A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer.

PubMed

Khan, Adil Mehmood; Lee, Young-Koo; Lee, Sungyoung Y; Kim, Tae-Seong

2010-09-01

Physical-activity recognition via wearable sensors can provide valuable information regarding an individual's degree of functional ability and lifestyle. In this paper, we present an accelerometer sensor-based approach for human-activity recognition. Our proposed recognition method uses a hierarchical scheme. At the lower level, the state to which an activity belongs, i.e., static, transition, or dynamic, is recognized by means of statistical signal features and artificial-neural nets (ANNs). The upper level recognition uses the autoregressive (AR) modeling of the acceleration signals, thus, incorporating the derived AR-coefficients along with the signal-magnitude area and tilt angle to form an augmented-feature vector. The resulting feature vector is further processed by the linear-discriminant analysis and ANNs to recognize a particular human activity. Our proposed activity-recognition method recognizes three states and 15 activities with an average accuracy of 97.9% using only a single triaxial accelerometer attached to the subject's chest.

Kumaraswamy autoregressive moving average models for double bounded environmental data

NASA Astrophysics Data System (ADS)

Bayer, Fábio Mariano; Bayer, Débora Missio; Pumi, Guilherme

2017-12-01

In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval (a,b) following the Kumaraswamy distribution. The Kumaraswamy family of distribution is widely applied in many areas, especially hydrology and related fields. Classical examples are time series representing rates and proportions observed over time. In the proposed KARMA model, the median is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and a link function. We introduce the new class of models and discuss conditional maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting. In particular, we provide closed-form expressions for the conditional score vector and conditional Fisher information matrix. An application to environmental real data is presented and discussed.

Correction of murine hemophilia A following nonmyeloablative transplantation of hematopoietic stem cells engineered to encode an enhanced human factor VIII variant using a safety-augmented retroviral vector

PubMed Central

Ramezani, Ali

2009-01-01

Insertional mutagenesis by retroviral vectors is a major impediment to the clinical application of hematopoietic stem cell gene transfer for the treatment of hematologic disorders. We recently developed an insulated self-inactivating gammaretroviral vector, RMSinOFB, which uses a novel enhancer-blocking element that significantly decreases genotoxicity of retroviral integration. In this study, we used the RMSinOFB vector to evaluate the efficacy of a newly bioengineered factor VIII (fVIII) variant (efVIII)—containing a combination of A1 domain point mutations (L303E/F309S) and an extended partial B domain for improved secretion plus A2 domain mutations (R484A/R489A/P492A) for reduced immunogenicity—toward successful treatment of murine hemophilia A. In cell lines, efVIII was secreted at up to 6-fold higher levels than an L303E/F309S A1 domain–only fVIII variant (sfVIIIΔB). Most important, when compared with a conventional gammaretroviral vector expressing sfVIIIΔB, lower doses of RMSin-efVIII-OFB–transduced hematopoietic stem cells were needed to generate comparable curative fVIII levels in hemophilia A BALB/c mice after reduced-intensity total body irradiation or nonmyeloablative chemotherapy conditioning regimens. These data suggest that the safety-augmented RMSin-efVIII-OFB platform represents an encouraging step in the development of a clinically appropriate gene addition therapy for hemophilia A. PMID:19470695

Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

PubMed

Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

2016-07-01

Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

The impact of media campaigns on smoking cessation activity: a structural vector autoregression analysis.

PubMed

Langley, Tessa E; McNeill, Ann; Lewis, Sarah; Szatkowski, Lisa; Quinn, Casey

2012-11-01

To evaluate the effect of tobacco control media campaigns and pharmaceutical company-funded advertising for nicotine replacement therapy (NRT) on smoking cessation activity. Multiple time series analysis using structural vector autoregression, January 2002-May 2010. England and Wales. Tobacco control campaign data from the Central Office of Information; commercial NRT campaign data; data on calls to the National Health Service (NHS) stop smoking helpline from the Department of Health; point-of-sale data on over-the-counter (OTC) sales of NRT; and prescribing data from The Health Improvement Network (THIN), a database of UK primary care records. Monthly calls to the NHS stop smoking helpline and monthly rates of OTC sales and prescribing of NRT. A 1% increase in tobacco control television ratings (TVRs), a standard measure of advertising exposure, was associated with a statistically significant 0.085% increase in calls in the same month (P = 0.007), and no statistically significant effect in subsequent months. Tobacco control TVRs were not associated with OTC NRT sales or prescribed NRT. NRT advertising TVRs had a significant effect on NRT sales which became non-significant in the seasonally adjusted model, and no significant effect on prescribing or calls. Tobacco control campaigns appear to be more effective at triggering quitting behaviour than pharmaceutical company NRT campaigns. Any effect of such campaigns on quitting behaviour seems to be restricted to the month of the campaign, suggesting that such campaigns need to be sustained over time. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

A Stimulus-Locked Vector Autoregressive Model for Slow Event-Related fMRI Designs

PubMed Central

Siegle, Greg

2009-01-01

Summary Neuroscientists have become increasingly interested in exploring dynamic relationships among brain regions. Such a relationship, when directed from one region toward another, is denoted by “effective connectivity.” An fMRI experimental paradigm which is well-suited for examination of effective connectivity is the slow event-related design. This design presents stimuli at sufficient temporal spacing for determining within-trial trajectories of BOLD activation, allowing for the analysis of stimulus-locked temporal covariation of brain responses in multiple regions. This may be especially important for emotional stimuli processing, which can evolve over the course of several seconds, if not longer. However, while several methods have been devised for determining fMRI effective connectivity, few are adapted to event-related designs, which include non-stationary BOLD responses and multiple levels of nesting. We propose a model tailored for exploring effective connectivity of multiple brain regions in event-related fMRI designs - a semi-parametric adaptation of vector autoregressive (VAR) models, termed “stimulus-locked VAR” (SloVAR). Connectivity coefficients vary as a function of time relative to stimulus onset, are regularized via basis expansions, and vary randomly across subjects. SloVAR obtains flexible, data-driven estimates of effective connectivity and hence is useful for building connectivity models when prior information on dynamic regional relationships is sparse. Indices derived from the coefficient estimates can also be used to relate effective connectivity estimates to behavioral or clinical measures. We demonstrate the SloVAR model on a sample of clinically depressed and normal controls, showing that early but not late cortico-amygdala connectivity appears crucial to emotional control and early but not late cortico-cortico connectivity predicts depression severity in the depressed group, relationships that would have been missed in a more

Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

NASA Astrophysics Data System (ADS)

Lohani, A. K.; Kumar, Rakesh; Singh, R. D.

2012-06-01

SummaryTime series modeling is necessary for the planning and management of reservoirs. More recently, the soft computing techniques have been used in hydrological modeling and forecasting. In this study, the potential of artificial neural networks and neuro-fuzzy system in monthly reservoir inflow forecasting are examined by developing and comparing monthly reservoir inflow prediction models, based on autoregressive (AR), artificial neural networks (ANNs) and adaptive neural-based fuzzy inference system (ANFIS). To take care the effect of monthly periodicity in the flow data, cyclic terms are also included in the ANN and ANFIS models. Working with time series flow data of the Sutlej River at Bhakra Dam, India, several ANN and adaptive neuro-fuzzy models are trained with different input vectors. To evaluate the performance of the selected ANN and adaptive neural fuzzy inference system (ANFIS) models, comparison is made with the autoregressive (AR) models. The ANFIS model trained with the input data vector including previous inflows and cyclic terms of monthly periodicity has shown a significant improvement in the forecast accuracy in comparison with the ANFIS models trained with the input vectors considering only previous inflows. In all cases ANFIS gives more accurate forecast than the AR and ANN models. The proposed ANFIS model coupled with the cyclic terms is shown to provide better representation of the monthly inflow forecasting for planning and operation of reservoir.

Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting

PubMed Central

Aydin, Alev Dilek; Caliskan Cavdar, Seyma

2015-01-01

The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR) method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method. PMID:26550010

Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

PubMed

Aydin, Alev Dilek; Caliskan Cavdar, Seyma

2015-01-01

The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR) method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method.

Detection of tripping gait patterns in the elderly using autoregressive features and support vector machines.

PubMed

Lai, Daniel T H; Begg, Rezaul K; Taylor, Simon; Palaniswami, Marimuthu

2008-01-01

Elderly tripping falls cost billions annually in medical funds and result in high mortality rates often perpetrated by pulmonary embolism (internal bleeding) and infected fractures that do not heal well. In this paper, we propose an intelligent gait detection system (AR-SVM) for screening elderly individuals at risk of suffering tripping falls. The motivation of this system is to provide early detection of elderly gait reminiscent of tripping characteristics so that preventive measures could be administered. Our system is composed of two stages, a predictor model estimated by an autoregressive (AR) process and a support vector machine (SVM) classifier. The system input is a digital signal constructed from consecutive measurements of minimum toe clearance (MTC) representative of steady-state walking. The AR-SVM system was tested on 23 individuals (13 healthy and 10 having suffered at least one tripping fall in the past year) who each completed a minimum of 10 min of walking on a treadmill at a self-selected pace. In the first stage, a fourth order AR model required at least 64 MTC values to correctly detect all fallers and non-fallers. Detection was further improved to less than 1 min of walking when the model coefficients were used as input features to the SVM classifier. The system achieved a detection accuracy of 95.65% with the leave one out method using only 16 MTC samples, but was reduced to 69.57% when eight MTC samples were used. These results demonstrate a fast and efficient system requiring a small number of strides and only MTC measurements for accurate detection of tripping gait characteristics.

Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality

NASA Astrophysics Data System (ADS)

Cherukuru, Nihanth Wagmi

Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars. Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona's Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as

Kepler AutoRegressive Planet Search

NASA Astrophysics Data System (ADS)

Caceres, Gabriel Antonio; Feigelson, Eric

2016-01-01

The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; AR-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. The analysis procedures of the project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. Our findings to date on real

Motivational factors and psychological processes in cosmetic breast augmentation surgery.

PubMed

Solvi, Anette S; Foss, Kaja; von Soest, Tilmann; Roald, Helge E; Skolleborg, Knut C; Holte, Arne

2010-04-01

We investigated how and why prospective cosmetic breast augmentation patients decide to undergo such surgery. The results can offer important insights to plastic surgeons in addressing their patients' motives and expectations, and thereby avoiding potential patient dissatisfaction and disappointment. It is also a necessary first step to better understand the increasing tendency among women in the Western society to seek cosmetic breast augmentation. A qualitative, descriptive and phenomenological design was employed. Fourteen female prospective breast augmentation patients, aged 19-46 years, were recruited from a private plastic surgery clinic and interviewed in depth based on an informant-centred format. The interviews were tape-recorded, transcribed verbatim and coded and analysed phenomenologically using a QSR-N*Vivo software program. We detected four psychological processes associated with cosmetic breast augmentation surgery (create, improve, repair and restore). The data could further be categorised into one basic drive (femininity), six generating factors (appearance dissatisfaction, ideal figure, self-esteem, comments, clothes and sexuality) and five eliciting factors motivating the decision (media, knowledge of former patients, physicians, finances and romantic partner). These new insights into how and why women seek cosmetic breast augmentation may aid plastic surgeons in enhancing their communication with patients. This can be achieved by addressing the patient's psychological process and motives, and thereby better assist them in making the best decision possible in their particular situation. It may also lay the groundwork for future quantitative studies on the prevalence of certain motives for undergoing such surgery and, as such, help explain the increasing popularity of cosmetic breast-augmentation surgery. Copyright 2009 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

NASA Astrophysics Data System (ADS)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

A novel rotational matrix and translation vector algorithm: geometric accuracy for augmented reality in oral and maxillofacial surgeries.

PubMed

Murugesan, Yahini Prabha; Alsadoon, Abeer; Manoranjan, Paul; Prasad, P W C

2018-06-01

Augmented reality-based surgeries have not been successfully implemented in oral and maxillofacial areas due to limitations in geometric accuracy and image registration. This paper aims to improve the accuracy and depth perception of the augmented video. The proposed system consists of a rotational matrix and translation vector algorithm to reduce the geometric error and improve the depth perception by including 2 stereo cameras and a translucent mirror in the operating room. The results on the mandible/maxilla area show that the new algorithm improves the video accuracy by 0.30-0.40 mm (in terms of overlay error) and the processing rate to 10-13 frames/s compared to 7-10 frames/s in existing systems. The depth perception increased by 90-100 mm. The proposed system concentrates on reducing the geometric error. Thus, this study provides an acceptable range of accuracy with a shorter operating time, which provides surgeons with a smooth surgical flow. Copyright © 2018 John Wiley & Sons, Ltd.

Incorporating measurement error in n = 1 psychological autoregressive modeling

PubMed Central

Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988

Incorporating measurement error in n = 1 psychological autoregressive modeling.

PubMed

Schuurman, Noémi K; Houtveen, Jan H; Hamaker, Ellen L

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30-50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters.

Characteristics of the transmission of autoregressive sub-patterns in financial time series

NASA Astrophysics Data System (ADS)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

2014-09-01

There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors.

Characteristics of the transmission of autoregressive sub-patterns in financial time series

PubMed Central

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

2014-01-01

There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors. PMID:25189200

Functional MRI and Multivariate Autoregressive Models

PubMed Central

Rogers, Baxter P.; Katwal, Santosh B.; Morgan, Victoria L.; Asplund, Christopher L.; Gore, John C.

2010-01-01

Connectivity refers to the relationships that exist between different regions of the brain. In the context of functional magnetic resonance imaging (fMRI), it implies a quantifiable relationship between hemodynamic signals from different regions. One aspect of this relationship is the existence of small timing differences in the signals in different regions. Delays of 100 ms or less may be measured with fMRI, and these may reflect important aspects of the manner in which brain circuits respond as well as the overall functional organization of the brain. The multivariate autoregressive time series model has features to recommend it for measuring these delays, and is straightforward to apply to hemodynamic data. In this review, we describe the current usage of the multivariate autoregressive model for fMRI, discuss the issues that arise when it is applied to hemodynamic time series, and consider several extensions. Connectivity measures like Granger causality that are based on the autoregressive model do not always reflect true neuronal connectivity; however, we conclude that careful experimental design could make this methodology quite useful in extending the information obtainable using fMRI. PMID:20444566

Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators

PubMed Central

Alwee, Razana; Hj Shamsuddin, Siti Mariyam; Sallehuddin, Roselina

2013-01-01

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models. PMID:23766729

Hybrid support vector regression and autoregressive integrated moving average models improved by particle swarm optimization for property crime rates forecasting with economic indicators.

PubMed

Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Sallehuddin, Roselina

2013-01-01

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

Iso-vector form factors of the delta and nucleon in QCD sum rules

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

Ozpineci, A.

Form factors are important non-perturbative properties of hadrons. They give information about the internal structure of the hadrons. In this work, iso-vector axial-vector and iso-vector tensor form factors of the nucleon and the iso-vector axial-vector {Delta}{yields}N transition form factor calculations in QCD Sum Rules are presented.

Gaussian Process Autoregression for Simultaneous Proportional Multi-Modal Prosthetic Control With Natural Hand Kinematics.

PubMed

Xiloyannis, Michele; Gavriel, Constantinos; Thomik, Andreas A C; Faisal, A Aldo

2017-10-01

Matching the dexterity, versatility, and robustness of the human hand is still an unachieved goal in bionics, robotics, and neural engineering. A major limitation for hand prosthetics lies in the challenges of reliably decoding user intention from muscle signals when controlling complex robotic hands. Most of the commercially available prosthetic hands use muscle-related signals to decode a finite number of predefined motions and some offer proportional control of open/close movements of the whole hand. Here, in contrast, we aim to offer users flexible control of individual joints of their artificial hand. We propose a novel framework for decoding neural information that enables a user to independently control 11 joints of the hand in a continuous manner-much like we control our natural hands. Toward this end, we instructed six able-bodied subjects to perform everyday object manipulation tasks combining both dynamic, free movements (e.g., grasping) and isometric force tasks (e.g., squeezing). We recorded the electromyographic and mechanomyographic activities of five extrinsic muscles of the hand in the forearm, while simultaneously monitoring 11 joints of hand and fingers using a sensorized data glove that tracked the joints of the hand. Instead of learning just a direct mapping from current muscle activity to intended hand movement, we formulated a novel autoregressive approach that combines the context of previous hand movements with instantaneous muscle activity to predict future hand movements. Specifically, we evaluated a linear vector autoregressive moving average model with exogenous inputs and a novel Gaussian process ( ) autoregressive framework to learn the continuous mapping from hand joint dynamics and muscle activity to decode intended hand movement. Our approach achieves high levels of performance (RMSE of 8°/s and ). Crucially, we use a small set of sensors that allows us to control a larger set of independently actuated degrees of freedom of a hand

Kepler AutoRegressive Planet Search: Motivation & Methodology

NASA Astrophysics Data System (ADS)

Caceres, Gabriel; Feigelson, Eric; Jogesh Babu, G.; Bahamonde, Natalia; Bertin, Karine; Christen, Alejandra; Curé, Michel; Meza, Cristian

2015-08-01

The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Auto-Regressive Moving-Average (ARMA) models, Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH), and related models are flexible, phenomenological methods used with great success to model stochastic temporal behaviors in many fields of study, particularly econometrics. Powerful statistical methods are implemented in the public statistical software environment R and its many packages. Modeling involves maximum likelihood fitting, model selection, and residual analysis. These techniques provide a useful framework to model stellar variability and are used in KARPS with the objective of reducing stellar noise to enhance opportunities to find as-yet-undiscovered planets. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; ARMA-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. We apply the procedures to simulated Kepler-like time series with known stellar and planetary signals to evaluate the effectiveness of the KARPS procedures. The ARMA-type modeling is effective at reducing stellar noise, but also reduces and transforms the transit signal into ingress/egress spikes. A periodogram based on the TCF is constructed to concentrate the signal

Development and human factors analysis of neuronavigation vs. augmented reality.

PubMed

Pandya, Abhilash; Siadat, Mohammad-Reza; Auner, Greg; Kalash, Mohammad; Ellis, R Darin

2004-01-01

This paper is focused on the human factors analysis comparing a standard neuronavigation system with an augmented reality system. We use a passive articulated arm (Microscribe, Immersion technology) to track a calibrated end-effector mounted video camera. In real time, we superimpose the live video view with the synchronized graphical view of CT-derived segmented object(s) of interest within a phantom skull. Using the same robotic arm, we have developed a neuronavigation system able to show the end-effector of the arm on orthogonal CT scans. Both the AR and the neuronavigation systems have been shown to be within 3mm of accuracy. A human factors study was conducted in which subjects were asked to draw craniotomies and answer questions to gage their understanding of the phantom objects. The human factors study included 21 subjects and indicated that the subjects performed faster, with more accuracy and less errors using the Augmented Reality interface.

Searching for transcription factor binding sites in vector spaces

PubMed Central

2012-01-01

Background Computational approaches to transcription factor binding site identification have been actively researched in the past decade. Learning from known binding sites, new binding sites of a transcription factor in unannotated sequences can be identified. A number of search methods have been introduced over the years. However, one can rarely find one single method that performs the best on all the transcription factors. Instead, to identify the best method for a particular transcription factor, one usually has to compare a handful of methods. Hence, it is highly desirable for a method to perform automatic optimization for individual transcription factors. Results We proposed to search for transcription factor binding sites in vector spaces. This framework allows us to identify the best method for each individual transcription factor. We further introduced two novel methods, the negative-to-positive vector (NPV) and optimal discriminating vector (ODV) methods, to construct query vectors to search for binding sites in vector spaces. Extensive cross-validation experiments showed that the proposed methods significantly outperformed the ungapped likelihood under positional background method, a state-of-the-art method, and the widely-used position-specific scoring matrix method. We further demonstrated that motif subtypes of a TF can be readily identified in this framework and two variants called the k NPV and k ODV methods benefited significantly from motif subtype identification. Finally, independent validation on ChIP-seq data showed that the ODV and NPV methods significantly outperformed the other compared methods. Conclusions We conclude that the proposed framework is highly flexible. It enables the two novel methods to automatically identify a TF-specific subspace to search for binding sites. Implementations are available as source code at: http://biogrid.engr.uconn.edu/tfbs_search/. PMID:23244338

Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia

PubMed Central

Eastin, Matthew D.; Delmelle, Eric; Casas, Irene; Wexler, Joshua; Self, Cameron

2014-01-01

Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors—all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C—the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts. PMID:24957546

Economic growth and CO2 emissions: an investigation with smooth transition autoregressive distributed lag models for the 1800-2014 period in the USA.

PubMed

Bildirici, Melike; Ersin, Özgür Ömer

2018-01-01

The study aims to combine the autoregressive distributed lag (ARDL) cointegration framework with smooth transition autoregressive (STAR)-type nonlinear econometric models for causal inference. Further, the proposed STAR distributed lag (STARDL) models offer new insights in terms of modeling nonlinearity in the long- and short-run relations between analyzed variables. The STARDL method allows modeling and testing nonlinearity in the short-run and long-run parameters or both in the short- and long-run relations. To this aim, the relation between CO 2 emissions and economic growth rates in the USA is investigated for the 1800-2014 period, which is one of the largest data sets available. The proposed hybrid models are the logistic, exponential, and second-order logistic smooth transition autoregressive distributed lag (LSTARDL, ESTARDL, and LSTAR2DL) models combine the STAR framework with nonlinear ARDL-type cointegration to augment the linear ARDL approach with smooth transitional nonlinearity. The proposed models provide a new approach to the relevant econometrics and environmental economics literature. Our results indicated the presence of asymmetric long-run and short-run relations between the analyzed variables that are from the GDP towards CO 2 emissions. By the use of newly proposed STARDL models, the results are in favor of important differences in terms of the response of CO 2 emissions in regimes 1 and 2 for the estimated LSTAR2DL and LSTARDL models.

Processing on weak electric signals by the autoregressive model

NASA Astrophysics Data System (ADS)

Ding, Jinli; Zhao, Jiayin; Wang, Lanzhou; Li, Qiao

2008-10-01

A model of the autoregressive model of weak electric signals in two plants was set up for the first time. The result of the AR model to forecast 10 values of the weak electric signals is well. It will construct a standard set of the AR model coefficient of the plant electric signal and the environmental factor, and can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on agricultural productions.

An adenovirus vectored mucosal adjuvant augments protection of mice immunized intranasally with an adenovirus-vectored foot-and-mouth disease virus subunit vaccine.

PubMed

Alejo, Diana M; Moraes, Mauro P; Liao, Xiaofen; Dias, Camila C; Tulman, Edan R; Diaz-San Segundo, Fayna; Rood, Debra; Grubman, Marvin J; Silbart, Lawrence K

2013-04-26

Foot-and-mouth disease virus (FMDV) is a highly contagious pathogen that causes severe morbidity and economic losses to the livestock industry in many countries. The oral and respiratory mucosae are the main ports of entry of FMDV, so the stimulation of local immunity in these tissues may help prevent initial infection and viral spread. E. coli heat-labile enterotoxin (LT) has been described as one of the few molecules that have adjuvant activity at mucosal surfaces. The objective of this study was to evaluate the efficacy of replication-defective adenovirus 5 (Ad5) vectors encoding either of two LT-based mucosal adjuvants, LTB or LTR72. These vectored adjuvants were delivered intranasally to mice concurrent with an Ad5-FMDV vaccine (Ad5-A24) to assess their ability to augment mucosal and systemic humoral immune responses to Ad5-A24 and protection against FMDV. Mice receiving Ad5-A24 plus Ad5-LTR72 had higher levels of mucosal and systemic neutralizing antibodies than those receiving Ad5-A24 alone or Ad5-A24 plus Ad5-LTB. The vaccine plus Ad5-LTR72 group also demonstrated 100% survival after intradermal challenge with a lethal dose of homologous FMDV serotype A24. These results suggest that Ad5-LTR72 could be used as an important tool to enhance mucosal and systemic immunity against FMDV and potentially other pathogens with a common route of entry. Copyright © 2013 Elsevier Ltd. All rights reserved.

Kepler AutoRegressive Planet Search

NASA Astrophysics Data System (ADS)

Feigelson, Eric

NASA's Kepler mission is the source of more exoplanets than any other instrument, but the discovery depends on complex statistical analysis procedures embedded in the Kepler pipeline. A particular challenge is mitigating irregular stellar variability without loss of sensitivity to faint periodic planetary transits. This proposal presents a two-stage alternative analysis procedure. First, parametric autoregressive ARFIMA models, commonly used in econometrics, remove most of the stellar variations. Second, a novel matched filter is used to create a periodogram from which transit-like periodicities are identified. This analysis procedure, the Kepler AutoRegressive Planet Search (KARPS), is confirming most of the Kepler Objects of Interest and is expected to identify additional planetary candidates. The proposed research will complete application of the KARPS methodology to the prime Kepler mission light curves of 200,000: stars, and compare the results with Kepler Objects of Interest obtained with the Kepler pipeline. We will then conduct a variety of astronomical studies based on the KARPS results. Important subsamples will be extracted including Habitable Zone planets, hot super-Earths, grazing-transit hot Jupiters, and multi-planet systems. Groundbased spectroscopy of poorly studied candidates will be performed to better characterize the host stars. Studies of stellar variability will then be pursued based on KARPS analysis. The autocorrelation function and nonstationarity measures will be used to identify spotted stars at different stages of autoregressive modeling. Periodic variables with folded light curves inconsistent with planetary transits will be identified; they may be eclipsing or mutually-illuminating binary star systems. Classification of stellar variables with KARPS-derived statistical properties will be attempted. KARPS procedures will then be applied to archived K2 data to identify planetary transits and characterize stellar variability.

Equivalent Dynamic Models.

PubMed

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

Electromagnetic and axial-vector form factors of the quarks and nucleon

NASA Astrophysics Data System (ADS)

Dahiya, Harleen; Randhawa, Monika

2017-11-01

In light of the improved precision of the experimental measurements and enormous theoretical progress, the nucleon form factors have been evaluated with an aim to understand how the static properties and dynamical behavior of nucleons emerge from the theory of strong interactions between quarks. We have analyzed the vector and axial-vector nucleon form factors (GE,Mp,n(Q2) and GAp,n(Q2)) using the spin observables in the chiral constituent quark model (χCQM) which has made a significant contribution to the unraveling of the internal structure of the nucleon in the nonperturbative regime. We have also presented a comprehensive analysis of the flavor decomposition of the form factors (GEq(Q2), GMq(Q2) and GAq(Q2) for q = u,d,s) within the framework of χCQM with emphasis on the extraction of the strangeness form factors which are fundamental to determine the spin structure and test the chiral symmetry breaking effects in the nucleon. The Q2 dependence of the vector and axial-vector form factors of the nucleon has been studied using the conventional dipole form of parametrization. The results are in agreement with the available experimental data.

Detection and classification of subject-generated artifacts in EEG signals using autoregressive models.

PubMed

Lawhern, Vernon; Hairston, W David; McDowell, Kaleb; Westerfield, Marissa; Robbins, Kay

2012-07-15

We examine the problem of accurate detection and classification of artifacts in continuous EEG recordings. Manual identification of artifacts, by means of an expert or panel of experts, can be tedious, time-consuming and infeasible for large datasets. We use autoregressive (AR) models for feature extraction and characterization of EEG signals containing several kinds of subject-generated artifacts. AR model parameters are scale-invariant features that can be used to develop models of artifacts across a population. We use a support vector machine (SVM) classifier to discriminate among artifact conditions using the AR model parameters as features. Results indicate reliable classification among several different artifact conditions across subjects (approximately 94%). These results suggest that AR modeling can be a useful tool for discriminating among artifact signals both within and across individuals. Copyright © 2012 Elsevier B.V. All rights reserved.

Mathematical model with autoregressive process for electrocardiogram signals

NASA Astrophysics Data System (ADS)

Evaristo, Ronaldo M.; Batista, Antonio M.; Viana, Ricardo L.; Iarosz, Kelly C.; Szezech, José D., Jr.; Godoy, Moacir F. de

2018-04-01

The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to obtain the tachograms and the electrocardiogram signals of young adults with normal heartbeats. Our results are compared with experimental tachogram by means of Poincaré plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.

Texture classification using autoregressive filtering

NASA Technical Reports Server (NTRS)

Lawton, W. M.; Lee, M.

1984-01-01

A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

Get Over It! A Multilevel Threshold Autoregressive Model for State-Dependent Affect Regulation.

PubMed

De Haan-Rietdijk, Silvia; Gottman, John M; Bergeman, Cindy S; Hamaker, Ellen L

2016-03-01

Intensive longitudinal data provide rich information, which is best captured when specialized models are used in the analysis. One of these models is the multilevel autoregressive model, which psychologists have applied successfully to study affect regulation as well as alcohol use. A limitation of this model is that the autoregressive parameter is treated as a fixed, trait-like property of a person. We argue that the autoregressive parameter may be state-dependent, for example, if the strength of affect regulation depends on the intensity of affect experienced. To allow such intra-individual variation, we propose a multilevel threshold autoregressive model. Using simulations, we show that this model can be used to detect state-dependent regulation with adequate power and Type I error. The potential of the new modeling approach is illustrated with two empirical applications that extend the basic model to address additional substantive research questions.

Kepler AutoRegressive Planet Search (KARPS)

NASA Astrophysics Data System (ADS)

Caceres, Gabriel

2018-01-01

One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The Kepler AutoRegressive Planet Search (KARPS) project implements statistical methodology associated with autoregressive processes (in particular, ARIMA and ARFIMA) to model stellar lightcurves in order to improve exoplanet transit detection. We also develop a novel Transit Comb Filter (TCF) applied to the AR residuals which provides a periodogram analogous to the standard Box-fitting Least Squares (BLS) periodogram. We train a random forest classifier on known Kepler Objects of Interest (KOIs) using select features from different stages of this analysis, and then use ROC curves to define and calibrate the criteria to recover the KOI planet candidates with high fidelity. These statistical methods are detailed in a contributed poster (Feigelson et al., this meeting).These procedures are applied to the full DR25 dataset of NASA’s Kepler mission. Using the classification criteria, a vast majority of known KOIs are recovered and dozens of new KARPS Candidate Planets (KCPs) discovered, including ultra-short period exoplanets. The KCPs will be briefly presented and discussed.

To center or not to center? Investigating inertia with a multilevel autoregressive model.

PubMed

Hamaker, Ellen L; Grasman, Raoul P P P

2014-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.

To center or not to center? Investigating inertia with a multilevel autoregressive model

PubMed Central

Hamaker, Ellen L.; Grasman, Raoul P. P. P.

2015-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model. PMID:25688215

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Three essays on price dynamics and causations among energy markets and macroeconomic information

NASA Astrophysics Data System (ADS)

Hong, Sung Wook

This dissertation examines three important issues in energy markets: price dynamics, information flow, and structural change. We discuss each issue in detail, building empirical time series models, analyzing the results, and interpreting the findings. First, we examine the contemporaneous interdependencies and information flows among crude oil, natural gas, and electricity prices in the United States (US) through the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, Directed Acyclic Graph (DAG) for contemporaneous causal structures and Bernanke factorization for price dynamic processes. Test results show that the DAG from residuals of out-of-sample-forecast is consistent with the DAG from residuals of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial indicators by using a Factor Augmented Vector Autoregression (FAVAR) model and a graphical model without any deductive assumption. The results show that, in contemporaneous time, the federal fund rate shock is exogenous as the identifying assumption in the Vector Autoregression (VAR) framework of the monetary shock transmission mechanism, whereas the WTI crude oil price return is not exogenous. Third, we examine price dynamics and contemporaneous causality among the price returns of WTI crude oil, gasoline, corn, and the S&P 500. We look for structural break points and then build an econometric model to find the consistent sub-periods having stable parameters in a given VAR framework and to explain recent movements and interdependency among returns. We found strong evidence of two structural breaks and contemporaneous causal relationships among the residuals, but also significant differences between contemporaneous causal structures for each sub-period.

Modeling the Effects of Augmentation Strategies on the Control of Dengue Fever With an Impulsive Differential Equation.

PubMed

Zhang, Xianghong; Tang, Sanyi; Cheke, Robert A; Zhu, Huaiping

2016-10-01

Dengue fever has rapidly become the world's most common vector-borne viral disease. Use of endosymbiotic Wolbachia is an innovative technology to prevent vector mosquitoes from reproducing and so break the cycle of dengue transmission. However, strategies such as population eradication and replacement will only succeed if appropriate augmentations with Wolbachia-infected mosquitoes that take account of a variety of factors are carried out. Here, we describe the spread of Wolbachia in mosquito populations using an impulsive differential system with four state variables, incorporating the effects of cytoplasmic incompatibility and the augmentation of Wolbachia-infected mosquitoes with different sex ratios. We then evaluated (a) how each parameter value contributes to the success of population replacement; (b) how different release quantities of infected mosquitoes with different sex ratios affect the success of population suppression or replacement; and (c) how the success of these two strategies can be realized to block the transmission of dengue fever. Analysis of the system's stability, bifurcations and sensitivity reveals the existence of forward and backward bifurcations, multiple attractors and the contribution of each parameter to the success of the strategies. The results indicate that the initial density of mosquitoes, the quantities of mosquitoes released in augmentations and their sex ratios have impacts on whether or not the strategies of population suppression or replacement can be achieved. Therefore, successful strategies rely on selecting suitable strains of Wolbachia and carefully designing the mosquito augmentation program.

Spatial Autocorrelation And Autoregressive Models In Ecology

Treesearch

Jeremy W. Lichstein; Theodore R. Simons; Susan A. Shriner; Kathleen E. Franzreb

2003-01-01

Abstract. Recognition and analysis of spatial autocorrelation has defined a new paradigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available...

Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

PubMed

Levine, Matthew E; Albers, David J; Hripcsak, George

2016-01-01

Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

CMG-Augmented Control of a Hovering VTOL Platform

NASA Technical Reports Server (NTRS)

Lim, K. B.; Moerder, D. D.

2007-01-01

This paper describes how Control Moment Gyroscopes (CMGs) can be used for stability augmentation to a thrust vectoring system for a generic Vertical Take-Off and Landing platform. The response characteristics of the platform which uses only thrust vectoring and a second configuration which includes a single-gimbal CMG array are simulated and compared for hovering flight while subject to severe air turbulence. Simulation results demonstrate the effectiveness of a CMG array in its ability to significantly reduce the agility requirement on the thrust vectoring system. Albeit simplifying physical assumptions on a generic CMG configuration, the numerical results also suggest that reasonably sized CMGs will likely be sufficient for a small hovering vehicle.

Restless legs syndrome augmentation among Japanese patients receiving pramipexole therapy: Rate and risk factors in a retrospective study

PubMed Central

Takahashi, Masayoshi; Nishida, Shingo; Nakamura, Masaki; Kobayashi, Mina; Matsui, Kentaro; Ito, Eiki; Usui, Akira; Inoue, Yuichi

2017-01-01

To investigate the rate of and risk factors for restless legs syndrome (RLS) augmentation in Japanese patients receiving pramipexole (PPX) treatment. Records of 231 consecutive patients with idiopathic RLS who received PPX therapy for more than one month in a single sleep disorder center were analyzed retrospectively. Augmentation was diagnosed based on the Max Planck Institute criteria; associated factors were identified by logistic regression analysis. Mean age at PPX initiation was 60.6 ± 14.9 years and mean treatment duration was 48.5 ± 26.4 months. Augmentation was diagnosed in 21 patients (9.1%). Daily PPX dose and treatment duration were significantly associated with augmentation. By analyzing the receiver operating characteristic curve, a PPX dose of 0.375 mg/day was found to be the optimal cut-off value for predicting augmentation. After stratifying patients according to PPX treatment duration, at median treatment duration of 46 months, optimal cut-off values for daily doses were 0.375 and 0.500 mg/day for <46 months and ≥46 months of treatment, respectively. The RLS augmentation with PPX treatment in Japanese patients was occurred at rate of 9.1%, being quite compatible with previously reported rates in Caucasian patients. The symptom could appear within a relatively short period after starting the treatment in possibly vulnerable cases even with a smaller drug dose. Our results support the importance of keeping doses of PPX low throughout the RLS treatment course to prevent augmentation. PMID:28264052

Growth/differentiation factor-5: pre-clinical and clinical evaluations of periodontal regeneration and alveolar augmentation--review.

PubMed

Lee, Jaebum; Wikesjö, Ulf M E

2014-08-01

Growth/differentiation factor-5 (GDF-5) plays critical roles in mesenchymal cell differentiation and stimulates human periodontal ligament cell proliferation. Potentially, GDF-5 may also play roles in wound healing including periodontal regeneration and alveolar augmentation. The objective of this review was to provide up-to-date information from pre-clinical/clinical studies evaluating GDF-5 for these indications. A comprehensive search using PubMed and Google search engines was conducted to identify reports on GDF-5 applied to periodontal and alveolar indications. Two reviewers independently screened the titles and abstracts from a total of 479 reports. Full-length articles of 17 pre-clinical and four clinical studies were selected and reviewed. Canine-, porcine- and non-human primate-based models as well as human clinical trials were used in the evaluation of GDF-5 in support of periodontal regeneration and alveolar augmentation. An absorbable collagen sponge (ACS), β-tricalcium phosphate (β-TCP) and a poly(lactic-co-glycolic) acid (PLGA) were evaluated as candidate carriers for GDF-5 using various dose and healing intervals demonstrating significantly enhanced periodontal regeneration/alveolar augmentation including cementum, periodontal ligament and alveolar bone with limited, if any, adverse effects. Growth/differentiation factor-5 supports periodontal regeneration/alveolar augmentation without aberrant healing events documented in qualified pre-clinical models and clinical pilot studies. In perspective, GDF-5 appears a promising technology for periodontal regeneration/alveolar augmentation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Longitudinal vector form factors in weak decays of nuclei

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

Šimkovic, F.; Department of Nuclear Physics and Biophysics, Comenius University, Mlynská dolina F1 SK–842 48 Bratislava; Kovalenko, S.

2015-10-28

The longitudinal form factors of the weak vector current of particles with spin J = 1/2 and isospin I = 1/2 are determined by the mass difference and the charge radii of members of the isotopic doublets. The most promising reactions to measure these form factors are the reactions with large momentum transfers involving the spin-1/2 isotopic doublets with a maximum mass splitting. Numerical estimates of longitudinal form factors are given for nucleons and eight nuclear spin-1/2 isotopic doublets.

Mechanical stretch augments insulin-induced vascular smooth muscle cell proliferation by insulin-like growth factor-1 receptor

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

Liu, Gang; Department of Anesthesiology, First Affiliated Hospital of China Medical University, Shenyang; Hitomi, Hirofumi, E-mail: hitomi@kms.ac.jp

Insulin resistance and hypertension have been implicated in the pathogenesis of cardiovascular disease; however, little is known about the roles of insulin and mechanical force in vascular smooth muscle cell (VSMC) remodeling. We investigated the contribution of mechanical stretch to insulin-induced VSMC proliferation. Thymidine incorporation was stimulated by insulin in stretched VSMCs, but not in un-stretched VSMCs. Insulin increased 2-deoxy-glucose incorporation in both stretched and un-stretched VSMCs. Mechanical stretch augmented insulin-induced extracellular signal-regulated kinase (ERK) and Akt phosphorylation. Inhibitors of epidermal growth factor (EGF) receptor tyrosine kinase and Src attenuated insulin-induced ERK and Akt phosphorylation, as well as thymidine incorporation,more » whereas 2-deoxy-glucose incorporation was not affected by these inhibitors. Moreover, stretch augmented insulin-like growth factor (IGF)-1 receptor expression, although it did not alter the expression of insulin receptor and insulin receptor substrate-1. Insulin-induced ERK and Akt activation, and thymidine incorporation were inhibited by siRNA for the IGF-1 receptor. Mechanical stretch augments insulin-induced VSMC proliferation via upregulation of IGF-1 receptor, and downstream Src/EGF receptor-mediated ERK and Akt activation. Similar to in vitro experiment, IGF-1 receptor expression was also augmented in hypertensive rats. These results provide a basis for clarifying the molecular mechanisms of vascular remodeling in hypertensive patients with hyperinsulinemia. -- Highlights: {yields} Mechanical stretch augments insulin-induced VSMC proliferation via IGF-1 receptor. {yields} Src/EGFR-mediated ERK and Akt phosphorylation are augmented in stretched VSMCs. {yields} Similar to in vitro experiment, IGF-1 receptor is increased in hypertensive rats. {yields} Results provide possible mechanisms of vascular remodeling in hypertension with DM.« less

Theoretical results on fractionally integrated exponential generalized autoregressive conditional heteroskedastic processes

NASA Astrophysics Data System (ADS)

Lopes, Sílvia R. C.; Prass, Taiane S.

2014-05-01

Here we present a theoretical study on the main properties of Fractionally Integrated Exponential Generalized Autoregressive Conditional Heteroskedastic (FIEGARCH) processes. We analyze the conditions for the existence, the invertibility, the stationarity and the ergodicity of these processes. We prove that, if { is a FIEGARCH(p,d,q) process then, under mild conditions, { is an ARFIMA(q,d,0) with correlated innovations, that is, an autoregressive fractionally integrated moving average process. The convergence order for the polynomial coefficients that describes the volatility is presented and results related to the spectral representation and to the covariance structure of both processes { and { are discussed. Expressions for the kurtosis and the asymmetry measures for any stationary FIEGARCH(p,d,q) process are also derived. The h-step ahead forecast for the processes {, { and { are given with their respective mean square error of forecast. The work also presents a Monte Carlo simulation study showing how to generate, estimate and forecast based on six different FIEGARCH models. The forecasting performance of six models belonging to the class of autoregressive conditional heteroskedastic models (namely, ARCH-type models) and radial basis models is compared through an empirical application to Brazilian stock market exchange index.

The Use of Recombinant Human Platelet-Derived Growth Factor for Maxillary Sinus Augmentation.

PubMed

Kubota, Atsushi; Sarmiento, Hector; Alqahtani, Mohammed Saad; Llobell, Arturo; Fiorellini, Joseph P

The maxillary sinus augmentation procedure has become a predictable treatment to regenerate bone for implant placement. The purpose of this study was to evaluate the effect of recombinant human platelet-derived growth factor BB (rhPDGF-BB) combined with a deproteinized cancellous bovine bone graft for sinus augmentation. The lateral window approach was used for maxillary sinuses with minimal residual bone. After a healing period of 4 months, dental implants were placed and then restored following a 2-month osseointegration period. The result demonstrated increased bone height and ISQ values and a 100% survival rate. This study indicates that the addition of rhPDGF-BB to deproteinized cancellous bovine bone accelerated the healing period in maxillary sinuses with minimal native bone.

[Exploration of influencing factors of price of herbal based on VAR model].

PubMed

Wang, Nuo; Liu, Shu-Zhen; Yang, Guang

2014-10-01

Based on vector auto-regression (VAR) model, this paper takes advantage of Granger causality test, variance decomposition and impulse response analysis techniques to carry out a comprehensive study of the factors influencing the price of Chinese herbal, including herbal cultivation costs, acreage, natural disasters, the residents' needs and inflation. The study found that there is Granger causality relationship between inflation and herbal prices, cultivation costs and herbal prices. And in the total variance analysis of Chinese herbal and medicine price index, the largest contribution to it is from its own fluctuations, followed by the cultivation costs and inflation.

Autoregressive Processes in Homogenization of GNSS Tropospheric Data

NASA Astrophysics Data System (ADS)

Klos, A.; Bogusz, J.; Teferle, F. N.; Bock, O.; Pottiaux, E.; Van Malderen, R.

2016-12-01

Offsets due to changes in hardware equipment or any other artificial event are all a subject of a task of homogenization of tropospheric data estimated within a processing of Global Navigation Satellite System (GNSS) observables. This task is aimed at identifying exact epochs of offsets and estimate their magnitudes since they may artificially under- or over-estimate trend and its uncertainty delivered from tropospheric data and used in climate studies. In this research, we analysed a common data set of differences of Integrated Water Vapour (IWV) from GPS and ERA-Interim (1995-2010) provided for a homogenization group working within ES1206 COST Action GNSS4SWEC. We analysed daily IWV records of GPS and ERA-Interim in terms of trend, seasonal terms and noise model with Maximum Likelihood Estimation in Hector software. We found that this data has a character of autoregressive process (AR). Basing on this analysis, we performed Monte Carlo simulations of 25 years long data with two different noise types: white as well as combination of white and autoregressive and also added few strictly defined offsets. This synthetic data set of exactly the same character as IWV from GPS and ERA-Interim was then subjected to a task of manual and automatic/statistical homogenization. We made blind tests and detected possible epochs of offsets manually. We found that simulated offsets were easily detected in series with white noise, no influence of seasonal signal was noticed. The autoregressive series were much more problematic when offsets had to be determined. We found few epochs, for which no offset was simulated. This was mainly due to strong autocorrelation of data, which brings an artificial trend within. Due to regime-like behaviour of AR it is difficult for statistical methods to properly detect epochs of offsets, which was previously reported by climatologists.

Methodology for the AutoRegressive Planet Search (ARPS) Project

NASA Astrophysics Data System (ADS)

Feigelson, Eric; Caceres, Gabriel; ARPS Collaboration

2018-01-01

The detection of periodic signals of transiting exoplanets is often impeded by the presence of aperiodic photometric variations. This variability is intrinsic to the host star in space-based observations (typically arising from magnetic activity) and from observational conditions in ground-based observations. The most common statistical procedures to remove stellar variations are nonparametric, such as wavelet decomposition or Gaussian Processes regression. However, many stars display variability with autoregressive properties, wherein later flux values are correlated with previous ones. Providing the time series is evenly spaced, parametric autoregressive models can prove very effective. Here we present the methodology of the Autoregessive Planet Search (ARPS) project which uses Autoregressive Integrated Moving Average (ARIMA) models to treat a wide variety of stochastic short-memory processes, as well as nonstationarity. Additionally, we introduce a planet-search algorithm to detect periodic transits in the time-series residuals after application of ARIMA models. Our matched-filter algorithm, the Transit Comb Filter (TCF), replaces the traditional box-fitting step. We construct a periodogram based on the TCF to concentrate the signal of these periodic spikes. Various features of the original light curves, the ARIMA fits, the TCF periodograms, and folded light curves at peaks of the TCF periodogram can then be collected to provide constraints for planet detection. These features provide input into a multivariate classifier when a training set is available. The ARPS procedure has been applied NASA's Kepler mission observations of ~200,000 stars (Caceres, Dissertation Talk, this meeting) and will be applied in the future to other datasets.

Image Augmentation for Object Image Classification Based On Combination of Pre-Trained CNN and SVM

NASA Astrophysics Data System (ADS)

Shima, Yoshihiro

2018-04-01

Neural networks are a powerful means of classifying object images. The proposed image category classification method for object images combines convolutional neural networks (CNNs) and support vector machines (SVMs). A pre-trained CNN, called Alex-Net, is used as a pattern-feature extractor. Alex-Net is pre-trained for the large-scale object-image dataset ImageNet. Instead of training, Alex-Net, pre-trained for ImageNet is used. An SVM is used as trainable classifier. The feature vectors are passed to the SVM from Alex-Net. The STL-10 dataset are used as object images. The number of classes is ten. Training and test samples are clearly split. STL-10 object images are trained by the SVM with data augmentation. We use the pattern transformation method with the cosine function. We also apply some augmentation method such as rotation, skewing and elastic distortion. By using the cosine function, the original patterns were left-justified, right-justified, top-justified, or bottom-justified. Patterns were also center-justified and enlarged. Test error rate is decreased by 0.435 percentage points from 16.055% by augmentation with cosine transformation. Error rates are increased by other augmentation method such as rotation, skewing and elastic distortion, compared without augmentation. Number of augmented data is 30 times that of the original STL-10 5K training samples. Experimental test error rate for the test 8k STL-10 object images was 15.620%, which shows that image augmentation is effective for image category classification.

Stability boundaries for command augmentation systems

NASA Technical Reports Server (NTRS)

Shrivastava, P. C.

1987-01-01

The Stability Augmentation System (SAS) is a special case of the Command Augmentation System (CAS). Control saturation imposes bounds on achievable commands. The state equilibrium depends only on the open loop dynamics and control deflection. The control magnitude to achieve a desired command equilibrium is independent of the feedback gain. A feedback controller provides the desired response, maintains the system equilibrium under disturbances, but it does not affect the equilibrium values of states and control. The saturation boundaries change with commands, but the location of the equilibrium points in the saturated region remains unchanged. Nonzero command vectors yield saturation boundaries that are asymmetric with respect to the state equilibrium. Except for the saddle point case with MCE control law, the stability boundaries change with commands. For the cases of saddle point and unstable nodes, the region of stability decreases with increasing command magnitudes.

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE PAGES

Buitrago, Jaime; Asfour, Shihab

2017-01-01

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

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

Buitrago, Jaime; Asfour, Shihab

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Sleep analysis for wearable devices applying autoregressive parametric models.

PubMed

Mendez, M O; Villantieri, O; Bianchi, A; Cerutti, S

2005-01-01

We applied time-variant and time-invariant parametric models in both healthy subjects and patients with sleep disorder recordings in order to assess the skills of those approaches to sleep disorders diagnosis in wearable devices. The recordings present the Obstructive Sleep Apnea (OSA) pathology which is characterized by fluctuations in the heart rate, bradycardia in apneonic phase and tachycardia at the recovery of ventilation. Data come from a web database in www.physionet.org. During OSA the spectral indexes obtained by time-variant lattice filters presented oscillations that correspond to the changes brady-tachycardia of the RR intervals and greater values than healthy ones. Multivariate autoregressive models showed an increment in very low frequency component (PVLF) at each apneic event. Also a rise in high frequency component (PHF) occurred over the breathing restore in the spectrum of both quadratic coherence and cross-spectrum in OSA. These autoregressive parametric approaches could help in the diagnosis of Sleep Disorder inside of the wearable devices.

Autoregressive Methods for Spectral Estimation from Interferograms.

DTIC Science & Technology

1986-09-19

RL83 6?6 AUTOREGRESSIVE METHODS FOR SPECTRAL. ESTIMTION FROM / SPACE ENGINEERING E N RICHARDS ET AL. 19 SEPINEFRGAS.()UA TT NV GNCNE O C: 31SSF...was AUG1085 performed under subcontract to . Center for Space Engineering Utah State University Logan, UT 84322-4140 4 4 Scientific Report No. 17 AFGL...MONITORING ORGANIZATION Center for Space Engineering (iapplicable) Air Force Geophysics Laboratory e. AORESS (City. State and ZIP Code) 7b. AOORESS (City

Vector Communication Curriculum: Moderate and Severe, Multiple Disabilities.

ERIC Educational Resources Information Center

Baine, David

This CD-ROM disk contains a curriculum on vector communication for students with moderate and severe multiple disabilities. Section 1 discusses pragmatic communication, functional analysis of behavior, augmentative and alternative communication, including gestures and signs, use of pictures and pictographs, and low, medium, and high tech…

Development of novel types of plastid transformation vectors and evaluation of factors controlling expression.

PubMed

Herz, Stefan; Füssl, Monika; Steiger, Sandra; Koop, Hans-Ulrich

2005-12-01

Two new vector types for plastid transformation were developed and uidA reporter gene expression was compared to standard transformation vectors. The first vector type does not contain any plastid promoter, instead it relies on extension of existing plastid operons and was therefore named "operon-extension" vector. When a strongly expressed plastid operon like psbA was extended by the reporter gene with this vector type, the expression level was superior to that of a standard vector under control of the 16S rRNA promoter. Different insertion sites, promoters and 5'-UTRs were analysed for their effect on reporter gene expression with standard and operon-extension vectors. The 5'-UTR of phage 7 gene 10 in combination with a modified N-terminus was found to yield the highest expression levels. Expression levels were also strongly dependent on external factors like plant or leaf age or light intensity. In the second vector type, named "split" plastid transformation vector, modules of the expression cassette were distributed on two separate vectors. Upon co-transformation of plastids with these vectors, the complete expression cassette became inserted into the plastome. This result can be explained by successive co-integration of the split vectors and final loop-out recombination of the duplicated sequences. The split vector concept was validated with different vector pairs.

High glucose augments angiotensinogen in human renal proximal tubular cells through hepatocyte nuclear factor-5

PubMed Central

Wang, Juan; Shibayama, Yuki; Kobori, Hiroyuki; Liu, Ya; Kobara, Hideki; Masaki, Tsutomu; Wang, Zhiyu

2017-01-01

High glucose has been demonstrated to induce angiotensinogen (AGT) synthesis in the renal proximal tubular cells (RPTCs) of rats, which may further activate the intrarenal renin-angiotensin system (RAS) and contribute to diabetic nephropathy. This study aimed to investigate the effects of high glucose on AGT in the RPTCs of human origin and identify the glucose-responsive transcriptional factor(s) that bind(s) to the DNA sequences of AGT promoter in human RPTCs. Human kidney (HK)-2 cells were treated with normal glucose (5.5 mM) and high glucose (15.0 mM), respectively. Levels of AGT mRNA and AGT secretion of HK-2 cells were measured by real-time polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA), respectively. Consecutive 5’-end deletion mutant constructs and different site-directed mutagenesis products of human AGT promoter sequences were respectively transfected into HK-2 cells, followed by AGT promoter activity measurement through dual luciferase assay. High glucose significantly augmented the levels of AGT mRNA and AGT secretion of HK-2 cells, compared with normal glucose treatment. High glucose also significantly augmented AGT promoter activity in HK-2 cells transfected with the constructs of human AGT promoter sequences, compared with normal glucose treatment. Hepatocyte nuclear factor (HNF)-5 was found to be one of the glucose-responsive transcriptional factors of AGT in human RPTCs, since the mutation of its binding sites within AGT promoter sequences abolished the above effects of high glucose on AGT promoter activity as well as levels of AGT mRNA and its secretion. The present study has demonstrated, for the first time, that high glucose augments AGT in human RPTCs through HNF-5, which provides a potential therapeutic target for diabetic nephropathy. PMID:29053707

Prediction of global ionospheric VTEC maps using an adaptive autoregressive model

NASA Astrophysics Data System (ADS)

Wang, Cheng; Xin, Shaoming; Liu, Xiaolu; Shi, Chuang; Fan, Lei

2018-02-01

In this contribution, an adaptive autoregressive model is proposed and developed to predict global ionospheric vertical total electron content maps (VTEC). Specifically, the spherical harmonic (SH) coefficients are predicted based on the autoregressive model, and the order of the autoregressive model is determined adaptively using the F-test method. To test our method, final CODE and IGS global ionospheric map (GIM) products, as well as altimeter TEC data during low and mid-to-high solar activity period collected by JASON, are used to evaluate the precision of our forecasting products. Results indicate that the predicted products derived from the model proposed in this paper have good consistency with the final GIMs in low solar activity, where the annual mean of the root-mean-square value is approximately 1.5 TECU. However, the performance of predicted vertical TEC in periods of mid-to-high solar activity has less accuracy than that during low solar activity periods, especially in the equatorial ionization anomaly region and the Southern Hemisphere. Additionally, in comparison with forecasting products, the final IGS GIMs have the best consistency with altimeter TEC data. Future work is needed to investigate the performance of forecasting products using the proposed method in an operational environment, rather than using the SH coefficients from the final CODE products, to understand the real-time applicability of the method.

