Preface to the special issue on "Integrated Microwave Photonic Signal Processing"
NASA Astrophysics Data System (ADS)
Azaña, José; Yao, Jianping
2016-08-01
As Guest Editors, we are pleased to introduce this special issue on ;Integrated Microwave Photonic Signal Processing; published by the Elsevier journal Optics Communications. Microwave photonics is a field of growing importance from both scientific and practical application perspectives. The field of microwave photonics is devoted to the study, development and application of optics-based techniques and technologies aimed to the generation, processing, control, characterization and/or distribution of microwave signals, including signals well into the millimeter-wave frequency range. The use of photonic technologies for these microwave applications translates into a number of key advantages, such as the possibility of dealing with high-frequency, wide bandwidth signals with minimal losses and reduced electromagnetic interferences, and the potential for enhanced reconfigurability. The central purpose of this special issue is to provide an overview of the state of the art of generation, processing and characterization technologies for high-frequency microwave signals. It is now widely accepted that the practical success of microwave photonics at a large scale will essentially depend on the realization of high-performance microwave-photonic signal-processing engines in compact and integrated formats, preferably on a chip. Thus, the focus of the issue is on techniques implemented using integrated photonic technologies, with the goal of providing an update of the most recent advances toward realization of this vision.
Poplová, Michaela; Sovka, Pavel; Cifra, Michal
2017-01-01
Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.
Poplová, Michaela; Sovka, Pavel
2017-01-01
Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207
Overcoming low-alignment signal contrast induced alignment failure by alignment signal enhancement
NASA Astrophysics Data System (ADS)
Lee, Byeong Soo; Kim, Young Ha; Hwang, Hyunwoo; Lee, Jeongjin; Kong, Jeong Heung; Kang, Young Seog; Paarhuis, Bart; Kok, Haico; de Graaf, Roelof; Weichselbaum, Stefan; Droste, Richard; Mason, Christopher; Aarts, Igor; de Boeij, Wim P.
2016-03-01
Overlay is one of the key factors which enables optical lithography extension to 1X node DRAM manufacturing. It is natural that accurate wafer alignment is a prerequisite for good device overlay. However, alignment failures or misalignments are commonly observed in a fab. There are many factors which could induce alignment problems. Low alignment signal contrast is one of the main issues. Alignment signal contrast can be degraded by opaque stack materials or by alignment mark degradation due to processes like CMP. This issue can be compounded by mark sub-segmentation from design rules in combination with double or quadruple spacer process. Alignment signal contrast can be improved by applying new material or process optimization, which sometimes lead to the addition of another process-step with higher costs. If we can amplify the signal components containing the position information and reduce other unwanted signal and background contributions then we can improve alignment performance without process change. In this paper we use ASML's new alignment sensor (as was introduced and released on the NXT:1980Di) and sample wafers with special stacks which can induce poor alignment signal to demonstrate alignment and overlay improvement.
Hernandez, Wilmar
2007-01-01
In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.
Jan, Shau-Shiun; Sun, Chih-Cheng
2010-01-01
The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.
Implantable electronics: emerging design issues and an ultra light-weight security solution.
Narasimhan, Seetharam; Wang, Xinmu; Bhunia, Swarup
2010-01-01
Implantable systems that monitor biological signals require increasingly complex digital signal processing (DSP) electronics for real-time in-situ analysis and compression of the recorded signals. While it is well-known that such signal processing hardware needs to be implemented under tight area and power constraints, new design requirements emerge with their increasing complexity. Use of nanoscale technology shows tremendous benefits in implementing these advanced circuits due to dramatic improvement in integration density and power dissipation per operation. However, it also brings in new challenges such as reliability and large idle power (due to higher leakage current). Besides, programmability of the device as well as security of the recorded information are rapidly becoming major design considerations of such systems. In this paper, we analyze the emerging issues associated with the design of the DSP unit in an implantable system. Next, we propose a novel ultra light-weight solution to address the information security issue. Unlike the conventional information security approaches like data encryption, which come at large area and power overhead and hence are not amenable for resource-constrained implantable systems, we propose a multilevel key-based scrambling algorithm, which exploits the nature of the biological signal to effectively obfuscate it. Analysis of the proposed algorithm in the context of neural signal processing and its hardware implementation shows that we can achieve high level of security with ∼ 13X lower power and ∼ 5X lower area overhead than conventional cryptographic solutions.
NASA Astrophysics Data System (ADS)
Lebiedz, Dirk; Brandt-Pollmann, Ulrich
2004-09-01
Specific external control of chemical reaction systems and both dynamic control and signal processing as central functions in biochemical reaction systems are important issues of modern nonlinear science. For example nonlinear input-output behavior and its regulation are crucial for the maintainance of the life process that requires extensive communication between cells and their environment. An important question is how the dynamical behavior of biochemical systems is controlled and how they process information transmitted by incoming signals. But also from a general point of view external forcing of complex chemical reaction processes is important in many application areas ranging from chemical engineering to biomedicine. In order to study such control issues numerically, here, we choose a well characterized chemical system, the CO oxidation on Pt(110), which is interesting per se as an externally forced chemical oscillator model. We show numerically that tuning of temporal self-organization by input signals in this simple nonlinear chemical reaction exhibiting oscillatory behavior can in principle be exploited for both specific external control of dynamical system behavior and processing of complex information.
Signal processing: opportunities for superconductive circuits
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ralston, R.W.
1985-03-01
Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data-processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described and examplesmore » of superconductive implementations given. A canonic signal-processing system is then configured using these components and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. (Reprints)« less
NASA Astrophysics Data System (ADS)
Blok, A. S.; Bukhenskii, A. F.; Krupitskii, É. I.; Morozov, S. V.; Pelevin, V. Yu; Sergeenko, T. N.; Yakovlev, V. I.
1995-10-01
An investigation is reported of acousto-optical and fibre-optic Fourier processors of electric signals, based on semiconductor lasers. A description is given of practical acousto-optical processors with an analysis band 120 MHz wide, a resolution of 200 kHz, and 7 cm × 8 cm × 18 cm dimensions. Fibre-optic Fourier processors are considered: they represent a new class of devices which are promising for the processing of gigahertz signals.
Decoding Signal Processing at the Single-Cell Level
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiley, H. Steven
The ability of cells to detect and decode information about their extracellular environment is critical to generating an appropriate response. In multicellular organisms, cells must decode dozens of signals from their neighbors and extracellular matrix to maintain tissue homeostasis while still responding to environmental stressors. How cells detect and process information from their surroundings through a surprisingly limited number of signal transduction pathways is one of the most important question in biology. Despite many decades of research, many of the fundamental principles that underlie cell signal processing remain obscure. However, in this issue of Cell Systems, Gillies et al presentmore » compelling evidence that the early response gene circuit can act as a linear signal integrator, thus providing significant insight into how cells handle fluctuating signals and noise in their environment.« less
NEET In-Pile Ultrasonic Sensor Enablement-Final Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
J. Daw; J. Rempe; J. Palmer
2014-09-01
Ultrasonic technologies offer the potential to measure a range of parameters during irradiation of fuels and materials, including geometry changes, temperature, crack initiation and growth, gas pressure and composition, and microstructural changes under harsh irradiation test conditions. There are two primary issues that currently limit in-pile deployment of ultrasonic sensors. The first is transducer survivability. The ability of ultrasonic transducer materials to maintain their useful properties during an irradiation must be demonstrated. The second issue is signal processing. Ultrasonic testing is typically performed in a lab or field environment, where the sensor and sample are accessible. The harsh nature ofmore » in-pile testing and the variety of desired measurements demand that an enhanced signal processing capability be developed to make in-pile ultrasonic sensors viable. To address these issues, the NEET ASI program funded a three year Ultrasonic Transducer Irradiation and Signal Processing Enhancements project, which is a collaborative effort between the Idaho National Laboratory, the Pacific Northwest National Laboratory, the Argonne National Laboratory, and the Pennsylvania State University. The objective of this report is to document the objectives and accomplishments from this three year project. As summarized within this document, significant work has been accomplished during this three year project.« less
NASA Astrophysics Data System (ADS)
Kiyashko, B. V.
1995-10-01
Partially coherent optical systems for signal processing are considered. The transfer functions are formed in these systems by interference of polarised light transmitted by an anisotropic medium. It is shown that such systems can perform various integral transformations of both optical and electric signals, in particular, two-dimensional Fourier and Fresnel transformations, as well as spectral analysis of weak light sources. It is demonstrated that such systems have the highest luminosity and vibration immunity among the systems with interference formation of transfer functions. An experimental investigation is reported of the application of these systems in the processing of signals from a linear hydroacoustic antenna array, and in measurements of the optical spectrum and of the intrinsic noise.
Surface Electromyography Signal Processing and Classification Techniques
Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.
2013-01-01
Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:24048337
A review of signals used in sleep analysis
Roebuck, A; Monasterio, V; Gederi, E; Osipov, M; Behar, J; Malhotra, A; Penzel, T; Clifford, GD
2014-01-01
This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep. PMID:24346125
Signal processing: opportunities for superconductive circuits
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ralston, R.W.
1985-03-01
Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described andmore » examples of superconductive implementations given. A canonic signal-processing system is then configured using these components in combination with analog/digital converters and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. Superconductive circuits hold promise for processing signals of 10-GHz bandwidth. Signal processing systems, however, can be properly designed and implemented only through a synergistic combination of the talents of device physicists, circuit designers, algorithm architects and system engineers. An immediate challenge to the applied superconductivity community is to begin sharing ideas with these other researchers.« less
Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy
NASA Astrophysics Data System (ADS)
Price, D. C.; Kocz, J.; Bailes, M.; Greenhill, L. J.
