotid. These results demonstrate minimal risk from radiation through the use of high-resolution computed tomography and support the use of such a protocol for diagnosis and preoperative planning.

Evaluation of organ doses in CT examinations with an infant anthropomorphic phantom.

PubMed

Fujii, K; Akahane, K; Miyazaki, O; Horiuchi, T; Shimada, A; Nagmatsu, H; Yamauchi, M; Yamauchi-Kawaura, C; Kawasaki, T

2011-09-01

The aim of this study is to evaluate organ doses in infant CT examinations with multi-detector row CT scanners. Radiation doses were measured with radiophotoluminescence glass dosemeters set in various organ positions within a 1-y-old child anthropomorphic phantom and organ doses were evaluated from the measurement values. Doses for tissues or organs within the scan range were 28-36 mGy in an infant head CT, 3-11 mGy in a chest CT, 5-11 mGy in an abdominal-pelvic CT and 2-14 mGy in a cardiac CT. The doses varied by the differences in the types of CT scanners and scan parameters used at each medical facility. Compared with those for children of various ages, the doses in an infant CT protocol were found to be similar to or slightly smaller than those in a paediatric CT for 5- or 6-y-old children.

Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model.

PubMed

Dropkin, Greg

2016-11-24

Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour. GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 - 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy. For all solid cancer incidence, RR estimated from 0 - 100 mGy and 0 - 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 - 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort. Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

The long-term effects of acute exposure to ionising radiation on survival and fertility in Daphnia magna

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

Sarapultseva, Elena I.

The results of recent studies have provided strong evidence for the transgenerational effects of parental exposure to ionising radiation and chemical mutagens. However, the transgenerational effects of parental exposure on survival and fertility remain poorly understood. To establish whether parental irradiation can affect the survival and fertility of directly exposed organisms and their offspring, crustacean Daphnia magna were given 10, 100, 1000 and 10,000 mGy of acute γ-rays. Exposure to 1000 and 10,000 mGy significantly compromised the viability of irradiated Daphnia and their first-generation progeny, but did not affect the second-generation progeny. The fertility of F{sub 0} and F{sub 1}Daphniamore » gradually declined with the dose of parental exposure and significantly decreased at dose of 100 mGy and at higher doses. The effects of parental irradiation on the number of broods were only observed among the F{sub 0}Daphnia exposed to 1000 and 10,000 mGy, whereas the brood size was equally affected in the two consecutive generations. In contrast, the F{sub 2} total fertility was compromised only among progeny of parents that received the highest dose of 10,000 mGy. We propose that the decreased fertility observed among the F{sub 2} progeny of parents exposed to 10,000 mGy is attributed to transgenerational effects of parental irradiation. Our results also indicate a substantial recovery of the F{sub 2} progeny of irradiated F{sub 0}Daphnia exposed to the lower doses of acute γ-rays. - Highlights: • Viability of irradiated daphnids and their F{sub 1} progeny is compromised. • Viability of the F{sub 2} progeny of irradiated parents is not affected. • Total fertility of irradiated daphnids and their F{sub 1} progeny declines with the dose. • Total fertility of the F{sub 2} progeny of parents exposed to 10,000 mGy is compromised. • The decreased fertility among the F{sub 2} progeny is transgenerational phenomenon.« less

SU-E-J-11: Measurement of Eye Lens Dose for Varian On-Board Imaging with Different CBCT Acquisition Techniques

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

Deshpande, S; Dhote, D; Kumar, R

Purpose: To measure actual patient eye lens dose for different cone beam computed tomography (CBCT) acquisition protocol of Varian’s On Board Imagining (OBI) system using Optically Stimulated Luminescence (OSL) dosimeter and study the eye lens dose with patient geometry and distance of isocenter to the eye lens Methods: OSL dosimeter was used to measure eye lens dose of patient. OSL dosimeter was placed on patient forehead center during CBCT image acquisition to measure eye lens dose. For three different cone beam acquisition protocol (standard dose head, low dose head and high quality head) of Varian On-Board Imaging, eye lens dosesmore » were measured. Measured doses were correlated with patient geometry and distance between isocenter to eye lens. Results: Measured eye lens dose for standard dose head was in the range of 1.8 mGy to 3.2 mGy, for high quality head protocol dose was in range of 4.5mGy to 9.9 mGy whereas for low dose head was in the range of 0.3mGy to 0.7mGy. Dose to eye lens is depends upon position of isocenter. For posterioraly located tumor eye lens dose is less. Conclusion: From measured doses it can be concluded that by proper selection of imagining protocol and frequency of imaging, it is possible to restrict the eye lens dose below the new limit set by ICRP. However, undoubted advantages of imaging system should be counter balanced by careful consideration of imaging protocol especially for very intense imaging sequences for Adoptive Radiotherapy or IMRT.« less

Comparison of skin dose measurement using nanoDot® dosimeter and machine readings of radiation dose during cardiac catheterization in children.

PubMed

Balaguru, Duraisamy; Rodriguez, Matthew; Leon, Stephanie; Wagner, Louis K; Beasley, Charles W; Sultzer, Andrew; Numan, Mohammed T

2018-01-01

Direct measurement of skin dose of radiation for children using optically stimulated luminescence (OSL) technology using nanoDot ® (Landauer, Glenwood, IL, USA). Radiation dose is estimated as cumulative air kerma (AK) and dosearea product based on standards established for adult size patients. Body size of pediatric patients who undergo cardiac catheterization for congenital heart disease vary widely from newborn to adolescence. Direct, skindose measurement applying OSL technology may eliminate errors in the estimate. The nanoDot ® (1 cm × 1 cm × flat plastic cassette) is applied to patient's skin using adhesive tape during cardiac catheterization and radiation skin doses were read within 24 hrs. nanoDot ® values were compared to the currently available cumulative AK values estimated and displayed on fluoroscopy monitor. A total of 12 children were studied, aged 4 months to 18 years (median 1.1 years) and weight range 5.3-86 kg (median 8.4 kg). nanoDot® readings ranged from 2.58 mGy to 424.8 mGy (median 84.1 mGy). Cumulative AK ranged from 16.2 mGy to 571.2 mGy (median 171.1 mGy). Linear correlation was noted between nanoDot® values and AK values ( R 2 = 0.88, R = 0.94). nanoDot® readings were approximately 65% of the estimated cumulative AK estimated using the International Electrotechnical Commission standards. Application of OSL technology using nanoDot® provides an alternative to directly measure fluoroscopic skin dose in children during cardiac catheterization. Our data show that the actual skin dose for children is approximately one-third lower than the AK estimated using international standards for adult size patients.

Translation and validation of the German version of the Mother-Generated Index and its application during the postnatal period.

PubMed

Grylka-Baeschlin, Susanne; van Teijlingen, Edwin; Stoll, Kathrin; Gross, Mechthild M

2015-01-01

the Mother-Generated Index (MGI) is a validated tool to assess postnatal quality of life. It is usually administered several weeks or months after birth and correlates with indices of post partum mood states and physical complaints. The instrument had not been translated into German before or validated for use among German-speaking women, nor have the results of the tool been assessed specifically for the administration directly after birth. This paper aims to describe the systematic translation process of the MGI into German and to assess the convergent validity of the German version of the instrument directly after birth and seven weeks post partum. prospective two-stage survey. two rural hospitals in the south of Germany and in the north of Switzerland. all women giving birth between 1st October and 15th December 2012 with sufficient knowledge of German and whose babies were not referred to a neonatal care unit; 226 women were eligible to participate. two questionnaires including questions relating to socio-demographic factors and perinatal care, and incorporating the MGI, the Hospital Anxiety and Depression Scale (HADS) and the Postnatal Morbidity Index (PMI). All instruments were subjected to forward and back translation and pilot-tested; the first questionnaire was then administered in the first two days after birth and the second six weeks post partum. Parametric and non-parametric tests were computed using SPSS. 129 surveys were returned an average of three days after birth and 83 after seven weeks. Higher postnatal quality of life showed a significant correlation with a lower anxiety and depression score (p<0.01), fewer maternal physical complaints (p<0.05) and more favourable baby adjective scores (p<0.05) after birth. Significant associations were found between MGI scores and sufficient help (p=0.03) as well as ability to cope at home (p<0.01). MGI scores three days and seven weeks after birth correlated highly significantly and positively (p<0

Long-Term Musical Group Interaction Has a Positive Influence on Empathy in Children

ERIC Educational Resources Information Center

Rabinowitch, Tal-Chen; Cross, Ian; Burnard, Pamela

2013-01-01

Musical group interaction (MGI) is a complex social setting requiring certain cognitive skills that may also elicit shared psychological states. We argue that many MGI-specific features may also be important for emotional empathy, the ability to experience another person's emotional state. We thus hypothesized that long-term repeated participation…

Dose response and repair kinetics of gamma-H2AX foci induced by in vitro irradiation of whole blood and T-lymphocytes with X- and gamma-radiation.

PubMed

Beels, Laurence; Werbrouck, Joke; Thierens, Hubert

2010-09-01

Dose response and repair kinetics of phosphorylated histone H2A isoform X (gamma-H2AX) foci in T-lymphocytes were investigated in the low-dose range after in vitro irradiation of whole blood and T-lymphocytes with 100 kVp X-rays and (60)Co gamma-rays. Whole blood or isolated T-lymphocytes were irradiated in vitro and gamma-H2AX foci were scored. Dose response was determined in the 0-500 mGy dose range. Foci kinetics were studied at doses of 5 and 200 mGy up to 24 h post-irradiation. After X-irradiation, the dose response for whole blood shows a biphasic behaviour with a low-dose hypersensitivity, which is less pronounced for isolated T-lymphocytes. In contrast, gamma-radiation shows a linear dose response for both irradiation conditions. Concerning repair kinetics, delayed repair was found after X-ray whole blood irradiation (5 and 200 mGy) with 40% of the foci persisting 24 h post-irradiation. This number of foci is reduced to 10% after irradiation of isolated T-lymphocytes with 200 mGy X-rays. On the contrary, gamma-H2AX foci are reduced to background levels 24 h post-irradiation with 200 mGy (60)Co gamma-rays. gamma-H2AX foci response and repair kinetics depend on irradiation conditions and radiation quality, possibly linked to Bystander response.

Increased apoptosis and DNA double-strand breaks in the embryonic mouse brain in response to very low-dose X-rays but not 50 Hz magnetic fields

PubMed Central

Saha, Shreya; Woodbine, Lisa; Haines, Jackie; Coster, Margaret; Ricket, Nicole; Barazzuol, Lara; Ainsbury, Elizabeth; Sienkiewicz, Zenon; Jeggo, Penny

2014-01-01

The use of X-rays for medical diagnosis is enhancing exposure to low radiation doses. Exposure to extremely low-frequency electromagnetic or magnetic fields is also increasing. Epidemiological studies show consistent associations of childhood leukaemia with exposure to magnetic fields but any causal relationship is unclear. A limitation in assessing the consequence of such exposure is the availability of sensitive assays. The embryonic neuronal stem and progenitor cell compartments are radiosensitive tissues. Using sensitive assays, we report a statistically significant increase in DNA double-strand break (DSB) formation and apoptosis in the embryonic neuronal stem cell compartment following in utero exposure to 10–200 mGy X-rays. Both endpoints show a linear response. We also show that DSB repair is delayed following exposure to doses below 50 mGy compared with 100 mGy. Thus, we demonstrate in vivo consequences of low-dose radiation. In contrast to these impacts, we did not observe any significant induction of DSBs or apoptosis following exposure to 50 Hz magnetic fields (100 or 300 µT). We conclude that any DSB induction by treatment with magnetic fields is lower than following exposure to 10 mGy X-rays. For comparison, certain procedures involving computed tomography scanning are equivalent to 1–5 mGy X-rays. PMID:25209403

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

NASA Technical Reports Server (NTRS)

Lure, Y. M. Fleming; Grody, Norman C.; Chiou, Y. S. Peter; Yeh, H. Y. Michael

1993-01-01

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular

Evidence that one is more likely to see the aurora near Moscow than near Ann Arbor

NASA Astrophysics Data System (ADS)

Liemohn, Michael; Immel, Thomas; Katus, Roxanne

We present a superposed epoch analysis of solar wind drivers and geomagnetic index responses during magnetic storms, categorized as a function of universal time (UT) of the storm peak, to investigate the dependency of storm intensity on UT. Storms with Dst minimum less than - 100 nT were identified in the 1970 - 2012 era (totaling 310 events), covering four solar cycles. The storms were classified into 6 groups based on the UT of the minimum Dst (36 to 82 events per bin), then each grouping was superposed on a timeline that aligns the time of the minimum Dst. Fifteen different quantities were considered, seven solar wind parameters and eight activity indices derived from ground-based magnetometers. Statistical analyses of the superposed means against each other (between the different UT groupings) were conducted to determine the mathematical significance of similarities and differences in the time series plots. It was found that most of the solar wind parameters have essentially no significant difference between the UT groupings, as expected. The exception is solar wind velocity, which appears to be bifurcated into two levels with three of the UT groupings systematically faster than the other three (although, interestingly, not three consecutive UT bins). The geomagnetic activity indices, however, all show statistically significant differences with UT during the main phase and/or early recovery phase. Specifically, the 16, 20, and 00 UT groupings are stronger storms than those in the other UT bins. That is, storms are stronger when the Asian sector is on the nightside (American sector on the dayside) during the main phase. An inference from these findings, therefore, is that one is more likely to see the aurora near Moscow in Russia than near Ann Arbor, Michigan in the United States, even though these two cities have very similar magnetic latitudes (52 degrees).

Thiamine Deficiency Complex Workshop final report: November 6-7, 2008, Ann Arbor, MI

USGS Publications Warehouse

Honeyfield, Dale C.; Tillitt, Donald E.; Riley, Stephen C.

2008-01-01

Fry mortality which was first observed in the late 1960s in Great Lakes salmonines and in Baltic Sea salmon in 1974 has now been linked to thiamine deficiency (historically referred to as Early Mortality Syndrome, or EMS and M74, respectively). Over the past 14 years significant strides have been made in our understanding of this perplexing problem. It is now known that thiamine deficiency causes embryonic mortality in these salmonids. Both overt mortality and secondary effects of thiamine deficiency are observed in juvenile and adult animals. Collectively the morbidity and mortality (fry and adult mortality, secondary metabolic and behavior affects in juveniles and adult fish) are referred to as Thiamine Deficiency Complex (TDC). A workshop was held in Ann Arbor, MI on 6-7 November 2008 that brought together 38 federal, state, provincial, tribal and university scientists to share information, present data and discuss the latest observations on thiamine status of aquatic animals with thiamine deficiency and the causative agent, thiaminase. Twenty presentations (13 oral and 7 posters) detailed current knowledge. In Lake Huron, low alewife Alosa pseudoharengus abundance has persisted and egg thiamine concentrations in salmonines continue to increase, along with evidence of natural reproduction in lake trout Salvelinus namaycush. Lake Michigan Chinook salmon Oncorhynchus tshawytscha appear to have a lower thiamine requirement than other salmonids in the lake. Lake Ontario American eel Anguilla rostrata foraging on alewife have approximately one third the muscle thiamine compared to eels not feeding on alewife, suggesting that eels may be suffering from thiamine deficiency. Secondary effects of low thiamine exist in Great Lakes salmonines and should not be ignored. Thiaminase activity in dreissenid mussels is extremely high but a connection to TDC has not been made. Thiaminase in net plankton was found more consistently in lakes Michigan and Ontario than other lakes

SU-E-I-09: Application of LiF:Mg,Cu (TLD-100H) Dosimeters for in Diagnostic Radiology

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

Sina, S; Zeinali, B; Karimipourfard, M

Purpose: Accurate dosimetery is very essential in diagnostic radiology. The goal of this study is to verify the application of LiF:Mg,Cu,P (TLD100H) in obtaining the Entrance skin dose (ESD) of patients undergoing diagnostic radiology. The results of dosimetry performed by TLD-100H, were compared with those obtained by TLD100, which is a common dosimeter in diagnostic radiology. Methods: In this study the ESD values were measured using two types of Thermoluminescence dosimeters (TLD-100, and TLD-100H) for 16 patients undergoing diagnostic radiology (lumbar spine imaging). The ESD values were also obtained by putting the two types of TLDs at the surface ofmore » Rando phantom for different imaging techniques and different views (AP, and lateral). The TLD chips were annealed with a standard procedure, and the ECC values for each TLD was obtained by exposing the chips to equal amount of radiation. Each time three TLD chips were covered by thin dark plastic covers, and were put at the surface of the phantom or the patient. The average reading of the three chips was used for obtaining the dose. Results: The results show a close agreement between the dose measuered by the two dosimeters.According to the results of this study, the TLD-100H dosimeters have higher sensitivities (i.e.signal(nc)/dose) than TLD-100.The ESD values varied between 2.71 mGy and 26.29 mGy with the average of 11.89 mGy for TLD-100, and between 2.55 mGy and 27.41 mGy with the average of 12.32 mGy for measurements. Conclusion: The TLD-100H dosimeters are suggested as effective dosimeters for dosimetry in low dose fields because of their higher sensitivities.« less

Assessment of DNA double-strand breaks induced by intravascular iodinated contrast media following in vitro irradiation and in vivo, during paediatric cardiac catheterization.

PubMed

Gould, Richard; McFadden, Sonyia L; Horn, Simon; Prise, Kevin M; Doyle, Philip; Hughes, Ciara M

2016-01-01

Paediatric cardiac catheterizations may result in the administration of substantial amounts of iodinated contrast media and ionizing radiation. The aim of this work was to investigate the effect of iodinated contrast media in combination with in vitro and in vivo X-ray radiation on lymphocyte DNA. Six concentrations of iodine (15, 17.5, 30, 35, 45, and 52.5 mg of iodine per mL blood) represented volumes of iodinated contrast media used in the clinical setting. Blood obtained from healthy volunteers was mixed with iodinated contrast media and exposed to radiation doses commonly used in paediatric cardiac catheterizations (0 mGy, 70 mGy, 140 mGy, 250 mGy and 450 mGy). Control samples contained no iodine. For in vivo experimentation, pre and post blood samples were collected from children undergoing cardiac catheterization, receiving iodine concentrations of up to 51 mg of iodine per mL blood and radiation doses of up to 400 mGy. Fluorescence microscopy was performed to assess γH2AX-foci induction, which corresponded to the number of DNA double-strand breaks. The presence of iodine in vitro resulted in significant increases of DNA double-strand breaks beyond that induced by radiation for ≥ 17.5 mg/mL iodine to blood. The in vivo effects of contrast media on children undergoing cardiac catheterization resulted in a 19% increase in DNA double-strand breaks in children receiving an average concentration of 19 mg/mL iodine to blood. A larger investigation is required to provide further information of the potential benefit of lowering the amount of iodinated contrast media received during X-ray radiation investigations. Copyright © 2015 John Wiley & Sons, Ltd.

Comparison of skin dose measurement using nanoDot® dosimeter and machine readings of radiation dose during cardiac catheterization in children

PubMed Central

Balaguru, Duraisamy; Rodriguez, Matthew; Leon, Stephanie; Wagner, Louis K; Beasley, Charles W; Sultzer, Andrew; Numan, Mohammed T

2018-01-01

Objectives: Direct measurement of skin dose of radiation for children using optically stimulated luminescence (OSL) technology using nanoDot® (Landauer, Glenwood, IL, USA). Background: Radiation dose is estimated as cumulative air kerma (AK) and dosearea product based on standards established for adult size patients. Body size of pediatric patients who undergo cardiac catheterization for congenital heart disease vary widely from newborn to adolescence. Direct, skindose measurement applying OSL technology may eliminate errors in the estimate. Materials and Methods: The nanoDot® (1 cm × 1 cm × flat plastic cassette) is applied to patient's skin using adhesive tape during cardiac catheterization and radiation skin doses were read within 24 hrs. nanoDot® values were compared to the currently available cumulative AK values estimated and displayed on fluoroscopy monitor. Results: A total of 12 children were studied, aged 4 months to 18 years (median 1.1 years) and weight range 5.3–86 kg (median 8.4 kg). nanoDot® readings ranged from 2.58 mGy to 424.8 mGy (median 84.1 mGy). Cumulative AK ranged from 16.2 mGy to 571.2 mGy (median 171.1 mGy). Linear correlation was noted between nanoDot® values and AK values (R2 = 0.88, R = 0.94). nanoDot® readings were approximately 65% of the estimated cumulative AK estimated using the International Electrotechnical Commission standards. Conclusions: Application of OSL technology using nanoDot® provides an alternative to directly measure fluoroscopic skin dose in children during cardiac catheterization. Our data show that the actual skin dose for children is approximately one-third lower than the AK estimated using international standards for adult size patients. PMID:29440825

Neuroimmune response and sleep studies after whole body irradiation with high-LET particles

NASA Astrophysics Data System (ADS)

Marquette, C.; Mathieu, J.; Bertho, J.-M.; Galonnier, M.; Wysoki, J.; Maubert, C.; Balanzat, E.; Gerbin, R.; Aigueperse, J.; Clarençon, D.

2009-10-01

In order to investigate the biological effects of galactic rays on astronaut cerebral functions after space flight, mice were exposed to different heavy ions (HZE) in whole-body conditions at doses comparable to the galactic flux: 12C, 16O and 20Ne (95 MeV/u, at 42-76 mGy). Animals were also exposed to 42 mGy of 60Co radiation for comparison with HZE. The neuroimmune response, evaluated by interleukin-1 (IL-1) measurement, showed that this cytokine was produced 3 h after irradiation by 16O or 60Co. In contrast, neither 12C (56.7 mGy) nor 20Ne (76 mGy) induced IL-1 production. However, immunohistochemical staining of 12C-irradiated mouse brain tissue showed 2 months later a marked inflammatory reaction in the hippocampus and a diffuse response in parenchyma. Sleep studies were realized before and after exposure to 42 mGy of 16O and 76 mGy of 20Ne: only the 20Ne radiation displayed a small effect. A slight decrease in paradoxical sleep, corresponding to a reduction in the number of episodes of paradoxical sleep, was manifested between 8 and 22 days after exposure. Exposure to 12C and 16O induced no changes either in cellularity of spleen or thymus, or in caspase 3 activity (as much as four months after irradiation). Taken together, these data indicate that the CNS could be sensitive to heavy ions and that responses to HZE impact depend on the nature of the particle, the dose threshold and the time delay to develop biological processes. Differences in responses to different HZE highlight the complex biological phenomena to which astronauts are submitted during space flight.

Mutational influences of low-dose and high let ionizing radiation in drosophila melanogaster

NASA Astrophysics Data System (ADS)

Lei, Huang; Fanjun, Kong; Sun, Yeqing

For cosmic environment consists of a varying kinds of radiation particles including high Z and energy ions which was charactered with low-dose and high RBE, it is important to determine the possible biofuctions of high LET radiation on human beings. To analyse the possible effectes of mutational influences of low-dose and high-LET ionizing radiation, wild fruit flies drosophila melanogaster were irradiated by 12C6+ ions in two LET levels (63.3 and 30 keV/µum) with different low doses from 2mGy to 2000mGy (2, 20, 200, 2000mGy) in HIRFL (Heavy ion radiation facility laboratory, lanzhou, China).In the same LET value group, the average polymorphic frequency was elevated along with adding doses of irradation, the frequency in 2000 mGy dose samples was significantly higher than other samples (p<0.01).These results suggest that genomic DNA sequence could be effected by low-dose and high-LET ionizing radiation, the irradiation dose is an important element in genomic mutation frequency origination.

Carol Anne Bond v the United States of America: how a woman scorned threatened the Chemical Weapons Convention.

PubMed

Muldoon, Anna; Kornblet, Sarah; Katz, Rebecca

2011-09-01

The case of Carol Anne Bond v the United States of America stemmed from a domestic dispute when Ms. Bond attempted to retaliate against her best friend by attacking her with chemical agents. What has emerged is a much greater issue--a test of standing on whether a private citizen can challenge the Tenth Amendment. Instead of being prosecuted in state court for assault, Ms. Bond was charged and tried in district court under a federal criminal statute passed as part of implementation of the Chemical Weapons Convention (CWC). Ms. Bond's argument rests on the claim that the statute exceeded the federal government's enumerated powers in criminalizing her behavior and violated the Constitution, while the government contends legislation implementing treaty obligations is well within its purview. This question remains unanswered because there is dispute among the lower courts as to whether Ms. Bond, as a citizen, even has the right to challenge an amendment guaranteeing states rights when a state is not a party to the action. The Supreme Court heard the case on February 22, 2011, and, if it decides to grant Ms. Bond standing to challenge her conviction, the case will be returned to the lower courts. Should the court decide Ms. Bond has the standing to challenge her conviction and further questions the constitutionality of the law, it would be a significant blow to implementation of the CWC in the U.S. and the effort of the federal government to ensure we are meeting our international obligations.

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

ClinicalTrials.gov

2018-06-11

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

The presence of polymeric material in radiolysed aqueous solutions of ammonium bicarbonate

NASA Astrophysics Data System (ADS)

Draganic, Z. D.; Negron-Mendoza, A.; Navarro-Gonzalez, R.; Vujosevic, S. I.

A polymeric material is present in radiolysed aqueous solutions (O 2-free) of ammonium bicarbonate (0.05 mol dm -3) at large doses of cobalt-60 gamma rays (0.15-1.7 MGy). Polymer is a secondary radiolytic product: its measurable amounts appear after about 0.15 MGy and increase with dose to become about 0.1 g dm -3 at 1.7 MGy. Throughout the dose range studied, the HPLC gives for molecular weight 16,000-14,000 dalton, and the i.r. spectra show the presence of characteristic functional groups of CH 2, CH, CO -3, COO - and NH +4. Possible chemical nature of polymeric material and its origin are considered.