Tumor Necrosis Factor α‐Gene Therapy for an Established Murine Melanoma Using RGB (Arg‐Gly‐Asp) Fiber‐mutant Adenovirus Vectors

PubMed Central

Okada, Yuka; Nakagawa, Shinsaku; Mizuguchi, Hiroyuki; Takahashi, Koichi; Mizuno, Nobuyasu; Fujita, Takuya; Yamamoto, Akira; Hayakawa, Takao; Mayumi, Tadanori

2002-01-01

Although adenovirus vectors (Ad) provide high‐level transduction efficacy to many cell types, extremely high doses of Ad are required for sufficient gene transduction into several tumors, including melanoma. Here, we demonstrated that the expression of coxsackie‐adenovirus receptor, a primitive Ad‐receptor, was very low in murine and human melanoma cells. We also found that fiber‐mutant Ad containing the Arg‐Gly‐Asp (RGD) sequence in the fiber knob remarkably augmented gene transduction efficacy in melanoma cells by targeting αv‐integrins. In addition, intratumoral injection of RGD fiber‐mutant Ad containing the tumor necrosis factor α gene (AdRGD‐TNFα) revealed dramatic anti‐tumor efficacy through hemolytic necrosis in an established murine B16 BL6 melanoma model. Ad‐RGD‐TNFα required one‐tenth the dosage of Ad‐TNFα to induce an equal therapeutic effect. These results suggest that αv‐integrin‐targeted Ad will be a very powerful tool for the advancement of melanoma gene therapy. PMID:11985794

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

Asynchronous arterial systolic expansion as a marker of vascular aging: assessment of the carotid artery with velocity vector imaging.

PubMed

Yang, Woo-In; Shim, Chi Y; Bang, Woo D; Oh, Chang M; Chang, Hyuk J; Chung, Namsik; Ha, Jong-Won

2011-12-01

Arterial elastic properties change with aging. Measurements of pulse wave velocity and augmentation index are useful for the evaluation of arterial stiffness. However, they likely represent only global characteristics of the arterial tree rather than local vascular alterations. The aim of this study was to evaluate whether local vascular properties assessed by velocity vector imaging differed with aging. Vascular properties of carotid arteries with ages were assessed in 100 healthy volunteers (52 men) ranging from 20 to 68 years using velocity vector imaging. The peak circumferential strain and strain rate of the six segments in left common carotid arteries were analyzed and the standard deviation of the time to peak circumferential strain and strain rate of the six segments, representing the synchronicity of the arterial expansion, were calculated. Central blood pressure, augmentation index and pulse wave velocity were assessed by commercially available radial artery tonometry, the SphygmoCor system (AtCor Medical, West Ryde, Australia). A validated generalized transfer function was used to acquire the central aortic pressures and pressure waveforms. Pulse wave velocity, augmentation index and velocity vector imaging parameters showed significant changes with age. However, the age-related changes in pulse wave velocity, augmentation index and velocity vector imaging parameters were different. The increase in pulse wave velocity was more prominent in older individuals, whereas the changes in augmentation index and carotid strain and strain rate were evident earlier, at the age of 30 years. Unlike augmentation index, which showed little change in older individuals, the standard deviation of time to peak strain and strain rate showed a steady increase from younger to older individuals. Asynchronous arterial expansion could be a useful discriminative marker of vascular aging independent of individual's age.

Psychosocial characteristics and motivational factors in woman seeking cosmetic breast augmentation surgery.

PubMed

Nikolić, Jelena; Janjić, Zlata; Marinković, Marija; Petrović, Jelica; Bozić, Teodora

2013-10-01

There are various opinions regarding the factors motivating women to undergo breast augmentation. The aim of this study was to estimate motivation for augmentation mammaplasty (AM), self-esteem and body image perception in breast augmentation patients. This prospective study involved AM patients operated in the Clinical Center of Vojvodina during a 3-year period. A total of 45 patients responded to our package of questionnaires designed to assess motivation for surgery, self-esteem level and body image perception. Those patients were compared to the control group of women who did not want to change their breast size, and who were similar in their age, social status and education level. Our package of questionnaires included a general questionnaire, Photographic Figure Rating Scale (PFRS) and Rosenberg's Self-Esteem Scale. Differences in marital status, educational level, habitation and employment status were statistically insignificant, but there was a significantly lower body mass index (BMI) in the operated women. Considering motives for surgery, a few factors were distinguished: desire to feel more feminine (82.2%), confident (75.5%) and attractive (73.3%), to feel less shy with men (64.4%), to improve their sex life (46.5%), teasing history (42.2%) and easier to find a partner (11.1%) and job (2.2%). Both groups demonstrated a high self-esteem level, but in the the AM group results were lower than in the control group. The mean current self-rating by the PFRS in the group AM was lower than in the control group (4.28 +/- 1.3 vs 5.12 +/- 1.23, respectively) and this coincided with lower BMI in the AM group. The women in the AM group had chosen significantly smaller body size as maximally attractive, and had chosen a narrower attractive body size range than the women in the control group. CONCLUSION. Preoperative evaluation of patients' motives for surgery can help surgeons to exclude woman with unrealistic expectations and different psychological problems.

Augmented renal clearance is not a risk factor for mortality in Enterobacteriaceae bloodstream infections treated with appropriate empiric antimicrobials.

PubMed

Burnham, Jason P; Micek, Scott T; Kollef, Marin H

2017-01-01

The main objective of the study was to assess whether augmented renal clearance was a risk factor for mortality in a cohort of patients with Enterobacteriaceae sepsis, severe sepsis, or septic shock that all received appropriate antimicrobial therapy within 12 hours. Using a retrospective cohort from Barnes-Jewish Hospital, a 1,250-bed teaching hospital, we collected data on individuals with Enterobacteriaceae sepsis, severe sepsis, and septic shock who received appropriate initial antimicrobial therapy between June 2009 and December 2013. Clinical outcomes were compared according to renal clearance, as assessed by Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas, sepsis classification, demographics, severity of illness, and comorbidities. We identified 510 patients with Enterobacteriaceae bacteremia and sepsis, severe sepsis, or septic shock. Sixty-seven patients (13.1%) were nonsurvivors. Augmented renal clearance was uncommon (5.1% of patients by MDRD and 3.0% by CKD-EPI) and was not associated with increased mortality. Our results are limited by the absence of prospective determination of augmented renal clearance. However, in this small cohort, augmented renal clearance as assessed by MDRD and CKD-EPI does not seem to be a risk factor for mortality in patients with Enterobacteriaceae sepsis. Future studies should assess this finding prospectively.

Repeated vertebral augmentation for new vertebral compression fractures of postvertebral augmentation patients: a nationwide cohort study

PubMed Central

Liang, Cheng-Loong; Wang, Hao-Kwan; Syu, Fei-Kai; Wang, Kuo-Wei; Lu, Kang; Liliang, Po-Chou

2015-01-01

Purpose Postvertebral augmentation vertebral compression fractures are common; repeated vertebral augmentation is usually performed for prompt pain relief. This study aimed to evaluate the incidence and risk factors of repeat vertebral augmentation. Methods We performed a retrospective, nationwide, population-based longitudinal observation study, using the National Health Insurance Research Database (NHIRD) of Taiwan. All patients who received vertebral augmentation for vertebral compression fractures were evaluated. The collected data included patient characteristics (demographics, comorbidities, and medication exposure) and repeat vertebral augmentation. Kaplan–Meier and stratified Cox proportional hazard regressions were performed for analyses. Results The overall incidence of repeat vertebral augmentation was 11.3% during the follow-up until 2010. Patients with the following characteristics were at greater risk for repeat vertebral augmentation: female sex (AOR=1.24; 95% confidence interval [CI]: 1.10–2.36), advanced age (AOR=1.60; 95% CI: 1.32–2.08), diabetes mellitus (AOR=4.31; 95% CI: 4.05–5.88), cerebrovascular disease (AOR=4.09; 95% CI: 3.44–5.76), dementia (AOR=1.97; 95% CI: 1.69–2.33), blindness or low vision (AOR=3.72; 95% CI: 2.32–3.95), hypertension (AOR=2.58; 95% CI: 2.35–3.47), and hyperlipidemia (AOR=2.09; 95% CI: 1.67–2.22). Patients taking calcium/vitamin D (AOR=2.98; 95% CI: 1.83–3.93), bisphosphonates (AOR=2.11; 95% CI: 1.26–2.61), or calcitonin (AOR=4.59; 95% CI: 3.40–5.77) were less likely to undergo repeat vertebral augmentation; however, those taking steroids (AOR=7.28; 95% CI: 6.32–8.08), acetaminophen (AOR=3.54; 95% CI: 2.75–4.83), or nonsteroidal anti-inflammatory drugs (NSAIDs) (AOR=6.14; 95% CI: 5.08–7.41) were more likely to undergo repeat vertebral augmentation. Conclusion We conclude that the incidence of repeat vertebral augmentation is rather high. An understanding of risk factors predicting repeat

Orion MPCV Continuum RCS Heating Augmentation Model Development

NASA Technical Reports Server (NTRS)

Hyatt, Andrew J.; White, Molly E.

2014-01-01

The reaction control system jets of the Orion Multi Purpose Crew Vehicle can have a significant impact on the magnitude and distribution of the surface heat flux on the leeside of the aft-body, when they are fired. Changes in surface heating are expressed in terms of augmentation factor over the baseline smooth body heating. Wind tunnel tests revealed heating augmentation factors as high as 13.0, 7.6, 2.8, and 5.8 for the roll, pitch down, pitch up, and yaw jets respectively. Heating augmentation factor models, based almost exclusively on data from a series of wind tunnel tests have been developed, for the purposes of thermal protection system design. The wind tunnel tests investigated several potential jet-to-freestream similarity parameters, and heating augmentation factors derived from the data showed correlation with the jet-to-freestream momentum ratio. However, this correlation was not utilized in the developed models. Instead augmentation factors were held constant throughout the potential trajectory space. This simplification was driven by the fact that ground to flight traceability and sting effects are not well understood. Given the sensitivity of the reaction control system jet heating augmentation to configuration, geometry, and orientation the focus in the present paper is on the methodology used to develop the models and the lessons learned from the data. The models that are outlined in the present work are specific to the aerothermal database used to design the thermal protection system for the Exploration Flight Test 1 vehicle.

EEG data reduction by means of autoregressive representation and discriminant analysis procedures.

PubMed

Blinowska, K J; Czerwosz, L T; Drabik, W; Franaszczuk, P J; Ekiert, H

1981-06-01

A program for automatic evaluation of EEG spectra, providing considerable reduction of data, was devised. Artefacts were eliminated in two steps: first, the longer duration eye movement artefacts were removed by a fast and simple 'moving integral' methods, then occasional spikes were identified by means of a detection function defined in the formalism of the autoregressive (AR) model. The evaluation of power spectra was performed by means of an FFT and autoregressive representation, which made possible the comparison of both methods. The spectra obtained by means of the AR model had much smaller statistical fluctuations and better resolution, enabling us to follow the time changes of the EEG pattern. Another advantage of the autoregressive approach was the parametric description of the signal. This last property appeared to be essential in distinguishing the changes in the EEG pattern. In a drug study the application of the coefficients of the AR model as input parameters in the discriminant analysis, instead of arbitrary chosen frequency bands, brought a significant improvement in distinguishing the effects of the medication. The favourable properties of the AR model are connected with the fact that the above approach fulfils the maximum entropy principle. This means that the method describes in a maximally consistent way the available information and is free from additional assumptions, which is not the case for the FFT estimate.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Insulated Foamy Viral Vectors

PubMed Central

Browning, Diana L.; Collins, Casey P.; Hocum, Jonah D.; Leap, David J.; Rae, Dustin T.; Trobridge, Grant D.

2016-01-01

Retroviral vector-mediated gene therapy is promising, but genotoxicity has limited its use in the clinic. Genotoxicity is highly dependent on the retroviral vector used, and foamy viral (FV) vectors appear relatively safe. However, internal promoters may still potentially activate nearby genes. We developed insulated FV vectors, using four previously described insulators: a version of the well-studied chicken hypersensitivity site 4 insulator (650cHS4), two synthetic CCCTC-binding factor (CTCF)-based insulators, and an insulator based on the CCAAT box-binding transcription factor/nuclear factor I (7xCTF/NF1). We directly compared these insulators for enhancer-blocking activity, effect on FV vector titer, and fidelity of transfer to both proviral long terminal repeats. The synthetic CTCF-based insulators had the strongest insulating activity, but reduced titers significantly. The 7xCTF/NF1 insulator did not reduce titers but had weak insulating activity. The 650cHS4-insulated FV vector was identified as the overall most promising vector. Uninsulated and 650cHS4-insulated FV vectors were both significantly less genotoxic than gammaretroviral vectors. Integration sites were evaluated in cord blood CD34+ cells and the 650cHS4-insulated FV vector had fewer hotspots compared with an uninsulated FV vector. These data suggest that insulated FV vectors are promising for hematopoietic stem cell gene therapy. PMID:26715244

Adaptive spline autoregression threshold method in forecasting Mitsubishi car sales volume at PT Srikandi Diamond Motors

NASA Astrophysics Data System (ADS)

Susanti, D.; Hartini, E.; Permana, A.

2017-01-01

Sale and purchase of the growing competition between companies in Indonesian, make every company should have a proper planning in order to win the competition with other companies. One of the things that can be done to design the plan is to make car sales forecast for the next few periods, it’s required that the amount of inventory of cars that will be sold in proportion to the number of cars needed. While to get the correct forecasting, on of the methods that can be used is the method of Adaptive Spline Threshold Autoregression (ASTAR). Therefore, this time the discussion will focus on the use of Adaptive Spline Threshold Autoregression (ASTAR) method in forecasting the volume of car sales in PT.Srikandi Diamond Motors using time series data.In the discussion of this research, forecasting using the method of forecasting value Adaptive Spline Threshold Autoregression (ASTAR) produce approximately correct.

Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

PubMed

Komasi, Mehdi; Sharghi, Soroush

2016-01-01

Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process.

Effective matrix-free preconditioning for the augmented immersed interface method

NASA Astrophysics Data System (ADS)

Xia, Jianlin; Li, Zhilin; Ye, Xin

2015-12-01

We present effective and efficient matrix-free preconditioning techniques for the augmented immersed interface method (AIIM). AIIM has been developed recently and is shown to be very effective for interface problems and problems on irregular domains. GMRES is often used to solve for the augmented variable(s) associated with a Schur complement A in AIIM that is defined along the interface or the irregular boundary. The efficiency of AIIM relies on how quickly the system for A can be solved. For some applications, there are substantial difficulties involved, such as the slow convergence of GMRES (particularly for free boundary and moving interface problems), and the inconvenience in finding a preconditioner (due to the situation that only the products of A and vectors are available). Here, we propose matrix-free structured preconditioning techniques for AIIM via adaptive randomized sampling, using only the products of A and vectors to construct a hierarchically semiseparable matrix approximation to A. Several improvements over existing schemes are shown so as to enhance the efficiency and also avoid potential instability. The significance of the preconditioners includes: (1) they do not require the entries of A or the multiplication of AT with vectors; (2) constructing the preconditioners needs only O (log ⁡ N) matrix-vector products and O (N) storage, where N is the size of A; (3) applying the preconditioners needs only O (N) flops; (4) they are very flexible and do not require any a priori knowledge of the structure of A. The preconditioners are observed to significantly accelerate the convergence of GMRES, with heuristical justifications of the effectiveness. Comprehensive tests on several important applications are provided, such as Navier-Stokes equations on irregular domains with traction boundary conditions, interface problems in incompressible flows, mixed boundary problems, and free boundary problems. The preconditioning techniques are also useful for

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

PubMed

Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting

PubMed Central

Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an “optimal” weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds. PMID:27382627

Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Ouyang, Huei-Tau

2017-07-01

Three types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive model with exogenous inputs (LARX), the nonlinear autoregressive model with exogenous inputs with wavelet function (NLARX-W) and the nonlinear autoregressive model with exogenous inputs with sigmoid function (NLARX-S). The forecast performance was evaluated by three indices: coefficient of efficiency, error in peak water level and relative time shift. Historical typhoon data were used to establish water-level forecasting models that satisfy all three objectives. A multi-objective genetic algorithm was employed to search for the Pareto-optimal model set that satisfies all three objectives and select the ideal models for the three indices. Findings showed that the optimized nonlinear models (NLARX-W and NLARX-S) outperformed the linear model (LARX). Among the nonlinear models, the optimized NLARX-W model achieved a more balanced performance on the three indices than the NLARX-S models and is recommended for inundation forecasting during typhoons.

Autoregressive modelling of species richness in the Brazilian Cerrado.

PubMed

Vieira, C M; Blamires, D; Diniz-Filho, J A F; Bini, L M; Rangel, T F L V B

2008-05-01

Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R(2) values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.

Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

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

Xiao, Xiao; Gang, Yi; Department of Infectious Diseases, Tangdu Hospital, Fourth Military Medical University, Xi’an 710038, Shaanxi Province

2015-02-06

Highlights: • A shRNA vector based transcription factor decoy, VB-ODN, was designed. • VB-ODN for NF-κB inhibited cell viability in HEK293 cells. • VB-ODN inhibited expression of downstream genes of target transcription factors. • VB-ODN may enhance nuclear entry ratio for its feasibility of virus production. - Abstract: In this study, we designed a short hairpin RNA vector-based oligodeoxynucleotide (VB-ODN) carrying transcription factor (TF) consensus sequence which could function as a decoy to block TF activity. Specifically, VB-ODN for Nuclear factor-κB (NF-κB) could inhibit cell viability and decrease downstream gene expression in HEK293 cells without affecting expression of NF-κB itself.more » The specific binding between VB-ODN produced double-stranded RNA and NF-κB was evidenced by electrophoretic mobility shift assay. Moreover, similar VB-ODNs designed for three other TFs also inhibit their downstream gene expression but not that of themselves. Our study provides a new design of decoy for blocking TF activity.« less

Capacity of tumor necrosis factor to augment lymphocyte-mediated tumor cell lysis of malignant mesothelioma

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

Bowman, R.V.; Manning, L.S.; Davis, M.R.

1991-01-01

Recombinant human tumor necrosis factor (rHuTNF) was evaluated both for direct anti-tumor action against human malignant mesothelioma and for its capacity to augment the generation and lytic phases of lymphocyte-mediated cytotoxicity against this tumor. rHuTNF was directly toxic by MTT assay to one of two mesothelioma cell lines evaluated, but had no effect on susceptibility to subsequent lymphocyte-mediated lysis of either line. TNF alone was incapable of generating anti-mesothelioma lymphokine-activated killer cell (LAK) activity. Furthermore, it did not augment the degree or LAK activity produced by submaximal interleukin-2 (IL-2) concentrations nor did it augment lysis of mesothelioma cells by naturalmore » killer (NK) or LAK effector cells during the 4-hr 51chromium release cytolytic reaction. The studies also suggest that mesothelioma targets are less responsive to TNF plus submaximal IL-2 concentrations than the standard LAK sensitive target Daudi, raising the possibility that intermediate LAK sensitive tumors such as mesothelioma may require separate and specific evaluation in immunomodulation studies. This in vitro study indicates that use of low-dose rHuTNF and IL-2 is unlikely to be an effective substitute for high-dose IL-2 in generation and maintenance of LAK activity in adoptive immunotherapy for mesothelioma.« less

Human Augmentics: augmenting human evolution.

PubMed

Kenyon, Robert V; Leigh, Jason

2011-01-01

Human Augmentics (HA) refers to technologies for expanding the capabilities, and characteristics of humans. One can think of Human Augmentics as the driving force in the non-biological evolution of humans. HA devices will provide technology to compensate for human biological limitations either natural or acquired. The strengths of HA lie in its applicability to all humans. Its interoperability enables the formation of ecosystems whereby augmented humans can draw from other realms such as "the Cloud" and other augmented humans for strength. The exponential growth in new technologies portends such a system but must be designed for interaction through the use of open-standards and open-APIs for system development. We discuss the conditions needed for HA to flourish with an emphasis on devices that provide non-biological rehabilitation.

Augmented Reality Based Doppler Lidar Data Visualization: Promises and Challenges

NASA Astrophysics Data System (ADS)

Cherukuru, N. W.; Calhoun, R.

2016-06-01

Augmented reality (AR) is a technology in which the enables the user to view virtual content as if it existed in real world. We are exploring the possibility of using this technology to view radial velocities or processed wind vectors from a Doppler wind lidar, thus giving the user an ability to see the wind in a literal sense. This approach could find possible applications in aviation safety, atmospheric data visualization as well as in weather education and public outreach. As a proof of concept, we used the lidar data from a recent field campaign and developed a smartphone application to view the lidar scan in augmented reality. In this paper, we give a brief methodology of this feasibility study, present the challenges and promises of using AR technology in conjunction with Doppler wind lidars.

Anomalous Fluctuations in Autoregressive Models with Long-Term Memory

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Honjo, Haruo

2015-10-01

An autoregressive model with a power-law type memory kernel is studied as a stochastic process that exhibits a self-affine-fractal-like behavior for a small time scale. We find numerically that the root-mean-square displacement Δ(m) for the time interval m increases with a power law as mα with α < 1/2 for small m but saturates at sufficiently large m. The exponent α changes with the power exponent of the memory kernel.

Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

NASA Astrophysics Data System (ADS)

Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

2018-06-01

Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

Diffusible signal factor-repressed extracellular traits enable attachment of Xylella fastidiosa to insect vectors and transmission.

PubMed

Baccari, Clelia; Killiny, Nabil; Ionescu, Michael; Almeida, Rodrigo P P; Lindow, Steven E

2014-01-01

The hypothesis that a wild-type strain of Xylella fastidiosa would restore the ability of rpfF mutants blocked in diffusible signal factor production to be transmitted to new grape plants by the sharpshooter vector Graphocephala atropunctata was tested. While the rpfF mutant was very poorly transmitted by vectors irrespective of whether they had also fed on plants infected with the wild-type strain, wild-type strains were not efficiently transmitted if vectors had fed on plants infected with the rpfF mutant. About 100-fewer cells of a wild-type strain attached to wings of a vector when suspended in xylem sap from plants infected with an rpfF mutant than in sap from uninfected grapes. The frequency of transmission of cells suspended in sap from plants that were infected by the rpfF mutant was also reduced over threefold. Wild-type cells suspended in a culture supernatant of an rpfF mutant also exhibited 10-fold less adherence to wings than when suspended in uninoculated culture media. A factor released into the xylem by rpfF mutants, and to a lesser extent by the wild-type strain, thus inhibits their attachment to, and thus transmission by, sharpshooter vectors and may also enable them to move more readily through host plants.

Augmentation method of XPNAV in Mars orbit based on Phobos and Deimos observations

NASA Astrophysics Data System (ADS)

Rong, Jiao; Luping, Xu; Zhang, Hua; Cong, Li

2016-11-01

Autonomous navigation for Mars probe spacecraft is required to reduce the operation costs and enhance the navigation performance in the future. X-ray pulsar-based navigation (XPNAV) is a potential candidate to meet this requirement. This paper addresses the use of the Mars' natural satellites to improve XPNAV for Mars probe spacecraft. Two observation variables of the field angle and natural satellites' direction vectors of Mars are added into the XPNAV positioning system. The measurement model of field angle and direction vectors is formulated by processing satellite image of Mars obtained from optical camera. This measurement model is integrated into the spacecraft orbit dynamics to build the filter model. In order to estimate position and velocity error of the spacecraft and reduce the impact of the system noise on navigation precision, an adaptive divided difference filter (ADDF) is applied. Numerical simulation results demonstrate that the performance of ADDF is better than Unscented Kalman Filter (UKF) DDF and EKF. In view of the invisibility of Mars' natural satellites in some cases, a visibility condition analysis is given and the augmented XPNAV in a different visibility condition is numerically simulated. The simulation results show that the navigation precision is evidently improved by using the augmented XPNAV based on the field angle and natural satellites' direction vectors of Mars in a comparison with the conventional XPNAV.

[Sinus floor elevation and augmentation. Evidence-based analysis of prognosis and risk factors].

PubMed

Strietzel, F P

2004-03-01

It was the aim of this investigation to analyze evidence of prognosis, predictors, and risk factors concerning sinus floor elevation and augmentation (SFEA). A MEDLINE search was performed to analyze the literature published between 1990 and 2002, limited to keywords ("sinus floor elevation and dental implants", "complications", "success"), study type (randomized as well as clinical prospective studies, retrospective studies, reviews), and language (German or English). Of 229 publications identified, 72 met the inclusion criteria (22 prospective and 47 retrospective studies, 3 reviews). Considering the augmentation material [autogenous bone (AB), bone substitution materials (BSM), and combinations of AB and BSM], the frequency of implant loss was not significantly different (AB 8%, BSM 9%, AB + BSM 5%, p>0.09) after an observation period of 2-4 years. The average duration of the healing period was 6 months (AB) and 8 months (BSM) with simultaneous SFEA and implantation and 6-7 months (AB and BSM) for the staged approach after an average healing period of 6 months for the augmentation materials. Frequency of implant loss was not different between simultaneous and staged approaches (7-8%). Postoperative sinusitis occurred in 3-8% of the cases. Smoking, positive sinusitis history, obstructive pathoses of the nose and ostium, allergic rhino-pathoses, use of short implants (<13 mm), treatment of edentulous maxilla compared to partially edentulous maxilla, bruxism, and uncontrolled early loading of implants were identified as predictors for complications. Presupposing proper consideration of indications, SFEA should be considered as an evidence-based and clinically established method for implant prosthetic rehabilitation of the atrophic posterior maxilla with an overall cumulative survival rate of 90% within an average observation period of 4 years.

Environmental and biological factors influencing Culex pipiens quinquefasciatus (Diptera: Culicidae) vector competence for West Nile Virus.

PubMed

Richards, Stephanie L; Lord, Cynthia C; Pesko, Kendra N; Tabachnick, Walter J

2010-07-01

Interactions between environmental and biological factors affect the vector competence of Culex pipiens quinquefasciatus for West Nile virus. Three age cohorts from two Cx. p. quinquefasciatus colonies were fed blood containing a low- or high-virus dose, and each group was held at two different extrinsic incubation temperatures (EIT) for 13 days. The colonies differed in the way that they responded to the effects of the environment on vector competence. The effects of mosquito age on aspects of vector competence were dependent on the EIT and dose, and they changed depending on the colony. Complex interactions must be considered in laboratory studies of vector competence, because the extent of the genetic and environmental variation controlling vector competence in nature is largely unknown. Differences in the environmental (EIT and dose) and biological (mosquito age and colony) effects from previous studies of Cx. p. quinquefasciatus vector competence for St. Louis encephalitis virus are discussed.

Towards Pervasive Augmented Reality: Context-Awareness in Augmented Reality.

PubMed

Grubert, Jens; Langlotz, Tobias; Zollmann, Stefanie; Regenbrecht, Holger

2017-06-01

Augmented Reality is a technique that enables users to interact with their physical environment through the overlay of digital information. While being researched for decades, more recently, Augmented Reality moved out of the research labs and into the field. While most of the applications are used sporadically and for one particular task only, current and future scenarios will provide a continuous and multi-purpose user experience. Therefore, in this paper, we present the concept of Pervasive Augmented Reality, aiming to provide such an experience by sensing the user's current context and adapting the AR system based on the changing requirements and constraints. We present a taxonomy for Pervasive Augmented Reality and context-aware Augmented Reality, which classifies context sources and context targets relevant for implementing such a context-aware, continuous Augmented Reality experience. We further summarize existing approaches that contribute towards Pervasive Augmented Reality. Based our taxonomy and survey, we identify challenges for future research directions in Pervasive Augmented Reality.

K π vector form factor, dispersive constraints and τ→ ν τ K π decays

NASA Astrophysics Data System (ADS)

Boito, Diogo R.; Escribano, Rafel; Jamin, Matthias

2009-02-01

Recent experimental data for the differential decay distribution of the decay τ -→ ν τ K S π - by the Belle collaboration are described by a theoretical model which is composed of the contributing vector and scalar form factors F {+/ K π }( s) and F {0/ K π }( s). Both form factors are constructed such that they fulfil constraints posed by analyticity and unitarity. A good description of the experimental measurement is achieved by incorporating two vector resonances and working with a three-times-subtracted dispersion relation in order to suppress higher-energy contributions. The resonance parameters of the charged K *(892) meson, defined as the pole of F {+/ K π }( s) in the complex s-plane, can be extracted, with the result M_{K^{*}}=892.0± 0.9 MeV and \\varGamma_{K^{*}}=46.2± 0.4 MeV . Finally, employing a three-times-subtracted dispersion relation allows one to determine the slope and curvature parameters λ'+=(24.7±0.8)×10-3 and λ″+=(12.0±0.2)×10-4 of the vector form factor F {+/ K π }( s) directly from the data.

Medium- and Long-term Prediction of LOD Change with the Leap-step Autoregressive Model

NASA Astrophysics Data System (ADS)

Liu, Q. B.; Wang, Q. J.; Lei, M. F.

2015-09-01

It is known that the accuracies of medium- and long-term prediction of changes of length of day (LOD) based on the combined least-square and autoregressive (LS+AR) decrease gradually. The leap-step autoregressive (LSAR) model is more accurate and stable in medium- and long-term prediction, therefore it is used to forecast the LOD changes in this work. Then the LOD series from EOP 08 C04 provided by IERS (International Earth Rotation and Reference Systems Service) is used to compare the effectiveness of the LSAR and traditional AR methods. The predicted series resulted from the two models show that the prediction accuracy with the LSAR model is better than that from AR model in medium- and long-term prediction.

Time to burn: Modeling wildland arson as an autoregressive crime function

Treesearch

Jeffrey P. Prestemon; David T. Butry

2005-01-01

Six Poisson autoregressive models of order p [PAR(p)] of daily wildland arson ignition counts are estimated for five locations in Florida (1994-2001). In addition, a fixed effects time-series Poisson model of annual arson counts is estimated for all Florida counties (1995-2001). PAR(p) model estimates reveal highly significant arson ignition autocorrelation, lasting up...

Evolving lessons on nanomaterial-coated viral vectors for local and systemic gene therapy

PubMed Central

Kasala, Dayananda; Yoon, A-Rum; Hong, Jinwoo; Kim, Sung Wan; Yun, Chae-Ok

2016-01-01

Viral vectors are promising gene carriers for cancer therapy. However, virus-mediated gene therapies have demonstrated insufficient therapeutic efficacy in clinical trials due to rapid dissemination to nontarget tissues and to the immunogenicity of viral vectors, resulting in poor retention at the disease locus and induction of adverse inflammatory responses in patients. Further, the limited tropism of viral vectors prevents efficient gene delivery to target tissues. In this regard, modification of the viral surface with nanomaterials is a promising strategy to augment vector accumulation at the target tissue, circumvent the host immune response, and avoid nonspecific interactions with the reticuloendothelial system or serum complement. In the present review, we discuss various chemical modification strategies to enhance the therapeutic efficacy of viral vectors delivered either locally or systemically. We conclude by highlighting the salient features of various nanomaterial-coated viral vectors and their prospects and directions for future research. PMID:27348247

The inertial attitude augmentation for ambiguity resolution in SF/SE-GNSS attitude determination.

PubMed

Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping

2014-06-26

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation.

The Inertial Attitude Augmentation for Ambiguity Resolution in SF/SE-GNSS Attitude Determination

PubMed Central

Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping

2014-01-01

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation. PMID:24971472

Computational problems in autoregressive moving average (ARMA) models

NASA Technical Reports Server (NTRS)

Agarwal, G. C.; Goodarzi, S. M.; Oneill, W. D.; Gottlieb, G. L.

1981-01-01

The choice of the sampling interval and the selection of the order of the model in time series analysis are considered. Band limited (up to 15 Hz) random torque perturbations are applied to the human ankle joint. The applied torque input, the angular rotation output, and the electromyographic activity using surface electrodes from the extensor and flexor muscles of the ankle joint are recorded. Autoregressive moving average models are developed. A parameter constraining technique is applied to develop more reliable models. The asymptotic behavior of the system must be taken into account during parameter optimization to develop predictive models.

Augmenting Human Performance in Remotely Piloted Aircraft.

PubMed

Gruenwald, Christina M; Middendorf, Matthew S; Hoepf, Michael R; Galster, Scott M

2018-02-01

An experiment in a program of research supporting the sense-assess-augment (SAA) framework is described. The objective is to use physiological measures to assess operator cognitive workload in remotely piloted aircraft (RPA) operations, and provide augmentation to assist the operator in times of high workload. In previous experiments, physiological measures were identified that demonstrate sensitivity to changes in workload. The current research solely focuses on the augmentation component of the SAA paradigm. This line of research uses a realistic RPA simulation with varying levels of workload. Recruited from the Midwest region were 12 individuals (6 women) to participate in the experiment. The subjects were trained to perform a surveillance task and a tracking task using RPAs. There was also a secondary task in which subjects were required to answer cognitive probes. A within subjects factorial design was employed with three factors per task. Subjective workload estimates were acquired using the NASA-TLX. Performance data were calculated using a composite scoring algorithm. Augmentation significantly improved performance and reduced workload in both tasks. In the surveillance task, augmentation increased performance from 573.78 to 679.04. Likewise, augmentation increased performance in the tracking task from 749.39 to 791.81. Augmentation was more beneficial in high workload conditions than low workload conditions. The increase in performance and decrease in workload associated with augmentation is an important and anticipated finding. This suggests that augmentation should only be provided when it is truly needed, especially if the augmentation requires additional assets and/or resources.Gruenwald CM, Middendorf MS, Hoepf MR, Galster SM. Augmenting human performance in remotely piloted aircraft. Aerosp Med Hum Perform. 2018; 89(2):115-121.

Predicting complications of percutaneous coronary intervention using a novel support vector method.

PubMed

Lee, Gyemin; Gurm, Hitinder S; Syed, Zeeshan

2013-01-01

To explore the feasibility of a novel approach using an augmented one-class learning algorithm to model in-laboratory complications of percutaneous coronary intervention (PCI). Data from the Blue Cross Blue Shield of Michigan Cardiovascular Consortium (BMC2) multicenter registry for the years 2007 and 2008 (n=41 016) were used to train models to predict 13 different in-laboratory PCI complications using a novel one-plus-class support vector machine (OP-SVM) algorithm. The performance of these models in terms of discrimination and calibration was compared to the performance of models trained using the following classification algorithms on BMC2 data from 2009 (n=20 289): logistic regression (LR), one-class support vector machine classification (OC-SVM), and two-class support vector machine classification (TC-SVM). For the OP-SVM and TC-SVM approaches, variants of the algorithms with cost-sensitive weighting were also considered. The OP-SVM algorithm and its cost-sensitive variant achieved the highest area under the receiver operating characteristic curve for the majority of the PCI complications studied (eight cases). Similar improvements were observed for the Hosmer-Lemeshow χ(2) value (seven cases) and the mean cross-entropy error (eight cases). The OP-SVM algorithm based on an augmented one-class learning problem improved discrimination and calibration across different PCI complications relative to LR and traditional support vector machine classification. Such an approach may have value in a broader range of clinical domains.

Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

NASA Astrophysics Data System (ADS)

Nabelek, Daniel P.; Ho, K. C.

2013-06-01

The detection of shallow buried low-metal content objects using ground penetrating radar (GPR) is a challenging task. This is because these targets are right underneath the ground and the ground bounce reflection interferes with their detections. They do not create distinctive hyperbolic signatures as required by most existing GPR detection algorithms due to their special geometric shapes and low metal content. This paper proposes the use of the Autoregressive (AR) modeling method for the detection of these targets. We fit an A-scan of the GPR data to an AR model. It is found that the fitting error will be small when such a target is present and large when it is absent. The ratio of the energy in an Ascan before and after AR model fitting is used as the confidence value for detection. We also apply AR model fitting over scans and utilize the fitting residual energies over several scans to form a feature vector for improving the detections. Using the data collected from a government test site, the proposed method can improve the detection of this kind of targets by 30% compared to the pre-screener, at a false alarm rate of 0.002/m2.

Analysis of the Westland Data Set

NASA Technical Reports Server (NTRS)

Wen, Fang; Willett, Peter; Deb, Somnath

2001-01-01

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Applied Augmented Reality for High Precision Maintenance

NASA Astrophysics Data System (ADS)

Dever, Clark

Augmented Reality had a major consumer breakthrough this year with Pokemon Go. The underlying technologies that made that app a success with gamers can be applied to improve the efficiency and efficacy of workers. This session will explore some of the use cases for augmented reality in an industrial environment. In doing so, the environmental impacts and human factors that must be considered will be explored. Additionally, the sensors, algorithms, and visualization techniques used to realize augmented reality will be discussed. The benefits of augmented reality solutions in industrial environments include automated data recording, improved quality assurance, reduction in training costs and improved mean-time-to-resolution. As technology continues to follow Moore's law, more applications will become feasible as performance-per-dollar increases across all system components.

Vector autoregressive models: A Gini approach

NASA Astrophysics Data System (ADS)

Mussard, Stéphane; Ndiaye, Oumar Hamady

2018-02-01

In this paper, it is proven that the usual VAR models may be performed in the Gini sense, that is, on a ℓ1 metric space. The Gini regression is robust to outliers. As a consequence, when data are contaminated by extreme values, we show that semi-parametric VAR-Gini regressions may be used to obtain robust estimators. The inference about the estimators is made with the ℓ1 norm. Also, impulse response functions and Gini decompositions for prevision errors are introduced. Finally, Granger's causality tests are properly derived based on U-statistics.

Modified Confidence Intervals for the Mean of an Autoregressive Process.

DTIC Science & Technology

1985-08-01

Validity of the method 45 3.6 Theorem 47 4 Derivation of corrections 48 Introduction 48 The zero order pivot 50 4.1 Algorithm 50 CONTENTS The first...of standard confidence intervals. There are several standard methods of setting confidence intervals in simulations, including the regener- ative... method , batch means, and time series methods . We-will focus-s on improved confidence intervals for the mean of an autoregressive process, and as such our

The Bartonella quintana Extracytoplasmic Function Sigma Factor RpoE Has a Role in Bacterial Adaptation to the Arthropod Vector Environment

PubMed Central

Abromaitis, Stephanie

2013-01-01

Bartonella quintana is a vector-borne bacterial pathogen that causes fatal disease in humans. During the infectious cycle, B. quintana transitions from the hemin-restricted human bloodstream to the hemin-rich body louse vector. Because extracytoplasmic function (ECF) sigma factors often regulate adaptation to environmental changes, we hypothesized that a previously unstudied B. quintana ECF sigma factor, RpoE, is involved in the transition from the human host to the body louse vector. The genomic context of B. quintana rpoE identified it as a member of the ECF15 family of sigma factors found only in alphaproteobacteria. ECF15 sigma factors are believed to be the master regulators of the general stress response in alphaproteobacteria. In this study, we examined the B. quintana RpoE response to two stressors that are encountered in the body louse vector environment, a decreased temperature and an increased hemin concentration. We determined that the expression of rpoE is significantly upregulated at the body louse (28°C) versus the human host (37°C) temperature. rpoE expression also was upregulated when B. quintana was exposed to high hemin concentrations. In vitro and in vivo analyses demonstrated that RpoE function is regulated by a mechanism involving the anti-sigma factor NepR and the response regulator PhyR. The ΔrpoE ΔnepR mutant strain of B. quintana established that RpoE-mediated transcription is important in mediating the tolerance of B. quintana to high hemin concentrations. We present the first analysis of an ECF15 sigma factor in a vector-borne human pathogen and conclude that RpoE has a role in the adaptation of B. quintana to the hemin-rich arthropod vector environment. PMID:23564167

On the Stationarity of Multiple Autoregressive Approximants: Theory and Algorithms

DTIC Science & Technology

1976-08-01

a I (3.4) Hannan and Terrell (1972) consider problems of a similar nature. Efficient estimates A(1),... , A(p) , and i of A(1)... ,A(p) and...34Autoregressive model fitting for control, Ann . Inst. Statist. Math., 23, 163-180. Hannan, E. J. (1970), Multiple Time Series, New York, John Wiley...Hannan, E. J. and Terrell , R. D. (1972), "Time series regression with linear constraints, " International Economic Review, 13, 189-200. Masani, P

Dengue Vectors and their Spatial Distribution

PubMed Central

Higa, Yukiko

2011-01-01

The distribution of dengue vectors, Ae. aegypti and Ae. albopictus, is affected by climatic factors. In addition, since their life cycles are well adapted to the human environment, environmental changes resulting from human activity such as urbanization exert a great impact on vector distribution. The different responses of Ae. aegypti and Ae albopictus to various environments result in a difference in spatial distribution along north-south and urban-rural gradients, and between the indoors and outdoors. In the north-south gradient, climate associated with survival is an important factor in spatial distribution. In the urban-rural gradient, different distribution reflects a difference in adult niches and is modified by geographic and human factors. The direct response of the two species to the environment around houses is related to different spatial distribution indoors and outdoors. Dengue viruses circulate mainly between human and vector mosquitoes, and the vector presence is a limiting factor of transmission. Therefore, spatial distribution of dengue vectors is a significant concern in the epidemiology of the disease. Current technologies such as GIS, satellite imagery and statistical models allow researchers to predict the spatial distribution of vectors in the changing environment. Although it is difficult to confirm the actual effect of environmental and climate changes on vector abundance and vector-borne diseases, environmental changes caused by humans and human behavioral changes due to climate change can be expected to exert an impact on dengue vectors. Longitudinal monitoring of dengue vectors and viruses is therefore necessary. PMID:22500133

Predicting complications of percutaneous coronary intervention using a novel support vector method

PubMed Central

Lee, Gyemin; Gurm, Hitinder S; Syed, Zeeshan

2013-01-01

Objective To explore the feasibility of a novel approach using an augmented one-class learning algorithm to model in-laboratory complications of percutaneous coronary intervention (PCI). Materials and methods Data from the Blue Cross Blue Shield of Michigan Cardiovascular Consortium (BMC2) multicenter registry for the years 2007 and 2008 (n=41 016) were used to train models to predict 13 different in-laboratory PCI complications using a novel one-plus-class support vector machine (OP-SVM) algorithm. The performance of these models in terms of discrimination and calibration was compared to the performance of models trained using the following classification algorithms on BMC2 data from 2009 (n=20 289): logistic regression (LR), one-class support vector machine classification (OC-SVM), and two-class support vector machine classification (TC-SVM). For the OP-SVM and TC-SVM approaches, variants of the algorithms with cost-sensitive weighting were also considered. Results The OP-SVM algorithm and its cost-sensitive variant achieved the highest area under the receiver operating characteristic curve for the majority of the PCI complications studied (eight cases). Similar improvements were observed for the Hosmer–Lemeshow χ2 value (seven cases) and the mean cross-entropy error (eight cases). Conclusions The OP-SVM algorithm based on an augmented one-class learning problem improved discrimination and calibration across different PCI complications relative to LR and traditional support vector machine classification. Such an approach may have value in a broader range of clinical domains. PMID:23599229

Augmented reality three-dimensional object visualization and recognition with axially distributed sensing.

PubMed

Markman, Adam; Shen, Xin; Hua, Hong; Javidi, Bahram

2016-01-15

An augmented reality (AR) smartglass display combines real-world scenes with digital information enabling the rapid growth of AR-based applications. We present an augmented reality-based approach for three-dimensional (3D) optical visualization and object recognition using axially distributed sensing (ADS). For object recognition, the 3D scene is reconstructed, and feature extraction is performed by calculating the histogram of oriented gradients (HOG) of a sliding window. A support vector machine (SVM) is then used for classification. Once an object has been identified, the 3D reconstructed scene with the detected object is optically displayed in the smartglasses allowing the user to see the object, remove partial occlusions of the object, and provide critical information about the object such as 3D coordinates, which are not possible with conventional AR devices. To the best of our knowledge, this is the first report on combining axially distributed sensing with 3D object visualization and recognition for applications to augmented reality. The proposed approach can have benefits for many applications, including medical, military, transportation, and manufacturing.

Three-dimensional imaging, an important factor of decision in breast augmentation.

PubMed

de Runz, A; Boccara, D; Bertheuil, N; Claudot, F; Brix, M; Simon, E

2018-04-01

Since the beginning of the 21st century, three-dimensional imaging systems have been used more often in plastic surgery, especially during preoperative planning for breast surgery and to simulate the postoperative appearance of the implant in the patient's body. The main objective of this study is to assess the patients' attitudes regarding 3D simulation for breast augmentation. A study was conducted, which included women who were operated on for primary breast augmentation. During the consultation, a three-dimensional simulation with Crisalix was done and different sized implants were fitted in the bra. Thirty-eight women were included. The median age was 29.4, and the median prosthesis volume was 310mL. The median rank given regarding the final result was 9 (IQR: 8-9). Ninety percent of patients agreed (66% absolutely agreed, and 24% partially agreed) that the final product after breast augmentations was similar to the Crisalix simulation. Ninety-three percent of the patients believed that the three-dimensional simulation helped them choose their prosthesis (61% a lot and 32% a little). After envisaging a breast enlargement, patients estimated that the Crisalix system was absolutely necessary (21%), very useful (32%), useful (45%), or unnecessary (3%). Regarding prosthesis choice, an equal number of women preferred the 3D simulation (19 patients) as preferred using different sizes of implants in the bra (19 patients). The present study demonstrated that 3D simulation is actually useful for patients in order to envisage a breast augmentation. But it should be used as a complement to the classic method of trying different sized breast implants in the bra. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

NASA Technical Reports Server (NTRS)

Grass, David; Jasinski, Michael F.; Govere, John

2003-01-01

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

PubMed Central

Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

2017-01-01

Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics. PMID:28604582

Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

NASA Astrophysics Data System (ADS)

Wang, Qijie

2015-08-01

The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

Virulence Factors of Geminivirus Interact with MYC2 to Subvert Plant Resistance and Promote Vector Performance[C][W

PubMed Central

Li, Ran; Weldegergis, Berhane T.; Li, Jie; Jung, Choonkyun; Qu, Jing; Sun, Yanwei; Qian, Hongmei; Tee, ChuanSia; van Loon, Joop J.A.; Dicke, Marcel; Chua, Nam-Hai; Liu, Shu-Sheng

2014-01-01

A pathogen may cause infected plants to promote the performance of its transmitting vector, which accelerates the spread of the pathogen. This positive effect of a pathogen on its vector via their shared host plant is termed indirect mutualism. For example, terpene biosynthesis is suppressed in begomovirus-infected plants, leading to reduced plant resistance and enhanced performance of the whiteflies (Bemisia tabaci) that transmit these viruses. Although begomovirus-whitefly mutualism has been known, the underlying mechanism is still elusive. Here, we identified βC1 of Tomato yellow leaf curl China virus, a monopartite begomovirus, as the viral genetic factor that suppresses plant terpene biosynthesis. βC1 directly interacts with the basic helix-loop-helix transcription factor MYC2 to compromise the activation of MYC2-regulated terpene synthase genes, thereby reducing whitefly resistance. MYC2 associates with the bipartite begomoviral protein BV1, suggesting that MYC2 is an evolutionarily conserved target of begomoviruses for the suppression of terpene-based resistance and the promotion of vector performance. Our findings describe how this viral pathogen regulates host plant metabolism to establish mutualism with its insect vector. PMID:25490915

Vertical ridge augmentation using an equine bone and collagen block infused with recombinant human platelet-derived growth factor-BB: a randomized single-masked histologic study in non-human primates.

PubMed

Nevins, Myron; Al Hezaimi, Khalid; Schupbach, Peter; Karimbux, Nadeem; Kim, David M

2012-07-01

This study tests the effectiveness of hydroxyapatite and collagen bone blocks of equine origin (eHAC), infused with recombinant human platelet-derived growth factor-BB (rhPDGF-BB), to augment localized posterior mandibular defects in non-human primates (Papio hamadryas). Bilateral critical-sized defects simulating severe atrophy were created at the time of the posterior teeth extraction. Test and control blocks (without growth factor) were randomly grafted into the respective sites in each non-human primate. All sites exhibited vertical ridge augmentation, with physiologic hard- and soft-tissue integration of the blocks when clinical and histologic examinations were done at 4 months after the vertical ridge augmentation procedure. There was a clear, although non-significant, tendency to increased regeneration in the test sites. As in the first two preclinical studies in this series using canines, experimental eHAC blocks infused with rhPDGF-BB proved to be a predictable and technically viable method to predictably regenerate bone and soft tissue in critical-sized defects. This investigation supplies additional evidence that eHAC blocks infused with rhPDGF-BB growth factor is a predictable and technically feasible option for vertical augmentation of severely resorbed ridges.

Maximum likelihood estimation for periodic autoregressive moving average models

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

A useful class of models for seasonal time series that cannot be filtered or standardized to achieve second-order stationarity is that of periodic autoregressive moving average (PARMA) models, which are extensions of ARMA models that allow periodic (seasonal) parameters. An approximation to the exact likelihood for Gaussian PARMA processes is developed, and a straightforward algorithm for its maximization is presented. The algorithm is tested on several periodic ARMA(1, 1) models through simulation studies and is compared to moment estimation via the seasonal Yule-Walker equations. Applicability of the technique is demonstrated through an analysis of a seasonal stream-flow series from the Rio Caroni River in Venezuela.

Secondary Breast Augmentation.

PubMed

Brown, Mitchell H; Somogyi, Ron B; Aggarwal, Shagun

2016-07-01

After studying this article, the participant should be able to: 1. Assess common clinical problems in the secondary breast augmentation patient. 2. Describe a treatment plan to correct the most common complications of breast augmentation. 3. Provide surgical and nonsurgical options for managing complications of breast augmentation. 4. Decrease the incidence of future complications through accurate assessment, preoperative planning, and precise surgical technique. Breast augmentation has been increasing steadily in popularity over the past three decades. Many of these patients present with secondary problems or complications following their primary breast augmentation. Two of the most common complications are capsular contracture and implant malposition. Familiarity and comfort with the assessment and management of these complications is necessary for all plastic surgeons. An up-to-date understanding of current devices and techniques may decrease the need to manage future complications from the current cohort of breast augmentation patients.

Chin augmentation

MedlinePlus

... page: //medlineplus.gov/ency/article/002986.htm Chin augmentation To use the sharing features on this page, please enable JavaScript. Chin augmentation is surgery to reshape or enhance the size ...

Vector Autoregressive Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example.

PubMed

Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M

Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display interrelated vital sign changes during situations of physiological stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. The purpose of this article is to illustrate the development of patient-specific VAR models using vital sign time series data in a sample of acutely ill, monitored, step-down unit patients and determine their Granger causal dynamics prior to onset of an incident CRI. CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40-140/minute, RR = 8-36/minute, SpO2 < 85%) and persisting for 3 minutes within a 5-minute moving window (60% of the duration of the window). A 6-hour time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity, (b) appropriate lag was determined using a lag-length selection criteria, (c) the VAR model was constructed, (d) residual autocorrelation was assessed with the Lagrange Multiplier test, (e) stability of the VAR system was checked, and (f) Granger causality was evaluated in the final stable model. The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%; i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing changes in HR occurred with equal frequency (18

Bone augmentation using a highly porous PLGA/β-TCP scaffold containing fibroblast growth factor-2.

PubMed

Yoshida, T; Miyaji, H; Otani, K; Inoue, K; Nakane, K; Nishimura, H; Ibara, A; Shimada, A; Ogawa, K; Nishida, E; Sugaya, T; Sun, L; Fugetsu, B; Kawanami, M

2015-04-01

Beta-tricalcium phosphate (β-TCP), a bio-absorbable ceramic, facilitates bone conductivity. We constructed a highly porous three-dimensional scaffold, using β-TCP, for bone tissue engineering and coated it with co-poly lactic acid/glycolic acid (PLGA) to improve the mechanical strength and biological performance. The aim of this study was to examine the effect of implantation of the PLGA/β-TCP scaffold loaded with fibroblast growth factor-2 (FGF-2) on bone augmentation. The β-TCP scaffold was fabricated by the replica method using polyurethane foam, then coated with PLGA. The PLGA/β-TCP scaffold was characterized by scanning electron miscroscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction, compressive testing, cell culture and a subcutaneous implant test. Subsequently, a bone-forming test was performed using 52 rats. The β-TCP scaffold, PLGA-coated scaffold, and β-TCP and PLGA-coated scaffolds loaded with FGF-2, were implanted into rat cranial bone. Histological observations were made at 10 and 35 d postsurgery. SEM and TEM observations showed a thin PLGA layer on the β-TCP particles after coating. High porosity (> 90%) of the scaffold was exhibited after PLGA coating, and the compressive strength of the PLGA/β-TCP scaffold was six-fold greater than that of the noncoated scaffold. Good biocompatibility of the PLGA/β-TCP scaffold was found in the culture and implant tests. Histological samples obtained following implantation of PLGA/β-TCP scaffold loaded with FGF-2 showed significant bone augmentation. The PLGA coating improved the mechanical strength of β-TCP scaffolds while maintaining high porosity and tissue compatibility. PLGA/β-TCP scaffolds, in combination with FGF-2, are bioeffective for bone augmentation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

TaiWan Ionospheric Model (TWIM) prediction based on time series autoregressive analysis

NASA Astrophysics Data System (ADS)

Tsai, L. C.; Macalalad, Ernest P.; Liu, C. H.

2014-10-01

As described in a previous paper, a three-dimensional ionospheric electron density (Ne) model has been constructed from vertical Ne profiles retrieved from the FormoSat3/Constellation Observing System for Meteorology, Ionosphere, and Climate GPS radio occultation measurements and worldwide ionosonde foF2 and foE data and named the TaiWan Ionospheric Model (TWIM). The TWIM exhibits vertically fitted α-Chapman-type layers with distinct F2, F1, E, and D layers, and surface spherical harmonic approaches for the fitted layer parameters including peak density, peak density height, and scale height. To improve the TWIM into a real-time model, we have developed a time series autoregressive model to forecast short-term TWIM coefficients. The time series of TWIM coefficients are considered as realizations of stationary stochastic processes within a processing window of 30 days. These autocorrelation coefficients are used to derive the autoregressive parameters and then forecast the TWIM coefficients, based on the least squares method and Lagrange multiplier technique. The forecast root-mean-square relative TWIM coefficient errors are generally <30% for 1 day predictions. The forecast TWIM values of foE and foF2 values are also compared and evaluated using worldwide ionosonde data.

Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology

NASA Astrophysics Data System (ADS)

Gao, Wei; Zhu, Linli; Wang, Kaiyun

2015-12-01

Ontology, a model of knowledge representation and storage, has had extensive applications in pharmaceutics, social science, chemistry and biology. In the age of “big data”, the constructed concepts are often represented as higher-dimensional data by scholars, and thus the sparse learning techniques are introduced into ontology algorithms. In this paper, based on the alternating direction augmented Lagrangian method, we present an ontology optimization algorithm for ontological sparse vector learning, and a fast version of such ontology technologies. The optimal sparse vector is obtained by an iterative procedure, and the ontology function is then obtained from the sparse vector. Four simulation experiments show that our ontological sparse vector learning model has a higher precision ratio on plant ontology, humanoid robotics ontology, biology ontology and physics education ontology data for similarity measuring and ontology mapping applications.

Noise-induced hearing loss and associated factors among vector control workers in a Malaysian state.

PubMed

Masilamani, Retneswari; Rasib, Abdul; Darus, Azlan; Ting, Anselm Su

2014-11-01

This study aims to determine the prevalence and associated factors of noise-induced hearing loss (NIHL) among vector control workers in the state of Negeri Sembilan, Malaysia. This was an analytical cross-sectional study conducted on 181 vector control workers who were working in district health offices in a state in Malaysia. Data were collected using a self-administered questionnaire and audiometry. Prevalence of NIHL was 26% among this group of workers. NIHL was significantly associated with the age-group of 40 years and older, length of service of 10 or more years, current occupational noise exposure, listening to loud music, history of firearms use, and history of mumps/measles infection. Following logistic regression, age of more than 40 years and noise exposure in current occupation were associated with NIHL with an odds ratio of 3.45 (95% confidence interval = 1.68-7.07) and 6.87 (95% confidence interval = 1.54-30.69), respectively, among this group of vector control workers. © 2012 APJPH.