2016-03-01
Advances in astronomy are intimately linked to advances in digital signal processing (DSP). This special issue is focused upon advances in DSP within radio astronomy. The trend within that community is to use off-the-shelf digital hardware where possible and leverage advances in high performance computing. In particular, graphics processing units (GPUs) and field programmable gate arrays (FPGAs) are being used in place of application-specific circuits (ASICs); high-speed Ethernet and Infiniband are being used for interconnect in place of custom backplanes. Further, to lower hurdles in digital engineering, communities have designed and released general-purpose FPGA-based DSP systems, such as the CASPER ROACH board, ASTRON Uniboard, and CSIRO Redback board. In this introductory paper, we give a brief historical overview, a summary of recent trends, and provide an outlook on future directions.
Instructive microenvironments in skin wound healing: Biomaterials as signal releasing platforms.
Castaño, Oscar; Pérez-Amodio, Soledad; Navarro-Requena, Claudia; Mateos-Timoneda, Miguel Ángel; Engel, Elisabeth
2018-04-05
Skin wound healing aims to repair and restore tissue through a multistage process that involves different cells and signalling molecules that regulate the cellular response and the dynamic remodelling of the extracellular matrix. Nowadays, several therapies that combine biomolecule signals (growth factors and cytokines) and cells are being proposed. However, a lack of reliable evidence of their efficacy, together with associated issues such as high costs, a lack of standardization, no scalable processes, and storage and regulatory issues, are hampering their application. In situ tissue regeneration appears to be a feasible strategy that uses the body's own capacity for regeneration by mobilizing host endogenous stem cells or tissue-specific progenitor cells to the wound site to promote repair and regeneration. The aim is to engineer instructive systems to regulate the spatio-temporal delivery of proper signalling based on the biological mechanisms of the different events that occur in the host microenvironment. This review describes the current state of the different signal cues used in wound healing and skin regeneration, and their combination with biomaterial supports to create instructive microenvironments for wound healing. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Pilipovich, V. A.; Esman, A. K.; Goncharenko, I. A.; Posed'ko, V. S.; Solonovich, I. F.
1995-10-01
A method for increasing the information capacity and enhancing the reliability of information storage in a dynamic fibre-optic memory is proposed. An additional built-in channel with counterpropagating circulation of signals is provided for this purpose. This additional channel can be used to transmit both information and service signals, such as address words, clock signals, correcting sequences, etc. The possibility of compensating the attenuation of an information signal by stimulated Raman scattering is considered.
Selection signature in domesticated animals.
Pan, Zhang-yuan; He, Xiao-yun; Wang, Xiang-yu; Guo, Xiao-fei; Cao, Xiao-han; Hu, Wen-ping; Di, Ran; Liu, Qiu-yue; Chu, Ming-xing
2016-12-20
Domesticated animals play an important role in the life of humanity. All these domesticated animals undergo same process, first domesticated from wild animals, then after long time natural and artificial selection, formed various breeds that adapted to the local environment and human needs. In this process, domestication, natural and artificial selection will leave the selection signal in the genome. The research on these selection signals can find functional genes directly, is one of the most important strategies in screening functional genes. The current studies of selection signal have been performed in pigs, chickens, cattle, sheep, goats, dogs and other domestic animals, and found a great deal of functional genes. This paper provided an overview of the types and the detected methods of selection signal, and outlined researches of selection signal in domestic animals, and discussed the key issues in selection signal analysis and its prospects.
Sparse signal representation and its applications in ultrasonic NDE.
Zhang, Guang-Ming; Zhang, Cheng-Zhong; Harvey, David M
2012-03-01
Many sparse signal representation (SSR) algorithms have been developed in the past decade. The advantages of SSR such as compact representations and super resolution lead to the state of the art performance of SSR for processing ultrasonic non-destructive evaluation (NDE) signals. Choosing a suitable SSR algorithm and designing an appropriate overcomplete dictionary is a key for success. After a brief review of sparse signal representation methods and the design of overcomplete dictionaries, this paper addresses the recent accomplishments of SSR for processing ultrasonic NDE signals. The advantages and limitations of SSR algorithms and various overcomplete dictionaries widely-used in ultrasonic NDE applications are explored in depth. Their performance improvement compared to conventional signal processing methods in many applications such as ultrasonic flaw detection and noise suppression, echo separation and echo estimation, and ultrasonic imaging is investigated. The challenging issues met in practical ultrasonic NDE applications for example the design of a good dictionary are discussed. Representative experimental results are presented for demonstration. Copyright © 2011 Elsevier B.V. All rights reserved.
Working group organizational meeting
NASA Technical Reports Server (NTRS)
1982-01-01
Scene radiation and atmospheric effects, mathematical pattern recognition and image analysis, information evaluation and utilization, and electromagnetic measurements and signal handling are considered. Research issues in sensors and signals, including radar (SAR) reflectometry, SAR processing speed, registration, including overlay of SAR and optical imagery, entire system radiance calibration, and lack of requirements for both sensors and systems, etc. were discussed.
Redox and Nitric Oxide-Mediated Regulation of Sensory Neuron Ion Channel Function
2015-01-01
Abstract Significance: Reactive oxygen and nitrogen species (ROS and RNS, respectively) can intimately control neuronal excitability and synaptic strength by regulating the function of many ion channels. In peripheral sensory neurons, such regulation contributes towards the control of somatosensory processing; therefore, understanding the mechanisms of such regulation is necessary for the development of new therapeutic strategies and for the treatment of sensory dysfunctions, such as chronic pain. Recent Advances: Tremendous progress in deciphering nitric oxide (NO) and ROS signaling in the nervous system has been made in recent decades. This includes the recognition of these molecules as important second messengers and the elucidation of their metabolic pathways and cellular targets. Mounting evidence suggests that these targets include many ion channels which can be directly or indirectly modulated by ROS and NO. However, the mechanisms specific to sensory neurons are still poorly understood. This review will therefore summarize recent findings that highlight the complex nature of the signaling pathways involved in redox/NO regulation of sensory neuron ion channels and excitability; references to redox mechanisms described in other neuron types will be made where necessary. Critical Issues: The complexity and interplay within the redox, NO, and other gasotransmitter modulation of protein function are still largely unresolved. Issues of specificity and intracellular localization of these signaling cascades will also be addressed. Future Directions: Since our understanding of ROS and RNS signaling in sensory neurons is limited, there is a multitude of future directions; one of the most important issues for further study is the establishment of the exact roles that these signaling pathways play in pain processing and the translation of this understanding into new therapeutics. Antioxid. Redox Signal. 22, 486–504. PMID:24735331
Endocannabinoid signalling: has it got rhythm?
Vaughn, Linda K; Denning, Gerene; Stuhr, Kara L; de Wit, Harriet; Hill, Matthew N; Hillard, Cecilia J
2010-01-01
Endogenous cannabinoid signalling is widespread throughout the body, and considerable evidence supports its modulatory role in many fundamental physiological processes. The daily and seasonal cycles of the relationship of the earth and sun profoundly affect the terrestrial environment. Terrestrial species have adapted to these cycles in many ways, most well studied are circadian rhythms and hibernation. The purpose of this review was to examine literature support for three hypotheses: (i) endocannabinoid signalling exhibits brain region-specific circadian rhythms; (ii) endocannabinoid signalling modulates the rhythm of circadian processes in mammals; and (iii) changes in endocannabinoid signalling contribute to the state of hibernation. The results of two novel studies are presented. First, we report the results of a study of healthy humans demonstrating that plasma concentrations of the endocannabinoid, N-arachidonylethanolamine (anandamide), exhibit a circadian rhythm. Concentrations of anandamide are threefold higher at wakening than immediately before sleep, a relationship that is dysregulated by sleep deprivation. Second, we investigated differences in endocannabinoids and congeners in plasma from Marmota monax obtained in the summer and during the torpor state of hibernation. We report that 2-arachidonoylglycerol is below detection in M. monax plasma and that concentrations of anandamide are not different. However, plasma concentrations of the anorexigenic lipid oleoylethanolamide were significantly lower in hibernation, while the concentrations of palmitoylethanolamide and 2-oleoylglycerol were significantly greater in hibernation. We conclude that available data support a bidirectional relationship between endocannabinoid signalling and circadian processes, and investigation of the contribution of endocannabinoid signalling to the dramatic physiological changes that occur during hibernation is warranted. This article is part of a themed issue on Cannabinoids. To view the editorial for this themed issue visit http://dx.doi.org/10.1111/j.1476-5381.2010.00831.x PMID:20590563
Huang, Wentao; Sun, Hongjian; Wang, Weijie
2017-06-03
Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD's theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis.
Huang, Wentao; Sun, Hongjian; Wang, Weijie
2017-01-01
Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD’s theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis. PMID:28587198
NASA Astrophysics Data System (ADS)
Jia, Feng; Lei, Yaguo; Lin, Jing; Zhou, Xin; Lu, Na
2016-05-01
Aiming to promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rotating machinery. Among these studies, the methods based on artificial neural networks (ANNs) are commonly used, which employ signal processing techniques for extracting features and further input the features to ANNs for classifying faults. Though these methods did work in intelligent fault diagnosis of rotating machinery, they still have two deficiencies. (1) The features are manually extracted depending on much prior knowledge about signal processing techniques and diagnostic expertise. In addition, these manual features are extracted according to a specific diagnosis issue and probably unsuitable for other issues. (2) The ANNs adopted in these methods have shallow architectures, which limits the capacity of ANNs to learn the complex non-linear relationships in fault diagnosis issues. As a breakthrough in artificial intelligence, deep learning holds the potential to overcome the aforementioned deficiencies. Through deep learning, deep neural networks (DNNs) with deep architectures, instead of shallow ones, could be established to mine the useful information from raw data and approximate complex non-linear functions. Based on DNNs, a novel intelligent method is proposed in this paper to overcome the deficiencies of the aforementioned intelligent diagnosis methods. The effectiveness of the proposed method is validated using datasets from rolling element bearings and planetary gearboxes. These datasets contain massive measured signals involving different health conditions under various operating conditions. The diagnosis results show that the proposed method is able to not only adaptively mine available fault characteristics from the measured signals, but also obtain superior diagnosis accuracy compared with the existing methods.