Low-dose radiation from 18F-FDG PET does not increase cancer frequency or shorten latency but reduces kidney disease in cancer-prone Trp53+/- mice

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

Taylor, Kristina; Lemon, Jennifer A.; Phan, Nghi

There is considerable interest in the health effects associated with low-level radiation exposure from medical imaging procedures. Concerns in the medical community that increased radiation exposure from imaging procedures may increase cancer risk among patients are confounded by research showing that low-dose radiation exposure can extend lifespan by increasing the latency period of some types of cancer. The most commonly used radiopharmaceutical for positron emission tomography (PET) scans is 2-[ 18F] fluoro-2-deoxy-d-glucose ( 18F-FDG), which exposes tissue to a low-dose, mixed radiation quality: 634 keV β+ and 511 keV γ-rays. The goal of this research was to investigate how modificationmore » of cancer risk associated with exposure to low-dose ionising radiation in cancer-prone Trp53+/- mice is influenced by radiation quality from PET. At 7-8 weeks of age, Trp53+/- female mice were exposed to one of five treatments: 0 Gy, 10 mGy γ-rays, 10 mGy 18F-FDG, 4 Gy γ-rays, 10 mGy 18F-FDG + 4 Gy γ-rays (n > 185 per group). The large 4-Gy radiation dose significantly reduced the lifespan by shortening the latency period of cancer and significantly increasing the number of mice with malignancies, compared with unirradiated controls. The 10 mGy γ-rays and 10 mGy PET doses did not significantly modify the frequency or latency period of cancer relative to unirradiated mice. Similarly, the PET scan administered prior to a large 4-Gy dose did not significantly modify the latency or frequency of cancer relative to mice receiving a dose of only 4 Gy. The relative biological effectiveness of radiation quality from 18F-FDG, with respect to malignancy, is approximately 1. Furthermore, when non-cancer endpoints were studied, it was found that the 10-mGy PET group had a significant reduction in kidney lesions (P < 0.021), indicating that a higher absorbed dose (20 ± 0.13 mGy), relative to the whole-body average, which occurs in specific tissues, may not be detrimental.« less

Low-dose radiation from 18F-FDG PET does not increase cancer frequency or shorten latency but reduces kidney disease in cancer-prone Trp53+/- mice

DOE PAGES

Taylor, Kristina; Lemon, Jennifer A.; Phan, Nghi; ...

2014-05-28

There is considerable interest in the health effects associated with low-level radiation exposure from medical imaging procedures. Concerns in the medical community that increased radiation exposure from imaging procedures may increase cancer risk among patients are confounded by research showing that low-dose radiation exposure can extend lifespan by increasing the latency period of some types of cancer. The most commonly used radiopharmaceutical for positron emission tomography (PET) scans is 2-[ 18F] fluoro-2-deoxy-d-glucose ( 18F-FDG), which exposes tissue to a low-dose, mixed radiation quality: 634 keV β+ and 511 keV γ-rays. The goal of this research was to investigate how modificationmore » of cancer risk associated with exposure to low-dose ionising radiation in cancer-prone Trp53+/- mice is influenced by radiation quality from PET. At 7-8 weeks of age, Trp53+/- female mice were exposed to one of five treatments: 0 Gy, 10 mGy γ-rays, 10 mGy 18F-FDG, 4 Gy γ-rays, 10 mGy 18F-FDG + 4 Gy γ-rays (n > 185 per group). The large 4-Gy radiation dose significantly reduced the lifespan by shortening the latency period of cancer and significantly increasing the number of mice with malignancies, compared with unirradiated controls. The 10 mGy γ-rays and 10 mGy PET doses did not significantly modify the frequency or latency period of cancer relative to unirradiated mice. Similarly, the PET scan administered prior to a large 4-Gy dose did not significantly modify the latency or frequency of cancer relative to mice receiving a dose of only 4 Gy. The relative biological effectiveness of radiation quality from 18F-FDG, with respect to malignancy, is approximately 1. Furthermore, when non-cancer endpoints were studied, it was found that the 10-mGy PET group had a significant reduction in kidney lesions (P < 0.021), indicating that a higher absorbed dose (20 ± 0.13 mGy), relative to the whole-body average, which occurs in specific tissues, may not be detrimental.« less

Cytoadherence and Genotype of Plasmodium falciparum Strains from Symptomatic Children in Franceville, Southeastern Gabon

PubMed Central

Touré, Fousseyni S.; Ouwe-Missi-Oukem-Boyer, Odile; Mezui-Me-Ndong, Jérôme; Ndong-Atome, Guy Roger; Bisvigou, Ulrick; Mazier, Dominique; Bisser, Sylvie

2007-01-01

Background: Plasmodium falciparum causes severe clinical manifestations by sequestering parasitized red blood cells (PRBC) in the microvasculature of major organs such as the brain. This sequestration results from PRBC adherence to vascular endothelial cells via erythrocyte membrane protein 1, a variant parasite surface antigen. Objective: To determine whether P. falciparum multiple genotype infection (MGI) is associated with stronger PRBC cytoadherence and greater clinical severity. Methods: Nested polymerase chain reaction was used to genotype P. falciparum isolates from symptomatic children and to distinguish between single genotype infection (SGI) and MGI. PRBC cytoadhesion was studied with cultured human lung endothelial cells. Results: Analysis of two highly polymorphic regions of the merozoite surface antigen (MSP)-1 and MSP-2 genes and a dimorphic region of the erythrocyte binding antigen-175 gene showed that 21.4% and 78.6% of the 42 children had SGI and MGI, respectively. It also showed that 37 (89%) of the 42 PRBC samples expressed MSP-1 allelic family K1. Cytoadherence values ranged from 58 to 1811 PRBC/mm2 of human lung endothelial cells monolayer in SGI and from 5 to 5744 PRBC/mm2 in MGI. MGI was not associated with higher cytoadherence values or with more severe malaria. Conclusions: These results suggested that infection of the same individual by multiple clones of P. falciparum does not significantly influence PRBC cytoadherence or disease severity and confirmed the predominance of the MSP-1 K1 genotype in southeastern Gabon. PMID:17607045

Estimation of mean glandular dose for patients who undergo mammography and studying the factors affecting it

NASA Astrophysics Data System (ADS)

Barzanje, Sana L. N. H.; Harki, Edrees M. Tahir Nury

2017-09-01

The objective of this study was to determine mean glandular dose (MGD) during diagnostic mammography. This study was done in two hospitals in Hawler city in Kurdistan -region /Iraq, the exposure parameters kVp and mAs was recorded for 40 patients under go mammography. The MGD estimated by multiplied ESD with normalized glandular dose (Dn). The ESD measured indirectly by measuring output radiation mGy/mAs by using PalmRAD 907 as a suitable detector (Gigger detector).the results; shown that the mean and its standard deviation of MGD for Screen Film Mammography and Digital Mammography are (0.95±0.18)mGy and (0.99±0.26)mGy, respectively. And there is a significant difference between MGD for Screen Film Mammography and Digital Mammography views (p≤0. 05). Also the mean value and its standard deviation of MGD for screen film mammography is (0.96±0.21) for CC projection and (1.03±0.3) mGy for MLO projection, but mean value and its standard deviation evaluated of MGD for digital mammography is (0.92±0.17) mGy for CC projection and (0.98±0.2) mGy for MLO projection. As well as, the effect of kVp and mAs in MGD were studied, shows that in general as kVp and mAs increased the MGD increased accordingly in both of mammography systems.

Diagnostic Accuracy of CT Enterography for Active Inflammatory Terminal Ileal Crohn Disease: Comparison of Full-Dose and Half-Dose Images Reconstructed with FBP and Half-Dose Images with SAFIRE.

PubMed

Gandhi, Namita S; Baker, Mark E; Goenka, Ajit H; Bullen, Jennifer A; Obuchowski, Nancy A; Remer, Erick M; Coppa, Christopher P; Einstein, David; Feldman, Myra K; Kanmaniraja, Devaraju; Purysko, Andrei S; Vahdat, Noushin; Primak, Andrew N; Karim, Wadih; Herts, Brian R

2016-08-01

Purpose To compare the diagnostic accuracy and image quality of computed tomographic (CT) enterographic images obtained at half dose and reconstructed with filtered back projection (FBP) and sinogram-affirmed iterative reconstruction (SAFIRE) with those of full-dose CT enterographic images reconstructed with FBP for active inflammatory terminal or neoterminal ileal Crohn disease. Materials and Methods This retrospective study was compliant with HIPAA and approved by the institutional review board. The requirement to obtain informed consent was waived. Ninety subjects (45 with active terminal ileal Crohn disease and 45 without Crohn disease) underwent CT enterography with a dual-source CT unit. The reference standard for confirmation of active Crohn disease was active terminal ileal Crohn disease based on ileocolonoscopy or established Crohn disease and imaging features of active terminal ileal Crohn disease. Data from both tubes were reconstructed with FBP (100% exposure); data from the primary tube (50% exposure) were reconstructed with FBP and SAFIRE strengths 3 and 4, yielding four datasets per CT enterographic examination. The mean volume CT dose index (CTDIvol) and size-specific dose estimate (SSDE) at full dose were 13.1 mGy (median, 7.36 mGy) and 15.9 mGy (median, 13.06 mGy), respectively, and those at half dose were 6.55 mGy (median, 3.68 mGy) and 7.95 mGy (median, 6.5 mGy). Images were subjectively evaluated by eight radiologists for quality and diagnostic confidence for Crohn disease. Areas under the receiver operating characteristic curves (AUCs) were estimated, and the multireader, multicase analysis of variance method was used to compare reconstruction methods on the basis of a noninferiority margin of 0.05. Results The mean AUCs with half-dose scans (FBP, 0.908; SAFIRE 3, 0.935; SAFIRE 4, 0.924) were noninferior to the mean AUC with full-dose FBP scans (0.908; P < .003). The proportion of images with inferior quality was significantly higher with all

Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure.

PubMed

Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc

2014-05-01

Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the HDTV algorithm shows the

Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure

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

Maier, Joscha, E-mail: joscha.maier@dkfz.de; Sawall, Stefan; Kachelrieß, Marc

2014-05-15

Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levelsmore » from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

PubMed

Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

2016-09-01

Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study

PubMed Central

Pearce, Mark S; Salotti, Jane A; Little, Mark P; McHugh, Kieran; Lee, Choonsik; Kim, Kwang Pyo; Howe, Nicola L; Ronckers, Cecile M; Rajaraman, Preetha; Craft, Alan W; Parker, Louise; de González, Amy Berrington

2012-01-01

Summary Background Although CT scans are very useful clinically, potential cancer risks exist from associated ionising radiation, in particular for children who are more radiosensitive than adults. We aimed to assess the excess risk of leukaemia and brain tumours after CT scans in a cohort of children and young adults. Methods In our retrospective cohort study, we included patients without previous cancer diagnoses who were first examined with CT in National Health Service (NHS) centres in England, Wales, or Scotland (Great Britain) between 1985 and 2002, when they were younger than 22 years of age. We obtained data for cancer incidence, mortality, and loss to follow-up from the NHS Central Registry from Jan 1, 1985, to Dec 31, 2008. We estimated absorbed brain and red bone marrow doses per CT scan in mGy and assessed excess incidence of leukaemia and brain tumours cancer with Poisson relative risk models. To avoid inclusion of CT scans related to cancer diagnosis, follow-up for leukaemia began 2 years after the first CT and for brain tumours 5 years after the first CT. Findings During follow-up, 74 of 178 604 patients were diagnosed with leukaemia and 135 of 176 587 patients were diagnosed with brain tumours. We noted a positive association between radiation dose from CT scans and leukaemia (excess relative risk [ERR] per mGy 0·036, 95% CI 0·005–0·120; p=0·0097) and brain tumours (0·023, 0·010–0·049; p<0·0001). Compared with patients who received a dose of less than 5 mGy, the relative risk of leukaemia for patients who received a cumulative dose of at least 30 mGy (mean dose 51·13 mGy) was 3·18 (95% CI 1·46–6·94) and the relative risk of brain cancer for patients who received a cumulative dose of 50–74 mGy (mean dose 60·42 mGy) was 2·82 (1·33–6·03). Interpretation Use of CT scans in children to deliver cumulative doses of about 50 mGy might almost triple the risk of leukaemia and doses of about 60 mGy might triple the risk of brain

Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study.

PubMed

Pearce, Mark S; Salotti, Jane A; Little, Mark P; McHugh, Kieran; Lee, Choonsik; Kim, Kwang Pyo; Howe, Nicola L; Ronckers, Cecile M; Rajaraman, Preetha; Sir Craft, Alan W; Parker, Louise; Berrington de González, Amy

2012-08-04

Although CT scans are very useful clinically, potential cancer risks exist from associated ionising radiation, in particular for children who are more radiosensitive than adults. We aimed to assess the excess risk of leukaemia and brain tumours after CT scans in a cohort of children and young adults. In our retrospective cohort study, we included patients without previous cancer diagnoses who were first examined with CT in National Health Service (NHS) centres in England, Wales, or Scotland (Great Britain) between 1985 and 2002, when they were younger than 22 years of age. We obtained data for cancer incidence, mortality, and loss to follow-up from the NHS Central Registry from Jan 1, 1985, to Dec 31, 2008. We estimated absorbed brain and red bone marrow doses per CT scan in mGy and assessed excess incidence of leukaemia and brain tumours cancer with Poisson relative risk models. To avoid inclusion of CT scans related to cancer diagnosis, follow-up for leukaemia began 2 years after the first CT and for brain tumours 5 years after the first CT. During follow-up, 74 of 178,604 patients were diagnosed with leukaemia and 135 of 176,587 patients were diagnosed with brain tumours. We noted a positive association between radiation dose from CT scans and leukaemia (excess relative risk [ERR] per mGy 0·036, 95% CI 0·005-0·120; p=0·0097) and brain tumours (0·023, 0·010-0·049; p<0·0001). Compared with patients who received a dose of less than 5 mGy, the relative risk of leukaemia for patients who received a cumulative dose of at least 30 mGy (mean dose 51·13 mGy) was 3·18 (95% CI 1·46-6·94) and the relative risk of brain cancer for patients who received a cumulative dose of 50-74 mGy (mean dose 60·42 mGy) was 2·82 (1·33-6·03). Use of CT scans in children to deliver cumulative doses of about 50 mGy might almost triple the risk of leukaemia and doses of about 60 mGy might triple the risk of brain cancer. Because these cancers are relatively rare, the cumulative

PC-ANN assisted to the determination of Vanadium (IV) ion using an optical sensor based on immobilization of Eriochorome Cyanine R on a triacetylcellulose film.

PubMed

Bordbar, Mohammad Mahdi; Khajehsharifi, Habibollah; Solhjoo, Aida

2015-01-01

More detailed analytical studies of an optical sensor based on immobilization of Eriochorome Cyanine R (ECR) on a triacetylcellulose film have been described to determine Vanadium (IV) ions in some real samples. The sensor based on complex formation between Vanadium (IV) ions and ECR in acidic media caused the color of the film to change from violet to blue along with the appearance of a strong peak appears at 595 nm. At the optimal conditions, the calibration curve showed a linear range of 9.90×10(-7)-8.25×10(-5)mol L(-1). Vanadium (IV) ions can be detected with a detection limit of 1.03×10(-7)mol L(-1) within 15 min depending on its concentration. Also, the working range was improved by using PC-ANN algorithm. The sensor could regenerate with dilute acetic acid solution and could be completely reversible. The proposed sensor was successfully applied for determining V (IV) ions in environmental water and tea leaves. Copyright © 2015 Elsevier B.V. All rights reserved.

Hydrology and sediment budget of Los Laureles Canyon, Tijuana, MX: Modelling channel, gully, and rill erosion with 3D photo-reconstruction, CONCEPTS, and AnnAGNPS

NASA Astrophysics Data System (ADS)

Taniguchi, Kristine; Gudiño, Napoleon; Biggs, Trent; Castillo, Carlos; Langendoen, Eddy; Bingner, Ron; Taguas, Encarnación; Liden, Douglas; Yuan, Yongping

2015-04-01

Several watersheds cross the US-Mexico boundary, resulting in trans-boundary environmental problems. Erosion in Tijuana, Mexico, increases the rate of sediment deposition in the Tijuana Estuary in the United States, altering the structure and function of the ecosystem. The well-being of residents in Tijuana is compromised by damage to infrastructure and homes built adjacent to stream channels, gully formation in dirt roads, and deposition of trash. We aim to understand the dominant source of sediment contributing to the sediment budget of the watershed (channel, gully, or rill erosion), where the hotspots of erosion are located, and what the impact of future planned and unplanned land use changes and Best Management Practices (BMPs) will be on sediment and storm flow. We will be using a mix of field methods, including 3D photo-reconstruction of stream channels, with two models, CONCEPTS and AnnAGNPS to constrain estimates of the sediment budget and impacts of land use change. Our research provides an example of how 3D photo-reconstruction and Structure from Motion (SfM) can be used to model channel evolution.

Process Design and Cost Estimating Algorithms for the Computer Assisted Procedure for Design and Evaluation of Wastewater Treatment Systems (CAPDET).

DTIC Science & Technology

1982-01-01

mg/l. 2.1.9.1.3.3 Nitrogen, I Mg 1. 2.1.9.1.3.4 Phosphorus (total and soluble), ag/l. 2.1.9.1.3.5 Oils and greases, mg/l. 2.1.9.1.3.6 Heavy metals , mg...greases, mg/I. 2.1.10.1.3.6 Heavy metals , m/l. 2.1.10.1.3.7 Toxic or special characteristics (e.g., phenols), mg/I. 2.1.10.1.3.8 Temperature, OF or °C...1 mg/l. 2.1.11.1.3.4 Phosphorus (total and soluble), mg/I. 2.1.11.1.3.5 Oils and greases, mgl. 2.1.11.1.3.6 Heavy metals , mg/l. 2.1.11.1.3.7 Toxic or

Combination Chemotherapy in Treating Young Patients With Newly Diagnosed T-Cell Acute Lymphoblastic Leukemia or T-cell Lymphoblastic Lymphoma

ClinicalTrials.gov

2018-01-24

Acute Lymphoblastic Leukemia; Adult T Acute Lymphoblastic Leukemia; Ann Arbor Stage II Adult T-Cell Leukemia/Lymphoma; Ann Arbor Stage II Childhood Lymphoblastic Lymphoma; Ann Arbor Stage II Contiguous Adult Lymphoblastic Lymphoma; Ann Arbor Stage II Non-Contiguous Adult Lymphoblastic Lymphoma; Ann Arbor Stage III Adult Lymphoblastic Lymphoma; Ann Arbor Stage III Adult T-Cell Leukemia/Lymphoma; Ann Arbor Stage III Childhood Lymphoblastic Lymphoma; Ann Arbor Stage IV Adult Lymphoblastic Lymphoma; Ann Arbor Stage IV Adult T-Cell Leukemia/Lymphoma; Ann Arbor Stage IV Childhood Lymphoblastic Lymphoma; Childhood T Acute Lymphoblastic Leukemia; Untreated Adult Acute Lymphoblastic Leukemia; Untreated Childhood Acute Lymphoblastic Leukemia

Doxorubicin Hydrochloride, Vinblastine, Dacarbazine, Brentuximab Vedotin, and Nivolumab in Treating Patients With Stage I-II Hodgkin Lymphoma

ClinicalTrials.gov

2018-04-30

Ann Arbor Stage I Hodgkin Lymphoma; Ann Arbor Stage IA Hodgkin Lymphoma; Ann Arbor Stage IB Hodgkin Lymphoma; Ann Arbor Stage II Hodgkin Lymphoma; Ann Arbor Stage IIA Hodgkin Lymphoma; Ann Arbor Stage IIB Hodgkin Lymphoma

Cryogenic electrical properties of irradiated cyanate ester/epoxy insulation for fusion magnets

NASA Astrophysics Data System (ADS)

Li, X.; Wu, Z. X.; Li, J.; Xu, D.; Liu, H. M.; Huang, R. J.; Li, L. F.

2017-12-01

The insulation materials used in high field fusion magnets require excellent mechanical properties, high electrical breakdown strength, good thermal conductivity and high radiation tolerance. Previous investigations showed that cyanate ester/epoxy (CE/EP) insulation material, a candidate insulation for fusion magnets, can maintain good mechanical performance at cryogenic temperature after 10 MGy irradiation and has a much longer pot life than traditional epoxy insulation material. In order to quantify the electrical properties of the CE/EP insulation material at low temperature, a cryogenic electrical property testing system cooled by a G-M cryocooler was developed for this study. An insulation material with 40% cyanate ester and 60% epoxy was subjected to 60Co γ-ray irradiation in air at ambient temperature with a dose rate of 300 Gy/min, and total doses of 1 MGy, 5 MGy and 10 MGy. The electrical breakdown strength of this CE/EP insulation material was measured before and after irradiation. The results show that cryogenic temperature has a positive effect on the electrical breakdown strength of this composite, while the influence of 60Co γ-ray irradiation is not obvious at 6.1 K.

Disease model curation improvements at Mouse Genome Informatics

PubMed Central

Bello, Susan M.; Richardson, Joel E.; Davis, Allan P.; Wiegers, Thomas C.; Mattingly, Carolyn J.; Dolan, Mary E.; Smith, Cynthia L.; Blake, Judith A.; Eppig, Janan T.

2012-01-01

Optimal curation of human diseases requires an ontology or structured vocabulary that contains terms familiar to end users, is robust enough to support multiple levels of annotation granularity, is limited to disease terms and is stable enough to avoid extensive reannotation following updates. At Mouse Genome Informatics (MGI), we currently use disease terms from Online Mendelian Inheritance in Man (OMIM) to curate mouse models of human disease. While OMIM provides highly detailed disease records that are familiar to many in the medical community, it lacks structure to support multilevel annotation. To improve disease annotation at MGI, we evaluated the merged Medical Subject Headings (MeSH) and OMIM disease vocabulary created by the Comparative Toxicogenomics Database (CTD) project. Overlaying MeSH onto OMIM provides hierarchical access to broad disease terms, a feature missing from the OMIM. We created an extended version of the vocabulary to meet the genetic disease-specific curation needs at MGI. Here we describe our evaluation of the CTD application, the extensions made by MGI and discuss the strengths and weaknesses of this approach. Database URL: http://www.informatics.jax.org/ PMID:22434831

TLD assessment of mouse dosimetry during microCT imaging

PubMed Central

Figueroa, Said Daibes; Winkelmann, Christopher T.; Miller, William H.; Volkert, Wynn A.; Hoffman, Timothy J.

2008-01-01

Advances in laboratory animal imaging have provided new resources for noninvasive biomedical research. Among these technologies is microcomputed tomography (microCT) which is widely used to obtain high resolution anatomic images of small animals. Because microCT utilizes ionizing radiation for image formation, radiation exposure during imaging is a concern. The objective of this study was to quantify the radiation dose delivered during a standard microCT scan. Radiation dose was measured using thermoluminescent dosimeters (TLDs), which were irradiated employing an 80 kVp x-ray source, with 0.5 mm Al filtration and a total of 54 mA s for a full 360 deg rotation of the unit. The TLD data were validated using a 3.2 cm3 CT ion chamber probe. TLD results showed a single microCT scan air kerma of 78.0±5.0 mGy when using a poly(methylmethacrylate) (PMMA) anesthesia support module and an air kerma of 92.0±6.0 mGy without the use of the anesthesia module. The validation CT ion chamber study provided a measured radiation air kerma of 81.0±4.0 mGy and 97.0±5.0 mGy with and without the PMMA anesthesia module, respectively. Internal TLD analysis demonstrated an average mouse organ radiation absorbed dose of 76.0±5.0 mGy. The author’s results have defined x-ray exposure for a routine microCT study which must be taken into consideration when performing serial molecular imaging studies involving the microCT imaging modality. PMID:18841837

Optimal conditions of LDR to protect the kidney from diabetes

PubMed Central

Cheng, Jie; Li, Fengsheng; Cui, Jiuwei; Guo, Weiying; Li, Cai; Li, Wei; Wang, Guixia; Xing, Xiao; Gao, Ying; Ge, Yuanyuan; Wang, Guanjun; Cai, Lu

2014-01-01

Aims We reported the attenuation of diabetes-induced renal dysfunction by exposure to multiple low-dose radiation (LDR) at 25 mGy every other day via suppressing renal oxidative damage. We here explored the optimal conditions of LDR to protect the kidney from diabetes. Main methods Type 1 diabetic mice were induced with multiple injections of low-dose streptozotocin in male C57BL/6J mice. Diabetic mice received whole body X-irradiation at dose of 12.5, 25 or 50 mGy every other day for either 4 or 8 weeks. Age-matched normal mice were similarly irradiated at the dose of 25 mGy for 4 or 8 weeks. The renal function and histopathological changes were examined at the 4th and 8th week of the study. Key findings Diabetes induced renal dysfunction, shown by the decreased creatinine and increased microalbumin in urinary. Renal oxidative damage, detected by protein nitration and lipid oxidation, and remodeling, reflected by increased expression of connective tissue growth factor, collagen IV and fibronectin, were significantly increased in diabetic mice. All these renal pathological and function changes in diabetic mice were significantly attenuated by exposure to LDR at all regimens, among which, however, exposure to LDR at 12.5 mGy for 8 weeks provided the best preventive effect on the kidney of diabetic mice. Significance Our results suggest that whole-body LDR at 12.5 mGy every other day for 8 weeks is the optimal condition of LDR to protect the kidney from diabetes. PMID:24631139

A gradient of radioactive contamination in Dolon village near the SNTS and comparison of computed dose values with instrumental estimates for the 29 August, 1949 nuclear test.

PubMed

Stepanenko, Valeriy F; Hoshi, Masaharu; Dubasov, Yuriy V; Sakaguchi, Aya; Yamamoto, Masayoshi; Orlov, Mark Y; Bailiff, Ian K; Ivannikov, Alexander I; Skvortsov, Valeriy G; Iaskova, Elena K; Kryukova, Irina G; Zhumadilov, Kassym S; Endo, Satoru; Tanaka, Kenichi; Apsalikov, Kazbek N; Gusev, Boris I

2006-02-01

Spatial distributions of soil contamination by 137Cs (89 sampling points) and 239+240Pu (76 points) near and within Dolon village were analyzed. An essential exponential decrease of contamination was found in Dolon village: the distance of a half reduction in contamination is about 0.87-1.25 km (in a northwest-southeast direction from the supposed centerline of the radioactive trace). This fact is in agreement with the available exposure rate measurements near Dolon (September 1949 archive data): on the basis of a few measurements the pattern of the trace was estimated to comprise a narrow 2 km corridor of maximum exposure rate. To compare computed external doses in air with local dose estimates by retrospective luminescence dosimetry (RLD) the gradient of radioactive soil contamination within the village was accounted for. The computed dose associated with the central axis of the trace was found to be equal to 2260 mGy (calculations based on archive exposure rate data). Local doses near the RLD sampling points (southeast of the village) were calculated to be in the range 466-780 mGy (averaged value: 645+/-70 mGy), which is comparable with RLD data (averaged value 460+/-92 mGy with range 380-618 mGy). A comparison of the computed mean dose in the settlement with dose estimates by ESR tooth enamel dosimetry makes it possible to estimate the "upper level" of the "shielding and behavior" factor in dose reduction for inhabitants of Dolon village which was found to be 0.28+/-0.068.

Dosimetric Quantities for Computed Tomography Examinations of Paediatric Patients on the Thoracic and Abdominal Regions

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

Flores-M, E.; Gamboa de Buen, I.; Buenfil, A. E.

