Academic literature on the topic 'Useful signal model'
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Journal articles on the topic "Useful signal model"
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Panteleev, Ivan, Aleksander Prokhorov, and Oleg Plekhov. "Strategies for Extracting Damage Induced AE Signals from Different Type Noise-Like Backgrounds for Carbon-Fibre Reinforced Polymers." Applied Sciences 11, no. 16 (August 16, 2021): 7506. http://dx.doi.org/10.3390/app11167506.
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This paper presents an algorithm for isolating a useful acoustic signal (corresponding to damage accumulation) against the background of a signal used to model the performance of an industrial rotary equipment. Acoustic emission signals induced by deformation and fracture were studied using a uniaxial tensile test on woven laminate samples cut along the fiber and weft directions. The background signal is a random composition of acoustic pulses used to model the performance of an industrial rotary equipment. A comparison of useful and noise signals enables us to develop two algorithms based on frequency filtering of a signal and its decomposition into empirical modes. These algorithms can be used to isolate useful AE pulses against the background of all signal intensities under consideration.
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Dutt, Vinayak, and James F. Greenleaf. "Ultrasound Echo Envelope Analysis Using a Homodyned K Distribution Signal Model." Ultrasonic Imaging 16, no. 4 (October 1994): 265–87. http://dx.doi.org/10.1177/016173469401600404.
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The statistics of ultrasound echo envelope signals can be used to characterize scattering media. The Rayleigh distribution and its generalized forms, the K and Rice distributions, have been previously used to model the echo signal. A more generalized statistical model, the homodyned K distribution, combines the K and Rice distribution features to better account for the statistics of the echo signal. We show that this model can give two parameters that are useful for media characterization: k, the ratio of coherent to diffuse signals, and, β, which characterizes the clustering of scatterers in the medium.
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HUANG, XIANGAO, JIANXUE XU, WEI HUANG, and ZEJUN LU. "UNMASKING CHAOTIC MASK BY A WAVELET MULTISCALE DECOMPOSITION ALGORITHM." International Journal of Bifurcation and Chaos 11, no. 02 (February 2001): 561–69. http://dx.doi.org/10.1142/s0218127401002274.
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A method is proposed for extracting a useful signal hidden in a deterministic chaotic signal using a wavelet multiscale decomposition algorithm that can separate two signals with different wavelet scales. The mask removal is done without resorting to chaos synchronization. It is a noise reduction method without knowing the dynamical model of chaotic system, and restricting the modulation ratio of the chaos signal and useful signal. So this method is effective for unmasking chaotic mask through the quantitative analyses and the numerical simulations of three examples.
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Tang, Shixi, Jinan Gu, Keming Tang, Rong Zou, Xiaohong Sun, and Saad Uddin. "A Fault-Signal-Based Generalizing Remaining Useful Life Prognostics Method for Wheel Hub Bearings." Applied Sciences 9, no. 6 (March 14, 2019): 1080. http://dx.doi.org/10.3390/app9061080.
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The goal of this work is to improve the generalization of remaining useful life (RUL) prognostics for wheel hub bearings. The traditional life prognostics methods assume that the data used in RUL prognostics is composed of one specific fatigue damage type, the data used in RUL prognostics is accurate, and the RUL prognostics are conducted in the short term. Due to which, a generalizing RUL prognostics method is designed based on fault signal data. Firstly, the fault signal model is designed with the signal in a complex and mutative environment. Then, the generalizing RUL prognostics method is designed based on the fault signal model. Lastly, the simplified solution of the generalizing RUL prognostics method is deduced. The experimental results show that the proposed method gained good accuracies for RUL prognostics for all the amplitude, energy, and kurtosis features with fatigue damage types. The proposed method can process inaccurate fault signals with different kinds of noise in the actual working environment, and it can be conducted in the long term. Therefore, the RUL prognostics method has a good generalization.
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Islam, Sheikh Md Rabiul, and Md Shakibul Islam. "Neural Mass Model-Based Different EEG Signal Generation and Analysis in Simulink." Indian Journal of Signal Processing 1, no. 3 (August 10, 2021): 1–7. http://dx.doi.org/10.35940/ijsp.c1008.081321.
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The electroencephalogram (EEG) is an electrophysiological monitoring strategy that records the spontaneous electrical movement of the brain coming about from ionic current inside the neurons of the brain. The importance of the EEG signal is mainly the diagnosis of different mental and brain neurodegenerative diseases and different abnormalities like seizure disorder, encephalopathy, dementia, memory problem, sleep disorder, stroke, etc. The EEG signal is very useful for someone in case of a coma to determine the level of brain activity. So, it is very important to study EEG generation and analysis. To reduce the complexity of understanding the pathophysiological mechanism of EEG signal generation and their changes, different simulation-based EEG modeling has been developed which are based on anatomical equivalent data. In this paper, Instead of a detailed model a neural mass model has been used to implement different simulation-based EEG models for EEG signal generation which refers to the simplified and straightforward method. This paper aims to introduce obtained EEG signals of own implementation of the Lopes da Silva model, Jansen-Rit model, and Wendling model in Simulink and to compare characteristic features with real EEG signals and better understanding the EEG abnormalities especially the seizure-like signal pattern.
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Islam, Sheikh Md Rabiul, and Md Shakibul Islam. "Neural Mass Model-Based Different EEG Signal Generation and Analysis in Simulink." Indian Journal of Signal Processing 1, no. 3 (August 10, 2021): 1–7. http://dx.doi.org/10.54105/ijsp.c1008.081321.
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The electroencephalogram (EEG) is an electrophysiological monitoring strategy that records the spontaneous electrical movement of the brain coming about from ionic current inside the neurons of the brain. The importance of the EEG signal is mainly the diagnosis of different mental and brain neurodegenerative diseases and different abnormalities like seizure disorder, encephalopathy, dementia, memory problem, sleep disorder, stroke, etc. The EEG signal is very useful for someone in case of a coma to determine the level of brain activity. So, it is very important to study EEG generation and analysis. To reduce the complexity of understanding the pathophysiological mechanism of EEG signal generation and their changes, different simulation-based EEG modeling has been developed which are based on anatomical equivalent data. In this paper, Instead of a detailed model a neural mass model has been used to implement different simulation-based EEG models for EEG signal generation which refers to the simplified and straightforward method. This paper aims to introduce obtained EEG signals of own implementation of the Lopes da Silva model, Jansen-Rit model, and Wendling model in Simulink and to compare characteristic features with real EEG signals and better understanding the EEG abnormalities especially the seizure-like signal pattern.
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Lv, Mingzhu, Shixun Liu, Xiaoming Su, and Changzheng Chen. "General Log-Linear Weibull Model Combining Vibration and Temperature Characteristics for Remaining Useful Life Prediction of Rolling Element Bearings." Shock and Vibration 2020 (August 20, 2020): 1–17. http://dx.doi.org/10.1155/2020/8829823.
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In industrial applications, the vibration and temperature measurements of rolling element bearings are known as two popular condition monitoring methods. The previously published method for remaining useful life (RUL) prediction has been limited to using the vibration signal. However, a single signal source cannot fully reflect the degradation trend of bearings, influencing the RUL prediction precision. In this paper, a novel general log-linear Weibull (GLL-Weibull) model is constructed by considering vibration and temperature condition monitoring signals to estimate the model parameters. During the feature extraction stage, the relative root mean square (RRMS) is derived from the monitored vibration signal, and the relative temperature trend value is extracted from the monitored temperature signal to eliminate individual differences in bearings and random signal fluctuations. Then, a fuzzy operator is introduced to describe the degree of an “overheated bearing” and “excessive bearing vibrations.” During the RUL prediction stage, both the extracted vibration and temperature characteristics are used to create the GLL-Weibull model. The best parameters are attained by employing the maximum likelihood estimation approach. The algorithm performance is checked with criteria like the root mean square error (RMSE) and the mean absolute percentage error (MAPE). The effectiveness and superiority of the presented approach are validated by two real-life prognosis cases. According to the experimental results, the presented approach provides superior prediction precision and lower computational cost than other approaches for bearings under constant or variable operating conditions.
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Otto, G. K. "Interferometry feedback in the laser resonator. Parametric model." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 3 (2019): 62–69. http://dx.doi.org/10.17721/1812-5409.2019/3.9.