Focus issue: teaching tools and learning opportunities.
Gough, Nancy R
2010-04-27
Science Signaling provides authoring experience for students and resources for educators. Students experience the writing and revision process involved in authoring short commentary articles that are published in the Journal Club section. By publishing peer-reviewed teaching materials, Science Signaling provides instructors with feedback that improves their materials and an outlet to share their tips and techniques and digital resources with other teachers.
Effects of Tasks on BOLD Signal Responses to Sentence Contrasts: Review and Commentary
ERIC Educational Resources Information Center
Caplan, David; Gow, David
2012-01-01
Functional neuroimaging studies of syntactic processing have been interpreted as identifying the neural locations of parsing and interpretive operations. However, current behavioral studies of sentence processing indicate that many operations occur simultaneously with parsing and interpretation. In this review, we point to issues that arise in…
Acousto-Optic Processing of 2-D Signals Using Temporal and Spatial Integration.
1983-05-31
Documents includes data on: Architectures; Coherence Properties of Pulsed Laser Diodes; Acousto - optic device data; Dynamic Range Issues; Image correlation; Synthetic aperture radar; 2-D Fourier transform; and Moments.
Non-Invasive UWB Sensing of Astronauts' Breathing Activity
Baldi, Marco; Cerri, Graziano; Chiaraluce, Franco; Eusebi, Lorenzo; Russo, Paola
2015-01-01
The use of a UWB system for sensing breathing activity of astronauts must account for many critical issues specific to the space environment. The aim of this paper is twofold. The first concerns the definition of design constraints about the pulse amplitude and waveform to transmit, as well as the immunity requirements of the receiver. The second issue concerns the assessment of the procedures and the characteristics of the algorithms to use for signal processing to retrieve the breathing frequency and respiration waveform. The algorithm has to work correctly in the presence of surrounding electromagnetic noise due to other sources in the environment. The highly reflecting walls increase the difficulty of the problem and the hostile scenario has to be accurately characterized. Examples of signal processing techniques able to recover breathing frequency in significant and realistic situations are shown and discussed. PMID:25558995
Biomedical signal and image processing.
Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro
2011-01-01
Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.
NASA Astrophysics Data System (ADS)
Asgari, Shadnaz
Recent developments in the integrated circuits and wireless communications not only open up many possibilities but also introduce challenging issues for the collaborative processing of signals for source localization and beamforming in an energy-constrained distributed sensor network. In signal processing, various sensor array processing algorithms and concepts have been adopted, but must be further tailored to match the communication and computational constraints. Sometimes the constraints are such that none of the existing algorithms would be an efficient option for the defined problem and as the result; the necessity of developing a new algorithm becomes undeniable. In this dissertation, we present the theoretical and the practical issues of Direction-Of-Arrival (DOA) estimation and source localization using the Approximate-Maximum-Likelihood (AML) algorithm for different scenarios. We first investigate a robust algorithm design for coherent source DOA estimation in a limited reverberant environment. Then, we provide a least-square (LS) solution for source localization based on our newly proposed virtual array model. In another scenario, we consider the determination of the location of a disturbance source which emits both wideband acoustic and seismic signals. We devise an enhanced AML algorithm to process the data collected at the acoustic sensors. For processing the seismic signals, two distinct algorithms are investigated to determine the DOAs. Then, we consider a basic algorithm for fusion of the results yielded by the acoustic and seismic arrays. We also investigate the theoretical and practical issues of DOA estimation in a three-dimensional (3D) scenario. We show that the performance of the proposed 3D AML algorithm converges to the Cramer-Rao Bound. We use the concept of an isotropic array to reduce the complexity of the proposed algorithm by advocating a decoupled 3D version. We also explore a modified version of the decoupled 3D AML algorithm which can be used for DOA estimation with non-isotropic arrays. In this dissertation, for each scenario, efficient numerical implementations of the corresponding AML algorithm are derived and applied into a real-time sensor network testbed. Extensive simulations as well as experimental results are presented to verify the effectiveness of the proposed algorithms.
Models and signal processing for an implanted ethanol bio-sensor.
Han, Jae-Joon; Doerschuk, Peter C; Gelfand, Saul B; O'Connor, Sean J
2008-02-01
The understanding of drinking patterns leading to alcoholism has been hindered by an inability to unobtrusively measure ethanol consumption over periods of weeks to months in the community environment. An implantable ethanol sensor is under development using microelectromechanical systems technology. For safety and user acceptability issues, the sensor will be implanted subcutaneously and, therefore, measure peripheral-tissue ethanol concentration. Determining ethanol consumption and kinetics in other compartments from the time course of peripheral-tissue ethanol concentration requires sophisticated signal processing based on detailed descriptions of the relevant physiology. A statistical signal processing system based on detailed models of the physiology and using extended Kalman filtering and dynamic programming tools is described which can estimate the time series of ethanol concentration in blood, liver, and peripheral tissue and the time series of ethanol consumption based on peripheral-tissue ethanol concentration measurements.
Identification of significant intrinsic mode functions for the diagnosis of induction motor fault.
Cho, Sangjin; Shahriar, Md Rifat; Chong, Uipil
2014-08-01
For the analysis of non-stationary signals generated by a non-linear process like fault of an induction motor, empirical mode decomposition (EMD) is the best choice as it decomposes the signal into its natural oscillatory modes known as intrinsic mode functions (IMFs). However, some of these oscillatory modes obtained from a fault signal are not significant as they do not bear any fault signature and can cause misclassification of the fault instance. To solve this issue, a novel IMF selection algorithm is proposed in this work.
Digital pulse shape discrimination.
Miller, L F; Preston, J; Pozzi, S; Flaska, M; Neal, J
2007-01-01
Pulse-shape discrimination (PSD) has been utilised for about 40 years as a method to obtain estimates for dose in mixed neutron and photon fields. Digitizers that operate close to GHz are currently available at a reasonable cost, and they can be used to directly sample signals from photomultiplier tubes. This permits one to perform digital PSD rather than the traditional, and well-established, analogoue techniques. One issue that complicates PSD for neutrons in mixed fields is that the light output characteristics of typical scintillators available for PSD, such as BC501A, vary as a function of energy deposited in the detector. This behaviour is more easily accommodated with digital processing of signals than with analogoue signal processing. Results illustrate the effectiveness of digital PSD.
NASA Astrophysics Data System (ADS)
Li, H.; Plink-Bjorklund, P.
2017-12-01
Studies (e.g., Jerolmack and Paola, 2010) have suggested that autogenic processes act as a filter for high-frequency environmental signals, and the underlying assumption is that autogenic processes can cause fluctuations in sediment and water discharge that modify or shred the signal. This assumption, however, fails to recognize that autogenic processes and their final products are dynamic and that they can respond to allogenic forcings. We compile a database containing published field studies, physical experiments, and numerical modeling works, and analyze the data under different boundary conditions. Our analyses suggest different conclusions. Autogenic processes are intrinsic to the sedimentary system, and they possess distinct patterns under steady boundary conditions. Upon changing boundary conditions, the autogenic patterns are also likely to change (depending on the magnitude of the change in the boundary conditions). Therefore, the pattern change provides us with the opportunity to restore the high-frequency signals that may not pass through the transfer zone. Here we present the theoretical basis for using autogenic deposits to infer high-frequency signals as well as modern and ancient field examples, physical experiments, and modeling works to illustrate the autogenic response to allogenic forcings. The field studies show the potential of using autogenic deposits to restore short-term climatic variability. The experiments demonstrate that autogenic processes in rivers are closely linked to sediment and water discharge. The modeling examples reveal the counteracting effects of some autogenic processes to form a self-organized pattern under a set of specific boundary conditions. We also highlight the limitations and challenges that need more research efforts to restore high-frequency signals. Some critical issues include the magnitude of the signals, the effect of the interference between different signals, and the incompleteness of the autogenic deposits.
Task effects on BOLD signal correlates of implicit syntactic processing
Caplan, David
2010-01-01
BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983
Task effects on BOLD signal correlates of implicit syntactic processing.
Caplan, David
2010-07-01
BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed.
Pfeifer, Mischa D; Scholkmann, Felix; Labruyère, Rob
2017-01-01
Even though research in the field of functional near-infrared spectroscopy (fNIRS) has been performed for more than 20 years, consensus on signal processing methods is still lacking. A significant knowledge gap exists between established researchers and those entering the field. One major issue regularly observed in publications from researchers new to the field is the failure to consider possible signal contamination by hemodynamic changes unrelated to neurovascular coupling (i.e., scalp blood flow and systemic blood flow). This might be due to the fact that these researchers use the signal processing methods provided by the manufacturers of their measurement device without an advanced understanding of the performed steps. The aim of the present study was to investigate how different signal processing approaches (including and excluding approaches that partially correct for the possible signal contamination) affect the results of a typical functional neuroimaging study performed with fNIRS. In particular, we evaluated one standard signal processing method provided by a commercial company and compared it to three customized approaches. We thereby investigated the influence of the chosen method on the statistical outcome of a clinical data set (task-evoked motor cortex activity). No short-channels were used in the present study and therefore two types of multi-channel corrections based on multiple long-channels were applied. The choice of the signal processing method had a considerable influence on the outcome of the study. While methods that ignored the contamination of the fNIRS signals by task-evoked physiological noise yielded several significant hemodynamic responses over the whole head, the statistical significance of these findings disappeared when accounting for part of the contamination using a multi-channel regression. We conclude that adopting signal processing methods that correct for physiological confounding effects might yield more realistic results in cases where multi-distance measurements are not possible. Furthermore, we recommend using manufacturers' standard signal processing methods only in case the user has an advanced understanding of every signal processing step performed.