Computed Tomography (CT) is a high dose X ray imaging procedure and its use has rapidly increased in the last two decades fueled by the development of helical CT. The aim of this study is to present values of the dosimetric quantities for CT paediatric examinations of thoracic and abdominal regions. The protocols studied were those of chest, lung-mediastine, chest-abdomen, pulmonary high resolution and mediastine-abdomen, which are the more common examinations performed at ''Hospital Infantil de Mexico Federico Gomez'' in the thoracic-abdominal region. The measurements were performed on a Siemens SOMATOM Sensation 16 CT Scanner and the equipment used wasmore » a CT pencil ionization chamber, connected to an electrometer. This system was calibrated for RQT9 CT beam quality. A PMMA head phantom with diameter of 16 cm and length of 15 cm was also used. The dosimetric quantities measured were the weighted air kerma index (C{sub w}), the volumetric dose index (C{sub vol}) and the CT air kerma-length product. It was found that the pulmonary high resolution examination presented the highest values for the C{sub w}(31.1 mGy) and C{sub vol}(11.1 mGy). The examination with the lowest values of these two quantities was the chest-abdomen protocol with 10.5 mGy for C{sub w} and 5.5 mGy for C{sub vol}. However, this protocol presented the highest value for P{sub KL,CT}(282.2 mGy cm) when considering the average clinical length of the examinations.« less

Comparison of two different artificial neural networks for prostate biopsy indication in two different patient populations.

PubMed

Stephan, Carsten; Xu, Chuanliang; Finne, Patrik; Cammann, Henning; Meyer, Hellmuth-Alexander; Lein, Michael; Jung, Klaus; Stenman, Ulf-Hakan

2007-09-01

Different artificial neural networks (ANNs) using total prostate-specific antigen (PSA) and percentage of free PSA (%fPSA) have been introduced to enhance the specificity of prostate cancer detection. The applicability of independently trained ANN and logistic regression (LR) models to different populations regarding the composition (screening versus referred) and different PSA assays has not yet been tested. Two ANN and LR models using PSA (range 4 to 10 ng/mL), %fPSA, prostate volume, digital rectal examination findings, and patient age were tested. A multilayer perceptron network (MLP) was trained on 656 screening participants (Prostatus PSA assay) and another ANN (Immulite-based ANN [iANN]) was constructed on 606 multicentric urologically referred men. These and other assay-adapted ANN models, including one new iANN-based ANN, were used. The areas under the curve for the iANN (0.736) and MLP (0.745) were equal but showed no differences to %fPSA (0.725) in the Finnish group. Only the new iANN-based ANN reached a significant larger area under the curve (0.77). At 95% sensitivity, the specificities of MLP (33%) and the new iANN-based ANN (34%) were significantly better than the iANN (23%) and %fPSA (19%). Reverse methodology using the MLP model on the referred patients revealed, in contrast, a significant improvement in the areas under the curve for iANN and MLP (each 0.83) compared with %fPSA (0.70). At 90% and 95% sensitivity, the specificities of all LR and ANN models were significantly greater than those for %fPSA. The ANNs based on different PSA assays and populations were mostly comparable, but the clearly different patient composition also allowed with assay adaptation no unbiased ANN application to the other cohort. Thus, the use of ANNs in other populations than originally built is possible, but has limitations.

The effects of γ-ray on charging behaviour using polyimide

NASA Astrophysics Data System (ADS)

Qin, Sichen; Tu, Youping; Tan, Tian; Wang, Shaohe; Yuan, Zhikang; Wang, Cong; Li, Laifeng; Wu, Zhixiong

2018-06-01

Insulation material is a key component of electrical equipment in satellites; its electrical properties determine the reliability and lifetime of the whole satellite. High-energy radioactive rays in space affect the molecular structure of the polymeric insulating materials. Under the action of plasma, high energy particles, along with the magnetic fields experienced in orbits, electric charges get injected into and trapped by the insulating material creating distortions in the electric field and even electrostatic discharges. Polyimides have been widely used for insulation in spacecraft. Choosing Co-60 gamma ray with irradiation doses of 1 MGy and 5 MGy to simulate the radiation environment of space, we investigated the effect of radiation on charging behaviour. The thermal stimulated current (TSC) from a high electric field over a wide range of temperatures was measured from which the activation energy was calculated. These results for the two sources show that the percentage increase in total charge was 133.3% and 119.4%. The γ, β 3, and α charge peaks of specimens after an irradiation dose of 1 MGy rose. In comparison, the β 2 peak of the 5 MGy-dosed specimens was enhanced. Also, there is almost no change in the γ, β 3, and α peaks. To understand the mechanism behind the TSC changes, the resulting physicochemical characteristics of an irradiated specimen were observed employing various analyses of chemical characteristics (x-ray photoelectron spectroscopy, differential scanning calorimetry and x-ray diffraction). Compared with the non-dosed specimen, the relative content of C–N and the glass transition temperature of the 1 MGy sample decreased, and the crystallinity increased, thus increasing the γ and α peak intensities. Compared with the 1 MGy sample, only the glass transition temperature had risen, thereby enhancing the β peak intensity. With the foregoing, a theoretical base for the selection and modification of insulation materials for

Characterization of MOSFET dosimeters for low-dose measurements in maxillofacial anthropomorphic phantoms.

PubMed

Koivisto, Juha H; Wolff, Jan E; Kiljunen, Timo; Schulze, Dirk; Kortesniemi, Mika

2015-07-08

The aims of this study were to characterize reinforced metal-oxide-semiconductor field-effect transistor (MOSFET) dosimeters to assess the measurement uncertainty, single exposure low-dose limit with acceptable accuracy, and the number of exposures required to attain the corresponding limit of the thermoluminescent dosimeters (TLD). The second aim was to characterize MOSFET dosimeter sensitivities for two dental photon energy ranges, dose dependency, dose rate dependency, and accumulated dose dependency. A further aim was to compare the performance of MOSFETs with those of TLDs in an anthropomorphic phantom head using a dentomaxillofacial CBCT device. The uncertainty was assessed by exposing 20 MOSFETs and a Barracuda MPD reference dosimeter. The MOSFET dosimeter sensitivities were evaluated for two photon energy ranges (50-90 kVp) using a constant dose and polymethylmethacrylate backscatter material. MOSFET and TLD comparative point-dose measurements were performed on an anthropomorphic phantom that was exposed with a clinical CBCT protocol. The MOSFET single exposure low dose limit (25% uncertainty, k = 2) was 1.69 mGy. An averaging of eight MOSFET exposures was required to attain the corresponding TLD (0.3 mGy) low-dose limit. The sensitivity was 3.09 ± 0.13 mV/mGy independently of the photon energy used. The MOSFET dosimeters did not present dose or dose rate sensitivity but, however, presented a 1% decrease of sensitivity per 1000 mV for accumulated threshold voltages between 8300 mV and 17500 mV. The point doses in an anthropomorphic phantom ranged for MOSFETs between 0.24 mGy and 2.29 mGy and for TLDs between 0.25 and 2.09 mGy, respectively. The mean difference was -8%. The MOSFET dosimeters presented statistically insignificant energy dependency. By averaging multiple exposures, the MOSFET dosimeters can achieve a TLD-comparable low-dose limit and constitute a feasible method for diagnostic dosimetry using anthropomorphic phantoms. However, for single in

SU-F-I-36: In-Utero Dose Measurements Within Postmortem Subjects for Estimating Fetal Doses in Pregnant Patients Examined with Pulmonary Embolism, Trauma, and Appendicitis CT

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

Lipnharski, I; Quails, N; Carranza, C

Purpose: The imaging of pregnant patients is medically necessary in certain clinical situations. The purpose of this work was to directly measure uterine doses in a cadaver scanned with CT protocols commonly performed on pregnant patients in order to estimate fetal dose and assess potential risk. Method: One postmortem subject was scanned on a 320-slice CT scanner with standard pulmonary embolism, trauma, and appendicitis protocols. All protocols were performed with the scan parameters and ranges currently used in clinical practice. Exams were performed both with and without iterative reconstruction to highlight the dose savings potential. Optically stimulated luminescent dosimeters (OSLDs)more » were inserted into the uterus in order to approximate fetal doses. Results: In the pulmonary embolism CT protocol, the uterus is outside of the primary beam, and the dose to the uterus was under 1 mGy. In the trauma and appendicitis protocols, the uterus is in the primary beam, the fetal dose estimates were 30.5 mGy for the trauma protocol, and 20.6 mGy for the appendicitis protocol. Iterative reconstruction reduced fetal doses by 30%, with uterine doses at 21.3 for the trauma and 14.3 mGy for the appendicitis protocol. Conclusion: Fetal doses were under 1 mGy when exposed to scatter radiation, and under 50 mGy when exposed to primary radiation with the trauma and appendicitis protocols. Consistent with the National Council on Radiation Protection & Measurements (NCRP) and the International Commission on Radiological Protection (ICRP), these doses exhibit a negligible risk to the fetus, with only a small increased risk of cancer. Still, CT scans are not recommended during pregnancy unless the benefits of the exam clearly outweigh the potential risk. Furthermore, when possible, pregnant patients should be examined on CT scanners equipped with iterative reconstruction in order to keep patient doses as low as reasonable achievable.« less

TU-H-CAMPUS-IeP1-04: Combined Organ Dose for Digital Subtraction Angiography and Computed Tomography Using Monte Carlo Simulation

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

Sakabe, D; Ohno, T; Araki, F

Purpose: The purpose of this study was to evaluate the combined organ dose of digital subtraction angiography (DSA) and computed tomography (CT) using a Monte Carlo (MC) simulation on the abdominal intervention. Methods: The organ doses for DSA and CT were obtained with MC simulation and actual measurements using fluorescent-glass dosimeters at 7 abdominal portions in an Alderson-Rando phantom. DSA was performed from three directions: posterior anterior (PA), right anterior oblique (RAO), and left anterior oblique (LAO). The organ dose with MC simulation was compared with actual radiation dose measurements. Calculations for the MC simulation were carried out with themore » GMctdospp (IMPS, Germany) software based on the EGSnrc MC code. Finally, the combined organ dose for DSA and CT was calculated from the MC simulation using the X-ray conditions of a patient with a diagnosis of hepatocellular carcinoma. Results: For DSA from the PA direction, the organ doses for the actual measurements and MC simulation were 2.2 and 2.4 mGy/100 mAs at the liver, respectively, and 3.0 and 3.1 mGy/100 mAs at the spinal cord, while for CT, the organ doses were 15.2 and 15.1 mGy/100 mAs at the liver, and 14.6 and 13.5 mGy/100 mAs at the spinal cord. The maximum difference in organ dose between the actual measurements and the MC simulation was 11.0% of the spleen at PA, 8.2% of the spinal cord at RAO, and 6.1% of left kidney at LAO with DSA and 9.3% of the stomach with CT. The combined organ dose (4 DSAs and 6 CT scans) with the use of actual patient conditions was found to be 197.4 mGy for the liver and 205.1 mGy for the spinal cord. Conclusion: Our method makes it possible to accurately assess the organ dose to patients for abdominal intervention with combined DSA and CT.« less

Dose responses for adaption to low doses of (60)Co gamma rays and (3)H beta particles in normal human fibroblasts.

PubMed

Broome, E J; Brown, D L; Mitchel, R E J

2002-08-01

The dose response for adaption to radiation at low doses was compared in normal human fibroblasts (AG1522) exposed to either (60)Co gamma rays or (3)H beta particles. Cells were grown in culture to confluence and exposed at either 37 degrees C or 0 degrees C to (3)H beta-particle or (60)Co gamma-ray adapting doses ranging from 0.1 mGy to 500 mGy. These cells, and unexposed control cells, were allowed to adapt during a fixed 3-h, 37 degrees C incubation prior to a 4-Gy challenge dose of (60)Co gamma rays. Adaption was assessed by measuring micronucleus frequency in cytokinesis-blocked, binucleate cells. No adaption was detected in cells exposed to (60)Co gamma radiation at 37 degrees C after a dose of 0.1 mGy given at a low dose rate or to 500 mGy given at a high dose rate. However, low-dose-rate exposure (1-3 mGy/min) to any dose between 1 and 500 mGy from either radiation, delivered at either temperature, caused cells to adapt and reduced the micronucleus frequency that resulted from the subsequent 4-Gy exposure. Within this dose range, the magnitude of the reduction was the same, regardless of the dose or radiation type. These results demonstrate that doses as low as (on average) about one track per cell (1 mGy) produce the same maximum adaptive response as do doses that deposit many tracks per cell, and that the two radiations were not different in this regard. Exposure at a temperature where metabolic processes, including DNA repair, were inactive (0 degrees C) did not alter the result, indicating that the adaptive response is not sensitive to changes in the accumulation of DNA damage within this range. The results also show that the RBE for low doses of tritium beta-particle radiation is 1, using adaption as the end point.

SU-C-12A-05: Radiation Dose in High-Pitch Pediatric Cardiac CTA: Correlation Between Lung Dose and CTDIvol, DLP, and Size Specific Dose Estimates (SSDE)

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

Wang, J; Kino, A; Newman, B

2014-06-01

Purpose: To investigate the radiation dose for pediatric high pitch cardiac CTA Methods: A total of 14 cases were included in this study, with mean age of 6.2 years (ranges from 2 months to 15 years). Cardiac CTA was performed using a dual-source CT system (Definition Flash, Siemens). Tube voltage (70, 80 and 100kV) was chosen based on patient weight. All patients were scanned using a high-pitch spiral mode (pitch ranges from 2.5 to 3) with tube current modulation technique (CareDose4D, Siemens). For each case, the three dimensional dose distributions were calculated using a Monte Carlo software package (IMPACT-MC, CTmore » Image GmbH). Scanning parameters of each exam, including tube voltage, tube current, beamshaping filters, beam collimation, were defined in the Monte Carlo calculation. Tube current profile along projection angles was obtained from projection data of each tube, which included data within the over-scanning range along z direction. The volume of lungs was segmented out with CT images (3DSlicer). Lung doses of all patients were calculated and compared with CTDIvol, DLP, and SSDE. Results: The average (range) of CTDIvol, DLP and SSDE of all patients was 1.19 mGy (0.58 to 3.12mGy), 31.54 mGy*cm (12.56 to 99 mGy*cm), 2.26 mGy (1.19 to 6.24 mGy), respectively. Radiation dose to the lungs ranged from 0.83 to 4.18 mGy. Lung doses correlated with CTDIvol, DLP and SSDE with correlation coefficients(k) at 0.98, 0.93, and 0.99. However, for the cases with CTDIvol less than 1mGy, only SSDE preserved a strong correlation with lung doses (k=0.83), while much weaker correlations were found for CTDIvol (k=0.29) and DLP (k=-0.47). Conclusion: Lung doses to pediatric patients during Cardiac CTA were estimated. SSDE showed the most robust correlation with lung doses in contrast to CTDIvol and DLP.« less

TU-D-209-01: Dosimetry of Diagnostic Work Up Mammography

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

Jallow, N; Sechopoulos, I

2016-06-15

Purpose: To investigate patient average glandular dose (AGD) characteristics of diagnostic mammography. Methods: The techniques used to image 14420 patients who received diagnostic work up mammography from October 2008 to December 2014 at one academic hospital were retrospectively collected. The most common diagnostic views and the techniques used for each according to compressed breast thickness were determined. For all techniques, 1st half value layer and air kerma output per tube current-exposure time product were measured; then the incident air kerma for each acquisition was calculated. The values for normalized glandular dose (DgN) were obtained with a validated Monte Carlo simulationmore » of mammographic acquisition. The mono-energetic DgN results were combined according to relative fluence using the TASMICS model to obtain DgN coefficients for each spectrum. The spectral DgN and calculated incident air kerma were used to estimate AGD of patients with breast thickness ranging from 2 to 8 cm. Results: The most common views utilized during diagnostic mammography were magnification craniocaudal (24%), magnification mediolateral (19%), spot craniocaudal (28%), and spot mediolateral oblique (24%). The AGD increased with increasing breast thickness for both the magnification and spot views. The AGD for a 5.5 cm thick breast was approximately 6.8 mGy and 2.2 mGy for the magnification and spot views, respectively. The AGD ranged from 3.6 mGy to 6.8 mGy for the magnification views and from 1.0 mGy to 3.1 mGy for spot views. The difference in AGD between the two magnification views or the two spot views was not significant. Conclusion: These results provide information on breast dose to which screening recalled women are exposed to. In addition to understanding the dose used for common clinical imaging tests, this data could be used when comparing use of mammography for diagnostic workup to other potential modalities, such as breast tomosynthesis and breast CT.« less

Fetal shielding combined with state of the art CT dose reduction strategies during maternal chest CT.

PubMed

Chatterson, Leslie C; Leswick, David A; Fladeland, Derek A; Hunt, Megan M; Webster, Stephen; Lim, Hyun

2014-07-01

Custom bismuth-antimony shields were previously shown to reduce fetal dose by 53% on an 8DR (detector row) CT scanner without dynamic adaptive section collimation (DASC), automatic tube current modulation (ATCM) or adaptive statistical iterative reconstruction (ASiR). The purpose of this study is to compare the effective maternal and average fetal organ dose reduction both with and without bismuth-antimony shields on a 64DR CT scanner using DASC, ATCM and ASiR during maternal CTPA. A phantom with gravid prosthesis and a bismuth-antimony shield were used. Thermoluminescent dosimeters (TLDs) measured fetal radiation dose. The average fetal organ dose and effective maternal dose were determined using 100 kVp, scanning from the lung apices to the diaphragm utilizing DASC, ATCM and ASiR on a 64DR CT scanner with and without shielding in the first and third trimester. Isolated assessment of DASC was done via comparing a new 8DR scan without DASC to a similar scan on the 64DR with DASC. Average third trimester unshielded fetal dose was reduced from 0.22 mGy ± 0.02 on the 8DR to 0.13 mGy ± 0.03 with the conservative 64DR protocol that included 30% ASiR, DASC and ATCM (42% reduction, P<0.01). Use of a shield further reduced average third trimester fetal dose to 0.04 mGy ± 0.01 (69% reduction, P<0.01). The average fetal organ dose reduction attributable to DASC alone was modest (6% reduction from 0.17 mGy ± 0.02 to 0.16 mGy ± 0.02, P=0.014). First trimester fetal organ dose on the 8DR protocol was 0.07 mGy ± 0.03. This was reduced to 0.05 mGy ± 0.03 on the 64DR protocol without shielding (30% reduction, P=0.009). Shields further reduced this dose to below accurately detectable levels. Effective maternal dose was reduced from 4.0 mSv on the 8DR to 2.5 mSv on the 64DR scanner using the conservative protocol (38% dose reduction). ASiR, ATCM and DASC combined significantly reduce effective maternal and fetal organ dose during CTPA. Shields continue to be an effective

Oxygen vacancies controlled multiple magnetic phases in epitaxial single crystal Co0.5(Mg0.55Zn0.45)0.5O1-v thin films

PubMed Central

Zhu, Dapeng; Cao, Qiang; Qiao, Ruimin; Zhu, Shimeng; Yang, Wanli; Xia, Weixing; Tian, Yufeng; Liu, Guolei; Yan, Shishen

2016-01-01

High quality single-crystal fcc-Cox(MgyZn1-y)1-xO1-v epitaxial thin films with high Co concentration up to x = 0.5 have been fabricated by molecular beam epitaxy. Systematic magnetic property characterization and soft X-ray absorption spectroscopy analysis indicate that the coexistence of ferromagnetic regions, superparamagnetic clusters, and non-magnetic boundaries in the as-prepared Cox(MgyZn1-y)1-xO1-v films is a consequence of the intrinsic inhomogeneous distribution of oxygen vacancies. Furthermore, the relative strength of multiple phases could be modulated by controlling the oxygen partial pressure during sample preparation. Armed with both controllable magnetic properties and tunable band-gap, Cox(MgyZn1-y)1-xO1-v films may have promising applications in future spintronics. PMID:27062992

Ofatumumab and Bendamustine Hydrochloride With or Without Bortezomib in Treating Patients With Untreated Follicular Non-Hodgkin Lymphoma

ClinicalTrials.gov

2018-04-17

Ann Arbor Stage III Grade 1 Follicular Lymphoma; Ann Arbor Stage III Grade 2 Follicular Lymphoma; Ann Arbor Stage III Grade 3 Follicular Lymphoma; Ann Arbor Stage IV Grade 1 Follicular Lymphoma; Ann Arbor Stage IV Grade 2 Follicular Lymphoma; Ann Arbor Stage IV Grade 3 Follicular Lymphoma; Grade 3a Follicular Lymphoma

Comparison of two data mining techniques in labeling diagnosis to Iranian pharmacy claim dataset: artificial neural network (ANN) versus decision tree model.

PubMed

Rezaei-Darzi, Ehsan; Farzadfar, Farshad; Hashemi-Meshkini, Amir; Navidi, Iman; Mahmoudi, Mahmoud; Varmaghani, Mehdi; Mehdipour, Parinaz; Soudi Alamdari, Mahsa; Tayefi, Batool; Naderimagham, Shohreh; Soleymani, Fatemeh; Mesdaghinia, Alireza; Delavari, Alireza; Mohammad, Kazem

2014-12-01

This study aimed to evaluate and compare the prediction accuracy of two data mining techniques, including decision tree and neural network models in labeling diagnosis to gastrointestinal prescriptions in Iran. This study was conducted in three phases: data preparation, training phase, and testing phase. A sample from a database consisting of 23 million pharmacy insurance claim records, from 2004 to 2011 was used, in which a total of 330 prescriptions were assessed and used to train and test the models simultaneously. In the training phase, the selected prescriptions were assessed by both a physician and a pharmacist separately and assigned a diagnosis. To test the performance of each model, a k-fold stratified cross validation was conducted in addition to measuring their sensitivity and specificity. Generally, two methods had very similar accuracies. Considering the weighted average of true positive rate (sensitivity) and true negative rate (specificity), the decision tree had slightly higher accuracy in its ability for correct classification (83.3% and 96% versus 80.3% and 95.1%, respectively). However, when the weighted average of ROC area (AUC between each class and all other classes) was measured, the ANN displayed higher accuracies in predicting the diagnosis (93.8% compared with 90.6%). According to the result of this study, artificial neural network and decision tree model represent similar accuracy in labeling diagnosis to GI prescription.

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

ClinicalTrials.gov

2018-06-25

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

Improving anxiety regulation in patients with breast cancer at the beginning of the survivorship period: a randomized clinical trial comparing the benefits of single-component and multiple-component group interventions.

PubMed

Merckaert, Isabelle; Lewis, Florence; Delevallez, France; Herman, Sophie; Caillier, Marie; Delvaux, Nicole; Libert, Yves; Liénard, Aurore; Nogaret, Jean-Marie; Ogez, David; Scalliet, Pierre; Slachmuylder, Jean-Louis; Van Houtte, Paul; Razavi, Darius

2017-08-01

To compare in a multicenter randomized controlled trial the benefits in terms of anxiety regulation of a 15-session single-component group intervention (SGI) based on support with those of a 15-session multiple-component structured manualized group intervention (MGI) combining support with cognitive-behavioral and hypnosis components. Patients with nonmetastatic breast cancer were randomly assigned at the beginning of the survivorship period to the SGI (n = 83) or MGI (n = 87). Anxiety regulation was assessed, before and after group interventions, through an anxiety regulation task designed to assess their ability to regulate anxiety psychologically (anxiety levels) and physiologically (heart rates). Questionnaires were used to assess psychological distress, everyday anxiety regulation, and fear of recurrence. Group allocation was computer generated and concealed till baseline completion. Compared with patients in the SGI group (n = 77), patients attending the MGI group (n = 82) showed significantly reduced anxiety after a self-relaxation exercise (P = .006) and after exposure to anxiety triggers (P = .013) and reduced heart rates at different time points throughout the task (P = .001 to P = .047). The MGI participants also reported better everyday anxiety regulation (P = .005), greater use of fear of recurrence-related coping strategies (P = .022), and greater reduction in fear of recurrence-related psychological distress (P = .017) compared with the SGI group. This study shows that an MGI combining support with cognitive-behavioral techniques and hypnosis is more effective than an SGI based only on support in improving anxiety regulation in patients with breast cancer. Copyright © 2016 John Wiley & Sons, Ltd.

Assessment of medical radiation exposure to patients and ambient doses in several diagnostic radiology departments

NASA Astrophysics Data System (ADS)

Sulieman, A.; Elhadi, T.; Babikir, E.; Alkhorayef, M.; Alnaaimi, M.; Alduaij, M.; Bradley, D. A.

2017-11-01

In many countries diagnostic medical exposures typically account for a very large fraction of the collective effective dose that can be assigned to anthropological sources and activities. This in part flags up the question of whether sufficient steps are being taken in regard to potential dose saving from such medical services. As a first step, one needs to survey doses to compare against those of best practice. The present study has sought evaluation of the radiation protection status and patient doses for certain key radiological procedures in four film-based radiology departments within Sudan. The radiation exposure survey, carried out using a survey meter and quality control test tools, involved a total of 299 patients their examinations being carried out at one or other of these four departments. The entrance surface air kerma (ESAK) was determined from exposure settings using DosCal software and an Unfors -Xi-meter. The mean ESAK for x-ray examination of the chest was 0.30±0.1 mGy, for the skull it was 0.96±0.7 mGy, for the abdomen 0.85±0.01 mGy, for spinal procedures 1.30±0.6 mGy and for procedures involving the limbs it was 0.43±0.3 mGy. Ambient dose-rates in the reception area, at the closed door of the x-ray room, recorded instantaneous values of up to 100 μSv/h. In regard to protection, the associated levels were found to be acceptable in three of the four departments, corrective action being required for one department, regular quality control also being recommended.