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The article is devoted to an alternative view on the explanation of the mechanism of action of devices based on laser feedback interferometry (LFI-model), which is caused by contradictions between the theory of existing models and practical results. A view other than the Lang-Kobayashi model (LK model) and the parametric LFI model (P model) are proposed. Due to the theory, which is based on the parametric properties of the LFI-model, the level of advantage of LFI technology over traditional technologies is quantitatively substantiated. The article gives an example of calculating the useful signal power. It is calculated that at a distance of 500 meters, the signal according to the P-model is 34 dB higher than the signal calculated by traditional models. Thus, from the traditional models follows the inverse square dependence of the signal-to-noise ratio (S / N ratio, hereinafter - SNR) on the distance to the target l_t, viz.: SNR ~ l_t^{-2}. In practice, the SNR is much higher. Within the P-model, another dependence of SNR on l_t, is theoretically proved and experimentally confirmed, viz.: SNR ~ (l_t * ln l_t^2)^{-1/2}. Traditional models do not consider the presence of a useful signal in the pump current, while, in fact, its power is more than 10 times greater than the radiation power in the resonator. The P-model eliminates contradictions between theoretical models and practical results.
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Hamam, Zeina, Nathalie Godin, Claudio Fusco, Aurélien Doitrand, and Thomas Monnier. "Acoustic Emission Signal Due to Fiber Break and Fiber Matrix Debonding in Model Composite: A Computational Study." Applied Sciences 11, no. 18 (September 10, 2021): 8406. http://dx.doi.org/10.3390/app11188406.
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Acoustic emission monitoring is a useful technique to deal with detection and identification of damage in composite materials. Over the last few years, identification of damage through intelligent signal processing was particularly emphasized. Data-driven models are developed to predict the remaining useful lifetime. Finite elements modeling (FEM) was used to simulate AE signals due to fiber break and fiber/matrix debonding in a model carbon fiber composite and thereby better understand the AE signals and physical phenomena. This paper presents a computational analysis of AE waveforms resulting from fiber break and fiber/matrix debonding. The objective of this research was to compare the AE signals from a validated fiber break simulation to the AE signals obtained from fiber/matrix debonding and fiber break obtained in several media and to discuss the capability to detect and identify each source.
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Bae, Hyeon, Youn-Tae Kim, Sungshin Kim, Sang-Hyuk Lee, and Bo-Hyeun Wang. "Fault Detection of Induction Motors Using Fourier and Wavelet Analysis." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 4 (July 20, 2004): 431–36. http://dx.doi.org/10.20965/jaciii.2004.p0431.
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The motor is the workhorse of industries. The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This paper introduces fault detection for induction motors. Stator currents are measured by current meters and stored by time domain. The time domain is not suitable for representing current signals, so the frequency domain is applied to display signals. The Fourier Transform is employed to convert signals. After signal conversion, signal features must be extracted by signal processing such as wavelet and spectrum analysis. Features are entered in a pattern classification model such as a neural network model, a polynomial neural network, or a fuzzy inference model. This paper describes fault detection results that use Fourier and wavelet analysis. This combined approach is very useful and powerful for detecting signal features.
Dissertations / Theses on the topic "Useful signal model"
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Філатова, Ганна Євгенівна. "Методи та засоби підтримки прийняття рішень в біомедичних системах на основі морфологічного аналізу біомедичних сигналів та зображень." Thesis, НТУ "ХПІ", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/32462.
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Дисертація на здобуття наукового ступеня доктора технічних наук за спеціальністю 05.11.17 – біологічні та медичні прилади i системи. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2017.
Дисертація присвячена вирішенню актуальної науково-прикладної проблеми розвитку теоретичних основ і засобів підтримки прийняття рішень при проектуванні біомедичних систем на основі морфологічного аналізу біомедичних сигналів та зображень з локально зосередженими ознаками з використанням узгодженої морфологічної фільтрації, яка враховує в явному або неявному вигляді моделі корисних одновимірних і двовимірних сигналів. Розроблено узагальнену модель процесу інструментального обстеження пацієнта у вигляді сукупності функціональної, інформаційної, структурної і математичної моделей. Розроблено півтоновий морфологічний фільтр на основі локальних статистик, який в неявному вигляді враховує модель корисного двовимірного сигналу. Розроблений узагальнений метод морфологічного аналізу біомедичних сигналів з локально зосередженими ознаками за допомогою багатоканального узгодженого морфологічного фільтра. Розроблено критерій оцінки якості методу морфологічного аналізу біомедичних сигналів з локально зосередженими ознаками на основі синтезованого багатоканального узгодженого морфологічного фільтра. Розроблена система альтернативних діагностичних ознак при морфологічному аналізі біомедичних сигналів з локально зосередженими ознаками, що враховує модель корисного одновимірного сигналу і властивості функції виявлення узгодженого морфологічного фільтра. Розроблена математична модель цифрового рентгенівського зображення, що враховує особливості візуалізації біологічних об'єктів і їх структурних елементів. Розроблений метод підвищення якості візуалізації біологічних об'єктів на рентгенівських зображеннях широкого класу на основі морфологічного аналізу біомедичних зображень з локально зосередженими ознаками. Розроблений об'єктивний інтегральний критерій оцінки якості візуалізації біологічних об'єктів та їх структурних елементів на медичних слабоконтрастних півтонових рентгенологічних зображеннях. Розроблена структура узагальненої біомедичної системи підтримки прийняття рішень, а також програмне забезпечення модулів морфологічного аналізу біомедичних сигналів та зображень з локально зосередженими ознаками. Виконано перевірку адекватності розроблених методів морфологічного аналізу при обробці реальних біомедичних сигналів та зображень.Dissertation for the doctor degree in the technical sciences area for specialty 05.11.17 – Biological and Medical Devices and Systems. – National Technical University "Kharkiv Polytechnic Institute", Kharkiv, 2017. The dissertation is devoted to the solution of the actual scientific and applied problem of the development of theoretical foundations and decision support means in the design of biomedical systems based on the morphological analysis of biomedical signals and images with locally concentrated features using consistent morphological filtering that takes into account explicitly or implicitly models of useful one- and twodimensional signals. The generalized model of the instrumental examination process of the patient as a set of functional, informational, structural and mathematical models was developed. The halftone morphological filter on the basis of local statistics which implicitly takes into account the model of a useful two-dimensional signal was developed. The generalized method for the morphological analysis of biomedical signals with locally concentrated features using a multichannel matched morphological filter was developed. The criterion for evaluating the quality of the morphological analysis method of biomedical signals with locally concentrated features on the basis of a synthesized multichannel matched morphological filter was developed. The system of alternative diagnostic features in the morphological analysis of biomedical signals with locally concentrated features taking into account the model of a useful one-dimensional signal and the properties of the detecting function of matched morphological filter was developed. The mathematical model of a digital X-ray image that takes into account the visualization features of biological objects and their structural elements was developed. The method for improving the quality of visualization of biological objects on X-ray images of a wide class was developed on the basis of the morphological analysis of biomedical images with locally concentrated features. The objective integral criterion for assessing the quality of visualization of biological objects and their structural elements on medical lowcontrast halftone X-ray images was developed. The structure of the generalized biomedical decision support system as well as the software for modules of morphological analysis of biomedical signals and images with locally concentrated features were developed. The adequacy of the developed methods of morphological analysis in the processing of real biomedical signals and images was checked.
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Філатова, Ганна Євгенівна. "Методи та засоби підтримки прийняття рішень в біомедичних системах на основі морфологічного аналізу біомедичних сигналів та зображень." Thesis, НТУ "ХПІ", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/32456.
Full textAbstract:
Дисертація на здобуття наукового ступеня доктора технічних наук за спеціальністю 05.11.17 – біологічні та медичні прилади i системи. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2017.