Properties of a center/surround retinex. Part 1: Signal processing design
NASA Technical Reports Server (NTRS)
Rahaman, Zia-Ur
1995-01-01
The last version of Edwin Land's retinex model for human vision's lightness and color constancy has been implemented. Previous research has established the mathematical foundations of Land's retinex but has not examined specific design issues and their effects on the properties of the retinex operation. Here we describe the signal processing design of the retinex. We find that the placement of the logarithmic function is important and produces best results when placed after the surround formation. We also find that best rendition is obtained for a 'canonical' gain-offset applied after the retinex operation.
Durantin, Gautier; Scannella, Sébastien; Gateau, Thibault; Delorme, Arnaud; Dehais, Frédéric
2015-01-01
Working memory (WM) is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor WM as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering, and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces (BCI). We used functional near infrared spectroscopy as it has been already successfully tested to measure WM capacity in complex environment with air traffic controllers (ATC), pilots, or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with nine participants involving a basic WM task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with ATC instructions (two levels of difficulty). The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence (MACD) filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in WM. In addition, the use of a Kalman filter increased the performance of the classification of WM levels based on brain signal. The results suggest that Kalman filter is a suitable approach for real-time improvement of near infrared spectroscopy signal in ecological situations and the development of BCI.
Durantin, Gautier; Scannella, Sébastien; Gateau, Thibault; Delorme, Arnaud; Dehais, Frédéric
2016-01-01
Working memory (WM) is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor WM as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering, and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces (BCI). We used functional near infrared spectroscopy as it has been already successfully tested to measure WM capacity in complex environment with air traffic controllers (ATC), pilots, or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with nine participants involving a basic WM task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with ATC instructions (two levels of difficulty). The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence (MACD) filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in WM. In addition, the use of a Kalman filter increased the performance of the classification of WM levels based on brain signal. The results suggest that Kalman filter is a suitable approach for real-time improvement of near infrared spectroscopy signal in ecological situations and the development of BCI. PMID:26834607
Report of the sensor readout electronics panel
NASA Technical Reports Server (NTRS)
Fossum, Eric R.; Carson, J.; Kleinhans, W.; Kosonocky, W.; Kozlowski, L.; Pecsalski, A.; Silver, A.; Spieler, H.; Woolaway, J.
1991-01-01
The findings of the Sensor Readout Electronics Panel are summarized in regard to technology assessment and recommended development plans. In addition to two specific readout issues, cryogenic readouts and sub-electron noise, the panel considered three advanced technology areas that impact the ability to achieve large format sensor arrays. These are mega-pixel focal plane packaging issues, focal plane to data processing module interfaces, and event driven readout architectures. Development in each of these five areas was judged to have significant impact in enabling the sensor performance desired for the Astrotech 21 mission set. Other readout issues, such as focal plane signal processing or other high volume data acquisition applications important for Eos-type mapping, were determined not to be relevant for astrophysics science goals.
Aquaporin-facilitated transmembrane diffusion of hydrogen peroxide.
Bienert, Gerd P; Chaumont, François
2014-05-01
Hydrogen peroxide (H2O2) is an important signaling compound that has recently been identified as a new substrate for several members of the aquaporin superfamily in various organisms. Evidence is emerging about the physiological significance of aquaporin-facilitated H2O2 diffusion. This review summarizes current knowledge about aquaporin-facilitated H2O2 diffusion across cellular membranes. It focuses on physicochemical and experimental evidence demonstrating the involvement of aquaporins in the transport of this redox signaling compound and discusses the regulation and structural prerequisites of these channels to transmit this signal. It also provides perspectives about the potential importance of aquaporin-facilitated H2O2 diffusion processes and places this knowledge in the context of the current understanding of transmembrane redox signaling processes. Specific aquaporin isoforms facilitate the passive diffusion of H2O2 across biological membranes and control H2O2 membrane permeability and signaling in living organisms. Redox signaling is a very important process regulating the physiology of cells and organisms in a similar way to the well-characterized hormonal and calcium signaling pathways. Efficient transmembrane diffusion of H2O2, a key molecule in the redox signaling network, requires aquaporins and makes these channels important players in this signaling process. Channel-mediated membrane transport allows the fine adjustment of H2O2 levels in the cytoplasm, intracellular organelles, the apoplast, and the extracellular space, which are essential for it to function as a signal molecule. This article is part of a Special Issue entitled Aquaporins. © 2013.
MEMD-enhanced multivariate fuzzy entropy for the evaluation of complexity in biomedical signals.
Azami, Hamed; Smith, Keith; Escudero, Javier
2016-08-01
Multivariate multiscale entropy (mvMSE) has been proposed as a combination of the coarse-graining process and multivariate sample entropy (mvSE) to quantify the irregularity of multivariate signals. However, both the coarse-graining process and mvSE may not be reliable for short signals. Although the coarse-graining process can be replaced with multivariate empirical mode decomposition (MEMD), the relative instability of mvSE for short signals remains a problem. Here, we address this issue by proposing the multivariate fuzzy entropy (mvFE) with a new fuzzy membership function. The results using white Gaussian noise show that the mvFE leads to more reliable and stable results, especially for short signals, in comparison with mvSE. Accordingly, we propose MEMD-enhanced mvFE to quantify the complexity of signals. The characteristics of brain regions influenced by partial epilepsy are investigated by focal and non-focal electroencephalogram (EEG) time series. In this sense, the proposed MEMD-enhanced mvFE and mvSE are employed to discriminate focal EEG signals from non-focal ones. The results demonstrate the MEMD-enhanced mvFE values have a smaller coefficient of variation in comparison with those obtained by the MEMD-enhanced mvSE, even for long signals. The results also show that the MEMD-enhanced mvFE has better performance to quantify focal and non-focal signals compared with multivariate multiscale permutation entropy.
PPM Receiver Implemented in Software
NASA Technical Reports Server (NTRS)
Gray, Andrew; Kang, Edward; Lay, Norman; Vilnrotter, Victor; Srinivasan, Meera; Lee, Clement
2010-01-01
A computer program has been written as a tool for developing optical pulse-position- modulation (PPM) receivers in which photodetector outputs are fed to analog-to-digital converters (ADCs) and all subsequent signal processing is performed digitally. The program can be used, for example, to simulate an all-digital version of the PPM receiver described in Parallel Processing of Broad-Band PPM Signals (NPO-40711), which appears elsewhere in this issue of NASA Tech Briefs. The program can also be translated into a design for digital PPM receiver hardware. The most notable innovation embodied in the software and the underlying PPM-reception concept is a digital processing subsystem that performs synchronization of PPM time slots, even though the digital processing is, itself, asynchronous in the sense that no attempt is made to synchronize it with the incoming optical signal a priori and there is no feedback to analog signal processing subsystems or ADCs. Functions performed by the software receiver include time-slot synchronization, symbol synchronization, coding preprocessing, and diagnostic functions. The program is written in the MATLAB and Simulink software system. The software receiver is highly parameterized and, hence, programmable: for example, slot- and symbol-synchronization filters have programmable bandwidths.
Mitochondrial Energy and Redox Signaling in Plants
Schwarzländer, Markus
2013-01-01
Abstract Significance: For a plant to grow and develop, energy and appropriate building blocks are a fundamental requirement. Mitochondrial respiration is a vital source for both. The delicate redox processes that make up respiration are affected by the plant's changing environment. Therefore, mitochondrial regulation is critically important to maintain cellular homeostasis. This involves sensing signals from changes in mitochondrial physiology, transducing this information, and mounting tailored responses, by either adjusting mitochondrial and cellular functions directly or reprogramming gene expression. Recent Advances: Retrograde (RTG) signaling, by which mitochondrial signals control nuclear gene expression, has been a field of very active research in recent years. Nevertheless, no mitochondrial RTG-signaling pathway is yet understood in plants. This review summarizes recent advances toward elucidating redox processes and other bioenergetic factors as a part of RTG signaling of plant mitochondria. Critical Issues: Novel insights into mitochondrial physiology and redox-regulation provide a framework of upstream signaling. On the other end, downstream responses to modified mitochondrial function have become available, including transcriptomic data and mitochondrial phenotypes, revealing processes in the plant that are under mitochondrial control. Future Directions: Drawing parallels to chloroplast signaling and mitochondrial signaling in animal systems allows to bridge gaps in the current understanding and to deduce promising directions for future research. It is proposed that targeted usage of new technical approaches, such as quantitative in vivo imaging, will provide novel leverage to the dissection of plant mitochondrial signaling. Antioxid. Redox Signal. 18, 2122–2144. PMID:23234467
NASA Astrophysics Data System (ADS)
Beskardes, G. D.; Hole, J. A.; Wang, K.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Michaelides, M.; Brown, L. D.; Quiros, D. A.
2016-12-01
Back-projection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. Back-projection is scalable to earthquakes with a wide range of magnitudes from very tiny to very large. Local dense arrays provide the opportunity to capture very tiny events for a range applications, such as tectonic microseismicity, source scaling studies, wastewater injection-induced seismicity, hydraulic fracturing, CO2 injection monitoring, volcano studies, and mining safety. While back-projection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed to overcome imaging issues. We compare the performance of back-projection using four previously used data pre-processing methods: full waveform, envelope, short-term averaging / long-term averaging (STA/LTA), and kurtosis. The goal is to identify an optimized strategy for an entirely automated imaging process that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the energy imaged at the source, preserves magnitude information, and considers computational cost. Real data issues include aliased station spacing, low signal-to-noise ratio (to <1), large noise bursts and spatially varying waveform polarity. For evaluation, the four imaging methods were applied to the aftershock sequence of the 2011 Virginia earthquake as recorded by the AIDA array with 200-400 m station spacing. These data include earthquake magnitudes from -2 to 3 with highly variable signal to noise, spatially aliased noise, and large noise bursts: realistic issues in many environments. Each of the four back-projection methods has advantages and disadvantages, and a combined multi-pass method achieves the best of all criteria. Preliminary imaging results from the 2011 Virginia dataset will be presented.