A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations.

PubMed

Eikenberry, Steffen E; Marmarelis, Vasilis Z

2013-02-01

We propose a new variant of Volterra-type model with a nonlinear auto-regressive (NAR) component that is a suitable framework for describing the process of AP generation by the neuron membrane potential, and we apply it to input-output data generated by the Hodgkin-Huxley (H-H) equations. Volterra models use a functional series expansion to describe the input-output relation for most nonlinear dynamic systems, and are applicable to a wide range of physiologic systems. It is difficult, however, to apply the Volterra methodology to the H-H model because is characterized by distinct subthreshold and suprathreshold dynamics. When threshold is crossed, an autonomous action potential (AP) is generated, the output becomes temporarily decoupled from the input, and the standard Volterra model fails. Therefore, in our framework, whenever membrane potential exceeds some threshold, it is taken as a second input to a dual-input Volterra model. This model correctly predicts membrane voltage deflection both within the subthreshold region and during APs. Moreover, the model naturally generates a post-AP afterpotential and refractory period. It is known that the H-H model converges to a limit cycle in response to a constant current injection. This behavior is correctly predicted by the proposed model, while the standard Volterra model is incapable of generating such limit cycle behavior. The inclusion of cross-kernels, which describe the nonlinear interactions between the exogenous and autoregressive inputs, is found to be absolutely necessary. The proposed model is general, non-parametric, and data-derived.

Light scattering of rectangular slot antennas: parallel magnetic vector vs perpendicular electric vector

NASA Astrophysics Data System (ADS)

Lee, Dukhyung; Kim, Dai-Sik

2016-01-01

We study light scattering off rectangular slot nano antennas on a metal film varying incident polarization and incident angle, to examine which field vector of light is more important: electric vector perpendicular to, versus magnetic vector parallel to the long axis of the rectangle. While vector Babinet’s principle would prefer magnetic field along the long axis for optimizing slot antenna function, convention and intuition most often refer to the electric field perpendicular to it. Here, we demonstrate experimentally that in accordance with vector Babinet’s principle, the incident magnetic vector parallel to the long axis is the dominant component, with the perpendicular incident electric field making a small contribution of the factor of 1/|ε|, the reciprocal of the absolute value of the dielectric constant of the metal, owing to the non-perfectness of metals at optical frequencies.

Substitution of blood coagulation factor X-binding to Ad5 by position-specific PEGylation: Preventing vector clearance and preserving infectivity.

PubMed

Krutzke, L; Prill, J M; Engler, T; Schmidt, C Q; Xu, Z; Byrnes, A P; Simmet, T; Kreppel, F

2016-08-10

The biodistribution of adenovirus type 5 (Ad5) vector particles is heavily influenced by interaction of the particles with plasma proteins, including coagulation factor X (FX), which binds specifically to the major Ad5 capsid protein hexon. FX mediates hepatocyte transduction by intravenously-injected Ad5 vectors and shields vector particles from neutralization by natural antibodies and complement. In mice, mutant Ad5 vectors that are ablated for FX-binding become detargeted from hepatocytes, which is desirable for certain applications, but unfortunately such FX-nonbinding vectors also become sensitive to neutralization by mouse plasma proteins. To improve the properties of Ad5 vectors for systemic delivery, we developed a strategy to replace the natural FX shield by a site-specific chemical polyethylene glycol shield. Coupling of polyethylene glycol to a specific site in hexon hypervariable region 1 yielded vector particles that were protected from neutralization by natural antibodies and complement although they were unable to bind FX. These vector particles evaded macrophages in vitro and showed significantly improved pharmacokinetics and hepatocyte transduction in vivo. Thus, site-specific shielding of Ad5 vectors with polyethylene glycol rendered vectors FX-independent and greatly improved their properties for systemic gene therapy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Augmentation of poly(ADP-ribose) polymerase-dependent neuronal cell death by acidosis.

PubMed

Zhang, Jian; Li, Xiaoling; Kwansa, Herman; Kim, Yun Tai; Yi, Liye; Hong, Gina; Andrabi, Shaida A; Dawson, Valina L; Dawson, Ted M; Koehler, Raymond C; Yang, Zeng-Jin

2017-06-01

Tissue acidosis is a key component of cerebral ischemic injury, but its influence on cell death signaling pathways is not well defined. One such pathway is parthanatos, in which oxidative damage to DNA results in activation of poly(ADP-ribose) polymerase and generation of poly(ADP-ribose) polymers that trigger release of mitochondrial apoptosis-inducing factor. In primary neuronal cultures, we first investigated whether acidosis per sé is capable of augmenting parthanatos signaling initiated pharmacologically with the DNA alkylating agent, N-methyl- N'-nitro- N-nitrosoguanidine. Exposure of neurons to medium at pH 6.2 for 4 h after N-methyl- N'-nitro- N-nitrosoguanidine washout increased intracellular calcium and augmented the N-methyl- N'-nitro- N-nitrosoguanidine-evoked increase in poly(ADP-ribose) polymers, nuclear apoptosis-inducing factor , and cell death. The augmented nuclear apoptosis-inducing factor and cell death were blocked by the acid-sensitive ion channel-1a inhibitor, psalmotoxin. In vivo, acute hyperglycemia during transient focal cerebral ischemia augmented tissue acidosis, poly(ADP-ribose) polymers formation, and nuclear apoptosis-inducing factor , which was attenuated by a poly(ADP-ribose) polymerase inhibitor. Infarct volume from hyperglycemic ischemia was decreased in poly(ADP-ribose) polymerase 1-null mice. Collectively, these results demonstrate that acidosis can directly amplify neuronal parthanatos in the absence of ischemia through acid-sensitive ion channel-1a . The results further support parthanatos as one of the mechanisms by which ischemia-associated tissue acidosis augments cell death.

Adeno-Associated Viral Vector (Serotype 2)-Nerve Growth Factor for Patients With Alzheimer Disease: A Randomized Clinical Trial.

PubMed

Rafii, Michael S; Tuszynski, Mark H; Thomas, Ronald G; Barba, David; Brewer, James B; Rissman, Robert A; Siffert, Joao; Aisen, Paul S

2018-03-26

Nerve growth factor (NGF) is an endogenous neurotrophic factor that prevents the death and augments the functional state of cholinergic neurons of the basal forebrain, a cell population that undergoes extensive degeneration in Alzheimer disease (AD). To determine whether stereotactically guided intracerebral injections of adeno-associated viral vector (serotype 2)-nerve growth factor (AAV2-NGF) are well tolerated and exhibit preliminary evidence of impact on cognitive decline in mild to moderate AD-associated dementia. In a multicenter phase 2 trial, 49 participants with mild to moderate AD were randomly assigned in a 1:1 ratio to receive stereotactically guided intracerebral injections of AAV2-NGF or sham surgery. Participants were enrolled between November 2009 and December 2012. Analyses began in February 2015. The study was conducted at 10 US academic medical centers. Eligibility required a diagnosis of mild to moderate dementia due to AD and individuals aged 55 to 80 years. A total of 39 participants did not pass screening; the most common reason was Mini-Mental State Examination scores below cutoff. Analyses were intention-to-treat. Stereotactically guided intracerebral injections of AAV2-NGF into the nucleus basalis of Meynert of each hemisphere or sham surgery. Change from baseline on the Alzheimer Disease Assessment Scale-cognitive subscale at month 24. Among 49 participants, 21 (43%) were women, 42 (86%) self-identified as white, and the mean (SD) age was 68 (6.4) years. AAV2-NGF was safe and well-tolerated through 24 months. No significant difference was noted between the treatment group and placebo on the primary outcome measure, the Alzheimer Disease Assessment Scale-cognitive subscale (mean [SD] score, 14.52 [4.66] vs 9.11 [4.65], P = .17). This multicenter randomized clinical trial demonstrated the feasibility of sham-surgery-controlled stereotactic gene delivery studies in patients with AD. AAV2-NGF delivery was well-tolerated but did not

A Determinate Model of Thrust-Augmenting Ejectors

NASA Astrophysics Data System (ADS)

Whitley, N.; Krothapalli, A.; van Dommelen, L.

1996-01-01

A theoretical analysis of the compressible flow through a constant-area jet-engine ejector in which a primary jet mixes with ambient fluid from a uniform free stream is pursued. The problem is reduced to a determinate mathematical one by prescribing the ratios of stagnation properties between the primary and secondary flows. For some selections of properties and parameters more than one solution is possible and the meaning of these solutions is discussed by means of asymptotic expansions. Our results further show that while under stationary conditions the thrust-augmentation ratio assumes a value of 2 in the large area-ratio limit, for a free-stream Mach number greater than 0.6 very little thrust augmentation is left. Due to the assumptions made, the analysis provides idealized values for the thrust-augmentation ratio and the mass flux entrainment factor.

Asymptotically stable phase synchronization revealed by autoregressive circle maps

NASA Astrophysics Data System (ADS)

Drepper, F. R.

2000-11-01

A specially designed of nonlinear time series analysis is introduced based on phases, which are defined as polar angles in spaces spanned by a finite number of delayed coordinates. A canonical choice of the polar axis and a related implicit estimation scheme for the potentially underlying autoregressive circle map (next phase map) guarantee the invertibility of reconstructed phase space trajectories to the original coordinates. The resulting Fourier approximated, invertibility enforcing phase space map allows us to detect conditional asymptotic stability of coupled phases. This comparatively general synchronization criterion unites two existing generalizations of the old concept and can successfully be applied, e.g., to phases obtained from electrocardiogram and airflow recordings characterizing cardiorespiratory interaction.

Fuzzy support vector machines for adaptive Morse code recognition.

PubMed

Yang, Cheng-Hong; Jin, Li-Cheng; Chuang, Li-Yeh

2006-11-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature.

[What makes an insect a vector?].

PubMed

Kampen, Helge

2009-01-01

Blood-feeding insects transmit numerous viruses, bacteria, protozoans and helminths to vertebrates. The developmental cycles of the microorganisms in their vectors and the mechanisms of transmission are generally extremely complex and the result of a long-lasting coevolution of vector and vectored pathogen based on mutual adaptation. The conditions necessary for an insect to become a vector are multiple but require an innate vector competence as a genetic basis. Next to the vector competence plenty of entomological, ecological and pathogen-related factors are decisive, given the availability of infection sources. The various modes of pathogen transmission by vectors are connected to the developmental routes of the microorganisms in their vectors. In particular, pathogens transmitted by saliva encounter a lot of cellular and acellular barriers during their migration from the insect's midgut through the hemocele into the salivary fluid, including components of the insect's immune system. With regard to intracellular development, receptor-mediated invasion mechanisms are of relevance. As an environmental factor, the temperature has a paramount impact on the vectorial roles of hematophagous insects. Not only has it a considerable influence on the duration of a pathogen's development in its vector (extrinsic incubation period) but it can render putatively vector-incompetent insects to vectors ("leaky gut" phenomenon). Equally crucial are behavioural aspects of both the insect and the pathogen such as blood host preferences, seasonal appearance and circadian biting activity on the vector's side and diurnal/nocturnal periodicity on the pathogen's side which facilitate a contact in the first place.

Environmental and biological factors influencing Culex pipiens quinquefasciatus Say (Diptera: Culicidae) vector competence for Saint Louis encephalitis virus.

PubMed

Richards, Stephanie L; Lord, Cynthia C; Pesko, Kendra; Tabachnick, Walter J

2009-08-01

Complex interactions between environmental and biological factors influence the susceptibility of Culex pipiens quinquefasciatus to St. Louis encephalitis virus and could affect the epidemiology of virus transmission. Similar interactions could have epidemiologic implications for other vector-virus systems. We conducted an experiment to examine four such factors in combination: mosquito age, extrinsic incubation temperature (EIT), virus dose, and colony. The proportion of mosquitoes with body infections or disseminated infections varied between colonies, and was dependant on age, EIT, and dose. We also show that the probability of a body or leg infection interacted in complex ways between colonies, ages, EITs, and doses. The complex interactive effects of environmental and biological factors must be taken into account for studies of vector competence and epidemiology, especially when laboratory studies are used to generalize to natural transmission dynamics where the extent of variation is largely unknown.

Orthobiologics in the augmentation of osteoporotic fractures.

PubMed

Watson, J Tracy; Nicolaou, Daemeon A

2015-02-01

Many orthobiologic adjuvants are available and widely utilized for general skeletal restoration. Their use for the specific task of osteoporotic fracture augmentation is less well recognized. Common conductive materials are reviewed for their value in this patient population including the large group of allograft adjuvants categorically known as the demineralized bone matrices (DBMs). Another large group of alloplastic materials is also examined-the calcium phosphate and sulfate ceramics. Both of these materials, when used for the proper indications, demonstrate efficacy for these patients. The inductive properties of bone morphogenic proteins (BMPs) and platelet concentrates show no clear advantages for this group of patients. Systemic agents including bisphosphonates, receptor activator of nuclear factor κβ ligand (RANKL) inhibitors, and parathyroid hormone augmentation all demonstrate positive effects with this fracture cohort. Newer modalities, such as trace ion bioceramic augmentation, are also reviewed for their positive effects on osteoporotic fracture healing.

Meta-image navigation augmenters for unmanned aircraft systems (MINA for UAS)

NASA Astrophysics Data System (ADS)

Òªelik, Koray; Somani, Arun K.; Schnaufer, Bernard; Hwang, Patrick Y.; McGraw, Gary A.; Nadke, Jeremy

2013-05-01

GPS is a critical sensor for Unmanned Aircraft Systems (UASs) due to its accuracy, global coverage and small hardware footprint, but is subject to denial due to signal blockage or RF interference. When GPS is unavailable, position, velocity and attitude (PVA) performance from other inertial and air data sensors is not sufficient, especially for small UASs. Recently, image-based navigation algorithms have been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. Performing absolute navigation with real-time aerial images requires georeferenced data, either images or landmarks, as a reference. Georeferenced imagery is readily available today, but requires a large amount of storage, whereas collections of discrete landmarks are compact but must be generated by pre-processing. An alternative, compact source of georeferenced data having large coverage area is open source vector maps from which meta-objects can be extracted for matching against real-time acquired imagery. We have developed a novel, automated approach called MINA (Meta Image Navigation Augmenters), which is a synergy of machine-vision and machine-learning algorithms for map aided navigation. As opposed to existing image map matching algorithms, MINA utilizes publicly available open-source geo-referenced vector map data, such as OpenStreetMap, in conjunction with real-time optical imagery from an on-board, monocular camera to augment the UAS navigation computer when GPS is not available. The MINA approach has been experimentally validated with both actual flight data and flight simulation data and results are presented in the paper.

Beyond long memory in heart rate variability: An approach based on fractionally integrated autoregressive moving average time series models with conditional heteroscedasticity

NASA Astrophysics Data System (ADS)

Leite, Argentina; Paula Rocha, Ana; Eduarda Silva, Maria

2013-06-01

Heart Rate Variability (HRV) series exhibit long memory and time-varying conditional variance. This work considers the Fractionally Integrated AutoRegressive Moving Average (ARFIMA) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors. ARFIMA-GARCH models may be used to capture and remove long memory and estimate the conditional volatility in 24 h HRV recordings. The ARFIMA-GARCH approach is applied to fifteen long term HRV series available at Physionet, leading to the discrimination among normal individuals, heart failure patients, and patients with atrial fibrillation.

Multifractality and autoregressive processes of dry spell lengths in Europe: an approach to their complexity and predictability

NASA Astrophysics Data System (ADS)

Lana, X.; Burgueño, A.; Serra, C.; Martínez, M. D.

2017-01-01

Dry spell lengths, DSL, defined as the number of consecutive days with daily rain amounts below a given threshold, may provide relevant information about drought regimes. Taking advantage of a daily pluviometric database covering a great extension of Europe, a detailed analysis of the multifractality of the dry spell regimes is achieved. At the same time, an autoregressive process is applied with the aim of predicting DSL. A set of parameters, namely Hurst exponent, H, estimated from multifractal spectrum, f( α), critical Hölder exponent, α 0, for which f( α) reaches its maximum value, spectral width, W, and spectral asymmetry, B, permits a first clustering of European rain gauges in terms of the complexity of their DSL series. This set of parameters also allows distinguishing between time series describing fine- or smooth-structure of the DSL regime by using the complexity index, CI. Results of previous monofractal analyses also permits establishing comparisons between smooth-structures, relatively low correlation dimensions, notable predictive instability and anti-persistence of DSL for European areas, sometimes submitted to long droughts. Relationships are also found between the CI and the mean absolute deviation, MAD, and the optimum autoregressive order, OAO, of an ARIMA( p, d,0) autoregressive process applied to the DSL series. The detailed analysis of the discrepancies between empiric and predicted DSL underlines the uncertainty over predictability of long DSL, particularly for the Mediterranean region.

Detecting P and S-wave of Mt. Rinjani seismic based on a locally stationary autoregressive (LSAR) model

NASA Astrophysics Data System (ADS)

Nurhaida, Subanar, Abdurakhman, Abadi, Agus Maman

2017-08-01

Seismic data is usually modelled using autoregressive processes. The aim of this paper is to find the arrival times of the seismic waves of Mt. Rinjani in Indonesia. Kitagawa algorithm's is used to detect the seismic P and S-wave. Householder transformation used in the algorithm made it effectively finding the number of change points and parameters of the autoregressive models. The results show that the use of Box-Cox transformation on the variable selection level makes the algorithm works well in detecting the change points. Furthermore, when the basic span of the subinterval is set 200 seconds and the maximum AR order is 20, there are 8 change points which occur at 1601, 2001, 7401, 7601,7801, 8001, 8201 and 9601. Finally, The P and S-wave arrival times are detected at time 1671 and 2045 respectively using a precise detection algorithm.

Environmental and Biological Factors Influencing Culex pipiens quinquefasciatus Say (Diptera: Culicidae) Vector Competence for Saint Louis Encephalitis Virus

PubMed Central

Richards, Stephanie L.; Lord, Cynthia C.; Pesko, Kendra; Tabachnick, Walter J.

2009-01-01

Complex interactions between environmental and biological factors influence the susceptibility of Culex pipiens quinquefasciatus to St. Louis encephalitis virus and could affect the epidemiology of virus transmission. Similar interactions could have epidemiologic implications for other vector-virus systems. We conducted an experiment to examine four such factors in combination: mosquito age, extrinsic incubation temperature (EIT), virus dose, and colony. The proportion of mosquitoes with body infections or disseminated infections varied between colonies, and was dependant on age, EIT, and dose. We also show that the probability of a body or leg infection interacted in complex ways between colonies, ages, EITs, and doses. The complex interactive effects of environmental and biological factors must be taken into account for studies of vector competence and epidemiology, especially when laboratory studies are used to generalize to natural transmission dynamics where the extent of variation is largely unknown. PMID:19635881

Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

PubMed

Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

2010-12-01

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

Point-based warping with optimized weighting factors of displacement vectors

NASA Astrophysics Data System (ADS)

Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

2000-06-01

The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

Augmented Reality Trends in Education: A Systematic Review of Research and Applications

ERIC Educational Resources Information Center

Bacca, Jorge; Baldiris, Silvia; Fabregat, Ramon; Graf, Sabine; Kinshuk

2014-01-01

In recent years, there has been an increasing interest in applying Augmented Reality (AR) to create unique educational settings. So far, however, there is a lack of review studies with focus on investigating factors such as: the uses, advantages, limitations, effectiveness, challenges and features of augmented reality in educational settings.…

Characteristics of Minimally Oversized Adeno-Associated Virus Vectors Encoding Human Factor VIII Generated Using Producer Cell Lines and Triple Transfection.

PubMed

Nambiar, Bindu; Cornell Sookdeo, Cathleen; Berthelette, Patricia; Jackson, Robert; Piraino, Susan; Burnham, Brenda; Nass, Shelley; Souza, David; O'Riordan, Catherine R; Vincent, Karen A; Cheng, Seng H; Armentano, Donna; Kyostio-Moore, Sirkka

2017-02-01

Several ongoing clinical studies are evaluating recombinant adeno-associated virus (rAAV) vectors as gene delivery vehicles for a variety of diseases. However, the production of vectors with genomes >4.7 kb is challenging, with vector preparations frequently containing truncated genomes. To determine whether the generation of oversized rAAVs can be improved using a producer cell-line (PCL) process, HeLaS3-cell lines harboring either a 5.1 or 5.4 kb rAAV vector genome encoding codon-optimized cDNA for human B-domain deleted Factor VIII (FVIII) were isolated. High-producing "masterwells" (MWs), defined as producing >50,000 vg/cell, were identified for each oversized vector. These MWs provided stable vector production for >20 passages. The quality and potency of the AAVrh8R/FVIII-5.1 and AAVrh8R/FVIII-5.4 vectors generated by the PCL method were then compared to those prepared via transient transfection (TXN). Southern and dot blot analyses demonstrated that both production methods resulted in packaging of heterogeneously sized genomes. However, the PCL-derived rAAV vector preparations contained some genomes >4.7 kb, whereas the majority of genomes generated by the TXN method were ≤4.7 kb. The PCL process reduced packaging of non-vector DNA for both the AAVrh8R/FVIII-5.1 and the AAVrh8R/FVIII-5.4 kb vector preparations. Furthermore, more DNA-containing viral particles were obtained for the AAVrh8R/FVIII-5.1 vector. In a mouse model of hemophilia A, animals administered a PCL-derived rAAV vector exhibited twofold higher plasma FVIII activity and increased levels of vector genomes in the liver than mice treated with vector produced via TXN did. Hence, the quality of oversized vectors prepared using the PCL method is greater than that of vectors generated using the TXN process, and importantly this improvement translates to enhanced performance in vivo.

Augmenting computer networks

NASA Technical Reports Server (NTRS)

Bokhari, S. H.; Raza, A. D.

1984-01-01

Three methods of augmenting computer networks by adding at most one link per processor are discussed: (1) A tree of N nodes may be augmented such that the resulting graph has diameter no greater than 4log sub 2((N+2)/3)-2. Thi O(N(3)) algorithm can be applied to any spanning tree of a connected graph to reduce the diameter of that graph to O(log N); (2) Given a binary tree T and a chain C of N nodes each, C may be augmented to produce C so that T is a subgraph of C. This algorithm is O(N) and may be used to produce augmented chains or rings that have diameter no greater than 2log sub 2((N+2)/3) and are planar; (3) Any rectangular two-dimensional 4 (8) nearest neighbor array of size N = 2(k) may be augmented so that it can emulate a single step shuffle-exchange network of size N/2 in 3(t) time steps.

Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

NASA Astrophysics Data System (ADS)

Khan, Muhammad Yousaf; Mittnik, Stefan

2018-01-01

In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

Expression of human factor IX gene in murine plasma through lentiviral vector-infected haematopoietic stem cells.

PubMed

Chen, Haoming; Yao, Hengmei; Huang, Lu; Shen, Qi; Jia, William; Xue, Jinglun

2006-12-01

1. Haematopoietic stem cells (HSC) are an attractive target for gene therapy. Gene transfer to HSC can provide a potential cure for many inherited diseases. Moreover, recombinant lentiviral vectors can transfer genes efficiently to HSC. In the present study, we used the recombinant lentiviruses FUGW (Flip, ubiquitin promoter, GFP and WRE vector) and FUXW (Flip, ubiquitin promoter, F IX and WRE vector), which carry the enhanced green fluorescent protein (EGFP) and human factor IX (hFIX) gene, respectively, to infect HSC. 2. High titres of recombinant lentivirus were prepared from 293T cells by calcium phosphate-mediated transient cotransfection. Murine mononuclear cells (MNC) separated from murine bone marrow and HSC separated by magnetic cell sorting were cultured in vitro. Cells they were infected by the recombinant lentiviruses FUGW and FUXW. The expression of EGFP was observed under a fluorescent microscope and was analysed by fluorescence-activated cell sorting, whereas the expression of hFIX was detected by ELISA. 3. The results show that the lentiviral vectors can efficiently infect murine HSC in vitro and that transduction was more efficient following cytokine treatment with interleukin (IL)-3, IL-6 and stem cell factor. 4. Haematopoietic stem cells infected with lentivirus FUXW were transplanted into [(60)Co]-irradiated non-obese diabetic/severe combined immunodeficiency (NOD-SCID) mice. The expression of hFIX in the blood plasma of the transplanted mice reached a peak of 44.9 +/- 7.6 ng/mL on Day 7. An assay of transaminase levels and a histological study of the liver showed that there was no significant damage following HSC transplantation to mice. 5. The results of the present study suggest that transplantation of HSC results in the persistant expression of hFIX in mice, which may be useful in haemophilia B gene therapy.

Parametric Investigation of Thrust Augmentation by Ejectors on a Pulsed Detonation Tube

NASA Technical Reports Server (NTRS)

Wilson, Jack; Sgondea, Alexandru; Paxson, Daniel E.; Rosenthal, Bruce N.

2005-01-01

A parametric investigation has been made of thrust augmentation of a 1 inch diameter pulsed detonation tube by ejectors. A set of ejectors was used which permitted variation of the ejector length, diameter, and nose radius, according to a statistical design of experiment scheme. The maximum augmentations for each ejector were fitted using a polynomial response surface, from which the optimum ejector diameters, and nose radius, were found. Thrust augmentations above a factor of 2 were measured. In these tests, the pulsed detonation device was run on approximately stoichiometric air-hydrogen mixtures, at a frequency of 20 Hz. Later measurements at a frequency of 40 Hz gave lower values of thrust augmentation. Measurements of thrust augmentation as a function of ejector entrance to detonation tube exit distance showed two maxima, one with the ejector entrance upstream, and one downstream, of the detonation tube exit. A thrust augmentation of 2.5 was observed using a tapered ejector.

Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

NASA Astrophysics Data System (ADS)

Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

2015-04-01

A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built

[Association between oxytocin augmentation intervals and the risk of postpartum haemorrhage].

PubMed

Loscul, C; Chantry, A-A; Caubit, L; Deneux-Tharaux, C; Goffinet, F; Le Ray, C

2016-09-01

To study the association between the duration of oxytocin augmentation intervals and the risk of postpartum haemorrhage (PPH) among primiparous women in spontaneous labour. Retrospective cohort including primiparous women in spontaneous labour who received oxytocin during labour (n=454). Oxytocin augmentation intervals were dichotomized in intervals<20minutes and≥20minutes. Obstetrical and neonatal issues were analyzed according to the duration oxytocin augmentation intervals. The association between oxytocin augmentation intervals and PPH was analyzed using univariate and multivariate analysis. Oxytocin augmentation intervals were shorter than 20minutes for 43.8% of the study population. The rate of PPH was higher (9.1% vs 3.5%; P=0.014), and the use of sulprostone was more frequent (6.5% vs 3.5%; P=0.013) if oxytocin augmentation intervals were shorter than 20minutes in comparison with intervals≥20minutes. The association between oxytocin augmentation intervals and PPH remains significant after adjustment on other PPH risk factors (adjusted OR=3.48, 95% CI [1.45-8.34]). The rate of adverse neonatal issue, defined by arterial pH at birth≤7.10 and/or 5minutes score d'Apgar≤7, was higher if oxytocin augmentation intervals were<20minutes (12.1% vs 4.3%; P=0.002). Our study demonstrated an increased risk of PPH for primiparous women in spontaneous labour who received oxytocin with augmentation intervals shorter than 20minutes. Copyright © 2016. Published by Elsevier Masson SAS.

Modelling malaria incidence by an autoregressive distributed lag model with spatial component.

PubMed

Laguna, Francisco; Grillet, María Eugenia; León, José R; Ludeña, Carenne

2017-08-01

The influence of climatic variables on the dynamics of human malaria has been widely highlighted. Also, it is known that this mosquito-borne infection varies in space and time. However, when the data is spatially incomplete most popular spatio-temporal methods of analysis cannot be applied directly. In this paper, we develop a two step methodology to model the spatio-temporal dependence of malaria incidence on local rainfall, temperature, and humidity as well as the regional sea surface temperatures (SST) in the northern coast of Venezuela. First, we fit an autoregressive distributed lag model (ARDL) to the weekly data, and then, we adjust a linear separable spacial vectorial autoregressive model (VAR) to the residuals of the ARDL. Finally, the model parameters are tuned using a Markov Chain Monte Carlo (MCMC) procedure derived from the Metropolis-Hastings algorithm. Our results show that the best model to account for the variations of malaria incidence from 2001 to 2008 in 10 endemic Municipalities in North-Eastern Venezuela is a logit model that included the accumulated local precipitation in combination with the local maximum temperature of the preceding month as positive regressors. Additionally, we show that although malaria dynamics is highly heterogeneous in space, a detailed analysis of the estimated spatial parameters in our model yield important insights regarding the joint behavior of the disease incidence across the different counties in our study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic cell identification and visualization using digital holographic microscopy with head mounted augmented reality devices.

PubMed

O'Connor, Timothy; Rawat, Siddharth; Markman, Adam; Javidi, Bahram

2018-03-01

We propose a compact imaging system that integrates an augmented reality head mounted device with digital holographic microscopy for automated cell identification and visualization. A shearing interferometer is used to produce holograms of biological cells, which are recorded using customized smart glasses containing an external camera. After image acquisition, segmentation is performed to isolate regions of interest containing biological cells in the field-of-view, followed by digital reconstruction of the cells, which is used to generate a three-dimensional (3D) pseudocolor optical path length profile. Morphological features are extracted from the cell's optical path length map, including mean optical path length, coefficient of variation, optical volume, projected area, projected area to optical volume ratio, cell skewness, and cell kurtosis. Classification is performed using the random forest classifier, support vector machines, and K-nearest neighbor, and the results are compared. Finally, the augmented reality device displays the cell's pseudocolor 3D rendering of its optical path length profile, extracted features, and the identified cell's type or class. The proposed system could allow a healthcare worker to quickly visualize cells using augmented reality smart glasses and extract the relevant information for rapid diagnosis. To the best of our knowledge, this is the first report on the integration of digital holographic microscopy with augmented reality devices for automated cell identification and visualization.

Training for planning tumour resection: augmented reality and human factors.

PubMed

Abhari, Kamyar; Baxter, John S H; Chen, Elvis C S; Khan, Ali R; Peters, Terry M; de Ribaupierre, Sandrine; Eagleson, Roy

2015-06-01

Planning surgical interventions is a complex task, demanding a high degree of perceptual, cognitive, and sensorimotor skills to reduce intra- and post-operative complications. This process requires spatial reasoning to coordinate between the preoperatively acquired medical images and patient reference frames. In the case of neurosurgical interventions, traditional approaches to planning tend to focus on providing a means for visualizing medical images, but rarely support transformation between different spatial reference frames. Thus, surgeons often rely on their previous experience and intuition as their sole guide is to perform mental transformation. In case of junior residents, this may lead to longer operation times or increased chance of error under additional cognitive demands. In this paper, we introduce a mixed augmented-/virtual-reality system to facilitate training for planning a common neurosurgical procedure, brain tumour resection. The proposed system is designed and evaluated with human factors explicitly in mind, alleviating the difficulty of mental transformation. Our results indicate that, compared to conventional planning environments, the proposed system greatly improves the nonclinicians' performance, independent of the sensorimotor tasks performed ( ). Furthermore, the use of the proposed system by clinicians resulted in a significant reduction in time to perform clinically relevant tasks ( ). These results demonstrate the role of mixed-reality systems in assisting residents to develop necessary spatial reasoning skills needed for planning brain tumour resection, improving patient outcomes.

Definitive treatment of the negative vector orbit.

PubMed

Mommaerts, Maurice Y

2018-05-09

In a negative vector orbit, the most anterior globe portion protrudes past the malar eminence. As bulging eyes are considered unaesthetic, patients usually seek correction. However, most current correction techniques produce suboptimal results. Here, we present a surgical technique that sets back the globe and protrudes the malar bone using an intraoral approach. All five patients (aged 17-41 years) in our case series reported being satisfied with the improvement achieved using this technique. Based on our experience, a transoral approach to malar augmentation by valgisation osteotomy may address the bulging eyes aspect through transantral orbital fat reduction in select cases. Copyright © 2018 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Pilot-optimal augmentation synthesis

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1978-01-01

An augmentation synthesis method usable in the absence of quantitative handling qualities specifications, and yet explicitly including design objectives based on pilot-rating concepts, is presented. The algorithm involves the unique approach of simultaneously solving for the stability augmentation system (SAS) gains, pilot equalization and pilot rating prediction via optimal control techniques. Simultaneous solution is required in this case since the pilot model (gains, etc.) depends upon the augmented plant dynamics, and the augmentation is obviously not a priori known. Another special feature is the use of the pilot's objective function (from which the pilot model evolves) to design the SAS.

Augmenting the access grid using augmented reality

NASA Astrophysics Data System (ADS)

Li, Ying

2012-01-01

The Access Grid (AG) targets an advanced collaboration environment, with which multi-party group of people from remote sites can collaborate over high-performance networks. However, current AG still employs VIC (Video Conferencing Tool) to offer only pure video for remote communication, while most AG users expect to collaboratively refer and manipulate the 3D geometric models of grid services' results in live videos of AG session. Augmented Reality (AR) technique can overcome the deficiencies with its characteristics of combining virtual and real, real-time interaction and 3D registration, so it is necessary for AG to utilize AR to better assist the advanced collaboration environment. This paper introduces an effort to augment the AG by adding support for AR capability, which is encapsulated in the node service infrastructure, named as Augmented Reality Service (ARS). The ARS can merge the 3D geometric models of grid services' results and real video scene of AG into one AR environment, and provide the opportunity for distributed AG users to interactively and collaboratively participate in the AR environment with better experience.

Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

NASA Astrophysics Data System (ADS)

Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

2014-09-01

Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

Patients and animal models of CNGβ1-deficient retinitis pigmentosa support gene augmentation approach

PubMed Central

Petersen-Jones, Simon M.; Occelli, Laurence M.; Winkler, Paige A.; Lee, Winston; Sparrow, Janet R.; Tsukikawa, Mai; Boye, Sanford L.; Chiodo, Vince; Capasso, Jenina E.; Becirovic, Elvir; Schön, Christian; Seeliger, Mathias W.; Levin, Alex V.; Hauswirth, William W.

2017-01-01

Retinitis pigmentosa (RP) is a major cause of blindness that affects 1.5 million people worldwide. Mutations in cyclic nucleotide-gated channel β 1 (CNGB1) cause approximately 4% of autosomal recessive RP. Gene augmentation therapy shows promise for treating inherited retinal degenerations; however, relevant animal models and biomarkers of progression in patients with RP are needed to assess therapeutic outcomes. Here, we evaluated RP patients with CNGB1 mutations for potential biomarkers of progression and compared human phenotypes with those of mouse and dog models of the disease. Additionally, we used gene augmentation therapy in a CNGβ1-deficient dog model to evaluate potential translation to patients. CNGB1-deficient RP patients and mouse and dog models had a similar phenotype characterized by early loss of rod function and slow rod photoreceptor loss with a secondary decline in cone function. Advanced imaging showed promise for evaluating RP progression in human patients, and gene augmentation using adeno-associated virus vectors robustly sustained the rescue of rod function and preserved retinal structure in the dog model. Together, our results reveal an early loss of rod function in CNGB1-deficient patients and a wide window for therapeutic intervention. Moreover, the identification of potential biomarkers of outcome measures, availability of relevant animal models, and robust functional rescue from gene augmentation therapy support future work to move CNGB1-RP therapies toward clinical trials. PMID:29202463

[Effects of plant viruses on vector and non-vector herbivorous arthropods and their natural enemies: a mini review].

PubMed

He, Xiao-Chan; Xu, Hong-Xing; Zhou, Xiao-Jun; Zheng, Xu-Song; Sun, Yu-Jian; Yang, Ya-Jun; Tian, Jun-Ce; Lü, Zhong-Xian

2014-05-01

Plant viruses transmitted by arthropods, as an important biotic factor, may not only directly affect the yield and quality of host plants, and development, physiological characteristics and ecological performances of their vector arthropods, but also directly or indirectly affect the non-vector herbivorous arthropods and their natural enemies in the same ecosystem, thereby causing influences to the whole agro-ecosystem. This paper reviewed the progress on the effects of plant viruses on herbivorous arthropods, including vector and non-vector, and their natural enemies, and on their ecological mechanisms to provide a reference for optimizing the management of vector and non-vector arthropod populations and sustainable control of plant viruses in agro-ecosystem.

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text

PubMed Central

Xin, Yu; Hochberg, Ephraim; Joshi, Rohit; Uzuner, Ozlem; Szolovits, Peter

2015-01-01

Objective Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability. Methods The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria. Results and Conclusion SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features. PMID:25862765

Emergence and Prevalence of Human Vector-Borne Diseases in Sink Vector Populations

PubMed Central

Rascalou, Guilhem; Pontier, Dominique; Menu, Frédéric; Gourbière, Sébastien

2012-01-01

Vector-borne diseases represent a major public health concern in most tropical and subtropical areas, and an emerging threat for more developed countries. Our understanding of the ecology, evolution and control of these diseases relies predominantly on theory and data on pathogen transmission in large self-sustaining ‘source’ populations of vectors representative of highly endemic areas. However, there are numerous places where environmental conditions are less favourable to vector populations, but where immigration allows them to persist. We built an epidemiological model to investigate the dynamics of six major human vector borne-diseases in such non self-sustaining ‘sink’ vector populations. The model was parameterized through a review of the literature, and we performed extensive sensitivity analysis to look at the emergence and prevalence of the pathogen that could be encountered in these populations. Despite the low vector abundance in typical sink populations, all six human diseases were able to spread in 15–55% of cases after accidental introduction. The rate of spread was much more strongly influenced by vector longevity, immigration and feeding rates, than by transmission and virulence of the pathogen. Prevalence in humans remained lower than 5% for dengue, leishmaniasis and Japanese encephalitis, but substantially higher for diseases with longer duration of infection; malaria and the American and African trypanosomiasis. Vector-related parameters were again the key factors, although their influence was lower than on pathogen emergence. Our results emphasize the need for ecology and evolution to be thought in the context of metapopulations made of a mosaic of sink and source habitats, and to design vector control program not only targeting areas of high vector density, but working at a larger spatial scale. PMID:22629337

Influence of vector dose on factor IX-specific T and B cell responses in muscle-directed gene therapy.

PubMed

Herzog, Roland W; Fields, Paul A; Arruda, Valder R; Brubaker, Jeff O; Armstrong, Elina; McClintock, Darryl; Bellinger, Dwight A; Couto, Linda B; Nichols, Timothy C; High, Katherine A

2002-07-20

Intramuscular injection of an adeno-associated virus (AAV) vector has resulted in vector dose-dependent, stable expression of canine factor IX (cF.IX) in hemophilia B dogs with an F.IX missense mutation (Herzog et al., Nat. Med. 1999;5:56-63). The use of a species-specific transgene allowed us to study risks and characteristics of antibody formation against the therapeutic transgene product. We analyzed seven dogs that had been injected at a single time point at multiple intramuscular sites with varying vector doses (dose per kilogram, dose per animal, dose per site). Comparison of individual animals suggests an increased likelihood of inhibitory anti-cF.IX (inhibitor) development with increased vector doses, with dose per site showing the strongest correlation with the risk of inhibitor formation. In six of seven animals, such immune responses were either absent or transient, and therefore did not prevent sustained systemic expression of cF.IX. Transient inhibitory/neutralizing anti-cF.IX responses occurred at vector doses of 2 x 10(12)/site, whereas a 6-fold higher dose resulted in a longer lasting, higher titer inhibitor. Anti-cF.IX was efficiently blocked in an eighth animal that was injected with a high vector dose per site, but in addition received transient immune suppression. Inhibitor formation was characterized by synthesis of two IgG subclasses and in vitro proliferation of lymphocytes to cF.IX antigen, indicating a helper T cell-dependent mechanism. Anti-cF.IX formation is likely influenced by the extent of local antigen presentation and may be avoided by limited vector doses or by transient immune modulation.

Microsphere-liposome complexes protect adenoviral vectors from neutralising antibody without losses in transfection efficiency, in-vitro.

PubMed

Steel, Jason C; Cavanagh, Heather M A; Burton, Mark A; Kalle, Wouter H J

2004-11-01

Adenoviral vectors have been commonly used in gene therapy protocols but the success of their use is often limited by the induction of host immunity to the vector. Following exposure to the adenoviral vector, adenoviral-specific neutralising antibodies are produced, which limits further administration. This study examines the effectiveness of a novel combination of microspheres and liposomes for the shielding of adenovirus from neutralising antibodies in an in-vitro setting. We show that liposomes are effective in the protection of adenovirus from neutralising antibody and that the conjugation of these complexes to microspheres augments the level of protection. This study further reveals that previously neutralised adenovirus may still be transported into the cell via liposome-cell interactions and is still capable of expressing its genes, making this vector an effective tool for circumvention of the humoral immune response. We also looked at possible side effects of using the complexes, namely increases in cytotoxicity and reductions in transfection efficiency. Our results showed that varying the liposome:adenovirus ratio can reduce the cytotoxicity of the vector as well as increase the transfection efficiency. In addition, in cell lines that are adenoviral competent, transfection efficiencies on par with uncomplexed adenoviral vectors were achievable with the combination vector.

Parametric Investigation of Thrust Augmentation by Ejectors on a Pulsed Detonation Tube

NASA Technical Reports Server (NTRS)

Wilson, Jack; Sgondea, Alexandru; Paxson, Daniel E.; Rosenthal, Bruce N.

2006-01-01

A parametric investigation has been made of thrust augmentation of a 1 in. diameter pulsed detonation tube by ejectors. A set of ejectors was used which permitted variation of the ejector length, diameter, and nose radius, according to a statistical design of experiment scheme. The maximum augmentation ratios for each ejector were fitted using a polynomial response surface, from which the optimum ratios of ejector diameter to detonation tube diameter, and ejector length and nose radius to ejector diameter, were found. Thrust augmentation ratios above a factor of 2 were measured. In these tests, the pulsed detonation device was run on approximately stoichiometric air-hydrogen mixtures, at a frequency of 20 Hz. Later measurements at a frequency of 40 Hz gave lower values of thrust augmentation. Measurements of thrust augmentation as a function of ejector entrance to detonation tube exit distance showed two maxima, one with the ejector entrance upstream, and one downstream, of the detonation tube exit. A thrust augmentation of 2.5 was observed using a tapered ejector.

Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model

NASA Astrophysics Data System (ADS)

Vazifedan, Turaj; Shitan, Mahendran

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

The Disparate Labor Market Impacts of Monetary Policy

ERIC Educational Resources Information Center

Carpenter, Seth B.; Rodgers, William M., III

2004-01-01

Employing two widely used approaches to identify the effects of monetary policy, this paper explores the differential impact of policy on the labor market outcomes of teenagers, minorities, out-of-school youth, and less-skilled individuals. Evidence from recursive vector autoregressions and autoregressive distributed lag models that use…

In the Age of Breast Augmentation, Breast Reconstruction Provides an Opportunity to Augment the Breast.

PubMed

Zimmerman, Amanda L; Tugertimur, Bugra; Smith, Paul D; Kumar, Ambuj; Dayicioglu, Deniz

2017-01-01

Augmentation mammoplasty remains the most common cosmetic surgery procedure performed. The objective of this article is to evaluate the impact of augmented volume of the reconstructed breast in patients that undergo nipple-sparing mastectomy and patients previously augmented who undergo mastectomy with tissue expander/implant-based reconstruction. Patients undergoing skin-sparing mastectomy, nipple-sparing mastectomy, and mastectomy after previous augmentation followed by tissue expander/implant-based reconstruction between June 2011 and April 2015 by 2 surgeons at the same institution were included. Retrospective chart review of the patients identified using these criteria was performed to record patient characteristics, complications, breast volume, implant volume, and percentage change in volume at the time of reconstruction. Percentage change of breast volume was calculated using the formula (implant breast weight)/(breast weight) for skin-sparing and nipple-sparing mastectomy patients and (final breast implant weight - [breast weight + augmentation breast implant weight])/([breast weight + augmentation breast implant]) for patients undergoing mastectomy following previous augmentation. A total of 293 patients were included in the study with 63 patients who underwent nipple-sparing mastectomy, 166 patients who underwent skin-sparing mastectomy, and 64 patients who underwent previous augmentation with subsequent mastectomy. Mean percentage change in breast volume was 66% in the nipple-sparing mastectomy group, 15% for the right breast and 18% for the left breast in the skin-sparing mastectomy group, and 81% for the right breast and 72% for the left breast in the mastectomy following previous augmentation group. Complication rate for nipple-sparing mastectomy was 27%, mastectomy following previous augmentation was 20.3%, and skin-sparing mastectomy group was 18.7%. Patients who undergo nipple-sparing mastectomy or mastectomy following previous augmentation have

Development and human factors analysis of an augmented reality interface for multi-robot tele-operation and control

NASA Astrophysics Data System (ADS)

Lee, Sam; Lucas, Nathan P.; Ellis, R. Darin; Pandya, Abhilash

2012-06-01

This paper presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semiautonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor's ability to control multiple robots. The role of this human multi-robot interface is to allow an operator to control groups of heterogeneous robots in real time in a collaborative manner. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. Each robot knows the environment and obstacles and can automatically generate a collision-free path to any user-selected target. It displayed sensor information from each individual robot directly on the robot in the video view. In addition, a sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks. Results show that the novel Augmented Reality multi-robot control (Point-and-Go and Path Planning) reduced mission completion times compared to the traditional joystick control for target detection missions. Usability tests and operator workload analysis are also investigated.

Fisher Consistency of AM-Estimates of the Autoregression Parameter Using Hard Rejection Filter Cleaners

DTIC Science & Technology

1987-02-04

U5tr,)! P(U 5-t Since U - F with F RS, we get (3.1). Case b: 0 S 5 k -a Now P([U~t]riM) = P(UZk-a) and P([ Ugt ]rM) = P(US-k-a) S P(US-(k-a)) which again...robustness for autoregressive processes." The Annals of Statistics, 12, 843-863. Mallows, C.L. (1980). "Some theory of nonlinear smoothen." The Annals of

Three-Dimensional Analysis of Long-Term Midface Volume Change After Vertical Vector Deep-Plane Rhytidectomy.

PubMed

Jacono, Andrew A; Malone, Melanie H; Talei, Benjamin

2015-07-01

Facial aging is a complicated process that includes volume loss and soft tissue descent. This study provides quantitative 3-dimensional (3D) data on the long-term effect of vertical vector deep-plane rhytidectomy on restoring volume to the midface. To determine if primary vertical vector deep-plane rhytidectomy resulted in long-term volume change in the midface. We performed a prospective study on patients undergoing primary vertical vector deep-plane rhytidectomy to quantitate 3D volume changes in the midface. Quantitative analysis of volume changes was made using the Vectra 3D imaging software (Canfield Scientific, Inc, Fairfield, New Jersey) at a minimum follow-up of 1 year. Forty-three patients (86 hemifaces) were analyzed. The average volume gained in each hemi-midface after vertical vector deep-plane rhytidectomy was 3.2 mL. Vertical vector deep-plane rhytidectomy provides significant long-term augmentation of volume in the midface. These quantitative data demonstrate that some midface volume loss is related to gravitational descent of the cheek fat compartments and that vertical vector deep-plane rhytidectomy may obviate the need for other volumization procedures such as autologous fat grafting in selected cases. 4 Therapeutic. © 2015 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

Vector Autoregressive (VAR) Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example

PubMed Central

Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M.

2016-01-01

Background Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display inter-related vital sign changes during situations of physiologic stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. Purpose The purpose of this article is to illustrate development of patient-specific VAR models using vital sign time series (VSTS) data in a sample of acutely ill, monitored, step-down unit (SDU) patients, and determine their Granger causal dynamics prior to onset of an incident CRI. Approach CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40–140/minute, RR = 8–36/minute, SpO2 < 85%) and persisting for 3 minutes within a 5-minute moving window (60% of the duration of the window). A 6-hour time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity; (b) appropriate lag was determined using a lag-length selection criteria; (c) the VAR model was constructed; (d) residual autocorrelation was assessed with the Lagrange Multiplier test; (e) stability of the VAR system was checked; and (f) Granger causality was evaluated in the final stable model. Results The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%) (i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing

Advances in biologic augmentation for rotator cuff repair

PubMed Central

Patel, Sahishnu; Gualtieri, Anthony P.; Lu, Helen H.; Levine, William N.

2016-01-01

Rotator cuff tear is a very common shoulder injury that often necessitates surgical intervention for repair. Despite advances in surgical techniques for rotator cuff repair, there is a high incidence of failure after surgery because of poor healing capacity attributed to many factors. The complexity of tendon-to-bone integration inherently presents a challenge for repair because of a large biomechanical mismatch between the tendon and bone and insufficient regeneration of native tissue, leading to the formation of fibrovascular scar tissue. Therefore, various biological augmentation approaches have been investigated to improve rotator cuff repair healing. This review highlights recent advances in three fundamental approaches for biological augmentation for functional and integrative tendon–bone repair. First, the exploration, application, and delivery of growth factors to improve regeneration of native tissue is discussed. Second, applications of stem cell and other cell-based therapies to replenish damaged tissue for better healing is covered. Finally, this review will highlight the development and applications of compatible biomaterials to both better recapitulate the tendon–bone interface and improve delivery of biological factors for enhanced integrative repair. PMID:27750374

Benefit assessment of solar-augmented natural gas systems

NASA Technical Reports Server (NTRS)

Davis, E. S.; French, R. L.; Sohn, R. L.

1980-01-01

Report details how solar-energy-augmented system can reduce natural gas consumption by 40% to 70%. Applications discussed include: domestic hot water system, solar-assisted gas heat pumps, direct heating from storage tank. Industrial uses, solar-assisted appliances, and economic factors are discussed.

Micro-CT image reconstruction based on alternating direction augmented Lagrangian method and total variation.

PubMed

Gopi, Varun P; Palanisamy, P; Wahid, Khan A; Babyn, Paul; Cooper, David

2013-01-01

Micro-computed tomography (micro-CT) plays an important role in pre-clinical imaging. The radiation from micro-CT can result in excess radiation exposure to the specimen under test, hence the reduction of radiation from micro-CT is essential. The proposed research focused on analyzing and testing an alternating direction augmented Lagrangian (ADAL) algorithm to recover images from random projections using total variation (TV) regularization. The use of TV regularization in compressed sensing problems makes the recovered image quality sharper by preserving the edges or boundaries more accurately. In this work TV regularization problem is addressed by ADAL which is a variant of the classic augmented Lagrangian method for structured optimization. The per-iteration computational complexity of the algorithm is two fast Fourier transforms, two matrix vector multiplications and a linear time shrinkage operation. Comparison of experimental results indicate that the proposed algorithm is stable, efficient and competitive with the existing algorithms for solving TV regularization problems. Copyright © 2013 Elsevier Ltd. All rights reserved.

Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China.

PubMed

Yu, Lijing; Zhou, Lingling; Tan, Li; Jiang, Hongbo; Wang, Ying; Wei, Sheng; Nie, Shaofa

2014-01-01

Outbreaks of hand-foot-mouth disease (HFMD) have been reported for many times in Asia during the last decades. This emerging disease has drawn worldwide attention and vigilance. Nowadays, the prevention and control of HFMD has become an imperative issue in China. Early detection and response will be helpful before it happening, using modern information technology during the epidemic. In this paper, a hybrid model combining seasonal auto-regressive integrated moving average (ARIMA) model and nonlinear auto-regressive neural network (NARNN) is proposed to predict the expected incidence cases from December 2012 to May 2013, using the retrospective observations obtained from China Information System for Disease Control and Prevention from January 2008 to November 2012. The best-fitted hybrid model was combined with seasonal ARIMA [Formula: see text] and NARNN with 15 hidden units and 5 delays. The hybrid model makes the good forecasting performance and estimates the expected incidence cases from December 2012 to May 2013, which are respectively -965.03, -1879.58, 4138.26, 1858.17, 4061.86 and 6163.16 with an obviously increasing trend. The model proposed in this paper can predict the incidence trend of HFMD effectively, which could be helpful to policy makers. The usefulness of expected cases of HFMD perform not only in detecting outbreaks or providing probability statements, but also in providing decision makers with a probable trend of the variability of future observations that contains both historical and recent information.

Long-term correction of canine hemophilia B by gene transfer of blood coagulation factor IX mediated by adeno-associated viral vector.

PubMed

Herzog, R W; Yang, E Y; Couto, L B; Hagstrom, J N; Elwell, D; Fields, P A; Burton, M; Bellinger, D A; Read, M S; Brinkhous, K M; Podsakoff, G M; Nichols, T C; Kurtzman, G J; High, K A

1999-01-01

Hemophilia B is a severe X-linked bleeding diathesis caused by the absence of functional blood coagulation factor IX, and is an excellent candidate for treatment of a genetic disease by gene therapy. Using an adeno-associated viral vector, we demonstrate sustained expression (>17 months) of factor IX in a large-animal model at levels that would have a therapeutic effect in humans (up to 70 ng/ml, adequate to achieve phenotypic correction, in an animal injected with 8.5x10(12) vector particles/kg). The five hemophilia B dogs treated showed stable, vector dose-dependent partial correction of the whole blood clotting time and, at higher doses, of the activated partial thromboplastin time. In contrast to other viral gene delivery systems, this minimally invasive procedure, consisting of a series of percutaneous intramuscular injections at a single timepoint, was not associated with local or systemic toxicity. Efficient gene transfer to muscle was shown by immunofluorescence staining and DNA analysis of biopsied tissue. Immune responses against factor IX were either absent or transient. These data provide strong support for the feasibility of the approach for therapy of human subjects.

Hedonic price models with omitted variables and measurement errors: a constrained autoregression-structural equation modeling approach with application to urban Indonesia

NASA Astrophysics Data System (ADS)

Suparman, Yusep; Folmer, Henk; Oud, Johan H. L.

2014-01-01

Omitted variables and measurement errors in explanatory variables frequently occur in hedonic price models. Ignoring these problems leads to biased estimators. In this paper, we develop a constrained autoregression-structural equation model (ASEM) to handle both types of problems. Standard panel data models to handle omitted variables bias are based on the assumption that the omitted variables are time-invariant. ASEM allows handling of both time-varying and time-invariant omitted variables by constrained autoregression. In the case of measurement error, standard approaches require additional external information which is usually difficult to obtain. ASEM exploits the fact that panel data are repeatedly measured which allows decomposing the variance of a variable into the true variance and the variance due to measurement error. We apply ASEM to estimate a hedonic housing model for urban Indonesia. To get insight into the consequences of measurement error and omitted variables, we compare the ASEM estimates with the outcomes of (1) a standard SEM, which does not account for omitted variables, (2) a constrained autoregression model, which does not account for measurement error, and (3) a fixed effects hedonic model, which ignores measurement error and time-varying omitted variables. The differences between the ASEM estimates and the outcomes of the three alternative approaches are substantial.

Adenovirus vector expressing keratinocyte growth factor using CAG promoter impairs pulmonary function of mice with elastase-induced emphysema.