Combined effects of alpha particles and depleted uranium on Zebrafish (Danio rerio) embryos

PubMed Central

Ng, Candy Y.P.; Pereira, Sandrine; Cheng, Shuk Han; Adam-Guillermin, Christelle; Garnier-Laplace, Jacqueline; Yu, Kwan Ngok

2016-01-01

The combined effects of low-dose or high-dose alpha particles and depleted uranium (DU) in Zebrafish (Danio rerio) embryos were studied. Three schemes were examined—(i) [ILUL]: 0.44 mGy alpha-particle dose + 10 µg/l DU exposure, (ii) [IHUH]: 4.4 mGy alpha-particle dose + 100 µg/l DU exposure and (iii) [IHUL]: 4.4 mGy alpha-particle dose + 10 µg/l DU exposure—in which Zebrafish embryos were irradiated with alpha particles at 5 h post fertilization (hpf) and/or exposed to uranium at 5–6 hpf. The results were also compared with our previous work, which studied the effects of [ILUH]: 0.44 mGy alpha-particle dose + 100 µg/l DU exposure. When the Zebrafish embryos developed to 24 hpf, the apoptotic signals in the entire embryos, used as the biological endpoint for this study, were quantified. Our results showed that [ILUL] and [IHUL] led to antagonistic effects, whereas [IHUH] led to an additive effect. The effect found for the previously studied case of [ILUH] was difficult to define because it was synergistic with reference to the 100 µg/l DU exposure, but it was antagonistic with reference to the 0.44 mGy alpha-particle dose. All the findings regarding the four different schemes showed that the combined effects critically depended on the dose response to each individual stressor. We also qualitatively explained these findings in terms of promotion of early death of cells predisposed to spontaneous transformation by alpha particles, interacting with the delay in cell death resulting from various concentrations of DU exposure. PMID:26937024

Diagnostic accuracy at several reduced radiation dose levels for CT imaging in the diagnosis of appendicitis

NASA Astrophysics Data System (ADS)

Zhang, Di; Khatonabadi, Maryam; Kim, Hyun; Jude, Matilda; Zaragoza, Edward; Lee, Margaret; Patel, Maitraya; Poon, Cheryce; Douek, Michael; Andrews-Tang, Denise; Doepke, Laura; McNitt-Gray, Shawn; Cagnon, Chris; DeMarco, John; McNitt-Gray, Michael

2012-03-01

Purpose: While several studies have investigated the tradeoffs between radiation dose and image quality (noise) in CT imaging, the purpose of this study was to take this analysis a step further by investigating the tradeoffs between patient radiation dose (including organ dose) and diagnostic accuracy in diagnosis of appendicitis using CT. Methods: This study was IRB approved and utilized data from 20 patients who underwent clinical CT exams for indications of appendicitis. Medical record review established true diagnosis of appendicitis, with 10 positives and 10 negatives. A validated software tool used raw projection data from each scan to create simulated images at lower dose levels (70%, 50%, 30%, 20% of original). An observer study was performed with 6 radiologists reviewing each case at each dose level in random order over several sessions. Readers assessed image quality and provided confidence in their diagnosis of appendicitis, each on a 5 point scale. Liver doses at each case and each dose level were estimated using Monte Carlo simulation based methods. Results: Overall diagnostic accuracy varies across dose levels: 92%, 93%, 91%, 90% and 90% across the 100%, 70%, 50%, 30% and 20% dose levels respectively. And it is 93%, 95%, 88%, 90% and 90% across the 13.5-22mGy, 9.6-13.5mGy, 6.4-9.6mGy, 4-6.4mGy, and 2-4mGy liver dose ranges respectively. Only 4 out of 600 observations were rated "unacceptable" for image quality. Conclusion: The results from this pilot study indicate that the diagnostic accuracy does not change dramatically even at significantly reduced radiation dose.

Non-induction of radioadaptive response in zebrafish embryos by neutrons

PubMed Central

Ng, Candy Y.P.; Kong, Eva Y.; Kobayashi, Alisa; Suya, Noriyoshi; Uchihori, Yukio; Cheng, Shuk Han; Konishi, Teruaki; Yu, Kwan Ngok

2016-01-01

In vivo neutron-induced radioadaptive response (RAR) was studied using zebrafish (Danio rerio) embryos. The Neutron exposure Accelerator System for Biological Effect Experiments (NASBEE) facility at the National Institute of Radiological Sciences (NIRS), Japan, was employed to provide 2-MeV neutrons. Neutron doses of 0.6, 1, 25, 50 and 100 mGy were chosen as priming doses. An X-ray dose of 2 Gy was chosen as the challenging dose. Zebrafish embryos were dechorionated at 4 h post fertilization (hpf), irradiated with a chosen neutron dose at 5 hpf and the X-ray dose at 10 hpf. The responses of embryos were assessed at 25 hpf through the number of apoptotic signals. None of the neutron doses studied could induce RAR. Non-induction of RAR in embryos having received 0.6- and 1-mGy neutron doses was attributed to neutron-induced hormesis, which maintained the number of damaged cells at below the threshold for RAR induction. On the other hand, non-induction of RAR in embryos having received 25-, 50- and 100-mGy neutron doses was explained by gamma-ray hormesis, which mitigated neutron-induced damages through triggering high-fidelity DNA repair and removal of aberrant cells through apoptosis. Separate experimental results were obtained to verify that high-energy photons could disable RAR. Specifically, 5- or 10-mGy X-rays disabled the RAR induced by a priming dose of 0.88 mGy of alpha particles delivered to 5-hpf zebrafish embryos against a challenging dose of 2 Gy of X-rays delivered to the embryos at 10 hpf. PMID:26850927

Estimates of Average Glandular Dose with Auto-modes of X-ray Exposures in Digital Breast Tomosynthesis.

PubMed

Kamal, Izdihar; Chelliah, Kanaga K; Mustafa, Nawal

2015-05-01

The aim of this research was to examine the average glandular dose (AGD) of radiation among different breast compositions of glandular and adipose tissue with auto-modes of exposure factor selection in digital breast tomosynthesis. This experimental study was carried out in the National Cancer Society, Kuala Lumpur, Malaysia, between February 2012 and February 2013 using a tomosynthesis digital mammography X-ray machine. The entrance surface air kerma and the half-value layer were determined using a 100H thermoluminescent dosimeter on 50% glandular and 50% adipose tissue (50/50) and 20% glandular and 80% adipose tissue (20/80) commercially available breast phantoms (Computerized Imaging Reference Systems, Inc., Norfolk, Virginia, USA) with auto-time, auto-filter and auto-kilovolt modes. The lowest AGD for the 20/80 phantom with auto-time was 2.28 milliGray (mGy) for two dimension (2D) and 2.48 mGy for three dimensional (3D) images. The lowest AGD for the 50/50 phantom with auto-time was 0.97 mGy for 2D and 1.0 mGy for 3D. The AGD values for both phantoms were lower against a high kilovolt peak and the use of auto-filter mode was more practical for quick acquisition while limiting the probability of operator error.

Assessment of patient dose and radiogenic risks during endoscopic retrograde cholangiopancreatography.

PubMed

Sulieman, A; Elzaki, M; Alkhorayef, M; Babikir, E; Abuzaid, M; Dalton, A; Bradley, D

2016-11-01

Endoscopic retrograde cholangiopancreatography (ERCP) is an invasive technique that has been used for over 30 years in the diagnosis and management of pancreaticobiliary disorders. The objectives of this study were to evaluate the patient entrance surface air kerma doses (ESAK) and estimate the organ and effective doses during ERCP in three hospitals in Khartoum. A total of 55 patients were examined in three hospitals in Khartoum state, Sudan. Calibrated thermoluinescent dosimeters (TLD) were used to measure patients' ESAK. Organ and effective doses were estimated using National Radiological Protection Board (NRPB) software. The overall mean of ESAK for all ERCP procedures was 42.4mGy. The mean patient ESAK in Fedail (A), Soba (B) and Ibn sena (C) hospitals were 26.7mGy, 26.0mGy and 72.4mGy, respectively. The effective doses in three hospitals were 1.60, 1.56 and 2.67mSv in that order and the overall mean effective dose was 1.94mSv. Patient radiation doses vary widely among the hospitals. Patient ESAK is low compared to previous studies in the light of the current practice. Patient dose was decreased significantly in the last two decades. Copyright © 2016 Elsevier Ltd. All rights reserved.

The rate of X-ray-induced DNA double-strand break repair in the embryonic mouse brain is unaffected by exposure to 50 Hz magnetic fields.

PubMed

Woodbine, Lisa; Haines, Jackie; Coster, Margaret; Barazzuol, Lara; Ainsbury, Elizabeth; Sienkiewicz, Zenon; Jeggo, Penny

2015-06-01

Following in utero exposure to low dose radiation (10-200 mGy), we recently observed a linear induction of DNA double-strand breaks (DSB) and activation of apoptosis in the embryonic neuronal stem/progenitor cell compartment. No significant induction of DSB or apoptosis was observed following exposure to magnetic fields (MF). In the present study, we exploited this in vivo system to examine whether exposure to MF before and after exposure to 100 mGy X-rays impacts upon DSB repair rates. 53BP1 foci were quantified following combined exposure to radiation and MF in the embryonic neuronal stem/progenitor cell compartment. Embryos were exposed in utero to 50 Hz MF at 300 μT for 3 h before and up to 9 h after exposure to 100 mGy X-rays. Controls included embryos exposed to MF or X-rays alone plus sham exposures. Exposure to MF before and after 100 mGy X-rays did not impact upon the rate of DSB repair in the embryonic neuronal stem cell compartment compared to repair rates following radiation exposure alone. We conclude that in this sensitive system MF do not exert any significant level of DNA damage and do not impede the repair of X-ray induced damage.

ESR dosimetry study of population in the vicinity of the Semipalatinsk Nuclear Test Site

PubMed Central

Zhumadilov, Kassym; Ivannikov, Alexander; Stepanenko, Valeriy; Zharlyganova, Dinara; Toyoda, Shin; Zhumadilov, Zhaxybay; Hoshi, Masaharu

2013-01-01

A tooth enamel electron spin resonance (ESR) dosimetry study was carried out with the purpose of obtaining the individual absorbed radiation doses of population from settlements in the Semipalatinsk region of Kazakhstan, which was exposed to radioactive fallout traces from nuclear explosions in the Semipalatinsk Nuclear Test Site and Lop Nor test base, China. Most of the settlements are located near the central axis of radioactive fallout trace from the most contaminating surface nuclear test, which was conducted on 29 August 1949, with the maximum detected excess dose being 430 ± 93 mGy. A maximum dose of 268 ± 79 mGy was determined from the settlements located close to radioactive fallout trace resulting from surface nuclear tests on 24 August 1956 (Ust-Kamenogorsk, Znamenka, Shemonaikha, Glubokoe, Tavriya and Gagarino). An accidental dose of 56 ± 42 mGy was found in Kurchatov city residents located close to fallout trace after the nuclear test on 7 August 1962. This method was applied to human tooth enamel to obtain individual absorbed doses of residents of the Makanchi, Urdzhar and Taskesken settlements located near the Kazakhstan–Chinese border due to the influence of nuclear tests (1964–1981) at Lop Nor. The highest dose was 123 ± 32 mGy. PMID:23404205

ESR dosimetry study of population in the vicinity of the Semipalatinsk Nuclear Test Site.

PubMed

Zhumadilov, Kassym; Ivannikov, Alexander; Stepanenko, Valeriy; Zharlyganova, Dinara; Toyoda, Shin; Zhumadilov, Zhaxybay; Hoshi, Masaharu

2013-07-01

A tooth enamel electron spin resonance (ESR) dosimetry study was carried out with the purpose of obtaining the individual absorbed radiation doses of population from settlements in the Semipalatinsk region of Kazakhstan, which was exposed to radioactive fallout traces from nuclear explosions in the Semipalatinsk Nuclear Test Site and Lop Nor test base, China. Most of the settlements are located near the central axis of radioactive fallout trace from the most contaminating surface nuclear test, which was conducted on 29 August 1949, with the maximum detected excess dose being 430 ± 93 mGy. A maximum dose of 268 ± 79 mGy was determined from the settlements located close to radioactive fallout trace resulting from surface nuclear tests on 24 August 1956 (Ust-Kamenogorsk, Znamenka, Shemonaikha, Glubokoe, Tavriya and Gagarino). An accidental dose of 56 ± 42 mGy was found in Kurchatov city residents located close to fallout trace after the nuclear test on 7 August 1962. This method was applied to human tooth enamel to obtain individual absorbed doses of residents of the Makanchi, Urdzhar and Taskesken settlements located near the Kazakhstan-Chinese border due to the influence of nuclear tests (1964-1981) at Lop Nor. The highest dose was 123 ± 32 mGy.

Combination Chemotherapy With or Without Bortezomib in Treating Younger Patients With Newly Diagnosed T-Cell Acute Lymphoblastic Leukemia or Stage II-IV T-Cell Lymphoblastic Lymphoma

ClinicalTrials.gov

2018-06-27

Adult T Acute Lymphoblastic Leukemia; Ann Arbor Stage II Adult Lymphoblastic Lymphoma; Ann Arbor Stage II Childhood Lymphoblastic Lymphoma; Ann Arbor Stage III Adult Lymphoblastic Lymphoma; Ann Arbor Stage III Childhood Lymphoblastic Lymphoma; Ann Arbor Stage IV Adult Lymphoblastic Lymphoma; Ann Arbor Stage IV Childhood Lymphoblastic Lymphoma; Childhood T Acute Lymphoblastic Leukemia; Untreated Adult Acute Lymphoblastic Leukemia; Untreated Childhood Acute Lymphoblastic Leukemia

Materials Genome Initiative

NASA Technical Reports Server (NTRS)

Vickers, John

2015-01-01

The Materials Genome Initiative (MGI) project element is a cross-Center effort that is focused on the integration of computational tools to simulate manufacturing processes and materials behavior. These computational simulations will be utilized to gain understanding of processes and materials behavior to accelerate process development and certification to more efficiently integrate new materials in existing NASA projects and to lead to the design of new materials for improved performance. This NASA effort looks to collaborate with efforts at other government agencies and universities working under the national MGI. MGI plans to develop integrated computational/experimental/ processing methodologies for accelerating discovery and insertion of materials to satisfy NASA's unique mission demands. The challenges include validated design tools that incorporate materials properties, processes, and design requirements; and materials process control to rapidly mature emerging manufacturing methods and develop certified manufacturing processes

Bridging the Gap: Linking Simulation and Testing

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

Krajewski, Paul E.; Carsley, John; Stoudt, Mark R.

2012-09-01

The Materials Genome Initiative (MGI) which is a key enabler for the Advanced Manufacturing Partnership, announced in 2011 by U.S. President Barack Obama, was established to accelerate the development and deployment of advanced materials. The MGI is driven by the need to "bridge the gap" between (I) experimental results and computational analysis to enable the rapid development and validation of new mateirals, and (II) the processes required to convert these materials into useable goods.

Water Quality Studies: Richard B. Russell and Clarks Hill Lakes.

DTIC Science & Technology

1986-12-01

total manga - nese ranged from 2.4 mg/i to 2.3 mg/i at Stations 130 and 140, respectively, by September. Dissolved forms exhibited similar patterns at...iron at mid-hypolimnetic depths was in the particulate form. 122. Figure 54 illustrates seasonal patterns in total dissolved manga - nese for Stations...was the fact that most of the iron in the outflow was in the particulate form. Manga - nese concentrations also increased during stratification and

Effect of Vascular Access Site Choice on Radiation Exposure During Coronary Angiography: The REVERE Trial (Randomized Evaluation of Vascular Entry Site and Radiation Exposure).

PubMed

Pancholy, Samir B; Joshi, Pankaj; Shah, Sanjay; Rao, Sunil V; Bertrand, Olivier F; Patel, Tejas M

2015-08-17

This study sought to perform a randomized noninferiority trial of radiation exposure during cardiac catheterization comparing femoral access (FA) with left radial access (LRA) and right radial access (RRA). Increased radiation exposure with radial approach compared with femoral approach remains a controversial issue. This study randomized 1,493 patients undergoing cardiac catheterization at a tertiary care center to FA, LRA, and RRA in a 1:1:1 fashion. The primary endpoint was air kerma. The secondary endpoints included dose-area product, fluoroscopy time and operator dose per procedure, number of cineangiograms, and number of catheters. Baseline and procedural characteristics were similar among groups. No significant differences were observed in air kerma (medians: FA: 421 mGy [interquartile range (IQR): 337 to 574 mGy], LRA: 454 mGy [IQR: 331 to 643 mGy], and RRA: 483 mGy [IQR: 382 to 592 mGy], p = 0.146), dose-area product (medians: FA: 25.5 Gy cm(2) [IQR: 19.6 to 34.5 Gy cm(2)], LRA: 26.6 Gy cm(2) [IQR: 19.5 to 37.5 Gy cm(2)], and RRA: 27.7 Gy cm(2) [IQR: 21.9 to 34.4 Gy cm(2)], p = 0.40), or fluoroscopy time (medians: FA: 1.3 min [IQR: 1.0 to 1.7 min], LRA: 1.3 min [IQR: 1.0 to 1.7 min], and RRA: 1.32 min [IQR: 1.0 to 1.7 min], p = 0.19) among the 3 access sites. Median operator exposure was higher in the LRA group (3 mrem [IQR: 2 to 5 mrem], p = 0.001 vs. FA, and p = 0.0001 vs. RRA) compared with the FA (2 mrem [IQR: 2 to 4 mrem] and RRA groups (3 mrem [IQR: 2 to 5 mrem]). Radiation exposure to patients was similar during diagnostic coronary angiography with FA, RRA, and LRA. However, LRA was associated with significantly higher operator radiation exposure than were FA and RRA procedures. (Randomized Evaluation of Vascular Entry Site and Radiation Exposure [REVERE]; NCT01677481). Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

WE-D-18A-04: How Iterative Reconstruction Algorithms Affect the MTFs of Variable-Contrast Targets in CT Images

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

Dodge, C.T.; Rong, J.; Dodge, C.W.

2014-06-15

Purpose: To determine how filtered back-projection (FBP), adaptive statistical (ASiR), and model based (MBIR) iterative reconstruction algorithms affect the measured modulation transfer functions (MTFs) of variable-contrast targets over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP401 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 24 mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 2.5mm thickness, 0.984 pitch. The images were reconstructed using GE's Standard kernel with FBP; 20%, 40% andmore » 70% ASiR; and MBIR. A task-based MTF (MTFtask) was computed for six cylindrical targets: 2 low-contrast (Polystyrene, LDPE), 2 medium-contrast (Delrin, PMP), and 2 high-contrast (Teflon, air). MTFtask was used to compare the performance of reconstruction algorithms with decreasing CTDIvol from 24mGy, which is currently used in the clinic. Results: For the air target and 75% dose savings (6 mGy), MBIR MTFtask at 5 lp/cm measured 0.24, compared to 0.20 for 70% ASiR and 0.11 for FBP. Overall, for both high-contrast targets, MBIR MTFtask improved with increasing CTDIvol and consistently outperformed ASiR and FBP near the system's Nyquist frequency. Conversely, for Polystyrene at 6 mGy, MBIR (0.10) and 70% ASiR (0.07) MTFtask was lower than for FBP (0.18). For medium and low-contrast targets, FBP remains the best overall algorithm for improved resolution at low CTDIvol (1–6 mGy) levels, whereas MBIR is comparable at higher dose levels (12–24 mGy). Conclusion: MBIR improved the MTF of small, high-contrast targets compared to FBP and ASiR at doses of 50%–12.5% of those currently used in the clinic. However, for imaging low- and mediumcontrast targets, FBP performed the best across all dose levels. For assessing MTF from different reconstruction algorithms, task-based MTF measurements are necessary.« less

Comparative proteomic analysis of rice after seed ground simulated radiation and spaceflight explains the radiation effects of space environment

NASA Astrophysics Data System (ADS)

Wang, Wei; Shi, Jinming; Liang, Shujian; Lei, Huang; Shenyi, Zhang; Sun, Yeqing

In previous work, we compared the proteomic profiles of rice plants growing after seed space-flights with ground controls by two-dimensional difference gel electrophoresis (2-D DIGE) and found that the protein expression profiles were changed after seed space environment exposures. Spaceflight represents a complex environmental condition in which several interacting factors such as cosmic radiation, microgravity and space magnetic fields are involved. Rice seed is in the process of dormant of plant development, showing high resistance against stresses, so the highly ionizing radiation (HZE) in space is considered as main factor causing biological effects to seeds. To further investigate the radiation effects of space environment, we performed on-ground simulated HZE particle radiation and compared between the proteomes of seed irra-diated plants and seed spaceflight (20th recoverable satellite) plants from the same rice variety. Space ionization shows low-dose but high energy particle effects, for searching the particle effects, ground radiations with the same low-dose (2mGy) but different liner energy transfer (LET) values (13.3KeV/µm-C, 30KeV/µm-C, 31KeV/µm-Ne, 62.2KeV/µm-C, 500Kev/µm-Fe) were performed; using 2-D DIGE coupled with clustering and principle component analysis (PCA) for data process and comparison, we found that the holistic protein expression patterns of plants irradiated by LET-62.2KeV/µm carbon particles were most similar to spaceflight. In addition, although space environment presents a low-dose radiation (0.177 mGy/day on the satellite), the equivalent simulated radiation dose effects should still be evaluated: radiations of LET-62.2KeV/µm carbon particles with different cumulative doses (2mGy, 20mGy, 200mGy, 2000mGy) were further carried out and resulted that the 2mGy radiation still shared most similar proteomic profiles with spaceflight, confirming the low-dose effects of space radiation. Therefore, in the protein expression level

Hierarchical Bayesian Model Averaging for Non-Uniqueness and Uncertainty Analysis of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Fijani, E.; Chitsazan, N.; Nadiri, A.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

Artificial Neural Networks (ANNs) have been widely used to estimate concentration of chemicals in groundwater systems. However, estimation uncertainty is rarely discussed in the literature. Uncertainty in ANN output stems from three sources: ANN inputs, ANN parameters (weights and biases), and ANN structures. Uncertainty in ANN inputs may come from input data selection and/or input data error. ANN parameters are naturally uncertain because they are maximum-likelihood estimated. ANN structure is also uncertain because there is no unique ANN model given a specific case. Therefore, multiple plausible AI models are generally resulted for a study. One might ask why good models have to be ignored in favor of the best model in traditional estimation. What is the ANN estimation variance? How do the variances from different ANN models accumulate to the total estimation variance? To answer these questions we propose a Hierarchical Bayesian Model Averaging (HBMA) framework. Instead of choosing one ANN model (the best ANN model) for estimation, HBMA averages outputs of all plausible ANN models. The model weights are based on the evidence of data. Therefore, the HBMA avoids overconfidence on the single best ANN model. In addition, HBMA is able to analyze uncertainty propagation through aggregation of ANN models in a hierarchy framework. This method is applied for estimation of fluoride concentration in the Poldasht plain and the Bazargan plain in Iran. Unusually high fluoride concentration in the Poldasht and Bazargan plains has caused negative effects on the public health. Management of this anomaly requires estimation of fluoride concentration distribution in the area. The results show that the HBMA provides a knowledge-decision-based framework that facilitates analyzing and quantifying ANN estimation uncertainties from different sources. In addition HBMA allows comparative evaluation of the realizations for each source of uncertainty by segregating the uncertainty sources in

Aquatic Plant Control Research Program: Chemical Control of Hydrilla in Flowing Water: Herbicide Uptake Characteristics and Concentrations versus Exposure.

DTIC Science & Technology

1988-03-01

and di ecious hydrilla with diquat, endothall, and fluridone , and (c) to examine time-course uptak characteristics of these herbicides by hydrilla...diquat is effective in hydrilla control at a lower rate than is endothall. Uptake of fluridone by excised hydrilla tissue was linear with time when...ambient fluridone levels were 0.1 to 0.5 mg/i. However, a biphasic uptake curve was obtained at the high treatment rate of 1.0 mg/i fluridone . At this

Cascade Cyclizations of Acyclic and Macrocyclic Alkynones: Studies toward the Synthesis of Phomactin A

PubMed Central

Ciesielski, Jennifer; Gandon, Vincent; Frontier, Alison J.

2013-01-01

A study of the reactivity and diastereoselectivity of the Lewis acid-promoted cascade cyclizations of both acyclic and macrocyclic alkynones is described. In these reactions, a β-iodoallenolate intermediate is generated via conjugate addition of iodide to an alkynone, followed by an intramolecular aldol reaction with a tethered aldehyde to afford a cyclohexenyl alcohol. The Lewis acid magnesium iodide (MgI2) was found to promote irreversible ring closure, while cyclizations using BF3·OEt2 as promoter occurred reversibly. For both acyclic and macrocyclic ynones, high diastereoselectivity was observed in the intramolecular aldol reaction. The MgI2 protocol for cyclization was applied to the synthesis of advanced intermediates relevant to the synthesis of phomactin natural products, during which a novel transannular cation-olefin cyclization was observed. DFT calculations were conducted to analyze the mechanism of this unusual MgI2-promoted process. PMID:23724905

Reduction in radiation dose for atrial fibrillation ablation over time: A 12-year single-center experience of 2344 patients.

PubMed

Voskoboinik, Aleksandr; Kalman, Elana S; Savicky, Yonatan; Sparks, Paul B; Morton, Joseph B; Lee, Geoffrey; Kistler, Peter M; Kalman, Jonathan M

2017-06-01

Pulmonary vein isolation (PVI) is a well-established treatment of atrial fibrillation (AF), with contact force (CF)-sensing catheters joining 3-dimensional mapping systems and image integration as technological advancements over the last decade. The purpose of this study was to analyze trends in radiation exposure for AF ablation over the last 12 years at our center. We reviewed prospectively collected data of 2344 consecutive PVI procedures for either paroxysmal or persistent AF between January 2004 and December 2015. During this period, all cases used 3-dimensional mapping systems, with 8 software and 2 hardware upgrades. Primary endpoints were fluoroscopy time, absorbed dose (Air Kerma in mGy), and effective dose (mSv). In total, 1914 patients underwent initial PVI, and 430 patients underwent redo PVI using radiofrequency energy. Fluoroscopy time, and absorbed and effective doses significantly and progressively decreased over the 12-year period for initial PVI as follows: 2004-2006: 61 ± 27 minutes; 2007-2009: 46 ± 14 minutes, 1365 ± 1369 mGy, 11.3 ± 12.5 mSv; 2010-2012: 31 ± 11, 464 ± 339 mGy, 9.0 ± 10.4 mSv; and 2013-2015: 17 ± 9 minutes, 304 ± 758 mGy, 5.5 ± 6.7 mSv. CF-sensing catheters were used for 357/508 PVI only cases between 2014 and 2015. Fluoroscopy times (11 ± 5 vs 21 ± 8 minutes; P <.001) and absorbed dose (200 ± 524 vs 470 ± 1326 mGy; P = .004) were significantly shorter with this catheter. Radiation exposure has dramatically decreased over the last decade for PVI and is related to operator experience, annual case volume, technology evolution, and more recently CF-sensing catheters. This has significant implications for both patient and operator long-term risk. Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Basin Scale Variation on the Composition and Diversity of Archaea in the Pacific Ocean.