Under-sampling in a Multiple-Channel Laser Vibrometry System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Corey, Jordan
2007-03-01
Laser vibrometry is a technique used to detect vibrations on objects using the interference of coherent light with itself. Most vibrometry systems process only one target location at a time, but processing multiple locations simultaneously provides improved detection capabilities. Traditional laser vibrometry systems employ oversampling to sample the incoming modulated-light signal, however as the number of channels increases in these systems, certain issues arise such a higher computational cost, excessive heat, increased power requirements, and increased component cost. This thesis describes a novel approach to laser vibrometry that utilizes undersampling to control the undesirable issues associated with over-sampled systems. Undersamplingmore » allows for significantly less samples to represent the modulated-light signals, which offers several advantages in the overall system design. These advantages include an improvement in thermal efficiency, lower processing requirements, and a higher immunity to the relative intensity noise inherent in laser vibrometry applications. A unique feature of this implementation is the use of a parallel architecture to increase the overall system throughput. This parallelism is realized using a hierarchical multi-channel architecture based on off-the-shelf programmable logic devices (PLDs).« less
LeRoith, Derek; Nissley, Peter
2005-01-01
The growth hormone/IGF-1–signaling (GH/IGF-1–signaling) system is involved in numerous physiological processes during normal growth and development and also in the aging process. Understanding the regulation of this system is therefore of importance to the biologist. Studies conducted over the past decade have shown that the JAK/STAT pathways are involved in GH signaling to the nucleus. More recently, evidence has been presented that a member of the SOCS family, SOCS2, is a negative regulator of GH signaling. This story began several years ago with the dramatic demonstration of gigantism in the SOCS2-knockout mouse. A more specific definition of the role of SOCS2 in GH signaling is provided in this issue of the JCI by the demonstration that the overgrowth phenotype of the SOCS2–/– mouse is dependent upon the presence of endogenous GH and that administration of GH to mice lacking both endogenous GH and SOCS2 produced excessive growth. PMID:15690080
Editorial: Mathematical Methods and Modeling in Machine Fault Diagnosis
Yan, Ruqiang; Chen, Xuefeng; Li, Weihua; ...
2014-12-18
Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yan, Ruqiang; Chen, Xuefeng; Li, Weihua
Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less
Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery
NASA Astrophysics Data System (ADS)
Si, Qian
Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.
Analysis of radiometric signal in sedimentating suspension flow in open channel
NASA Astrophysics Data System (ADS)
Zych, Marcin; Hanus, Robert; Petryka, Leszek; Świsulski, Dariusz; Doktor, Marek; Mastej, Wojciech
2015-05-01
The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.
Digital signal processing techniques for pitch shifting and time scaling of audio signals
NASA Astrophysics Data System (ADS)
Buś, Szymon; Jedrzejewski, Konrad
2016-09-01
In this paper, we present the techniques used for modifying the spectral content (pitch shifting) and for changing the time duration (time scaling) of an audio signal. A short introduction gives a necessary background for understanding the discussed issues and contains explanations of the terms used in the paper. In subsequent sections we present three different techniques appropriate both for pitch shifting and for time scaling. These techniques use three different time-frequency representations of a signal, namely short-time Fourier transform (STFT), continuous wavelet transform (CWT) and constant-Q transform (CQT). The results of simulation studies devoted to comparison of the properties of these methods are presented and discussed in the paper.
Computational problems and signal processing in SETI
NASA Technical Reports Server (NTRS)
Deans, Stanley R.; Cullers, D. K.; Stauduhar, Richard
1991-01-01
The Search for Extraterrestrial Intelligence (SETI), currently being planned at NASA, will require that an enormous amount of data (on the order of 10 exp 11 distinct signal paths for a typical observation) be analyzed in real time by special-purpose hardware. Even though the SETI system design is not based on maximum entropy and Bayesian methods (partly due to the real-time processing constraint), it is expected that enough data will be saved to be able to apply these and other methods off line where computational complexity is not an overriding issue. Interesting computational problems that relate directly to the system design for processing such an enormous amount of data have emerged. Some of these problems are discussed, along with the current status on their solution.
Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.
2012-01-01
Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239
Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G
2012-01-01
Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
What does voice-processing technology support today?
Nakatsu, R; Suzuki, Y
1995-01-01
This paper describes the state of the art in applications of voice-processing technologies. In the first part, technologies concerning the implementation of speech recognition and synthesis algorithms are described. Hardware technologies such as microprocessors and DSPs (digital signal processors) are discussed. Software development environment, which is a key technology in developing applications software, ranging from DSP software to support software also is described. In the second part, the state of the art of algorithms from the standpoint of applications is discussed. Several issues concerning evaluation of speech recognition/synthesis algorithms are covered, as well as issues concerning the robustness of algorithms in adverse conditions. Images Fig. 3 PMID:7479720
Process observation in fiber laser-based selective laser melting
NASA Astrophysics Data System (ADS)
Thombansen, Ulrich; Gatej, Alexander; Pereira, Milton
2015-01-01
The process observation in selective laser melting (SLM) focuses on observing the interaction point where the powder is processed. To provide process relevant information, signals have to be acquired that are resolved in both time and space. Especially in high-power SLM, where more than 1 kW of laser power is used, processing speeds of several meters per second are required for a high-quality processing results. Therefore, an implementation of a suitable process observation system has to acquire a large amount of spatially resolved data at low sampling speeds or it has to restrict the acquisition to a predefined area at a high sampling speed. In any case, it is vitally important to synchronously record the laser beam position and the acquired signal. This is a prerequisite that allows the recorded data become information. Today, most SLM systems employ f-theta lenses to focus the processing laser beam onto the powder bed. This report describes the drawbacks that result for process observation and suggests a variable retro-focus system which solves these issues. The beam quality of fiber lasers delivers the processing laser beam to the powder bed at relevant focus diameters, which is a key prerequisite for this solution to be viable. The optical train we present here couples the processing laser beam and the process observation coaxially, ensuring consistent alignment of interaction zone and observed area. With respect to signal processing, we have developed a solution that synchronously acquires signals from a pyrometer and the position of the laser beam by sampling the data with a field programmable gate array. The relevance of the acquired signals has been validated by the scanning of a sample filament. Experiments with grooved samples show a correlation between different powder thicknesses and the acquired signals at relevant processing parameters. This basic work takes a first step toward self-optimization of the manufacturing process in SLM. It enables the addition of cognitive functions to the manufacturing system to the extent that the system could track its own process. The results are based on analyzing and redesigning the optical train, in combination with a real-time signal acquisition system which provides a solution to certain technological barriers.
Software for a GPS-Reflection Remote-Sensing System
NASA Technical Reports Server (NTRS)
Lowe, Stephen
2003-01-01
A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).
Cognitive Algorithms for Signal Processing
2011-03-18
Analysis of Millennial Spiritual Issues,” Zygon, Journal of Science and Religion , 43(4), 797-821, 2008. [46] R. Linnehan, C. Mutz, L.I. Perlovsky, B...dimensions of X and Y : (a) true ‘smile’ and ‘frown’ patterns are shown without clutter; (b) actual image available for recognition (signal is below...clutter in 2 dimensions of X(n) = (X, Y ), is given by l(X(n)|m = clutter) = 1/ (X • Y ), X = (Xmax-Xmin), Y = (Ymax-Ymin); (6) 13 Minimal
Signal Processing Algorithms for the Terminal Doppler Weather Radar: Build 2
2010-04-30
the various TDWR base data quality issues, range-velocity (RV) ambiguity was deemed to be the most severe challenge nationwide. Compared to S - band ... power is computed as PN = median(|5«| 2)/(ln 2), where s is the complex I&Q signal, k is the range gate number, and / is the pulse time index. The...frequencies to the ground-clutter band around zero, the clutter filtering also removes power from the aliased frequencies and distorts the phase response
Effects of Tasks on BOLD Signal Responses to Sentence Contrasts: Review and Commentary
Caplan, David; Gow, David
2010-01-01
Functional neuroimaging studies of syntactic processing have been interpreted as identifying the neural locations of parsing and interpretive operations. However, current behavioral studies of sentence processing indicate that many operations occur simultaneously with parsing and interpretation. In this review, we point to issues that arise in discriminating the effects of these concurrent processes from those of the parser/interpreter in neural measures and to approaches that may help resolve them. PMID:20932562
Cyclostationarity approach for monitoring chatter and tool wear in high speed milling
NASA Astrophysics Data System (ADS)
Lamraoui, M.; Thomas, M.; El Badaoui, M.