PubMed

Oki, Hiroshi; Yazawa, Takuya; Baba, Yasuko; Kanegae, Yumi; Sato, Hanako; Sakamoto, Seiko; Goto, Takahisa; Saito, Izumu; Kurahashi, Kiyoyasu

2017-07-01

Pulmonary emphysema impairs quality of life and increases mortality. It has previously been shown that administration of adenovirus vector expressing murine keratinocyte growth factor (KGF) before elastase instillation prevents pulmonary emphysema in mice. We therefore hypothesized that therapeutic administration of KGF would restore damage to lungs caused by elastase instillation and thus improve pulmonary function in an animal model. KGF expressing adenovirus vector, which prevented bleomycin-induced pulmonary fibrosis in a previous study, was constructed. Adenovirus vector (1.0 × 10 9 plaque-forming units) was administered intratracheally one week after administration of elastase into mouse lungs. One week after administration of KGF-vector, exercise tolerance testing and blood gas analysis were performed, after which the lungs were removed under deep anesthesia. KGF-positive pneumocytes were more numerous, surfactant protein secretion in the airspace greater and mean linear intercept of lungs shorter in animals that had received KGF than in control animals. Unexpectedly, however, arterial blood oxygenation was worse in the KGF group and maximum running speed, an indicator of exercise capacity, had not improved after KGF in mice with elastase-induced emphysema, indicating that KGF-expressing adenovirus vector impaired pulmonary function in these mice. Notably, vector lacking KGF-expression unit did not induce such impairment, implying that the KGF expression unit itself may cause the damage to alveolar cells. Possible involvement of the CAG promoter used for KGF expression in impairing pulmonary function is discussed. © 2017 The Societies and John Wiley & Sons Australia, Ltd.

[Augmentation technique on the proximal humerus].

PubMed

Scola, A; Gebhard, F; Röderer, G

2015-09-01

The treatment of osteoporotic fractures is still a challenge. The advantages of augmentation with respect to primary in vitro stability and the clinical use for the proximal humerus are presented in this article. In this study six paired human humeri were randomized into an augmented and a non-augmented group. Osteosynthesis was performed with a PHILOS plate (Synthes®). In the augmented group the two screws finding purchase in the weakest cancellous bone were augmented. The specimens were tested in a 3-part fracture model in a varus bending test. The augmented PHILOS plates withstood significantly more load cycles until failure. The correlation to bone mineral density (BMD) showed that augmentation could partially compensate for low BMD. The augmentation of the screws in locked plating in a proximal humerus fracture model is effective in improving the primary stability in a cyclic varus bending test. The targeted augmentation of two particular screws in a region of low bone quality within the humeral head was almost as effective as four screws with twice the amount of bone cement. Screw augmentation combined with a knowledge of the local bone quality could be more effective in enhancing the primary stability of a proximal humerus locking plate because the effect of augmentation can be exploited more effectively limiting it to the degree required. The technique of augmentation is simple and can be applied in open and minimally invasive procedures. When the correct procedure is used, complications (cement leakage into the joint) can be avoided.

Projecting county pulpwood production with historical production and macro-economic variables

Treesearch

Consuelo Brandeis; Dayton M. Lambert

2014-01-01

We explored forecasting of county roundwood pulpwood produc-tion with county-vector autoregressive (CVAR) and spatial panelvector autoregressive (SPVAR) methods. The analysis used timberproducts output data for the state of Florida, together with a set ofmacro-economic variables. Overall, we found the SPVAR specifica-tion produced forecasts with lower error rates...

Advanced intellect-augmentation techniques

NASA Technical Reports Server (NTRS)

Engelbart, D. C.

1972-01-01

User experience in applying our augmentation tools and techniques to various normal working tasks within our center is described so as to convey a subjective impression of what it is like to work in an augmented environment. It is concluded that working-support, computer-aid systems for augmenting individuals and teams, are undoubtedly going to be widely developed and used. A very special role in this development is seen for multi-access computer networks.

Axial-vector form factors of the nucleon from lattice QCD

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

Gupta, Rajan; Jang, Yong-Chull; Lin, Huey-Wen

In this paper, we present results for the form factors of the isovector axial vector current in the nucleon state using large scale simulations of lattice QCD. The calculations were done using eight ensembles of gauge configurations generated by the MILC collaboration using the HISQ action with 2 + 1 + 1 dynamical flavors. These ensembles span three lattice spacings a ≈ 0.06 , 0.09, and 0.12 fm and light-quark masses corresponding to the pion masses M π ≈ 135, 225, and 310 MeV. High-statistics estimates allow us to quantify systematic uncertainties in the extraction of G A (Q 2)more » and the induced pseudoscalar form factor G P(Q 2) . We perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses of the axial charge radius r A data to obtain physical estimates. Using the dipole ansatz to fit the Q 2 behavior we obtain r A | dipole = 0.49(3) fm , which corresponds to M A = 1.39(9) GeV , and is consistent with M A = 1.35(17) GeV obtained by the miniBooNE collaboration. The estimate obtained using the z -expansion is r A | z - expansion = 0.46(6) fm, and the combined result is r A | combined = 0.48(4) fm. Analysis of the induced pseudoscalar form factor G P (Q 2) yields low estimates for g* P and g πNN compared to their phenomenological values. To understand these, we analyze the partially conserved axial current (PCAC) relation by also calculating the pseudoscalar form factor. Lastly, we find that these low values are due to large deviations in the PCAC relation between the three form factors, and in the pion-pole dominance hypothesis.« less

Axial-vector form factors of the nucleon from lattice QCD

DOE PAGES

Gupta, Rajan; Jang, Yong-Chull; Lin, Huey-Wen; ...

2017-12-04

In this paper, we present results for the form factors of the isovector axial vector current in the nucleon state using large scale simulations of lattice QCD. The calculations were done using eight ensembles of gauge configurations generated by the MILC collaboration using the HISQ action with 2 + 1 + 1 dynamical flavors. These ensembles span three lattice spacings a ≈ 0.06 , 0.09, and 0.12 fm and light-quark masses corresponding to the pion masses M π ≈ 135, 225, and 310 MeV. High-statistics estimates allow us to quantify systematic uncertainties in the extraction of G A (Q 2)more » and the induced pseudoscalar form factor G P(Q 2) . We perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses of the axial charge radius r A data to obtain physical estimates. Using the dipole ansatz to fit the Q 2 behavior we obtain r A | dipole = 0.49(3) fm , which corresponds to M A = 1.39(9) GeV , and is consistent with M A = 1.35(17) GeV obtained by the miniBooNE collaboration. The estimate obtained using the z -expansion is r A | z - expansion = 0.46(6) fm, and the combined result is r A | combined = 0.48(4) fm. Analysis of the induced pseudoscalar form factor G P (Q 2) yields low estimates for g* P and g πNN compared to their phenomenological values. To understand these, we analyze the partially conserved axial current (PCAC) relation by also calculating the pseudoscalar form factor. Lastly, we find that these low values are due to large deviations in the PCAC relation between the three form factors, and in the pion-pole dominance hypothesis.« less

Augmented reality in neurosurgery

PubMed Central

Tagaytayan, Raniel; Kelemen, Arpad

2016-01-01

Neurosurgery is a medical specialty that relies heavily on imaging. The use of computed tomography and magnetic resonance images during preoperative planning and intraoperative surgical navigation is vital to the success of the surgery and positive patient outcome. Augmented reality application in neurosurgery has the potential to revolutionize and change the way neurosurgeons plan and perform surgical procedures in the future. Augmented reality technology is currently commercially available for neurosurgery for simulation and training. However, the use of augmented reality in the clinical setting is still in its infancy. Researchers are now testing augmented reality system prototypes to determine and address the barriers and limitations of the technology before it can be widely accepted and used in the clinical setting. PMID:29765445

Augmented reality in neurosurgery.

PubMed

Tagaytayan, Raniel; Kelemen, Arpad; Sik-Lanyi, Cecilia

2018-04-01

Neurosurgery is a medical specialty that relies heavily on imaging. The use of computed tomography and magnetic resonance images during preoperative planning and intraoperative surgical navigation is vital to the success of the surgery and positive patient outcome. Augmented reality application in neurosurgery has the potential to revolutionize and change the way neurosurgeons plan and perform surgical procedures in the future. Augmented reality technology is currently commercially available for neurosurgery for simulation and training. However, the use of augmented reality in the clinical setting is still in its infancy. Researchers are now testing augmented reality system prototypes to determine and address the barriers and limitations of the technology before it can be widely accepted and used in the clinical setting.

The effect of case management and vector-control interventions on space-time patterns of malaria incidence in Uganda.

PubMed

Ssempiira, Julius; Kissa, John; Nambuusi, Betty; Kyozira, Carol; Rutazaana, Damian; Mukooyo, Eddie; Opigo, Jimmy; Makumbi, Fredrick; Kasasa, Simon; Vounatsou, Penelope

2018-04-12

Electronic reporting of routine health facility data in Uganda began with the adoption of the District Health Information Software System version 2 (DHIS2) in 2011. This has improved health facility reporting and overall data quality. In this study, the effects of case management with artemisinin-based combination therapy (ACT) and vector control interventions on space-time patterns of disease incidence were determined using DHIS2 data reported during 2013-2016. Bayesian spatio-temporal negative binomial models were fitted on district-aggregated monthly malaria cases, reported by two age groups, defined by a cut-off age of 5 years. The effects of interventions were adjusted for socio-economic and climatic factors. Spatial and temporal correlations were taken into account by assuming a conditional autoregressive and a first-order autoregressive AR(1) process on district and monthly specific random effects, respectively. Fourier trigonometric functions were incorporated in the models to take into account seasonal fluctuations in malaria transmission. The temporal variation in incidence was similar in both age groups and depicted a steady decline up to February 2014, followed by an increase from March 2015 onwards. The trends were characterized by a strong bi-annual seasonal pattern with two peaks during May-July and September-December. Average monthly incidence in children < 5 years declined from 74.7 cases (95% CI 72.4-77.1) in 2013 to 49.4 (95% CI 42.9-55.8) per 1000 in 2015 and followed by an increase in 2016 of up to 51.3 (95% CI 42.9-55.8). In individuals ≥ 5 years, a decline in incidence from 2013 to 2015 was followed by an increase in 2016. A 100% increase in insecticide-treated nets (ITN) coverage was associated with a decline in incidence by 44% (95% BCI 28-59%). Similarly, a 100% increase in ACT coverage reduces incidence by 28% (95% BCI 11-45%) and 25% (95% BCI 20-28%) in children < 5 years and individuals ≥ 5 years, respectively

Analysis of pelagic species decline in the upper San Francisco Estuary using multivariate autoregressive modeling (MAR)

USGS Publications Warehouse

Mac Nally, Ralph; Thomson, James R.; Kimmerer, Wim J.; Feyrer, Frederick; Newman, Ken B.; Sih, Andy; Bennett, William A.; Brown, Larry; Fleishman, Erica; Culberson, Steven D.; Castillo, Gonzalo

2010-01-01

Four species of pelagic fish of particular management concern in the upper San Francisco Estuary, California, USA, have declined precipitously since ca. 2002: delta smelt (Hypomesus transpacificus), longfin smelt (Spirinchus thaleichthys), striped bass (Morone saxatilis), and threadfin shad (Dorosoma petenense). The estuary has been monitored since the late 1960s with extensive collection of data on the fishes, their pelagic prey, phytoplankton biomass, invasive species, and physical factors. We used multivariate autoregressive (MAR) modeling to discern the main factors responsible for the declines. An expert-elicited model was built to describe the system. Fifty-four relationships were built into the model, only one of which was of uncertain direction a priori. Twenty-eight of the proposed relationships were strongly supported by or consistent with the data, while 26 were close to zero (not supported by the data but not contrary to expectations). The position of the 2‰ isohaline (a measure of the physical response of the estuary to freshwater flow) and increased water clarity over the period of analyses were two factors affecting multiple declining taxa (including fishes and the fishes' main zooplankton prey). Our results were relatively robust with respect to the form of stock–recruitment model used and to inclusion of subsidiary covariates but may be enhanced by using detailed state–space models that describe more fully the life-history dynamics of the declining species.

Analysis of pelagic species decline in the upper San Francisco Estuary using multivariate autoregressive modeling (MAR).

PubMed

Mac Nally, Ralph; Thomson, James R; Kimmerer, Wim J; Feyrer, Frederick; Newman, Ken B; Sih, Andy; Bennett, William A; Brown, Larry; Fleishman, Erica; Culberson, Steven D; Castillo, Gonzalo

2010-07-01

Four species of pelagic fish of particular management concern in the upper San Francisco Estuary, California, USA, have declined precipitously since ca. 2002: delta smelt (Hypomesus transpacificus), longfin smelt (Spirinchus thaleichthys), striped bass (Morone saxatilis), and threadfin shad (Dorosoma petenense). The estuary has been monitored since the late 1960s with extensive collection of data on the fishes, their pelagic prey, phytoplankton biomass, invasive species, and physical factors. We used multivariate autoregressive (MAR) modeling to discern the main factors responsible for the declines. An expert-elicited model was built to describe the system. Fifty-four relationships were built into the model, only one of which was of uncertain direction a priori. Twenty-eight of the proposed relationships were strongly supported by or consistent with the data, while 26 were close to zero (not supported by the data but not contrary to expectations). The position of the 2 per thousand isohaline (a measure of the physical response of the estuary to freshwater flow) and increased water clarity over the period of analyses were two factors affecting multiple declining taxa (including fishes and the fishes' main zooplankton prey): Our results were relatively robust with respect to the form of stock-recruitment model used and to inclusion of subsidiary covariates but may be enhanced by using detailed state-space models that describe more fully the life-history dynamics of the declining species.

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

The effects of weekly augmentation therapy in patients with PiZZ α1-antitrypsin deficiency

PubMed Central

Schmid, ST; Koepke, J; Dresel, M; Hattesohl, A; Frenzel, E; Perez, J; Lomas, DA; Miranda, E; Greulich, T; Noeske, S; Wencker, M; Teschler, H; Vogelmeier, C; Janciauskiene, S; Koczulla, AR

2012-01-01

Background The major concept behind augmentation therapy with human α1-antitrypsin (AAT) is to raise the levels of AAT in patients with protease inhibitor phenotype ZZ (Glu342Lys)-inherited AAT deficiency and to protect lung tissues from proteolysis and progression of emphysema. Objective To evaluate the short-term effects of augmentation therapy (Prolastin®) on plasma levels of AAT, C-reactive protein, and chemokines/cytokines. Materials and methods Serum and exhaled breath condensate were collected from individuals with protease inhibitor phenotype ZZ AAT deficiency-related emphysema (n = 12) on the first, third, and seventh day after the infusion of intravenous Prolastin. Concentrations of total and polymeric AAT, interleukin-8 (IL-8), monocyte chemotactic protein-1, IL-6, tumor necrosis factor-α, vascular endothelial growth factor, and C-reactive protein were determined. Blood neutrophils and primary epithelial cells were also exposed to Prolastin (1 mg/mL). Results There were significant fluctuations in serum (but not in exhaled breath condensate) levels of AAT polymers, IL-8, monocyte chemotactic protein-1, IL-6, tumor necrosis factor-α, and vascular endothelial growth factor within a week of augmentation therapy. In general, augmented individuals had higher AAT and lower serum levels of IL-8 than nonaugmented subjects. Prolastin added for 3 hours to neutrophils from protease inhibitor phenotype ZZ individuals in vitro reduced IL-8 release but showed no effect on cytokine/chemokine release from human bronchial epithelial cells. Conclusion Within a week, augmentation with Prolastin induced fluctuations in serum levels of AAT polymers and cytokine/chemokines but specifically lowered IL-8 levels. It remains to be determined whether these effects are related to the Prolastin preparation per se or to the therapeutic efficacy of augmentation with AAT. PMID:23055718

Evidence for the role of the Atlantic multidecadal oscillation and the ocean heat uptake in hiatus prediction

NASA Astrophysics Data System (ADS)

Pasini, Antonello; Triacca, Umberto; Attanasio, Alessandro

2017-08-01

The recent hiatus in global temperature at the surface has been analysed by several studies, mainly using global climate models. The common accepted picture is that since the late 1990s, the increase in anthropogenic radiative forcings has been counterbalanced by other factors, e.g., a decrease in natural forcings, augmented ocean heat storage and negative phases of ocean-atmosphere-coupled oscillation patterns. Here, simple vector autoregressive models are used for forecasting the temperature hiatus in the period 2001-2014. This gives new insight into the problem of understanding the ocean contribution (in terms of heat uptake and atmosphere-ocean-coupled oscillations) to the appearance of this recent hiatus. In particular, considering data about the ocean heat content until a depth of 700 m and the Atlantic multidecadal oscillation is necessary for correctly forecasting the hiatus, so catching both trend and interannual variability. Our models also show that the ocean heat uptake is substantially driven by the natural component of the total radiative forcing at a decadal time scale, confining the importance of the anthropogenic influences to a longer range warming of the ocean.

Note: Vector network analyzer-ferromagnetic resonance spectrometer using high Q-factor cavity.

PubMed

Lo, C K; Lai, W C; Cheng, J C

2011-08-01

A ferromagnetic resonance (FMR) spectrometer whose main components consist of an X-band resonator and a vector network analyzer (VNA) was developed. This spectrometer takes advantage of a high Q-factor (9600) cavity and state-of-the-art VNA. Accordingly, field modulation lock-in technique for signal to noise ratio (SNR) enhancement is no longer necessary, and FMR absorption can therefore be extracted directly. Its derivative for the ascertainment of full width at half maximum height of FMR peak can be found by taking the differentiation of original data. This system was characterized with different thicknesses of permalloy (Py) films and its multilayer, and found that the SNR of 5 nm Py on glass was better than 50, and did not have significant reduction even at low microwave excitation power (-20 dBm), and at low Q-factor (3000). The FMR other than X-band can also be examined in the same manner by using a suitable band cavity within the frequency range of VNA.

On The Value at Risk Using Bayesian Mixture Laplace Autoregressive Approach for Modelling the Islamic Stock Risk Investment

NASA Astrophysics Data System (ADS)

Miftahurrohmah, Brina; Iriawan, Nur; Fithriasari, Kartika

2017-06-01

Stocks are known as the financial instruments traded in the capital market which have a high level of risk. Their risks are indicated by their uncertainty of their return which have to be accepted by investors in the future. The higher the risk to be faced, the higher the return would be gained. Therefore, the measurements need to be made against the risk. Value at Risk (VaR) as the most popular risk measurement method, is frequently ignore when the pattern of return is not uni-modal Normal. The calculation of the risks using VaR method with the Normal Mixture Autoregressive (MNAR) approach has been considered. This paper proposes VaR method couple with the Mixture Laplace Autoregressive (MLAR) that would be implemented for analysing the first three biggest capitalization Islamic stock return in JII, namely PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLMK), and PT. Unilever Indonesia Tbk (UNVR). Parameter estimation is performed by employing Bayesian Markov Chain Monte Carlo (MCMC) approaches.

Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control

PubMed Central

Stewart Ibarra, Anna M.; Ryan, Sadie J.; Beltrán, Efrain; Mejía, Raúl; Silva, Mercy; Muñoz, Ángel

2013-01-01

Background Dengue fever, a mosquito-borne viral disease, is now the fastest spreading tropical disease globally. Previous studies indicate that climate and human behavior interact to influence dengue virus and vector (Aedes aegypti) population dynamics; however, the relative effects of these variables depends on local ecology and social context. We investigated the roles of climate and socio-ecological factors on Ae. aegypti population dynamics in Machala, a city in southern coastal Ecuador where dengue is hyper-endemic. Methods/Principal findings We studied two proximate urban localities where we monitored weekly Ae. aegypti oviposition activity (Nov. 2010-June 2011), conducted seasonal pupal surveys, and surveyed household to identify dengue risk factors. The results of this study provide evidence that Ae. aegypti population dynamics are influenced by social risk factors that vary by season and lagged climate variables that vary by locality. Best-fit models to predict the presence of Ae. aegypti pupae included parameters for household water storage practices, access to piped water, the number of households per property, condition of the house and patio, and knowledge and perceptions of dengue. Rainfall and minimum temperature were significant predictors of oviposition activity, although the effect of rainfall varied by locality due to differences in types of water storage containers. Conclusions These results indicate the potential to reduce the burden of dengue in this region by conducting focused vector control interventions that target high-risk households and containers in each season and by developing predictive models using climate and non-climate information. These findings provide the region's public health sector with key information for conducting time and location-specific vector control campaigns, and highlight the importance of local socio-ecological studies to understand dengue dynamics. See Text S1 for an executive summary in Spanish. PMID:24324542

Stimulus augmenting and field dependence in children of alcoholic fathers.

PubMed

Hennecke, L

1984-11-01

The relationship between paternal alcoholism and two perceptual characteristics, stimulus augmenting and field dependence, was tested in boys and girls aged 10-12. Thirty children of alcoholic fathers, presumed at high risk for the disease because of its familial-genetic component, were compared with 30 children of nonalcoholic parents. Stimulus augmenting was measured by the Kinesthetic Figural After-Effect (KFA) test and field dependence by the Embedded Figures Test (EFT). It was reasoned that the consistent findings of field dependence in alcoholics could be a manifestation of brain damage and the consequent cognitive deficits often found in alcoholics. Thus it was proposed that field dependence would not differentiate the children of alcoholic fathers from those of nonalcoholics. No difference in field dependence was found between the groups, which supports other evidence that alcoholism can lead to field dependence. Since KFA scores revealed a significantly higher incidence of stimulus augmenters in the children of alcoholic fathers, it is proposed that stimulus augmenting is premorbid to alcoholism. It remains unclear, however, whether this phenomenon is due to an environmental or genetic factor.

Geographic range of vector-borne infections and their vectors: the role of African wildlife.

PubMed

van Vuuren, M; Penzhorn, B L

2015-04-01

The role of African wildlife in the occurrence of vector-borne infections in domestic animals has gained renewed interest as emerging and re-emerging infections occur worldwide at an increasing rate. In Africa, biodiversity conservation and the expansion of livestock production have increased the risk of transmitting vector-borne infections between wildlife and livestock. The indigenous African pathogens with transboundary potential, such as Rift Valley fever virus, African horse sickness virus, bluetongue virus, lumpy skin disease virus, African swine fever virus, and blood-borne parasites have received the most attention. There is no evidence for persistent vector-borne viral infections in African wildlife. For some viral infections, wildlife may act as a reservoir through the inter-epidemic circulation of viruses with mild or subclinical manifestations. Wildlife may also act as introductory or transporting hosts when moved to new regions, e.g. for lumpy skin disease virus, Rift Valley fever virus and West Nile virus. Wildlife may also act as amplifying hosts when exposed to viruses in the early part of the warm season when vectors are active, with spillover to domestic animals later in the season, e.g. with bluetongue and African horse sickness. Some tick species found on domestic animals are more abundant on wildlife hosts; some depend on wildlife hosts to complete their life cycle. Since the endemic stability of a disease depends on a sufficiently large tick population to ensure that domestic animals become infected at an early age, the presence of wildlife hosts that augment tick numbers may be beneficial. Many wild ungulate species are reservoirs of Anaplasma spp., while the role of wildlife in the epidemiology of heartwater (Ehrlichia ruminantium infection) has not been elucidated. Wild ungulates are not usually reservoirs of piroplasms that affect livestock; however, there are two exceptions: zebra, which are reservoirs of Babesia caballi and Theileria

[Augmentation with PMMA cement].

PubMed

Kühn, K-D; Höntzsch, D

2015-09-01

Cements based on polymethyl methacrylate (PMMA) can be used without any problem in a variety of clinical augmentations. Cement-related complications in surgical procedures involving PMMA cements, such as embolism, thermal necrosis, toxicity and hypersensitivity, are often due to other causes. Knowledge about the properties of the cement helps the user to safely employ PMMA cements in augmentations. High radio-opacity is required in vertebral body augmentations and this is provided in particular by zirconium dioxide. In vertebral body augmentations, a low benzoyl peroxide (BPO) content can considerably prolong the liquid dough phase. In augmentations with cement fillings in the region of a tumor, a high BPO content can specifically increase the peak temperature of the PMMA cement. In osteosynthetic augmentations with PMMA, necrosis is rare because heat development in the presence of metallic implants is low due to heat conduction via the implant. Larger cement fillings where there is no heat conduction via metal implants can exhibit substantially higher peak temperatures. The flow properties of PMMA cements are of particular importance for the user to allow optimum handling of PMMA cements. In patients with hypersensitivity to antibiotics, there is no need to avoid the use of PMMA as there are sufficient PMMA-based alternatives. The PMMA cements are local drug delivery systems and antibiotics, antiseptics, antimycotics and also cytostatics can be mixed with the cement. Attention must be paid to antagonistic and synergistic effects.

A hybrid least squares support vector machines and GMDH approach for river flow forecasting

NASA Astrophysics Data System (ADS)

Samsudin, R.; Saad, P.; Shabri, A.

2010-06-01

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

Augmented reality: a review.

PubMed

Berryman, Donna R

2012-01-01

Augmented reality is a technology that overlays digital information on objects or places in the real world for the purpose of enhancing the user experience. It is not virtual reality, that is, the technology that creates a totally digital or computer created environment. Augmented reality, with its ability to combine reality and digital information, is being studied and implemented in medicine, marketing, museums, fashion, and numerous other areas. This article presents an overview of augmented reality, discussing what it is, how it works, its current implementations, and its potential impact on libraries.

Comparisons of Four Methods for Estimating a Dynamic Factor Model

ERIC Educational Resources Information Center

Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.

2008-01-01

Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…

2-Dimensional changes of the soft tissue profile of augmented and non-augmented human extraction sockets: a randomized pilot study.

PubMed

Flügge, Tabea; Nelson, Katja; Nack, Claudia; Stricker, Andres; Nahles, Susanne

2015-04-01

This study identified the soft tissue changes of the alveolar ridge at different time points within 12 weeks after tooth extraction with and without socket augmentation. In 38 patients with single tooth extractions, 40 sockets were augmented and 39 extraction sockets were not augmented. At 2, 4, 6, 8 and 12 weeks impressions were taken and casts digitized with a laser scanner. The horizontal and vertical changes were compared between augmented and non-augmented sites. A p-value <0.05 was considered statistically significant. The mean changes of augmented sockets were between 0.4 mm (2 weeks) and 0.8 mm (12 weeks). In non-augmented sockets changes of 0.7 mm (2 weeks) and of 1.0 mm (12 weeks) were demonstrated. The mean values differed significantly between the buccal and oral region (p < 0.01). Overall, there were significant differences of the mean dimensional changes regarding time (p < 0.01) and augmentation (p < 0.01). Augmented sockets showed less resorption within 4 weeks after extraction compared to non-augmented sockets. Non-augmented sockets showed a continuous dimensional loss with a great variation over 12 weeks whereas augmented sockets had the highest degree of resorption between 4 and 6 weeks. At 12 weeks a comparable resorption in augmented and non-augmented sockets was observed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The nucleon as a test case to calculate vector-isovector form factors at low energies

NASA Astrophysics Data System (ADS)

Leupold, Stefan

2018-01-01

Extending a recent suggestion for hyperon form factors to the nucleon case, dispersion theory is used to relate the low-energy vector-isovector form factors of the nucleon to the pion vector form factor. The additionally required input, i.e. the pion-nucleon scattering amplitudes are determined from relativistic next-to-leading-order (NLO) baryon chiral perturbation theory including the nucleons and optionally the Delta baryons. Two methods to include pion rescattering are compared: a) solving the Muskhelishvili-Omnès (MO) equation and b) using an N/D approach. It turns out that the results differ strongly from each other. Furthermore the results are compared to a fully dispersive calculation of the (subthreshold) pion-nucleon amplitudes based on Roy-Steiner (RS) equations. In full agreement with the findings from the hyperon sector it turns out that the inclusion of Delta baryons is not an option but a necessity to obtain reasonable results. The magnetic isovector form factor depends strongly on a low-energy constant of the NLO Lagrangian. If it is adjusted such that the corresponding magnetic radius is reproduced, then the results for the corresponding pion-nucleon scattering amplitude (based on the MO equation) agree very well with the RS results. Also in the electric sector the Delta degrees of freedom are needed to obtain the correct order of magnitude for the isovector charge and the corresponding electric radius. Yet quantitative agreement is not achieved. If the subtraction constant that appears in the solution of the MO equation is not taken from nucleon+Delta chiral perturbation theory but adjusted such that the electric radius is reproduced, then one obtains also in this sector a pion-nucleon scattering amplitude that agrees well with the RS results.

Effects of augmented reality-based Otago exercise on balance, gait, and physical factors in elderly women to prevent falls: a randomized controlled trial.

PubMed

Lee, Jin; Yoo, Ha-Na; Lee, Byoung-Hee

2017-09-01

[Purpose] To determine the effect of augmented reality (AR)-based otago exercise on muscle strength, balance, and physical factors in falls of elderly women. [Subjects and Methods] Thirty subjects were randomly assigned to AR group (AR, n=10), yoga group (yoga, n=10), and self-exercise group (self, n=10). For 12 weeks, these groups were given lessons related to AR-based otago exercise including strengthening, balance training, or yoga three times a week (60 minutes each time) and self-exercise using elastic band exercise program. [Results] Knee flexion and ankle dorsiflexion strength were significantly improved in all three groups (AR, yoga, and self-exercise groups). Regarding balance, eye open center of pressure-x (EO CoP-x) was significantly decreased in AR group and yoga group. However, eye close CoP-x, eye open standard deviation-x (EO SD-x), and eye open height of ellipse (EO HoE) were only significantly decreased in AR group. AR group also showed meaningfully improved results in morse fall scale. [Conclusion] Augmented reality-based otago exercise can improve muscle strength, balance, and physical factors in elderly women to prevent falls.

Insecticide resistance in the dengue vector Aedes aegypti from Martinique: distribution, mechanisms and relations with environmental factors.

PubMed

Marcombe, Sébastien; Mathieu, Romain Blanc; Pocquet, Nicolas; Riaz, Muhammad-Asam; Poupardin, Rodolphe; Sélior, Serge; Darriet, Frédéric; Reynaud, Stéphane; Yébakima, André; Corbel, Vincent; David, Jean-Philippe; Chandre, Fabrice

2012-01-01

Dengue is an important mosquito borne viral disease in Martinique Island (French West Indies). The viruses responsible for dengue are transmitted by Aedes aegypti, an indoor day-biting mosquito. The most effective proven method for disease prevention has been by vector control by various chemical or biological means. Unfortunately insecticide resistance has already been observed on the Island and recently showed to significantly reduce the efficacy of vector control interventions. In this study, we investigated the distribution of resistance and the underlying mechanisms in nine Ae. aegypti populations. Statistical multifactorial approach was used to investigate the correlations between insecticide resistance levels, associated mechanisms and environmental factors characterizing the mosquito populations. Bioassays revealed high levels of resistance to temephos and deltamethrin and susceptibility to Bti in the 9 populations tested. Biochemical assays showed elevated detoxification enzyme activities of monooxygenases, carboxylesterases and glutathione S-tranferases in most of the populations. Molecular screening for common insecticide target-site mutations, revealed the presence of the "knock-down resistance" V1016I Kdr mutation at high frequency (>87%). Real time quantitative RT-PCR showed the potential involvement of several candidate detoxification genes in insecticide resistance. Principal Component Analysis (PCA) performed with variables characterizing Ae. aegypti from Martinique permitted to underline potential links existing between resistance distribution and other variables such as agriculture practices, vector control interventions and urbanization. Insecticide resistance is widespread but not homogeneously distributed across Martinique. The influence of environmental and operational factors on the evolution of the resistance and mechanisms are discussed.

Insecticide Resistance in the Dengue Vector Aedes aegypti from Martinique: Distribution, Mechanisms and Relations with Environmental Factors

PubMed Central

Marcombe, Sébastien; Mathieu, Romain Blanc; Pocquet, Nicolas; Riaz, Muhammad-Asam; Poupardin, Rodolphe; Sélior, Serge; Darriet, Frédéric; Reynaud, Stéphane; Yébakima, André; Corbel, Vincent; David, Jean-Philippe; Chandre, Fabrice

2012-01-01

Dengue is an important mosquito borne viral disease in Martinique Island (French West Indies). The viruses responsible for dengue are transmitted by Aedes aegypti, an indoor day-biting mosquito. The most effective proven method for disease prevention has been by vector control by various chemical or biological means. Unfortunately insecticide resistance has already been observed on the Island and recently showed to significantly reduce the efficacy of vector control interventions. In this study, we investigated the distribution of resistance and the underlying mechanisms in nine Ae. aegypti populations. Statistical multifactorial approach was used to investigate the correlations between insecticide resistance levels, associated mechanisms and environmental factors characterizing the mosquito populations. Bioassays revealed high levels of resistance to temephos and deltamethrin and susceptibility to Bti in the 9 populations tested. Biochemical assays showed elevated detoxification enzyme activities of monooxygenases, carboxylesterases and glutathione S-tranferases in most of the populations. Molecular screening for common insecticide target-site mutations, revealed the presence of the “knock-down resistance” V1016I Kdr mutation at high frequency (>87%). Real time quantitative RT-PCR showed the potential involvement of several candidate detoxification genes in insecticide resistance. Principal Component Analysis (PCA) performed with variables characterizing Ae. aegypti from Martinique permitted to underline potential links existing between resistance distribution and other variables such as agriculture practices, vector control interventions and urbanization. Insecticide resistance is widespread but not homogeneously distributed across Martinique. The influence of environmental and operational factors on the evolution of the resistance and mechanisms are discussed. PMID:22363529

Augmentation of the ascending component of the peristaltic reflex and substance P release by glial cell line-derived neurotrophic factor.

PubMed

Grider, J R; Heuckeroth, R O; Kuemmerle, J F; Murthy, K S

2010-07-01

Glial cell line-derived neurotrophic factor (GDNF) is present in adult gut although its role in the mature enteric nervous system is not well defined. The aim of the present study was to examine the role of GDNF as neuromodulator of the ascending phase of the peristaltic reflex. Colonic segments were prepared as flat sheets and placed in compartmented chambers so as to separate the sensory and motor limbs of the reflex. Ascending contraction was measured in the orad compartment and mucosal stroking stimuli (two to eight strokes) were applied in the caudad compartment. GDNF and substance P (SP) release were measured and the effects of GDNF and GDNF antibody on contraction and release were determined. Mice with reduced levels of GDNF (Gdnf(+/-)) and wild type littermates were also examined. GDNF was released in a stimulus-dependent manner into the orad motor but not caudad sensory compartment. Addition of GDNF to the orad motor but not caudad sensory compartment augmented ascending contraction and SP release. Conversely, addition of GDNF antibody to the orad motor but not caudad sensory compartment reduced ascending contraction and SP release. Similarly, the ascending contraction and SP release into the orad motor compartment was reduced in Gdnf(+/-) mice as compared to wild type littermates. The results suggest that endogenous GDNF is released during the ascending contraction component of the peristaltic reflex where it acts as a neuromodulator to augment SP release from motor neurons thereby augmenting contraction of circular muscle orad to the site of stimulation.

Induction of Shock After Intravenous Injection of Adenovirus Vectors: A Critical Role for Platelet-activating Factor

PubMed Central

Xu, Zhili; Smith, Jeffrey S.; Tian, Jie; Byrnes, Andrew P.

2009-01-01

Innate immune responses are a major barrier to safe systemic gene therapy with adenovirus (Ad) vectors. We show that intravenous (IV) injection of rats with Ad5 vectors causes a novel rapid shock reaction that involves hypotension, hemoconcentration, tissue edema, and vasocongestion, with notable pathology in the pancreas and the gastrointestinal system. We show for the first time that this reaction is dependent on platelet-activating factor (PAF), a lipid signaling molecule that is a known shock inducer. Ad upregulated PAF within 5 minutes in vivo, and antagonists of the PAF receptor were able to prevent Ad-induced shock. Ad upregulated PAF via the reticuloendothelial system (RES), because splenectomy or depletion of phagocytes blocked the ability of Ad to induce both PAF and shock. Rats were considerably more sensitive to Ad-induced shock than were mice, but PAF mediated shock in both species. Other Ad-induced innate immune responses such as cytokine induction and thrombocytopenia were not mediated by PAF. In summary, systemic IV injection of Ad stimulates the RES to upregulate PAF within a matter of minutes, which results in shock. The identification of this novel pathway suggests strategies to improve the safety of systemic gene therapy with Ad vectors. PMID:19953082

Augmented Reality for the Improvement of Remote Laboratories: An Augmented Remote Laboratory

ERIC Educational Resources Information Center

Andujar, J. M.; Mejias, A.; Marquez, M. A.

2011-01-01

Augmented reality (AR) provides huge opportunities for online teaching in science and engineering, as these disciplines place emphasis on practical training and unsuited to completely nonclassroom training. This paper proposes a new concept in virtual and remote laboratories: the augmented remote laboratory (ARL). ARL is being tested in the first…

Dynamic augmentation restores anterior tibial translation in ACL suture repair: a biomechanical comparison of non-, static and dynamic augmentation techniques.

PubMed

Hoogeslag, Roy A G; Brouwer, Reinoud W; Huis In 't Veld, Rianne; Stephen, Joanna M; Amis, Andrew A

2018-02-03

There is a lack of objective evidence investigating how previous non-augmented ACL suture repair techniques and contemporary augmentation techniques in ACL suture repair restrain anterior tibial translation (ATT) across the arc of flexion, and after cyclic loading of the knee. The purpose of this work was to test the null hypotheses that there would be no statistically significant difference in ATT after non-, static- and dynamic-augmented ACL suture repair, and they will not restore ATT to normal values across the arc of flexion of the knee after cyclic loading. Eleven human cadaveric knees were mounted in a test rig, and knee kinematics from 0° to 90° of flexion were recorded by use of an optical tracking system. Measurements were recorded without load and with 89-N tibial anterior force. The knees were tested in the following states: ACL-intact, ACL-deficient, non-augmented suture repair, static tape augmentation and dynamic augmentation after 10 and 300 loading cycles. Only static tape augmentation and dynamic augmentation restored ATT to values similar to the ACL-intact state directly postoperation, and maintained this after cyclic loading. However, contrary to dynamic augmentation, the ATT after static tape augmentation failed to remain statistically less than for the ACL-deficient state after cyclic loading. Moreover, after cyclic loading, ATT was significantly less with dynamic augmentation when compared to static tape augmentation. In contrast to non-augmented ACL suture repair and static tape augmentation, only dynamic augmentation resulted in restoration of ATT values similar to the ACL-intact knee and decreased ATT values when compared to the ACL-deficient knee immediately post-operation and also after cyclic loading, across the arc of flexion, thus allowing the null hypotheses to be rejected. This may assist healing of the ruptured ACL. Therefore, this study would support further clinical evaluation of dynamic augmentation of ACL repair.

Vector-virus interactions and transmission dynamics of West Nile virus.

PubMed

Ciota, Alexander T; Kramer, Laura D

2013-12-09

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission.

Vector-Virus Interactions and Transmission Dynamics of West Nile Virus

PubMed Central

Ciota, Alexander T.; Kramer, Laura D.

2013-01-01

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission. PMID:24351794

Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

PubMed

Witoonchart, Peerajak; Chongstitvatana, Prabhas

2017-08-01

In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

Condition Monitoring for Helicopter Data. Appendix A

NASA Technical Reports Server (NTRS)

Wen, Fang; Willett, Peter; Deb, Somnath

2000-01-01

In this paper the classical "Westland" set of empirical accelerometer helicopter data is analyzed with the aim of condition monitoring for diagnostic purposes. The goal is to determine features for failure events from these data, via a proprietary signal processing toolbox, and to weigh these according to a variety of classification algorithms. As regards signal processing, it appears that the autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; it has also been found that augmentation of these by harmonic and other parameters can improve classification significantly. As regards classification, several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior on training data and is thus able to quantify probability of error in an exact manner, such that features may be discarded or coarsened appropriately.

Reductive Augmentation of the Breast.

PubMed

Chasan, Paul E

2018-06-01

Although breast reduction surgery plays an invaluable role in the correction of macromastia, it almost always results in a breast lacking in upper pole fullness and/or roundness. We present a technique of breast reduction combined with augmentation termed "reductive augmentation" to solve this problem. The technique is also extremely useful for correcting breast asymmetry, as well as revising significant pseudoptosis in the patient who has previously undergone breast augmentation with or without mastopexy. An evolution of techniques has been used to create a breast with more upper pole fullness and anterior projection in those patients desiring a more round, higher-profile appearance. Reductive augmentation is a one-stage procedure in which a breast augmentation is immediately followed by a modified superomedial pedicle breast reduction. Often, the excision of breast tissue is greater than would normally be performed with breast reduction alone. Thirty-five patients underwent reductive augmentation, of which 12 were primary surgeries and 23 were revisions. There was an average tissue removal of 255 and 227 g, respectively, per breast for the primary and revision groups. Six of the reductive augmentations were performed for gross asymmetry. Fourteen patients had a previous mastopexy, and 3 patients had a previous breast reduction. The average follow-up was 26 months. Reductive augmentation is an effective one-stage method for achieving a more round-appearing breast with upper pole fullness both in primary breast reduction candidates and in revisionary breast surgery. This technique can also be applied to those patients with significant asymmetry. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Robust RNAi enhancement via human Argonaute-2 overexpression from plasmids, viral vectors and cell lines

PubMed Central

Börner, Kathleen; Niopek, Dominik; Cotugno, Gabriella; Kaldenbach, Michaela; Pankert, Teresa; Willemsen, Joschka; Zhang, Xian; Schürmann, Nina; Mockenhaupt, Stefan; Serva, Andrius; Hiet, Marie-Sophie; Wiedtke, Ellen; Castoldi, Mirco; Starkuviene, Vytaute; Erfle, Holger; Gilbert, Daniel F.; Bartenschlager, Ralf; Boutros, Michael; Binder, Marco; Streetz, Konrad; Kräusslich, Hans-Georg; Grimm, Dirk

2013-01-01

As the only mammalian Argonaute protein capable of directly cleaving mRNAs in a small RNA-guided manner, Argonaute-2 (Ago2) is a keyplayer in RNA interference (RNAi) silencing via small interfering (si) or short hairpin (sh) RNAs. It is also a rate-limiting factor whose saturation by si/shRNAs limits RNAi efficiency and causes numerous adverse side effects. Here, we report a set of versatile tools and widely applicable strategies for transient or stable Ago2 co-expression, which overcome these concerns. Specifically, we engineered plasmids and viral vectors to co-encode a codon-optimized human Ago2 cDNA along with custom shRNAs. Furthermore, we stably integrated this Ago2 cDNA into a panel of standard human cell lines via plasmid transfection or lentiviral transduction. Using various endo- or exogenous targets, we demonstrate the potential of all three strategies to boost mRNA silencing efficiencies in cell culture by up to 10-fold, and to facilitate combinatorial knockdowns. Importantly, these robust improvements were reflected by augmented RNAi phenotypes and accompanied by reduced off-targeting effects. We moreover show that Ago2/shRNA-co-encoding vectors can enhance and prolong transgene silencing in livers of adult mice, while concurrently alleviating hepatotoxicity. Our customizable reagents and avenues should broadly improve future in vitro and in vivo RNAi experiments in mammalian systems. PMID:24049077

Testing the Causal Links between School Climate, School Violence, and School Academic Performance: A Cross-Lagged Panel Autoregressive Model

ERIC Educational Resources Information Center

Benbenishty, Rami; Astor, Ron Avi; Roziner, Ilan; Wrabel, Stephani L.

2016-01-01

The present study explores the causal link between school climate, school violence, and a school's general academic performance over time using a school-level, cross-lagged panel autoregressive modeling design. We hypothesized that reductions in school violence and climate improvement would lead to schools' overall improved academic performance.…

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

PubMed

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P<0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are

(Re)evaluating the Implications of the Autoregressive Latent Trajectory Model Through Likelihood Ratio Tests of Its Initial Conditions.

PubMed

Ou, Lu; Chow, Sy-Miin; Ji, Linying; Molenaar, Peter C M

2017-01-01

The autoregressive latent trajectory (ALT) model synthesizes the autoregressive model and the latent growth curve model. The ALT model is flexible enough to produce a variety of discrepant model-implied change trajectories. While some researchers consider this a virtue, others have cautioned that this may confound interpretations of the model's parameters. In this article, we show that some-but not all-of these interpretational difficulties may be clarified mathematically and tested explicitly via likelihood ratio tests (LRTs) imposed on the initial conditions of the model. We show analytically the nested relations among three variants of the ALT model and the constraints needed to establish equivalences. A Monte Carlo simulation study indicated that LRTs, particularly when used in combination with information criterion measures, can allow researchers to test targeted hypotheses about the functional forms of the change process under study. We further demonstrate when and how such tests may justifiably be used to facilitate our understanding of the underlying process of change using a subsample (N = 3,995) of longitudinal family income data from the National Longitudinal Survey of Youth.

Augmented assessment as a means to augmented reality.

PubMed

Bergeron, Bryan

2006-01-01

Rigorous scientific assessment of educational technologies typically lags behind the availability of the technologies by years because of the lack of validated instruments and benchmarks. Even when the appropriate assessment instruments are available, they may not be applied because of time and monetary constraints. Work in augmented reality, instrumented mannequins, serious gaming, and similar promising educational technologies that haven't undergone timely, rigorous evaluation, highlights the need for assessment methodologies that address the limitations of traditional approaches. The most promising augmented assessment solutions incorporate elements of rapid prototyping used in the software industry, simulation-based assessment techniques modeled after methods used in bioinformatics, and object-oriented analysis methods borrowed from object oriented programming.

A prospective, randomized pilot study on the safety and efficacy of recombinant human growth and differentiation factor-5 coated onto β-tricalcium phosphate for sinus lift augmentation.

PubMed

Koch, Felix P; Becker, Jürgen; Terheyden, Hendrik; Capsius, Björn; Wagner, Wilfried

2010-11-01

The aim of this prospective, randomized clinical trial was to investigate the potential of recombinant human growth and differentiation factor-5 (rhGDF-5) coated onto β-tricalcium phosphate (β-TCP) (rhGDF-5/β-TCP) to support bone formation after sinus lift augmentation. In total, 31 patients participated in this multicenter clinical trial. They required a two-stage unilateral maxillary sinus floor augmentation (residual bone height <5 mm). According to a parallel-group design, the patients were randomized to three treatment groups: (a) augmentation with rhGDF-5/β-TCP and a 3-month healing period, (b) augmentation with rhGDF-5/β-TCP and a 4-month healing period and (c) medical device β-TCP mixed with autologous bone and a 4-month healing period. The primary study objective was the area of newly formed bone within the augmented area as assessed by histomorphometric evaluation of trephine bur biopsies. The osseous regeneration was similar in each treatment group; the amount of newly formed bone ranged between 28% (± 15.5%) and 31.8% (± 17.9%). Detailed analysis of histological data will be published elsewhere. As secondary efficacy variables, the augmentation height at the surgery site was measured by radiography. The largest augmentation was radiologically achieved in the rhGDF-5/β-TCP - 3-month and the rhGDF-5/β-TCP - 4-month treatment groups. As safety parameters, adverse events were recorded and anti-drug antibody levels were evaluated. Most of the adverse events were judged as unrelated to the study medication. Four out of 47 (8.5%) implants failed in patients treated with rhGDF-5/β-TCP, a result that is in agreement with the general implant failure rate of 5-15%. Transiently very low amounts of anti-rhGDF-5 antibodies were detected in some patients who received rhGDF-5, which was not related to the bone formation outcome. rhGDF-5/β-TCP was found to be effective and safe as the control treatment with autologous bone mixed β-TCP in sinus floor

Vector-based RNA interference against vascular endothelial growth factor-A significantly limits vascularization and growth of prostate cancer in vivo.

PubMed

Wannenes, Francesca; Ciafré, Silvia Anna; Niola, Francesco; Frajese, Gaetano; Farace, Maria Giulia

2005-12-01

RNA interference technology is emerging as a very potent tool to obtain a cellular knockdown of a desired gene. In this work we used vector-based RNA interference to inhibit vascular endothelial growth factor (VEGF) expression in prostate cancer in vitro and in vivo. We demonstrated that transduction with a plasmid carrying a small interfering RNA targeting all isoforms of VEGF, dramatically impairs the expression of this growth factor in the human prostate cancer cell line PC3. As a consequence, PC3 cells loose their ability to induce one of the fundamental steps of angiogenesis, namely the formation of a tube-like network in vitro. Most importantly, our "therapeutic" vector is able to impair tumor growth rate and vascularization in vivo. We show that a single injection of naked plasmid in developing neoplastic mass significantly decreases microvessel density in an androgen-refractory prostate xenograft and is able to sustain a long-term slowing down of tumor growth. In conclusion, our results confirm the basic role of VEGF in the angiogenic development of prostate carcinoma, and suggest that the use of our vector-based RNA interference approach to inhibit angiogenesis could be an effective tool in view of future gene therapy applications for prostate cancer.

Remote sensing, global warming, and vector-borne disease

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

Wood, B.; Beck, L.; Dister, S.

1997-12-31

The relationship between climate change and the pattern of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are changes such as global warming, which are continental in scale and occur over periods of years, decades, or longer. At the opposite extreme are changes associated with severe weather events, which can occur at local and regional scales over periods of days, weeks, or months. Key ecological factors affecting the distribution of vector-borne diseases include temperature, precipitation, and habitat availability, and their impact on vectors, pathogens, reservoirs, and hosts. Global warming can potentially altermore » these factors, thereby affecting the spatial and temporal patterns of disease.« less

Pedicle screw cement augmentation. A mechanical pullout study on different cement augmentation techniques.

PubMed

Costa, Francesco; Ortolina, Alessandro; Galbusera, Fabio; Cardia, Andrea; Sala, Giuseppe; Ronchi, Franco; Uccelli, Carlo; Grosso, Rossella; Fornari, Maurizio

2016-02-01

Pedicle screws with polymethyl methacrylate (PMMA) cement augmentation have been shown to significantly improve the fixation strength in a severely osteoporotic spine. However, the efficacy of screw fixation for different cement augmentation techniques remains unknown. This study aimed to determine the difference in pullout strength between different cement augmentation techniques. Uniform synthetic bones simulating severe osteoporosis were used to provide a platform for each augmentation technique. In all cases a polyaxial screw and acrylic cement (PMMA) at medium viscosity were used. Five groups were analyzed: I) only screw without PMMA (control group); II) retrograde cement pre-filling of the tapped area; III) cannulated and fenestrate screw with cement injection through perforation; IV) injection using a standard trocar of PMMA (vertebroplasty) and retrograde pre-filling of the tapped area; V) injection through a fenestrated trocar and retrograde pre-filling of the tapped area. Standard X-rays were taken in order to visualize cement distribution in each group. Pedicle screws at full insertion were then tested for axial pullout failure using a mechanical testing machine. A total of 30 screws were tested. The results of pullout analysis revealed better results of all groups with respect to the control group. In particular the statistical analysis showed a difference of Group V (p = 0.001) with respect to all other groups. These results confirm that the cement augmentation grants better results in pullout axial forces. Moreover they suggest better load resistance to axial forces when the distribution of the PMMA is along all the screw combining fenestration and pre-filling augmentation technique. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

A feature selection approach towards progressive vector transmission over the Internet

NASA Astrophysics Data System (ADS)

Miao, Ru; Song, Jia; Feng, Min

2017-09-01

WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

Construction, Analysis, and Data-Driven Augmentation of Supersaturated Designs

DTIC Science & Technology

2013-09-01

guidelines and considerations. 27 Table 7. Supersaturated Design Example with 8 Runs and 14 Factors Design Factors Run x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11...much larger than the guidelines proposed by Marley 55 and Woods (2010). They recommend the factor-to-run ratio should be less than 2. Because our ratio...established approach in experimental design: Box (1992) provided general guidelines to consider, and traditional augmentation strategies like fold-over

Augmented Reality: A Brand New Challenge for the Assessment and Treatment of Psychological Disorders

PubMed Central

Chicchi Giglioli, Irene Alice; Pedroli, Elisa

2015-01-01

Augmented Reality is a new technological system that allows introducing virtual contents in the real world in order to run in the same representation and, in real time, enhancing the user's sensory perception of reality. From another point of view, Augmented Reality can be defined as a set of techniques and tools that add information to the physical reality. To date, Augmented Reality has been used in many fields, such as medicine, entertainment, maintenance, architecture, education, and cognitive and motor rehabilitation but very few studies and applications of AR exist in clinical psychology. In the treatment of psychological disorders, Augmented Reality has given preliminary evidence to be a useful tool due to its adaptability to the patient needs and therapeutic purposes and interactivity. Another relevant factor is the quality of the user's experience in the Augmented Reality system determined from emotional engagement and sense of presence. This experience could increase the AR ecological validity in the treatment of psychological disorders. This paper reviews the recent studies on the use of Augmented Reality in the evaluation and treatment of psychological disorders, focusing on current uses of this technology and on the specific features that delineate Augmented Reality a new technique useful for psychology. PMID:26339283

Augmented Reality: A Brand New Challenge for the Assessment and Treatment of Psychological Disorders.

PubMed

Chicchi Giglioli, Irene Alice; Pallavicini, Federica; Pedroli, Elisa; Serino, Silvia; Riva, Giuseppe

2015-01-01

Augmented Reality is a new technological system that allows introducing virtual contents in the real world in order to run in the same representation and, in real time, enhancing the user's sensory perception of reality. From another point of view, Augmented Reality can be defined as a set of techniques and tools that add information to the physical reality. To date, Augmented Reality has been used in many fields, such as medicine, entertainment, maintenance, architecture, education, and cognitive and motor rehabilitation but very few studies and applications of AR exist in clinical psychology. In the treatment of psychological disorders, Augmented Reality has given preliminary evidence to be a useful tool due to its adaptability to the patient needs and therapeutic purposes and interactivity. Another relevant factor is the quality of the user's experience in the Augmented Reality system determined from emotional engagement and sense of presence. This experience could increase the AR ecological validity in the treatment of psychological disorders. This paper reviews the recent studies on the use of Augmented Reality in the evaluation and treatment of psychological disorders, focusing on current uses of this technology and on the specific features that delineate Augmented Reality a new technique useful for psychology.

Factors affecting the initial adhesion and retention of the plant pathogen Xylella fastidiosa in the foregut of an insect vector.

PubMed

Killiny, Nabil; Almeida, Rodrigo P P

2014-01-01

Vector transmission of bacterial plant pathogens involves three steps: pathogen acquisition from an infected host, retention within the vector, and inoculation of cells into susceptible tissue of an uninfected plant. In this study, a combination of plant and artificial diet systems were used to determine the importance of several genes on the initial adhesion and retention of the bacterium Xylella fastidiosa to an efficient insect vector. Mutant strains included fimbrial (fimA and pilB) and afimbrial (hxfA and hxfB) adhesins and three loci involved in regulatory systems (rpfF, rpfC, and cgsA). Transmission assays with variable retention time indicated that HxfA and HxfB were primarily important for early adhesion to vectors, while FimA was necessary for both adhesion and retention. The long pilus protein PilB was not deficient in initial adhesion but may be important for retention. Genes upregulated under the control of rpfF are important for both initial adhesion and retention, as transmission rates of this mutant strain were initially low and decreased over time, while disruption of rpfC and cgsA yielded trends similar to that shown by the wild-type control. Because induction of an X. fastidiosa transmissible state requires pectin, a series of experiments were used to test the roles of a polygalacturonase (pglA) and the pectin and galacturonic acid carbohydrates on the transmission of X. fastidiosa. Results show that galacturonic acid, or PglA activity breaking pectin into its major subunit (galacturonic acid), is required for X. fastidiosa vector transmission using an artificial diet system. This study shows that early adhesion and retention of X. fastidiosa are mediated by different factors. It also illustrates that the interpretation of results of vector transmission experiments, in the context of vector-pathogen interaction studies, is highly dependent on experimental design.