PubMed

Xia, Xiaomin; Guo, Wang; Liu, Hongbin

2017-01-01

The Archaea are a widely distributed group of prokaryotes that inhabit and thrive in many different environments. In the sea, they play key roles in various global biogeochemical processes. Here, in order to investigate the vertical profiles of archaeal community across a large geographic distance, the compositions of archaeal communities in seven seawater columns in the Pacific Ocean were investigated using high throughput 454 pyrosequencing of the 16S rRNA gene. The surface archaeal communities showed lower diversity and greater variability than those in the deeper layers. Two of the major archaeal phyla that displayed different depth preferences were Thaumarchaeota and Euryarchaeota. The majority of Thaumarchaeota belonged to Marine Group I (MGI), which had high relative abundance in deep water. In contrast, Euryarchaeota, which mainly consisted of Marine Group II (MGII) and III (MGIII), were dominant in the surface layer. Compared with MGI and MGII, MGIII were less abundant in seawater and generally absent from the surface water of the subarctic Pacific. In addition, niche separation in the MGI, MGII, and MGIII subgroups was also observed. For example, MGI.C and MGII.A (the major subgroups of MGI and MGII, respectively) displayed a strong negative correlation with each other. The highest level of archaeal diversity was found in the core of an oxygen minimum zone (OMZ) located off Costa Rica, which resulted from the co-occurrence of both anaerobic and aerobic archaea. For example, methanotrophic archaea ANME-2, methanogenic archaea and several sediment origin archaea, such as Marine Benthic Group A (MBGA) and Bathyarchaeota, were all detected at relatively high abundance in the OMZ. Together, our findings indicate that vertical heterogeneities along water columns and latitudinal differentiation in the surface waters are ubiquitous features of archaeal communities in the Pacific Ocean, and the OMZ off Costa Rica is an archaeal biodiversity hot-spot.

[Decision process of Notification Value by the Dose Index Registry system in X-ray computed tomography].

PubMed

Shinozaki, Masafumi; Muramatsu, Yoshihisa; Sasaki, Toru

2014-01-01

A new technical standard for X-ray computed tomography (CT) has been published by the National Electrical Manufacturers Association (NEMA) that allows the Alert Value and Notification Value for cumulative dose to be configurable by CT systems operators in conjunction with the XR-25 (Dose check) standard. In this study, a decision method of the Notification Values for reducing the radiation dose was examined using the dose index registry (DIR) system, during 122 continuous days from August 1, 2012 to November 30, 2012. CT images were obtained using the Discovery CT 750HD (GE Healthcare) and the dose index was calculated using the DoseWatch DIR system. The CT dose index-volume (CTDIvol) and dose-length product (DLP) were output from the DIR system in comma-separated value (CSV) file format for each examination protocol. All data were shown as a schematic boxplot using statistical processing software. The CTDIvol of a routine chest examination showed the following values (maximum: 23.84 mGy; minimum: 2.55 mGy; median: 7.60 mGy; 75% tile: 10.01 mGy; 25% tile: 6.54 mGy). DLP showed the following values (maximum: 944.56 mGy·cm; minimum: 97.25 mGy·cm; median: 307.35 mGy·cm; 75% tile: 406.87 mGy·cm; 25% tile: 255.75 mGy·cm). These results indicate that the 75% tile of CTDIvol and DLP as an initial value proved to be safe and efficient for CT examination and operation. We have thus established one way of determining the Notification Value from the output of the DIR system. Transfer back to the protocol of the CT and automated processing each numeric value in the DIR system is desired.

SU-F-I-33: Estimating Radiation Dose in Abdominal Fat Quantitative CT

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

Li, X; Yang, K; Liu, B

Purpose: To compare size-specific dose estimate (SSDE) in abdominal fat quantitative CT with another dose estimate D{sub size,L} that also takes into account scan length. Methods: This study complied with the requirements of the Health Insurance Portability and Accountability Act. At our institution, abdominal fat CT is performed with scan length = 1 cm and CTDI{sub vol} = 4.66 mGy (referenced to body CTDI phantom). A previously developed CT simulation program was used to simulate single rotation axial scans of 6–55 cm diameter water cylinders, and dose integral of the longitudinal dose profile over the central 1 cm length wasmore » used to predict the dose at the center of one-cm scan range. SSDE and D{sub size,L} were assessed for 182 consecutive abdominal fat CT examinations with mean water-equivalent diameter (WED) of 27.8 cm ± 6.0 (range, 17.9 - 42.2 cm). Patient age ranged from 18 to 75 years, and weight ranged from 39 to 163 kg. Results: Mean SSDE was 6.37 mGy ± 1.33 (range, 3.67–8.95 mGy); mean D{sub size,L} was 2.99 mGy ± 0.85 (range, 1.48 - 4.88 mGy); and mean D{sub size,L}/SSDE ratio was 0.46 ± 0.04 (range, 0.40 - 0.55). Conclusion: The conversion factors for size-specific dose estimate in AAPM Report No. 204 were generated using 15 - 30 cm scan lengths. One needs to be cautious in applying SSDE to small length CT scans. For abdominal fat CT, SSDE was 80–150% higher than the dose of 1 cm scan length.« less

Radium-226 dose to a boy from playing on mill tailings

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

Mays, C.W.; Lucas, H.F.; Lloyd, R.D.

Two boys born in September 1949 played on uranium mill tailings from about ages 8 to 12. One of these boys was diagnosed as having leukemia at age 15.5. The 226Ra body burden of the survivor was measured at age 38. The whole-body 226Ra content measured by counting in vivo was 0 {plus minus} 17 Bq and independently by Rn breath analysis as 4.3 {plus minus} 2.1 Bq. At the same time, a control subject with no known exposure to 226Ra, matched in age, height, and weight, was also measured. The whole-body content was estimated as 4 {plus minus} 15more » Bq and independently by Rn breath analysis as 5.5 {plus minus} 3.7 Bq. The body burden of the control subject was not significantly different from that of the exposed person. The radiation dose to the marrow-free skeleton assuming a constant 226Ra:Ca ratio since birth was 0.49 and 1.33 mGy at ages 14 and 38, respectively. The radiation dose to the marrow-free skeleton assuming 226Ra intake only between ages 8 to 12 was 1.4 and 2.8 mGy at ages 14 and 38, respectively. The best estimate is the mean of these two estimates: 0.9 and 2.1 mGy at ages 14 and 38, respectively. The alpha-particle dose to the red marrow from 226Ra and its decay products was 0.05 mGy at age 14 and 0.10 mGy at age 38. Since no excess was found for the radium dial painters whose doses were much higher, the induction of leukemia by doses of this magnitude would seem quite unlikely.« less

Non-induction of radioadaptive response in zebrafish embryos by neutrons.

PubMed

Ng, Candy Y P; Kong, Eva Y; Kobayashi, Alisa; Suya, Noriyoshi; Uchihori, Yukio; Cheng, Shuk Han; Konishi, Teruaki; Yu, Kwan Ngok

2016-06-01

In vivo neutron-induced radioadaptive response (RAR) was studied using zebrafish (Danio rerio) embryos. The Neutron exposure Accelerator System for Biological Effect Experiments (NASBEE) facility at the National Institute of Radiological Sciences (NIRS), Japan, was employed to provide 2-MeV neutrons. Neutron doses of 0.6, 1, 25, 50 and 100 mGy were chosen as priming doses. An X-ray dose of 2 Gy was chosen as the challenging dose. Zebrafish embryos were dechorionated at 4 h post fertilization (hpf), irradiated with a chosen neutron dose at 5 hpf and the X-ray dose at 10 hpf. The responses of embryos were assessed at 25 hpf through the number of apoptotic signals. None of the neutron doses studied could induce RAR. Non-induction of RAR in embryos having received 0.6- and 1-mGy neutron doses was attributed to neutron-induced hormesis, which maintained the number of damaged cells at below the threshold for RAR induction. On the other hand, non-induction of RAR in embryos having received 25-, 50- and 100-mGy neutron doses was explained by gamma-ray hormesis, which mitigated neutron-induced damages through triggering high-fidelity DNA repair and removal of aberrant cells through apoptosis. Separate experimental results were obtained to verify that high-energy photons could disable RAR. Specifically, 5- or 10-mGy X-rays disabled the RAR induced by a priming dose of 0.88 mGy of alpha particles delivered to 5-hpf zebrafish embryos against a challenging dose of 2 Gy of X-rays delivered to the embryos at 10 hpf. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Risk of Lung Cancer Mortality in Nuclear Workers from Internal Exposure to Alpha Particle-emitting Radionuclides

PubMed Central

Atkinson, Will; Bérard, Philippe; Bingham, Derek; Birchall, Alan; Blanchardon, Eric; Bull, Richard; Guseva Canu, Irina; Challeton-de Vathaire, Cécile; Cockerill, Rupert; Do, Minh T.; Engels, Hilde; Figuerola, Jordi; Foster, Adrian; Holmstock, Luc; Hurtgen, Christian; Laurier, Dominique; Puncher, Matthew; Riddell, Anthony E.; Samson, Eric; Thierry-Chef, Isabelle; Tirmarche, Margot; Vrijheid, Martine; Cardis, Elisabeth

2017-01-01

Background: Carcinogenic risks of internal exposures to alpha-emitters (except radon) are poorly understood. Since exposure to alpha particles—particularly through inhalation—occurs in a range of settings, understanding consequent risks is a public health priority. We aimed to quantify dose–response relationships between lung dose from alpha-emitters and lung cancer in nuclear workers. Methods: We conducted a case–control study, nested within Belgian, French, and UK cohorts of uranium and plutonium workers. Cases were workers who died from lung cancer; one to three controls were matched to each. Lung doses from alpha-emitters were assessed using bioassay data. We estimated excess odds ratio (OR) of lung cancer per gray (Gy) of lung dose. Results: The study comprised 553 cases and 1,333 controls. Median positive total alpha lung dose was 2.42 mGy (mean: 8.13 mGy; maximum: 316 mGy); for plutonium the median was 1.27 mGy and for uranium 2.17 mGy. Excess OR/Gy (90% confidence interval)—adjusted for external radiation, socioeconomic status, and smoking—was 11 (2.6, 24) for total alpha dose, 50 (17, 106) for plutonium, and 5.3 (−1.9, 18) for uranium. Conclusions: We found strong evidence for associations between low doses from alpha-emitters and lung cancer risk. The excess OR/Gy was greater for plutonium than uranium, though confidence intervals overlap. Risk estimates were similar to those estimated previously in plutonium workers, and in uranium miners exposed to radon and its progeny. Expressed as risk/equivalent dose in sieverts (Sv), our estimates are somewhat larger than but consistent with those for atomic bomb survivors. See video abstract at, http://links.lww.com/EDE/B232. PMID:28520643

SU-E-I-15: Comparison of Radiation Dose for Radiography and EOS in Adolescent Scoliosis Patients

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

Schueler, B; Walz-Flannigan, A

Purpose: To estimate patient radiation dose for whole spine imaging using EOS, a new biplanar slot-scanning radiographic system and compare with standard scoliosis radiography. Methods: The EOS imaging system (EOS Imaging, Paris, France) consists of two orthogonal x-ray fan beams which simultaneously acquire frontal and lateral projection images of a standing patient. The patient entrance skin air kerma was measured for each projection image using manufacturer-recommended exposure parameters for spine imaging. Organ and effective doses were estimated using a commercially-available Monte Carlo simulation program (PCXMC, STUK, Radiation and Nuclear Safety Authority, Helsinki, Finland) for a 15 year old mathematical phantommore » model. These results were compared to organ and effective dose estimated for scoliosis radiography using computed radiography (CR) with standard exposure parameters obtained from a survey of pediatric radiographic projections. Results: The entrance skin air kerma for EOS was found to be 0.18 mGy and 0.33 mGy for posterior-anterior (PA) and lateral projections, respectively. This compares to 0.76 mGy and 1.4 mGy for CR, PA and lateral projections. Effective dose for EOS (PA and lateral projections combined) is 0.19 mSv compared to 0.51 mSv for CR. Conclusion: The EOS slot-scanning radiographic system allows for reduced patient radiation dose in scoliosis patients as compared to standard CR radiography.« less

Dose profiles for lung and breast regions at prospective and retrospective CT coronary angiography using optically stimulated luminescence dosimeters on a 64-detector CT scanner.

PubMed

Funama, Yoshinori; Taguchi, Katsuyuki; Utsunomiya, Daisuke; Oda, Seitaro; Murasaki, Hiroo; Yamashita, Yasuyuki; Awai, Kazuo

2012-01-01

The purpose of our study was to acquire dose profiles at critical organs of lung and breast regions using optically stimulated luminescence (OSL) dosimeters; assess the actual radiation dose delivered at retrospective and prospective computed tomography coronary angiography (CTCA). Using a chest CT phantom we applied a prospectively-gated step-and-shoot- and a retrospectively-gated helical mode on a 64-detector row CT scanner. Retrospective scan mode was used with and without electrocardiogram (ECG) based tube current modulation. OSL dosimeters were used to measure dose profiles. In the both scan modes we acquired dose profiles and determined the mean and maximum dose in left lung and in left breast regions. In prospective mode, the mean dose was 21.53 mGy in left lung- and 23.59 mGy in left breast region. With respect to the retrospective mode, the mean dose with tube current modulation was 38.63 mGy for left lung- and 46.02 mGy for left breast region, i.e. 0.56 and 0.55 times lower than the mean dose without modulation. The OSL dosimeter is useful for measurement of the actual radiation dose along z-axis at lung and breast regions in the prospective and the retrospective CTCA. Copyright © 2011 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Assessment of runoff and sediment yields using the AnnAGNPS model in a Three-Gorge watershed of China.

PubMed

Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

2012-05-01

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km(2) Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R(2) of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R(2) of 0.93). Additionally, the model was validated using annual average sediment of 2000-2002 (relative error of -0.34) and 2003-2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km(-2)·y(-1)). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km(-2)·y(-1). Sloping areas and low coverage areas are the main source of soil loss in the

Effects of single and dual physical modifications on pinhão starch.

PubMed

Pinto, Vânia Zanella; Vanier, Nathan Levien; Deon, Vinicius Gonçalves; Moomand, Khalid; El Halal, Shanise Lisie Mello; Zavareze, Elessandra da Rosa; Lim, Loong-Tak; Dias, Alvaro Renato Guerra

2015-11-15

Pinhão starch was modified by annealing (ANN), heat-moisture (HMT) or sonication (SNT) treatments. The starch was also modified by a combination of these treatments (ANN-HMT, ANN-SNT, HMT-ANN, HMT-SNT, SNT-ANN, SNT-HMT). Whole starch and debranched starch fractions were analyzed by gel-permeation chromatography. Moreover, crystallinity, morphology, swelling power, solubility, pasting and gelatinization characteristics were evaluated. Native and single ANN and SNT-treated starches exhibited a CA-type crystalline structure while other modified starches showed an A-type structure. The relative crystallinity increased in ANN-treated starches and decreased in single HMT- and SNT-treated starches. The ANN, HMT and SNT did not provide visible cracks, notches or grooves to pinhão starch granule. SNT applied as second treatment was able to increase the peak viscosity of single ANN- and HMT-treated starches. HMT used alone or in dual modifications promoted the strongest effect on gelatinization temperatures and enthalpy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Treating Combat Hearing Loss with Atoh1 Gene Therapy

DTIC Science & Technology

2015-06-01

Student Rende Gu, M.D., Staff Scientist Hongyuan Zhang, Research Technician 10   8. REPORTABLE OUTCOMES: Informatics : We have compiled two...cochlear development. Materials and Methods Experimental animals. Atoh1 / [Mouse Genome Informatics (MGI): Atoh1tm1Hzo], Atoh1A1GFP/A1GFP (MGI...pregnant females at E15.5, E16.5, or E17.5 by oral gavage. Tamoxifen and progesterone were dissolved to- gether in peanut oil , both at a concentration of 20

Application of artificial neural networks to establish a predictive mortality risk model in children admitted to a paediatric intensive care unit.

PubMed

Chan, C H; Chan, E Y; Ng, D K; Chow, P Y; Kwok, K L

2006-11-01

Paediatric risk of mortality and paediatric index of mortality (PIM) are the commonly-used mortality prediction models (MPM) in children admitted to paediatric intensive care unit (PICU). The current study was undertaken to develop a better MPM using artificial neural network, a domain of artificial intelligence. The purpose of this retrospective case series was to compare an artificial neural network (ANN) model and PIM with the observed mortality in a cohort of patients admitted to a five-bed PICU in a Hong Kong non-teaching general hospital. The patients were under the age of 17 years and admitted to our PICU from April 2001 to December 2004. Data were collected from each patient admitted to our PICU. All data were randomly allocated to either the training or validation set. The data from the training set were used to construct a series of ANN models. The data from the validation set were used to validate the ANN and PIM models. The accuracy of ANN models and PIM was assessed by area under the receiver operator characteristics (ROC) curve and calibration. All data were randomly allocated to either the training (n=274) or validation set (n=273). Three ANN models were developed using the data from the training set, namely ANN8 (trained with variables required for PIM), ANN9 (trained with variables required for PIM and pre-ICU intubation) and ANN23 (trained with variables required for ANN9 and 14 principal ICU diagnoses). Three ANN models and PIM were used to predict mortality in the validation set. We found that PIM and ANN9 had a high ROC curve (PIM: 0.808, 95 percent confidence interval 0.552 to 1.000, ANN9: 0.957, 95 percent confidence interval 0.915 to 1.000), whereas ANN8 and ANN23 gave a suboptimal area under the ROC curve. ANN8 required only five variables for the calculation of risk, compared with eight for PIM. The current study demonstrated the process of predictive mortality risk model development using ANN. Further multicentre studies are required to

Enzalutamide in Treating Patients With Relapsed or Refractory Mantle Cell Lymphoma

ClinicalTrials.gov

2018-03-27

Ann Arbor Stage I Mantle Cell Lymphoma; Ann Arbor Stage II Mantle Cell Lymphoma; Ann Arbor Stage III Mantle Cell Lymphoma; Ann Arbor Stage IV Mantle Cell Lymphoma; Recurrent Mantle Cell Lymphoma; Refractory Mantle Cell Lymphoma

GASCan 2 payload integration

NASA Technical Reports Server (NTRS)

Cody, Dennis J.; Concepcion, Allan G.; Watras, Edward C., III

1995-01-01

This project, conducted in cooperation with the NASA Advanced Space Design Program, is part of an ongoing effort to place an experiment package into space. The goal of this project is to build and test flight-ready hardware that can be launched from the Space Shuttle. Get Away Special Canister 2 (GASCan 2) consists of three separate experiments. The Ionospheric Properties and Propagation Experiment (IPPE) determines effects of the ionosphere on radio wave propagation. The Microgravity Ignition experiment (MGI) tests the effects of combustion in a microgravity environment. The Rotational Fluid Flow experiment (RFF) examines fluid behavior under varying levels of gravity. This year the following tasks were completed: design of the IPPE antenna, X- and J-cell battery boxes, J-cell battery box enclosure, and structural bumpers; construction of the MGI canisters, MGI mounting brackets, IPPE antenna, and battery boxes; and the selection of the RFF's operating fluid and the analysis of the fluid behavior under microgravity test conditions.

Results of EPR dosimetry for population in the vicinity of the most contaminating radioactive fallout trace after the first nuclear test in the Semipalatinsk test site.

PubMed

Ivannikov, Alexander; Zhumadilov, Kassym; Tieliewuhan, Eldana; Jiao, Ling; Zharlyganova, Dinara; Apsalikov, Kazbek N; Berekenova, Gulnara; Zhumadilov, Zhaxybay; Toyoda, Shin; Miyazawa, Chuzou; Skvortsov, Valeriy; Stepanenko, Valeriy; Endo, Satoru; Tanaka, Kenichi; Hoshi, Masaharu

2006-02-01

The method of electron paramagnetic resonance (EPR) spectroscopy for tooth enamel is applied to individual radiation dose determination to residents of two villages (Dolon and Mostik) in the vicinity of the Semipalatinsk nuclear test site in Kazakhstan. These villages are located near the central axis of the radioactive fallout trace of the most contaminating surface nuclear test conducted in 1949. It is found that excess doses obtained by subtraction of natural background dose from dose absorbed in enamel range up to 440 mGy to residents of Dolon, whose enamel was formed before 1949, and do not exceed 120 mGy to younger residents. To residents of Mostik, excess doses do not exceed 100 mGy regardless of age except for one resident with an extremely high dose of 1.25 Gy. These results are in agreement with the pattern of radioactive contamination of the territory after the nuclear test of 1949 except one case of extremely high dose, which should be additionally investigated.

Study of the radiated energy loss during massive gas injection mitigated disruptions on EAST

NASA Astrophysics Data System (ADS)

Duan, Y. M.; Hao, Z. K.; Hu, L. Q.; Wang, L.; Xu, P.; Xu, L. Q.; Zhuang, H. D.; EAST Team

2015-08-01

The MGI mitigated disruption experiments were carried out on EAST with a new fast gas controlling valve in 2012. Different amounts of noble gas He or mixed gas of 99% He + 1% Ar are injected into plasma in current flat-top phase and current ramp-down phase separately. The initial results of MGI experiments are described. The MGI system and the radiation measurement system are briefly introduced. The characteristics of radiation distribution and radiation energy loss are analyzed. About 50% of the stored thermal energy Wdia is dissipated by radiation during the entire disruption process and the impurities of C and Li from the PFC play important roles to radiative energy loss. The amount of the gas can affect the pre-TQ phase. Strong poloidal asymmetry of radiation begins to appear in the CQ phase, which is possibly caused by the plasma configuration changes as a result of VDE. No toroidal radiation asymmetry is observed presently.

Le groupe de recherches transfusionnelles d’Afrique francophone: bilan des cinq premières années

PubMed Central

Tagny, Claude Tayou; Murphy, Edward L.; Lefrère, Jean-Jacques

2016-01-01

Les travaux de recherches sur la sécurité transfusionnelle en Afrique sub-saharienne sont peu nombreux, souvent limités à des initiatives locales avec des conclusions difficilement représentatives de cette région. Le Groupe de recherches transfusionnelles en Afrique sub-saharienne francophone a été créé en mai 2007 avec pour objectif de développer des stratégies globales d’amélioration de la sécurité transfusionnelle mais adaptables à la situation de chaque pays. Les activités du Groupe à ce jour ont porté essentiellement sur l’obtention de données épidémiologiques et de laboratoire sur la transfusion sanguine et à proposer des stratégies de sécurité transfusionnelle dans le domaine des infections transmissibles par la transfusion. Pour mener à bien ces activités de recherche, le Groupe travaille en étroite collaboration avec les Centres nationaux de transfusion sanguine (CNTS), les Centres régionaux de transfusion sanguine (CRTS), les banques de sang hospitalières (BSH) et les postes de collecte de sang. Pour les 5 premières années, quatre priorités de recherche ont été identifiées: (i) des études descriptives sur les caractéristiques des donneurs de sang et des centres de transfusion; (ii) une estimation du risque résiduel post-transfusionnel des principales infections virales transmissibles par la transfusion; (iii) une analyse des stratégies de sélection médicale des donneurs de sang; et (iv) une description des stratégies de dépistage des ITT et une description du système d’assurance qualité externe existant. Durant cette période, sept projets ont été mis en œuvre au niveau national et publiés et cinq études multicentriques ont été réalisées et publiées. La présente étude rapporte les principales observations et recommandations de ces études. PMID:24360798

Applications of artificial neural networks in medical science.

PubMed

Patel, Jigneshkumar L; Goyal, Ramesh K

2007-09-01

Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

Optimization of metformin HCl 500 mg sustained release matrix tablets using Artificial Neural Network (ANN) based on Multilayer Perceptrons (MLP) model.

PubMed

Mandal, Uttam; Gowda, Veeran; Ghosh, Animesh; Bose, Anirbandeep; Bhaumik, Uttam; Chatterjee, Bappaditya; Pal, Tapan Kumar

2008-02-01

The aim of the present study was to apply the simultaneous optimization method incorporating Artificial Neural Network (ANN) using Multi-layer Perceptron (MLP) model to the development of a metformin HCl 500 mg sustained release matrix tablets with an optimized in vitro release profile. The amounts of HPMC K15M and PVP K30 at three levels (-1, 0, +1) for each were selected as casual factors. In vitro dissolution time profiles at four different sampling times (1 h, 2 h, 4 h and 8 h) were chosen as output variables. 13 kinds of metformin matrix tablets were prepared according to a 2(3) factorial design (central composite) with five extra center points, and their dissolution tests were performed. Commercially available STATISTICA Neural Network software (Stat Soft, Inc., Tulsa, OK, U.S.A.) was used throughout the study. The training process of MLP was completed until a satisfactory value of root square mean (RSM) for the test data was obtained using feed forward back propagation method. The root mean square value for the trained network was 0.000097, which indicated that the optimal MLP model was reached. The optimal tablet formulation based on some predetermined release criteria predicted by MLP was 336 mg of HPMC K15M and 130 mg of PVP K30. Calculated difference (f(1) 2.19) and similarity (f(2) 89.79) factors indicated that there was no difference between predicted and experimentally observed drug release profiles for the optimal formulation. This work illustrates the potential for an artificial neural network with MLP, to assist in development of sustained release dosage forms.

In utero exposure to iodine-131 from Chernobyl fallout and anthropometric characteristics in adolescence.

PubMed

Neta, Gila; Hatch, Maureen; Kitahara, Cari M; Ostroumova, Evgenia; Bolshova, Elena V; Tereschenko, Valery P; Tronko, Mykola D; Brenner, Alina V

2014-03-01

Prenatal exposure to external radiation has been linked to growth retardation among atomic bomb survivors in adolescence. It is unclear from previous studies whether in utero exposure to internal radiation such as iodine-131 (I-131), which concentrates in the thyroid gland, has an effect on physical growth. We examined the associations between estimated thyroid gland dose from prenatal exposure to I-131 and self-reported height and weight in a cohort of 2,460 individuals exposed to radioactive fallout from the 1986 Chernobyl nuclear accident [mean I-131 dose = 72 (mGy)] and screened for thyroid diseases in adolescence. Using multivariable linear regression models, we estimated the mean differences in height, weight and body mass index (BMI) per unit increase in dose (100 mGy) in models adjusted for gender, age at examination, type of residence (rural/urban) and presence of thyroid disease diagnosed at screening. All of the adjustment factors as well as the trimester of exposure were evaluated as potential modifiers of the dose response. Overall, no significant dose response was found for height (P = 0.29), weight (P = 0.14) or BMI (P = 0.16). We found significant modification of the dose response for weight and BMI by presence/absence of thyroid disease (P = 0.02 and P = 0.03, respectively), but not for other factors. In individuals without thyroid disease (n = 1,856), there was a weak, significant association between I-131 thyroid dose and higher weight (210 g per 100 mGy, P = 0.02) or BMI (70 g/m² per 100 mGy, P = 0.02) that depended on individuals (n = 52) exposed to ≥500 mGy. In individuals with thyroid disease (n = 579, 67.4% with simple diffuse goiter) no significant association with I-131 for weight (P = 0.14) or BMI (P = 0.14) was found. These results do not support the hypothesis that in utero exposure to I-131 at levels experienced by a majority of study subjects may be associated with meaningful differences in adolescent anthropometry. However

In Utero Exposure to Iodine-131 from Chernobyl Fallout and Anthropometric Characteristics in Adolescence

PubMed Central

Neta, Gila; Hatch, Maureen; Kitahara, Cari M.; Ostroumova, Evgenia; Bolshova, Elena V.; Tereschenko, Valery P.; Tronko, Mykola D.; Brenner, Alina V.