Дисертація присвячена вирішенню актуальної науково-прикладної проблеми розвитку теоретичних основ і засобів підтримки прийняття рішень при проектуванні біомедичних систем на основі морфологічного аналізу біомедичних сигналів та зображень з локально зосередженими ознаками з використанням узгодженої морфологічної фільтрації, яка враховує в явному або неявному вигляді моделі корисних одновимірних і двовимірних сигналів. Розроблено узагальнену модель процесу інструментального обстеження пацієнта у вигляді сукупності функціональної, інформаційної, структурної і математичної моделей. Розроблено півтоновий морфологічний фільтр на основі локальних статистик, який в неявному вигляді враховує модель корисного двовимірного сигналу. Розроблений узагальнений метод морфологічного аналізу біомедичних сигналів з локально зосередженими ознаками за допомогою багатоканального узгодженого морфологічного фільтра. Розроблено критерій оцінки якості методу морфологічного аналізу біомедичних сигналів з локально зосередженими ознаками на основі синтезованого багатоканального узгодженого морфологічного фільтра. Розроблена система альтернативних діагностичних ознак при морфологічному аналізі біомедичних сигналів з локально зосередженими ознаками, що враховує модель корисного одновимірного сигналу і властивості функції виявлення узгодженого морфологічного фільтра. Розроблена математична модель цифрового рентгенівського зображення, що враховує особливості візуалізації біологічних об'єктів і їх структурних елементів. Розроблений метод підвищення якості візуалізації біологічних об'єктів на рентгенівських зображеннях широкого класу на основі морфологічного аналізу біомедичних зображень з локально зосередженими ознаками. Розроблений об'єктивний інтегральний критерій оцінки якості візуалізації біологічних об'єктів та їх структурних елементів на медичних слабоконтрастних півтонових рентгенологічних зображеннях. Розроблена структура узагальненої біомедичної системи підтримки прийняття рішень, а також програмне забезпечення модулів морфологічного аналізу біомедичних сигналів та зображень з локально зосередженими ознаками. Виконано перевірку адекватності розроблених методів морфологічного аналізу при обробці реальних біомедичних сигналів та зображень.Dissertation for the doctor degree in the technical sciences area for specialty 05.11.17 – Biological and Medical Devices and Systems. – National Technical University "Kharkiv Polytechnic Institute", Kharkiv, 2017. The dissertation is devoted to the solution of the actual scientific and applied problem of the development of theoretical foundations and decision support means in the design of biomedical systems based on the morphological analysis of biomedical signals and images with locally concentrated features using consistent morphological filtering that takes into account explicitly or implicitly models of useful one- and twodimensional signals. The generalized model of the instrumental examination process of the patient as a set of functional, informational, structural and mathematical models was developed. The halftone morphological filter on the basis of local statistics which implicitly takes into account the model of a useful two-dimensional signal was developed. The generalized method for the morphological analysis of biomedical signals with locally concentrated features using a multichannel matched morphological filter was developed. The criterion for evaluating the quality of the morphological analysis method of biomedical signals with locally concentrated features on the basis of a synthesized multichannel matched morphological filter was developed. The system of alternative diagnostic features in the morphological analysis of biomedical signals with locally concentrated features taking into account the model of a useful one-dimensional signal and the properties of the detecting function of matched morphological filter was developed. The mathematical model of a digital X-ray image that takes into account the visualization features of biological objects and their structural elements was developed. The method for improving the quality of visualization of biological objects on X-ray images of a wide class was developed on the basis of the morphological analysis of biomedical images with locally concentrated features. The objective integral criterion for assessing the quality of visualization of biological objects and their structural elements on medical lowcontrast halftone X-ray images was developed. The structure of the generalized biomedical decision support system as well as the software for modules of morphological analysis of biomedical signals and images with locally concentrated features were developed. The adequacy of the developed methods of morphological analysis in the processing of real biomedical signals and images was checked.
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Jha, Mayank Shekhar. "Diagnostic et Pronostic de Systèmes Dynamiques Incertains dans un contexte Bond Graph." Thesis, Ecole centrale de Lille, 2015. http://www.theses.fr/2015ECLI0027/document.
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Cette thèse développe des approches pour le diagnostic et le pronostic de systèmes dynamiques incertains en utilisant la technique de modélisation Bond Graph (BG). Tout d'abord, une représentation par intervalles des incertitudes paramétriques et de mesures est intégrée à un modèle BG-LFT (Linear Fractional Transformation). Une méthode de détection robuste de défaut est développée en utilisant les règles de l'arithmétique d'intervalle pour la génération de seuils robustes et adaptatifs sur les résidus nominaux. La méthode est validée en temps réel sur un système de générateur de vapeur.Deuxièmement, une nouvelle méthodologie de pronostic hybride est développée en utilisant les Relations de Redondance Analytique déduites d'un modèle BG et les Filtres Particulaires. Une estimation de l'état courant du paramètre candidat pour le pronostic est obtenue en termes probabilistes. La prédiction de la durée de vie résiduelle est atteinte en termes probabilistes. Les incertitudes associées aux mesures bruitées, les conditions environnementales, etc. sont gérées efficacement. La méthode est validée en temps réel sur un système mécatronique incertain.Enfin, la méthodologie de pronostic développée est mise en œuvre et validée pour le suivi efficace de la santé d'un sous-système électrochimique d’une pile à combustible à membrane échangeuse de protons (PEMFC) industrielle à l’aide de données de dégradation réellesThis thesis develops the approaches for diagnostics and prognostics of uncertain dynamic systems in Bond Graph (BG) modeling framework. Firstly, properties of Interval Arithmetic (IA) and BG in Linear Fractional Transformation, are integrated for representation of parametric and measurement uncertainties on an uncertain BG model. Robust fault detection methodology is developed by utilizing the rules of IA for the generation of adaptive interval valued thresholds over the nominal residuals. The method is validated in real time on an uncertain and highly complex steam generator system.Secondly, a novel hybrid prognostic methodology is developed using BG derived Analytical Redundancy Relationships and Particle Filtering algorithms. Estimations of the current state of health of a system parameter and the associated hidden parameters are achieved in probabilistic terms. Prediction of the Remaining Useful Life (RUL) of the system parameter is also achieved in probabilistic terms. The associated uncertainties arising out of noisy measurements, environmental conditions etc. are effectively managed to produce a reliable prediction of RUL with suitable confidence bounds. The method is validated in real time on an uncertain mechatronic system.Thirdly, the prognostic methodology is validated and implemented on the electrical electro-chemical subsystem of an industrial Proton Exchange Membrane Fuel Cell. A BG of the latter is utilized which is suited for diagnostics and prognostics. The hybrid prognostic methodology is validated, involving real degradation data sets
Books on the topic "Useful signal model"
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Huffaker, Ray, Marco Bittelli, and Rodolfo Rosa. Capstone: Application of NLTS to Real-World Data. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198782933.003.0010.
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This chapter investigates the use of Extreme Value Statistics (EVS) to probabilistically model extreme events separated as unstructured noise in signal processing. We apply a version of EVS that computes the likelihood of extreme discrepancies exceeding a selected threshold value within a given time interval. In theory, exceedances follow a Generalized Pareto (GP) distribution, and we run diagnostics to determine how well the data actually fit this distribution. If we find a reasonable fit, we can invert the GP distribution to solve for quantiles providing a useful noise diagnostic: return level plots. Return level plots show the return periods expected before particular extreme noise levels return levels are realized.
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Prado, Raquel. Multistate models for mental fatigue. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.29.
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This article discusses the use of structured, multivariate Bayesian dynamic models in the analysis of experimental data involving large-scale electroencephalography (EEG) signals or time series generated on individuals subject to tasks inducing mental fatigue. It first provides an overview of the goals and challenges in the analysis of brain signals, using the EEG case as example, before describing the development and application of novel time-varying autoregressive and regime switching models, which incorporate relevant prior information via structured priors and fitted using novel, customized Bayesian computational methods. In the experiment, a subject was asked to perform simple arithmetic operations for a period of three hours. Prior to the experiment, the subject was confirmed to be alert. After the experiment ended, the subject was fatigued. The study demonstrates that Bayesian analysis is useful for real time detection of cognitive fatigue.
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Display description and information template. Society for Information Display, 2012. http://dx.doi.org/10.55410/hwjr7479.
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This template lists the kind of information that is useful to record for keeping a good record of the conditions of the measurements. It includes, display information, description, colors, pitch, signal and power, standard conditions and modes, display size and mechanical facts, deviations, detector properties, and other information.
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Busemeyer, Jerome R., Zheng Wang, James T. Townsend, and Ami Eidels, eds. The Oxford Handbook of Computational and Mathematical Psychology. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.001.0001.
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A comprehensive and authoritative review on most important developments in computational and mathematical psychology that have impacted many other fields in past decades. Written in tutorial style by leading scientists in each topic area, with an emphasis on examples and applications. Each chapter is self-contained and aims to engage readers with various levels of modeling experience. The Handbook covers the key developments in elementary cognitive mechanisms (e.g., signal detection, information processing, reinforcement learning), basic cognitive skills (e.g., perceptual judgment, categorization, episodic memory), higher-level cognition (e.g., Bayesian cognition, decision making, semantic memory, shape perception), modeling tools (e.g., Bayesian estimation and other new model comparison methods), and emerging new directions (e.g., neurocognitive modeling, applications to clinical psychology, quantum cognition) in computation and mathematical psychology. The chapters were written for a typical graduate student in virtually any area of psychology, cognitive science, and related social and behavioral sciences, such as consumer behavior and communication. We also expect it to be useful for readers ranging from advanced undergraduate students to experienced faculty members and researchers. Beyond being a handy reference book, it should be beneficial as a textbook for self-teaching, and for graduate level (or advanced undergraduate level) courses in computational and mathematical psychology.