Factors Affecting the Initial Adhesion and Retention of the Plant Pathogen Xylella fastidiosa in the Foregut of an Insect Vector

PubMed Central

Almeida, Rodrigo P. P.

2014-01-01

Vector transmission of bacterial plant pathogens involves three steps: pathogen acquisition from an infected host, retention within the vector, and inoculation of cells into susceptible tissue of an uninfected plant. In this study, a combination of plant and artificial diet systems were used to determine the importance of several genes on the initial adhesion and retention of the bacterium Xylella fastidiosa to an efficient insect vector. Mutant strains included fimbrial (fimA and pilB) and afimbrial (hxfA and hxfB) adhesins and three loci involved in regulatory systems (rpfF, rpfC, and cgsA). Transmission assays with variable retention time indicated that HxfA and HxfB were primarily important for early adhesion to vectors, while FimA was necessary for both adhesion and retention. The long pilus protein PilB was not deficient in initial adhesion but may be important for retention. Genes upregulated under the control of rpfF are important for both initial adhesion and retention, as transmission rates of this mutant strain were initially low and decreased over time, while disruption of rpfC and cgsA yielded trends similar to that shown by the wild-type control. Because induction of an X. fastidiosa transmissible state requires pectin, a series of experiments were used to test the roles of a polygalacturonase (pglA) and the pectin and galacturonic acid carbohydrates on the transmission of X. fastidiosa. Results show that galacturonic acid, or PglA activity breaking pectin into its major subunit (galacturonic acid), is required for X. fastidiosa vector transmission using an artificial diet system. This study shows that early adhesion and retention of X. fastidiosa are mediated by different factors. It also illustrates that the interpretation of results of vector transmission experiments, in the context of vector-pathogen interaction studies, is highly dependent on experimental design. PMID:24185853

Augmentation of the Ascending Component of the Peristaltic Reflex and Substance P Release by Glial Cell Line-Derived Neurotrophic Factor (GDNF)

PubMed Central

Grider, JR; Heuckeroth, RO; Kuemmerle, JF; Murthy, KS

2010-01-01

Glial cell line derived neurotrophic factor (GDNF) is present in adult gut although its role in the mature enteric nervous system is not well defined. The aim of the present study was to examine the role of GDNF as neuromodulator of the ascending phase of the peristaltic reflex. Colonic segments were prepared as flat sheets and placed in compartmented chambers so as to separate the sensory and motor limbs of the reflex. Ascending contraction was measured in the orad compartment and mucosal stroking stimuli (2-8 strokes) were applied in the caudad compartment. GDNF and substance P release were measured and the effects of GDNF and GDNF antibody on contraction and release were determined. Mice with reduced levels of GDNF (Gdnf+/-) and wild type littermates were also examined. GDNF was released in a stimulus-dependent manner into the orad motor but not caudad sensory compartment. Addition of GDNF to the orad motor but not caudad sensory compartment augmented ascending contraction and substance P release. Conversely, addition of GDNF antibody to the orad motor but not caudad sensory compartment reduced ascending contraction and substance P release. Similarly, the ascending contraction and substance P release into the orad motor compartment was reduced in Gdnf+/- mice as compared to wild type littermates. The results suggest that endogenous GDNF is released during the ascending contraction component of the peristaltic reflex where it acts as a neuromodulator to augment substance P release from motor neurons thereby augmenting contraction of circular muscle orad to the site of stimulation. PMID:20331804

What makes an effective Chagas disease vector? Factors underlying Trypanosoma cruzi-triatomine interactions.

PubMed

de Fuentes-Vicente, José A; Gutiérrez-Cabrera, Ana E; Flores-Villegas, A Laura; Lowenberger, Carl; Benelli, Giovanni; Salazar-Schettino, Paz M; Córdoba-Aguilar, Alex

2018-07-01

The Chagas disease is caused by the parasite Trypanosoma cruzi, which infect blood-feeding triatomine bugs to finally reach mammal hosts. Chagas disease is endemic in Latin America, and is ranked among the 13 neglected tropical diseases worldwide. Currently, an estimate of 7 million people is infected by T. cruzi, leading to about 22 000 deaths per year throughout the Americas. As occurs with other vectors, a major question towards control programs is what makes a susceptible bug. In this review, we focus on findings linked to insect gut structure and microbiota, immunity, genetics, blood sources, abiotic factors (with special reference to ambient temperature and altitude) to understand the interactions occurring between T. cruzi and triatomine bugs, under a co-evolutionary scenario. These factors lead to varying fitness benefits and costs for bugs, explaining why infection in the insect takes place and how it varies in time and space. Our analysis highlights that major factors are gut components and microbiota, blood sources and temperature. Although their close interaction has never been clarified, knowledge reviewed here may help to boost the success of triatomine control programs, reducing the use of insecticides. Copyright © 2018 Elsevier B.V. All rights reserved.

Augmentation-related brain plasticity

PubMed Central

Di Pino, Giovanni; Maravita, Angelo; Zollo, Loredana; Guglielmelli, Eugenio; Di Lazzaro, Vincenzo

2014-01-01

Today, the anthropomorphism of the tools and the development of neural interfaces require reconsidering the concept of human-tools interaction in the framework of human augmentation. This review analyses the plastic process that the brain undergoes when it comes into contact with augmenting artificial sensors and effectors and, on the other hand, the changes that the use of external augmenting devices produces in the brain. Hitherto, few studies investigated the neural correlates of augmentation, but clues on it can be borrowed from logically-related paradigms: sensorimotor training, cognitive enhancement, cross-modal plasticity, sensorimotor functional substitution, use and embodiment of tools. Augmentation modifies function and structure of a number of areas, i.e., primary sensory cortices shape their receptive fields to become sensitive to novel inputs. Motor areas adapt the neuroprosthesis representation firing-rate to refine kinematics. As for normal motor outputs, the learning process recruits motor and premotor cortices and the acquisition of proficiency decreases attentional recruitment, focuses the activity on sensorimotor areas and increases the basal ganglia drive on the cortex. Augmentation deeply relies on the frontoparietal network. In particular, premotor cortex is involved in learning the control of an external effector and owns the tool motor representation, while the intraparietal sulcus extracts its visual features. In these areas, multisensory integration neurons enlarge their receptive fields to embody supernumerary limbs. For operating an anthropomorphic neuroprosthesis, the mirror system is required to understand the meaning of the action, the cerebellum for the formation of its internal model and the insula for its interoception. In conclusion, anthropomorphic sensorized devices can provide the critical sensory afferences to evolve the exploitation of tools through their embodiment, reshaping the body representation and the sense of the self

Confronting an Augmented Reality

ERIC Educational Resources Information Center

Munnerley, Danny; Bacon, Matt; Wilson, Anna; Steele, James; Hedberg, John; Fitzgerald, Robert

2012-01-01

How can educators make use of augmented reality technologies and practices to enhance learning and why would we want to embrace such technologies anyway? How can an augmented reality help a learner confront, interpret and ultimately comprehend reality itself ? In this article, we seek to initiate a discussion that focuses on these questions, and…

Advanced Intellect-Augmentation Techniques.

ERIC Educational Resources Information Center

Engelbart, D. C.

This progress report covers a two-year project which is part of a program that is exploring the value of computer aids in augmenting human intellectual capability. The background and nature of the program, its resources, and the activities it has undertaken are outlined. User experience in applying augmentation tools and techniques to various…

Augmented Reality for Maintenance and Repair (ARMAR)

DTIC Science & Technology

2007-08-01

800×600 resolution monocular display, whose small size and lack of an opaque “ frame ”, provides the closest experience to an eyeglass form factor, and...Alternatively, fiducials could be mounted on lightweight rigid frames that are attached to predetermined points on the maintained system. Figure...stereo at 800×600 resolution, thirty frames per second, creating a compelling experience of an augmented workspace. Based on our preliminary

Clifford support vector machines for classification, regression, and recurrence.

PubMed

Bayro-Corrochano, Eduardo Jose; Arana-Daniel, Nancy

2010-11-01

This paper introduces the Clifford support vector machines (CSVM) as a generalization of the real and complex-valued support vector machines using the Clifford geometric algebra. In this framework, we handle the design of kernels involving the Clifford or geometric product. In this approach, one redefines the optimization variables as multivectors. This allows us to have a multivector as output. Therefore, we can represent multiple classes according to the dimension of the geometric algebra in which we work. We show that one can apply CSVM for classification and regression and also to build a recurrent CSVM. The CSVM is an attractive approach for the multiple input multiple output processing of high-dimensional geometric entities. We carried out comparisons between CSVM and the current approaches to solve multiclass classification and regression. We also study the performance of the recurrent CSVM with experiments involving time series. The authors believe that this paper can be of great use for researchers and practitioners interested in multiclass hypercomplex computing, particularly for applications in complex and quaternion signal and image processing, satellite control, neurocomputation, pattern recognition, computer vision, augmented virtual reality, robotics, and humanoids.

The Augmentation System Framework.

ERIC Educational Resources Information Center

Engelbart, Doug; Hooper, Kristina

1986-01-01

Augmentation systems are composed of things that will add to what the human is genetically endowed with in order to extend the net capabilities that a human or human organization can apply to the problems or goals of human society. A broad brush categorization of the components of an augmentation system includes three distinct though interacting…

Orbits of Two-Body Problem From the Lenz Vector

ERIC Educational Resources Information Center

Caplan, S.; And Others

1978-01-01

Obtains the orbits with reference to the center of mass of two bodies under mutual universe square law interaction by use of the eccentricity vector which is equivalent to the Lenz vector within a numerical factor. (Author/SL)

Hepatocyte Growth Factor Gene-Modified Mesenchymal Stem Cells Augment Sinonasal Wound Healing

PubMed Central

Li, Jing; Li, Yong; Yang, Chen; Lin, Hai; Duan, Hong-Gang

2015-01-01

This study was designed to investigate the effects of hepatocyte growth factor (HGF) transgenic mesenchymal stem cells (HGF-MSCs) on wound healing in the sinonasal mucosa and nasal epithelial cells (NECs). We also sought to determine whether HGF-MSCs and MSCs can migrate into the injured mucosa and differentiate into ciliated cells. Human HGF-overexpressing umbilical cord MSCs (hHGF-UCMSCs) were established, and upregulation of hHGF expression was confirmed by real-time PCR (RT-PCR) and enzyme-linked immunosorbant assay (ELISA). To investigate the paracrine effect of human MSCs (hMSCs) on nasal epithelial repair, hMSC- and HGF-MSC-conditioned media (CM) were used in NEC proliferation assays and in an in vitro scratch-wound repair model. The in vivo sinonasal wound-healing model was established, and all enrolled rabbits were randomly assigned to four groups: the GFP-MSC group, the HGF-MSC group, the Ad-HGF group, and the surgery control group. The average decreased diameter was recorded, and the medial wall of the maxillary sinus was removed for histological analysis and scanning electron microscopy. Collagen deposition in the wound tissue was detected via Masson trichrome (M&T) staining. The distribution of MSCs and HGF-MSCs was observed by immunofluorescence. MSCs improved nasal wound healing both in vivo and in vitro. HGF overexpression in MSCs augmented the curative effects. Reduced collagen deposition and transforming growth factor beta1 (TGF-β1) expression were detected in the HGF-MSC group compared with the MSC-, Ad-HGF-, and phosphate-buffered saline-treated groups based on M&T staining and ELISA. The enhanced therapeutic effects of HGF-MSCs were accompanied by decreased level of the fibrogenic cytokine TGF-β1. In addition, both HGF-MSCs and MSCs can migrate to the injured mucosa and epithelial layer. PMID:25835956

Hepatocyte Growth Factor Gene-Modified Mesenchymal Stem Cells Augment Sinonasal Wound Healing.

PubMed

Li, Jing; Zheng, Chun-Quan; Li, Yong; Yang, Chen; Lin, Hai; Duan, Hong-Gang

2015-08-01

This study was designed to investigate the effects of hepatocyte growth factor (HGF) transgenic mesenchymal stem cells (HGF-MSCs) on wound healing in the sinonasal mucosa and nasal epithelial cells (NECs). We also sought to determine whether HGF-MSCs and MSCs can migrate into the injured mucosa and differentiate into ciliated cells. Human HGF-overexpressing umbilical cord MSCs (hHGF-UCMSCs) were established, and upregulation of hHGF expression was confirmed by real-time PCR (RT-PCR) and enzyme-linked immunosorbant assay (ELISA). To investigate the paracrine effect of human MSCs (hMSCs) on nasal epithelial repair, hMSC- and HGF-MSC-conditioned media (CM) were used in NEC proliferation assays and in an in vitro scratch-wound repair model. The in vivo sinonasal wound-healing model was established, and all enrolled rabbits were randomly assigned to four groups: the GFP-MSC group, the HGF-MSC group, the Ad-HGF group, and the surgery control group. The average decreased diameter was recorded, and the medial wall of the maxillary sinus was removed for histological analysis and scanning electron microscopy. Collagen deposition in the wound tissue was detected via Masson trichrome (M&T) staining. The distribution of MSCs and HGF-MSCs was observed by immunofluorescence. MSCs improved nasal wound healing both in vivo and in vitro. HGF overexpression in MSCs augmented the curative effects. Reduced collagen deposition and transforming growth factor beta1 (TGF-β1) expression were detected in the HGF-MSC group compared with the MSC-, Ad-HGF-, and phosphate-buffered saline-treated groups based on M&T staining and ELISA. The enhanced therapeutic effects of HGF-MSCs were accompanied by decreased level of the fibrogenic cytokine TGF-β1. In addition, both HGF-MSCs and MSCs can migrate to the injured mucosa and epithelial layer.

On the maximum-entropy/autoregressive modeling of time series

NASA Technical Reports Server (NTRS)

Chao, B. F.

1984-01-01

The autoregressive (AR) model of a random process is interpreted in the light of the Prony's relation which relates a complex conjugate pair of poles of the AR process in the z-plane (or the z domain) on the one hand, to the complex frequency of one complex harmonic function in the time domain on the other. Thus the AR model of a time series is one that models the time series as a linear combination of complex harmonic functions, which include pure sinusoids and real exponentials as special cases. An AR model is completely determined by its z-domain pole configuration. The maximum-entropy/autogressive (ME/AR) spectrum, defined on the unit circle of the z-plane (or the frequency domain), is nothing but a convenient, but ambiguous visual representation. It is asserted that the position and shape of a spectral peak is determined by the corresponding complex frequency, and the height of the spectral peak contains little information about the complex amplitude of the complex harmonic functions.

Effectiveness of basic display augmentation in vehicular control by visual field cues

NASA Technical Reports Server (NTRS)

Grunwald, A. J.; Merhav, S. J.

1978-01-01

The paper investigates the effectiveness of different basic display augmentation concepts - fixed reticle, velocity vector, and predicted future vehicle path - for RPVs controlled by a vehicle-mounted TV camera. The task is lateral manual control of a low flying RPV along a straight reference line in the presence of random side gusts. The man-machine system and the visual interface are modeled as a linear time-invariant system. Minimization of a quadratic performance criterion is assumed to underlie the control strategy of a well-trained human operator. The solution for the optimal feedback matrix enables the explicit computation of the variances of lateral deviation and directional error of the vehicle and of the control force that are used as performance measures.

The Emotion Recognition System Based on Autoregressive Model and Sequential Forward Feature Selection of Electroencephalogram Signals

PubMed Central

Hatamikia, Sepideh; Maghooli, Keivan; Nasrabadi, Ali Motie

2014-01-01

Electroencephalogram (EEG) is one of the useful biological signals to distinguish different brain diseases and mental states. In recent years, detecting different emotional states from biological signals has been merged more attention by researchers and several feature extraction methods and classifiers are suggested to recognize emotions from EEG signals. In this research, we introduce an emotion recognition system using autoregressive (AR) model, sequential forward feature selection (SFS) and K-nearest neighbor (KNN) classifier using EEG signals during emotional audio-visual inductions. The main purpose of this paper is to investigate the performance of AR features in the classification of emotional states. To achieve this goal, a distinguished AR method (Burg's method) based on Levinson-Durbin's recursive algorithm is used and AR coefficients are extracted as feature vectors. In the next step, two different feature selection methods based on SFS algorithm and Davies–Bouldin index are used in order to decrease the complexity of computing and redundancy of features; then, three different classifiers include KNN, quadratic discriminant analysis and linear discriminant analysis are used to discriminate two and three different classes of valence and arousal levels. The proposed method is evaluated with EEG signals of available database for emotion analysis using physiological signals, which are recorded from 32 participants during 40 1 min audio visual inductions. According to the results, AR features are efficient to recognize emotional states from EEG signals, and KNN performs better than two other classifiers in discriminating of both two and three valence/arousal classes. The results also show that SFS method improves accuracies by almost 10-15% as compared to Davies–Bouldin based feature selection. The best accuracies are %72.33 and %74.20 for two classes of valence and arousal and %61.10 and %65.16 for three classes, respectively. PMID:25298928

ARSC: Augmented Reality Student Card--An Augmented Reality Solution for the Education Field

ERIC Educational Resources Information Center

El Sayed, Neven A. M.; Zayed, Hala H.; Sharawy, Mohamed I.

2011-01-01

Augmented Reality (AR) is the technology of adding virtual objects to real scenes through enabling the addition of missing information in real life. As the lack of resources is a problem that can be solved through AR, this paper presents and explains the usage of AR technology we introduce Augmented Reality Student Card (ARSC) as an application of…

Declining Prevalence of Disease Vectors Under Climate Change

NASA Astrophysics Data System (ADS)

Escobar, Luis E.; Romero-Alvarez, Daniel; Leon, Renato; Lepe-Lopez, Manuel A.; Craft, Meggan E.; Borbor-Cordova, Mercy J.; Svenning, Jens-Christian

2016-12-01

More than half of the world population is at risk of vector-borne diseases including dengue fever, chikungunya, zika, yellow fever, leishmaniasis, chagas disease, and malaria, with highest incidences in tropical regions. In Ecuador, vector-borne diseases are present from coastal and Amazonian regions to the Andes Mountains; however, a detailed characterization of the distribution of their vectors has never been carried out. We estimate the distribution of 14 vectors of the above vector-borne diseases under present-day and future climates. Our results consistently suggest that climate warming is likely threatening some vector species with extinction, locally or completely. These results suggest that climate change could reduce the burden of specific vector species. Other vector species are likely to shift and constrain their geographic range to the highlands in Ecuador potentially affecting novel areas and populations. These forecasts show the need for development of early prevention strategies for vector species currently absent in areas projected as suitable under future climate conditions. Informed interventions could reduce the risk of human exposure to vector species with distributional shifts, in response to current and future climate changes. Based on the mixed effects of future climate on human exposure to disease vectors, we argue that research on vector-borne diseases should be cross-scale and include climatic, demographic, and landscape factors, as well as forces facilitating disease transmission at fine scales.

Syngeneic AAV pseudo-vectors potentiates full vector transduction

USDA-ARS?s Scientific Manuscript database

An excessive amount of empty capsids are generated during regular AAV vector production process. These pseudo-vectors often remain in final vectors used for animal studies or clinical trials. The potential effects of these pseudo-vectors on AAV transduction have been a major concern. In the current ...

Why did bluetongue spread the way it did? Environmental factors influencing the velocity of bluetongue virus serotype 8 epizootic wave in France.

PubMed

Pioz, Maryline; Guis, Hélène; Crespin, Laurent; Gay, Emilie; Calavas, Didier; Durand, Benoît; Abrial, David; Ducrot, Christian

2012-01-01

Understanding where and how fast an infectious disease will spread during an epidemic is critical for its control. However, the task is a challenging one as numerous factors may interact and drive the spread of a disease, specifically when vector-borne diseases are involved. We advocate the use of simultaneous autoregressive models to identify environmental features that significantly impact the velocity of disease spread. We illustrate this approach by exploring several environmental factors influencing the velocity of bluetongue (BT) spread in France during the 2007-2008 epizootic wave to determine which ones were the most important drivers. We used velocities of BT spread estimated in 4,495 municipalities and tested sixteen covariates defining five thematic groups of related variables: elevation, meteorological-related variables, landscape-related variables, host availability, and vaccination. We found that ecological factors associated with vector abundance and activity (elevation and meteorological-related variables), as well as with host availability, were important drivers of the spread of the disease. Specifically, the disease spread more slowly in areas with high elevation and when heavy rainfall associated with extreme temperature events occurred one or two months prior to the first clinical case. Moreover, the density of dairy cattle was correlated negatively with the velocity of BT spread. These findings add substantially to our understanding of BT spread in a temperate climate. Finally, the approach presented in this paper can be used with other infectious diseases, and provides a powerful tool to identify environmental features driving the velocity of disease spread.

Why Did Bluetongue Spread the Way It Did? Environmental Factors Influencing the Velocity of Bluetongue Virus Serotype 8 Epizootic Wave in France

PubMed Central

Pioz, Maryline; Guis, Hélène; Crespin, Laurent; Gay, Emilie; Calavas, Didier; Durand, Benoît; Abrial, David; Ducrot, Christian

2012-01-01

Understanding where and how fast an infectious disease will spread during an epidemic is critical for its control. However, the task is a challenging one as numerous factors may interact and drive the spread of a disease, specifically when vector-borne diseases are involved. We advocate the use of simultaneous autoregressive models to identify environmental features that significantly impact the velocity of disease spread. We illustrate this approach by exploring several environmental factors influencing the velocity of bluetongue (BT) spread in France during the 2007–2008 epizootic wave to determine which ones were the most important drivers. We used velocities of BT spread estimated in 4,495 municipalities and tested sixteen covariates defining five thematic groups of related variables: elevation, meteorological-related variables, landscape-related variables, host availability, and vaccination. We found that ecological factors associated with vector abundance and activity (elevation and meteorological-related variables), as well as with host availability, were important drivers of the spread of the disease. Specifically, the disease spread more slowly in areas with high elevation and when heavy rainfall associated with extreme temperature events occurred one or two months prior to the first clinical case. Moreover, the density of dairy cattle was correlated negatively with the velocity of BT spread. These findings add substantially to our understanding of BT spread in a temperate climate. Finally, the approach presented in this paper can be used with other infectious diseases, and provides a powerful tool to identify environmental features driving the velocity of disease spread. PMID:22916249

Optical Vector Receiver Operating Near the Quantum Limit

NASA Astrophysics Data System (ADS)

Vilnrotter, V. A.; Lau, C.-W.

2005-05-01

An optical receiver concept for binary signals with performance approaching the quantum limit at low average-signal energies is developed and analyzed. A conditionally nulling receiver that reaches the quantum limit in the absence of background photons has been devised by Dolinar. However, this receiver requires ideal optical combining and complicated real-time shaping of the local field; hence, it tends to be difficult to implement at high data rates. A simpler nulling receiver that approaches the quantum limit without complex optical processing, suitable for high-rate operation, had been suggested earlier by Kennedy. Here we formulate a vector receiver concept that incorporates the Kennedy receiver with a physical beamsplitter, but it also utilizes the reflected signal component to improve signal detection. It is found that augmenting the Kennedy receiver with classical coherent detection at the auxiliary beamsplitter output, and optimally processing the vector observations, always improves on the performance of the Kennedy receiver alone, significantly so at low average-photon rates. This is precisely the region of operation where modern codes approach channel capacity. It is also shown that the addition of background radiation has little effect on the performance of the coherent receiver component, suggesting a viable approach for near-quantum-limited performance in high background environments.

MEK inhibition prevents tumour-shed transforming growth factor-β-induced T-regulatory cell augmentation in tumour milieu.

PubMed

Hossain, Dewan M S; Panda, Abir K; Chakrabarty, Sreeparna; Bhattacharjee, Pushpak; Kajal, Kirti; Mohanty, Suchismita; Sarkar, Irene; Sarkar, Diptendra K; Kar, Santosh K; Sa, Gaurisankar

2015-04-01

Tumour progression is associated with immune-suppressive conditions that facilitate the escape of tumour cells from the regimen of immune cells, subsequently paralysing the host defence mechanisms. Induction of CD4(+)  CD25(+)  FoxP3(+) T regulatory (Treg) cells has been implicated in the tumour immune escape mechanism, although the novel anti-cancer treatment strategies targeting Treg cells remain unknown. The focus of this study is to define the interaction between tumour and immune system, i.e. how immune tolerance starts and gradually leads to the induction of adaptive Treg cells in the tumour microenvironment. Our study identified hyperactivated mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) -signalling as a potential target for reversing Treg cell augmentation in breast cancer patients. In more mechanistic detail, pharmacological inhibitors of MEK/ERK signalling inhibited transforming growth factor-β (TGF-β) production in tumour cells that essentially blocked TGF-β-SMAD3/SMAD4-mediated induction of CD25/interleukin-2 receptor α on CD4(+) T-cell surface. As a result high-affinity binding of interleukin-2 on those cells was prohibited, causing lack of Janus kinase 1 (JAK1)/JAK3-mediated signal transducer and activator of transcription 3 (STAT3)/STAT5 activation required for FoxP3 expression. Finally, for a more radical approach towards a safe MEK inhibitor, we validate the potential of multi-kinase inhibitor curcumin, especially the nano-curcumin made out of pure curcumin with greater bioavailability; in repealing tumour-shed TGF-β-induced Treg cell augmentation. © 2014 Bose Institute.

MEK inhibition prevents tumour-shed transforming growth factor-β-induced T-regulatory cell augmentation in tumour milieu

PubMed Central

Hossain, Dewan M S; Panda, Abir K; Chakrabarty, Sreeparna; Bhattacharjee, Pushpak; Kajal, Kirti; Mohanty, Suchismita; Sarkar, Irene; Sarkar, Diptendra K; Kar, Santosh K; Sa, Gaurisankar

2015-01-01

Tumour progression is associated with immune-suppressive conditions that facilitate the escape of tumour cells from the regimen of immune cells, subsequently paralysing the host defence mechanisms. Induction of CD4+ CD25+ FoxP3+ T regulatory (Treg) cells has been implicated in the tumour immune escape mechanism, although the novel anti-cancer treatment strategies targeting Treg cells remain unknown. The focus of this study is to define the interaction between tumour and immune system, i.e. how immune tolerance starts and gradually leads to the induction of adaptive Treg cells in the tumour microenvironment. Our study identified hyperactivated mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) -signalling as a potential target for reversing Treg cell augmentation in breast cancer patients. In more mechanistic detail, pharmacological inhibitors of MEK/ERK signalling inhibited transforming growth factor-β (TGF-β) production in tumour cells that essentially blocked TGF-β-SMAD3/SMAD4-mediated induction of CD25/interleukin-2 receptor α on CD4+ T-cell surface. As a result high-affinity binding of interleukin-2 on those cells was prohibited, causing lack of Janus kinase 1 (JAK1)/JAK3-mediated signal transducer and activator of transcription 3 (STAT3)/STAT5 activation required for FoxP3 expression. Finally, for a more radical approach towards a safe MEK inhibitor, we validate the potential of multi-kinase inhibitor curcumin, especially the nano-curcumin made out of pure curcumin with greater bioavailability; in repealing tumour-shed TGF-β-induced Treg cell augmentation. PMID:25284464

Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM

ERIC Educational Resources Information Center

Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman

2012-01-01

This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…

Impact of Release Rates on the Effectiveness of Augmentative Biological Control Agents

PubMed Central

Crowder, David W.

2007-01-01

To access the effect of augmentative biological control agents, 31 articles were reviewed that investigated the impact of release rates of 35 augmentative biological control agents on the control of 42 arthropod pests. In 64% of the cases, the release rate of the biological control agent did not significantly affect the density or mortality of the pest insect. Results where similar when parasitoidsor predators were utilized as the natural enemy. Within any order of natural enemy, there were more cases where release rates did not affect augmentative biological control than cases where release rates were significant. There were more cases in which release rates did not affect augmentative biological control when pests were from the orders Hemiptera, Acari, or Diptera, but not with pests from the order Lepidoptera. In most cases, there was an optimal release rate that produced effective control of a pest species. This was especially true when predators were used as a biological control agent. Increasing the release rate above the optimal rate did not improve control of the pest and thus would be economically detrimental. Lower release rates were of ten optimal when biological control was used in conjunction with insecticides. In many cases, the timing and method of biological control applications were more significant factors impacting the effectiveness of biological control than the release rate. Additional factors that may limit the relative impact of release rates include natural enemy fecundity, establishment rates, prey availability, dispersal, and cannibalism. PMID:20307240

Virtual and Augmented Reality Systems for Renal Interventions: A Systematic Review.

PubMed

Detmer, Felicitas J; Hettig, Julian; Schindele, Daniel; Schostak, Martin; Hansen, Christian

2017-01-01

Many virtual and augmented reality systems have been proposed to support renal interventions. This paper reviews such systems employed in the treatment of renal cell carcinoma and renal stones. A systematic literature search was performed. Inclusion criteria were virtual and augmented reality systems for radical or partial nephrectomy and renal stone treatment, excluding systems solely developed or evaluated for training purposes. In total, 52 research papers were identified and analyzed. Most of the identified literature (87%) deals with systems for renal cell carcinoma treatment. About 44% of the systems have already been employed in clinical practice, but only 20% in studies with ten or more patients. Main challenges remaining for future research include the consideration of organ movement and deformation, human factor issues, and the conduction of large clinical studies. Augmented and virtual reality systems have the potential to improve safety and outcomes of renal interventions. In the last ten years, many technical advances have led to more sophisticated systems, which are already applied in clinical practice. Further research is required to cope with current limitations of virtual and augmented reality assistance in clinical environments.

Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

PubMed

Biswas, Paritosh K; Islam, Md Zohorul; Debnath, Nitish C; Yamage, Mat

2014-01-01

The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered.

Augmented Reality-Guided Lumbar Facet Joint Injections.

PubMed

Agten, Christoph A; Dennler, Cyrill; Rosskopf, Andrea B; Jaberg, Laurenz; Pfirrmann, Christian W A; Farshad, Mazda

2018-05-08

The aim of this study was to assess feasibility and accuracy of augmented reality-guided lumbar facet joint injections. A spine phantom completely embedded in hardened opaque agar with 3 ring markers was built. A 3-dimensional model of the phantom was uploaded to an augmented reality headset (Microsoft HoloLens). Two radiologists independently performed 20 augmented reality-guided and 20 computed tomography (CT)-guided facet joint injections each: for each augmented reality-guided injection, the hologram was manually aligned with the phantom container using the ring markers. The radiologists targeted the virtual facet joint and tried to place the needle tip in the holographic joint space. Computed tomography was performed after each needle placement to document final needle tip position. Time needed from grabbing the needle to final needle placement was measured for each simulated injection. An independent radiologist rated images of all needle placements in a randomized order blinded to modality (augmented reality vs CT) and performer as perfect, acceptable, incorrect, or unsafe. Accuracy and time to place needles were compared between augmented reality-guided and CT-guided facet joint injections. In total, 39/40 (97.5%) of augmented reality-guided needle placements were either perfect or acceptable compared with 40/40 (100%) CT-guided needle placements (P = 0.5). One augmented reality-guided injection missed the facet joint space by 2 mm. No unsafe needle placements occurred. Time to final needle placement was substantially faster with augmented reality guidance (mean 14 ± 6 seconds vs 39 ± 15 seconds, P < 0.001 for both readers). Augmented reality-guided facet joint injections are feasible and accurate without potentially harmful needle placement in an experimental setting.

Challenges associated with reentry maxillary sinus augmentation.

PubMed

Mardinger, Ofer; Moses, Ofer; Chaushu, Gavriel; Manor, Yifat; Tulchinsky, Ze'ev; Nissan, Joseph

2010-09-01

This study was a retrospective assessment of reentry sinus augmentation compared with sinus augmentation performed for the first time. There were 38 subjects who required sinus augmentation. The study group (17 patients, 21 sinuses) included subjects following failure of a previous sinus augmentation procedure that required reentry augmentation. The control group (21 patients, 21 sinuses) included subjects in which sinus augmentation was performed for the first time. Patients' medical files were reviewed. A preformed questionnaire was used to collect data regarding demographic parameters, medical and dental health history, habits, and intra- and postoperative data. Operative challenges in the study group included adhesions of the buccal flap to the Schneiderian membrane (62%, 13/21, P<.001), bony fenestration of the lateral wall with adhesions (71%, 15/21, P<.001), limited mobility of a clinical fibrotic Schneiderian membrane (71%, 15/21, P<.001), and increased incidence of membrane perforations (47%, 10/21, versus 9.5%, 2/21, P=.03). In the control group the Schneiderian membrane was thin and flexible. Sinus augmentation succeeded in all cases of both groups. Implant failure was significantly higher in the study group (11% versus 0%, P<.001). Clinical success of reentry sinus augmentation is predictable despite its complexity. Clinicians should be aware of anatomical changes caused by previous failure of this procedure. Patients should be informed about the lower success rate of implants when reentry sinus augmentation is required. Copyright (c) 2010 Mosby, Inc. All rights reserved.

Neurophysiological changes associated with implant-associated augmentation procedures in the lower jaw.

PubMed

Hartmann, Amely; Welte-Jzyk, Claudia; Seiler, Marcus; Daubländer, Monika

2017-08-01

Neurophysiological changes after oral and maxillofacial surgery remain one of the topics of current research. This study evaluated if implant placement associated with augmentation procedures increases the possibility of sensory disturbances or result in impaired quality of life during the healing period. Patients who had obtained an implant placement in the lower jaw in combination with augmentation procedures were examined by implementing a comprehensive Quantitative Sensory Testing (QST) protocol for extra- and intraoral use. As augmentation procedures, we used Guided Bone Regeneration (Group A) and Customized Bone Regeneration (Group B) techniques. Patients were tested bilaterally at the chin and mucosal lower lip. Results were compared to a group without augmentation procedures (Group C). Patients' quality of life and psychological comorbidity after the surgical procedures was assessed with the Oral Health Impact Profile and the Hospital Anxiety and Depression Scale. For groups A (n = 20) and B (n = 8), mechanical QST parameters showed no significant differences in all qualities of the inferior alveolar nerve compared to the contralateral side and compared to the nonaugmentation control group (n = 32) as well. Evaluation of quality of life and psychological factors showed no statistical differences. Augmentation procedures did not increase sensory disturbances, indicating no changes in the neurophysiological pathways. Extended augmentation procedures did not lead to sensory changes either or result in an impaired quality of life or modified anxiety and depression scores. © 2017 Wiley Periodicals, Inc.

Bardoxolone: augmenting the Yin in chronic kidney disease.

PubMed

Thomas, Merlin C

2011-10-01

Nrf-2 (NF-E2-related factor 2) is a regulator of anti-oxidant, anti-inflammatory and detoxification pathways. Coordinated augmentation of these key defence pathways via Nrf-2 signalling is being investigated for the treatment of chronic diseases, including diabetes and its complications. The first to reach commercial development is the triterpenoid, bardoxolone methyl. In recent clinical trial, bardoxolone rapidly improved kidney function on average by 5-10 ml/min within 4 weeks of therapy. Importantly, this improvement was sustained during one year of active treatment. This suggests that rather that overworking a failing system, bardoxolone appeared to safely augment renal function, at least to one year. If similar improvements in kidney function can be reproduced in the upcoming BEACON trial, it will represent a major advance on conventional therapy and new way to bring balance to the failing kidney.

Augmented GNSS Differential Corrections Minimum Mean Square Error Estimation Sensitivity to Spatial Correlation Modeling Errors

PubMed Central

Kassabian, Nazelie; Presti, Letizia Lo; Rispoli, Francesco

2014-01-01

Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS) signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE) algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs). This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs) distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold. PMID:24922454

Emerging Vector-Borne Diseases - Incidence through Vectors.

PubMed

Savić, Sara; Vidić, Branka; Grgić, Zivoslav; Potkonjak, Aleksandar; Spasojevic, Ljubica

2014-01-01

Vector-borne diseases use to be a major public health concern only in tropical and subtropical areas, but today they are an emerging threat for the continental and developed countries also. Nowadays, in intercontinental countries, there is a struggle with emerging diseases, which have found their way to appear through vectors. Vector-borne zoonotic diseases occur when vectors, animal hosts, climate conditions, pathogens, and susceptible human population exist at the same time, at the same place. Global climate change is predicted to lead to an increase in vector-borne infectious diseases and disease outbreaks. It could affect the range and population of pathogens, host and vectors, transmission season, etc. Reliable surveillance for diseases that are most likely to emerge is required. Canine vector-borne diseases represent a complex group of diseases including anaplasmosis, babesiosis, bartonellosis, borreliosis, dirofilariosis, ehrlichiosis, and leishmaniosis. Some of these diseases cause serious clinical symptoms in dogs and some of them have a zoonotic potential with an effect to public health. It is expected from veterinarians in coordination with medical doctors to play a fundamental role at primarily prevention and then treatment of vector-borne diseases in dogs. The One Health concept has to be integrated into the struggle against emerging diseases. During a 4-year period, from 2009 to 2013, a total number of 551 dog samples were analyzed for vector-borne diseases (borreliosis, babesiosis, ehrlichiosis, anaplasmosis, dirofilariosis, and leishmaniasis) in routine laboratory work. The analysis was done by serological tests - ELISA for borreliosis, dirofilariosis, and leishmaniasis, modified Knott test for dirofilariosis, and blood smear for babesiosis, ehrlichiosis, and anaplasmosis. This number of samples represented 75% of total number of samples that were sent for analysis for different diseases in dogs. Annually, on average more then half of the samples

Is ridge preservation/augmentation at periodontally compromised extraction sockets safe? A retrospective study.

PubMed

Kim, Jung-Ju; Ben Amara, Heithem; Schwarz, Frank; Kim, Hae-Young; Lee, Jung-Won; Wikesjö, Ulf M E; Koo, Ki-Tae

2017-10-01

This study aimed to evaluate the safety of ridge preservation/augmentation procedures when performed at compromised extraction sockets. Patients subject to ridge preservation/augmentation at periodontally compromised sockets at Seoul National University Dental Hospital (SNUDH) were evaluated in a chart review. Tooth extractions due to acute infection were not included in our study as chronically formed lesions are the only lesions that can be detected from radiographic images. If inflammatory symptoms persisted following ridge preservation/augmentation and antimicrobial and anti-inflammatory therapy, the patient was categorized as a re-infection case and implanted biomaterial removed. Of 10,060 patients subject to tooth extractions at SNUDH, 2011 through 2015, 297 cases meeting inclusion criteria were reviewed. The severity and type of lesions were not specific because extracting data was only done by radiographic images and chart records. The review identified eight patients exhibiting inflammatory symptoms that required additional antimicrobial and anti-inflammatory therapy. Within this group, re-infection occurred in two patients requiring biomaterials removal. The final safety rate for the ridge preservation/augmentation was 99.3%. None of the demographic factors, systemic conditions or choice of biomaterial affected the safety of ridge preservation/augmentation. Alveolar ridge preservation/augmentation at periodontally compromised sockets appears safe following thorough removal of infectious source. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Japanese encephalitis: the vectors, ecology and potential for expansion.

PubMed

Pearce, James C; Learoyd, Tristan P; Langendorf, Benjamin J; Logan, James G

2018-05-01

Japanese encephalitis (JE) is a viral disease predominantly located in South East Asia and commonly associated with transmission between amplifying hosts, such as pigs, and the mosquito Culex tritaeniorhynchus, where human infection represents a dead end in the life cycle of the virus. The expansion of JE beyond an Asiatic confine is dependent on a multitude of complex factors that stem back to genetic subtype variation. A complex interplay of the genetic variation and vector competencies combine with variables such as geography, climate change and urbanization. Our understanding of JE is still at an early stage with long-term longitudinal vector surveillance necessary to better understand the dynamics of JE transmission and to characterize the role of potential secondary vectors such as Cx. pipiens and Cx. bitaeniorhynchus. The authors review the vectors indicated in transmission and the ecological, genetic and anthropological factors that affect the disease's range and epidemiology. Monitoring for the presence of JE virus in mosquitoes in general can be used to estimate levels of potential JE exposure, intensity of viral activity and genetic variation of JEV throughout surveyed areas. Increased surveillance and diagnosis of viral encephalitis caused by genotype 5 JE virus is required in particular, with the expansion in epidemiology and disease prevalence in new geographic areas an issue of great concern. Additional studies that measure the impact of vectors (e.g. bionomics and vector competence) in the transmission of JEV and that incorporate environmental factors (e.g. weekly rainfall) are needed to define the roles of Culex species in the viral pathogenesis during outbreak and non-outbreak years.

VectorBase: a home for invertebrate vectors of human pathogens

PubMed Central

Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Emmert, David; Hammond, Martin; Hill, Catherine A.; Kennedy, Ryan C.; Lobo, Neil F.; MacCallum, M. Robert; Madey, Greg; Megy, Karine; Redmond, Seth; Russo, Susan; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Zdobnov, Evgeny M.; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.

2007-01-01

VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever. PMID:17145709

Space Launch System Implementation of Adaptive Augmenting Control

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Wall, John H.; Orr, Jeb S.

2014-01-01

Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to robustly demonstrate stable and high performance flight. On its development path to preliminary design review (PDR), the stability of the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant dynamics. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an adaptive augmenting control (AAC) algorithm previously presented by Orr and VanZwieten, has been shown to extend the envelope of failures and flight anomalies for which the SLS control system can accommodate while maintaining a direct link to flight control stability criteria (e.g. gain & phase margin). In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the SLS digital 3-axis autopilot, including existing load-relief elements, and necessary steps for integration with the production flight software prototype have been implemented. Several updates to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

Space Launch System Implementation of Adaptive Augmenting Control

NASA Technical Reports Server (NTRS)

Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.

2014-01-01

Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

[Cement augmentation on the spine : Biomechanical considerations].

PubMed

Kolb, J P; Weiser, L; Kueny, R A; Huber, G; Rueger, J M; Lehmann, W

2015-09-01

Vertebral compression fractures are the most common osteoporotic fractures. Since the introduction of vertebroplasty and screw augmentation, the management of osteoporotic fractures has changed significantly. The biomechanical characteristics of the risk of adjacent fractures and novel treatment modalities for osteoporotic vertebral fractures, including pure cement augmentation by vertebroplasty, and cement augmentation of screws for posterior instrumentation, are explored. Eighteen human osteoporotic lumbar spines (L1-5) adjacent to vertebral bodies after vertebroplasty were tested in a servo-hydraulic machine. As augmentation compounds we used standard cement and a modified low-strength cement. Different anchoring pedicle screws were tested with and without cement augmentation in another cohort of human specimens with a simple pull-out test and a fatigue test that better reflects physiological conditions. Cement augmentation in the osteoporotic spine leads to greater biomechanical stability. However, change in vertebral stiffness resulted in alterations with the risk of adjacent fractures. By using a less firm cement compound, the risk of adjacent fractures is significantly reduced. Both screw augmentation techniques resulted in a significant increase in the withdrawal force compared with the group without cement. Augmentation using perforated screws showed the highest stability in the fatigue test. The augmentation of cement leads to a significant change in the biomechanical properties. Differences in the stability of adjacent vertebral bodies increase the risk of adjacent fractures, which could be mitigated by a modified cement compound with reduced strength. Screws that were specifically designed for cement application displayed greatest stability in the fatigue test.

Augmented Reality Comes to Physics

NASA Astrophysics Data System (ADS)

Buesing, Mark; Cook, Michael

2013-04-01

Augmented reality (AR) is a technology used on computing devices where processor-generated graphics are rendered over real objects to enhance the sensory experience in real time. In other words, what you are really seeing is augmented by the computer. Many AR games already exist for systems such as Kinect and Nintendo 3DS and mobile apps, such as Tagwhat and Star Chart (a must for astronomy class). The yellow line marking first downs in a televised football game2 and the enhanced puck that makes televised hockey easier to follow3 both use augmented reality to do the job.

Predicting Language Outcomes for Children Learning Augmentative and Alternative Communication: Child and Environmental Factors

ERIC Educational Resources Information Center

Brady, Nancy C.; Thiemann-Bourque, Kathy; Fleming, Kandace; Matthews, Kris

2013-01-01

Purpose: To investigate a model of language development for nonverbal preschool-age children learning to communicate with augmentative or alternative communication. Method: Ninety-three preschool children with intellectual disabilities were assessed at Time 1, and 82 of these children were assessed 1 year later, at Time 2. The outcome variable was…

Level shift two-components autoregressive conditional heteroscedasticity modelling for WTI crude oil market

NASA Astrophysics Data System (ADS)

Sin, Kuek Jia; Cheong, Chin Wen; Hooi, Tan Siow

2017-04-01

This study aims to investigate the crude oil volatility using a two components autoregressive conditional heteroscedasticity (ARCH) model with the inclusion of abrupt jump feature. The model is able to capture abrupt jumps, news impact, clustering volatility, long persistence volatility and heavy-tailed distributed error which are commonly observed in the crude oil time series. For the empirical study, we have selected the WTI crude oil index from year 2000 to 2016. The results found that by including the multiple-abrupt jumps in ARCH model, there are significant improvements of estimation evaluations as compared with the standard ARCH models. The outcomes of this study can provide useful information for risk management and portfolio analysis in the crude oil markets.

An efficient viral vector for functional genomic studies of Prunus fruit trees and its induced resistance to Plum pox virus via silencing of a host factor gene.

PubMed

Cui, Hongguang; Wang, Aiming

2017-03-01

RNA silencing is a powerful technology for molecular characterization of gene functions in plants. A commonly used approach to the induction of RNA silencing is through genetic transformation. A potent alternative is to use a modified viral vector for virus-induced gene silencing (VIGS) to degrade RNA molecules sharing similar nucleotide sequence. Unfortunately, genomic studies in many allogamous woody perennials such as peach are severely hindered because they have a long juvenile period and are recalcitrant to genetic transformation. Here, we report the development of a viral vector derived from Prunus necrotic ringspot virus (PNRSV), a widespread fruit tree virus that is endemic in all Prunus fruit production countries and regions in the world. We show that the modified PNRSV vector, harbouring the sense-orientated target gene sequence of 100-200 bp in length in genomic RNA3, could efficiently trigger the silencing of a transgene or an endogenous gene in the model plant Nicotiana benthamiana. We further demonstrate that the PNRSV-based vector could be manipulated to silence endogenous genes in peach such as eukaryotic translation initiation factor 4E isoform (eIF(iso)4E), a host factor of many potyviruses including Plum pox virus (PPV). Moreover, the eIF(iso)4E-knocked down peach plants were resistant to PPV. This work opens a potential avenue for the control of virus diseases in perennial trees via viral vector-mediated silencing of host factors, and the PNRSV vector may serve as a powerful molecular tool for functional genomic studies of Prunus fruit trees. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Measurements by a Vector Network Analyzer at 325 to 508 GHz

NASA Technical Reports Server (NTRS)

Fung, King Man; Samoska, Lorene; Chattopadhyay, Goutam; Gaier, Todd; Kangaslahti, Pekka; Pukala, David; Lau, Yuenie; Oleson, Charles; Denning, Anthony

2008-01-01

Recent experiments were performed in which return loss and insertion loss of waveguide test assemblies in the frequency range from 325 to 508 GHz were measured by use of a swept-frequency two-port vector network analyzer (VNA) test set. The experiments were part of a continuing effort to develop means of characterizing passive and active electronic components and systems operating at ever increasing frequencies. The waveguide test assemblies comprised WR-2.2 end sections collinear with WR-3.3 middle sections. The test set, assembled from commercially available components, included a 50-GHz VNA scattering- parameter test set and external signal synthesizers, augmented with recently developed frequency extenders, and further augmented with attenuators and amplifiers as needed to adjust radiofrequency and intermediate-frequency power levels between the aforementioned components. The tests included line-reflect-line calibration procedures, using WR-2.2 waveguide shims as the "line" standards and waveguide flange short circuits as the "reflect" standards. Calibrated dynamic ranges somewhat greater than about 20 dB for return loss and 35 dB for insertion loss were achieved. The measurement data of the test assemblies were found to substantially agree with results of computational simulations.

Alkyl isothiocyanates suppress epidermal growth factor receptor kinase activity but augment tyrosine kinase activity.

PubMed

Nomura, Takahiro; Uehara, Yoshimasa; Kawajiri, Hiroo; Ryoyama, Kazuo; Yamori, Takao; Fuke, Yoko

2009-10-01

We have reported the in vitro and in vivo anticancer activities of 6-(methylsulfinyl)hexyl isothiocyanate (6-MITC) derived from a Japanese spice, wasabi. In order to obtain some clues about the mechanism of the anticancer activity, we have studied the effect of alkyl isothiocyanates (MITCs) on protein kinase activities. The anti-autophosphorylation activity of MITCs with respect to the epidermal growth factor (EGF)-stimulated receptor kinase of A431 epidermoid carcinoma cells was examined by incorporation of radioactive ATP into an acid-insoluble fraction. Their anti-phosphorylation activity with respect to the non-receptor protein kinase was analyzed by a standard SDS-PAGE method. All the tested MITCs interfered with the EGF-stimulated receptor kinase activity in a dose-dependent manner, although their effects were less than 1/10 of that of erbstatin in microg/ml. On the other hand, the MITCs did not interfere with non-receptor kinases (kinase A, kinase C, tyrosine kinase and calmodulin dependent kinase III), but enhanced non-receptor tyrosine kinase. A possible anticancer mechanism of MITCs may involve the suppression of EGF receptor kinase activity and augmentation of non-receptor PTK.

The development of augmented video system on postcards

NASA Astrophysics Data System (ADS)

Chen, Chien-Hsu; Chou, Yin-Ju

2013-03-01

This study focuses on development of augmented video system on traditional picture postcards. The system will provide users to print out the augmented reality marker on the sticker to stick on the picture postcard, and it also allows users to record their real time image and video to augment on that stick marker. According dynamic image, users can share travel moods, greeting, and travel experience to their friends. Without changing in the traditional picture postcards, we develop augmented video system on them by augmented reality (AR) technology. It not only keeps the functions of traditional picture postcards, but also enhances user's experience to keep the user's memories and emotional expression by augmented digital media information on them.

Efficient Exact Inference With Loss Augmented Objective in Structured Learning.

PubMed

Bauer, Alexander; Nakajima, Shinichi; Muller, Klaus-Robert

2016-08-19

Structural support vector machine (SVM) is an elegant approach for building complex and accurate models with structured outputs. However, its applicability relies on the availability of efficient inference algorithms--the state-of-the-art training algorithms repeatedly perform inference to compute a subgradient or to find the most violating configuration. In this paper, we propose an exact inference algorithm for maximizing nondecomposable objectives due to special type of a high-order potential having a decomposable internal structure. As an important application, our method covers the loss augmented inference, which enables the slack and margin scaling formulations of structural SVM with a variety of dissimilarity measures, e.g., Hamming loss, precision and recall, Fβ-loss, intersection over union, and many other functions that can be efficiently computed from the contingency table. We demonstrate the advantages of our approach in natural language parsing and sequence segmentation applications.

Proper Conformal Killing Vectors in Kantowski-Sachs Metric

NASA Astrophysics Data System (ADS)

Hussain, Tahir; Farhan, Muhammad

2018-04-01

This paper deals with the existence of proper conformal Killing vectors (CKVs) in Kantowski-Sachs metric. Subject to some integrability conditions, the general form of vector filed generating CKVs and the conformal factor is presented. The integrability conditions are solved generally as well as in some particular cases to show that the non-conformally flat Kantowski-Sachs metric admits two proper CKVs, while it admits a 15-dimensional Lie algebra of CKVs in the case when it becomes conformally flat. The inheriting conformal Killing vectors (ICKVs), which map fluid lines conformally, are also investigated.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality.

PubMed

Yang, Lei; Qin, Guoyou; Zhao, Naiqing; Wang, Chunfang; Song, Guixiang

2012-10-30

Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton's method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

PubMed Central

2012-01-01

Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Computerized tomography-assisted calculation of sinus augmentation volume.

PubMed

Krennmair, Gerald; Krainhöfner, Martin; Maier, Harald; Weinländer, Michael; Piehslinger, Eva

2006-01-01

This study was intended to calculate the augmentation volume for a sinus lift procedure based on cross-sectional computerized tomography (CT) scans for 2 different augmentation heights. Based on area calculations of cross-sectional CT scans, the volume of additional bone needed was calculated for 44 sinus lift procedures. The amount of bone volume needed to raise the sinus floor to heights of both 12 and 17 mm was calculated. To achieve a sinus floor height of 12 mm, it was necessary to increase the height by a mean of 7.2+/-2.1 mm (range, 3.0 to 10.5 mm), depending on the residual ridge height; to achieve a height of 17 mm, a mean of 12.4+/-2.0 mm (range, 8.5 to 15.5 mm) was required (P < .01). The calculated augmentation volume for an augmentation height of 12 mm was 1.7+/-.9 cm3; for an augmentation height of 17 mm, the volume required was 3.6+/-1.5 cm3. Increasing the height of the sinus lift by 5 mm, ie, from 12 mm to 17 mm augmentation height, increased the augmentation volume by 100%. A significant correlation was found between augmentation height and the calculated sinus lift augmentation volume (r = 0. 78, P < .01). Detailed preoperative knowledge of sinus lift augmentation volume is helpful as a predictive value in deciding on a donor site for harvesting autogenous bone and on the ratio of bone to bone substitute to use. Calculation of the augmentation size can help determine the surgical approach and thus perioperative treatment and the costs of the surgery for both patients and clinicians.

Corrected goodness-of-fit test in covariance structure analysis.

PubMed

Hayakawa, Kazuhiko

2018-05-17

Many previous studies report simulation evidence that the goodness-of-fit test in covariance structure analysis or structural equation modeling suffers from the overrejection problem when the number of manifest variables is large compared with the sample size. In this study, we demonstrate that one of the tests considered in Browne (1974) can address this long-standing problem. We also propose a simple modification of Satorra and Bentler's mean and variance adjusted test for non-normal data. A Monte Carlo simulation is carried out to investigate the performance of the corrected tests in the context of a confirmatory factor model, a panel autoregressive model, and a cross-lagged panel (panel vector autoregressive) model. The simulation results reveal that the corrected tests overcome the overrejection problem and outperform existing tests in most cases. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

RMS active damping augmentation

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.; Scott, Michael A.; Demeo, Martha E.

1992-01-01

The topics are presented in viewgraph form and include: RMS active damping augmentation; potential space station assembly benefits to CSI; LaRC/JSC bridge program; control law design process; draper RMS simulator; MIMO acceleration control laws improve damping; potential load reduction benefit; DRS modified to model distributed accelerations; accelerometer location; Space Shuttle aft cockpit simulator; simulated shuttle video displays; SES test goals and objectives; and SES modifications to support RMS active damping augmentation.

Helper-dependent adenoviral vectors for liver-directed gene therapy

PubMed Central

Brunetti-Pierri, Nicola; Ng, Philip

2011-01-01

Helper-dependent adenoviral (HDAd) vectors devoid of all viral-coding sequences are promising non-integrating vectors for liver-directed gene therapy because they have a large cloning capacity, can efficiently transduce a wide variety of cell types from various species independent of the cell cycle and can result in long-term transgene expression without chronic toxicity. The main obstacle preventing clinical applications of HDAd for liver-directed gene therapy is the host innate inflammatory response against the vector capsid proteins that occurs shortly after intravascular vector administration resulting in acute toxicity, the severity of which is dependent on vector dose. Intense efforts have been focused on elucidating the factors involved in this acute response and various strategies have been investigated to improve the therapeutic index of HDAd vectors. These strategies have yielded encouraging results with the potential for clinical translation. PMID:21470977

Vista/F-16 Multi-Axis Thrust Vectoring (MATV) control law design and evaluation

NASA Technical Reports Server (NTRS)

Zwerneman, W. D.; Eller, B. G.