2014-02-01
Detection of chatter and tool wear is crucial in the machining process and their monitoring is a key issue, for: (1) insuring better surface quality, (2) increasing productivity and (3) protecting both machines and safe workpiece. This paper presents an investigation of chatter and tool wear using the cyclostationary method to process the vibrations signals acquired from high speed milling. Experimental cutting tests were achieved on slot milling operation of aluminum alloy. The experimental set-up is designed for acquisition of accelerometer signals and encoding information picked up from an encoder. The encoder signal is used for re-sampling accelerometers signals in angular domain using a specific algorithm that was developed in LASPI laboratory. The use of cyclostationary on accelerometer signals has been applied for monitoring chatter and tool wear in high speed milling. The cyclostationarity appears on average properties (first order) of signals, on the energetic properties (second order) and it generates spectral lines at cyclic frequencies in spectral correlation. Angular power and kurtosis are used to analyze chatter phenomena. The formation of chatter is characterized by unstable, chaotic motion of the tool and strong anomalous fluctuations of cutting forces. Results show that stable machining generates only very few cyclostationary components of second order while chatter is strongly correlated to cyclostationary components of second order. By machining in the unstable region, chatter results in flat angular kurtosis and flat angular power, such as a pseudo (white) random signal with flat spectrum. Results reveal that spectral correlation and Wigner Ville spectrum or integrated Wigner Ville issued from second-order cyclostationary are an efficient parameter for the early diagnosis of faults in high speed machining, such as chatter, tool wear and bearings, compared to traditional stationary methods. Wigner Ville representation of the residual signal shows that the energy corresponding to the tooth passing decreases when chatter phenomenon occurs. The effect of the tool wear and the number of broken teeth on the excitation of structure resonances appears in Wigner Ville presentation.
Psycho-physiological training approach for amputee rehabilitation.
Dhal, Chandan; Wahi, Akshat
2015-01-01
Electromyography (EMG) signals are very noisy and difficult to acquire. Conventional techniques involve amplification and filtering through analog circuits, which makes the system very unstable. The surface EMG signals lie in the frequency range of 6Hz to 600Hz, and the dominant range is between the ranges from 20Hz to 150Hz. 1 Our project aimed to analyze an EMG signal effectively over its complete frequency range. To remove these defects, we designed what we think is an easy, effective, and reliable signal processing technique. We did spectrum analysis, so as to perform all the processing such as amplification, filtering, and thresholding on an Arduino Uno board, hence removing the need for analog amplifiers and filtering circuits, which have stability issues. The conversion of time domain to frequency domain of any signal gives a detailed data of the signal set. Our main aim is to use this useful data for an alternative methodology for rehabilitation called a psychophysiological approach to rehabilitation in prosthesis, which can reduce the cost of the myoelectric arm, as well as increase its efficiency. This method allows the user to gain control over their muscle sets in a less stressful environment. Further, we also have described how our approach is viable and can benefit the rehabilitation process. We used our DSP EMG signals to play an online game and showed how this approach can be used in rehabilitation.
A dynamic multi-channel speech enhancement system for distributed microphones in a car environment
NASA Astrophysics Data System (ADS)
Matheja, Timo; Buck, Markus; Fingscheidt, Tim
2013-12-01
Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers' signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.
Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.
Stec, Bronisław; Susek, Waldemar
2018-05-06
Determination of the signal power-to-noise power ratio on the input and output of reception systems is essential to the estimation of their quality and signal reception capability. This issue is especially important in the case when both signal and noise have the same characteristic as Gaussian white noise. This article considers the problem of how a signal-to-noise ratio is changed as a result of signal processing in the correlation receiver of a noise radar in order to determine the ability to detect weak features in the presence of strong clutter-type interference. These studies concern both theoretical analysis and practical measurements of a noise radar with a digital correlation receiver for 9.2 GHz bandwidth. Firstly, signals participating individually in the correlation process are defined and the terms signal and interference are ascribed to them. Further studies show that it is possible to distinguish a signal and a noise on the input and output of a correlation receiver, respectively, when all the considered noises are in the form of white noise. Considering the above, a measurement system is designed in which it is possible to represent the actual conditions of noise radar operation and power measurement of a useful noise signal and interference noise signals—in particular the power of an internal leakage signal between a transmitter and a receiver of the noise radar. The proposed measurement stands and the obtained results show that it is possible to optimize with the use of the equipment and not with the complex processing of a noise signal. The radar parameters depend on its prospective application, such as short- and medium-range radar, ground-penetrating radar, and through-the-wall detection radar.
A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
NASA Astrophysics Data System (ADS)
Quintero-Rincón, Antonio; Pereyra, Marcelo; D'Giano, Carlos; Batatia, Hadj; Risk, Marcelo
2016-04-01
Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.
Focus Issue: Cell biology meets cancer therapy.
Gough, Nancy R
2016-02-16
Cells are the targets of anticancer therapy, whether the therapy is directed at the tumor cells themselves or the cells of the immune system. Articles in this issue and in the 2015 Science Signaling archives provide insights into what makes a cell responsive to therapy and how understanding the cellular processes affected by the drugs (including endosomal trafficking and response to proteotoxic stress) can lead to personalized cancer therapies, thereby minimizing side effects and ineffective treatment strategies. Copyright © 2016, American Association for the Advancement of Science.
Canada’s Foreign Policy Objectives and Canadian Security Arrangements in the North,
1980-02-01
NATO - but really the issue is greater even than that. The importance of sea communciations is so clearly perceived, the evidence of two world wars...submarines in transit, with computer processing of signals from fixed and mobile acoustic sensors somewhat compensating for the inability to detect
Radiation effects in reconfigurable FPGAs
NASA Astrophysics Data System (ADS)
Quinn, Heather
2017-04-01
Field-programmable gate arrays (FPGAs) are co-processing hardware used in image and signal processing. FPGA are programmed with custom implementations of an algorithm. These algorithms are highly parallel hardware designs that are faster than software implementations. This flexibility and speed has made FPGAs attractive for many space programs that need in situ, high-speed signal processing for data categorization and data compression. Most commercial FPGAs are affected by the space radiation environment, though. Problems with TID has restricted the use of flash-based FPGAs. Static random access memory based FPGAs must be mitigated to suppress errors from single-event upsets. This paper provides a review of radiation effects issues in reconfigurable FPGAs and discusses methods for mitigating these problems. With careful design it is possible to use these components effectively and resiliently.
Light Signaling in Bud Outgrowth and Branching in Plants
Leduc, Nathalie; Roman, Hanaé; Barbier, François; Péron, Thomas; Huché-Thélier, Lydie; Lothier, Jérémy; Demotes-Mainard, Sabine; Sakr, Soulaiman
2014-01-01
Branching determines the final shape of plants, which influences adaptation, survival and the visual quality of many species. It is an intricate process that includes bud outgrowth and shoot extension, and these in turn respond to environmental cues and light conditions. Light is a powerful environmental factor that impacts multiple processes throughout plant life. The molecular basis of the perception and transduction of the light signal within buds is poorly understood and undoubtedly requires to be further unravelled. This review is based on current knowledge on bud outgrowth-related mechanisms and light-mediated regulation of many physiological processes. It provides an extensive, though not exhaustive, overview of the findings related to this field. In parallel, it points to issues to be addressed in the near future. PMID:27135502
Non-stationary least-squares complex decomposition for microseismic noise attenuation
NASA Astrophysics Data System (ADS)
Chen, Yangkang
2018-06-01
Microseismic data processing and imaging are crucial for subsurface real-time monitoring during hydraulic fracturing process. Unlike the active-source seismic events or large-scale earthquake events, the microseismic event is usually of very small magnitude, which makes its detection challenging. The biggest trouble of microseismic data is the low signal-to-noise ratio issue. Because of the small energy difference between effective microseismic signal and ambient noise, the effective signals are usually buried in strong random noise. I propose a useful microseismic denoising algorithm that is based on decomposing a microseismic trace into an ensemble of components using least-squares inversion. Based on the predictive property of useful microseismic event along the time direction, the random noise can be filtered out via least-squares fitting of multiple damping exponential components. The method is flexible and almost automated since the only parameter needed to be defined is a decomposition number. I use some synthetic and real data examples to demonstrate the potential of the algorithm in processing complicated microseismic data sets.
Analysis on electronic control unit of continuously variable transmission
NASA Astrophysics Data System (ADS)
Cao, Shuanggui
Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.
Role of the ceramide-signaling pathways in ionizing radiation-induced apoptosis.
Vit, Jean-Philippe; Rosselli, Filippo
2003-11-27
Ionizing radiations (IR) exposure leads to damage on several cellular targets. How signals from different targets are integrated to determine the cell fate remains a controversial issue. Understanding the pathway(s) responsible(s) for the cell killing effect of the IR exposure is of prime importance in light of using radiations as anticancer agent or as diagnostic tool. In this study, we have established that IR-induced cell damage initiates two independent signaling pathways that lead to a biphasic intracellular ceramide increase. A transitory increase of ceramide is observed within minutes after IR exposure as a consequence of DNA damage-independent acid sphingomyelinase activation. Several hours after irradiation, a second wave of ceramide accumulation is observed depending on the DNA damage-dependent activation of ceramide synthase, which requires a signaling pathway involving ATM. Importantly, we have demonstrated that the late ceramide accumulation is also dependent on the first one and is rate limiting for the apoptotic process induced by IR. In conclusion, our observations suggest that ceramide is a major determinant of the IR-induced apoptotic process at the cross-point of different signal transduction pathways.
NASA Astrophysics Data System (ADS)
Halverson, Peter G.; Loya, Frank M.
2017-11-01
Projects such as the Space Interferometry Mission (SIM) [1] and Terrestrial Planet Finder (TPF) [2] rely heavily on sub-nanometer accuracy metrology systems to define their optical paths and geometries. The James Web Space Telescope (JWST) is using this metrology in a cryogenic dilatometer for characterizing material properties (thermal expansion, creep) of optical materials. For all these projects, a key issue has been the reliability and stability of the electronics that convert displacement metrology signals into real-time distance determinations. A particular concern is the behavior of the electronics in situations where laser heterodyne signals are weak or noisy and subject to abrupt Doppler shifts due to vibrations or the slewing of motorized optics. A second concern is the long-term (hours to days) stability of the distance measurements under conditions of drifting laser power and ambient temperature. This paper describes heterodyne displacement metrology gauge signal processing methods that achieve satisfactory robustness against low signal strength and spurious signals, and good long-term stability. We have a proven displacement-measuring approach that is useful not only to space-optical projects at JPL, but also to the wider field of distance measurements.