2014-01-01

Prenatal exposure to external radiation has been linked to growth retardation among atomic bomb survivors in adolescence. It is unclear from previous studies whether in utero exposure to internal radiation such as iodine-131 (I-131), which concentrates in the thyroid gland, has an effect on physical growth. We examined the associations between estimated thyroid gland dose from prenatal exposure to I-131 and self-reported height and weight in a cohort of 2,460 individuals exposed to radioactive fallout from the 1986 Chernobyl nuclear accident [mean I-131 dose = 72 (mGy)] and screened for thyroid diseases in adolescence. Using multivariable linear regression models, we estimated the mean differences in height, weight and body mass index (BMI) per unit increase in dose (100 mGy) in models adjusted for gender, age at examination, type of residence (rural/urban) and presence of thyroid disease diagnosed at screening. All of the adjustment factors as well as the trimester of exposure were evaluated as potential modifiers of the dose response. Overall, no significant dose response was found for height (P = 0.29), weight (P = 0.14) or BMI (P = 0.16). We found significant modification of the dose response for weight and BMI by presence/absence of thyroid disease (P = 0.02 and P = 0.03, respectively), but not for other factors. In individuals without thyroid disease (n = 1,856), there was a weak, significant association between I-131 thyroid dose and higher weight (210 g per 100 mGy, P = 0.02) or BMI (70 g/m2 per 100 mGy, P = 0.02) that depended on individuals (n = 52) exposed to ≥500 mGy. In individuals with thyroid disease (n = 579, 67.4% with simple diffuse goiter) no significant association with I-131 for weight (P = 0.14) or BMI (P = 0.14) was found. These results do not support the hypothesis that in utero exposure to I-131 at levels experienced by a majority of study subjects may be associated with meaningful differences in adolescent anthropometry. However

Adaptive statistical iterative reconstruction: reducing dose while preserving image quality in the pediatric head CT examination.

PubMed

McKnight, Colin D; Watcharotone, Kuanwong; Ibrahim, Mohannad; Christodoulou, Emmanuel; Baer, Aaron H; Parmar, Hemant A

2014-08-01

Over the last decade there has been escalating concern regarding the increasing radiation exposure stemming from CT exams, particularly in children. Adaptive statistical iterative reconstruction (ASIR) is a relatively new and promising tool to reduce radiation dose while preserving image quality. While encouraging results have been found in adult head and chest and body imaging, validation of this technique in pediatric population is limited. The objective of our study was to retrospectively compare the image quality and radiation dose of pediatric head CT examinations obtained with ASIR compared to pediatric head CT examinations without ASIR in a large patient population. Retrospective analysis was performed on 82 pediatric head CT examinations. This group included 33 pediatric head CT examinations obtained with ASIR and 49 pediatric head CT examinations without ASIR. Computed tomography dose index (CTDIvol) was recorded on all examinations. Quantitative analysis consisted of standardized measurement of attenuation and the standard deviation at the bilateral centrum semiovale and cerebellar white matter to evaluate objective noise. Qualitative analysis consisted of independent assessment by two radiologists in a blinded manner of gray-white differentiation, sharpness and overall diagnostic quality. The average CTDIvol value of the ASIR group was 21.8 mGy (SD = 4.0) while the average CTDIvol for the non-ASIR group was 29.7 mGy (SD = 13.8), reflecting a statistically significant reduction in CTDIvol in the ASIR group (P < 0.01). There were statistically significant reductions in CTDI for the 3- to 12-year-old ASIR group as compared to the 3- to 12-year-old non-ASIR group (21.5 mGy vs. 30.0 mGy; P = 0.004) as well as statistically significant reductions in CTDI for the >12-year-old ASIR group as compared to the >12-year-old non-ASIR group (29.7 mGy vs. 49.9 mGy; P = 0.0002). Quantitative analysis revealed no significant difference in the

Investigating the dose distribution in the uncompressed breast with a dedicated CT mammotomography system

NASA Astrophysics Data System (ADS)

Crotty, Dominic J.; Brady, Samuel L.; Jackson, D'Vone C.; Toncheva, Greta I.; Anderson, Colin E.; Yoshizumi, Terry T.; Tornai, Martin P.

2010-04-01

A dual modality SPECT-CT prototype dedicated to uncompressed breast imaging (mammotomography) has been developed. The CT subsystem incorporates an ultra-thick K-edge filtration technique producing a quasi-monochromatic x-ray cone beam to optimize the dose efficiency for uncompressed breast tomography. We characterize the absorbed dose to the breast under normal tomographic cone beam image acquisition protocols using both TLD measurements and ionization chamber-calibrated radiochromic film. Geometric and anthropomorphic breast phantoms are filled with 1000mL of water and oil to simulate different breast compositions and varying object shapes having density bounds of 100% glandular and fatty breast compositions, respectively. Doses to the water filled geometric and anthropomorphic breast phantoms for a tomographic scan range from 1.3-7.3mGy and 1.7-6.3mGy, respectively, with a mean whole-breast dose of 4.5mGy for the water-filled anthropomorphic phantom. Measured dose distribution trends indicate lower doses in the center of the breast phantoms towards the chest wall along with higher doses near the peripheries and nipple regions. Measured doses to the oil-filled phantoms are consistently lower across all volume shapes (mean dose, 3.8mGy for the anthropomorphic breast). Results agree with Monte Carlo dose estimates generated for uncompressed breast imaging and illustrate the advantages of using the novel K-edge filtered beam to minimize absorbed dose to the breast during fully-3D imaging.

Dosimetric measurements and comparison studies in digital imaging system

NASA Astrophysics Data System (ADS)

Jung, Ji-Young; Kim, Hee-Joung; Lee, Chang-Lae; Cho, Hyo-Min; Nam, Sora

2008-03-01

Number of radiologic exams using digital imaging systems has rapidly increased with advanced imaging technologies. However, it has not been paid attention to the radiation dose in clinical situations. It was the motivation to study radiation dosimetry in the DR system. The objective of this study was to measure beam quality and patient's dose using DR system and to compare them to both IEC standard and IAEA guidelines. The measured average dose for chest and abdomen was 1.376 mGy and 9.501 mGy, respectively, compared to 0.4 mGy and 10.0 mGy in IAEA guidelines. The results also indicated that the DR system has a lower radiation beam quality than that of the IEC standard. The results showed that the patients may be exposed higher radiation for chest exams and lower radiation for abdomen exams using DR system. IAEA Guidelines were prepared based on western people which may be different weight and height for patients compared them to Korean. In conclusion, a new guideline for acceptable DR dosimetry for Korean patients may need to be developed with further studies for large populations. We believe that this research greatly help to introduce the importance of the dosimetry in diagnostic radiology in Korea. And, a development of database for dosimetry in diagnostic radiology will become an opportunity of making aware of radiation safety of medical examination to patient.

Low-dose/dose-rate γ radiation depresses neural differentiation and alters protein expression profiles in neuroblastoma SH-SY5Y cells and C17.2 neural stem cells.

PubMed

Bajinskis, Ainars; Lindegren, Heléne; Johansson, Lotta; Harms-Ringdahl, Mats; Forsby, Anna

2011-02-01

The effects of low doses of ionizing radiation on cellular development in the nervous system are presently unclear. The focus of the present study was to examine low-dose γ-radiation-induced effects on the differentiation of neuronal cells and on the development of neural stem cells to glial cells. Human neuroblastoma SH-SY5Y cells were exposed to (137)Cs γ rays at different stages of retinoic acid-induced neuronal differentiation, and neurite formation was determined 6 days after exposure. When SH-SY5Y cells were exposed to low-dose-rate γ rays at the onset of differentiation, the number of neurites formed per cell was significantly less after exposure to either 10, 30 or 100 mGy compared to control cells. Exposure to 10 and 30 mGy attenuated differentiation of immature C17.2 mouse-derived neural stem cells to glial cells, as verified by the diminished expression of glial fibrillary acidic protein. Proteomic analysis of the neuroblastoma cells by 2D-PAGE after 30 mGy irradiation showed that proteins involved in neuronal development were downregulated. Proteins involved in cell cycle and proliferation were altered in both cell lines after exposure to 30 mGy; however, the rate of cell proliferation was not affected in the low-dose range. The radiation-induced attenuation of differentiation and the persistent changes in protein expression is indicative of an epigenetic rather than a cytotoxic mechanism.

Nonlinear ionizing radiation-induced changes in eye lens cell proliferation, cyclin D1 expression and lens shape.

PubMed

Markiewicz, Ewa; Barnard, Stephen; Haines, Jackie; Coster, Margaret; van Geel, Orry; Wu, Weiju; Richards, Shane; Ainsbury, Elizabeth; Rothkamm, Kai; Bouffler, Simon; Quinlan, Roy A

2015-04-01

Elevated cataract risk after radiation exposure was established soon after the discovery of X-rays in 1895. Today, increased cataract incidence among medical imaging practitioners and after nuclear incidents has highlighted how little is still understood about the biological responses of the lens to low-dose ionizing radiation (IR). Here, we show for the first time that in mice, lens epithelial cells (LECs) in the peripheral region repair DNA double strand breaks (DSB) after exposure to 20 and 100 mGy more slowly compared with circulating blood lymphocytes, as demonstrated by counts of γH2AX foci in cell nuclei. LECs in the central region repaired DSBs faster than either LECs in the lens periphery or lymphocytes. Although DSB markers (γH2AX, 53BP1 and RAD51) in both lens regions showed linear dose responses at the 1 h timepoint, nonlinear responses were observed in lenses for EdU (5-ethynyl-2'-deoxy-uridine) incorporation, cyclin D1 staining and cell density after 24 h at 100 and 250 mGy. After 10 months, the lens aspect ratio was also altered, an indicator of the consequences of the altered cell proliferation and cell density changes. A best-fit model demonstrated a dose-response peak at 500 mGy. These data identify specific nonlinear biological responses to low (less than 1000 mGy) dose IR-induced DNA damage in the lens epithelium.

Nonlinear ionizing radiation-induced changes in eye lens cell proliferation, cyclin D1 expression and lens shape

PubMed Central

Markiewicz, Ewa; Barnard, Stephen; Haines, Jackie; Coster, Margaret; van Geel, Orry; Wu, Weiju; Richards, Shane; Ainsbury, Elizabeth; Rothkamm, Kai; Bouffler, Simon; Quinlan, Roy A.

2015-01-01

Elevated cataract risk after radiation exposure was established soon after the discovery of X-rays in 1895. Today, increased cataract incidence among medical imaging practitioners and after nuclear incidents has highlighted how little is still understood about the biological responses of the lens to low-dose ionizing radiation (IR). Here, we show for the first time that in mice, lens epithelial cells (LECs) in the peripheral region repair DNA double strand breaks (DSB) after exposure to 20 and 100 mGy more slowly compared with circulating blood lymphocytes, as demonstrated by counts of γH2AX foci in cell nuclei. LECs in the central region repaired DSBs faster than either LECs in the lens periphery or lymphocytes. Although DSB markers (γH2AX, 53BP1 and RAD51) in both lens regions showed linear dose responses at the 1 h timepoint, nonlinear responses were observed in lenses for EdU (5-ethynyl-2′-deoxy-uridine) incorporation, cyclin D1 staining and cell density after 24 h at 100 and 250 mGy. After 10 months, the lens aspect ratio was also altered, an indicator of the consequences of the altered cell proliferation and cell density changes. A best-fit model demonstrated a dose-response peak at 500 mGy. These data identify specific nonlinear biological responses to low (less than 1000 mGy) dose IR-induced DNA damage in the lens epithelium. PMID:25924630

Effect of Photon Hormesis on Dose Responses to Alpha Particles in Zebrafish Embryos.

PubMed

Ng, Candy Yuen Ping; Cheng, Shuk Han; Yu, Kwan Ngok

2017-02-11

Photon hormesis refers to the phenomenon where the biological effect of ionizing radiation with a high linear energy transfer (LET) value is diminished by photons with a low LET value. The present paper studied the effect of photon hormesis from X-rays on dose responses to alpha particles using embryos of the zebrafish ( Danio rerio ) as the in vivo vertebrate model. The toxicity of these ionizing radiations in the zebrafish embryos was assessed using the apoptotic counts at 20, 24, or 30 h post fertilization (hpf) revealed through acridine orange (AO) staining. For alpha-particle doses ≥ 4.4 mGy, the additional X-ray dose of 10 mGy significantly reduced the number of apoptotic cells at 24 hpf, which proved the presence of photon hormesis. Smaller alpha-particle doses might not have inflicted sufficient aggregate damages to trigger photon hormesis. The time gap T between the X-ray (10 mGy) and alpha-particle (4.4 mGy) exposures was also studied. Photon hormesis was present when T ≤ 30 min, but was absent when T = 60 min, at which time repair of damage induced by alpha particles would have completed to prevent their interactions with those induced by X-rays. Finally, the drop in the apoptotic counts at 24 hpf due to photon hormesis was explained by bringing the apoptotic events earlier to 20 hpf, which strongly supported the removal of aberrant cells through apoptosis as an underlying mechanism for photon hormesis.

Chromosome aberrations in workers occupationally exposed to tritium.

PubMed

Tawn, E Janet; Curwen, Gillian B; Riddell, Anthony E

2018-06-01

This paper reports the findings of an historical chromosome analysis for unstable aberrations, undertaken on 34 nuclear workers with monitored exposure to tritium. The mean recorded β-particle dose from tritium was 9.33 mGy (range 0.25-79.71 mGy) and the mean occupational dose from external, mainly γ-ray, irradiation was 1.94 mGy (range 0.00-7.71 mGy). The dicentric frequency of 1.91 ± 0.53 × 10 -3 per cell was significantly raised, in comparison with that of 0.61 ± 0.30 × 10 -3 per cell for a group of 66 comparable worker controls unexposed to occupational radiation. The frequency of total aberrations was also significantly higher in the tritium workers. Comparisons with in vitro studies indicate that at these dose levels an increase in aberration frequency is not expected. However, the available historical tritium dose records were produced for the purposes of radiological protection and based on a methodology that has since been updated, so tritium doses are subject to considerable uncertainty. It is therefore recommended that, if possible, tritium doses are reassessed using information on historical recording practices in combination with current dosimetry methodology, and that further chromosome studies are undertaken using modern FISH techniques to establish stable aberration frequencies, as these will provide information on a cumulative biological effect.

Experiences with the European guidelines on quality criteria for radiographic images in Tanzania

PubMed Central

Muhogora, W. E.; Nyanda, A. M.; Kazema, R. R.

2001-01-01

Objective assessment of the quality of radiographic images is practically a difficult task and protocols that address this problem are few. In 1996, the European union published nearly objective image quality criteria to unify the practices in Europe. However, experience with these criteria in countries of lower health care levels is little documented. As a case study in Tanzania, we present the general performance of European guidelines in some Tanzanian hospitals to a total of 200 radiographs obtained from some common x‐ray examinations. The results show that more than 70% of chest (PA), lumbar spine (AP), and pelvis AP radiographs passed the quality criteria, while the performance of lumbar spine LAT x‐ray examinations was about 50% and therefore less satisfactory. The corresponding mean entrance dose to the patient for specified x‐ray techniques was of range 0.08–0.56 mGy, 3.1–7.7 mGy, 2.53–5.4 mGy, and 4.0–16.78 mGy for chest PA, lumbar spine AP, pelvis AP and lumbar spine LAT x‐ray examinations, respectively. Although a good number of observers were not well familiar to the guidelines, the quality criteria have been found useful and their adoption in the country recommended. The need to provide relevant education and training to staff in the radiology departments is of utmost importance. PACS number(s): 87.57.–s, 87.52.–g PMID:11686743

A New Artificial Neural Network Enhanced by the Shuffled Complex Evolution Optimization with Principal Component Analysis (SP-UCI) for Water Resources Management

NASA Astrophysics Data System (ADS)

Hayatbini, N.; Faridzad, M.; Yang, T.; Akbari Asanjan, A.; Gao, X.; Sorooshian, S.

2016-12-01

The Artificial Neural Networks (ANNs) are useful in many fields, including water resources engineering and management. However, due to the non-linear and chaotic characteristics associated with natural processes and human decision making, the use of ANNs in real-world applications is still limited, and its performance needs to be further improved for a broader practical use. The commonly used Back-Propagation (BP) scheme and gradient-based optimization in training the ANNs have already found to be problematic in some cases. The BP scheme and gradient-based optimization methods are associated with the risk of premature convergence, stuck in local optimums, and the searching is highly dependent on initial conditions. Therefore, as an alternative to BP and gradient-based searching scheme, we propose an effective and efficient global searching method, termed the Shuffled Complex Evolutionary Global optimization algorithm with Principal Component Analysis (SP-UCI), to train the ANN connectivity weights. Large number of real-world datasets are tested with the SP-UCI-based ANN, as well as various popular Evolutionary Algorithms (EAs)-enhanced ANNs, i.e., Particle Swarm Optimization (PSO)-, Genetic Algorithm (GA)-, Simulated Annealing (SA)-, and Differential Evolution (DE)-enhanced ANNs. Results show that SP-UCI-enhanced ANN is generally superior over other EA-enhanced ANNs with regard to the convergence and computational performance. In addition, we carried out a case study for hydropower scheduling in the Trinity Lake in the western U.S. In this case study, multiple climate indices are used as predictors for the SP-UCI-enhanced ANN. The reservoir inflows and hydropower releases are predicted up to sub-seasonal to seasonal scale. Results show that SP-UCI-enhanced ANN is able to achieve better statistics than other EAs-based ANN, which implies the usefulness and powerfulness of proposed SP-UCI-enhanced ANN for reservoir operation, water resources engineering and management

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database

PubMed Central

Drabkin, Harold J.; Blake, Judith A.

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as ‘GO’ or ‘homology’ or ‘phenotype’. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as ‘papers selected for GO that refer to genes with NO GO annotation’. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database.

PubMed

Drabkin, Harold J; Blake, Judith A

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as 'GO' or 'homology' or 'phenotype'. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as 'papers selected for GO that refer to genes with NO GO annotation'. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported

Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool.

PubMed

Brady, S L; Kaufman, R A

2015-05-01

To develop an automated methodology to estimate patient examination dose in digital radiography (DR) imaging using DICOM metadata as a quality assurance (QA) tool. Patient examination and demographical information were gathered from metadata analysis of DICOM header data. The x-ray system radiation output (i.e., air KERMA) was characterized for all filter combinations used for patient examinations. Average patient thicknesses were measured for head, chest, abdomen, knees, and hands using volumetric images from CT. Backscatter factors (BSFs) were calculated from examination kVp. Patient entrance skin air KERMA (ESAK) was calculated by (1) looking up examination technique factors taken from DICOM header metadata (i.e., kVp and mA s) to derive an air KERMA (k air) value based on an x-ray characteristic radiation output curve; (2) scaling k air with a BSF value; and (3) correcting k air for patient thickness. Finally, patient entrance skin dose (ESD) was calculated by multiplying a mass-energy attenuation coefficient ratio by ESAK. Patient ESD calculations were computed for common DR examinations at our institution: dual view chest, anteroposterior (AP) abdomen, lateral (LAT) skull, dual view knee, and bone age (left hand only) examinations. ESD was calculated for a total of 3794 patients; mean age was 11 ± 8 yr (range: 2 months to 55 yr). The mean ESD range was 0.19-0.42 mGy for dual view chest, 0.28-1.2 mGy for AP abdomen, 0.18-0.65 mGy for LAT view skull, 0.15-0.63 mGy for dual view knee, and 0.10-0.12 mGy for bone age (left hand) examinations. A methodology combining DICOM header metadata and basic x-ray tube characterization curves was demonstrated. In a regulatory era where patient dose reporting has become increasingly in demand, this methodology will allow a knowledgeable user the means to establish an automatable dose reporting program for DR and perform patient dose related QA testing for digital x-ray imaging.

Characterization of MOSFET dosimeters for low‐dose measurements in maxillofacial anthropomorphic phantoms

PubMed Central

Wolff, Jan E.; Kiljunen, Timo; Schulze, Dirk; Kortesniemi, Mika

2015-01-01

The aims of this study were to characterize reinforced metal‐oxide‐semiconductor field‐effect transistor (MOSFET) dosimeters to assess the measurement uncertainty, single exposure low‐dose limit with acceptable accuracy, and the number of exposures required to attain the corresponding limit of the thermoluminescent dosimeters (TLD). The second aim was to characterize MOSFET dosimeter sensitivities for two dental photon energy ranges, dose dependency, dose rate dependency, and accumulated dose dependency. A further aim was to compare the performance of MOSFETs with those of TLDs in an anthropomorphic phantom head using a dentomaxillofacial CBCT device. The uncertainty was assessed by exposing 20 MOSFETs and a Barracuda MPD reference dosimeter. The MOSFET dosimeter sensitivities were evaluated for two photon energy ranges (50–90 kVp) using a constant dose and polymethylmethacrylate backscatter material. MOSFET and TLD comparative point‐dose measurements were performed on an anthropomorphic phantom that was exposed with a clinical CBCT protocol. The MOSFET single exposure low dose limit (25% uncertainty, k=2) was 1.69 mGy. An averaging of eight MOSFET exposures was required to attain the corresponding TLD (0.3 mGy) low‐dose limit. The sensitivity was 3.09±0.13 mV/mGy independently of the photon energy used. The MOSFET dosimeters did not present dose or dose rate sensitivity but, however, presented a 1% decrease of sensitivity per 1000 mV for accumulated threshold voltages between 8300 mV and 17500 mV. The point doses in an anthropomorphic phantom ranged for MOSFETs between 0.24 mGy and 2.29 mGy and for TLDs between 0.25 and 2.09 mGy, respectively. The mean difference was −8%. The MOSFET dosimeters presented statistically insignificant energy dependency. By averaging multiple exposures, the MOSFET dosimeters can achieve a TLD‐comparable low‐dose limit and constitute a feasible method for diagnostic dosimetry using anthropomorphic phantoms. However

SU-F-P-45: Clinical Experience with Radiation Dose Reduction of CT Examinations Using Iterative Reconstruction Algorithms

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

Weir, V; Zhang, J

2016-06-15

Purpose: Iterative reconstruction (IR) algorithms have been adopted by medical centers in the past several years. IR has a potential to substantially reduce patient dose while maintaining or improving image quality. This study characterizes dose reductions in clinical settings for CT examinations using IR. Methods: We retrospectively analyzed dose information from patients who underwent abdomen/pelvis CT examinations with and without contrast media in multiple locations of our Healthcare system. A total of 743 patients scanned with ASIR on 64 slice GE lightspeed VCTs at three sites, and 30 patients scanned with SAFIRE on a Siemens 128 slice Definition Flash inmore » one site was retrieved. For comparison, patient data (n=291) from a GE scanner and patient data (n=61) from two Siemens scanners where filtered back-projection (FBP) was used was collected retrospectively. 30% and 10% ASIR, and SAFIRE Level 2 was used. CTDIvol, Dose-length-product (DLP), weight and height from all patients was recorded. Body mass index (BMI) was calculated accordingly. To convert CTDIvol to SSDE, AP and lateral dimensions at the mid-liver level was measured for each patient. Results: Compared with FBP, 30% ASIR reduces dose by 44.1% (SSDE: 12.19mGy vs. 21.83mGy), while 10% ASIR reduced dose by 20.6% (SSDE 17.32mGy vs. 21.83). Use of SAFIRE reduced dose by 61.4% (SSDE: 8.77mGy vs. 22.7mGy). The geometric mean for patients scanned with ASIR was larger than for patients scanned with FBP (geometric mean is 297.48 mmm vs. 284.76 mm). The same trend was observed for the Siemens scanner where SAFIRE was used (geometric mean: 316 mm with SAFIRE vs. 239 mm with FBP). Patient size differences suggest that further dose reduction is possible. Conclusion: Our data confirmed that in clinical practice IR can significantly reduce dose to patients who undergo CT examinations, while meeting diagnostic requirements for image quality.« less

Prospective Evaluation of Prior Image Constrained Compressed Sensing (PICCS) Algorithm in Abdominal CT: A comparison of reduced dose with standard dose imaging

PubMed Central

Lubner, Meghan G.; Pickhardt, Perry J.; Kim, David H.; Tang, Jie; Munoz del Rio, Alejandro; Chen, Guang-Hong

2014-01-01

Purpose To prospectively study CT dose reduction using the “prior image constrained compressed sensing” (PICCS) reconstruction technique. Methods Immediately following routine standard dose (SD) abdominal MDCT, 50 patients (mean age, 57.7 years; mean BMI, 28.8) underwent a second reduced-dose (RD) scan (targeted dose reduction, 70-90%). DLP, CTDIvol and SSDE were compared. Several reconstruction algorithms (FBP, ASIR, and PICCS) were applied to the RD series. SD images with FBP served as reference standard. Two blinded readers evaluated each series for subjective image quality and focal lesion detection. Results Mean DLP, CTDIvol, and SSDE for RD series was 140.3 mGy*cm (median 79.4), 3.7 mGy (median 1.8), and 4.2 mGy (median 2.3) compared with 493.7 mGy*cm (median 345.8), 12.9 mGy (median 7.9 mGy) and 14.6 mGy (median 10.1) for SD series, respectively. Mean effective patient diameter was 30.1 cm (median 30), which translates to a mean SSDE reduction of 72% (p<0.001). RD-PICCS image quality score was 2.8±0.5, improved over the RD-FBP (1.7±0.7) and RD-ASIR(1.9±0.8)(p<0.001), but lower than SD (3.5±0.5)(p<0.001). Readers detected 81% (184/228) of focal lesions on RD-PICCS series, versus 67% (153/228) and 65% (149/228) for RD-FBP and RD-ASIR, respectively. Mean image noise was significantly reduced on RD-PICCS series (13.9 HU) compared with RD-FBP (57.2) and RD-ASIR (44.1) (p<0.001). Conclusion PICCS allows for marked dose reduction at abdominal CT with improved image quality and diagnostic performance over reduced-dose FBP and ASIR. Further study is needed to determine indication-specific dose reduction levels that preserve acceptable diagnostic accuracy relative to higher-dose protocols. PMID:24943136

[Application of an artificial neural network in the design of sustained-release dosage forms].