1994-01-01

For the Multi-Axis Thrust Vectoring (MATV) program, a new control law was developed using multi-axis thrust vectoring to augment the aircraft's aerodynamic control power to provide maneuverability above the normal F-16 angle of attack limit. The control law architecture was developed using Lockheed Fort Worth's offline and piloted simulation capabilities. The final flight control laws were used in flight test to demonstrate tactical benefits gained by using thrust vectoring in air-to-air combat. Differences between the simulator aerodynamics data base and the actual aircraft aerodynamics led to significantly different lateral-directional flying qualities during the flight test program than those identified during piloted simulation. A 'dial-a-gain' flight test control law update was performed in the middle of the flight test program. This approach allowed for inflight optimization of the aircraft's flying qualities. While this approach is not preferred over updating the simulator aerodynamic data base and then updating the control laws, the final selected gain set did provide adequate lateral-directional flying qualities over the MATV flight envelope. The resulting handling qualities and the departure resistance of the aircraft allowed the 422nd_squadron pilots to focus entirely on evaluating the aircraft's tactical utility.

A novel autologous scaffold for diced-cartilage grafts in dorsal augmentation rhinoplasty.

PubMed

Bullocks, Jamal M; Echo, Anthony; Guerra, Gerardo; Stal, Samuel; Yuksel, Eser

2011-08-01

Diced-cartilage grafts have been used for dorsal nasal augmentation for several years with good results. However, compounds such as Surgicel and temporalis fascia used as a wrap have inherent problems associated with them, predominantly inflammation and graft resorption. An autologous carrier could provide stabilization of cartilage grafts while avoiding the complications seen with earlier techniques. In our patients, a malleable construct was used for dorsal nasal augmentation in which autologous diced-cartilage grafts were stabilized with autologous tissue glue (ATG) created from platelet-rich plasma (platelet gel) and platelet-poor plasma (fibrin glue). A prospective analysis of 68 patients, who underwent dorsal nasal augmentation utilizing ATG and diced-cartilage grafts between 2005 and 2008, were included in the study. Although there was notable maintenance of the dorsal height, no complications occurred that required explantation over a mean follow-up of 15 months. The use of ATG to stabilize diced-cartilage grafts is a safe, reliable technique for dorsal nasal augmentation. The platelet gel provides growth factors while the fibrin glue creates a scaffold that allows stabilization and diffusion of nutrients to the cartilage graft.

Nonsteady-Flow Thrust Augmenting Ejectors

NASA Technical Reports Server (NTRS)

Foa, J. V.

1979-01-01

Ejector augmenters in which the transfer of mechanical energy from the primary to the secondary flow takes place through the work of interface pressure forces are investigated. Nonsteady flow processes are analyzed from the standpoint of energy transfer efficiency and a comparison of a rotary jet augmenter to an ejector is presented.

VectorBase: a data resource for invertebrate vector genomics

PubMed Central

Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Hammond, Martin; Hill, Catherine A.; Konopinski, Nathan; Lobo, Neil F.; MacCallum, Robert M.; Madey, Greg; Megy, Karine; Meyer, Jason; Redmond, Seth; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.

2009-01-01

VectorBase (http://www.vectorbase.org) is an NIAID-funded Bioinformatic Resource Center focused on invertebrate vectors of human pathogens. VectorBase annotates and curates vector genomes providing a web accessible integrated resource for the research community. Currently, VectorBase contains genome information for three mosquito species: Aedes aegypti, Anopheles gambiae and Culex quinquefasciatus, a body louse Pediculus humanus and a tick species Ixodes scapularis. Since our last report VectorBase has initiated a community annotation system, a microarray and gene expression repository and controlled vocabularies for anatomy and insecticide resistance. We have continued to develop both the software infrastructure and tools for interrogating the stored data. PMID:19028744

Drivers, dynamics, and control of emerging vector-borne zoonotic diseases

PubMed Central

Kilpatrick, A. Marm; Randolph, Sarah E.

2013-01-01

Emerging vector-borne diseases represent an important issue for global health. Many vector-borne pathogens have appeared in new regions in the past two decades, and many endemic diseases have increased in incidence. Although introductions and local emergence are frequently considered distinct processes, many emerging endemic pathogens are in fact invading at a local scale coincident with habitat change. We highlight key differences in the dynamics and disease burden that result from increased pathogen transmission following habitat change compared with the introduction of pathogens to new regions. Truly in situ emergence is commonly driven by changes in human factors as much as by enhanced enzootic cycles whereas pathogen invasion results from anthropogenic trade and travel and suitable conditions for a pathogen, including hosts, vectors, and climate. Once established, ecological factors related to vector characteristics shape the evolutionary selective pressure on pathogens that may result in increased use of humans as transmission hosts. We describe challenges inherent in the control of vector-borne zoonotic diseases and some emerging non-traditional strategies that may be more effective in the long term. PMID:23200503

Comparative evaluation of monocular augmented-reality display for surgical microscopes.

PubMed

Rodriguez Palma, Santiago; Becker, Brian C; Lobes, Louis A; Riviere, Cameron N

2012-01-01

Medical augmented reality has undergone much development recently. However, there is a lack of studies quantitatively comparing the different display options available. This paper compares the effects of different graphical overlay systems in a simple micromanipulation task with "soft" visual servoing. We compared positioning accuracy in a real-time visually-guided task using Micron, an active handheld tremor-canceling microsurgical instrument, using three different displays: 2D screen, 3D screen, and microscope with monocular image injection. Tested with novices and an experienced vitreoretinal surgeon, display of virtual cues in the microscope via an augmented reality injection system significantly decreased 3D error (p < 0.05) compared to the 2D and 3D monitors when confounding factors such as magnification level were normalized.

Emerging Vector-Borne Diseases – Incidence through Vectors

PubMed Central

Savić, Sara; Vidić, Branka; Grgić, Zivoslav; Potkonjak, Aleksandar; Spasojevic, Ljubica

2014-01-01

Vector-borne diseases use to be a major public health concern only in tropical and subtropical areas, but today they are an emerging threat for the continental and developed countries also. Nowadays, in intercontinental countries, there is a struggle with emerging diseases, which have found their way to appear through vectors. Vector-borne zoonotic diseases occur when vectors, animal hosts, climate conditions, pathogens, and susceptible human population exist at the same time, at the same place. Global climate change is predicted to lead to an increase in vector-borne infectious diseases and disease outbreaks. It could affect the range and population of pathogens, host and vectors, transmission season, etc. Reliable surveillance for diseases that are most likely to emerge is required. Canine vector-borne diseases represent a complex group of diseases including anaplasmosis, babesiosis, bartonellosis, borreliosis, dirofilariosis, ehrlichiosis, and leishmaniosis. Some of these diseases cause serious clinical symptoms in dogs and some of them have a zoonotic potential with an effect to public health. It is expected from veterinarians in coordination with medical doctors to play a fundamental role at primarily prevention and then treatment of vector-borne diseases in dogs. The One Health concept has to be integrated into the struggle against emerging diseases. During a 4-year period, from 2009 to 2013, a total number of 551 dog samples were analyzed for vector-borne diseases (borreliosis, babesiosis, ehrlichiosis, anaplasmosis, dirofilariosis, and leishmaniasis) in routine laboratory work. The analysis was done by serological tests – ELISA for borreliosis, dirofilariosis, and leishmaniasis, modified Knott test for dirofilariosis, and blood smear for babesiosis, ehrlichiosis, and anaplasmosis. This number of samples represented 75% of total number of samples that were sent for analysis for different diseases in dogs. Annually, on average more then half of the samples

Development of Defective and Persistent Sendai Virus Vector

PubMed Central

Nishimura, Ken; Sano, Masayuki; Ohtaka, Manami; Furuta, Birei; Umemura, Yoko; Nakajima, Yoshiro; Ikehara, Yuzuru; Kobayashi, Toshihiro; Segawa, Hiroaki; Takayasu, Satoko; Sato, Hideyuki; Motomura, Kaori; Uchida, Eriko; Kanayasu-Toyoda, Toshie; Asashima, Makoto; Nakauchi, Hiromitsu; Yamaguchi, Teruhide; Nakanishi, Mahito

2011-01-01

The ectopic expression of transcription factors can reprogram differentiated tissue cells into induced pluripotent stem cells. However, this is a slow and inefficient process, depending on the simultaneous delivery of multiple genes encoding essential reprogramming factors and on their sustained expression in target cells. Moreover, once cell reprogramming is accomplished, these exogenous reprogramming factors should be replaced with their endogenous counterparts for establishing autoregulated pluripotency. Complete and designed removal of the exogenous genes from the reprogrammed cells would be an ideal option for satisfying this latter requisite as well as for minimizing the risk of malignant cell transformation. However, no single gene delivery/expression system has ever been equipped with these contradictory characteristics. Here we report the development of a novel replication-defective and persistent Sendai virus (SeVdp) vector based on a noncytopathic variant virus, which fulfills all of these requirements for cell reprogramming. The SeVdp vector could accommodate up to four exogenous genes, deliver them efficiently into various mammalian cells (including primary tissue cells and human hematopoietic stem cells) and express them stably in the cytoplasm at a prefixed balance. Furthermore, interfering with viral transcription/replication using siRNA could erase the genomic RNA of SeVdp vector from the target cells quickly and thoroughly. A SeVdp vector installed with Oct4/Sox2/Klf4/c-Myc could reprogram mouse primary fibroblasts quite efficiently; ∼1% of the cells were reprogrammed to Nanog-positive induced pluripotent stem cells without chromosomal gene integration. Thus, this SeVdp vector has potential as a tool for advanced cell reprogramming and for stem cell research. PMID:21138846

Augmentation cystoplasty in neurogenic bladder

PubMed Central

Kocjancic, Ervin; Demirdağ, Çetin

2016-01-01

The aim of this review is to update the indications, contraindications, technique, complications, and the tissue engineering approaches of augmentation cystoplasty (AC) in patients with neurogenic bladder. PubMed/MEDLINE was searched for the keywords "augmentation cystoplasty," "neurogenic bladder," and "bladder augmentation." Additional relevant literature was determined by examining the reference lists of articles identified through the search. The update review of of the indications, contraindications, technique, outcome, complications, and tissue engineering approaches of AC in patients with neurogenic bladder is presented. Although some important progress has been made in tissue engineering AC, conventional AC still has an important role in the surgical treatment of refractory neurogenic lower urinary tract dysfunction. PMID:27617312

Autoregressive models for estimating phylogenetic and environmental effects: accounting for within-species variations.

PubMed

Cornillon, P A; Pontier, D; Rochet, M J

2000-02-21

Comparative methods are used to investigate the attributes of present species or higher taxa. Difficulties arise from the phylogenetic heritage: taxa are not independent and neglecting phylogenetic inertia can lead to inaccurate results. Within-species variations in life-history traits are also not negligible, but most comparative methods are not designed to take them into account. Taxa are generally described by a single value for each trait. We have developed a new model which permits the incorporation of both the phylogenetic relationships among populations and within-species variations. This is an extension of classical autoregressive models. This family of models was used to study the effect of fishing on six demographic traits measured on 77 populations of teleost fishes. Copyright 2000 Academic Press.

Is a synthetic augmentation in medial open wedge high tibial osteotomies superior to no augmentation in terms of bone-healing?

PubMed

Ferner, Felix; Dickschas, Joerg; Ostertag, Helmut; Poske, Ulrich; Schwitulla, Judith; Harrer, Joerg; Strecker, Wolf

2016-01-01

Medial open-wedge high tibial osteotomy (MOWHTO) is an established method to treat unicompartimental osteoarthritis of the knee joint. However, augmentation of the created tibial gap after osteotomy is controversially discussed. We performed a prospective investigation of 49 consecutive cases of MOWHTO at our department. Patients were divided into two groups: group A consisted of 19 patients while group B consisted of 30 patients. In group A, the augmentation of the opening gap after osteotomy was filled with a synthetic bone graft, whereas group B received no augmentation. As an indicator for bone healing we investigated the non-union rate in our study population and compared the non-union-rate between the two groups. The non-union rate was 28% in group A (five of 19 patients had to undergo revision) which received synthetic augmentation, while it was 3.3% in group B (one of 30 patients had to undergo revision) which received no augmentation. The difference between the groups was statistically significant (p-value 0.027). With regard to bone healing after MOWHTO, synthetic augmentation was not superior to no augmentation in terms of non-union rates after surgery. In fact, we registered a significantly higher rate of non-union after augmentation with synthetic bone graft. III. Copyright © 2015 Elsevier B.V. All rights reserved.

Study on homogenization of synthetic GNSS-retrieved IWV time series and its impact on trend estimates with autoregressive noise

NASA Astrophysics Data System (ADS)

Klos, Anna; Pottiaux, Eric; Van Malderen, Roeland; Bock, Olivier; Bogusz, Janusz

2017-04-01

A synthetic benchmark dataset of Integrated Water Vapour (IWV) was created within the activity of "Data homogenisation" of sub-working group WG3 of COST ES1206 Action. The benchmark dataset was created basing on the analysis of IWV differences retrieved by Global Positioning System (GPS) International GNSS Service (IGS) stations using European Centre for Medium-Range Weather Forecats (ECMWF) reanalysis data (ERA-Interim). Having analysed a set of 120 series of IWV differences (ERAI-GPS) derived for IGS stations, we delivered parameters of a number of gaps and breaks for every certain station. Moreover, we estimated values of trends, significant seasonalities and character of residuals when deterministic model was removed. We tested five different noise models and found that a combination of white and autoregressive processes of first order describes the stochastic part with a good accuracy. Basing on this analysis, we performed Monte Carlo simulations of 25 years long data with two different types of noise: white as well as combination of white and autoregressive processes. We also added few strictly defined offsets, creating three variants of synthetic dataset: easy, less-complicated and fully-complicated. The 'Easy' dataset included seasonal signals (annual, semi-annual, 3 and 4 months if present for a particular station), offsets and white noise. The 'Less-complicated' dataset included above-mentioned, as well as the combination of white and first order autoregressive processes (AR(1)+WH). The 'Fully-complicated' dataset included, beyond above, a trend and gaps. In this research, we show the impact of manual homogenisation on the estimates of trend and its error. We also cross-compare the results for three above-mentioned datasets, as the synthetized noise type might have a significant influence on manual homogenisation. Therefore, it might mostly affect the values of trend and their uncertainties when inappropriately handled. In a future, the synthetic dataset

Prediction of municipal solid waste generation using nonlinear autoregressive network.

PubMed

Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; Maulud, K N A

2015-12-01

Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.

Augmented Reality Comes to Physics

ERIC Educational Resources Information Center

Buesing, Mark; Cook, Michael

2013-01-01

Augmented reality (AR) is a technology used on computing devices where processor-generated graphics are rendered over real objects to enhance the sensory experience in real time. In other words, what you are really seeing is augmented by the computer. Many AR games already exist for systems such as Kinect and Nintendo 3DS and mobile apps, such as…

Exclusive diffractive production of real photons and vector mesons in a factorized Regge-pole model with nonlinear Pomeron trajectory

NASA Astrophysics Data System (ADS)

Fazio, S.; Fiore, R.; Jenkovszky, L.; Lavorini, A.

2012-03-01

Exclusive diffractive production of real photons and vector mesons in ep collisions has been studied at HERA in a wide kinematic range. Here we present and discuss a Regge-type model of real photon production (deeply virtual Compton scattering), as well as production of vector mesons treated on the same footing by using an extension of a factorized Regge-pole model proposed earlier. The model has been fitted to the HERA data. Despite the very small number of the free parameters, the model gives a satisfactory description of the experimental data, both for the total cross section as a function of the photon virtuality Q2 or the energy W in the center of mass of the γ*p system, and the differential cross sections as a function of the squared four-momentum transfer t with fixed Q2 and W.

RNA Interference in Insect Vectors for Plant Viruses.

PubMed

Kanakala, Surapathrudu; Ghanim, Murad

2016-12-12

Insects and other arthropods are the most important vectors of plant pathogens. The majority of plant pathogens are disseminated by arthropod vectors such as aphids, beetles, leafhoppers, planthoppers, thrips and whiteflies. Transmission of plant pathogens and the challenges in managing insect vectors due to insecticide resistance are factors that contribute to major food losses in agriculture. RNA interference (RNAi) was recently suggested as a promising strategy for controlling insect pests, including those that serve as important vectors for plant pathogens. The last decade has witnessed a dramatic increase in the functional analysis of insect genes, especially those whose silencing results in mortality or interference with pathogen transmission. The identification of such candidates poses a major challenge for increasing the role of RNAi in pest control. Another challenge is to understand the RNAi machinery in insect cells and whether components that were identified in other organisms are also present in insect. This review will focus on summarizing success cases in which RNAi was used for silencing genes in insect vector for plant pathogens, and will be particularly helpful for vector biologists.

RNA Interference in Insect Vectors for Plant Viruses

PubMed Central

Kanakala, Surapathrudu; Ghanim, Murad

2016-01-01

Insects and other arthropods are the most important vectors of plant pathogens. The majority of plant pathogens are disseminated by arthropod vectors such as aphids, beetles, leafhoppers, planthoppers, thrips and whiteflies. Transmission of plant pathogens and the challenges in managing insect vectors due to insecticide resistance are factors that contribute to major food losses in agriculture. RNA interference (RNAi) was recently suggested as a promising strategy for controlling insect pests, including those that serve as important vectors for plant pathogens. The last decade has witnessed a dramatic increase in the functional analysis of insect genes, especially those whose silencing results in mortality or interference with pathogen transmission. The identification of such candidates poses a major challenge for increasing the role of RNAi in pest control. Another challenge is to understand the RNAi machinery in insect cells and whether components that were identified in other organisms are also present in insect. This review will focus on summarizing success cases in which RNAi was used for silencing genes in insect vector for plant pathogens, and will be particularly helpful for vector biologists. PMID:27973446

Oxytocin Augmentation in Spontaneously Laboring, Nulliparous Women: Multilevel Assessment of Maternal BMI and Oxytocin Dose

PubMed Central

Carlson, Nicole S.; Corwin, Elizabeth J.; Lowe, Nancy K.

2017-01-01

Background Synthetic oxytocin, the primary tool for labor augmentation, is less effective among obese women, leading to more unplanned cesarean deliveries for slow labor progress. It is not known if obese women require higher doses of oxytocin due to maternal, fetal, or labor factors related to maternal obesity. Objectives This study had two main objectives: 1) Examine the influence of maternal body mass index (BMI) on hourly doses of oxytocin from augmentation initiation until vaginal delivery in obese women; and 2) Examine the influence of other maternal, fetal, and labor factors on hourly doses of oxytocin in obese women. Study design Longitudinal study of a cohort (N = 136) of healthy, nulliparous, spontaneously laboring obese women (BMI ≥ 30 kg/m2) who received oxytocin augmentation and achieved vaginal delivery. We performed iterative multilevel analyses to examine the influence of maternal BMI and other factors on hourly oxytocin doses. Results Maternal BMI explained 16.56% (95% CI [13.7-20.04], p < 0.001) of the variance in hourly oxytocin doses received in a multilevel model controlling for influence of maternal, fetal, and labor characteristics. Maternal age, gestational age, status of amniotic membranes at hospital admission, and admission cervical dilation examination were not significant; however, neonatal birthweight and cervical dilation at oxytocin initiation were significant predictors of hourly oxytocin dose in these women (p < 0.001). Conclusions Even when parturition preparation has progressed adequately for spontaneous labor initiation, there still may be some obesity-related blunting of myometrial contractility and response to oxytocin used for augmentation. PMID:28347147

Oxytocin Augmentation in Spontaneously Laboring, Nulliparous Women: Multilevel Assessment of Maternal BMI and Oxytocin Dose.

PubMed

Carlson, Nicole S; Corwin, Elizabeth J; Lowe, Nancy K

2017-07-01

Synthetic oxytocin, the primary tool for labor augmentation, is less effective among obese women, leading to more unplanned cesarean deliveries for slow labor progress. It is not known if obese women require higher doses of oxytocin due to maternal, fetal, or labor factors related to maternal obesity. This study had two main objectives: (1) examine the influence of maternal body mass index (BMI) on hourly doses of oxytocin from augmentation initiation until vaginal delivery in obese women; and (2) examine the influence of other maternal, fetal, and labor factors on hourly doses of oxytocin in obese women. Longitudinal study of a cohort ( N = 136) of healthy, nulliparous, spontaneously laboring obese women (BMI ≥ 30 kg/m 2 ) who received oxytocin augmentation and achieved vaginal delivery. We performed iterative multilevel analyses to examine the influence of maternal BMI and other factors on hourly oxytocin doses. Maternal BMI explained 16.56% (95% confidence interval [CI] = [13.7, 20.04], p < .001) of the variance in hourly oxytocin doses received in a multilevel model controlling for influence of maternal, fetal, and labor characteristics. Maternal age, gestational age, status of amniotic membranes at hospital admission, and admission cervical dilation examination were not significant; however, neonatal birthweight and cervical dilation at oxytocin initiation were significant predictors of hourly oxytocin dose in these women ( p < .001). Even when parturition preparation has progressed adequately for spontaneous labor initiation, there still may be some obesity-related blunting of myometrial contractility and response to oxytocin used for augmentation.

Palm oil price forecasting model: An autoregressive distributed lag (ARDL) approach

NASA Astrophysics Data System (ADS)

Hamid, Mohd Fahmi Abdul; Shabri, Ani

2017-05-01

Palm oil price fluctuated without any clear trend or cyclical pattern in the last few decades. The instability of food commodities price causes it to change rapidly over time. This paper attempts to develop Autoregressive Distributed Lag (ARDL) model in modeling and forecasting the price of palm oil. In order to use ARDL as a forecasting model, this paper modifies the data structure where we only consider lagged explanatory variables to explain the variation in palm oil price. We then compare the performance of this ARDL model with a benchmark model namely ARIMA in term of their comparative forecasting accuracy. This paper also utilize ARDL bound testing approach to co-integration in examining the short run and long run relationship between palm oil price and its determinant; production, stock, and price of soybean as the substitute of palm oil and price of crude oil. The comparative forecasting accuracy suggests that ARDL model has a better forecasting accuracy compared to ARIMA.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

Effects of Forecasts on the Revisions of Concurrent Seasonally Adjusted Data Using the X-11 Seasonal Adjustment Procedure.

ERIC Educational Resources Information Center

Bobbitt, Larry; Otto, Mark

Three Autoregressive Integrated Moving Averages (ARIMA) forecast procedures for Census Bureau X-11 concurrent seasonal adjustment were empirically tested. Forty time series from three Census Bureau economic divisions (business, construction, and industry) were analyzed. Forecasts were obtained from fitted seasonal ARIMA models augmented with…

The effects of radiation on antitumor efficacy of an oncolytic adenovirus vector in the Syrian hamster model

PubMed Central

Young, Brittany A.; Spencer, Jacqueline F.; Ying, Baoling; Toth, Karoly; Wold, William S. M.

2013-01-01

We report that radiation enhances the antitumor efficacy of the oncolytic adenovirus vector VRX-007 in Syrian hamster tumors. We used tumor-specific irradiation of subcutaneous tumors and compared treatment options of radiation alone or combined with VRX-007 and cyclophosphamide (CP). Radiation therapy further augmented the VRX-007-mediated inhibition of tumor growth, in both CP-treated and non-CP-treated hamsters, even though radiation did not lead to increased viral replication in tumors when compared to those treated with VRX-007 alone. Moreover, tumor growth inhibition was similar in tumors irradiated either one week before or after injection with VRX-007, which suggests that radiation exerts its antitumor effect independently from vector therapy. Thus, our results demonstrate that these two therapies do not have to be provided simultaneously to enhance their combined effectiveness against subcutaneous hamster tumors. PMID:23928730

The effects of radiation on antitumor efficacy of an oncolytic adenovirus vector in the Syrian hamster model.

PubMed

Young, B A; Spencer, J F; Ying, B; Toth, K; Wold, W S M

2013-09-01

We report that radiation enhances the antitumor efficacy of the oncolytic adenovirus vector VRX-007 in Syrian hamster tumors. We used tumor-specific irradiation of subcutaneous tumors and compared treatment options of radiation alone or combined with VRX-007 and cyclophosphamide (CP). Radiation therapy further augmented the VRX-007-mediated inhibition of tumor growth, in both CP-treated and non-CP-treated hamsters, even though radiation did not lead to increased viral replication in tumors when compared with those treated with VRX-007 alone. Moreover, tumor growth inhibition was similar in tumors irradiated either 1 week before or after injection with VRX-007, which suggests that radiation exerts its antitumor effect independently from vector therapy. Thus, our results demonstrate that these two therapies do not have to be provided simultaneously to enhance their combined effectiveness against subcutaneous hamster tumors.

Activation of human gingival epithelial cells by cell-surface components of black-pigmented bacteria: augmentation of production of interleukin-8, granulocyte colony-stimulating factor and granulocyte-macrophage colony-stimulating factor and expression of intercellular adhesion molecule 1.

PubMed

Sugiyama, A; Uehara, A; Iki, K; Matsushita, K; Nakamura, R; Ogawa, T; Sugawara, S; Takada, H

2002-01-01

Black-pigmented anaerobic bacteria, such as Porphyromonas gingivalis and Prevotella intermedia, are amongst the predominant bacteria in periodontal pockets and have been implicated in periodontal diseases. To elucidate the roles of gingival keratinocytes, which are the first cells encountered by oral bacteria in periodontal diseases, human gingival keratinocytes in primary culture were stimulated with cell-surface components of P gingivalis and Pr. intermedia. A glycoprotein fraction from Pr. intermedia (PGP) clearly augmented the release of interleukin-8, granulocyte colony-stimulating factor and granulocyte-macrophage colony-stimulating factor, as determined by enzyme-linked immunosorbent assay. This PGP also induced expression of intercellular adhesion molecule-1 (ICAM-1), as determined by flow cytometry. The augmentation of mRNA expression for these molecules was also confirmed by reverse transcription PCR. In contrast, lipopolysaccharide (LPS) from Pr. intermedia and Escherichia coli was completely inactive in these assays. LPS fraction and purified fimbriae from P gingivalis exhibited weak activities. Cytokine production and ICAM-1 expression by gingival keratinocytes might cause accumulation and activation of neutrophils in the epithelium and, therefore, may be involved in the initiation and development of inflammation in periodontal tissues.

Strategies and Challenges in Simultaneous Augmentation Mastopexy.

PubMed

Spring, Michelle A; Hartmann, Emily C; Stevens, W Grant

2015-10-01

Simultaneous breast augmentation and mastopexy is a common procedure often considered to be one of the most difficult cosmetic breast surgeries. One-stage augmentation mastopexy was initially described more than 50 years ago. The challenge lies in the fact that the surgery has multiple opposing goals: to increasing the volume of a breast, enhance the shape, and simultaneously decrease the skin envelope. Successful outcomes in augmentation can be expected with proper planning, technique, and patient education. This article focuses on common indications for simultaneous augmentation mastopexy, techniques for safe and effective combined procedures, challenges of the procedure, and potential complications. Copyright © 2015 Elsevier Inc. All rights reserved.

Augmented superfield approach to gauge-invariant massive 2-form theory

NASA Astrophysics Data System (ADS)

Kumar, R.; Krishna, S.

2017-06-01

We discuss the complete sets of the off-shell nilpotent (i.e. s^2_{(a)b} = 0) and absolutely anticommuting (i.e. s_b s_{ab} + s_{ab} s_b = 0) Becchi-Rouet-Stora-Tyutin (BRST) (s_b) and anti-BRST (s_{ab}) symmetries for the (3+1)-dimensional (4D) gauge-invariant massive 2-form theory within the framework of an augmented superfield approach to the BRST formalism. In this formalism, we obtain the coupled (but equivalent) Lagrangian densities which respect both BRST and anti-BRST symmetries on the constrained hypersurface defined by the Curci-Ferrari type conditions. The absolute anticommutativity property of the (anti-) BRST transformations (and corresponding generators) is ensured by the existence of the Curci-Ferrari type conditions which emerge very naturally in this formalism. Furthermore, the gauge-invariant restriction plays a decisive role in deriving the proper (anti-) BRST transformations for the Stückelberg-like vector field.

Performance of a solar augmented heat pump

NASA Astrophysics Data System (ADS)

Bedinger, A. F. G.; Tomlinson, J. J.; Reid, R. L.; Chaffin, D. J.

Performance of a residential size solar augmented heat pump is reported for the 1979-1980 heating season. The facility located in Knoxville, Tennessee, has a measured heat load coefficient of 339.5 watt/C (644 BTU/hr- F). The solar augmented heat pump system consists of 7.4 cu m of one inch diameter crushed limestone. The heat pump is a nominal 8.8 KW (2 1/2 ton) high efficiency unit. The system includes electric resistance heaters to give the option of adding thermal energy to the pebble bed storage during utility off-peak periods, thus offering considerable load management capability. A 15 KW electric resistance duct heater is used to add thermal energy to the pebble bin as required during off-peak periods. Hourly thermal performance and on site weather data was taken for the period November 1, 1979, to April 13, 1980. Thermal performance data consists of heat flow summations for all modes of the system, pebble bed temperatures, and space temperature. Weather data consists of dry bulb temperature, dew point temperature, total global insolation (in the plane of the collector), and wind speed and direction. An error analysis was performed and the least accurate of the measurements was determined to be the heat flow at 5%. Solar system thermal performance factor was measured to be 8.77. The heat pump thermal performance factor was 1.64. Total system seasonal performance factor was measured to be 1.66. Using a modified version of TRNSYS, the thermal performance of this system was simulated. When simulation results were compared with data collected onsite, the predicted heat flow and power consumption generally were within experimental accuracy.

The design and implementation of cost-effective algorithms for direct solution of banded linear systems on the vector processor system 32 supercomputer

NASA Technical Reports Server (NTRS)

Samba, A. S.

1985-01-01

The problem of solving banded linear systems by direct (non-iterative) techniques on the Vector Processor System (VPS) 32 supercomputer is considered. Two efficient direct methods for solving banded linear systems on the VPS 32 are described. The vector cyclic reduction (VCR) algorithm is discussed in detail. The performance of the VCR on a three parameter model problem is also illustrated. The VCR is an adaptation of the conventional point cyclic reduction algorithm. The second direct method is the Customized Reduction of Augmented Triangles' (CRAT). CRAT has the dominant characteristics of an efficient VPS 32 algorithm. CRAT is tailored to the pipeline architecture of the VPS 32 and as a consequence the algorithm is implicitly vectorizable.

Vectorized program architectures for supercomputer-aided circuit design

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

Rizzoli, V.; Ferlito, M.; Neri, A.

1986-01-01

Vector processors (supercomputers) can be effectively employed in MIC or MMIC applications to solve problems of large numerical size such as broad-band nonlinear design or statistical design (yield optimization). In order to fully exploit the capabilities of a vector hardware, any program architecture must be structured accordingly. This paper presents a possible approach to the ''semantic'' vectorization of microwave circuit design software. Speed-up factors of the order of 50 can be obtained on a typical vector processor (Cray X-MP), with respect to the most powerful scaler computers (CDC 7600), with cost reductions of more than one order of magnitude. Thismore » could broaden the horizon of microwave CAD techniques to include problems that are practically out of the reach of conventional systems.« less

Vascular Endothelial Growth Factor Augments Arginine Transport and Nitric Oxide Generation via a KDR Receptor Signaling Pathway.

PubMed

Shashar, Moshe; Chernichovski, Tamara; Pasvolsky, Oren; Levi, Sharon; Grupper, Ayelet; Hershkovitz, Rami; Weinstein, Talia; Schwartz, Idit F

2017-01-01

Vascular endothelial growth factor (VEGF) is an endothelium-specific peptide that stimulates angiogenesis via two receptor tyrosine kinases, Flt-1 and KDR. Endothelial nitric oxide synthase (eNOS) plays a major role in VEGF signaling. Delivery of arginine to membrane bound eNOS by the cationic amino acid transporter-1 (CAT-1) has been shown to modulate eNOS activity. The current studies were designed to test the hypothesis that VEGF enhances eNOS activity via modulation of arginine transport by CAT-1. Using radio-labeled arginine, {[3H] L-arginine} uptake was determined in human umbilical vein endothelial cells (HUVEC) following incubation with VEGF with and without silencing the VEGF receptors Flt-1 or KDR. Subsequently, western blotting for CAT-1, PKCα, ERK 1/2, JNK, and their phosphorylated forms were performed. NO generation was measured by the Griess reaction. VEGF (50 and 100 ng/ml) significantly augmented endothelial arginine transport in a time dependent manner, an effect which was prevented by Sunitinib (2 µM), a multi targeted receptor tyrosine kinase inhibitor. The increase in arginine transport velocities by VEGF was not affected by silencing Flt-1 while silencing KDR abrogated VEGF effect. Furthermore, incubating cells with 50 and 100 ng of VEGF for 30 minutes significantly augmented CAT-1 abundance. The expression of PKC-α, JNK, and ERK1/2 and their phosphorylated forms were unchanged following incubation of HUVEC with VEGF. The concentration of NO2/NO3 following incubation with VEGF was significantly higher than from untreated cells. This increase was significantly attenuated by silencing KDR. VEGF increases arginine transport via modulation of CAT-1 in endothelial cells. This effect is exclusively dependent on KDR rather than Flt-1. © 2017 The Author(s). Published by S. Karger AG, Basel.

Augmentation therapy for alpha-1 antitrypsin deficiency: towards a personalised approach

PubMed Central

2013-01-01

Background Intravenous augmentation therapy is the only specific treatment available for emphysema associated with alpha-1 antitrypsin deficiency. Despite large observational studies and limited interventional studies there remains controversy about the efficacy of this treatment due to the impracticality of conducting adequately powered studies to evaluate the rate of decline in lung function, due to the low prevalence and the slow progression of the disease. However, measurement of lung density by computed tomography is a more specific and sensitive marker of the evolution of emphysema and two small placebo-controlled clinical trials have provided evidence supporting a reduction in the rate of decline in lung density with augmentation therapy. The problem Where augmentation therapy has become available there has been little consideration of a structured approach to therapy which is often introduced on the basis of functional impairment at diagnosis. Data from registries have shown a great variability in the evolution of lung disease according to patient acquisition and the presence of recognised risk factors. Avoidance of risk factors may, in many cases, stabilise the disease. Since augmentation therapy itself will at best preserve the presenting level of lung damage yet require intravenous administration for life with associated costs, identification of patients at risk of continued rapid or long term progression is essential to select those for whom this treatment can be most appropriate and hence generally more cost-effective. This represents a major reconsideration of the current practice in order to develop a consistent approach to management world wide. Purpose of this review The current review assesses the evidence for efficacy of augmentation therapy and considers how the combination of age, physiological impairment, exacerbation history and rate of decline in spirometry and other measures of emphysema may be used to improve therapeutic decision making

A lifting surface theory for thrust augmenting ejectors

NASA Technical Reports Server (NTRS)

Bevilaqua, P. M.

1977-01-01

The circulation theory of airfoil lift has been applied to calculate the performance of thrust augmenting ejectors. The ejector shroud is considered to be 'flying' in the secondary velocity field induced by the entrainment of the primary jet, so that the augmenting thrust is viewed as analogous to the lift on an airfoil. Vortex lattice methods are utilized to compute the thrust augmentation from the force on the flaps. The augmentation is shown to be a function of the length and shape of the flaps, as well as their position and orientation. Predictions of this new theory are compared with the results of classical methods of calculating the augmentation by integration of the stream thrust.

An augmented aging process in brain white matter in HIV.

PubMed

Kuhn, Taylor; Kaufmann, Tobias; Doan, Nhat Trung; Westlye, Lars T; Jones, Jacob; Nunez, Rodolfo A; Bookheimer, Susan Y; Singer, Elyse J; Hinkin, Charles H; Thames, April D

2018-06-01

HIV infection and aging are both associated with neurodegeneration. However, whether the aging process alone or other factors associated with advanced age account for the progression of neurodegeneration in the aging HIV-positive (HIV+) population remains unclear. HIV+ (n = 70) and HIV-negative (HIV-, n = 34) participants underwent diffusion tensor imaging (DTI) and metrics of microstructural properties were extracted from regions of interest (ROIs). A support vector regression model was trained on two independent datasets of healthy adults across the adult life-span (n = 765, Cam-CAN = 588; UiO = 177) to predict participant age from DTI metrics, and applied to the HIV dataset. Predicted brain age gap (BAG) was computed as the difference between predicted age and chronological age, and statistically compared between HIV groups. Regressions assessed the relationship between BAG and HIV severity/medical comorbidities. Finally, correlation analyses tested for associations between BAG and cognitive performance. BAG was significantly higher in the HIV+ group than the HIV- group F (1, 103) = 12.408, p = .001). HIV RNA viral load was significantly associated with BAG, particularly in older HIV+ individuals (R 2  = 0.29, F(7, 70) = 2.66, p = .021). Further, BAG was negatively correlated with domain-level cognitive function (learning: r = -0.26, p = .008; memory: r = -0.21, p = .034). HIV infection is associated with augmented white matter aging, and greater brain aging is associated with worse cognitive performance in multiple domains. © 2018 Wiley Periodicals, Inc.

QSPR model for bioconcentration factors of nonpolar organic compounds using molecular electronegativity distance vector descriptors.

PubMed

Qin, Li-Tang; Liu, Shu-Shen; Liu, Hai-Ling

2010-02-01

A five-variable model (model M2) was developed for the bioconcentration factors (BCFs) of nonpolar organic compounds (NPOCs) by using molecular electronegativity distance vector (MEDV) to characterize the structures of NPOCs and variable selection and modeling based on prediction (VSMP) to select the optimum descriptors. The estimated correlation coefficient (r (2)) and the leave-one-out cross-validation correlation coefficients (q (2)) of model M2 were 0.9271 and 0.9171, respectively. The model was externally validated by splitting the whole data set into a representative training set of 85 chemicals and a validation set of 29 chemicals. The results show that the main structural factors influencing the BCFs of NPOCs are -cCc, cCcc, -Cl, and -Br (where "-" refers to a single bond and "c" refers to a conjugated bond). The quantitative structure-property relationship (QSPR) model can effectively predict the BCFs of NPOCs, and the predictions of the model can also extend the current BCF database of experimental values.

Comparison of the hydrogeology and water quality of a ground-water augmented lake with two non-augmented lakes in northwest Hillsborough County, Florida

USGS Publications Warehouse

Metz, Patricia A.; Sacks, Laura A.

2002-01-01

, indicating that the water is capable of dissolving calcite in the underlying limestone aquifer. Annual and monthly ground-water outflow (lake leakage) was significantly higher at Round Lake than at the non-augmented lakes for the 3-year study period. Minimum estimates of the total annual ground-water inflow and outflow were made from monthly net ground-water flow values. Based on these estimates, total annual groundwater outflow from Round Lake was more than 10 times higher than for the non-augmented lakes. Local ground-water pumping, augmentation, and hydrogeologic factors are responsible for the high net ground-water outflow at Round Lake. Localized ground-water pumping causes the head difference between the lake and the Upper Floridan aquifer to increase, which increases lake leakage and results in lower lake levels. Augmenting the lake further increases the head difference between the lake, the water table, and the Upper Floridan aquifer, which results in an increase in lateral and vertical lake leakage. The lack of confinement or breaches in the intermediate confining unit facilitates the downward movement of this augmented lake water back into the Upper Floridan aquifer. The increase in ground-water circulation in the leakage-dominated hydrogeologic setting at Round Lake has made the basin more susceptible to karst activity (limestone dissolution, subsidence, and sinkhole formation)

Analysis of Factors Influencing PM2.5 in Beijing: A Microcosmic and Dynamic Perspective for Sustainable Development

NASA Astrophysics Data System (ADS)

Wang, Yani; Wang, Jun; Tao, Guiping

2017-12-01

Haze pollution has become a hot issue concerned with the process of modernization and one serious problem requiring urgent solution, especially in Beijing. PM2.5 is the main reason causing haze and its harm. Although there has been research centering on factors affecting PM2.5, little attention has been devoted to the microcosmic and dynamic effects on it. Vector auto-regression (VAR) mode is applied in this study to explore the interaction between PM2.5, PM10, SO2, CO and NO2. Results of Granger causality tests tell that there exists causal relationship between PM10, SO2, CO, NO2 and PM2.5. Impulse response functions (IRFs) show that the response of PM2.5 to a shock in CO is positive and large in the short period, while the reaction of PM2.5 to a shock in SO2 increases over time. Meanwhile, variance decomposition indicate that PM2.5 is more closely related to CO in the short term while SO2’ influence accounts for a higher proportion in the long run. The findings provide a novel perspective to analyze the factors influencing PM2.5 dynamically and contribute to a better understanding of haze and its relationship with sustainable development.

Are Bred Vectors The Same As Lyapunov Vectors?

NASA Astrophysics Data System (ADS)

Kalnay, E.; Corazza, M.; Cai, M.

Regional loss of predictability is an indication of the instability of the underlying flow, where small errors in the initial conditions (or imperfections in the model) grow to large amplitudes in finite times. The stability properties of evolving flows have been studied using Lyapunov vectors (e.g., Alligood et al, 1996, Ott, 1993, Kalnay, 2002), singular vectors (e.g., Lorenz, 1965, Farrell, 1988, Molteni and Palmer, 1993), and, more recently, with bred vectors (e.g., Szunyogh et al, 1997, Cai et al, 2001). Bred vectors (BVs) are, by construction, closely related to Lyapunov vectors (LVs). In fact, after an infinitely long breeding time, and with the use of infinitesimal ampli- tudes, bred vectors are identical to leading Lyapunov vectors. In practical applications, however, bred vectors are different from Lyapunov vectors in two important ways: a) bred vectors are never globally orthogonalized and are intrinsically local in space and time, and b) they are finite-amplitude, finite-time vectors. These two differences are very significant in a dynamical system whose size is very large. For example, the at- mosphere is large enough to have "room" for several synoptic scale instabilities (e.g., storms) to develop independently in different regions (say, North America and Aus- tralia), and it is complex enough to have several different possible types of instabilities (such as barotropic, baroclinic, convective, and even Brownian motion). Bred vectors share some of their properties with leading LVs (Corazza et al, 2001a, 2001b, Toth and Kalnay, 1993, 1997, Cai et al, 2001). For example, 1) Bred vectors are independent of the norm used to define the size of the perturba- tion. Corazza et al. (2001) showed that bred vectors obtained using a potential enstro- phy norm were indistinguishable from bred vectors obtained using a streamfunction squared norm, in contrast with singular vectors. 2) Bred vectors are independent of the length of the rescaling period as long as the

Augmented reality in dentistry: a current perspective.

PubMed

Kwon, Ho-Beom; Park, Young-Seok; Han, Jung-Suk

2018-02-21

Augmentation reality technology offers virtual information in addition to that of the real environment and thus opens new possibilities in various fields. The medical applications of augmentation reality are generally concentrated on surgery types, including neurosurgery, laparoscopic surgery and plastic surgery. Augmentation reality technology is also widely used in medical education and training. In dentistry, oral and maxillofacial surgery is the primary area of use, where dental implant placement and orthognathic surgery are the most frequent applications. Recent technological advancements are enabling new applications of restorative dentistry, orthodontics and endodontics. This review briefly summarizes the history, definitions, features, and components of augmented reality technology and discusses its applications and future perspectives in dentistry.

Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model

PubMed Central

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume. PMID:22203886

Long-term prediction of emergency department revenue and visitor volume using autoregressive integrated moving average model.

PubMed

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume.

Autoregressive modeling for the spectral analysis of oceanographic data

NASA Technical Reports Server (NTRS)

Gangopadhyay, Avijit; Cornillon, Peter; Jackson, Leland B.

1989-01-01

Over the last decade there has been a dramatic increase in the number and volume of data sets useful for oceanographic studies. Many of these data sets consist of long temporal or spatial series derived from satellites and large-scale oceanographic experiments. These data sets are, however, often 'gappy' in space, irregular in time, and always of finite length. The conventional Fourier transform (FT) approach to the spectral analysis is thus often inapplicable, or where applicable, it provides questionable results. Here, through comparative analysis with the FT for different oceanographic data sets, the possibilities offered by autoregressive (AR) modeling to perform spectral analysis of gappy, finite-length series, are discussed. The applications demonstrate that as the length of the time series becomes shorter, the resolving power of the AR approach as compared with that of the FT improves. For the longest data sets examined here, 98 points, the AR method performed only slightly better than the FT, but for the very short ones, 17 points, the AR method showed a dramatic improvement over the FT. The application of the AR method to a gappy time series, although a secondary concern of this manuscript, further underlines the value of this approach.

Augmented Reality Tower Technology Assessment

NASA Technical Reports Server (NTRS)

Reisman, Ronald J.; Brown, David M.

2009-01-01

Augmented Reality technology may help improve Air Traffic Control Tower efficiency and safety during low-visibility conditions. This paper presents the assessments of five off-duty controllers who shadow-controlled' with an augmented reality prototype in their own facility. Initial studies indicated unanimous agreement that this technology is potentially beneficial, though the prototype used in the study was not adequate for operational use. Some controllers agreed that augmented reality technology improved situational awareness, had potential to benefit clearance, control, and coordination tasks and duties and could be very useful for acquiring aircraft and weather information, particularly aircraft location, heading, and identification. The strongest objections to the prototype used in this study were directed at aircraft registration errors, unacceptable optical transparency, insufficient display performance in sunlight, inadequate representation of the static environment and insufficient symbology.

Experience with a vectorized general circulation weather model on Star-100

NASA Technical Reports Server (NTRS)

Soll, D. B.; Habra, N. R.; Russell, G. L.

1977-01-01

A version of an atmospheric general circulation model was vectorized to run on a CDC STAR 100. The numerical model was coded and run in two different vector languages, CDC and LRLTRAN. A factor of 10 speed improvement over an IBM 360/95 was realized. Efficient use of the STAR machine required some redesigning of algorithms and logic. This precludes the application of vectorizing compilers on the original scalar code to achieve the same results. Vector languages permit a more natural and efficient formulation for such numerical codes.

"Triplet" polycistronic vectors encoding Gata4, Mef2c, and Tbx5 enhances postinfarct ventricular functional improvement compared with singlet vectors.

PubMed

Mathison, Megumi; Singh, Vivek P; Gersch, Robert P; Ramirez, Maricela O; Cooney, Austin; Kaminsky, Stephen M; Chiuchiolo, Maria J; Nasser, Ahmed; Yang, Jianchang; Crystal, Ronald G; Rosengart, Todd K

2014-10-01

The in situ reprogramming of cardiac fibroblasts into induced cardiomyocytes by the administration of gene transfer vectors encoding Gata4 (G), Mef2c (M), and Tbx5 (T) has been shown to improve ventricular function in myocardial infarction models. The efficacy of this strategy could, however, be limited by the need for fibroblast targets to be infected 3 times--once by each of the 3 transgene vectors. We hypothesized that a polycistronic "triplet" vector encoding all 3 transgenes would enhance postinfarct ventricular function compared with use of "singlet" vectors. After validation of the polycistronic vector expression in vitro, adult male Fischer 344 rats (n=6) underwent coronary ligation with or without intramyocardial administration of an adenovirus encoding all 3 major vascular endothelial growth factor (VEGF) isoforms (AdVEGF-All6A positive), followed 3 weeks later by the administration to AdVEGF-All6A-positive treated rats of singlet lentivirus encoding G, M, or T (1×10(5) transducing units each) or the same total dose of a GMT "triplet" lentivirus vector. Western blots demonstrated that triplet and singlet vectors yielded equivalent GMT transgene expression, and fluorescence activated cell sorting demonstrated that triplet vectors were nearly twice as potent as singlet vectors in generating induced cardiomyocytes from cardiac fibroblasts. Echocardiography demonstrated that GMT triplet vectors were more effective than the 3 combined singlet vectors in enhancing ventricular function from postinfarct baselines (triplet, 37%±10%; singlet, 13%±7%; negative control, 9%±5%; P<.05). These data have confirmed that the in situ administration of G, M, and T induces postinfarct ventricular functional improvement and that GMT polycistronic vectors enhance the efficacy of this strategy. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Climate change and vector-borne diseases of public health significance.

PubMed

Ogden, Nicholas H

2017-10-16

There has been much debate as to whether or not climate change will have, or has had, any significant effect on risk from vector-borne diseases. The debate on the former has focused on the degree to which occurrence and levels of risk of vector-borne diseases are determined by climate-dependent or independent factors, while the debate on the latter has focused on whether changes in disease incidence are due to climate at all, and/or are attributable to recent climate change. Here I review possible effects of climate change on vector-borne diseases, methods used to predict these effects and the evidence to date of changes in vector-borne disease risks that can be attributed to recent climate change. Predictions have both over- and underestimated the effects of climate change. Mostly under-estimations of effects are due to a focus only on direct effects of climate on disease ecology while more distal effects on society's capacity to control and prevent vector-borne disease are ignored. There is increasing evidence for possible impacts of recent climate change on some vector-borne diseases but for the most part, observed data series are too short (or non-existent), and impacts of climate-independent factors too great, to confidently attribute changing risk to climate change. © Crown copyright 2017.

Antidepressant augmentation with anti-inflammatory agents.

PubMed

Andrade, Chittaranjan

2014-09-01

Antidepressant augmentation strategies are commonly employed to treat depressed patients who do not respond to antidepressant monotherapy. Neuroinflammatory mechanisms have been implicated in depression, and nonsteroidal anti-inflammatory drugs (NSAIDs) have been found effective in animal models of depression both in monotherapy and when used to augment antidepressant drugs. However, results with NSAIDs have been mixed in human observational studies, with both better and worse depression outcomes reported. Four small (pooled N = 160) randomized controlled trials suggest that celecoxib (200-400 mg/d) augmentation of antidepressant medication improves 4-6 week outcomes in major depressive disorder. There are no data, however, to support the use of celecoxib or other NSAIDs in antidepressant-resistant depression. There are also concerns about adverse events associated with NSAID treatment, and about pharmacodynamic drug interactions between these drugs and serotonin reuptake inhibitors. A reasonable conclusion for the present is that NSAID augmentation of antidepressants is, at best, a tentative approach in nonrefractory major depression. © Copyright 2014 Physicians Postgraduate Press, Inc.

Augmented macrophage differentiation and polarization of tumor-associated macrophages towards M1 subtype in listeria-administered tumor-bearing host.

PubMed

Rai, Rakesh K; Vishvakarma, Naveen K; Mohapatra, Tribhuban M; Singh, Sukh Mahendra

2012-09-01

This study investigates the effect of Listeria administration on differentiation of macrophages from precursor bone marrow cells and functional status of tumor-associated macrophages (TAM). Listeria administration not only resulted in an augmented infiltration of tumor by F4/80 macrophages but also repolarized the functional status of TAM displaying features of some M1 macrophage subtype with upregulated phagocytosis and tumoricidal activity accompanied by altered expression of monocarboxylate transporter-1, toll-like receptor-2, surface markers: CD11c, interleukin-2 receptor, CD62L, and secreted molecules: nitric oxide, interleukin (IL)-1, IL-6, tumor necrosis factor-α, and vascular endothelial growth factor. Declined tumor cell survival and modulated repertoire of cytokines: interferon-γ, IL-6, IL-10, and transforming growth factor-β in tumor microenvironment indicated their role in polarization of TAM towards proinflammatory state. Bone marrow cell of Listeria-administered tumor-bearing mice showed augmented survival, declined expression of p53 upregulated modulator of apoptosis with an upregulated differentiation into activation responsive bone marrow-derived macrophages along with altered expression of macrophage-colony stimulating factor, macrophage-colony stimulating factor receptor, and granulocyte macrophage-colony stimulating factor receptor. These findings indicate that Listeria infection is associated with an augmented differentiation of macrophages accompanied by tumoricidal activation of TAM.

Absorptive corrections for vector mesons: matching to complex mass scheme and longitudinal corrections

NASA Astrophysics Data System (ADS)

Jiménez Pérez, L. A.; Toledo Sánchez, G.

2017-12-01

Unstable spin-1 particles are properly described by including absorptive corrections to the electromagnetic vertex and propagator, without breaking the electromagnetic gauge invariance. We show that the modified propagator can be set in a complex mass form, provided the mass and width parameters, which are properly defined at the pole, are replaced by energy dependent functions fulfilling the same requirements at the pole. We exemplify the case for the {K}* (892) vector meson, and find that the mass function deviates around 2 MeV from the Kπ threshold to the pole, and that the width function exhibits a different behavior compared to the uncorrected energy dependent width. Considering the {τ }-\\to {K}{{S}}{π }-{ν }τ decay as dominated by the {K}* (892) and {K}{\\prime * }(1410) vectors and one scalar particle, we exhibit the role of the transversal and longitudinal corrections to the vector propagator by obtaining the modified vector and scalar form factors. The modified vector form factor is found to be the same as in the complex mass form, while the scalar form factor receives a modification from the longitudinal correction to the vector propagator. A fit to the experimental Kπ spectrum shows that the phase induced by the presence of this new contribution in the scalar sector improves the description of the experimental data in the troublesome region around 0.7 GeV. Besides that, the correction to the scalar form factor is found to be negligible.

Improved Prefusion Stability, Optimized Codon Usage, and Augmented Virion Packaging Enhance the Immunogenicity of Respiratory Syncytial Virus Fusion Protein in a Vectored-Vaccine Candidate

PubMed Central

Liang, Bo; Ngwuta, Joan O.; Surman, Sonja; Kabatova, Barbora; Liu, Xiang; Lingemann, Matthias; Liu, Xueqiao; Yang, Lijuan; Herbert, Richard; Swerczek, Joanna; Chen, Man; Moin, Syed M.; Kumar, Azad; McLellan, Jason S.; Kwong, Peter D.; Graham, Barney S.; Collins, Peter L.

2017-01-01

ABSTRACT Respiratory syncytial virus (RSV) is the most important viral agent of severe pediatric respiratory tract disease worldwide, but it lacks a licensed vaccine or suitable antiviral drug. A live attenuated chimeric bovine/human parainfluenza virus type 3 (rB/HPIV3) was developed previously as a vector expressing RSV fusion (F) protein to confer bivalent protection against RSV and HPIV3. In a previous clinical trial in virus-naive children, rB/HPIV3 was well tolerated but the immunogenicity of wild-type RSV F was unsatisfactory. We previously modified RSV F with a designed disulfide bond (DS) to increase stability in the prefusion (pre-F) conformation and to be efficiently packaged in the vector virion. Here, we further stabilized pre-F by adding both disulfide and cavity-filling mutations (DS-Cav1), and we also modified RSV F codon usage to have a lower CpG content and a higher level of expression. This RSV F open reading frame was evaluated in rB/HPIV3 in three forms: (i) pre-F without vector-packaging signal, (ii) pre-F with vector-packaging signal, and (iii) secreted pre-F ectodomain trimer. Despite being efficiently expressed, the secreted pre-F was poorly immunogenic. DS-Cav1 stabilized pre-F, with or without packaging, induced higher titers of pre-F specific antibodies in hamsters, and improved the quality of RSV-neutralizing serum antibodies. Codon-optimized RSV F containing fewer CpG dinucleotides had higher F expression, replicated more efficiently in vivo, and was more immunogenic. The combination of DS-Cav1 pre-F stabilization, optimized codon usage, reduced CpG content, and vector packaging significantly improved vector immunogenicity and protective efficacy against RSV. This provides an improved vectored RSV vaccine candidate suitable for pediatric clinical evaluation. IMPORTANCE RSV and HPIV3 are the first and second leading viral causes of severe pediatric respiratory disease worldwide. Licensed vaccines or suitable antiviral drugs are not

Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

PubMed

Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

2008-02-01

Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

From Augmentation Media to Meme Media.