Detection and enforcement of failure-to-yield in an emergency vehicle preemption system
NASA Technical Reports Server (NTRS)
Bachelder, Aaron (Inventor); Wickline, Richard (Inventor)
2007-01-01
An intersection controlled by an intersection controller receives trigger signals from on-coming emergency vehicles responding to an emergency call. The intersection controller initiates surveillance of the intersection via cameras installed at the intersection in response to a received trigger signal. The surveillance may begin immediately upon receipt of the trigger signal from an emergency vehicle, or may wait until the intersection controller determines that the signaling emergency vehicle is in the field of view of the cameras at the intersection. Portions of the captured images are tagged by the intersection controller based on tag signals transmitted by the vehicle or based on detected traffic patterns that indicate a potential traffic violation. The captured images are downloaded to a processing facility that analyzes the images and automatically issues citations for captured traffic violations.
Zinc Signal in Brain Diseases.
Portbury, Stuart D; Adlard, Paul A
2017-11-23
The divalent cation zinc is an integral requirement for optimal cellular processes, whereby it contributes to the function of over 300 enzymes, regulates intracellular signal transduction, and contributes to efficient synaptic transmission in the central nervous system. Given the critical role of zinc in a breadth of cellular processes, its cellular distribution and local tissue level concentrations remain tightly regulated via a series of proteins, primarily including zinc transporter and zinc import proteins. A loss of function of these regulatory pathways, or dietary alterations that result in a change in zinc homeostasis in the brain, can all lead to a myriad of pathological conditions with both acute and chronic effects on function. This review aims to highlight the role of zinc signaling in the central nervous system, where it may precipitate or potentiate diverse issues such as age-related cognitive decline, depression, Alzheimer's disease or negative outcomes following brain injury.
NASA Astrophysics Data System (ADS)
Carson, John C.
1990-11-01
Various papers on materials, devices, techniques, and applications for X-plane focal plane array technology are presented. Individual topics addressed include: application of Z-plane technology to the remote sensing of the earth from GEO, applications of smart neuromorphic focal planes, image-processing of Z-plane technology, neural network Z-plane implementation with very high interconnection rates, using a small IR surveillance satellite for tactical applications, establishing requirements for homing applications, Z-plane technology. Also discussed are: on-array spike suppression signal processing, algorithms for on-focal-plane gamma circumvention and time-delay integration, current HYMOSS Z-technology, packaging of electrons for on- and off-FPA signal processing, space/performance qualification of tape automated bonded devices, automation in tape automated bonding, high-speed/high-volume radiometric testing of Z-technology focal planes, 128-layer HYMOSS-module fabrication issues, automation of IRFPA production processes.
Asynchronous signal-dependent non-uniform sampler
NASA Astrophysics Data System (ADS)
Can-Cimino, Azime; Chaparro, Luis F.; Sejdić, Ervin
2014-05-01
Analog sparse signals resulting from biomedical and sensing network applications are typically non-stationary with frequency-varying spectra. By ignoring that the maximum frequency of their spectra is changing, uniform sampling of sparse signals collects unnecessary samples in quiescent segments of the signal. A more appropriate sampling approach would be signal-dependent. Moreover, in many of these applications power consumption and analog processing are issues of great importance that need to be considered. In this paper we present a signal dependent non-uniform sampler that uses a Modified Asynchronous Sigma Delta Modulator which consumes low-power and can be processed using analog procedures. Using Prolate Spheroidal Wave Functions (PSWF) interpolation of the original signal is performed, thus giving an asynchronous analog to digital and digital to analog conversion. Stable solutions are obtained by using modulated PSWFs functions. The advantage of the adapted asynchronous sampler is that range of frequencies of the sparse signal is taken into account avoiding aliasing. Moreover, it requires saving only the zero-crossing times of the non-uniform samples, or their differences, and the reconstruction can be done using their quantized values and a PSWF-based interpolation. The range of frequencies analyzed can be changed and the sampler can be implemented as a bank of filters for unknown range of frequencies. The performance of the proposed algorithm is illustrated with an electroencephalogram (EEG) signal.
1982-02-01
of i, nd to (! Lvel op an awareness of the T&E roles and responsioi Ii ties Viir~dte various Air Force organizations involved in the T&EC process... mathematical models to determine controller messages and issue controller messages using computer generated speech. AUTOMATED PERFORMANCE ALERTS: Signals
ERIC Educational Resources Information Center
Holroyd, Clay B.; Baker, Travis E.; Kerns, Kimberly A.; Muller, Ulrich
2008-01-01
Behavioral and neurophysiological evidence suggest that attention-deficit hyperactivity disorder (ADHD) is characterized by the impact of abnormal reward prediction error signals carried by the midbrain dopamine system on frontal brain areas that implement cognitive control. To investigate this issue, we recorded the event-related brain potential…
Middle Atmosphere Program. Handbook for MAP. Volume 30: International School on Atmospheric Radar
NASA Technical Reports Server (NTRS)
Fukao, Shoichiro (Editor)
1989-01-01
Broad, tutorial coverage is given to the technical and scientific aspects of mesosphere stratosphere troposphere (MST) meteorological radar systems. Control issues, signal processing, atmospheric waves, the historical aspects of radar atmospheric dynamics, incoherent scatter radars, radar echoes, radar targets, and gravity waves are among the topics covered.
NASA Astrophysics Data System (ADS)
Lo, Yi-Chuan; Lee, Chih-Hsiung; Lin, Hsun-Peng; Peng, Chiou-Shian
1998-06-01
Several continuous splits for wafer alignment target topography conditions to improve epitaxy film alignment were applied. The alignment evaluation among former layer pad oxide thickness (250 angstrom - 500 angstrom), drive oxide thickness (6000 angstrom - 10000 angstrom), nitride film thickness (600 angstrom - 1500 angstrom), initial oxide etch (fully wet etch, fully dry etch and dry plus wet etch) will be split to this experiment. Also various epitaxy deposition recipe such as: epitaxy source (SiHCl2 or SiCHCl3) and growth rate (1.3 micrometer/min approximately 2.0 micrometer/min) will be used to optimize the process window for alignment issue. All the reflectance signal and cross section photography of alignment target during NIKON stepper alignment process will be examined. Experimental results show epitaxy recipe plays an important role to wafer alignment. Low growth rate with good performance conformity epitaxy lead to alignment target avoid washout, pattern shift and distortion. All the results (signal monitor and film character) combined with NIKON's stepper standard laser scanning alignment system will be discussed in this paper.
Palaeoclimate signal recorded by stable isotopes in cave ice: a modeling approach
NASA Astrophysics Data System (ADS)
Perşoiu, A.; Bojar, A.-V.
2012-04-01
Ice accumulations in caves preserve a large variety of geochemical information as candidate proxies for both past climate and environmental changes, one of the most significant being the stable isotopic composition of the ice. A series of recent studies have targeted oxygen and hydrogen stable isotopes in cave ice as proxies for past air temperatures, but the results are far from being as straightforward as they are in high latitude and altitude glaciers and ice caps. The main problems emerging from these studies are related to the mechanisms of cave ice formation (i.e., freezing of water) and post-formation processes (melting and refreezing), which both alter the original isotopic signal in water. Different methods have been put forward to solve these issues and a fair understanding of the present-day link between stable isotopes in precipitation and cave ice exists now. However, the main issues still lays unsolved: 1) is it possible to extend this link to older ice and thus reconstruct past changes in air temperature?; 2) to what extent are ice dynamics processes modifying the original climatic signal and 3) what is the best method to be used in extracting a climatic signal from stable isotopes in cave ice? To respond to these questions, we have conducted a modeling experiment, in which a theoretical cave ice stable isotope record was constructed using present-day observations on stable isotope behavior in cave ice and ice dynamics, and different methods (presently used for both polar and cave glaciers), were used to reconstruct the original, known, isotopic values. Our results show that it is possible to remove the effects of ice melting and refreezing on stable isotope composition of cave ice, and thus reconstruct the original isotopic signal, and further the climatic one.
NASA Technical Reports Server (NTRS)
1982-01-01
Research issues in the area of electromagnetic measurements and signal handling of remotely sensed data are identified. The following seven issues are discussed; platform/sensor system position and velocity, platform/sensor attitudes and attitude rates, optics and antennas, detectors and associated electronics, sensor calibration, signal handling, and system design.
Redox-mediated signal transduction by cardiovascular Nox NADPH oxidases.
Brandes, Ralf P; Weissmann, Norbert; Schröder, Katrin
2014-08-01
The only known function of the Nox family of NADPH oxidases is the production of reactive oxygen species (ROS). Some Nox enzymes show high tissue-specific expression and the ROS locally produced are required for synthesis of hormones or tissue components. In the cardiovascular system, Nox enzymes are low abundant and function as redox-modulators. By reacting with thiols, nitric oxide (NO) or trace metals, Nox-derived ROS elicit a plethora of cellular responses required for physiological growth factor signaling and the induction and adaptation to pathological processes. The interactions of Nox-derived ROS with signaling elements in the cardiovascular system are highly diverse and will be detailed in this article, which is part of a Special Issue entitled "Redox Signalling in the Cardiovascular System". Copyright © 2014 Elsevier Ltd. All rights reserved.
Anomaly Detection of Electromyographic Signals.