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Simpson, Stephen J., Carlos Ribeiro, and Daniel González-Tokman. Feeding behavior. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797500.003.0008.
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Insects need to ingest nutrients at appropriate levels to attain a balanced diet and maximize fitness. They do so by integrated responses that involve physiological mechanisms for sensing current nutritional needs, releasing systemic signals, and producing specific appetites for key required nutrients. Historically, the study of insect feeding behavior was appreciated for its importance in the understanding and control of crop pests and disease vectors. However, current evidence has shown that some mechanisms regulating feeding are highly conserved in animals, from insects to humans, bringing additional interest in insects as models in medicine. The study of insect feeding behavior and nutrition has also given rise to an integrative modelling approach called the geometric framework for nutrition. This approach has proven useful beyond the insects, and allows the understanding of the impact of multiple nutrients on individuals and their interactions in populations, communities, and ecosystems.
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Goswami, B. N., and Soumi Chakravorty. Dynamics of the Indian Summer Monsoon Climate. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.613.
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Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales.The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient.The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.
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Galderisi, Maurizio, and Sergio Mondillo. Assessment of diastolic function. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199599639.003.0009.
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Modern assessment of left ventricular (LV) diastolic function should be based on the estimation of degree of LV filling pressure (LVFP), which is the true determinant of symptoms/signs and prognosis in heart failure.In order to achieve this goal, standard Doppler assessment of mitral inflow pattern (E/A ratio, deceleration time, isovolumic relaxation time) should be combined with additional manoeuvres and/or ultrasound tools such as: ◆ Valsalva manoeuvre applied to mitral inflow pattern. ◆ Pulmonary venous flow pattern. ◆ Velocity flow propagation by colour M-mode. ◆ Pulsed wave tissue Doppler of mitral annuls (average of septal and lateral E′ velocity).In intermediate doubtful situations, the two-dimensional determination of left atrial (LA) volume can be diagnostic, since LA enlargement is associated with a chronic increase of LVFP in the absence of mitral valve disease and atrial fibrillation.Some new echocardiographic technologies, such as the speckle tracking-derived LV longitudinal strain and LV torsion, LA strain, and even the three-dimensional determination of LA volumes can be potentially useful to add further information. In particular, the reduction of LV longitudinal strain in patients with LV diastolic dysfunction and normal ejection fraction demonstrates that a subclinical impairment of LV systolic function already exists under these circumstances.
Book chapters on the topic "Useful signal model"
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Thabet, Mohamad, David Sanders, and Nils Bausch. "Detection of Patterns in Pressure Signal of Compressed Air System Using Wavelet Transform." In Springer Proceedings in Energy, 61–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_8.
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AbstractThis paper investigates detecting patterns in the pressure signal of a compressed air system (CAS) with a load/unload control using a wavelet transform. The pressure signal of a CAS carries useful information about operational events. These events form patterns that can be used as ‘signatures’ for event detection. Such patterns are not always apparent in the time domain and hence the signal was transformed to the time-frequency domain. Three different CAS operating modes were considered: idle, tool activation and faulty. The wavelet transforms of the CAS pressure signal reveal unique features to identify events within each mode. Future work will investigate creating machine learning tools for that utilize these features for fault detection in CAS.
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Veshkurtsev, Yury. "COMPUTER SIMULATION OF THE MODEM." In THE FOUNDATIONS OF THE THEORY OF CONSTRUCTION OF NEW-GENERATION MODEMS, 142–55. au: AUS PUBLISHERS, 2022. http://dx.doi.org/10.26526/chapter_628a89252ca618.76723701.
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The monography presents the fundamentals of the theory of construction new-generation modems. Modems are built on the principles of statistical communication theory, based on the use of a random signal (chaos) as a carrier of information. In such a signal, a characteristic function is modulated, which is a fundamental characteristic of a random process. The signal modulation and demodulation method is patented and allows you to create modems with efficiency and noise immunity indicators several orders of magnitude higher than those of the known devices of the same name. New-generation modems immediately improve the technical characteristics of digital IT equipment by several orders of magnitude, since they work without errors in wired and radio channels when receiving one hundred duodecillion of binary symbols. The book is recommended for scientists and specialists in the field of digital communication systems, statistical radio engineering and instrumentation, and may be useful for graduate students, masters and students of relevant specialties.
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Boškoski, Pavle, Matej Gašperin, and Dejan Petelin. "Signal Complexity and Gaussian Process Models Approach for Bearing Remaining Useful Life Estimation." In Lecture Notes in Mechanical Engineering, 91–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39348-8_7.
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Veshkurtsev, Yury. "NOISE IMMUNITY OF THE MODEM IN THE CHANNEL WITH "WHITE" NOISE." In THE FOUNDATIONS OF THE THEORY OF CONSTRUCTION OF NEW-GENERATION MODEMS, 48–98. au: AUS PUBLISHERS, 2022. http://dx.doi.org/10.26526/chapter_628a89252a3fa2.30236651.
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The monography presents the fundamentals of the theory of construction new-generation modems. Modems are built on the principles of statistical communication theory, based on the use of a random signal (chaos) as a carrier of information. In such a signal, a characteristic function is modulated, which is a fundamental characteristic of a random process. The signal modulation and demodulation method is patented and allows you to create modems with efficiency and noise immunity indicators several orders of magnitude higher than those of the known devices of the same name. New-generation modems immediately improve the technical characteristics of digital IT equipment by several orders of magnitude, since they work without errors in wired and radio channels when receiving one hundred duodecillion of binary symbols. The book is recommended for scientists and specialists in the field of digital communication systems, statistical radio engineering and instrumentation, and may be useful for graduate students, masters and students of relevant specialties.
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Diomedi, Stefano, Francesco Edoardo Vaccari, Kostas Hadjidimitrakis, and Patrizia Fattori. "Using HMM to Model Neural Dynamics and Decode Useful Signals for Neuroprosthetic Control." In Unsupervised and Semi-Supervised Learning, 59–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99142-5_3.
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Veshkurtsev, Yury. "NOISE IMMUNITY OF THE MODEM IN THE CHANNEL WITH "NON- WHITE" NOISE." In THE FOUNDATIONS OF THE THEORY OF CONSTRUCTION OF NEW-GENERATION MODEMS, 99–141. au: AUS PUBLISHERS, 2022. http://dx.doi.org/10.26526/chapter_628a89252b5337.85338589.
Full textAbstract:
The monography presents the fundamentals of the theory of construction new-generation modems. Modems are built on the principles of statistical communication theory, based on the use of a random signal (chaos) as a carrier of information. In such a signal, a characteristic function is modulated, which is a fundamental characteristic of a random process. The signal modulation and demodulation method is patented and allows you to create modems with efficiency and noise immunity indicators several orders of magnitude higher than those of the known devices of the same name. New-generation modems immediately improve the technical characteristics of digital IT equipment by several orders of magnitude, since they work without errors in wired and radio channels when receiving one hundred duodecillion of binary symbols. The book is recommended for scientists and specialists in the field of digital communication systems, statistical radio engineering and instrumentation, and may be useful for graduate students, masters and students of relevant specialties.
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Litvinov, O., D. Murodyans, and I. Karandashev. "Research of Useful Signal Losses in Adaptive Antenna Arrays with Neural Network Control of Phase Shifters in Various Modes of Their Operation." In Advances in Neural Computation, Machine Learning, and Cognitive Research V, 285–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91581-0_38.
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Benneworth, Paul, Elena Castro-Martínez, Julia Olmos-Peñuela, and Reetta Muhonen. "Rethinking the Role of Productive Interactions in Explaining SSH Research Societal Impacts: Towards a Conceptual Framework for Productive Science System Dynamics." In University-Industry Knowledge Interactions, 45–64. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84669-5_4.