ERIC Educational Resources Information Center

Tanaka, Yuzuru

Computers as meta media are now evolving from augmentation media vehicles to meme media vehicles. While an augmentation media system provides a seamlessly integrated environment of various tools and documents, meme media system provides further functions to edit and distribute tools and documents. Documents and tools on meme media can easily…

Coherent vector meson photoproduction from deuterium at intermediate energies

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

Rogers, T.C.; Strikman, M.I.; Sargsian, M.M.

2006-04-15

We analyze the cross section for vector meson photoproduction off a deuteron for the intermediate range of photon energies starting at a few giga-electron-volts above the threshold and higher. We reproduce the steps in the derivation of the conventional nonrelativistic Glauber expression based on an effective diagrammatic method while making corrections for Fermi motion and intermediate-energy kinematic effects. We show that, for intermediate-energy vector meson production, the usual Glauber factorization breaks down, and we derive corrections to the usual Glauber method to linear order in longitudinal nucleon momentum. The purpose of our analysis is to establish methods for probing interestingmore » physics in the production mechanism for {phi} mesons and heavier vector mesons. We demonstrate how neglecting the breakdown of Glauber factorization can lead to errors in measurements of basic cross sections extracted from nuclear data.« less

Culicoides-virus interactions: infection barriers and possible factors underlying vector competence

USDA-ARS?s Scientific Manuscript database

In the United States, Culicoides midges vector arboviruses of economic importance such as Bluetongue Virus and Epizootic Hemorrhagic Disease Virus. A limited number of studies have demonstrated the complexities of midge-virus interactions, including dynamic changes in virus titer and prevalence over...

Stability-Augmentation Devices for Miniature Aircraft

NASA Technical Reports Server (NTRS)

Wood, RIchard M.

2005-01-01

Non-aerodynamic mechanical devices are under consideration as means to augment the stability of miniature autonomous and remotely controlled aircraft. Such aircraft can be used for diverse purposes, including military reconnaissance, radio communications, and safety-related monitoring of wide areas. The need for stability-augmentation devices arises because adverse meteorological conditions generally affect smaller aircraft more strongly than they affect larger aircraft: Miniature aircraft often become uncontrollable under conditions that would not be considered severe enough to warrant grounding of larger aircraft. The need for the stability-augmentation devices to be non-aerodynamic arises because there is no known way to create controlled aerodynamic forces sufficient to counteract the uncontrollable meteorological forces on miniature aircraft. A stability-augmentation device of the type under consideration includes a mass pod (a counterweight) at the outer end of a telescoping shaft, plus associated equipment to support the operation of the aircraft. The telescoping shaft and mass pod are stowed in the rear of the aircraft. When deployed, they extend below the aircraft. Optionally, an antenna for radio communication can be integrated into the shaft. At the time of writing this article, the deployment of the telescoping shaft and mass pod was characterized as passive and automatic, but information about the deployment mechanism(s) was not available. The feasibility of this stability-augmentation concept was demonstrated in flights of hand-launched prototype aircraft.

Potential costs of breast augmentation mammaplasty.

PubMed

Schmitt, William P; Eichhorn, Mitchell G; Ford, Ronald D

2016-01-01

Augmentation mammaplasty is one of the most common surgical procedures performed by plastic surgeons. The aim of this study was to estimate the cost of the initial procedure and its subsequent complications, as well as project the cost of Food and Drug Administration (FDA)-recommended surveillance imaging. The potential costs to the individual patient and society were calculated. Local plastic surgeons provided billing data for the initial primary silicone augmentation and reoperative procedures. Complication rates used for the cost analysis were obtained from the Allergen Core study on silicone implants. Imaging surveillance costs were considered in the estimations. The average baseline initial cost of silicone augmentation mammaplasty was calculated at $6335. The average total cost of primary breast augmentation over the first decade for an individual patient, including complications requiring reoperation and other ancillary costs, was calculated at $8226. Each decade thereafter cost an additional $1891. Costs may exceed $15,000 over an averaged lifetime, and the recommended implant surveillance could cost an additional $33,750. The potential cost of a breast augmentation, which includes the costs of complications and imaging, is significantly higher than the initial cost of the procedure. Level III, economic and decision analysis study. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Vector Addition: Effect of the Context and Position of the Vectors

NASA Astrophysics Data System (ADS)

Barniol, Pablo; Zavala, Genaro

2010-10-01

In this article we investigate the effect of: 1) the context, and 2) the position of the vectors, on 2D vector addition tasks. We administered a test to 512 students completing introductory physics courses at a private Mexican university. In the first part, we analyze students' responses in three isomorphic problems: displacements, forces, and no physical context. Students were asked to draw two vectors and the vector sum. We analyzed students' procedures detecting the difficulties when drawing the vector addition and proved that the context matters, not only compared to the context-free case but also between the contexts. In the second part, we analyze students' responses with three different arrangements of the sum of two vectors: tail-to-tail, head-to-tail and separated vectors. We compared the frequencies of the errors in the three different positions to deduce students' conceptions in the addition of vectors.

Parallel/Vector Integration Methods for Dynamical Astronomy

NASA Astrophysics Data System (ADS)

Fukushima, T.

Progress of parallel/vector computers has driven us to develop suitable numerical integrators utilizing their computational power to the full extent while being independent on the size of system to be integrated. Unfortunately, the parallel version of Runge-Kutta type integrators are known to be not so efficient. Recently we developed a parallel version of the extrapolation method (Ito and Fukushima 1997), which allows variable timesteps and still gives an acceleration factor of 3-4 for general problems. While the vector-mode usage of Picard-Chebyshev method (Fukushima 1997a, 1997b) will lead the acceleration factor of order of 1000 for smooth problems such as planetary/satellites orbit integration. The success of multiple-correction PECE mode of time-symmetric implicit Hermitian integrator (Kokubo 1998) seems to enlighten Milankar's so-called "pipelined predictor corrector method", which is expected to lead an acceleration factor of 3-4. We will review these directions and discuss future prospects.

The effect of elevated temperatures on the life history and insecticide resistance phenotype of the major malaria vector Anopheles arabiensis (Diptera: Culicidae).

PubMed

Oliver, Shüné V; Brooke, Basil D

2017-02-14

Temperature plays a crucial role in the life history of insects. Recent climate change research has highlighted the importance of elevated temperature on malaria vector distribution. This study aims to examine the role of elevated temperatures on epidemiologically important life-history traits in the major malaria vector, Anopheles arabiensis. Specifically, the differential effects of temperature on insecticide-resistant and susceptible strains were examined. Two laboratory strains of A. arabiensis, the insecticide-susceptible SENN and the insecticide-resistant SENN DDT strains, were used to examine the effect of elevated temperatures on larval development and adult longevity. The effects of various elevated temperatures on insecticide resistance phenotypes were also examined and the biochemical basis of the changes in insecticide resistance phenotype was assessed. SENN and SENN DDT larvae developed at similar rates at elevated temperatures. SENN DDT adult survivorship did not vary between control and elevated temperatures, while the longevity of SENN adults at constantly elevated temperatures was significantly reduced. SENN DDT adults lived significantly longer than SENN at constantly elevated temperatures. Elevated rearing temperatures, as well as a short-term exposure to 37 and 39 °C as adults, augmented pyrethroid resistance in adult SENN DDT, and increased pyrethroid tolerance in SENN. Detoxification enzyme activity was not implicated in this phenotypic effect. Quercertin-induced synergism of inducible heat shock proteins negated this temperature-mediated augmentation of pyrethroid resistance. Insecticide-resistant A. arabiensis live longer than their susceptible counterparts at elevated temperatures. Exposure to heat shock augments pyrethroid resistance in both resistant and susceptible strains. This response is potentially mediated by inducible heat shock proteins.

Autoregressive model in the Lp norm space for EEG analysis.

PubMed

Li, Peiyang; Wang, Xurui; Li, Fali; Zhang, Rui; Ma, Teng; Peng, Yueheng; Lei, Xu; Tian, Yin; Guo, Daqing; Liu, Tiejun; Yao, Dezhong; Xu, Peng

2015-01-30

The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome. However, most of the current AR models are based on the L2 norm structure, which exaggerates the outlier effect due to the square property of the L2 norm. In this paper, a novel AR object function is constructed in the Lp (p≤1) norm space with the aim to compress the outlier effects on EEG analysis, and a fast iteration procedure is developed to solve this new AR model. The quantitative evaluation using simulated EEGs with outliers proves that the proposed Lp (p≤1) AR can estimate the AR parameters more robustly than the Yule-Walker, Burg and LS methods, under various simulated outlier conditions. The actual application to the resting EEG recording with ocular artifacts also demonstrates that Lp (p≤1) AR can effectively address the outliers and recover a resting EEG power spectrum that is more consistent with its physiological basis. Copyright © 2014 Elsevier B.V. All rights reserved.

Non performing loans (NPLs) in a crisis economy: Long-run equilibrium analysis with a real time VEC model for Greece (2001-2015)

NASA Astrophysics Data System (ADS)

Konstantakis, Konstantinos N.; Michaelides, Panayotis G.; Vouldis, Angelos T.

2016-06-01

As a result of domestic and international factors, the Greek economy faced a severe crisis which is directly comparable only to the Great Recession. In this context, a prominent victim of this situation was the country's banking system. This paper attempts to shed light on the determining factors of non-performing loans in the Greek banking sector. The analysis presents empirical evidence from the Greek economy, using aggregate data on a quarterly basis, in the time period 2001-2015, fully capturing the recent recession. In this work, we use a relevant econometric framework based on a real time Vector Autoregressive (VAR)-Vector Error Correction (VEC) model, which captures the dynamic interdependencies among the variables used. Consistent with international evidence, the empirical findings show that both macroeconomic and financial factors have a significant impact on non-performing loans in the country. Meanwhile, the deteriorating credit quality feeds back into the economy leading to a self-reinforcing negative loop.

[Climate change - a pioneer for the expansion of canine vector-borne diseases?].

PubMed

Krämer, F; Mencke, N

2011-01-01

Vector-transmitted diseases are one of the major contributors to the global burden of disease in humans and animals. Climate change is consistently held responsible for the spread of parasitic acarid and insect vectors such as ticks, fleas, sand flies and mosquitoes, and their transmitted pathogens (in the case of the dog the so-called canine vector-borne diseases [CVBD]). Currently, there is only insufficient data available to prove whether climate change is a major driving force for vector and disease expansion, but the evidence is growing. Other reasons, such as ecological, demographic and socio-economic factors, e.g. pet travel into and pet import from endemic areas, also play a role in this development. Apart from all the controversial discussion of the factors leading to vector and disease expansion, preventative measures should include dog owners' education as they are responsible for individual parasite protection as well as for the minimisation of adverse risk behaviour, e.g. regarding pet travel. Broad-spectrum vector control should be practised by using parasiticides that repel and kill blood feeders in order to minimize the risk of CVBD-pathogen transmission.

Chagas' disease: risk factors for house infestation by Triatoma dimidiata, the major vector of Trypanosoma cruzi in Costa Rica.

PubMed

Starr, M D; Rojas, J C; Zeledón, R; Hird, D W; Carpenter, T E

1991-04-01

The reduction of domiciliary infestation by insect vectors, the key to controlling Chagas' disease, depends on identification of housing features associated with infestation. In this study, log-linear modeling was used to reanalyze data collected in 1964-1968 from 371 houses on characteristics potentially associated with infestation by the vector Triatoma dimidiata in a Costa Rican town with endemic Chagas' disease. A possible increased risk of infestation was observed for houses with a dirt floor (as compared with houses with another floor type) and for houses in poor sanitary condition (as compared with houses in good sanitary condition). A new risk factor for house infestation, the presence of roof tiles, was identified; the odds of infestation for houses with a tile roof were 2.4 times greater than the odds for houses with a galvanized metal roof. This significantly increased risk is probably due to the harboring of T. dimidiata in stacks of spare tiles next to house walls rather than to the tile roofs themselves.

Breast augmentation surgery

MedlinePlus

... the shape of your breasts. Talk with a plastic surgeon if you are considering breast augmentation. Discuss ... mammograms or breast x-rays before surgery. The plastic surgeon will do a routine breast exam. Several ...

Customized biomaterials to augment chondrocyte gene therapy.

PubMed

Aguilar, Izath Nizeet; Trippel, Stephen; Shi, Shuiliang; Bonassar, Lawrence J

2017-04-15

A persistent challenge in enhancing gene therapy is the transient availability of the target gene product. This is particularly true in tissue engineering applications. The transient exposure of cells to the product could be insufficient to promote tissue regeneration. Here we report the development of a new material engineered to have a high affinity for a therapeutic gene product. We focus on insulin-like growth factor-I (IGF-I) for its highly anabolic effects on many tissues such as spinal cord, heart, brain and cartilage. One of the ways that tissues store IGF-I is through a group of insulin like growth factor binding proteins (IGFBPs), such as IGFBP-5. We grafted the IGF-I binding peptide sequence from IGFBP-5 onto alginate in order to retain the endogenous IGF-I produced by transfected chondrocytes. This novel material bound IGF-I and released the growth factor for at least 30days in culture. We found that this binding enhanced the biosynthesis of transfected cells up to 19-fold. These data demonstrate the coordinated engineering of cell behavior and material chemistry to greatly enhance extracellular matrix synthesis and tissue assembly, and can serve as a template for the enhanced performance of other therapeutic proteins. The present manuscript focuses on the enhancement of chondrocyte gene therapy through the modification of scaffold materials to enhance the retention of targeted gene products. This study combined tissue engineering and gene therapy, where customized biomaterials augmented the action of IGF-I by enhancing the retention of protein produced by transfection of the IGF-I gene. This approach enabled tuning of binding of IGF-I to alginate, which increased GAG and HYPRO production by transfected chondrocytes. To our knowledge, peptide-based modification of materials to augment growth factor-targeted gene therapy has not been reported previously. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Autoregressive spatially varying coefficients model for predicting daily PM2.5 using VIIRS satellite AOT

NASA Astrophysics Data System (ADS)

Schliep, E. M.; Gelfand, A. E.; Holland, D. M.

2015-12-01

There is considerable demand for accurate air quality information in human health analyses. The sparsity of ground monitoring stations across the United States motivates the need for advanced statistical models to predict air quality metrics, such as PM2.5, at unobserved sites. Remote sensing technologies have the potential to expand our knowledge of PM2.5 spatial patterns beyond what we can predict from current PM2.5 monitoring networks. Data from satellites have an additional advantage in not requiring extensive emission inventories necessary for most atmospheric models that have been used in earlier data fusion models for air pollution. Statistical models combining monitoring station data with satellite-obtained aerosol optical thickness (AOT), also referred to as aerosol optical depth (AOD), have been proposed in the literature with varying levels of success in predicting PM2.5. The benefit of using AOT is that satellites provide complete gridded spatial coverage. However, the challenges involved with using it in fusion models are (1) the correlation between the two data sources varies both in time and in space, (2) the data sources are temporally and spatially misaligned, and (3) there is extensive missingness in the monitoring data and also in the satellite data due to cloud cover. We propose a hierarchical autoregressive spatially varying coefficients model to jointly model the two data sources, which addresses the foregoing challenges. Additionally, we offer formal model comparison for competing models in terms of model fit and out of sample prediction of PM2.5. The models are applied to daily observations of PM2.5 and AOT in the summer months of 2013 across the conterminous United States. Most notably, during this time period, we find small in-sample improvement incorporating AOT into our autoregressive model but little out-of-sample predictive improvement.

Covariantized vector Galileons

NASA Astrophysics Data System (ADS)

Hull, Matthew; Koyama, Kazuya; Tasinato, Gianmassimo

2016-03-01

Vector Galileons are ghost-free systems containing higher derivative interactions of vector fields. They break the vector gauge symmetry, and the dynamics of the longitudinal vector polarizations acquire a Galileon symmetry in an appropriate decoupling limit in Minkowski space. Using an Arnowitt-Deser-Misner approach, we carefully reconsider the coupling with gravity of vector Galileons, with the aim of studying the necessary conditions to avoid the propagation of ghosts. We develop arguments that put on a more solid footing the results previously obtained in the literature. Moreover, working in analogy with the scalar counterpart, we find indications for the existence of a "beyond Horndeski" theory involving vector degrees of freedom that avoids the propagation of ghosts thanks to secondary constraints. In addition, we analyze a Higgs mechanism for generating vector Galileons through spontaneous symmetry breaking, and we present its consistent covariantization.

Chin augmentation - slideshow

MedlinePlus

... page: //medlineplus.gov/ency/presentations/100009.htm Chin augmentation - series—Normal anatomy To use the sharing features ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated: ...

Breast augmentation - slideshow

MedlinePlus

... page: //medlineplus.gov/ency/presentations/100205.htm Breast augmentation - series—Normal anatomy To use the sharing features ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated: ...

A flight investigation of the stability, control, and handling qualities of an augmented jet flap STOL airplane

NASA Technical Reports Server (NTRS)

Vomaske, R. F.; Innis, R. C.; Swan, B. E.; Grossmith, S. W.

1978-01-01

The stability, control, and handling qualities of an augmented jet flap STOL airplane are presented. The airplane is an extensively modified de Havilland Buffalo military transport. The modified airplane has two fan-jet engines which provide vectorable thrust and compressed air for the augmentor jet flap and Boundary-Layer Control (BLC). The augmentor and BLC air is cross ducted to minimize asymmetric moments produced when one engine is inoperative. The modifications incorporated in the airplane include a Stability Augmentation System (SAS), a powered elevator, and a powered lateral control system. The test gross weight of the airplane was between 165,000 and 209,000 N (37,000 and 47,000 lb). Stability, control, and handling qualities are presented for the airspeed range of 40 to 180 knots. The lateral-directional handling qualities are considered satisfactory for the normal operating range of 65 to 160 knots airspeed when the SAS is functioning. With the SAS inoperative, poor turn coordination and spiral instability are primary deficiencies contributing to marginal handling qualities in the landing approach. The powered elevator control system enhanced the controllability in pitch, particularly in the landing flare and stall recovery.

Self-organising mixture autoregressive model for non-stationary time series modelling.

PubMed

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

A time series model: First-order integer-valued autoregressive (INAR(1))

NASA Astrophysics Data System (ADS)

Simarmata, D. M.; Novkaniza, F.; Widyaningsih, Y.

2017-07-01

Nonnegative integer-valued time series arises in many applications. A time series model: first-order Integer-valued AutoRegressive (INAR(1)) is constructed by binomial thinning operator to model nonnegative integer-valued time series. INAR (1) depends on one period from the process before. The parameter of the model can be estimated by Conditional Least Squares (CLS). Specification of INAR(1) is following the specification of (AR(1)). Forecasting in INAR(1) uses median or Bayesian forecasting methodology. Median forecasting methodology obtains integer s, which is cumulative density function (CDF) until s, is more than or equal to 0.5. Bayesian forecasting methodology forecasts h-step-ahead of generating the parameter of the model and parameter of innovation term using Adaptive Rejection Metropolis Sampling within Gibbs sampling (ARMS), then finding the least integer s, where CDF until s is more than or equal to u . u is a value taken from the Uniform(0,1) distribution. INAR(1) is applied on pneumonia case in Penjaringan, Jakarta Utara, January 2008 until April 2016 monthly.

Augmented reality-assisted skull base surgery.

PubMed

Cabrilo, I; Sarrafzadeh, A; Bijlenga, P; Landis, B N; Schaller, K

2014-12-01

Neuronavigation is widely considered as a valuable tool during skull base surgery. Advances in neuronavigation technology, with the integration of augmented reality, present advantages over traditional point-based neuronavigation. However, this development has not yet made its way into routine surgical practice, possibly due to a lack of acquaintance with these systems. In this report, we illustrate the usefulness and easy application of augmented reality-based neuronavigation through a case example of a patient with a clivus chordoma. We also demonstrate how augmented reality can help throughout all phases of a skull base procedure, from the verification of neuronavigation accuracy to intraoperative image-guidance. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Therapeutics: Alpha-1 Antitrypsin Augmentation Therapy.

PubMed

Campos, Michael; Lascano, Jorge

2017-01-01

Subjects with alpha-1 antitrypsin deficiency who develop pulmonary disease are managed following general treatment guidelines, including disease management interventions. In addition, administration of intravenous infusions of alpha-1 proteinase inhibitor (augmentation therapy) at regular schedules is a specific therapy for individuals with AATD with pulmonary involvement.This chapter summarizes the manufacturing differences of commercially available formulations and the available evidence of the effects of augmentation therapy. Biologically, there is clear evidence of in vivo local antiprotease effects in the lung and systemic immunomodulatory effects. Clinically, there is cumulative evidence of slowing lung function decline and emphysema progression. The optimal dose of augmentation therapy is being revised as well as more individualized assessment of who needs this therapy.

The hopf algebra of vector fields on complex quantum groups

NASA Astrophysics Data System (ADS)

Drabant, Bernhard; Jurčo, Branislav; Schlieker, Michael; Weich, Wolfgang; Zumino, Bruno

1992-10-01

We derive the equivalence of the complex quantum enveloping algebra and the algebra of complex quantum vector fields for the Lie algebra types A n , B n , C n , and D n by factorizing the vector fields uniquely into a triangular and a unitary part and identifying them with the corresponding elements of the algebra of regular functionals.

Enhancing Education through Mobile Augmented Reality

ERIC Educational Resources Information Center

Joan, D. R. Robert

2015-01-01

In this article, the author has discussed about the Mobile Augmented Reality and enhancing education through it. The aim of the present study was to give some general information about mobile augmented reality which helps to boost education. Purpose of the current study reveals the mobile networks which are used in the institution campus as well…

Augmented Reality as a Countermeasure for Sleep Deprivation.

PubMed

Baumeister, James; Dorrlan, Jillian; Banks, Siobhan; Chatburn, Alex; Smith, Ross T; Carskadon, Mary A; Lushington, Kurt; Thomas, Bruce H

2016-04-01

Sleep deprivation is known to have serious deleterious effects on executive functioning and job performance. Augmented reality has an ability to place pertinent information at the fore, guiding visual focus and reducing instructional complexity. This paper presents a study to explore how spatial augmented reality instructions impact procedural task performance on sleep deprived users. The user study was conducted to examine performance on a procedural task at six time points over the course of a night of total sleep deprivation. Tasks were provided either by spatial augmented reality-based projections or on an adjacent monitor. The results indicate that participant errors significantly increased with the monitor condition when sleep deprived. The augmented reality condition exhibited a positive influence with participant errors and completion time having no significant increase when sleep deprived. The results of our study show that spatial augmented reality is an effective sleep deprivation countermeasure under laboratory conditions.

Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation.

PubMed

Zhang, Xiangjun; Wu, Xiaolin

2008-06-01

The challenge of image interpolation is to preserve spatial details. We propose a soft-decision interpolation technique that estimates missing pixels in groups rather than one at a time. The new technique learns and adapts to varying scene structures using a 2-D piecewise autoregressive model. The model parameters are estimated in a moving window in the input low-resolution image. The pixel structure dictated by the learnt model is enforced by the soft-decision estimation process onto a block of pixels, including both observed and estimated. The result is equivalent to that of a high-order adaptive nonseparable 2-D interpolation filter. This new image interpolation approach preserves spatial coherence of interpolated images better than the existing methods, and it produces the best results so far over a wide range of scenes in both PSNR measure and subjective visual quality. Edges and textures are well preserved, and common interpolation artifacts (blurring, ringing, jaggies, zippering, etc.) are greatly reduced.

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

NASA Astrophysics Data System (ADS)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-09-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

Gas Chromatography Data Classification Based on Complex Coefficients of an Autoregressive Model

DOE PAGES

Zhao, Weixiang; Morgan, Joshua T.; Davis, Cristina E.

2008-01-01

This paper introduces autoregressive (AR) modeling as a novel method to classify outputs from gas chromatography (GC). The inverse Fourier transformation was applied to the original sensor data, and then an AR model was applied to transform data to generate AR model complex coefficients. This series of coefficients effectively contains a compressed version of all of the information in the original GC signal output. We applied this method to chromatograms resulting from proliferating bacteria species grown in culture. Three types of neural networks were used to classify the AR coefficients: backward propagating neural network (BPNN), radial basis function-principal component analysismore » (RBF-PCA) approach, and radial basis function-partial least squares regression (RBF-PLSR) approach. This exploratory study demonstrates the feasibility of using complex root coefficient patterns to distinguish various classes of experimental data, such as those from the different bacteria species. This cognition approach also proved to be robust and potentially useful for freeing us from time alignment of GC signals.« less

Media-Augmented Exercise Machines

NASA Astrophysics Data System (ADS)

Krueger, T.

2002-01-01

Cardio-vascular exercise has been used to mitigate the muscle and cardiac atrophy associated with adaptation to micro-gravity environments. Several hours per day may be required. In confined spaces and long duration missions this kind of exercise is inevitably repetitive and rapidly becomes uninteresting. At the same time, there are pressures to accomplish as much as possible given the cost- per-hour for humans occupying orbiting or interplanetary. Media augmentation provides a the means to overlap activities in time by supplementing the exercise with social, recreational, training or collaborative activities and thereby reducing time pressures. In addition, the machine functions as an interface to a wide range of digital environments allowing for spatial variety in an otherwise confined environment. We hypothesize that the adoption of media augmented exercise machines will have a positive effect on psycho-social well-being on long duration missions. By organizing and supplementing exercise machines, data acquisition hardware, computers and displays into an interacting system this proposal increases functionality with limited additional mass. This paper reviews preliminary work on a project to augment exercise equipment in a manner that addresses these issues and at the same time opens possibilities for additional benefits. A testbed augmented exercise machine uses a specialty built cycle trainer as both input to a virtual environment and as an output device from it using spatialized sound, and visual displays, vibration transducers and variable resistance. The resulting interactivity increases a sense of engagement in the exercise, provides a rich experience of the digital environments. Activities in the virtual environment and accompanying physiological and psychological indicators may be correlated to track and evaluate the health of the crew.

Receptor-mediated gene transfer vectors: progress towards genetic pharmaceuticals.

PubMed

Molas, M; Gómez-Valadés, A G; Vidal-Alabró, A; Miguel-Turu, M; Bermudez, J; Bartrons, R; Perales, J C

2003-10-01

Although specific delivery to tissues and unique cell types in vivo has been demonstrated for many non-viral vectors, current methods are still inadequate for human applications, mainly because of limitations on their efficiencies. All the steps required for an efficient receptor-mediated gene transfer process may in principle be exploited to enhance targeted gene delivery. These steps are: DNA/vector binding, internalization, subcellular trafficking, vesicular escape, nuclear import, and unpacking either for transcription or other functions (i.e., antisense, RNA interference, etc.). The large variety of vector designs that are currently available, usually aimed at improving the efficiency of these steps, has complicated the evaluation of data obtained from specific derivatives of such vectors. The importance of the structure of the final vector and the consequences of design decisions at specific steps on the overall efficiency of the vector will be discussed in detail. We emphasize in this review that stability in serum and thus, proper bioavailability of vectors to their specific receptors may be the single greatest limiting factor on the overall gene transfer efficiency in vivo. We discuss current approaches to overcome the intrinsic instability of synthetic vectors in the blood. In this regard, a summary of the structural features of the vectors obtained from current protocols will be presented and their functional characteristics evaluated. Dissecting information on molecular conjugates obtained by such methodologies, when carefully evaluated, should provide important guidelines for the creation of effective, targeted and safe DNA therapeutics.

Analytic calculation of finite-population reproductive numbers for direct- and vector-transmitted diseases with homogeneous mixing.

PubMed

Keegan, Lindsay; Dushoff, Jonathan

2014-05-01

The basic reproductive number, R0, provides a foundation for evaluating how various factors affect the incidence of infectious diseases. Recently, it has been suggested that, particularly for vector-transmitted diseases, R0 should be modified to account for the effects of finite host population within a single disease transmission generation. Here, we use a transmission factor approach to calculate such "finite-population reproductive numbers," under the assumption of homogeneous mixing, for both vector-borne and directly transmitted diseases. In the case of vector-borne diseases, we estimate finite-population reproductive numbers for both host-to-host and vector-to-vector generations, assuming that the vector population is effectively infinite. We find simple, interpretable formulas for all three of these quantities. In the direct case, we find that finite-population reproductive numbers diverge from R0 before R0 reaches half of the population size. In the vector-transmitted case, we find that the host-to-host number diverges at even lower values of R0, while the vector-to-vector number diverges very little over realistic parameter ranges.

Genetic variation in arthropod vectors of disease-causing organisms: obstacles and opportunities.

PubMed Central

Gooding, R H

1996-01-01

An overview of the genetic variation in arthropods that transmit pathogens to vertebrates is presented, emphasizing the genetics of vector-pathogen relationships and the biochemical genetics of vectors. Vector-pathogen interactions are reviewed briefly as a prelude to a discussion of the genetics of susceptibility and refractoriness in vectors. Susceptibility to pathogens is controlled by maternally inherited factors, sex-linked dominant alleles, and dominant and recessive autosomal genes. There is widespread interpopulation (including intercolony) and temporal variation in susceptibility to pathogens. The amount of biochemical genetic variation in vectors is similar to that found in other invertebrates. However, the amount varies widely among species, among populations within species, and temporally within populations. Biochemical genetic studies show that there is considerable genetic structuring of many vectors at the local, regional, and global levels. It is argued that genetic variation in vectors is critical in understanding vector-pathogen interactions and that genetic variation in vectors creates both obstacles to and opportunities for application of genetic techniques to the control of vectors. PMID:8809462

Periodontal considerations for esthetics: edentulous ridge augmentation.

PubMed

Rosenberg, E S; Cutler, S A

1993-01-01

Edentulous ridge augmentation is a plastic surgical technique that is performed to improve patient esthetics when unsightly, deformed ridges exist. This article describes the etiology of ridge deformities and the many procedures that can be executed to achieve an esthetic, functional result. Historically, soft-tissue mucogingival techniques were described to augment collapsed ridges. Pedicle grafts, free soft-tissue grafts, and subepithelial connective tissue grafts are predictable forms of therapy. More recently, ridge augmentation techniques were developed that regenerate the lost periodontium. These include allografts, bioglasses, guided tissue regenerative procedures, and tissue expansion.

Optimal control applied to a model for species augmentation.

PubMed

Bodine, Erin N; Gross, Louis J; Lenhart, Suzanne

2008-10-01

Species augmentation is a method of reducing species loss via augmenting declining or threatened populations with individuals from captive-bred or stable, wild populations. In this paper, we develop a differential equations model and optimal control formulation for a continuous time augmentation of a general declining population. We find a characterization for the optimal control and show numerical results for scenarios of different illustrative parameter sets. The numerical results provide considerably more detail about the exact dynamics of optimal augmentation than can be readily intuited. The work and results presented in this paper are a first step toward building a general theory of population augmentation, which accounts for the complexities inherent in many conservation biology applications.

Strategies for vectorizing the sparse matrix vector product on the CRAY XMP, CRAY 2, and CYBER 205

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Partridge, Harry

1987-01-01

Large, randomly sparse matrix vector products are important in a number of applications in computational chemistry, such as matrix diagonalization and the solution of simultaneous equations. Vectorization of this process is considered for the CRAY XMP, CRAY 2, and CYBER 205, using a matrix of dimension of 20,000 with from 1 percent to 6 percent nonzeros. Efficient scatter/gather capabilities add coding flexibility and yield significant improvements in performance. For the CYBER 205, it is shown that minor changes in the IO can reduce the CPU time by a factor of 50. Similar changes in the CRAY codes make a far smaller improvement.

Relating Factor Models for Longitudinal Data to Quasi-Simplex and NARMA Models

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2005-01-01

In this article we show the one-factor model can be rewritten as a quasi-simplex model. Using this result along with addition theorems from time series analysis, we describe a common general model, the nonstationary autoregressive moving average (NARMA) model, that includes as a special case, any latent variable model with continuous indicators…

Assessment of Climate Change and Vector-borne Diseases in the United States

NASA Astrophysics Data System (ADS)

Monaghan, A. J.; Beard, C. B.; Eisen, R. J.; Barker, C. M.; Garofalo, J.; Hahn, M.; Hayden, M.; Ogden, N.; Schramm, P.

2016-12-01

Vector-borne diseases are illnesses that are transmitted by vectors, which include mosquitoes, ticks, and fleas. The seasonality, distribution, and prevalence of vector-borne diseases are influenced significantly by climate factors, primarily high and low temperature extremes and precipitation patterns. In this presentation we summarize key findings from Chapter 5 ("Vector-borne Diseases") of the recently published USGCRP Scientific Assessment of the Impacts of Climate Change on Human Health in the United States. Climate change is expected to alter geographic and seasonal distributions of vectors and vector-borne diseases, leading to earlier activity and northward range expansion of ticks capable of carrying the bacteria that cause Lyme disease and other pathogens, and influencing the distribution, abundance and prevalence of infection in mosquitoes that transmit West Nile virus and other pathogens. The emergence or reemergence of vector-borne pathogens is also likely.

Recent Development of Augmented Reality in Surgery: A Review

PubMed Central

Vávra, P.; Zonča, P.; Ihnát, P.; El-Gendi, A.

2017-01-01

Introduction The development augmented reality devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency, safety, and cost and to enhance surgical training. However, the awareness of possibilities of augmented reality is generally low. This review evaluates whether augmented reality can presently improve the results of surgical procedures. Methods We performed a review of available literature dating from 2010 to November 2016 by searching PubMed and Scopus using the terms “augmented reality” and “surgery.” Results. The initial search yielded 808 studies. After removing duplicates and including only journal articles, a total of 417 studies were identified. By reading of abstracts, 91 relevant studies were chosen to be included. 11 references were gathered by cross-referencing. A total of 102 studies were included in this review. Conclusions The present literature suggest an increasing interest of surgeons regarding employing augmented reality into surgery leading to improved safety and efficacy of surgical procedures. Many studies showed that the performance of newly devised augmented reality systems is comparable to traditional techniques. However, several problems need to be addressed before augmented reality is implemented into the routine practice. PMID:29065604

Recent Development of Augmented Reality in Surgery: A Review.

PubMed

Vávra, P; Roman, J; Zonča, P; Ihnát, P; Němec, M; Kumar, J; Habib, N; El-Gendi, A

2017-01-01

The development augmented reality devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency, safety, and cost and to enhance surgical training. However, the awareness of possibilities of augmented reality is generally low. This review evaluates whether augmented reality can presently improve the results of surgical procedures. We performed a review of available literature dating from 2010 to November 2016 by searching PubMed and Scopus using the terms "augmented reality" and "surgery." Results . The initial search yielded 808 studies. After removing duplicates and including only journal articles, a total of 417 studies were identified. By reading of abstracts, 91 relevant studies were chosen to be included. 11 references were gathered by cross-referencing. A total of 102 studies were included in this review. The present literature suggest an increasing interest of surgeons regarding employing augmented reality into surgery leading to improved safety and efficacy of surgical procedures. Many studies showed that the performance of newly devised augmented reality systems is comparable to traditional techniques. However, several problems need to be addressed before augmented reality is implemented into the routine practice.

Education and Economic Growth in Pakistan: A Cointegration and Causality Analysis

ERIC Educational Resources Information Center

Afzal, Muhammad; Rehman, Hafeez Ur; Farooq, Muhammad Shahid; Sarwar, Kafeel

2011-01-01

This study explored the cointegration and causality between education and economic growth in Pakistan by using time series data on real gross domestic product (RGDP), labour force, physical capital and education from 1970-1971 to 2008-2009 were used. Autoregressive Distributed Lag (ARDL) Model of Cointegration and the Augmented Granger Causality…

The protective effect of platelet released growth factors and bone augmentation (Bio-Oss®) on ethanol impaired osteoblasts.

PubMed

Sönmez, Tolga Taha; Bayer, Andreas; Cremer, Tillman; Hock, Jennifer Vanessa Phi; Lethaus, Bernd; Kweider, Nisreen; Wruck, Christoph Jan; Drescher, Wolf; Jahr, Holger; Lippross, Sebastian; Pufe, Thomas; Tohidnezhad, Mersedeh

2017-11-01

Chronic alcohol consumption is a known limiting factor for bone healing. One promising strategy to improve bone augmentation techniques with Bio-Oss ® in oral and maxillofacial surgery might be the supportive application of platelet-concentrated biomaterials as platelet-released growth factor (PRGF). To address this matter, we performed an in vitro study investigating the protective effects of PRGF and Bio-Oss ® in ethanol (EtOH) treated osteoblasts. The SAOS-2 osteosarcoma cell line, with and without EtOH pretreatment was used. The cell viability, proliferation and alkali phosphatase activity (ALP) after application of 0%, 5% and 10% PRGF and Bio-Oss ® were assessed. The application of PRGF and Bio-Oss ® in EtOH impaired osteoblasts showed a significant beneficial influence increasing the viability of the osteoblasts in cell culture. The synergistic effect of Bio-Oss ® and 5% PRGF on the proliferation of osteoblasts was also demonstrated. Bio-Oss ® only in combination with PRGF increases the alkaline phosphatase (ALP) activity in EtOH pretreated cells. These results indicate that the simultaneous application of PRGF and Bio-Oss ® inhibits EtOH induced bone healing impairment. Furthermore, in the cells, PRGF induced a protective mechanism which might promote bone regeneration. Copyright © 2017 Elsevier GmbH. All rights reserved.

Sparse representation based image interpolation with nonlocal autoregressive modeling.

PubMed

Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

2013-04-01

Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

Problems Inherent to Augmentation of Natural Enemies in Open Agriculture.

PubMed

Michaud, J P

2018-04-01

Augmentation biological control has successfully replaced a lot of insecticide use in 'closed system' agriculture (e.g., greenhouses). The profitable commercialization of biocontrol agents in greenhouses has created an incentive to expand markets for mass-reared beneficial insects into open agricultural systems, often without sufficient scientific justification. However, the semi-contained nature of greenhouse culture is often critical to the success of augmentation and can serve to mask potential pitfalls and intrinsic limitations of this approach in open systems. Factors contributing to greenhouse successes include the reduced biological diversity of contained agroecosystems, the prevention of agent dispersal, the ability to maintain environmental conditions within a range favorable for the agent, the exclusion of competitors and natural enemies of the agent that might otherwise diminish its efficacy, and the absence of alternative prey/hosts that could divert predation/parasitism from the target pest. There are also problems arising from collection of source material from locally adapted populations, and the inadvertent imposition of artificial selection in the course of laboratory rearing. Besides highlighting these pitfalls, this paper aims to encourage more consideration of conservation approaches prior to investment in augmentation programs which entice farmers into perpetual cycles of 'rear and release.' I argue that although augmentation can benefit agriculture whenever it replaces pesticide applications, it does not constitute an ecologically sustainable solution because it requires continued inputs, and it can distract research attention away from more sustainable objectives. Sustainable biological control is best achieved through modifications to cultural practices that increasingly 'naturalize' agroecosystems, thus facilitating the natural recruitment and persistence of beneficial arthropod fauna, combined with habitat management geared to increasing

An acceptance model for smart glasses based tourism augmented reality

NASA Astrophysics Data System (ADS)

Obeidy, Waqas Khalid; Arshad, Haslina; Huang, Jiung Yao

2017-10-01

Recent mobile technologies have revolutionized the way people experience their environment. Although, there is only limited research on users' acceptance of AR in the cultural tourism context, previous researchers have explored the opportunities of using augmented reality (AR) in order to enhance user experience. Recent AR research lack works that integrates dimensions which are specific to cultural tourism and smart glass specific context. Hence, this work proposes an AR acceptance model in the context of cultural heritage tourism and smart glasses capable of performing augmented reality. Therefore, in this paper we aim to present an AR acceptance model to understand the AR usage behavior and visiting intention for tourists who use Smart Glass based AR at UNESCO cultural heritage destinations in Malaysia. Furthermore, this paper identifies information quality, technology readiness, visual appeal, and facilitating conditions as external variables and key factors influencing visitors' beliefs, attitudes and usage intention.

Double breast contour in primary aesthetic breast augmentation: incidence, prevention and treatment.

PubMed

Médard de Chardon, Victor; Balaguer, Thierry; Chignon-Sicard, Bérengère; Lebreton, Elisabeth

2010-04-01

The goal of this study was to define the incidence of double breast contour in primary aesthetic breast augmentation and to analyze its risk factors. An independent plastic surgeon analyzed the data of 200 patients who had a primary aesthetic breast augmentation with silicone gel implant and with a minimum 12-month follow-up. All patients had pre and postoperative standardized photography. Mastopexy-augmentations, breast reconstructions, breast malformations (tuberous breasts and Poland syndrome), and patients with incomplete data were excluded from the study. Assessment was achieved using an original standardized evaluation form (preoperative breast morphology, surgical options, postoperative aesthetic results). Patients were also asked to complete an exhaustive satisfaction form. A double breast contour was assessed clinically using Massiha's classification. The mean follow-up was 36 months. The double breast contour incidence was 7%. All of them were type I (the so called waterfall deformity). There was no type II (double inframammary crease). They were minor for 6.5% and major for 0.5%. They were related to a preoperative breast ptosis, subpectoral placement, and implant upper malposition. The rate of the type I was 10.5% of submuscular augmentation and 15% of preoperative breast ptosis. A double breast contour was primitive for 6% and secondary for 1% (pregnancy and breast-feeding postaugmentation). It was bilateral for 4.5% (3 cases of upper malposition, 1 case of medial malposition, 2 cases of pregnancy with breast-feeding postaugmentation and 1 patient refused a mastopexy-augmentation). It was unilateral for 2.5% related to a preoperative breast asymmetry with ptosis asymmetry and skin quality asymmetry. The satisfaction rate in the group "double contour" (14 patients) was 85.7% (vs. 91.9%). One patient had revision surgery (upper malposition). These types of deformities are fundamentally different with consideration on their clinical aspects

Augmented Reality for Close Quarters Combat

ScienceCinema

None

2018-01-16

Sandia National Laboratories has developed a state-of-the-art augmented reality training system for close-quarters combat (CQB). This system uses a wearable augmented reality system to place the user in a real environment while engaging enemy combatants in virtual space (Boston Dynamics DI-Guy). Umbra modeling and simulation environment is used to integrate and control the AR system.

Age grouping to optimize augmentation success.

PubMed

Gordon, Robert W

2010-05-01

This article has described the different age groups that present for noninvasive injectable lip and perioral augmentation, as well as the breakdown of 3 subgroups that present within the 4 general age groups. With the fundamental understanding of these presenting groups and subgroups, the practicing augmenter will be able to better treatment plan and educate the patient on realistic and optimal aesthetic outcomes.

Magnetohydrodynamic Augmentation of Pulse Detonation Rocket Engines (Preprint)

DTIC Science & Technology

2010-09-28

augmentation of the thrust . Ejectors typically transfer energy between streams through shear stress between separate flow streams, where a portion of the...the opportunity to extract energy and apply it to a separate stream where the net thrust can be increased. With MHD augmentation , such as in the Pulse...with the PDRIME for separate or additional thrust augmentation . Results show potential performance gains under many flight and operating conditions

On feature augmentation for semantic argument classification of the Quran English translation using support vector machine

NASA Astrophysics Data System (ADS)

Khaira Batubara, Dina; Arif Bijaksana, Moch; Adiwijaya

2018-03-01

Research on the semantic argument classification requires semantically labeled data in large numbers, called corpus. Because building a corpus is costly and time-consuming, recently many studies have used existing corpus as the training data to conduct semantic argument classification research on new domain. But previous studies have proven that there is a significant decrease in performance when classifying semantic arguments on different domain between the training and the testing data. The main problem is when there is a new argument that found in the testing data but it is not found in the training data. This research carries on semantic argument classification on a new domain that is Quran English Translation by utilizing Propbank corpus as the training data. To recognize the new argument in the training data, this research proposes four new features for extending the argument features in the training data. By using SVM Linear, the experiment has proven that augmenting the proposed features to the baseline system with some combinations option improve the performance of semantic argument classification on Quran data using Propbank Corpus as training data.

Versatile generation of optical vector fields and vector beams using a non-interferometric approach.

PubMed

Tripathi, Santosh; Toussaint, Kimani C

2012-05-07

We present a versatile, non-interferometric method for generating vector fields and vector beams which can produce all the states of polarization represented on a higher-order Poincaré sphere. The versatility and non-interferometric nature of this method is expected to enable exploration of various exotic properties of vector fields and vector beams. To illustrate this, we study the propagation properties of some vector fields and find that, in general, propagation alters both their intensity and polarization distribution, and more interestingly, converts some vector fields into vector beams. In the article, we also suggest a modified Jones vector formalism to represent vector fields and vector beams.

Support vector machine in crash prediction at the level of traffic analysis zones: Assessing the spatial proximity effects.

PubMed

Dong, Ni; Huang, Helai; Zheng, Liang

2015-09-01

In zone-level crash prediction, accounting for spatial dependence has become an extensively studied topic. This study proposes Support Vector Machine (SVM) model to address complex, large and multi-dimensional spatial data in crash prediction. Correlation-based Feature Selector (CFS) was applied to evaluate candidate factors possibly related to zonal crash frequency in handling high-dimension spatial data. To demonstrate the proposed approaches and to compare them with the Bayesian spatial model with conditional autoregressive prior (i.e., CAR), a dataset in Hillsborough county of Florida was employed. The results showed that SVM models accounting for spatial proximity outperform the non-spatial model in terms of model fitting and predictive performance, which indicates the reasonableness of considering cross-zonal spatial correlations. The best model predictive capability, relatively, is associated with the model considering proximity of the centroid distance by choosing the RBF kernel and setting the 10% of the whole dataset as the testing data, which further exhibits SVM models' capacity for addressing comparatively complex spatial data in regional crash prediction modeling. Moreover, SVM models exhibit the better goodness-of-fit compared with CAR models when utilizing the whole dataset as the samples. A sensitivity analysis of the centroid-distance-based spatial SVM models was conducted to capture the impacts of explanatory variables on the mean predicted probabilities for crash occurrence. While the results conform to the coefficient estimation in the CAR models, which supports the employment of the SVM model as an alternative in regional safety modeling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

NASA Astrophysics Data System (ADS)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

Vector processing efficiency of plasma MHD codes by use of the FACOM 230-75 APU

NASA Astrophysics Data System (ADS)

Matsuura, T.; Tanaka, Y.; Naraoka, K.; Takizuka, T.; Tsunematsu, T.; Tokuda, S.; Azumi, M.; Kurita, G.; Takeda, T.

1982-06-01

In the framework of pipelined vector architecture, the efficiency of vector processing is assessed with respect to plasma MHD codes in nuclear fusion research. By using a vector processor, the FACOM 230-75 APU, the limit of the enhancement factor due to parallelism of current vector machines is examined for three numerical codes based on a fluid model. Reasonable speed-up factors of approximately 6,6 and 4 times faster than the highly optimized scalar version are obtained for ERATO (linear stability code), AEOLUS-R1 (nonlinear stability code) and APOLLO (1-1/2D transport code), respectively. Problems of the pipelined vector processors are discussed from the viewpoint of restructuring, optimization and choice of algorithms. In conclusion, the important concept of "concurrency within pipelined parallelism" is emphasized.

Gene therapy using retrovirus vectors: vector development and biosafety at clinical trials.

PubMed

Doi, Knayo; Takeuchi, Yasuhiro

2015-01-01

Retrovirus vectors (gammaretroviral and lentiviral vectors) have been considered as promising tools to transfer therapeutic genes into patient cells because they can permanently integrate into host cellular genome. To treat monogenic, inherited diseases, retroviral vectors have been used to add correct genes into patient cells. Conventional gammaretroviral vectors achieved successful results in clinical trials: treated patients had therapeutic gene expression in target cells and had improved symptoms of diseases. However, serious side-effects of leukemia occurred, caused by retroviral insertional mutagenesis (IM). These incidences stressed the importance of monitoring vector integration sites in patient cells as well as of re-consideration on safer vectors. More recently lentiviral vectors which can deliver genes into non-dividing cells started to be used in clinical trials including neurological disorders, showing their efficacy. Vector integration site analysis revealed that lentiviruses integrate less likely to near promoter regions of oncogenes than gammaretroviruses and no adverse events have been reported in lentiviral vector-mediated gene therapy clinical trials. Therefore lentiviral vectors have promises to be applied to a wide range of common diseases in near future. For example, T cells from cancer patients were transduced to express chimeric T cell receptors recognizing their tumour cells enhancing patients' anti-cancer immunity.

Assessment of changes of vector borne diseases with wetland characteristics using multivariate analysis.

PubMed

Sheela, A M; Sarun, S; Justus, J; Vineetha, P; Sheeja, R V

2015-04-01

Vector borne diseases are a threat to human health. Little attention has been paid to the prevention of these diseases. We attempted to identify the significant wetland characteristics associated with the spread of chikungunya, dengue fever and malaria in Kerala, a tropical region of South West India using multivariate analyses (hierarchical cluster analysis, factor analysis and multiple regression). High/medium turbid coastal lagoons and inland water-logged wetlands with aquatic vegetation have significant effect on the incidence of chikungunya while dengue influenced by high turbid coastal beaches and malaria by medium turbid coastal beaches. The high turbidity in water is due to the urban waste discharge namely sewage, sullage and garbage from the densely populated cities and towns. The large extent of wetland is low land area favours the occurrence of vector borne diseases. Hence the provision of pollution control measures at source including soil erosion control measures is vital. The identification of vulnerable zones favouring the vector borne diseases will help the authorities to control pollution especially from urban areas and prevent these vector borne diseases. Future research should cover land use cover changes, climatic factors, seasonal variations in weather and pollution factors favouring the occurrence of vector borne diseases.

An experimental test of alternative population augmentation scenarios.

PubMed

Kronenberger, John A; Gerberich, Jill C; Fitzpatrick, Sarah W; Broder, E Dale; Angeloni, Lisa M; Funk, W Chris

2018-01-19

Human land use is fragmenting habitats worldwide and inhibiting dispersal among previously connected populations of organisms, often leading to inbreeding depression and reduced evolutionary potential in the face of rapid environmental change. To combat this augmentation of isolated populations with immigrants is sometimes used to facilitate demographic and genetic rescue. Augmentation with immigrants that are genetically and adaptively similar to the target population effectively increases population fitness, but if immigrants are very genetically or adaptively divergent, augmentation can lead to outbreeding depression. Despite well-cited guidelines for the best practice selection of immigrant sources, often only highly divergent populations remain, and experimental tests of these riskier augmentation scenarios are essentially nonexistent. We conducted a mesocosm experiment with Trinidadian guppies (Poecilia reticulata) to test the multigenerational demographic and genetic effects of augmenting 2 target populations with 3 types of divergent immigrants. We found no evidence of demographic rescue, but we did observe genetic rescue in one population. Divergent immigrant treatments tended to maintain greater genetic diversity, abundance, and hybrid fitness than controls that received immigrants from the source used to seed the mesocosms. In the second population, divergent immigrants had a slightly negative effect in one treatment, and the benefits of augmentation were less apparent overall, likely because this population started with higher genetic diversity and a lower reproductive rate that limited genetic admixture. Our results add to a growing consensus that gene flow can increase population fitness even when immigrants are more highly divergent and may help reduce uncertainty about the use of augmentation in conservation. © 2018 Society for Conservation Biology.

Augmentation in the treatment of restless legs syndrome with transdermal rotigotine.

PubMed

Beneš, Heike; García-Borreguero, Diego; Ferini-Strambi, Luigi; Schollmayer, Erwin; Fichtner, Andreas; Kohnen, Ralf

2012-06-01

To assess the risk of augmentation under treatment with the transdermally delivered dopamine agonist rotigotine for restless legs syndrome (RLS). Experts in RLS augmentation retrospectively reviewed data from two double-blind, placebo-controlled 6-month trials (745 rotigotine and 214 placebo subjects, NCT00136045 and NCT00135993) and from two open-label 1-year trials (620 rotigotine subjects, NCT00498108 and NCT00263068). All study visits were systematically evaluated applying the Max Planck Institute (MPI) criteria for the diagnosis of both augmentation and clinically relevant augmentation. MPI criteria for augmentation were met on at least one visit by 8.2% of all subjects in the double-blind trials with 12 subjects meeting the criteria for clinically relevant augmentation: 11 under rotigotine (1.5%) and one under placebo treatment. In the open-label trials, 9.7% of all subjects met the MPI criteria for augmentation and 2.9% met the criteria for clinically relevant augmentation. None of the patients treated with rotigotine for up to 1.5 years (double-blind plus open-label trial) discontinued prematurely owing to augmentation. Neither could dose-dependency or a time pattern for clinically relevant augmentation episodes be detected. Our analyses suggest that the risk for clinically relevant augmentation for the duration of up to 18 months of rotigotine treatment is low. Copyright © 2012 Elsevier B.V. All rights reserved.

Two dynamic regimes in the human gut microbiome

PubMed Central

Smillie, Chris S.; Alm, Eric J.

2017-01-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes. PMID:28222117

Two dynamic regimes in the human gut microbiome.

PubMed

Gibbons, Sean M; Kearney, Sean M; Smillie, Chris S; Alm, Eric J

2017-02-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)-a multivariate method developed for econometrics-to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.

Efficacy and safety of a clinically relevant foamy vector design in human hematopoietic repopulating cells.

PubMed

Everson, Elizabeth M; Hocum, Jonah D; Trobridge, Grant D

2018-06-23

Previous studies have shown that foamy viral (FV) vectors are a promising alternative to gammaretroviral and lentiviral vectors and insulators can improve FV vector safety. However, in a previous analysis of insulator effects on FV vector safety, strong viral promoters were used to elicit genotoxic events. Here we developed and analyzed the efficacy and safety of a high-titer, clinically relevant FV vector driven by the housekeeping promoter elongation factor-1α and insulated with an enhancer blocking A1 insulator (FV-EGW-A1). Human CD34 + cord blood cells were exposed to an enhanced green fluorescent protein expressing vector, FV-EGW-A1, at a multiplicity of infection of 10 and then maintained in vitro or transplanted into immunodeficient mice. Flow cytometry was used to measure engraftment and marking in vivo. FV vector integration sites were analyzed to assess safety. FV-EGW-A1 resulted in high-marking, multi-lineage engraftment of human repopulating cells with no evidence of silencing. Engraftment was highly polyclonal with no clonal dominance and a promising safety profile based on integration site analysis. An FV vector with an elongation factor-1α promoter and an A1 insulator is a promising vector design for use in the clinic. This article is protected by copyright. All rights reserved.

Canine vector-borne diseases in Brazil

PubMed Central

Dantas-Torres, Filipe

2008-01-01

Canine vector-borne diseases (CVBDs) are highly prevalent in Brazil and represent a challenge to veterinarians and public health workers, since some diseases are of great zoonotic potential. Dogs are affected by many protozoa (e.g., Babesia vogeli, Leishmania infantum, and Trypanosoma cruzi), bacteria (e.g., Anaplasma platys and Ehrlichia canis), and helminths (e.g., Dirofilaria immitis and Dipylidium caninum) that are transmitted by a diverse range of arthropod vectors, including ticks, fleas, lice, triatomines, mosquitoes, tabanids, and phlebotomine sand flies. This article focuses on several aspects (etiology, transmission, distribution, prevalence, risk factors, diagnosis, control, prevention, and public health significance) of CVBDs in Brazil and discusses research gaps to be addressed in future studies. PMID:18691408

The role of remote sensing and GIS for spatial prediction of vector-borne diseases transmission: a systematic review.