PubMed

Wei, X H; Wu, J J; Liang, W Q

2001-09-01

To use the artificial neural network (ANN) in Matlab 5.1 tool-boxes to predict the formulations of sustained-release tablets. The solubilities of nine drugs and various ratios of HPMC: Dextrin for 63 tablet formulations were used as the ANN model input, and in vitro accumulation released at 6 sampling times were used as output. The ANN model was constructed by selecting the optimal number of iterations (25) and model structure in which there are one hidden layer and five hidden layer nodes. The optimized ANN model was used for prediction of formulation based on desired target in vitro dissolution-time profiles. ANN predicted profiles based on ANN predicted formulations were closely similar to the target profiles. The ANN could be used for predicting the dissolution profiles of sustained release dosage form and for the design of optimal formulation.

Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model in a Three-Gorge Watershed of China

PubMed Central

Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

2012-01-01

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93). Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34) and 2003–2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2·y−1. Sloping areas and low coverage areas are the main source of soil loss in the

[Estimation of Maximum Entrance Skin Dose during Cerebral Angiography].

PubMed

Kawauchi, Satoru; Moritake, Takashi; Hayakawa, Mikito; Hamada, Yusuke; Sakuma, Hideyuki; Yoda, Shogo; Satoh, Masayuki; Sun, Lue; Koguchi, Yasuhiro; Akahane, Keiichi; Chida, Koichi; Matsumaru, Yuji

2015-09-01

Using radio-photoluminescence glass dosimeter, we measured the entrance skin dose (ESD) in 46 cases and analyzed the correlations between maximum ESD and angiographic parameters [total fluoroscopic time (TFT); number of digital subtraction angiography (DSA) frames, air kerma at the interventional reference point (AK), and dose-area product (DAP)] to estimate the maximum ESD in real time. Mean (± standard deviation) maximum ESD, dose of the right lens, and dose of the left lens were 431.2 ± 135.8 mGy, 33.6 ± 15.5 mGy, and 58.5 ± 35.0 mGy, respectively. Correlation coefficients (r) between maximum ESD and TFT, number of DSA frames, AK, and DAP were r=0.379 (P<0.01), r=0.702 (P<0.001), r=0.825 (P<0.001), and r=0.709 (P<0.001), respectively. AK was identified as the most useful parameter for real-time prediction of maximum ESD. This study should contribute to the development of new diagnostic reference levels in our country.

Optimizing a readout protocol for low dose retrospective OSL-dosimetry using household salt.

PubMed

Christiansson, Maria; Mattsson, Sören; Bernhardsson, Christian; Rääf, Christopher L

2012-06-01

The authors' aim has been to find a single aliquot regenerative dose (SAR) protocol that accurately recovers an unknown absorbed dose in the region between 1-250 mGy in household salt. The main investigation has been conducted on a specific mine salt (>98.5% NaCl) intended for household use, using optical stimulation by blue LED (λ = 462 nm). The most accurate dose recovery for this brand of salt is found to be achieved when using Peak Signal Summing (PSS) of the OSL-decay and a preheat temperature of 200°C after the test dose. A SAR protocol for the household salt with preset values of regenerative doses (R1--R5) and a test dose (TED) of 17 mGy is also suggested here. Under laboratory conditions, the suggested protocol recovers unknown absorbed doses in this particular brand within 5% (2 SD) in the dose range between 1-250 mGy. This is a very promising result for low dose applications of household salt as a retrospective dosimeter after a nuclear or radiological event.

Mitochondrial Genome Integrity Mutations Uncouple the Yeast Saccharomyces cerevisiae ATP Synthase*║

PubMed Central

Wang, Yamin; Singh, Usha; Mueller, David M.

2013-01-01

The mitochondrial ATP synthase is a molecular motor, which couples the flow of rotons with phosphorylation of ADP. Rotation of the central stalk within the core of ATP synthase effects conformational changes in the active sites driving the synthesis of ATP. Mitochondrial genome integrity (mgi) mutations have been previously identified in the α-, β-, and γ-subunits of ATP synthase in yeast Kluyveromyces lactis and trypanosome Trypanosoma brucei. These mutations reverse the lethality of the loss of mitochondrial DNA in petite negative strains. Introduction of the homologous mutations in Saccharomyces cerevisiae results in yeast strains that lose mitochondrial DNA at a high rate and accompanied decreases in the coupling of the ATP synthase. The structure of yeast F1-ATPase reveals that the mgi residues cluster around the γ-subunit and selectively around the collar region of F1. These results indicate that residues within the mgi complementation group are necessary for efficient coupling of ATP synthase, possibly acting as a support to fix the axis of rotation of the central stalk. PMID:17244612

Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

PubMed

Tigges, P; Kathmann, N; Engel, R R

1997-07-01

Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.

PubMed

Kim, Seongjung; Kim, Jongman; Ahn, Soonjae; Kim, Youngho

2018-04-18

Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and 7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.

Artificial intelligence against breast cancer (A.N.N.E.S-B.C.-Project).

PubMed

Parmeggiani, Domenico; Avenia, Nicola; Sanguinetti, Alessandro; Ruggiero, Roberto; Docimo, Giovanni; Siciliano, Mattia; Ambrosino, Pasquale; Madonna, Imma; Peltrini, Roberto; Parmeggiani, Umberto

2012-01-01

Our preliminary study examined the development of an advanced innovative technology with the objectives of--developing methodologies and algorithms for a Artificial Neural Network (ANN) system, improving mammography and ultra-sonography images interpretation;--creating autonomous software as a diagnostic tool for the physicians, allowing the possibility for the advanced application of databases using Artificial Intelligence (Expert System). Since 2004 550 F patients over 40 yrs old were divided in two groups: 1) 310 pts underwent echo every 6 months and mammography every year by expert radiologists. 2) 240 pts had the same screening program and were also examined by our diagnosis software, developed with ANN-ES technology by the Engineering Aircraft Research Project team. The information was continually updated and returned to the Expert System, defining the principal rules of automatic diagnosis. In the second group we selected: Expert radiologist decision; ANN-ES decision; Expert radiologists with ANN-ES decision. The second group had significantly better diagnosis for cancer and better specificity for breast lesions risk as well as the highest percentage account when the radiologist's decision was helped by the ANN software. The ANN-ES group was able to select, by anamnestic, diagnostic and genetic means, 8 patients for prophylactic surgery, finding 4 cancers in a very early stage. Although it is only a preliminary study, this innovative diagnostic tool seems to provide better positive and negative predictive value in cancer diagnosis as well as in breast risk lesion identification.

Neural networks in chemistry

NASA Astrophysics Data System (ADS)

Zupan, Jure

1995-04-01

All problems that in some way are linked to handling of multi-variate experiments versus multi-variate responses can be approached by the group of methods that has recently became known as the artificial neural network (ANN) techniques. In this lecture, the types of the problems that can be solved by ANN techniques rather than the ANN techniques themselves will be addressed first. This issue is rather important due to the fact that the ANN techniques can be used for a very broad range of problems and choosing the wrong method can often result in either a failure to produce an effective solution or in a very time consuming and ineffective handling. Among the types of problems that can be solved by different ANN techniques the classification, mapping, look-up table, and modelling will be emphasized and discussed. Because all mentioned methods can be solved by different standard techniques, special emphasis will be paid to stress the advantages and drawbacks when employing different ANN techniques. Due to the fact that the range of possible use of ANN is so broad, even a very specific problem can be solved by many different ANN architectures or even using different learning strategies within ANN. In the second part the main learning strategies and corresponding choices of ANN architectures will be discussed. In this part the parameters and some guidelines how to select the method and the design of the ANNs will be shown on the examples of reported ANN applications in chemistry. The ANN learning strategies discussed will be back-propagation of errors, the Kohonen, and the counter propagation learning. The potential user of ANN should first, consider the problem, second, he must inspect the availability of data and the data themselves to decide for which ANN method they are best suited. In this respect, the amount of data, the dimensionality of the measurement space, the form of data (alphanumeric entries, binary, real, or even mixed forms of data) are crucial. After

Dosimetric study of mandible examinations performed with three cone-beam computed tomography scanners.

PubMed

Khoury, Helen J; Andrade, Marcos E; Araujo, Max Well; Brasileiro, Izabela V; Kramer, Richard; Huda, Amir

2015-07-01

The objective of this work was to evaluate the air kerma-area product (PKA) and the skin absorbed dose in the region of the eyes, salivary glands and thyroid of the patient from mandible examinations performed with three cone-beam computed tomography (CBCT) scanners, i.e. i-CAT classic, Gendex CB-500 and PreXion 3D. For the dosimetric evaluation, an anthropomorphic head phantom (model RS-250) was used to simulate an adult patient. The CBCT examinations were performed using standard and high-resolution protocols for mandible acquisitions for adult patients. During the phantom's exposure, the PKA was measured using an ionising chamber and the absorbed doses to the skin in the region of the eyes, thyroid and salivary glands were estimated using thermoluminescence dosemeters (TLDs) positioned on the phantom's surface. The PKA values estimated with the CBCT scanners varied from 26 to 138 µGy m(2). Skin absorbed doses in the region of the eyes varied from 0.07 to 0.34 mGy; at the parotid glands, from 1.31 to 5.93 mGy; at the submandibular glands, from 1.41 to 6.86 mGy; and at the thyroid, from 0.18 to 2.45 mGy. PKA and absorbed doses showed the highest values for the PreXion 3D scanner due to the use of the continuous exposure mode and a high current-time product. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Increasing antiplaque/antigingivitis efficacy of an essential oil mouthrinse over time: an in vivo study.

PubMed

Charles, Christine A; McGuire, J A; Qaqish, James; Amini, Pejmon

2013-01-01

This randomized, observer-blind, parallel, controlled study determined the efficacy of an essential oils-containing (EO) antiseptic mouthrinse (in conjunction with toothbrushing) in reducing and/or controlling existing plaque or gingivitis over 6 months. Toothbrushing, combined with placebo rinsing, served as the control (C). Following ethics board approval (Biosci Research Canada, Ltd. Institutional Review Board), 139 healthy adults with mild to moderate plaque and gingivitis were randomized into EO or C groups. All subjects received oral/written instructions, monthly monitoring, and assigned unsupervised rinses. Efficacy variables were whole-mouth mean modified gingival index (MGI), Turesky modification of the Quigley Hein plaque index (PI), bleeding index (BI) at 6, 12, and 24 weeks, and data analysis through an analysis of covariance (ANCOVA) model. The EO group provided greater and increasing MGI, PI, and BI reductions than did C group over all examination periods. Compared to the C group, at 6, 12, and 24 weeks, MGI reductions for the EO group were 4.7%, 9.1%, and 20.4%, and PI reductions were 7.6%, 12.6%, and 26.3%, respectively. BI scores decreased over time and were significant compared to those for the C group (P < 0.001). Additionally, the percentages of sites improved versus baseline MGI over time for EO were 14.1%, 26.4%, and 43.3%, respectively. This study demonstrated that an EO-containing mouthrinse can provide an increasing benefit over a period of 6 months with twice daily use. This study also confirmed that an antiseptic EO rinse can provide a clinically significant benefit in reducing existing plaque and gingivitis.

Genome-enabled transcriptomics reveals archaeal populations that drive nitrification in a deep-sea hydrothermal plume.

PubMed

Baker, Brett J; Lesniewski, Ryan A; Dick, Gregory J

2012-12-01

Ammonia-oxidizing Archaea (AOA) are among the most abundant microorganisms in the oceans and have crucial roles in biogeochemical cycling of nitrogen and carbon. To better understand AOA inhabiting the deep sea, we obtained community genomic and transcriptomic data from ammonium-rich hydrothermal plumes in the Guaymas Basin (GB) and from surrounding deep waters of the Gulf of California. Among the most abundant and active lineages in the sequence data were marine group I (MGI) Archaea related to the cultured autotrophic ammonia-oxidizer, Nitrosopumilus maritimus. Assembly of MGI genomic fragments yielded 2.9 Mb of sequence containing seven 16S rRNA genes (95.4-98.4% similar to N. maritimus), including two near-complete genomes and several lower-abundance variants. Equal copy numbers of MGI 16S rRNA genes and ammonia monooxygenase genes and transcription of ammonia oxidation genes indicates that all of these genotypes actively oxidize ammonia. De novo genomic assembly revealed the functional potential of MGI populations and enhanced interpretation of metatranscriptomic data. Physiological distinction from N. maritimus is evident in the transcription of novel genes, including genes for urea utilization, suggesting an alternative source of ammonia. We were also able to determine which genotypes are most active in the plume. Transcripts involved in nitrification were more prominent in the plume and were among the most abundant transcripts in the community. These unique data sets reveal populations of deep-sea AOA thriving in the ammonium-rich GB that are related to surface types, but with key genomic and physiological differences.

Positive Enteric Contrast Material for Abdominal and Pelvic CT with Automatic Exposure Control: What Is the Effect On Patient Radiation Exposure?

PubMed Central

Wang, Zhen J.; Chen, Katherine S.; Gould, Robert; Coakley, Fergus V.; Fu, Yanjun; Yeh, Benjamin M.

2014-01-01

Objective To assess the effect of positive enteric contrast administration on automatic exposure control (AEC) CT radiation exposure in 1) a CT phantom, and 2) a retrospective review of patients. Materials and Methods We scanned a CT phantom containing simulated bowel that was sequentially filled with water and positive enteric contrast, and recorded the mean volume CT dose index (CTDIvol). We also identified 17 patients who had undergone 2 technically comparable CT scans of the abdomen and pelvis, one with positive enteric contrast and the other with oral water. Paired student t-tests were used to compare the mean CTDIvol between scans performed with and without positive enteric contrast. Both the phantom and patient CT scans were performed using AEC with a fixed noise index. Results The mean CTDIvol for the phantom with simulated bowel containing water and positive enteric contrast were 8.2 ± 0.2 mGy, and 8.7 ± 0.1 mGy (6.1% higher than water, p=0.02), respectively. The mean CTDIvol for patients scanned with oral water and with positive enteric contrast were 11.8mGy and 13.1mGy, respectively (p=0.003). This corresponded to a mean CTDIvol which was 11.0% higher (range: 0.0–20.7% higher) in scans with positive enteric contrast than those with oral water in patients. Conclusions When automatic exposure control is utilized for abdominopelvic CT, the radiation exposure, as measured by CTDIvol, is higher for scans performed with positive enteric contrast than those with oral water. PMID:21493028

Fast accretion of the earth with a late moon-forming giant impact.

PubMed

Yu, Gang; Jacobsen, Stein B

2011-10-25

Constraints on the formation history of the Earth are critical for understanding of planet formation processes. (182)Hf-(182)W chronometry of terrestrial rocks points to accretion of Earth in approximately 30 Myr after the formation of the solar system, immediately followed by the Moon-forming giant impact (MGI). Nevertheless, some N-body simulations and (182)Hf-(182)W and (87)Rb-(87)Sr chronology of some lunar rocks have been used to argue for a later formation of the Moon at 52 to > 100 Myr. This discrepancy is often explained by metal-silicate disequilibrium during giant impacts. Here we describe a model of the (182)W isotopic evolution of the accreting Earth, including constraints from partitioning of refractory siderophile elements (Ni, Co, W, V, and Nb) during core formation, which can explain the discrepancy. Our modeling shows that the concentrations of the siderophile elements of the mantle are consistent with high-pressure metal-silicate equilibration in a terrestrial magma ocean. Our analysis shows that the timing of the MGI is inversely correlated with the time scale of the main accretion stage of the Earth. Specifically, the earliest time the MGI could have taken place right at approximately 30 Myr, corresponds to the end of main-stage accretion at approximately 30 Myr. A late MGI (> 52 Myr) requires the main stage of the Earth's accretion to be completed rapidly in < 10.7 ± 2.5 Myr. These are the two end member solutions and a continuum of solutions exists in between these extremes.

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)

PubMed Central

Dülger, L. Canan; Kapucu, Sadettin

2016-01-01

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles. PMID:27610129

Prediction of Soil Deformation in Tunnelling Using Artificial Neural Networks.

PubMed

Lai, Jinxing; Qiu, Junling; Feng, Zhihua; Chen, Jianxun; Fan, Haobo

2016-01-01

In the past few decades, as a new tool for analysis of the tough geotechnical problems, artificial neural networks (ANNs) have been successfully applied to address a number of engineering problems, including deformation due to tunnelling in various types of rock mass. Unlike the classical regression methods in which a certain form for the approximation function must be presumed, ANNs do not require the complex constitutive models. Additionally, it is traced that the ANN prediction system is one of the most effective ways to predict the rock mass deformation. Furthermore, it could be envisaged that ANNs would be more feasible for the dynamic prediction of displacements in tunnelling in the future, especially if ANN models are combined with other research methods. In this paper, we summarized the state-of-the-art and future research challenges of ANNs on the tunnel deformation prediction. And the application cases as well as the improvement of ANN models were also presented. The presented ANN models can serve as a benchmark for effective prediction of the tunnel deformation with characters of nonlinearity, high parallelism, fault tolerance, learning, and generalization capability.

Prediction of Soil Deformation in Tunnelling Using Artificial Neural Networks

PubMed Central

Lai, Jinxing

2016-01-01

In the past few decades, as a new tool for analysis of the tough geotechnical problems, artificial neural networks (ANNs) have been successfully applied to address a number of engineering problems, including deformation due to tunnelling in various types of rock mass. Unlike the classical regression methods in which a certain form for the approximation function must be presumed, ANNs do not require the complex constitutive models. Additionally, it is traced that the ANN prediction system is one of the most effective ways to predict the rock mass deformation. Furthermore, it could be envisaged that ANNs would be more feasible for the dynamic prediction of displacements in tunnelling in the future, especially if ANN models are combined with other research methods. In this paper, we summarized the state-of-the-art and future research challenges of ANNs on the tunnel deformation prediction. And the application cases as well as the improvement of ANN models were also presented. The presented ANN models can serve as a benchmark for effective prediction of the tunnel deformation with characters of nonlinearity, high parallelism, fault tolerance, learning, and generalization capability. PMID:26819587

A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242).

PubMed

Almusawi, Ahmed R J; Dülger, L Canan; Kapucu, Sadettin

2016-01-01

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles.

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design.

PubMed

Huang, Ri-Bo; Du, Qi-Shi; Wei, Yu-Tuo; Pang, Zong-Wen; Wei, Hang; Chou, Kuo-Chen

2009-02-07

Predicting the bioactivity of peptides and proteins is an important challenge in drug development and protein engineering. In this study we introduce a novel approach, the so-called "physics and chemistry-driven artificial neural network (Phys-Chem ANN)", to deal with such a problem. Unlike the existing ANN approaches, which were designed under the inspiration of biological neural system, the Phys-Chem ANN approach is based on the physical and chemical principles, as well as the structural features of proteins. In the Phys-Chem ANN model the "hidden layers" are no longer virtual "neurons", but real structural units of proteins and peptides. It is a hybridization approach, which combines the linear free energy concept of quantitative structure-activity relationship (QSAR) with the advanced mathematical technique of ANN. The Phys-Chem ANN approach has adopted an iterative and feedback procedure, incorporating both machine-learning and artificial intelligence capabilities. In addition to making more accurate predictions for the bioactivities of proteins and peptides than is possible with the traditional QSAR approach, the Phys-Chem ANN approach can also provide more insights about the relationship between bioactivities and the structures involved than the ANN approach does. As an example of the application of the Phys-Chem ANN approach, a predictive model for the conformational stability of human lysozyme is presented.

Artificial neural networks: fundamentals, computing, design, and application.

PubMed

Basheer, I A; Hajmeer, M

2000-12-01

Artificial neural networks (ANNs) are relatively new computational tools that have found extensive utilization in solving many complex real-world problems. The attractiveness of ANNs comes from their remarkable information processing characteristics pertinent mainly to nonlinearity, high parallelism, fault and noise tolerance, and learning and generalization capabilities. This paper aims to familiarize the reader with ANN-based computing (neurocomputing) and to serve as a useful companion practical guide and toolkit for the ANNs modeler along the course of ANN project development. The history of the evolution of neurocomputing and its relation to the field of neurobiology is briefly discussed. ANNs are compared to both expert systems and statistical regression and their advantages and limitations are outlined. A bird's eye review of the various types of ANNs and the related learning rules is presented, with special emphasis on backpropagation (BP) ANNs theory and design. A generalized methodology for developing successful ANNs projects from conceptualization, to design, to implementation, is described. The most common problems that BPANNs developers face during training are summarized in conjunction with possible causes and remedies. Finally, as a practical application, BPANNs were used to model the microbial growth curves of S. flexneri. The developed model was reasonably accurate in simulating both training and test time-dependent growth curves as affected by temperature and pH.

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

PubMed

Bertleff, Marco; Domsch, Sebastian; Weingärtner, Sebastian; Zapp, Jascha; O'Brien, Kieran; Barth, Markus; Schad, Lothar R

2017-12-01

Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least-squares regression (LSR) and state-of-the-art multi-step fitting (LSR-MS) in Monte-Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR-MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo-diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR-MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR-MS, 19%; LSR, 8%), D* (ANN, 21%; LSR-MS, 25%; LSR, 23%) and K (ANN, 0%; LSR-MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR-MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state-of-the-art method LSR-MS with several advantages in the estimation of IVIM-kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times. Copyright © 2017 John Wiley & Sons, Ltd.

Differential expression of members of the annexin multigene family in Arabidopsis

NASA Technical Reports Server (NTRS)

Clark, G. B.; Sessions, A.; Eastburn, D. J.; Roux, S. J.

2001-01-01

Although in most plant species no more than two annexin genes have been reported to date, seven annexin homologs have been identified in Arabidopsis, Annexin Arabidopsis 1-7 (AnnAt1--AnnAt7). This establishes that annexins can be a diverse, multigene protein family in a single plant species. Here we compare and analyze these seven annexin gene sequences and present the in situ RNA localization patterns of two of these genes, AnnAt1 and AnnAt2, during different stages of Arabidopsis development. Sequence analysis of AnnAt1--AnnAt7 reveals that they contain the characteristic four structural repeats including the more highly conserved 17-amino acid endonexin fold region found in vertebrate annexins. Alignment comparisons show that there are differences within the repeat regions that may have functional importance. To assess the relative level of expression in various tissues, reverse transcription-PCR was carried out using gene-specific primers for each of the Arabidopsis annexin genes. In addition, northern blot analysis using gene-specific probes indicates differences in AnnAt1 and AnnAt2 expression levels in different tissues. AnnAt1 is expressed in all tissues examined and is most abundant in stems, whereas AnnAt2 is expressed mainly in root tissue and to a lesser extent in stems and flowers. In situ RNA localization demonstrates that these two annexin genes display developmentally regulated tissue-specific and cell-specific expression patterns. These patterns are both distinct and overlapping. The developmental expression patterns for both annexins provide further support for the hypothesis that annexins are involved in the Golgi-mediated secretion of polysaccharides.

Knowledge and intelligent computing system in medicine.

PubMed

Pandey, Babita; Mishra, R B

2009-03-01

Knowledge-based systems (KBS) and intelligent computing systems have been used in the medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) whereas intelligent computing method (ICM) encompasses genetic algorithm (GA), artificial neural network (ANN), fuzzy logic (FL) and others. The combination of methods in KBS such as CBR-RBR, CBR-MBR and RBR-CBR-MBR and the combination of methods in ICM is ANN-GA, fuzzy-ANN, fuzzy-GA and fuzzy-ANN-GA. The combination of methods from KBS to ICM is RBR-ANN, CBR-ANN, RBR-CBR-ANN, fuzzy-RBR, fuzzy-CBR and fuzzy-CBR-ANN. In this paper, we have made a study of different singular and combined methods (185 in number) applicable to medical domain from mid 1970s to 2008. The study is presented in tabular form, showing the methods and its salient features, processes and application areas in medical domain (diagnosis, treatment and planning). It is observed that most of the methods are used in medical diagnosis very few are used for planning and moderate number in treatment. The study and its presentation in this context would be helpful for novice researchers in the area of medical expert system.

A new evolutionary system for evolving artificial neural networks.

PubMed

Yao, X; Liu, Y

1997-01-01

This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

Application of principal component regression and artificial neural network in FT-NIR soluble solids content determination of intact pear fruit

NASA Astrophysics Data System (ADS)

Ying, Yibin; Liu, Yande; Fu, Xiaping; Lu, Huishan

2005-11-01

The artificial neural networks (ANNs) have been used successfully in applications such as pattern recognition, image processing, automation and control. However, majority of today's applications of ANNs is back-propagate feed-forward ANN (BP-ANN). In this paper, back-propagation artificial neural networks (BP-ANN) were applied for modeling soluble solid content (SSC) of intact pear from their Fourier transform near infrared (FT-NIR) spectra. One hundred and sixty-four pear samples were used to build the calibration models and evaluate the models predictive ability. The results are compared to the classical calibration approaches, i.e. principal component regression (PCR), partial least squares (PLS) and non-linear PLS (NPLS). The effects of the optimal methods of training parameters on the prediction model were also investigated. BP-ANN combine with principle component regression (PCR) resulted always better than the classical PCR, PLS and Weight-PLS methods, from the point of view of the predictive ability. Based on the results, it can be concluded that FT-NIR spectroscopy and BP-ANN models can be properly employed for rapid and nondestructive determination of fruit internal quality.

Verification and Validation of KBS with Neural Network Components

NASA Technical Reports Server (NTRS)

Wen, Wu; Callahan, John

1996-01-01

Artificial Neural Network (ANN) play an important role in developing robust Knowledge Based Systems (KBS). The ANN based components used in these systems learn to give appropriate predictions through training with correct input-output data patterns. Unlike traditional KBS that depends on a rule database and a production engine, the ANN based system mimics the decisions of an expert without specifically formulating the if-than type of rules. In fact, the ANNs demonstrate their superiority when such if-then type of rules are hard to generate by human expert. Verification of traditional knowledge based system is based on the proof of consistency and completeness of the rule knowledge base and correctness of the production engine.These techniques, however, can not be directly applied to ANN based components.In this position paper, we propose a verification and validation procedure for KBS with ANN based components. The essence of the procedure is to obtain an accurate system specification through incremental modification of the specifications using an ANN rule extraction algorithm.

Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?