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AbstractIn this paper we seek to realise the potential that Spaapen and van Drooge’s productive interactions concept offers, but which we argue has been lost through its operationalisation as a process of ‘counting interactions’. Productive interactions arise through moments of contact between two very different systems (the societal and the scientific), and each system values societal impact in very different ways. Finding mutual value in that interaction is important, and we argue that value in both arises when network arrangements shift, as academic disciplines solve urgent scientific problems and as societies improve living conditions. Productive interactions approach assumes the value-frameworks of the wider networks within which particular knowledge sets become actionable. However, our constructive critique highlights the omission of the wider elements of science and social systems within which productive interactions takes place (and whose dynamics ultimately determine the final scientific and societal impact of that research). Indeed, research evaluation to date has not considered the consequences of the productive interactions in terms of these changing relationships. To contribute to this lacuna, we propose a model that conceptualises a meso-level system comprising interactions between actors within two subsystems, highlighting the importance of coupling between researchers and users, valuation signals given to particular productive interactions from researcher and societal communities and the way these signals in turn embed useful knowledge practices. We apply it to a set of examples of productive interactions in the field of social sciences and humanities (SSH) gathered in the framework of a European project.
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Oury, Jacob D., and Frank E. Ritter. "Cognition and Operator Performance." In Human–Computer Interaction Series, 37–62. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-47775-2_3.
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AbstractDeveloping systems that foster situation awareness in operators requires that stakeholders can make informed decisions about the design. These decisions must account for the operator’s underlying cognitive processes based on perception, comprehension, and projection of the system state. This chapter reviews the core cognitive processes responsible for monitoring and responding to changes in system state. Operators must perceive information before they can act in response, and the interface design affects operator accuracy and speed via known mechanisms (i.e., effects of color on visual search time). Perception of key information also relies on how the operator thinks during tasks, and certain design choices can support better attention control and detection of signals. After perceiving the information, operators also must comprehend and interpret the information. Design guidance and factors related to supporting comprehension are presented alongside explanations of how cognitive load and working memory affect the operator’s ability to develop and maintain a useful mental model of the system. This review of cognitive mechanisms gives designers a strong foundation to make informed decisions ranging from choosing an alarm color to assessing how much information should be on screen at once.
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Dela Haije, Tom, and Aasa Feragen. "Conceptual Parallels Between Stochastic Geometry and Diffusion-Weighted MRI." In Mathematics and Visualization, 193–202. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-56215-1_9.
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AbstractDiffusion-weighted magnetic resonance imaging (MRI) is sensitive to ensemble-averaged molecular displacements, which provide valuable information on e.g. structural anisotropy in brain tissue. However, a concrete interpretation of diffusion-weighted MRI data in terms of physiological or structural parameters turns out to be extremely challenging. One of the main reasons for this is the multi-scale nature of the diffusion-weighted signal, as it is sensitive to the microscopic motion of particles averaged over macroscopic volumes. In order to analyze the geometrical patterns that occur in (diffusion-weighted measurements of) biological tissue and many other structures, we may invoke tools from the field of stochastic geometry. Stochastic geometry describes statistical methods and models that apply to random geometrical patterns of which we may only know the distribution. Despite its many uses in geology, astronomy, telecommunications, etc., its application in diffusion-weighted MRI has so far remained limited. In this work we review some fundamental results in the field of diffusion-weighted MRI from a stochastic geometrical perspective, and discuss briefly for which other questions stochastic geometry may prove useful. The observations presented in this paper are partly inspired by the Workshop on Diffusion MRI and Stochastic Geometry held at Sandbjerg Estate (Denmark) in 2019, which aimed to foster communication and collaboration between the two fields of research.
Conference papers on the topic "Useful signal model"
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Tsiporkova, Ksenia, Nikita Tsiporkov, Larisa Revkova, and Andrey Dubovikov. "Method of Orthogonal Decomposition for Generalized Useful Signal Model." In 2019 8th Mediterranean Conference on Embedded Computing (MECO). IEEE, 2019. http://dx.doi.org/10.1109/meco.2019.8760182.
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Al-Dulaimi, Ali, Soheil Zabihi, Amir Asif, and Arash Mohammadi. "Hybrid Deep Neural Network Model for Remaining Useful Life Estimation." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683763.
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Zou, Gang, Lei Song, and Zhen Yan. "Lithium-ion Battery Remaining Useful Life Prediction Based on Hybrid Model." In 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP). IEEE, 2022. http://dx.doi.org/10.1109/icsp54964.2022.9778611.
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Harita, K., and M. Anburajan. "Patient specific CAD model of useful carotid artery (CA) for CFD analysis of CA with plaque condition." In 2013 International Conference on Communications and Signal Processing (ICCSP). IEEE, 2013. http://dx.doi.org/10.1109/iccsp.2013.6577078.
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Ghorbanian, Parham, Subramanian Ramakrishnan, Adam J. Simon, and Hashem Ashrafiuon. "Stochastic Dynamic Modeling of the Human Brain EEG Signal." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3881.
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The occurrence and risk of recurrence of brain related injuries and diseases are difficult to characterize due to various factors including inter-individual variability. A useful approach is to analyze the brain electroencephalogram (EEG) for differences in brain frequency bands in the signals obtained from potentially injured and healthy normal subjects. However, significant shortcomings include: (1) contrary to empirical evidence, current spectral signal analysis based methods often assume that the EEG signal is linear and stationary; (2) nonlinear time series analysis methods are mostly numerical and do not possess any predictive features. In this work, we develop models based on stochastic differential equations that can output signals with similar frequency and magnitude characteristics of the brain EEG. Initially, a coupled linear oscillator model with a large number of degrees of freedom is developed and shown to capture the characteristics of the EEG signal in the major brain frequency bands. Then, a nonlinear stochastic model based on the Duffing oscillator with far fewer degrees of freedom is developed and shown to produce outputs that can closely match the EEG signal. It is shown that such a compact nonlinear model can provide better insight into EEG dynamics through only few parameters, which is a step towards developing a framework with predictive capabilities for addressing brain injuries.
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Li, Xin, and Xiaolei Fang. "Multistream Sensor Fusion-Based Prognostics Model for Systems Under Multiple Operational Conditions." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-62348.
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Abstract The residual useful lifetime prediction of complex engineering systems operating under dynamic multi-operational conditions is crucial yet challenging. One of the key challenges is that sensing signals consist of both degradation information that resulted from the physical deterioration of the system and amplitude jumps due to the switch of operational conditions. To accurately predict the failure times, we need to separate the degradation information from sensing signals and exclude jumps. Another challenge stems from the fact that complex engineering systems are typically monitored by multiple sensors that generate multi-stream sensing signals but not all the signals are informative for failure time prediction. Therefore, a systematical sensor selection method needs to be developed to identify informative sensors. The third challenge is that signals from the informative sensors are high-dimensional and may provide redundant information. As a result, a data fusion method is needed to fuse the multi-stream signals from the informative sensors. To address the aforementioned challenges, this paper focuses on developing a prognostic framework for systems that operate under dynamic multiple operational conditions. The framework will first extract the degradation signal from each sensor by removing the jump information resulted from the change of operational conditions. Next, informative sensors are selected using a sensor selection method. Finally, the degradation signals from the selected sensors are fused to predict the failure time of a partially degraded system. The effectiveness of the proposed prognostic framework is validated using a degradation data set of aircraft turbofan engines from NASA repository.
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Sammons, Patrick M., Douglas A. Bristow, and Robert G. Landers. "A Model Predictive Repetitive Process Control Formulation for Additive Manufacturing Processes." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9780.
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Additive Manufacturing (AM) processes are a class of manufacturing processes in which parts are fabricated in a layer-by-layer fashion. The layer-by-layer fabrication method creates layer-to-layer dynamics. Implementing process control that neglects the layer-to-layer dynamics can lead to process instability. While repetitive process controllers which utilize only layer-to-layer feedback are a viable method, their usefulness is limited in that they are not well-suited for tracking non-periodic layer-domain references. However, since the entire reference signal is typically known a priori in AM process fabrications, a predictive control methodology can be useful for controlling fabrications in which the reference signal is non-periodic. In this paper a model predictive control formulation is extended to two-dimensions and utilized for repetitive process control Simulation results comparing open-loop and controlled fabrications for a Laser Metal Deposition process are given.
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Savazzi, José Otávio, Sidney Bruce Shiki, Gustavo Franco Barbosa, and David Guerra-Zubiaga. "Tool Remaining Useful Life Prediction in Robotic Machining of Composite Materials Based on Mechanical Vibrations." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70682.