PubMed

Palaniyandi, M

2012-12-01

There have been several attempts made to the appreciation of remote sensing and GIS for the study of vectors, biodiversity, vector presence, vector abundance and the vector-borne diseases with respect to space and time. This study was made for reviewing and appraising the potential use of remote sensing and GIS applications for spatial prediction of vector-borne diseases transmission. The nature of the presence and the abundance of vectors and vector-borne diseases, disease infection and the disease transmission are not ubiquitous and are confined with geographical, environmental and climatic factors, and are localized. The presence of vectors and vector-borne diseases is most complex in nature, however, it is confined and fueled by the geographical, climatic and environmental factors including man-made factors. The usefulness of the present day availability of the information derived from the satellite data including vegetation indices of canopy cover and its density, soil types, soil moisture, soil texture, soil depth, etc. is integrating the information in the expert GIS engine for the spatial analysis of other geoclimatic and geoenvironmental variables. The present study gives the detailed information on the classical studies of the past and present, and the future role of remote sensing and GIS for the vector-borne diseases control. The ecological modeling directly gives us the relevant information to understand the spatial variation of the vector biodiversity, vector presence, vector abundance and the vector-borne diseases in association with geoclimatic and the environmental variables. The probability map of the geographical distribution and seasonal variations of horizontal and vertical distribution of vector abundance and its association with vector -borne diseases can be obtained with low cost remote sensing and GIS tool with reliable data and speed.

Vector independent transmission of the vector-borne bluetongue virus.

PubMed

van der Sluijs, Mirjam Tineke Willemijn; de Smit, Abraham J; Moormann, Rob J M

2016-01-01

Bluetongue is an economically important disease of ruminants. The causative agent, Bluetongue virus (BTV), is mainly transmitted by insect vectors. This review focuses on vector-free BTV transmission, and its epizootic and economic consequences. Vector-free transmission can either be vertical, from dam to fetus, or horizontal via direct contract. For several BTV-serotypes, vertical (transplacental) transmission has been described, resulting in severe congenital malformations. Transplacental transmission had been mainly associated with live vaccine strains. Yet, the European BTV-8 strain demonstrated a high incidence of transplacental transmission in natural circumstances. The relevance of transplacental transmission for the epizootiology is considered limited, especially in enzootic areas. However, transplacental transmission can have a substantial economic impact due to the loss of progeny. Inactivated vaccines have demonstrated to prevent transplacental transmission. Vector-free horizontal transmission has also been demonstrated. Since direct horizontal transmission requires close contact of animals, it is considered only relevant for within-farm spreading of BTV. The genetic determinants which enable vector-free transmission are present in virus strains circulating in the field. More research into the genetic changes which enable vector-free transmission is essential to better evaluate the risks associated with outbreaks of new BTV serotypes and to design more appropriate control measures.

Vectors and Rotations in 3-Dimensions: Vector Algebra for the C++ Programmer

DTIC Science & Technology

2016-12-01

Proving Ground, MD 21005-5068 This report describes 2 C++ classes: a Vector class for performing vector algebra in 3-dimensional space ( 3D ) and a Rotation...class for performing rotations of vectors in 3D . Each class is self-contained in a single header file (Vector.h and Rotation.h) so that a C...vector, rotation, 3D , quaternion, C++ tools, rotation sequence, Euler angles, yaw, pitch, roll, orientation 98 Richard Saucier 410-278-6721Unclassified

Scalar and vector form factors of D →π (K )ℓν decays with Nf=2 +1 +1 twisted fermions

NASA Astrophysics Data System (ADS)

Lubicz, V.; Riggio, L.; Salerno, G.; Simula, S.; Tarantino, C.; ETM Collaboration

2017-09-01

We present a lattice determination of the vector and scalar form factors of the D →π ℓν and D →K ℓν semileptonic decays, which are relevant for the extraction of the CKM matrix elements |Vc d| and |Vc s| from experimental data. Our analysis is based on the gauge configurations produced by the European Twisted Mass Collaboration with Nf=2 +1 +1 flavors of dynamical quarks, at three different values of the lattice spacing (a ≃0.062 ,0.082 ,0.089 fm ) and with pion masses as small as 210 MeV. Quark momenta are injected on the lattice using nonperiodic boundary conditions. The matrix elements of both vector and scalar currents are determined for plenty of kinematical conditions in which parent and child mesons are either moving or at rest. Lorentz symmetry breaking due to hypercubic effects is clearly observed in the data and included in the decomposition of the current matrix elements in terms of additional form factors. After the extrapolations to the physical pion mass and to the continuum limit, we determine the vector and scalar form factors in the whole kinematical region from q2=0 up to qmax2=(MD-Mπ (K ))2 accessible in the experiments, obtaining a good overall agreement with experiments, except in the region at high values of q2 where some deviations are visible. A set of synthetic data points, representing our results for f+Dπ (K )(q2) and f0D π (K )(q2) for several selected values of q2, is provided and also the corresponding covariance matrix is available. At zero four-momentum transfer, we get f+D→π(0 )=0.612 (35 ) and f+D→K(0 )=0.765 (31 ). Using the experimental averages for |Vc d|f+D→π(0 ) and |Vc s|f+D→K(0 ), we extract |Vc d|=0.2330 (137 ) and |Vc s|=0.945 (38 ), respectively. The second row of the CKM matrix is found to be in agreement with unitarity within the current uncertainties: |Vc d|2+|Vc s|2+|Vc b|2=0.949 (78 ).

The comparison study among several data transformations in autoregressive modeling

NASA Astrophysics Data System (ADS)

Setiyowati, Susi; Waluyo, Ramdhani Try

2015-12-01

In finance, the adjusted close of stocks are used to observe the performance of a company. The extreme prices, which may increase or decrease drastically, are often become particular concerned since it can impact to bankruptcy. As preventing action, the investors have to observe the future (forecasting) stock prices comprehensively. For that purpose, time series analysis could be one of statistical methods that can be implemented, for both stationary and non-stationary processes. Since the variability process of stocks prices tend to large and also most of time the extreme values are always exist, then it is necessary to do data transformation so that the time series models, i.e. autoregressive model, could be applied appropriately. One of popular data transformation in finance is return model, in addition to ratio of logarithm and some others Tukey ladder transformation. In this paper these transformations are applied to AR stationary models and non-stationary ARCH and GARCH models through some simulations with varying parameters. As results, this work present the suggestion table that shows transformations behavior for some condition of parameters and models. It is confirmed that the better transformation is obtained, depends on type of data distributions. In other hands, the parameter conditions term give significant influence either.

Augmentation and impulsive behaviors in restless legs syndrome: Coexistence or association?

PubMed

Heim, Beatrice; Djamshidian, Atbin; Heidbreder, Anna; Stefani, Ambra; Zamarian, Laura; Pertl, Marie-Theres; Brandauer, Elisabeth; Delazer, Margarete; Seppi, Klaus; Poewe, Werner; Högl, Birgit

2016-07-05

To assess the frequency of impulse control disorders (ICDs) in patients with restless legs syndrome (RLS) with and without augmentation under dopaminergic therapy in a case-control study. Augmentation and ICDs are both serious complications of dopaminergic treatment of RLS but little is known about possible associations between these drug-induced disorders. In total, 58 patients with idiopathic RLS diagnosed according to the International Restless Legs Syndrome Study Group criteria were recruited. Of these, 35 patients had augmentation. The frequency of ICD symptoms was assessed using semi-structural interviews. Demographic variables did not differ between patients with RLS with and without augmentation but those with augmentation took higher dopaminergic medication than patients without augmentation. Twenty-three patients with RLS (39.7%) had ICD symptoms, with 12 patients (20.7%) having definitive ICDs. Patients with augmentation had an increased risk of expressing ICD symptoms (p = 0.007, odds ratio 5.64, 95% confidence interval 1.59-20.02). Patients with RLS with augmentation have an almost 6-fold increased risk of exhibiting ICD symptoms. This implies that augmentation and ICDs are related and may share a common pathophysiology. Moreover, our results have clinical implications, suggesting that patients with RLS with augmentation should be screened for ICD symptoms. © 2016 American Academy of Neurology.

14 CFR 91.1061 - Augmented flight crews.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Augmented flight crews. 91.1061 Section 91...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1061 Augmented flight crews. (a) No program manager may assign any flight...

14 CFR 91.1061 - Augmented flight crews.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Augmented flight crews. 91.1061 Section 91...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Fractional Ownership Operations Program Management § 91.1061 Augmented flight crews. (a) No program manager may assign any flight...

Embedding Augmentative Communication within Early Childhood Classrooms.

ERIC Educational Resources Information Center

DiCarlo, Cynthia; Banajee, Meher; Stricklin, Sarintha Buras

2000-01-01

This article first describes various augmentative communication systems including sign language, picture symbols, and voice output communication devices. It then explains ways to embed augmentative communication within four types of early childhood classroom activities: (1) special or planned activities, (2) meal time, (3) circle time, and (4)…

[Display technologies for augmented reality in medical applications].

PubMed

Eck, Ulrich; Winkler, Alexander

2018-04-01

One of the main challenges for modern surgery is the effective use of the many available imaging modalities and diagnostic methods. Augmented reality systems can be used in the future to blend patient and planning information into the view of surgeons, which can improve the efficiency and safety of interventions. In this article we present five visualization methods to integrate augmented reality displays into medical procedures and the advantages and disadvantages are explained. Based on an extensive literature review the various existing approaches for integration of augmented reality displays into medical procedures are divided into five categories and the most important research results for each approach are presented. A large number of mixed and augmented reality solutions for medical interventions have been developed as research prototypes; however, only very few systems have been tested on patients. In order to integrate mixed and augmented reality displays into medical practice, highly specialized solutions need to be developed. Such systems must comply with the requirements with respect to accuracy, fidelity, ergonomics and seamless integration into the surgical workflow.

Different evolution dynamics of vector solitons depending on their polarization states

NASA Astrophysics Data System (ADS)

Chen, Wei-Cheng; Chen, Guo-Jie

2014-03-01

There are three types of temporal evolution dynamics of vector solitons observed in a ring fiber laser with a semiconductor saturable absorption mirror (SESAM) as a mode-locker. It is found that the polarization property of vector solitons is an important factor for achieving different evolution dynamics. The vector soliton with a uniform polarization state across the whole pulse profile and zero polarization extinction ratio operates at a fundamental repetition rate with a single pulse profile. The elliptically polarized vector soliton with a larger polarization extinction ratio exhibits a harmonic pulse train. The soliton bunching with multi-peak structures exists between the above two states and shows elliptical polarization with a small polarization extinction ratio.

Augmented Reality in Architecture: Rebuilding Archeological Heritage

NASA Astrophysics Data System (ADS)

de la Fuente Prieto, J.; Castaño Perea, E.; Labrador Arroyo, F.

2017-02-01

With the development in recent years of augmented reality and the appearance of new mobile terminals and storage bases on-line, we find the possibility of using a powerful tool for transmitting architecture. This paper analyzes the relationship between Augmented Reality and Architecture. Firstly, connects the theoretical framework of both disciplines through the Representation concept. Secondly, describes the milestones and possibilities of Augmented Reality in the particular field of archaeological reconstruction. And lastly, once recognized the technology developed, we face the same analysis from a critical point of view, assessing their suitability to the discipline that concerns us is the architecture and within archeology.

Normative Data for Interpreting the BREAST-Q: Augmentation

PubMed Central

Mundy, Lily R.; Homa, Karen; Klassen, Anne F.; Pusic, Andrea L.; Kerrigan, Carolyn L.

2016-01-01

Background The BREAST-Q is a rigorously developed, well-validated, patient-reported outcome (PRO) instrument with a module designed for evaluating breast augmentation outcomes. However, there are no published normative BREAST-Q scores, limiting interpretation. Methods Normative data were generated for the BREAST-Q Augmentation Module via the Army of Women (AOW), an online community of women (with and without breast cancer) engaged in breast-cancer related research. Members were recruited via email, with women 18 years or older without a history of breast cancer or breast surgery invited to participate. Descriptive statistics and a linear multivariate regression were performed. A separate analysis compared normative scores to findings from previously published BREAST-Q augmentation studies. Results The preoperative BREAST-Q Augmentation Module was completed by 1,211 women. Mean age was 54 ±24 years, mean body mass index (BMI) was 27 ±6, and 39% (n=467) had a bra cup size ≥D. Mean scores were Satisfaction with Breasts (54 ±19), Psychosocial Well-being (66 ±20), Sexual Well-being (49 ±20), and Physical Well-being (86 ±15). Women with a BMI of 30 or greater and bra cup size D or greater had lower scores. In comparison to AOW scores, published BREAST-Q augmentation scores were lower before and higher after surgery for all scales except Physical Well-being. Conclusions The AOW normative data represent breast-related satisfaction and well-being in woman not actively seeking breast augmentation. This data may be used as normative comparison values for those seeking and undergoing surgery as we did, demonstrating the value of breast augmentation in this patient population. PMID:28350657

Fluid Lensing based Machine Learning for Augmenting Earth Science Coral Datasets

NASA Astrophysics Data System (ADS)

Li, A.; Instrella, R.; Chirayath, V.

2016-12-01

Recently, there has been increased interest in monitoring the effects of climate change upon the world's marine ecosystems, particularly coral reefs. These delicate ecosystems are especially threatened due to their sensitivity to ocean warming and acidification, leading to unprecedented levels of coral bleaching and die-off in recent years. However, current global aquatic remote sensing datasets are unable to quantify changes in marine ecosystems at spatial and temporal scales relevant to their growth. In this project, we employ various supervised and unsupervised machine learning algorithms to augment existing datasets from NASA's Earth Observing System (EOS), using high resolution airborne imagery. This method utilizes NASA's ongoing airborne campaigns as well as its spaceborne assets to collect remote sensing data over these afflicted regions, and employs Fluid Lensing algorithms to resolve optical distortions caused by the fluid surface, producing cm-scale resolution imagery of these diverse ecosystems from airborne platforms. Support Vector Machines (SVMs) and K-mean clustering methods were applied to satellite imagery at 0.5m resolution, producing segmented maps classifying coral based on percent cover and morphology. Compared to a previous study using multidimensional maximum a posteriori (MAP) estimation to separate these features in high resolution airborne datasets, SVMs are able to achieve above 75% accuracy when augmented with existing MAP estimates, while unsupervised methods such as K-means achieve roughly 68% accuracy, verified by manually segmented reference data provided by a marine biologist. This effort thus has broad applications for coastal remote sensing, by helping marine biologists quantify behavioral trends spanning large areas and over longer timescales, and to assess the health of coral reefs worldwide.

Augmented Cognitive Behavioral Therapy for Poststroke Depressive Symptoms: A Randomized Controlled Trial.

PubMed

Kootker, Joyce A; Rasquin, Sascha M C; Lem, Frederik C; van Heugten, Caroline M; Fasotti, Luciano; Geurts, Alexander C H

2017-04-01

To evaluate the effectiveness of individually tailored cognitive behavioral therapy (CBT) for reducing depressive symptoms with or without anxiety poststroke. Multicenter, assessor-blinded, randomized controlled trial. Ambulatory rehabilitation setting. Patients who had a Hospital Anxiety and Depression Scale-depression subscale (HADS-D) score >7 at least 3 months poststroke (N=61). Participants were randomly allocated to either augmented CBT or computerized cognitive training (CCT). The CBT intervention was based on the principles of recognizing, registering, and altering negative thoughts and cognitions. CBT was augmented with goal-directed real-life activity training given by an occupational or movement therapist. HADS-D was the primary outcome, and measures of participation and quality of life were secondary outcomes. Outcome measurements were performed at baseline, immediately posttreatment, and at 4- and 8-month follow-up. Analysis was performed with linear mixed models using group (CBT vs CCT) as the between-subjects factor and time (4 assessments) as the within-subjects factor. Mixed model analyses showed a significant and persistent time effect for HADS-D (mean difference, -4.6; 95% confidence interval, -5.7 to -3.6; P<.001) and for participation and quality of life in both groups. There was no significant group × time effect for any of the outcome measures. Our augmented CBT intervention was not superior to CCT for the treatment of mood disorders after stroke. Future studies should determine whether both interventions are better than natural history. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Pulmonary Embolism from Cement Augmentation of the Vertebral Body.

PubMed

Ignacio, Jose Manuel Fernando; Ignacio, Katrina Hannah Dizon

2018-04-01

Pulmonary cement embolism (PCE) can follow cement augmentation procedures for spine fractures due to osteoporosis, traumatic injuries, and painful metastatic lesions. PCE is underreported and it is likely that many cases remain undiagnosed. Risk factors for PCE have been identified, which can help alert clinicians to patients likely to develop the condition, and there are recommended techniques to reduce its incidence. Most patients with PCE are asymptomatic or only develop transient symptoms, although a few may exhibit florid cardiorespiratory manifestations which can ultimately be fatal. Diagnosis is mainly by radiographic means, commonly using simple radiographs and computed tomography scans of the chest with ancillary tests that assess the patient's cardiorespiratory condition. Management depends on the location and size of the emboli as well as the patient's symptomatology. The aim of this review is to raise awareness of the not uncommon complications of PCE following vertebral cement augmentation and the possibility of serious sequelae. Recommendations for the diagnosis and management of PCE are presented, based on the most recent literature.

Facial skeletal augmentation using hydroxyapatite cement.

PubMed

Shindo, M L; Costantino, P D; Friedman, C D; Chow, L C

1993-02-01

This study investigates the use of a new calcium phosphate cement, which sets to solid, microporous hydroxyapatite, for facial bone augmentation. In six dogs, the supraorbital ridges were augmented bilaterally with this hydroxyapatite cement. On one side, the hydroxyapatite cement was placed directly onto the bone within a subperiosteal pocket. On the opposite side, the cement was contained within a collagen membrane tubule and then inserted into a subperiosteal pocket. The use of collagen tubules facilitated easy, precise placement of the cement. All implants maintained their original augmented height throughout the duration of the study. They were well tolerated without extrusion or migration, and there was no significant sustained inflammatory response. Histologic studies, performed at 3, 6, and 9 months revealed that when the cement was placed directly onto bone, progressive replacement of the implant by bone (osseointegration of the hydroxyapatite with the underlying bone) without a loss of volume was observed. In contrast, when the cement-collagen tubule combination was inserted, primarily a fibrous union was noted. Despite such fibrous union, the hydroxyapatite-collagen implant solidly bonded to the underlying bone, and no implant resorption was observed. Hydroxyapatite cement can be used successfully for the experimental augmentation of the craniofacial skeleton and may be applicable for such uses in humans.

Bladder stones after bladder augmentation are not what they seem.

PubMed

Szymanski, Konrad M; Misseri, Rosalia; Whittam, Benjamin; Lingeman, James E; Amstutz, Sable; Ring, Joshua D; Kaefer, Martin; Rink, Richard C; Cain, Mark P

2016-04-01

Bladder and renal calculi after bladder augmentation are thought to be primarily infectious, yet few studies have reported stone composition. The primary aim was to assess bladder stone composition after augmentation, and renal stone composition in those with subsequent nephrolithiasis. The exploratory secondary aim was to screen for possible risk factors for developing infectious stones. Patients treated for bladder stones after bladder augmentation at the present institution between 1981 and 2012 were retrospectively reviewed. Data were collected on demographics, surgeries and stone composition. Patients without stone analysis were excluded. Stones containing struvite, carbonate apatite or ammonium acid ureate were classified as infectious. The following variables were analyzed for a possible association with infectious bladder stone composition: gender, history of cloacal exstrophy, ambulatory status, nephrolithiasis, recurrent urea-splitting urinary tract infections, first vs recurrent stones, timing of presentation with a calculus, history of bladder neck procedures, catheterizable channel and vesicoureteral reflux. Fisher's exact test was used for analysis. Of the 107 patients with bladder stones after bladder augmentation, 85 met inclusion criteria. Median age at augmentation was 8.0 years (follow-up 10.8 years). Forty-four patients (51.8%) recurred (14 multiple recurrences, 143 bladder stones). Renal calculi developed in 19 (22.4%) patients with a bladder stone, and 10 (52.6%) recurred (30 renal stones). Overall, 30.8% of bladder stones were non-infectious (Table). Among patients recurring after an infectious bladder stone, 30.4% recurred with a non-infectious one. Among patients recurring after a non-infectious stone, 84.6% recurred with a non-infectious one (P = 0.005). Compared with bladder stones, renal stones were more likely to be non-infectious (60.0%, P = 0.003). Of patients with recurrent renal calculi after an infectious stone, 40.0% recurred with

Asymmetric impact of rainfall on India's food grain production: evidence from quantile autoregressive distributed lag model

NASA Astrophysics Data System (ADS)

Pal, Debdatta; Mitra, Subrata Kumar

2018-01-01

This study used a quantile autoregressive distributed lag (QARDL) model to capture asymmetric impact of rainfall on food production in India. It was found that the coefficient corresponding to the rainfall in the QARDL increased till the 75th quantile and started decreasing thereafter, though it remained in the positive territory. Another interesting finding is that at the 90th quantile and above the coefficients of rainfall though remained positive was not statistically significant and therefore, the benefit of high rainfall on crop production was not conclusive. However, the impact of other determinants, such as fertilizer and pesticide consumption, is quite uniform over the whole range of the distribution of food grain production.

Simulation development and evaluation of an improved longitudinal velocity vector control wheel steering mode and electronic display format

NASA Technical Reports Server (NTRS)

Steinmetz, G. G.

1980-01-01

Using simulation, an improved longitudinal velocity vector control wheel steering mode and an improved electronic display format for an advanced flight system were developed and tested. Guidelines for the development phase were provided by test pilot critique summaries of the previous system. The results include performances from computer generated step column inputs across the full airplane speed and configuration envelope, as well as piloted performance results taken from a reference line tracking task and an approach to landing task conducted under various environmental conditions. The analysis of the results for the reference line tracking and approach to landing tasks indicates clearly detectable improvement in pilot tracking accuracy with a reduction in physical workload. The original objectives of upgrading the longitudinal axis of the velocity vector control wheel steering mode were successfully met when measured against the test pilot critique summaries and the original purpose outlined for this type of augment control mode.

A novel framework to simulating non-stationary, non-linear, non-Normal hydrological time series using Markov Switching Autoregressive Models

NASA Astrophysics Data System (ADS)

Birkel, C.; Paroli, R.; Spezia, L.; Tetzlaff, D.; Soulsby, C.

2012-12-01

In this paper we present a novel model framework using the class of Markov Switching Autoregressive Models (MSARMs) to examine catchments as complex stochastic systems that exhibit non-stationary, non-linear and non-Normal rainfall-runoff and solute dynamics. Hereby, MSARMs are pairs of stochastic processes, one observed and one unobserved, or hidden. We model the unobserved process as a finite state Markov chain and assume that the observed process, given the hidden Markov chain, is conditionally autoregressive, which means that the current observation depends on its recent past (system memory). The model is fully embedded in a Bayesian analysis based on Markov Chain Monte Carlo (MCMC) algorithms for model selection and uncertainty assessment. Hereby, the autoregressive order and the dimension of the hidden Markov chain state-space are essentially self-selected. The hidden states of the Markov chain represent unobserved levels of variability in the observed process that may result from complex interactions of hydroclimatic variability on the one hand and catchment characteristics affecting water and solute storage on the other. To deal with non-stationarity, additional meteorological and hydrological time series along with a periodic component can be included in the MSARMs as covariates. This extension allows identification of potential underlying drivers of temporal rainfall-runoff and solute dynamics. We applied the MSAR model framework to streamflow and conservative tracer (deuterium and oxygen-18) time series from an intensively monitored 2.3 km2 experimental catchment in eastern Scotland. Statistical time series analysis, in the form of MSARMs, suggested that the streamflow and isotope tracer time series are not controlled by simple linear rules. MSARMs showed that the dependence of current observations on past inputs observed by transport models often in form of the long-tailing of travel time and residence time distributions can be efficiently explained by

Nonlinear Autoregressive Exogenous modeling of a large anaerobic digester producing biogas from cattle waste.

PubMed

Dhussa, Anil K; Sambi, Surinder S; Kumar, Shashi; Kumar, Sandeep; Kumar, Surendra

2014-10-01

In waste-to-energy plants, there is every likelihood of variations in the quantity and characteristics of the feed. Although intermediate storage tanks are used, but many times these are of inadequate capacity to dampen the variations. In such situations an anaerobic digester treating waste slurry operates under dynamic conditions. In this work a special type of dynamic Artificial Neural Network model, called Nonlinear Autoregressive Exogenous model, is used to model the dynamics of anaerobic digesters by using about one year data collected on the operating digesters. The developed model consists of two hidden layers each having 10 neurons, and uses 18days delay. There are five neurons in input layer and one neuron in output layer for a day. Model predictions of biogas production rate are close to plant performance within ±8% deviation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Vector-borne Infections

PubMed Central

Ben Beard, C.

2011-01-01

Infections with vector-borne pathogens are a major source of emerging diseases. The ability of vectors to bridge spatial and ecologic gaps between animals and humans increases opportunities for emergence. Small adaptations of a pathogen to a vector can have profound effects on the rate of transmission to humans. PMID:21529382

SmartG: Spontaneous Malaysian Augmented Reality Tourist Guide

NASA Astrophysics Data System (ADS)

Kasinathan, Vinothini; Mustapha, Aida; Subramaniam, Tanabalan

2016-11-01

In effort to attract higher tourist expenditure along with higher tourist arrivals, this paper proposes a travel application called the SmartG, acronym for Spontaneous Malaysian Augmented Reality Tourist Guide, which operates by making recommendations to user based on the travel objective and individual budget constraints. The applications relies on augmented reality technology, whereby a three dimensional model is presented to the user based on input from real world environment. User testing returned a favorable feedback on the concept of using augmented reality in promoting Malaysian tourism.

Applying Augmented Reality in practical classes for engineering students

NASA Astrophysics Data System (ADS)

Bazarov, S. E.; Kholodilin, I. Yu; Nesterov, A. S.; Sokhina, A. V.

2017-10-01

In this article the Augmented Reality application for teaching engineering students of electrical and technological specialties is introduced. In order to increase the motivation for learning and the independence of students, new practical guidelines on Augmented Reality were developed in the application to practical classes. During the application development, the authors used software such as Unity 3D and Vuforia. The Augmented Reality content consists of 3D-models, images and animations, which are superimposed on real objects, helping students to study specific tasks. A user who has a smartphone, a tablet PC, or Augmented Reality glasses can visualize on-screen virtual objects added to a real environment. Having analyzed the current situation in higher education: the learner’s interest in studying, their satisfaction with the educational process, and the impact of the Augmented Reality application on students, a questionnaire was developed and offered to students; the study involved 24 learners.

Bladder calculi in the augmented bladder: a follow-up study of 160 children and adolescents.

PubMed

Kisku, S; Sen, S; Karl, S; Mathai, J; Thomas, R J; Barla, R

2015-04-01

Bladder augmentation (BA) has been used for various congenital and acquired conditions to create a low pressure, continent catheterizable reservoir. The prevalence of calculi within the BA have been reported to be from 3 to 52.5%. The present study reports the prevalence and risk factors of bladder calculi in patients with BA. A retrospective review of 160 patients was performed from January 1997 through December 2012. The various risk factors for the formation of bladder calculi such as the nature of the anatomical defect, presence of preoperative urinary calculi, type of bowel augmentation, addition of a mitrofanoff and/or bladder neck procedure, prevalence of post-operative urinary tract infections (UTIs), need for mitrofanoff revision due to stenosis/difficulty catheterization, postoperative significant hydronephrosis and bladder calculi were recorded for analysis. The children underwent open removal or endoscopic cystolithotripsy. One hundred and eight males and 52 females (average age 6.3 years) were followed up for a median of 70.5 months. All patients performed daily bladder irrigation with tap or drinking water. Post-operative bladder calculi were noted in 14 (8.8%) of 160 patients following BA. Median time to stone formation was 37.5 months (11-120 months). Recurrent febrile UTIs were noted in 16 of the 160 patients following BA. The various risk factors and their outcomes are summarized in table. Eight patients underwent open cystolithotomy and four patients were treated by cystolithotripsy. Post-operative recurrent bladder calculi were noted in 2 patients. Multivariate analysis revealed that exstrophy/epispadias (OR 17.2) and recurrent UTI (OR 55.4) were independent risk factors for developing postoperative calculi in bladder augmentations. All other risk factors did not achieve statistical significance. There seemed to be no difference in the prevalence of calculi in the ileal or colonic augmentations. Mucus secreted by the bowel segment blocks

Magnetic concentration of a retroviral vector using magnetite cationic liposomes.

PubMed

Ito, Akira; Takahashi, Tetsuya; Kameyama, Yujiro; Kawabe, Yoshinori; Kamihira, Masamichi

2009-03-01

For tissue engineering purposes, retroviral vectors represent an efficient method of delivering exogenous genes such as growth factors to injured tissues because gene-transduced cells can produce stable and constant levels of the gene product. However, retroviral vector technology suffers from low yields. In the present study, we used magnetite nanoparticles and magnetic force to concentrate the retroviral vectors to enhance the transduction efficiency and to enable their magnetic manipulation. Magnetite nanoparticles modified with cationic liposomes were added to a solution containing a retroviral vector pseudotyped with vesicular stomatitis virus glycoprotein. The magnetic particles that captured the viral vectors were collected using a magnetic force and seeded into mouse neuroblastoma Neuro2a cells. The viral titer was up to 55 times greater (up to 3 x 10(8) infectious units/mL). Additionally, the magnetically labeled retroviral vectors can be directed to the desired regions for infection by applying magnetic fields, and micro-patterns of gene-transduced cell regions could be created on a cellular monolayer using micro-patterned magnetic concentrators. These results suggest that this technique provides a promising approach to capturing and concentrating viral vectors, thus achieving high transduction efficiency and the ability to deliver genes to a specific injured site by applying a magnetic field.

Virtually-augmented interfaces for tactical aircraft.

PubMed

Haas, M W

1995-05-01

The term Fusion Interface is defined as a class of interface which integrally incorporates both virtual and non-virtual concepts and devices across the visual, auditory and haptic sensory modalities. A fusion interface is a multi-sensory virtually-augmented synthetic environment. A new facility has been developed within the Human Engineering Division of the Armstrong Laboratory dedicated to exploratory development of fusion-interface concepts. One of the virtual concepts to be investigated in the Fusion Interfaces for Tactical Environments facility (FITE) is the application of EEG and other physiological measures for virtual control of functions within the flight environment. FITE is a specialized flight simulator which allows efficient concept development through the use of rapid prototyping followed by direct experience of new fusion concepts. The FITE facility also supports evaluation of fusion concepts by operational fighter pilots in a high fidelity simulated air combat environment. The facility was utilized by a multi-disciplinary team composed of operational pilots, human-factors engineers, electronics engineers, computer scientists, and experimental psychologists to prototype and evaluate the first multi-sensory, virtually-augmented cockpit. The cockpit employed LCD-based head-down displays, a helmet-mounted display, three-dimensionally localized audio displays, and a haptic display. This paper will endeavor to describe the FITE facility architecture, some of the characteristics of the FITE virtual display and control devices, and the potential application of EEG and other physiological measures within the FITE facility.

Augmented reality for anatomical education.

PubMed

Thomas, Rhys Gethin; John, Nigel William; Delieu, John Michael

2010-03-01

The use of Virtual Environments has been widely reported as a method of teaching anatomy. Generally such environments only convey the shape of the anatomy to the student. We present the Bangor Augmented Reality Education Tool for Anatomy (BARETA), a system that combines Augmented Reality (AR) technology with models produced using Rapid Prototyping (RP) technology, to provide the student with stimulation for touch as well as sight. The principal aims of this work were to provide an interface more intuitive than a mouse and keyboard, and to evaluate such a system as a viable supplement to traditional cadaver based education.

Anorganic bovine-derived hydroxyapatite vs β-tricalcium phosphate in sinus augmentation: a comparative histomorphometric study.

PubMed

Kurkcu, Mehmet; Benlidayi, M Emre; Cam, Burcu; Sertdemir, Yasar

2012-09-01

The choice of augmentation material is a crucial factor in sinus augmentation surgery. Bovine-derived hydroxyapatite (BHA) and beta-tricalcium phosphate (β-TCP) have been used successfully in sinus augmentation procedures. Choosing one of these materials for sinus augmentation is still controversial. The aim of this clinical study was to compare the biological performance of the new BHA graft material and the well-known synthetic β-TCP material in the sinus augmentation procedure. The study consisted of 23 patients (12 male and 11 female) who were either edentulous or partially edentulous in the posterior maxilla and required implant placement. A total of 23 two-step sinus-grafting procedures were performed. BHA was used in 13 patients, and β-TCP was used in 10 patients. After an average of 6.5 months of healing, bone biopsies were taken from the grafted areas. Undecalcified sections were prepared for histomorphometric analysis. The mean new bone formation was 30.13% ± 3.45% in the BHA group and 21.09% ± 2.86% in the β-TCP group (P = .001). The mean percentage of residual graft particle area was 31.88% ± 6.05% and 34.05% ± 3.01% for the BHA group and β-TCP group, respectively (P = .047). The mean percentage of soft-tissue area was 37.99% ± 5.92% in the BHA group and 44.86% ± 4.28% in the β-TCP group (P = .011). Both graft materials demonstrated successful biocompatibility and osteoconductivity in the sinus augmentation procedure. However, BHA appears to be more efficient in osteoconduction when compared with β-TCP.

Anorganic bovine-derived hydroxyapatite versus β-tricalcium phosphate in sinus augmentation. A comparative histomorphometric study.

PubMed

Kurkcu, Mehmet; Benlidayi, Mehmet Emre; Cam, Burcu; Sertdemir, Yasar

2012-05-22

Abstract AbstractIntroduction: The choice of augmentation material is a crucial factor in sinus augmentation surgery. Bovine-derived hydroxyapatite (BHA) and beta-tricalcium phosphate (β-TCP) have been used successfully in sinus augmentation procedures. Choosing one of these materials for sinus augmentation is still controversial. The aim of this clinical study was to compare the biological performance of the new BHA graft material and the well known synthetic β-TCP material in sinus augmentation procedure.Material and Methods: The study consisted of 23 patients (12 male and 11 female) who were either edentulous or partially edentulous in the posterior maxilla and required implant placement. A total of 23 two-step sinus grafting procedures were performed. BHA was used in 13 patients and β-TCP was used in 10 patients. After average of 6.5 months of healing bone biopsies were taken from the grafted areas. Undecalcified sections were prepared for histomorphometric analysis. Results: The mean new bone formation was 30.13±3.45% in BHA group and 21.09±2.86% in β-TCP group (p=0.001). The mean percentage of residual graft particle area was 31.88±6.05% and 34.05±3.01% for BHA group and β-TCP group, respectively (p=0.047). The mean percentage of soft tissue area was 37.99±5.92% in BHA group and 44.86±4.28% in β-TCP group (p=0.011).Conclusion: Both graft materials demonstrated successful biocompatibility and osteoconductivity in sinus augmentation procedure. However, BHA appears to be more efficient in osteoconduction when compared to β-TCP.

Four-point injection technique for lip augmentation.

PubMed

Sahan, Ali; Funda, Tamer

2018-06-01

Lip augmentation procedures with hyaluronic acid dermal fillers have become increasingly popular worldwide because full lips are often considered beautiful and youthful. The goal of a lip augmentation procedure is to create smooth lips with adequate volume and a natural appearance. Various techniques for lip augmentation have been utilized and described. In the four-point injection technique, the lips were divided equally into right side and left side. Four entry points were made above the vermilion border for the upper lip and below the vermilion border for the lower lip. The filler was administered with a fanning technique through each entry point. Between January 2017 and November 2017, 50 female patients underwent a nonsurgical lip augmentation procedure with injectable fillers using this technique. Forty-five patients (90%) reported that they were satisfied or extremely satisfied with their lip enhancement procedure. No serious complications were observed. The advantages of this technique are reducing the risk of complications like erythema, edema, and vascular injuries, and providing easy access to injection sites.

Cosmetic tourism for breast augmentation: a systematic review.

PubMed

Brightman, Louise; Ng, Sze; Ahern, Susannah; Cooter, Rodney; Hopper, Ingrid

2017-12-03

The medical tourism industry, and in particular cosmetic tourism for breast augmentation, is becoming an increasingly popular global phenomenon. The objective of this study is to determine the extent of medical literature and the patient risk profiles associated with cosmetic tourism for breast augmentation both locally and abroad. OVID MEDLINE, OVID Embase, Cochrane Central and Proquest electronic databases. The search was conducted through to April 2017. Studies pertaining entirely or partly to cosmetic tourism for breast augmentation were considered for inclusion. Exclusion criteria included non-English articles, studies relating to non-cosmetic or non-implant breast augmentation, and studies that did not separately report on findings associated with breast augmentation abroad. We identified 17 observational studies. Common destinations included Europe, South America and South East Asia. Infectious complications were common. Wound dehiscence and aesthetic dissatisfaction also featured. Catastrophic outcomes such as sepsis, intubation and ventilation, radical bilateral mastectomy, irreversible hypoxic brain injury and death were also reported. There were expectations that home country health systems would treat complications and provide non-medically indicated revision procedures. The burden on home country health systems was evident from a public health perspective. Determining the extent of cosmetic tourism for breast augmentation, including outcomes and complications, will help to inform Australian patients who this seek procedure abroad. Furthermore, it will aid in better understanding the health system implications and may help to guide future research and public health interventions both locally and internationally. © 2017 Royal Australasian College of Surgeons.

Augmenting ejector endwall effects. [V/STOL aircraft

NASA Technical Reports Server (NTRS)

Porter, J. L.; Squyers, R. A.

1979-01-01

Rectangular inlet ejectors which had multiple hypermixing nozzles for their primary jets were investigated for the effects of endwall blowing on thrust augmentation performance. The ejector configurations tested had both straight wall and active boundary layer control type diffusers. Endwall flows were energized and controlled by simple blowing jets suitably located in the ejector. Both the endwall and boundary layer control diffuser blowing rates were varied to determine optimum performance. High area ratio diffusers with insufficient endwall blowing showed endwall separation and rapid degradation of thrust performance. Optimized values of diffuser boundary layer control and endwall nozzle blowing rates in an ejector augmenter were shown to achieve high levels of augmentation performance for maximum compactness.

Probing GATA factor function in mouse Leydig cells via testicular injection of adenoviral vectors.

PubMed

Penny, Gervette M; Cochran, Rebecca B; Pihlajoki, Marjut; Kyrönlahti, Antti; Schrade, Anja; Häkkinen, Merja; Toppari, Jorma; Heikinheimo, Markku; Wilson, David B

2017-10-01

Testicular Leydig cells produce androgens essential for proper male reproductive development and fertility. Here, we describe a new Leydig cell ablation model based on Cre/Lox recombination of mouse Gata4 and Gata6 , two genes implicated in the transcriptional regulation of steroidogenesis. The testicular interstitium of adult Gata4 flox/flox ; Gata6 flox/flox mice was injected with adenoviral vectors encoding Cre + GFP (Ad-Cre-IRES-GFP) or GFP alone (Ad-GFP). The vectors efficiently and selectively transduced Leydig cells, as evidenced by GFP reporter expression. Three days after Ad-Cre-IRES-GFP injection, expression of androgen biosynthetic genes ( Hsd3b1 , Cyp17a1 and Hsd17b3 ) was reduced, whereas expression of another Leydig cell marker, Insl3 , was unchanged. Six days after Ad-Cre-IRES-GFP treatment, the testicular interstitium was devoid of Leydig cells, and there was a concomitant loss of all Leydig cell markers. Chromatin condensation, nuclear fragmentation, mitochondrial swelling, and other ultrastructural changes were evident in the degenerating Leydig cells. Liquid chromatography-tandem mass spectrometry demonstrated reduced levels of androstenedione and testosterone in testes from mice injected with Ad-Cre-IRES-GFP. Late effects of treatment included testicular atrophy, infertility and the accumulation of lymphoid cells in the testicular interstitium. We conclude that adenoviral-mediated gene delivery is an expeditious way to probe Leydig cell function in vivo Our findings reinforce the notion that GATA factors are key regulators of steroidogenesis and testicular somatic cell survival.Free Finnish abstract: A Finnish translation of this abstract is freely available at http://www.reproduction-online.org/content/154/4/455/suppl/DC2. © 2017 Society for Reproduction and Fertility.

A comparison of in situ measurements of vector-E and - vector-V x vector-B from Dynamics Explorer 2

NASA Technical Reports Server (NTRS)

Hanson, W. B.; Coley, W. R.; Heelis, R. A.; Maynard, N. C.; Aggson, T. L.

1993-01-01

Dynamics Explorer-2 provided the first opportunity to make a direct comparison of in situ measurements of the high-latitude convection electric field by two distinctly different techniques. The vector electric field instrument (VEFI) used antennae to measure the intrinsic electric fields and the ion drift meter (IDM) and retarding potential analyzer (RPA) measured the ion drift velocity vector, from which the convection electric field can be deduced. The data from three orbits having large electric fields at high latitude are presented, one at high, one at medium, and one at low altitudes. The general agreement between the two measurements of electric field is very good, with typical differences at high latitudes of the order of a few millivolts per meter, but there are some regions where the particle fluxes are extremely large (e.g., the cusp) and the disagreement is worse, probably because of IDM difficulties. The auroral zone potential patterns derived from the two devices are in excellent agreement for two of the cases, but not in the third, where bad attitude data may be the problem. At low latitudes there are persistent differences in the measurements of a few millivolts per meter, though these differences are quite constant from orbit to orbit. This problem seems to arise from some shortcoming in the VEFI measurments. Overall, however, these measurements confirm the concept of `frozen-in' plasma that drifts with velocity vector-E x vector-B/B(exp 2) within the measurement errors of the two techniques.

Space-based augmentation for global navigation satellite systems.

PubMed

Grewal, Mohinder S

2012-03-01

This paper describes space-based augmentation for global navigation satellite systems (GNSS). Space-based augmentations increase the accuracy and integrity of the GNSS, thereby enhancing users' safety. The corrections for ephemeris, ionospheric delay, and clocks are calculated from reference station measurements of GNSS data in wide-area master stations and broadcast via geostationary earth orbit (GEO) satellites. This paper discusses the clock models, satellite orbit determination, ionospheric delay estimation, multipath mitigation, and GEO uplink subsystem (GUS) as used in the Wide Area Augmentation System developed by the FAA.

Biological augmentation and tissue engineering approaches in meniscus surgery.

PubMed

Moran, Cathal J; Busilacchi, Alberto; Lee, Cassandra A; Athanasiou, Kyriacos A; Verdonk, Peter C

2015-05-01

The purpose of this review was to evaluate the role of biological augmentation and tissue engineering strategies in meniscus surgery. Although clinical (human), preclinical (animal), and in vitro tissue engineering studies are included here, we have placed additional focus on addressing preclinical and clinical studies reported during the 5-year period used in this review in a systematic fashion while also providing a summary review of some important in vitro tissue engineering findings in the field over the past decade. A search was performed on PubMed for original works published from 2009 to March 31, 2014 using the term "meniscus" with all the following terms: "scaffolds," "constructs," "cells," "growth factors," "implant," "tissue engineering," and "regenerative medicine." Inclusion criteria were the following: English-language articles and original clinical, preclinical (in vivo), and in vitro studies of tissue engineering and regenerative medicine application in knee meniscus lesions published from 2009 to March 31, 2014. Three clinical studies and 18 preclinical studies were identified along with 68 tissue engineering in vitro studies. These reports show the increasing promise of biological augmentation and tissue engineering strategies in meniscus surgery. The role of stem cell and growth factor therapy appears to be particularly useful. A review of in vitro tissue engineering studies found a large number of scaffold types to be of promise for meniscus replacement. Limitations include a relatively low number of clinical or preclinical in vivo studies, in addition to the fact there is as yet no report in the literature of a tissue-engineered meniscus construct used clinically. Neither does the literature provide clarity on the optimal meniscus scaffold type or biological augmentation with which meniscus repair or replacement would be best addressed in the future. There is increasing focus on the role of mechanobiology and biomechanical and

Remote Sensing Proxies for Vector-borne Disease Risk Assessment (Invited)

NASA Astrophysics Data System (ADS)

Anyamba, A.

2010-12-01

The spread of re-emerging vector-borne diseases such Rift Valley fever (RVF) and Chikungunya (CHIK) is a major issue of global public health concern. This combined with a variable climate regime has opened an avenue for satellite remote sensing to contribute towards a comprehensive understanding of some of the drivers influencing such vector-borne disease outbreaks. Satellite derived measurements such as vegetation indices, rainfall estimates, and land-surface temperature; can be used to infer the complex mosaic of factors that influence ecology and habitat suitability, emergence and population dynamics of disease vectors. However, there are still some gaps in application including appropriate temporal resolution of remote sensing measurements, the complexity of the virus-vector-disease-ecology system and human components that contribute to disease risk that need to be addressed. Geographic Distribution of Recent Rift Valley fever oubreaks

Rotations with Rodrigues' Vector

ERIC Educational Resources Information Center

Pina, E.

2011-01-01

The rotational dynamics was studied from the point of view of Rodrigues' vector. This vector is defined here by its connection with other forms of parametrization of the rotation matrix. The rotation matrix was expressed in terms of this vector. The angular velocity was computed using the components of Rodrigues' vector as coordinates. It appears…

Augmented Reality 2.0

NASA Astrophysics Data System (ADS)

Schmalstieg, Dieter; Langlotz, Tobias; Billinghurst, Mark

Augmented Reality (AR) was first demonstrated in the 1960s, but only recently have technologies emerged that can be used to easily deploy AR applications to many users. Camera-equipped cell phones with significant processing power and graphics abilities provide an inexpensive and versatile platform for AR applications, while the social networking technology of Web 2.0 provides a large-scale infrastructure for collaboratively producing and distributing geo-referenced AR content. This combination of widely used mobile hardware and Web 2.0 software allows the development of a new type of AR platform that can be used on a global scale. In this paper we describe the Augmented Reality 2.0 concept and present existing work on mobile AR and web technologies that could be used to create AR 2.0 applications.

Orthogonal vector algorithm to obtain the solar vector using the single-scattering Rayleigh model.

PubMed

Wang, Yinlong; Chu, Jinkui; Zhang, Ran; Shi, Chao

2018-02-01

Information obtained from a polarization pattern in the sky provides many animals like insects and birds with vital long-distance navigation cues. The solar vector can be derived from the polarization pattern using the single-scattering Rayleigh model. In this paper, an orthogonal vector algorithm, which utilizes the redundancy of the single-scattering Rayleigh model, is proposed. We use the intersection angles between the polarization vectors as the main criteria in our algorithm. The assumption that all polarization vectors can be considered coplanar is used to simplify the three-dimensional (3D) problem with respect to the polarization vectors in our simulation. The surface-normal vector of the plane, which is determined by the polarization vectors after translation, represents the solar vector. Unfortunately, the two-directionality of the polarization vectors makes the resulting solar vector ambiguous. One important result of this study is, however, that this apparent disadvantage has no effect on the complexity of the algorithm. Furthermore, two other universal least-squares algorithms were investigated and compared. A device was then constructed, which consists of five polarized-light sensors as well as a 3D attitude sensor. Both the simulation and experimental data indicate that the orthogonal vector algorithms, if used with a suitable threshold, perform equally well or better than the other two algorithms. Our experimental data reveal that if the intersection angles between the polarization vectors are close to 90°, the solar-vector angle deviations are small. The data also support the assumption of coplanarity. During the 51 min experiment, the mean of the measured solar-vector angle deviations was about 0.242°, as predicted by our theoretical model.

Current procedures of the integrated urban vector-mosquito control as an example in Cotonou (Benin, West Africa) and Wrocław area (Poland).

PubMed

Rydzanicz, Katarzyna; Lonc, Elzbieta; Becker, Norbert

2009-01-01

Current strategy of Integrated Vector Management (IVM) comprises the general approach of environmentally friendly control measures. With regard to mosquitoes it includes first of all application of microbial insecticides based on Bacillus thuringiensis israelensis (Bti) and B. sphaericus (Bs) delta-endotoxins as well as the reduction of breeding habitats and natural enemy augmentation. It can be achieved thorough implementation of the interdisciplinary program, i. e., understanding of mosquito vector ecology, the appropriate vector-diseases (e. g., malariometric) measurements and training of local personnel responsible for mosquito abatement activities, as well as community involvement. Biocontrol methods as an alternative to chemical insecticides result from the sustainability development concept, growing awareness of environmental pollution and the development of insecticide-resistant strains of vector-mosquito populations in many parts of the world. Although sustainable trends are usually considered in terms of the monetary and training resources within countries, environmental concerns are actually more limiting factors for the duration of an otherwise successful vector control effort. In order to meet these new needs, increasing efforts have been made in search of and application of natural enemies, such as parasites, bacterial pathogens and predators which may control populations of insect vectors. The biological control agent based on the bacterial toxins Bti and Bs has been used in the Wrocław's University and Municipal Mosquito Control Programs since 1998. In West-Africa biocontrol appears to be an effective and safe tool to combat malaria in addition to bed-nets, residual indoor spraying and appropriate diagnosis and treatment of malaria parasites which are the major tools in the WHO Roll Back Malaria Program. IVM studies carried out 2005-2008 in Cotonou (Benin) as well those in Wrocław Irrigated Fields during the last years include the following major

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Personalized augmented reality for anatomy education.

PubMed

Ma, Meng; Fallavollita, Pascal; Seelbach, Ina; Von Der Heide, Anna Maria; Euler, Ekkehard; Waschke, Jens; Navab, Nassir

2016-05-01

Anatomy education is a challenging but vital element in forming future medical professionals. In this work, a personalized and interactive augmented reality system is developed to facilitate education. This system behaves as a "magic mirror" which allows personalized in-situ visualization of anatomy on the user's body. Real-time volume visualization of a CT dataset creates the illusion that the user can look inside their body. The system comprises a RGB-D sensor as a real-time tracking device to detect the user moving in front of a display. In addition, the magic mirror system shows text information, medical images, and 3D models of organs that the user can interact with. Through the participation of 7 clinicians and 72 students, two user studies were designed to respectively assess the precision and acceptability of the magic mirror system for education. The results of the first study demonstrated that the average precision of the augmented reality overlay on the user body was 0.96 cm, while the results of the second study indicate 86.1% approval for the educational value of the magic mirror, and 91.7% approval for the augmented reality capability of displaying organs in three dimensions. The usefulness of this unique type of personalized augmented reality technology has been demonstrated in this paper. © 2015 Wiley Periodicals, Inc.

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for

Participatory Risk Mapping of Malaria Vector Exposure in Northern South America using Environmental and Population Data

PubMed Central

Fuller, D.O.; Troyo, A.; Alimi, T.O.; Beier, J.C.

2014-01-01

Malaria elimination remains a major public health challenge in many tropical regions, including large areas of northern South America. In this study, we present a new high spatial resolution (90 × 90 m) risk map for Colombia and surrounding areas based on environmental and human population data. The map was created through a participatory multi-criteria decision analysis in which expert opinion was solicited to determine key environmental and population risk factors, different fuzzy functions to standardize risk factor inputs, and variable factor weights to combine risk factors in a geographic information system. The new risk map was compared to a map of malaria cases in which cases were aggregated to the municipio (municipality) level. The relationship between mean municipio risk scores and total cases by muncípio showed a weak correlation. However, the relationship between pixel-level risk scores and vector occurrence points for two dominant vector species, Anopheles albimanus and An. darlingi, was significantly different (p < 0.05) from a random point distribution, as was a pooled point distribution for these two vector species and An. nuneztovari. Thus, we conclude that the new risk map derived based on expert opinion provides an accurate spatial representation of risk of potential vector exposure rather than malaria transmission as shown by the pattern of malaria cases, and therefore it may be used to inform public health authorities as to where vector control measures should be prioritized to limit human-vector contact in future malaria outbreaks. PMID:24976656

Cloning vector

DOEpatents

Guilfoyle, R.A.; Smith, L.M.

1994-12-27

A vector comprising a filamentous phage sequence containing a first copy of filamentous phage gene X and other sequences necessary for the phage to propagate is disclosed. The vector also contains a second copy of filamentous phage gene X downstream from a promoter capable of promoting transcription in a bacterial host. In a preferred form of the present invention, the filamentous phage is M13 and the vector additionally includes a restriction endonuclease site located in such a manner as to substantially inactivate the second gene X when a DNA sequence is inserted into the restriction site. 2 figures.

Cloning vector

DOEpatents

Guilfoyle, Richard A.; Smith, Lloyd M.

1994-01-01

A vector comprising a filamentous phage sequence containing a first copy of filamentous phage gene X and other sequences necessary for the phage to propagate is disclosed. The vector also contains a second copy of filamentous phage gene X downstream from a promoter capable of promoting transcription in a bacterial host. In a preferred form of the present invention, the filamentous phage is M13 and the vector additionally includes a restriction endonuclease site located in such a manner as to substantially inactivate the second gene X when a DNA sequence is inserted into the restriction site.

Augmented reality based real-time subcutaneous vein imaging system

PubMed Central

Ai, Danni; Yang, Jian; Fan, Jingfan; Zhao, Yitian; Song, Xianzheng; Shen, Jianbing; Shao, Ling; Wang, Yongtian

2016-01-01

A novel 3D reconstruction and fast imaging system for subcutaneous veins by augmented reality is presented. The study was performed to reduce the failure rate and time required in intravenous injection by providing augmented vein structures that back-project superimposed veins on the skin surface of the hand. Images of the subcutaneous vein are captured by two industrial cameras with extra reflective near-infrared lights. The veins are then segmented by a multiple-feature clustering method. Vein structures captured by the two cameras are matched and reconstructed based on the epipolar constraint and homographic property. The skin surface is reconstructed by active structured light with spatial encoding values and fusion displayed with the reconstructed vein. The vein and skin surface are both reconstructed in the 3D space. Results show that the structures can be precisely back-projected to the back of the hand for further augmented display and visualization. The overall system performance is evaluated in terms of vein segmentation, accuracy of vein matching, feature points distance error, duration times, accuracy of skin reconstruction, and augmented display. All experiments are validated with sets of real vein data. The imaging and augmented system produces good imaging and augmented reality results with high speed. PMID:27446690

Augmented reality based real-time subcutaneous vein imaging system.

PubMed

Ai, Danni; Yang, Jian; Fan, Jingfan; Zhao, Yitian; Song, Xianzheng; Shen, Jianbing; Shao, Ling; Wang, Yongtian

2016-07-01

A novel 3D reconstruction and fast imaging system for subcutaneous veins by augmented reality is presented. The study was performed to reduce the failure rate and time required in intravenous injection by providing augmented vein structures that back-project superimposed veins on the skin surface of the hand. Images of the subcutaneous vein are captured by two industrial cameras with extra reflective near-infrared lights. The veins are then segmented by a multiple-feature clustering method. Vein structures captured by the two cameras are matched and reconstructed based on the epipolar constraint and homographic property. The skin surface is reconstructed by active structured light with spatial encoding values and fusion displayed with the reconstructed vein. The vein and skin surface are both reconstructed in the 3D space. Results show that the structures can be precisely back-projected to the back of the hand for further augmented display and visualization. The overall system performance is evaluated in terms of vein segmentation, accuracy of vein matching, feature points distance error, duration times, accuracy of skin reconstruction, and augmented display. All experiments are validated with sets of real vein data. The imaging and augmented system produces good imaging and augmented reality results with high speed.

Breast Cancer after Augmentation: Oncologic and Reconstructive Considerations among Women Undergoing Mastectomy.