PubMed

Dobchev, Dimitar; Karelson, Mati

2016-07-01

Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably, in the past two decades, ANNs have been used widely in the process of drug discovery. In this review, the authors discuss advantages and disadvantages of ANNs in drug discovery as incorporated into the quantitative structure-activity relationships (QSAR) framework. Furthermore, the authors examine the recent studies, which span over a broad area with various diseases in drug discovery. In addition, the authors attempt to answer the question about the expectations of the ANNs in drug discovery and discuss the trends in this field. The old pitfalls of overtraining and interpretability are still present with ANNs. However, despite these pitfalls, the authors believe that ANNs have likely met many of the expectations of researchers and are still considered as excellent tools for nonlinear data modeling in QSAR. It is likely that ANNs will continue to be used in drug development in the future.

Ann Richards Middle School.

ERIC Educational Resources Information Center

Kell, John H.

2001-01-01

Presents photos and basic information about a Texas middle school whose architecture reflects the hybrid culture of the borderlands and "regionalism" in which it is located. A line drawing of the site plan is included. (GR)

Reply to Ann Bradshaw.

PubMed

Allmark, Peter

1996-02-01

My original paper suggested that an ethics of care which failed to specify how, and about what, to care would be devoid of normative and descriptive content. Bradshaw's approach provides such a specification and is, therefore, not devoid of such content. However, as all ethical approaches suggest something about the 'what' and 'how' of care, they are all 'ethics of care' in this broader sense. This reinforces rather than undermines my original conclusion. Furthermore, Bradshaw's 'ethics of care' has philosophical and historical problems which I outline.

Anne K. Starace | NREL

Science.gov Websites

, Thermal Systems Group, 2010-2013 Featured Publications "Effects of Torrefaction Temperature on ;Biomass Catalytic Pyrolysis on Ni/ZSM-5: Effects of Nickel Pretreatment and Loading," Energy and inorganic dispersions be high-temperature heat-transfer and thermal energy storage fluids?" Journal of

Anne Elizabeth Ware | NREL

Science.gov Websites

Accumulation in Leaves of Sorghum bicolor (L.) Moench: A Source of Natural Food Pigment," J. Agricultural and Food Chemistry (2014) "Catalytic deoxygenation of triglycerides and fatty acids to

Reply to Ann Bradshaw.

PubMed Central

Allmark, Peter

1996-01-01

My original paper suggested that an ethics of care which failed to specify how, and about what, to care would be devoid of normative and descriptive content. Bradshaw's approach provides such a specification and is, therefore, not devoid of such content. However, as all ethical approaches suggest something about the 'what' and 'how' of care, they are all 'ethics of care' in this broader sense. This reinforces rather than undermines my original conclusion. Furthermore, Bradshaw's 'ethics of care' has philosophical and historical problems which I outline. PMID:11644877

Overview of artificial neural networks.

PubMed

Zou, Jinming; Han, Yi; So, Sung-Sau

2008-01-01

The artificial neural network (ANN), or simply neural network, is a machine learning method evolved from the idea of simulating the human brain. The data explosion in modem drug discovery research requires sophisticated analysis methods to uncover the hidden causal relationships between single or multiple responses and a large set of properties. The ANN is one of many versatile tools to meet the demand in drug discovery modeling. Compared to a traditional regression approach, the ANN is capable of modeling complex nonlinear relationships. The ANN also has excellent fault tolerance and is fast and highly scalable with parallel processing. This chapter introduces the background of ANN development and outlines the basic concepts crucially important for understanding more sophisticated ANN. Several commonly used learning methods and network setups are discussed briefly at the end of the chapter.

RADIATION DOSES AND CANCER RISKS IN THE MARSHALL ISLANDS ASSOCIATED WITH EXPOSURE TO RADIOACTIVE FALLOUT FROM BIKINI AND ENEWETAK NUCLEAR WEAPONS TESTS: SUMMARY

PubMed Central

Simon, Steven L.; Bouville, André; Land, Charles E.; Beck, Harold L.

2014-01-01

Nuclear weapons testing conducted at Bikini and Enewetak Atolls during 1946–1958 resulted in exposures of the resident population of the present-day Republic of the Marshall Islands to radioactive fallout. This paper summarizes the results of a thorough and systematic reconstruction of radiation doses to that population, by year, age at exposure, and atoll of residence, and the related cancer risks. Detailed methods and results are presented in a series of companion papers in this volume. From our analysis, we concluded that 20 of the 66 nuclear tests conducted in or near the Marshall Islands resulted in measurable fallout deposition on one or more of the inhabited atolls of the Marshall Islands. In this work, we estimated deposition densities (kBq m−2) of all important dose-contributing radionuclides at each of the 32 atolls and separate reef islands of the Marshall Islands. Quantitative deposition estimates were made for 63 radionuclides from each test at each atoll. Those estimates along with reported measurements of exposure rates at various times after fallout were used to estimate radiation absorbed doses to the red bone marrow, thyroid gland, stomach wall, and colon wall of atoll residents from both external and internal exposure. Annual doses were estimated for six age groups ranging from newborns to adults. We found that the total deposition of 137Cs, external dose, internal organ doses, and cancer risks followed the same geographic pattern with the large population of the southern atolls receiving the lowest doses. Permanent residents of the southern atolls who were of adult age at the beginning of the testing period received external doses ranging from 5 to 12 mGy on average; the external doses to adults at the mid-latitude atolls ranged from 22 to 59 mGy on average, while the residents of the northern atolls received external doses in the hundreds to over 1,000 mGy. Internal doses varied significantly by age at exposure, location, and organ. Except

Radiation doses and cancer risks in the Marshall Islands associated with exposure to radioactive fallout from Bikini and Enewetak nuclear weapons tests: summary.

PubMed

Simon, Steven L; Bouville, André; Land, Charles E; Beck, Harold L

2010-08-01

Nuclear weapons testing conducted at Bikini and Enewetak Atolls during 1946-1958 resulted in exposures of the resident population of the present-day Republic of the Marshall Islands to radioactive fallout. This paper summarizes the results of a thorough and systematic reconstruction of radiation doses to that population, by year, age at exposure, and atoll of residence, and the related cancer risks. Detailed methods and results are presented in a series of companion papers in this volume. From our analysis, we concluded that 20 of the 66 nuclear tests conducted in or near the Marshall Islands resulted in measurable fallout deposition on one or more of the inhabited atolls of the Marshall Islands. In this work, we estimated deposition densities (kBq m(-2)) of all important dose-contributing radionuclides at each of the 32 atolls and separate reef islands of the Marshall Islands. Quantitative deposition estimates were made for 63 radionuclides from each test at each atoll. Those estimates along with reported measurements of exposure rates at various times after fallout were used to estimate radiation absorbed doses to the red bone marrow, thyroid gland, stomach wall, and colon wall of atoll residents from both external and internal exposure. Annual doses were estimated for six age groups ranging from newborns to adults. We found that the total deposition of 137Cs, external dose, internal organ doses, and cancer risks followed the same geographic pattern with the large population of the southern atolls receiving the lowest doses. Permanent residents of the southern atolls who were of adult age at the beginning of the testing period received external doses ranging from 5 to 12 mGy on average; the external doses to adults at the mid-latitude atolls ranged from 22 to 59 mGy on average, while the residents of the northern atolls received external doses in the hundreds to over 1,000 mGy. Internal doses varied significantly by age at exposure, location, and organ. Except

[Algorithms of artificial neural networks--practical application in medical science].

PubMed

Stefaniak, Bogusław; Cholewiński, Witold; Tarkowska, Anna

2005-12-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer applications of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. This paper presents practical aspects of scientific application of ANN in medicine using widely available algorithms. Several main steps of analysis with ANN were discussed starting from material selection and dividing it into groups, to the quality assessment of obtained results at the end. The most frequent, typical reasons for errors as well as the comparison of ANN method to the modeling by regression analysis were also described.

Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool

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

Brady, S. L., E-mail: samuel.brady@stjude.org; Kaufman, R. A., E-mail: robert.kaufman@stjude.org

Purpose: To develop an automated methodology to estimate patient examination dose in digital radiography (DR) imaging using DICOM metadata as a quality assurance (QA) tool. Methods: Patient examination and demographical information were gathered from metadata analysis of DICOM header data. The x-ray system radiation output (i.e., air KERMA) was characterized for all filter combinations used for patient examinations. Average patient thicknesses were measured for head, chest, abdomen, knees, and hands using volumetric images from CT. Backscatter factors (BSFs) were calculated from examination kVp. Patient entrance skin air KERMA (ESAK) was calculated by (1) looking up examination technique factors taken frommore » DICOM header metadata (i.e., kVp and mA s) to derive an air KERMA (k{sub air}) value based on an x-ray characteristic radiation output curve; (2) scaling k{sub air} with a BSF value; and (3) correcting k{sub air} for patient thickness. Finally, patient entrance skin dose (ESD) was calculated by multiplying a mass–energy attenuation coefficient ratio by ESAK. Patient ESD calculations were computed for common DR examinations at our institution: dual view chest, anteroposterior (AP) abdomen, lateral (LAT) skull, dual view knee, and bone age (left hand only) examinations. Results: ESD was calculated for a total of 3794 patients; mean age was 11 ± 8 yr (range: 2 months to 55 yr). The mean ESD range was 0.19–0.42 mGy for dual view chest, 0.28–1.2 mGy for AP abdomen, 0.18–0.65 mGy for LAT view skull, 0.15–0.63 mGy for dual view knee, and 0.10–0.12 mGy for bone age (left hand) examinations. Conclusions: A methodology combining DICOM header metadata and basic x-ray tube characterization curves was demonstrated. In a regulatory era where patient dose reporting has become increasingly in demand, this methodology will allow a knowledgeable user the means to establish an automatable dose reporting program for DR and perform patient dose related QA testing

A methodology for on‐board CBCT imaging dose using optically stimulated luminescence detectors

PubMed Central

Yusuf, Muhammad; Alothmany, Nazeeh; Kinsara, A. Abdulrahman; Abdulkhaliq, Fahad; Ghamdi, Suliman M.; Saoudi, Abdelhamid

2016-01-01

Cone‐beam computed tomography CBCT systems are used in radiation therapy for patient alignment and positioning. The CBCT imaging procedure for patient setup adds substantial radiation dose to patient's normal tissue. This study presents a complete procedure for the CBCT dosimetry using the InLight optically‐stimulated‐luminescence (OSL) nanoDots. We report five dose parameters: the mean slice dose (DMSD); the cone beam dose index (CBDIW); the mean volume dose (DMVD); point‐dose profile, D(FOV); and the off‐field Dose. In addition, CBCT skin doses for seven pelvic tumor patients are reported. CBCT‐dose measurement was performed on a custom‐made cylindrical acrylic body phantom (50 cm length, 32 cm diameter). We machined 25 circular disks (2 cm thick) with grooves and holes to hold OSL‐nanoDots. OSLs that showed similar sensitivities were selected and calibrated against a Farmer‐type ionization‐chamber (0.6 CT) before being inserted into the grooves and holes. For the phantom scan, a standard CBCT‐imaging protocol (pelvic sites: 125 kVp, 80 mA and 25 ms) was used. Five dose parameters were quantified: DMSD, CBDIW, DMVD, D(FOV), and the off‐field dose. The DMSD for the central slice was 31.1±0.85 mGy, and CBDIW was 34.5±0.6 mGy at 16 cm FOV. The DMVD was 25.6±1.1 mGy. The off‐field dose was 10.5 mGy. For patients, the anterior and lateral skin doses attributable to CBCT imaging were 39.04±4.4 and 27.1±1.3 mGy, respectively. OSL nanoDots were convenient to use in measuring CBCT dose. The method of selecting the nanoDots greatly reduced uncertainty in the OSL measurements. Our detailed calibration procedure and CBCT dose measurements and calculations could prove useful in developing OSL routines for CBCT quality assessment, which in turn gives them the property of high spatial resolution, meaning that they have the potential for measurement of dose in regions of severe dose‐gradients. PACS number(s): 87.57.‐s, 87.57.Q, 87.57.uq PMID

Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

NASA Astrophysics Data System (ADS)

Correa, R.; Chesta, M. A.; Morales, J. R.; Dinator, M. I.; Requena, I.; Vila, I.

2006-08-01

An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses.

Prospective Measurement of Patient Exposure to Radiation During Pediatric Ureteroscopy

PubMed Central

Kokorowski, Paul J.; Chow, Jeanne S.; Strauss, Keith; Pennison, Melanie; Routh, Jonathan C.; Nelson, Caleb P.

2013-01-01

Objective Little data have been reported regarding radiation exposure during pediatric endourologic procedures, including ureteroscopy (URS). We sought to measure radiation exposure during pediatric URS and identify opportunities for exposure reduction. Methods We prospectively observed URS procedures as part of a quality improvement initiative. Pre-operative patient characteristics, operative factors, fluoroscopy settings and radiation exposure were recorded. Our outcomes were entrance skin dose (ESD, in mGy) and midline dose (MLD, in mGy). Specific modifiable factors were identified as targets for potential quality improvement. Results Direct observation was performed on 56 consecutive URS procedures. Mean patient age was 14.8 ± 3.8 years (range 7.4 to 19.2); 9 children were under age 12 years. Mean ESD was 46.4 ± 48 mGy. Mean MLD was 6.2 ± 5.0 mGy. The most important major determinant of radiation dose was total fluoroscopy time (mean 2.68 ± 1.8 min) followed by dose rate setting, child anterior-posterior (AP) diameter, and source to skin distance (all p<0.01). The analysis of factors affecting exposure levels found that the use of ureteral access sheaths (p=0.01) and retrograde pyelography (p=0.04) were significantly associated with fluoroscopy time. We also found that dose rate settings were higher than recommended in up to 43% of cases and ideal C-arm positioning could have reduced exposure 14% (up to 49% in some cases). Conclusions Children receive biologically significant radiation doses during URS procedures. Several modifiable factors contribute to dose and could be targeted in efforts to implement dose reduction strategies. PMID:22341275

Fast accretion of the Earth with a late Moon-forming giant impact

PubMed Central

Yu, Gang; Jacobsen, Stein B.

2011-01-01

Constraints on the formation history of the Earth are critical for understanding of planet formation processes. 182Hf-182W chronometry of terrestrial rocks points to accretion of Earth in approximately 30 Myr after the formation of the solar system, immediately followed by the Moon-forming giant impact (MGI). Nevertheless, some N-body simulations and 182Hf-182W and 87Rb-87Sr chronology of some lunar rocks have been used to argue for a later formation of the Moon at 52 to > 100 Myr. This discrepancy is often explained by metal-silicate disequilibrium during giant impacts. Here we describe a model of the 182W isotopic evolution of the accreting Earth, including constraints from partitioning of refractory siderophile elements (Ni, Co, W, V, and Nb) during core formation, which can explain the discrepancy. Our modeling shows that the concentrations of the siderophile elements of the mantle are consistent with high-pressure metal-silicate equilibration in a terrestrial magma ocean. Our analysis shows that the timing of the MGI is inversely correlated with the time scale of the main accretion stage of the Earth. Specifically, the earliest time the MGI could have taken place right at approximately 30 Myr, corresponds to the end of main-stage accretion at approximately 30 Myr. A late MGI (> 52 Myr) requires the main stage of the Earth’s accretion to be completed rapidly in < 10.7 ± 2.5 Myr. These are the two end member solutions and a continuum of solutions exists in between these extremes. PMID:22006299

Effectiveness of Fluorography versus Cineangiography at Reducing Radiation Exposure During Diagnostic Coronary Angiography

PubMed Central

Shah, Binita; Mai, Xingchen; Tummala, Lakshmi; Kliger, Chad; Bangalore, Sripal; Miller, Louis H.; Sedlis, Steven P.; Feit, Frederick; Liou, Michael; Attubato, Michael; Coppola, John; Slater, James

2014-01-01

Coronary angiography is the gold standard for defining obstructive coronary disease. However, radiation exposure remains an unwanted hazard. Patients referred for coronary angiography with abdominal circumference <45 inches and glomerular filtration rate >60mL/min were randomized to the Fluorography (n=25) or Cineangiography (n=25) group. Patients in the Fluorography group underwent coronary angiography using retrospectively-stored fluorography with repeat injection under cineangiography only when needed for better resolution per operator’s discretion. Patients in the Cineangiography group underwent coronary angiography using routine cineangiography. The primary endpoint was patient radiation exposure measured by radiochromic film. Secondary endpoints included the radiation output measurement of kerma-area product (KAP) and air kerma at the interventional reference point (Ka,r), and operator radiation exposure measured by dosimeter. Patient radiation exposure (158.2mGy [76.5–210.2] vs 272.5mGy [163.3–314.0], p=0.001), KAP (1323μGy m2 [826–1765] vs 3451μGy m2 [2464–4818], p<0.001), and Ka,r (175 mGy [112–252] vs 558 mGy [313–621], p<0.001)was significantly lower in the Fluorography compared with Cineangiography group (42%, 62%, and 69% relative reduction, respectively). Operator radiation exposure trended in the same direction though statistically non-significant (Fluorography 2.35 μGy [1.24–6.30] vs Cineangiography 5.03μGy [2.48–7.80], p=0.059). In conclusion, the use of fluorography in a select group of patients during coronary angiography with repeat injection under cineangiography only when needed was efficacious at reducing patient radiation exposure. PMID:24513469

Morphological and histological studies on freshwater prawn Macrobrachium rosenbergii (de man) irradiated with (60)Co gamma radiation.

PubMed

Stalin, A; Broos, K V; Sadiq Bukhari, A; Syed Mohamed, H E; Singhal, R K; Venu-Babu, P

2013-11-15

This study was framed to investigate the (60)Co gamma radiation induced morphological and histological variations in freshwater prawn Macrobrachium rosenbergii. The LD50 value of (60)Co gamma irradiated M. rosenbergii observed (by probit analysis) at 30 Gy. Prawns were irradiated to four different dose levels (3 mGy, 30 mGy, 300 mGy and 3,000 mGy) using Theratron Phoenix TeleCobalt Unit [P-33] and one control group (without irradiation) maintained separately. Irradiated groups exhibited several morphological variations such as discoloration; damaged rostrum; opaque coloration in cephalothorax; black bands and dot formation in abdomen; deformed uropods and telson in tail regions when compared with control group. The Hepato Somatic Index reflected the severity of radiation on hepatopancreas. Histological variations in gills, hepatopancreas and muscles of irradiated groups were observed. In gills, structural changes such as swollen and fused lamellae, abnormal gill tips, hyperplasic, necrotic and clavate-globate lamellae were observed in gamma irradiated prawns. Accumulation of hemocytes in hemocoelic space, interstitial sinuses filled with abnormal infiltrated hemocytes, the tubular epithelium with ruptured basal laminae, abnormal and coagulated lumen, necrotic tubules, thickened basal laminae, tissue debris, necrotic hepatocytes were observed in irradiated prawn hepatopancreas. In muscle, shrinkage of muscular fiber and necrotic musculature were observed in irradiated prawns. These structural alterations of the organs it is felt could affect the vital physiological functions such as respiration, osmotic and ionic regulation in gills and muscles; absorption, storage and secretion of the hepatopancreas which in turn could adversely affect the growth and survival of freshwater prawn M. rosenbergii. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessment of the effects of a stannous fluoride dentifrice on gingivitis in a two-month positive-controlled clinical study.

PubMed

He, Tao; Barker, Matthew L; Biesbock, A R; Sharma, N C; Qaqish, J; Goyal, C R

2012-01-01

The purpose of this study was to evaluate the anti-gingivitis effectiveness of a 0.454% stannous fluoride test dentifrice relative to a marketed positive-control triclosan-containing dentifrice in adults with gingivitis. This was a two-month, randomized and controlled, double-blind, parallel group, single-center investigation involving 150 adults with existing mild to moderate gingivitis. Pre-treatment gingivitis levels were assessed at baseline using the Lobene Modified Gingival Index (MGI) and the Gingival Bleeding Index (GBI). Qualified subjects were randomly assigned to either a 0.454% stannous fluoride test dentifrice or a marketed, positive-control 0.30% triclosan/copolymer dentifrice. Subjects then brushed for two months unsupervised in the home setting with their assigned dentifrice per manufacturer's instructions. At Month 2, subjects were re-evaluated for gingivitis via MGI and GBI examinations. All 150 enrolled subjects completed the trial and were evaluable. Both the stannous fluoride test and triclosan/copolymer control dentifrices provided statistically significant reductions in average MGI, GBI, and number of bleeding sites relative to pre-treatment (p < 0.0001) at Month 2. The adjusted mean improvement from baseline at Month 2 for the stannous fluoride test dentifrice group was 65% greater for number of bleeding sites, 62% greater for GBI, and 45% greater for MGI compared to the triclosan/copolymer positive-control group, with groups differing significantly (p < 0.0001) via each of the three gingivitis measures. Both dentifrices were well-tolerated. An advanced stannous fluoride test dentifrice provided superior reductions in gingival inflammation and gingival bleeding compared to a commercially available triclosan/copolymer positive-control dentifrice after two months of tooth brushing.

Perfusion CT of the Brain and Liver and of Lung Tumors: Use of Monte Carlo Simulation for Patient Dose Estimation for Examinations With a Cone-Beam 320-MDCT Scanner.

PubMed

Cros, Maria; Geleijns, Jacob; Joemai, Raoul M S; Salvadó, Marçal

2016-01-01

The purpose of this study was to estimate the patient dose from perfusion CT examinations of the brain, lung tumors, and the liver on a cone-beam 320-MDCT scanner using a Monte Carlo simulation and the recommendations of the International Commission on Radiological Protection (ICRP). A Monte Carlo simulation based on the Electron Gamma Shower Version 4 package code was used to calculate organ doses and the effective dose in the reference computational phantoms for an adult man and adult woman as published by the ICRP. Three perfusion CT acquisition protocols--brain, lung tumor, and liver perfusion--were evaluated. Additionally, dose assessments were performed for the skin and for the eye lens. Conversion factors were obtained to estimate effective doses and organ doses from the volume CT dose index and dose-length product. The sex-averaged effective doses were approximately 4 mSv for perfusion CT of the brain and were between 23 and 26 mSv for the perfusion CT body protocols. The eye lens dose from the brain perfusion CT examination was approximately 153 mGy. The sex-averaged peak entrance skin dose (ESD) was 255 mGy for the brain perfusion CT studies, 157 mGy for the lung tumor perfusion CT studies, and 172 mGy for the liver perfusion CT studies. The perfusion CT protocols for imaging the brain, lung tumors, and the liver performed on a 320-MDCT scanner yielded patient doses that are safely below the threshold doses for deterministic effects. The eye lens dose, peak ESD, and effective doses can be estimated for other clinical perfusion CT examinations from the conversion factors that were derived in this study.

Triphasic low-dose response in zebrafish embryos irradiated by microbeam protons.

PubMed

Choi, Viann Wing Yan; Yum, Emily Hoi Wa; Konishi, Teruaki; Oikawa, Masakazu; Cheng, Shuk Han; Yu, Kwan Ngok

2012-01-01

The microbeam irradiation system (Single-Particle Irradiation System to Cell, acronym as SPICE) at the National Institute of Radiological Sciences (NIRS), Japan, was employed to irradiate dechorionated zebrafish embryos at the 2-cell stage at 0.75 h post fertilization (hpf) by microbeam protons. Either one or both of the cells of the embryos were irradiated with 10, 20, 40, 50, 80, 100, 160, 200, 300 and 2000 protons each with an energy of 3.37 MeV. The embryos were then returned back to the incubator until 24 hpf for analyses. The levels of apoptosis in zebrafish embryos at 25 hpf were quantified through terminal dUTP transferase-mediated nick end-labeling (TUNEL) assay, with the apoptotic signals captured by a confocal microscope. The results revealed a triphasic dose-response for zebrafish embryos with both cells irradiated at the 2-cell stage, namely, (1) increase in apoptotic signals for < 200 protons (< 30 mGy), (2) hormesis to reduce the apoptotic signals below the spontaneous number for 200-400 protons (at doses of 30-60 mGy), and (3) increase in apoptotic signals again for > 600 protons (at doses > 90 mGy). The dose response for zebrafish embryos with only one cell irradiated at the 2-cell stage was also likely a triphasic one, but the apoptotic signals in the first zone (< 200 protons or < 30 mGy) did not have significant differences from those of the background. At the same time, the experimental data were in line with induction of radiation-induced bystander effect as well as rescue effect in the zebrafish embryos, particular in those embryos with unirradiated cells.

Effect of gamma-ray irradiation on structural properties of GaAsN films grown by metal organic vapor phase epitaxy

NASA Astrophysics Data System (ADS)

Klangtakai, Pawinee; Sanorpim, Sakuntam; Wattanawareekul, Atiwat; Suwanyangyaun, Pattana; Srepusharawoot, Pornjuk; Onabe, Kentaro

2015-05-01

The effects of gamma-ray irradiation on the structural properties of GaAs1-xNx films (N concentration=1.9 and 5.1 at%) grown by metal organic vapor phase epitaxy on GaAs (001) substrates were investigated. The GaAs1-xNx films were irradiated by gamma rays with irradiation strength of 0-2.0 MGy. Scanning electron microscopy and atomic force microscopy results showed that a gamma ray with a strength of 0, 0.5, 1.0, 1.5, and 2.0 MGy formed holes with a density of 0.0, 8.8, 9.4, 11.5, and 11.9 μm-2, respectively, on the surface of a GaAs0.981N0.019 film with low N content. On the other hand, the irradiated high-N-content GaAs0.949N0.051 film exhibited a cross-hatch pattern, which was induced by partial strain relaxation at high N levels, with a line density of 0.0, 0.21, 0.37, 0.67, and 0.26 μm-1 corresponding to an irradiation strength of 0, 0.5, 1.0, 1.5, and 2.0 MGy, respectively. The high-resolution X-ray diffraction and Raman scattering results revealed an increase in N incorporation and strain relaxation after irradiation. In addition, the GaAs0.949N0.051 films exhibited phase separation, which took place via N out-diffusion across the interface when the irradiation strength exceeded 1.0 MGy. Based on these results, the main cause of structural change was determined to be the irradiation effects including displacement damage and gamma-ray heating.

Ibrutinib, Rituximab, Etoposide, Prednisone, Vincristine Sulfate, Cyclophosphamide, and Doxorubicin Hydrochloride in Treating Patients With HIV-Positive Stage II-IV Diffuse Large B-Cell Lymphomas

ClinicalTrials.gov

2018-06-11

AIDS-Related Lymphoma; Ann Arbor Stage II Diffuse Large B-Cell Lymphoma; Ann Arbor Stage III Diffuse Large B-Cell Lymphoma; Ann Arbor Stage IV Diffuse Large B-Cell Lymphoma; CD20 Negative; CD20 Positive; Human Immunodeficiency Virus Positive