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Abstract The development of materials and methods used in the aircraft manufacturing industry has been advancing in order to provide a reliable and light aircraft. The use of composite materials becomes indispensable, meanwhile, the processing of this kind of material must be studied to obtain the higher manufacturing efficiency and the best quality of the final product. Industry 4.0 concepts as internet of things, cloud computing and others can be used to fulfil these demands. In this sense, this study aims to create a remaining useful life prediction model for the tools used on the machining of composite materials with robotic manipulators. This task is performed by monitoring and analyzing the mechanical vibrations of the motor assembly and the cutting tool, then reducing the consumption of this material and ensuring the quality and surface integrity of the finished parts. The self-awareness of the process is improved by combining signal processing algorithms and statistical techniques to assist the constant monitoring of the tool wear. In this sense, a digital model is constantly updated aiming the optimization of the cutting process. In the conclusions of the paper, the advantages and drawbacks of the proposed methodology are presented.
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Roberts, Michael D., and Richard T. Hart. "Contour Based Implementation of Long Bone Adaptation." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/bed-23024.
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Abstract The adaptation of bone to its mechanical demands is often described as a feedback control system wherein some aspect of the tissue strain environment acts as a driving signal to initiate cellular-level formation and resorption processes on bone surfaces. While this description may be somewhat simplified, the control system view is useful for organizing ideas, experiments, and simulations of adaptation. In the past 25 years, several investigators have introduced mathematical models and (finite element-based) computer simulations of bone adaptation, using numerous candidate driving mechanical signals as proposed bone mass regulators [1]. These simulations generally use the finite element method — including the appropriate geometry, material description, and loading — to calculate the needed tissue strain parameter being considered as the specific regulation signal. Based on the adaptive response being simulated — geometric and/or material property changes — the finite element model is updated, and re-analyzed in a series of discrete time steps.
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Matsuoka, Taichi, Takuya Wada, and Mizuki Katakura. "Vibration Suppression of Traffic Signal Pole by Generating Electrical Power." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97351.
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The authors propose a damper that generates electrical power in order to not only suppress vibration and also get electrical energy when many traffic signal poles are oscillated by wind, traffic turbulence, and earthquake. The damper consists of a displacement magnifying mechanism by using levers, solenoid coils and rare-earth magnets. It is useful for small deformation between a beam and a column of the traffic pole. Vibration modes of the pole are analyzed by using FEM, and then a small scale model of the traffic pole is built up. The small scale model has 2.3 m high, consists of a steel column and a cantilever beam due to rescale about 1/3 of real scale one, and natural frequency is about 3.5 Hz. Trial damper is manufactured and a damping force, which is caused by the coils crossing magnetic field, is adjusted. Dynamic characteristics of the trial damper are measured by a shaking actuator. In order to confirm vibration reduction, both of seismic and harmonic vibration tests of small scale model when the trial damper is installed are carried out by using a shaking table. The experimental results of harmonic responses are compared with the calculated results by FEM, and effect of vibration suppression and efficiency of generating power are discussed experimentally and numerically.
Reports on the topic "Useful signal model"
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Delmer, Deborah P., Douglas Johnson, and Alex Levine. The Role of Small Signal Transducing Gtpases in the Regulation of Cell Wall Deposition Patterns in Plants. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570571.bard.
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The combined research of the groups of Delmer, Levine and Johnson has led to a number of interesting findings with respect to the function of the small GTPase Rac in plants and also opened up new leads for future research. The results have shown: 1) The Rac13 protein undergoes geranylgeranlyation and is also translocated to the plasma membrane as found for Rac in mammals; 2) When cotton Rac13 is highly- expressed in yeast, it leads to an aberrant phenotype reminiscent of mutants impaired in actin function, supporting a role for Rac13 in cytoskeletal organization; 3) From our searches, there is no strong evidence that plants contain homologs of the related CDC42 genes found in yeast and mammals; 4) We have identified a rather unique Rac gene in Arabidopsis that has unusual extensions at both the N- and C-terminal portions of the protein; 5) New evidence was obtained that an oxidative burst characterized by substantial and sustained production of H202 occurs coincident with the onset of secondary wall synthesis in cotton fibers. Further work indicates that the H202 produced may be a signal for the onset of this phase of development and also strongly suggests that Rac plays an important role in signaling for event. Since the secondary walls of plants that contain high levels of lignin and cellulose are the major source of biomass on earth, understanding what signals control this process may well in the future have important implications for manipulating the timing and extent of secondary wall deposition. 6) When the cotton Rac13 promoter is fused to the reporter gene GUS, expression patterns in Arabidopsis indicate very strong and specific expression in developing trichomes and in developing xyelm. Since both of these cell types are engaged in secondary wall synthesis, this further supports a role for Rac in signaling for onset of this process. Since cotton fibers are anatomically defined as trichomes, these data may also be quite useful for future studies in which the trichomes of Arabidopsis may serve as a model for cotton fiber development; the Rac promoter can therefore be useful to drive expression of other genes proposed to affect fiber development and study the effects on the process; 7) The Rac promoter has also been shown to be the best so far tested for use in development of a system for transient transformation of developing cotton fibers, a technique that should have many applications in the field of cotton biotechnology; 8) One candidate protein that may interact with Rac13 to be characterized further in the future is a protein kinase that may be analogous to the PAK kinase that is known to interact with Rac in mammals.
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Philosoph-Hadas, Sonia, Peter Kaufman, Shimon Meir, and Abraham Halevy. Signal Transduction Pathway of Hormonal Action in Control and Regulation of the Gravitropic Response of Cut Flowering Stems during Storage and Transport. United States Department of Agriculture, October 1999. http://dx.doi.org/10.32747/1999.7695838.bard.
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Original objectives: The basic goal of the present project was to increase our understanding of the cellular mechanisms operating during the gravitropic response of cut flowers, for solving their bending problem without affecting flower quality. Thus, several elements operating at the 3 levels o the gravity-induced signal transduction pathway, were proposed to be examined in snapdragon stems according to the following research goals: 1) Signaling: characterize the signal transduction pathway leading to the gravitropic response, regarding the involvement of [Ca2+]cyt as a mediator of IAA movement and sensitivity to auxin. 2) Transduction by plant hormones: a) Examine the involvement of auxin in the gravitropic response of flower stems with regard to: possible participation of auxin binding protein (ABP), auxin redistribution, auxin mechanism of action (activation of H+-ATPase) mediation by changes in [Ca2+]cyt and possible regulation of auxin-induced Ca2+ action b: calmodulin-activated or Ca2+-activated protein kinases (PK). b) Examine the involvement of ethylene in the gravitropic response of flower stems with regard to auxin-induced ethylene production and sensitivity of the tissue to ethylene. 3) Response: examine the effect of gravistimulation on invertase (associated with growth and elongation) activity and invertase gene expression. 4) Commercial practice: develop practical and simple treatments to prevent bending of cut flowers grown for export. Revisions: 1) Model systems: in addition to snapdragon (Antirrhinum majus L.), 3 other model shoe systems, consisting of oat (Avena sativa) pulvini, Ornithogalun 'Nova' cut flowers and Arabidopsis thaliana inflorescence, were targeted to confirm a more general mechanism for shoot gravitropism. 2 Research topics: the involvement of ABP, auxin action, PK and invertase in the gravitropic response of snapdragon stems could not be demonstrated. Alternatively, the involvement in the gravity signaling cascade of several other physiological mediators apart of [Ca2+]cyt such as: IP3, protein phosphorylation and actin cytoskeleton, was shown. Additional topics introduced: starch statolith reorientation, differential expression of early auxin responsive genes, and differential shoot growth. Background to the topic: The gravitropic bending response of flowering shoots occurring upon their horizontal placement during shipment exhibits a major horticultural problem. In spite of extensive studies in various aboveground organs, the gravitropic response was hardly investigated in flowering shoots. Being a complex multistep process that requires the participation of various cellular components acting in succession or in parallel, analysis of the negative gravitropic response of shoot includes investigation of signal transduction elements and various regulatory physiological mediators. Major achievements: 1) A correlative role for starch statoliths as gravireceptors in flowering shoot was initially established. 2) Differentially phosphorylated proteins and IP3 levels across the oat shoe pulvini, as well as a differential appearance of 2 early auxin-responsive genes in snapdragon stems were all detected within 5-30 minutes following gravistimulation. 3) Unlike in roots, involvement of actin cytoskeleton in early events of the gravitropic response of snapdragon shoots was established. 4) An asymmetric IAA distribution, followed by an asymmetric ethylene production across snapdragon stems was found following gravistimulation. 5) The gravity-induced differential growth in shoots of snapdragon was derived from initial shrinkage of the upper stem side and a subsequent elongation o the lower stem side. 6) Shoot bending could be successfully inhibited by Ca2+ antagonists (that serve as a basis for practical treatments), kinase and phosphatase inhibitors and actin-cytoskeleton modulators. All these agents did not affect vertical growth. The essential characterization of these key events and their sequence led us to the conclusion that blocking gravity perception may be the most powerful means to inhibit bending without hampering shoot and flower growth after harvest. Implications, scientific and agriculture: The innovative results of this project have provided some new insight in the basic understanding of gravitropism in flower stalks, that partially filled the gap in our knowledge, and established useful means for its control. Additionally, our analysis has advanced the understanding of important and fundamental physiological processes involved, thereby leading to new ideas for agriculture. Gravitropism has an important impact on agriculture, particularly for controlling the bending of various important agricultural products with economic value. So far, no safe control of the undesired bending problem of flower stalks has been established. Our results show for the first time that shoot bending of cut flowers can be inhibited without adverse effects by controlling the gravity perception step with Ca2+ antagonists and cytoskeleton modulators. Such a practical benefit resulting from this project is of great economic value for the floriculture industry.
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Naim, Michael, Andrew Spielman, Shlomo Nir, and Ann Noble. Bitter Taste Transduction: Cellular Pathways, Inhibition and Implications for Human Acceptance of Agricultural Food Products. United States Department of Agriculture, February 2000. http://dx.doi.org/10.32747/2000.7695839.bard.
Full textAbstract:
Historically, the aversive response of humans and other mammals to bitter-taste substances has been useful for survival, since many toxic constituents taste bitter. Today, the range of foods available is more diverse. Many bitter foods are not only safe for consumption but contain bitter constituents that provide nutritional benefits. Despite this, these foods are often eliminated from our current diets because of their unacceptable bitterness. Extensive technology has been developed to remove or mask bitterness in foods, but a lack of understanding of the mechanisms of bitterness perception at the taste receptor level has prevented the development of inhibitors or efficient methods for reducing bitterness. In our original application we proposed to: (a) investigate the time course and effect of selected bitter tastants relevant to agricultural products on the formation of intracellular signal molecules (cAMP, IP3, Ca2+) in intact taste cells, in model cells and in membranes derived therefrom; (b) study the effect of specific bitter taste inhibitors on messenger formation and identify G-proteins that may be involved in tastant-induced bitter sensation; (c) investigate interactions and self-aggregation of bitter tastants within membranes; (d) study human sensory responses over time to these bitter-taste stimuli and inhibitors in order to validate the biochemical data. Quench-flow module (QFM) and fast pipetting system (FPS) allowed us to monitor fast release of the aforementioned signal molecules (cGMP, as a putative initial signal was substituted for Ca2+ ions) - using taste membranes and intact taste cells in a time range below 500 ms (real time of taste sensation) - in response to bitter-taste stimulation. Limonin (citrus) and catechin (wine) were found to reduce cellular cAMP and increase IP3 contents. Naringin (citrus) stimulated an IP3 increase whereas the cheese-derived bitter peptide cyclo(leu-Trp) reduced IP3 but significantly increased cAMP levels. Thus, specific transduction pathways were identified, the results support the notion of multiple transduction pathways for bitter taste and cross-talk between a few of those transduction pathways. Furthermore, amphipathic tastants permeate rapidly (within seconds) into liposomes and taste cells suggesting their availability for direct activation of signal transduction components by means of receptor-independent mechanisms within the time course of taste sensation. The activation of pigment movement and transduction pathways in frog melanophores by these tastants supports such mechanisms. Some bitter tastants, due to their amphipathic properties, permeated (or interacted with) into a bitter tastant inhibitor (specific phospholipid mixture) which apparently forms micelles. Thus, a mechanism via which this bitter taste inhibitor acts is proposed. Human sensory evaluation experiments humans performed according to their 6-n-propyl thiouracil (PROP) status (non-tasters, tasters, super-tasters), indicated differential perception of bitterness threshold and intensity of these bitter compounds by different individuals independent of PROP status. This suggests that natural products containing bitter compounds (e.g., naringin and limonin in citrus), are perceived very differently, and are in line with multiple transduction pathways suggested in the biochemical experiments. This project provides the first comprehensive effort to explore the molecular basis of bitter taste at the taste-cell level induced by economically important and agriculturally relevant food products. The findings, proposing a mechanism for bitter-taste inhibition by a bitter taste inhibitor (made up of food components) pave the way for the development of new, and perhaps more potent bitter-taste inhibitors which may eventually become economically relevant.
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Bobashev, Georgiy, John Holloway, Eric Solano, and Boris Gutkin. A Control Theory Model of Smoking. RTI Press, June 2017. http://dx.doi.org/10.3768/rtipress.2017.op.0040.1706.
Full textAbstract:
We present a heuristic control theory model that describes smoking under restricted and unrestricted access to cigarettes. The model is based on the allostasis theory and uses a formal representation of a multiscale opponent process. The model simulates smoking behavior of an individual and produces both short-term (“loading up” after not smoking for a while) and long-term smoking patterns (e.g., gradual transition from a few cigarettes to one pack a day). By introducing a formal representation of withdrawal- and craving-like processes, the model produces gradual increases over time in withdrawal- and craving-like signals associated with abstinence and shows that after 3 months of abstinence, craving disappears. The model was programmed as a computer application allowing users to select simulation scenarios. The application links images of brain regions that are activated during the binge/intoxication, withdrawal, or craving with corresponding simulated states. The model was calibrated to represent smoking patterns described in peer-reviewed literature; however, it is generic enough to be adapted to other drugs, including cocaine and opioids. Although the model does not mechanistically describe specific neurobiological processes, it can be useful in prevention and treatment practices as an illustration of drug-using behaviors and expected dynamics of withdrawal and craving during abstinence.
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Friedman, Haya, Julia Vrebalov, and James Giovannoni. Elucidating the ripening signaling pathway in banana for improved fruit quality, shelf-life and food security. United States Department of Agriculture, October 2014. http://dx.doi.org/10.32747/2014.7594401.bard.
Full textAbstract:
Background : Banana being a monocot and having distinct peel and pulp tissues is unique among the fleshy fruits and hence can provide a more comprehensive understanding of fruit ripening. Our previous research which translated ripening discoveries from tomato, led to the identification of six banana fruit-associated MADS-box genes, and we confirmed the positive role of MaMADS1/2 in banana ripening. The overall goal was to further elucidate the banana ripening signaling pathway as mediated by MADS-boxtranscriptional regulators. Specific objectives were: 1) characterize transcriptional profiles and quality of MaMADS1/2 repressed fruit; 2) reveal the role of additional MaMADSgenes in ripening; 3) develop a model of fruit MaMADS-box mode of action; and 4) isolate new components of the banana ripening signaling pathway. Major conclusion: The functions of the banana MaMADS1-5 have been examined by complimenting the rinor the TAGL1-suppressed lines of tomato. Only MaMADS5 exhibited partial complementation of TAGL1-suppressed and rinlines, suggesting that while similar genes play corresponding roles in ripening, evolutionary divergence makes heterologous complementation studies challenging. Nevertheless, the partial complementation of tomato TAGL1-surpessed and rinlines with MaMADS5 suggests this gene is likely an important ripening regulator in banana, worthy of further study. RNA-seqtranscriptome analysis during ripening was performed on WT and MaMADS2-suppressed lines revealing additional candidate genes contributing to ripening control mechanisms. In summary, we discovered 39 MaMADS-box genes in addition to homologues of CNR, NOR and HB-1 expressed in banana fruits, and which were shown in tomato to play necessary roles in ripening. For most of these genes the expression in peel and pulp was similar. However, a number of key genes were differentially expressed between these tissues indicating that the regulatory components which are active in peel and pulp include both common and tissue-specific regulatory systems, a distinction as compared to the more uniform tomato fruit pericarp. Because plant hormones are well documented to affect fruit ripening, the expressions of genes within the auxin, gibberellin, abscisic acid, jasmonic acid, salicylic and ethylene signal transduction and synthesis pathways were targeted in our transcriptome analysis. Genes’ expression associated with these pathways generally declined during normal ripening in both peel and pulp, excluding cytokinin and ethylene, and this decline was delayed in MaMADS2-suppressed banana lines. Hence, we suggest that normal MaMADS2 activity promotes the observed downward expression within these non-ethylene pathways (especially in the pulp), thus enabling ripening progression. In contrast, the expressions of ACSand ACOof the ethylene biosynthesis pathway increase in peel and pulp during ripening and are delayed/inhibited in the transgenic bananas, explaining the reduced ethylene production of MaMADS2-suppressed lines. Inferred by the different genes’ expression in peel and pulp of the gibberellins, salicylic acid and cytokinins pathways, it is suggested that hormonal regulation in these tissues is diverse. These results provide important insights into possible avenues of ripening control in the diverse fruit tissues of banana which was not previously revealed in other ripening systems. As such, our transcriptome analysis of WT and ripening delayed banana mutants provides a starting point for further characterization of ripening. In this study we also developed novel evidence that the cytoskeleton may have a positive role in ripening as components of this pathway were down-regulated by MaMADS2 suppression. The mode of cytoskeleton involvement in fruit ripening remains unclear but presents a novel new frontier in ripening investigations. In summary, this project yielded functional understanding of the role and mode of action of MaMADS2 during ripening, pointing to both induction of ethylene and suppression of non-ethylene hormonal singling pathways. Furthermore, our data suggest important roles for cytoskeleton components and MaMADS5 in the overall banana ripening control network. Implications: The project revealed new molecular components/genes involved in banana ripening and refines our understanding of ripening responses in the peel and pulp tissues of this important species. This information is novel as compared to that derived from the more uniform carpel tissues of other highly studied ripening systems including tomato and grape. The work provides specific target genes for potential modification through genetic engineering or for exploration of useful genetic diversity in traditional breeding. The results from the project might point toward improved methods or new treatments to improve banana fruit storage and quality.
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Meir, Shimon, Michael Reid, Cai-Zhong Jiang, Amnon Lers, and Sonia Philosoph-Hadas. Molecular Studies of Postharvest Leaf and Flower Abscission. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7696523.bard.
Full textAbstract:
Original objectives: Understanding the regulation of abscission competence by exploring the nature and function of auxin-related gene expression changes in the leaf and pedicelAZs of tomato (as a model system), was the main goal of the previously submitted proposal. We proposed to achieve this goal by using microarray GeneChip analysis, to identify potential target genes for functional analysis by virus-induced gene silencing (VIGS). To increase the potential of accomplishing the objectives of the previously submitted proposal, we were asked by BARD to show feasibility for the use of these two modern techniques in our abscission system. Thus, the following new objectives were outlined for the one-year feasibility study: 1.to demonstrate the feasibility of the VIGS system in tomato to perform functional analysis of known abscission-related genes; 2. to demonstrate that by using microarray analysis we can identify target genes for further VIGS functional analysis. Background to the topic: It is a generally accepted model that auxin flux through the abscission zone (AZ) prevents organ abscission by rendering the AZ insensitive to ethylene. However, the molecular mechanisms responsible for acquisition of abscission competence and the way in which the auxin gradient modulates it are still unknown. Understanding this basic stage of the abscission process may provide us with future tools to control abscission for agricultural applications. Based on our previous study, performed to investigate the molecular changes occurring in leaf and stem AZs of MirabillisJalapaL., we have expanded our research to tomato, using genomic approaches that include modern techniques for gene discovery and functional gene characterization. In our one-year feasibility study, the US team has established a useful system for VIGS in tomato, using vectors based on the tobacco rattle virus (TRV), a Lcreporter gene for silencing (involved in regulation of anthocyanin biosynthesis), and the gene of interest. In parallel, the Israeli team has used the newly released Affymetrix Tomato GeneChip to measure gene expression in AZ and non-AZ tissues at various time points after flower removal, when increased sensitivity to ethylene is acquired prior to abscission (at 0-8 h), and during pedicelabscission (at 14 h). In addition, gene expression was measured in the pedicel AZ pretreated with the ethylene action inhibitor, 1-methylcyclopropene (1-MCP) before flower removal, to block any direct effects of ethylene. Major conclusions, solutions and achievements: 1) The feasibility study unequivocally established that VIGS is an ideal tool for testing the function of genes with putative roles in abscission; 2) The newly released Affymetrix Tomato GeneChip was found to be an excellent tool to identify AZ genes possibly involved in regulation and execution of abscission. The VIGS-based study allowed us to show that TAPG, a polygalacturonase specifically associated with the tomato AZ, is a key enzyme in the abscission process. Using the newly released Affymetrix Tomato GeneChip we have identified potential abscission regulatory genes as well as new AZ-specific genes, the expression of which was modified after flower removal. These include: members of the Aux/IAAgene family, ethylene signal transduction-related genes, early and late expressed transcription factors, genes which encode post-translational regulators whose expression was modified specifically in the AZ, and many additional novel AZ-specific genes which were previously not associated with abscission. This microarray analysis allowed us to select an initial set of target genes for further functional analysis by VIGS. Implications: Our success in achieving the two objectives of this feasibility study provides us with a solid basis for further research outlined in the original proposal. This will significantly increase the probability of success of a full 3-year project. Additionally, our feasibility study yielded highly innovative results, as they represent the first direct demonstration of the functional involvement of a TAPG in abscission, and the first microarray analysis of the abscission process. Using these approaches we could identify a large number of genes involved in abscission regulation, initiation and execution, and in auxin-ethylene cross-talk, which are of great importance, and could enable their potential functional analysis by VIGS.
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Hefetz, Abraham, and Justin O. Schmidt. Use of Bee-Borne Attractants for Pollination of Nonrewarding Flowers: Model System of Male-Sterile Tomato Flowers. United States Department of Agriculture, October 2003. http://dx.doi.org/10.32747/2003.7586462.bard.
Full textAbstract:
The use of bee natural product for enhancing pollination is especially valuable in problematic crops that are generally avoided by bees. In the present research we attempted to enhance bee visitation to Male Sterile (M-S) tomato flowers generally used in the production of hybrid seeds. These flowers that lack both pollen and nectar are unattractive to bees that learn rapidly to avoid them. The specific objects were to elucidate the chemical composition of the exocrine products of two bumble bee species the North American Bombus impatiens and the Israeli B. terrestris. Of these, to isolate and identify a bee attractant which when sprayed on M-S tomato flowers will enhance bee visitation, and to provide a procedure of the pheromone application regime. During the research we realized that our knowledge of B. impatiens is too little and we narrowed the objective to learning the basic social behavior of the bees and the pattern of foraging in a flight chamber and how it is affected by biogenic amines. Colonies of B. impatiens are characterized by a high number of workers and a relatively small number of queens. Size differences between queens and workers are pronounced and the queen seems to have full control over egg laying. Only about 9% of the workers in mature colonies had mature oocytes, and there were no signs of a "competition phase" as we know in B. terrestris. Queens and workers differ in their exocrine bouquet. Queen's Dufour's gland possesses a series of linear, saturated and unsaturated hydrocarbons whereas that of workers contains in addition a series of wax-type esters. Bees were trained to either visit or avoid artificially scented electronic flowers in a flight chamber. Since bee also learned to avoid scented non-rewarding flowers we attempted to interfere with this learning. We tested the effect of octopamine, a biogenic amine affecting bee behavior, on the choice behavior of free-flying bumblebees. Our results show that octopamine had no significant effect on the bees' equilibrium choice or on the overall rate of the behavioral change in response to the change in reward. Rather, octopamine significantly affected the time interval between the change in reward status and the initiation of behavioral change in the bee. In B. terrestris we studied the foraging pattern of the bees on tomato flowers in a semi commercial greenhouse in Yad Mordechai. Bee learned very quickly to avoid the non- rewarding M-S flowers, irrespective of their arrangement in the plot, i.e., their mixing with normal, pollen bearing flowers. However, bees seem to "forget" this information during the night since the foraging pattern repeats itself the next morning. Several exocrine products were tested as visitation enhancers. Among these, tarsal gland extracts are the most attractive. The compounds identified in the tarsal gland extract are mostly linear saturated hydrocarbons with small amounts of unsaturated ones. Application was performed every second day on leaves in selected inflorescences. Bee visitation increased significantly in the treated inflorescences as compared to the control, solvent treated. Treatment of the anthers cone was more effective than on the flower petals or the surrounding leaves. Methanol proved to be a non-flower-destructive solvent. We have shown that bumble bees (B. terrestris) can be manipulated by bee-borne attractants to visit non-rewarding flowers. We have further demonstrated that the bees learning ability can be manipulated by applying exogenously octopamine. Both methods can be additively applied in enhancing pollination of desired crops. Such manipulation will be especially useful in tomato cultivation for hybrid seed production.