Ijaz, Ahsan; Choi, Jongeun
2018-04-01
In this paper, we provide a robust framework to detect anomalous electromyographic (EMG) signals and identify contamination types. As a first step for feature selection, optimally selected Lawton wavelets transform is applied. Robust principal component analysis (rPCA) is then performed on these wavelet coefficients to obtain features in a lower dimension. The rPCA based features are used for constructing a self-organizing map (SOM). Finally, hierarchical clustering is applied on the SOM that separates anomalous signals residing in the smaller clusters and breaks them into logical units for contamination identification. The proposed methodology is tested using synthetic and real world EMG signals. The synthetic EMG signals are generated using a heteroscedastic process mimicking desired experimental setups. A sub-part of these synthetic signals is introduced with anomalies. These results are followed with real EMG signals introduced with synthetic anomalies. Finally, a heterogeneous real world data set is used with known quality issues under an unsupervised setting. The framework provides recall of 90% (± 3.3) and precision of 99%(±0.4).
On-chip temperature-based digital signal processing for customized wireless microcontroller
NASA Astrophysics Data System (ADS)
Farhah Razanah Faezal, Siti; Isa, Mohd Nazrin Md; Harun, Azizi; Nizam Mohyar, Shaiful; Bahari Jambek, Asral
2017-11-01
Increases in die size and power density inside system-on-chip (SoC) design have brought thermal issue inside the system. Uneven heat-up and increasing in temperature offset on-chip has become a major factor that can limits the system performance. This paper presents the design and simulation of a temperature-based digital signal processing for modern system-on-chip design using the Verilog HDL. This design yields continuous monitoring of temperature and reacts to specified conditions. The simulation of the system has been done on Altera Quartus Software v. 14. With system above, microcontroller can achieve nominal power dissipation and operation is within the temperature range due to the incorporate of an interrupt-based system.
NASA Astrophysics Data System (ADS)
Twareque Ali, Syed; Antoine, Jean-Pierre; Bagarello, Fabio; Gazeau, Jean-Pierre
2011-07-01
This is a call for contributions to a special issue of Journal of Physics A: Mathematical and Theoretical dedicated to coherent states. The motivation behind this special issue is to gather in a single comprehensive volume the main aspects (past and present), latest developments, different viewpoints and directions being followed in this multidisciplinary field. Given the impressive development of the field in the past two decades, the topicality of such a volume can hardly be overemphasized. We strongly believe that such a special issue could become a particularly valuable reference for the broad scientific community working in mathematical and theoretical physics, as well as in signal processing and mathematics. Editorial policy The Guest Editors for this issue will be Syed Twareque Ali, Jean-Pierre Antoine, Fabio Bagarello and Jean-Pierre Gazeau. Potential topics include, but are not limited to, developments in the theory and applications of coherent states in: quantum optics, optomechanics, Bose-Einstein condensates quantum information, quantum measurement signal processing quantum gravity pseudo-Hermitian quantum mechanics supersymmetric quantum mechanics non-commutative quantum mechanics quantization theory harmonic and functional analysis operator theory Berezin-Toeplitz operators, PT-symmetric operators holomorphic representation theory, reproducing kernel spaces generalization of coherent states All contributions will be refereed and processed according to the usual procedure of the journal. Papers should report original and significant research that has not already been published. Guidelines for preparation of contributions The deadline for contributed papers will be 31 October 2011. This deadline will allow the special issue to appear before the end of May 2012 There is a nominal page limit of 15 printed pages per contribution (invited review papers can be longer). For papers exceeding this limit, the Guest Editors reserve the right to request a reduction in length. Further advice on publishing your work in Journal of Physics A: Mathematical and Theoretical may be found at iopscience.iop.org/jphysa. Contributions to the special issue should be submitted by web upload via authors.iop.org/, or by email to jphysa@iop.org, quoting `JPhysA Special issue on coherent states: mathematical and physical aspects'. Submissions should ideally be in standard LaTeX form. Please see the website for further information on electronic submissions. All contributions should be accompanied by a read-me file or covering letter giving the postal and e-mail addresses for correspondence. The Publishing Office should be notified of any subsequent change of address. The special issue will be published in the print and online versions of the journal.
NASA Astrophysics Data System (ADS)
Twareque Ali, Syed; Antoine, Jean-Pierre; Bagarello, Fabio; Gazeau, Jean-Pierre
2011-06-01
This is a call for contributions to a special issue of Journal of Physics A: Mathematical and Theoretical dedicated to coherent states. The motivation behind this special issue is to gather in a single comprehensive volume the main aspects (past and present), latest developments, different viewpoints and directions being followed in this multidisciplinary field. Given the impressive development of the field in the past two decades, the topicality of such a volume can hardly be overemphasized. We strongly believe that such a special issue could become a particularly valuable reference for the broad scientific community working in mathematical and theoretical physics, as well as in signal processing and mathematics. Editorial policy The Guest Editors for this issue will be Syed Twareque Ali, Jean-Pierre Antoine, Fabio Bagarello and Jean-Pierre Gazeau. Potential topics include, but are not limited to, developments in the theory and applications of coherent states in: quantum optics, optomechanics, Bose-Einstein condensates quantum information, quantum measurement signal processing quantum gravity pseudo-Hermitian quantum mechanics supersymmetric quantum mechanics non-commutative quantum mechanics quantization theory harmonic and functional analysis operator theory Berezin-Toeplitz operators, PT-symmetric operators holomorphic representation theory, reproducing kernel spaces generalization of coherent states All contributions will be refereed and processed according to the usual procedure of the journal. Papers should report original and significant research that has not already been published. Guidelines for preparation of contributions The deadline for contributed papers will be 31 October 2011. This deadline will allow the special issue to appear before the end of May 2012 There is a nominal page limit of 15 printed pages per contribution (invited review papers can be longer). For papers exceeding this limit, the Guest Editors reserve the right to request a reduction in length. Further advice on publishing your work in Journal of Physics A: Mathematical and Theoretical may be found at iopscience.iop.org/jphysa. Contributions to the special issue should be submitted by web upload via authors.iop.org/, or by email to jphysa@iop.org, quoting `JPhysA Special issue on coherent states: mathematical and physical aspects'. Submissions should ideally be in standard LaTeX form. Please see the website for further information on electronic submissions. All contributions should be accompanied by a read-me file or covering letter giving the postal and e-mail addresses for correspondence. The Publishing Office should be notified of any subsequent change of address. The special issue will be published in the print and online versions of the journal.
Filter design for cancellation of baseline-fluctuation in needle EMG recordings.
Rodríguez-Carreño, I; Malanda-Trigueros, A; Gila-Useros, L; Navallas-Irujo, J; Rodríguez-Falces, J
2006-01-01
Appropriate cancellation of the baseline fluctuation (BLF) is an important issue when recording EMG signals as it may degrade signal quality and distort qualitative and quantitative analysis. We present a novel filter-design approach for automatic cancellation of the BLF based on several signal processing techniques used sequentially. The methodology is to estimate the spectral content of the BLF, and then to use this estimation to design a high-pass FIR filter that cancel the BLF present in the signal. Two merit figures are devised for measuring the degree of BLF present in an EMG record. These figures are used to compare our method with the conventional approach, which naively considers the baseline course to be of constant (without any fluctuation) potential shift. Applications of the technique on real and simulated EMG signals show the superior performance of our approach in terms of both visual inspection and the merit figures.
NASA Astrophysics Data System (ADS)
Changqing, Zhao; Kai, Liu; Tong, Zhao; Takei, Masahiro; Weian, Ren
2014-04-01
The mud-pulse logging instrument is an advanced measurement-while-drilling (MWD) tool and widely used by the industry in the world. In order to improve the signal transmission rate, ensure the accurate transmission of information and address the issue of the weak signal on the ground of oil and gas wells, the signal generator should send out the strong mud-pulse signals with the maximum amplitude. With the rotary valve pulse generator as the study object, the three-dimensional Reynolds NS equations and standard k - ɛ turbulent model were used as a mathematical model. The speed and pressure coupling calculation was done by simple algorithms to get the amplitudes of different rates of flow and axial clearances. Tests were done to verify the characteristics of the pressure signals. The pressure signal was captured by the standpiece pressure monitoring system. The study showed that the axial clearances grew bigger as the pressure wave amplitude value decreased and caused the weakening of the pulse signal. As the rate of flow got larger, the pressure wave amplitude would increase and the signal would be enhanced.
Compressive sensing for efficient health monitoring and effective damage detection of structures
NASA Astrophysics Data System (ADS)
Jayawardhana, Madhuka; Zhu, Xinqun; Liyanapathirana, Ranjith; Gunawardana, Upul
2017-02-01
Real world Structural Health Monitoring (SHM) systems consist of sensors in the scale of hundreds, each sensor generating extremely large amounts of data, often arousing the issue of the cost associated with data transfer and storage. Sensor energy is a major component included in this cost factor, especially in Wireless Sensor Networks (WSN). Data compression is one of the techniques that is being explored to mitigate the effects of these issues. In contrast to traditional data compression techniques, Compressive Sensing (CS) - a very recent development - introduces the means of accurately reproducing a signal by acquiring much less number of samples than that defined by Nyquist's theorem. CS achieves this task by exploiting the sparsity of the signal. By the reduced amount of data samples, CS may help reduce the energy consumption and storage costs associated with SHM systems. This paper investigates CS based data acquisition in SHM, in particular, the implications of CS on damage detection and localization. CS is implemented in a simulation environment to compress structural response data from a Reinforced Concrete (RC) structure. Promising results were obtained from the compressed data reconstruction process as well as the subsequent damage identification process using the reconstructed data. A reconstruction accuracy of 99% could be achieved at a Compression Ratio (CR) of 2.48 using the experimental data. Further analysis using the reconstructed signals provided accurate damage detection and localization results using two damage detection algorithms, showing that CS has not compromised the crucial information on structural damages during the compression process.
MEMS ultrasonic transducer for monitoring of steel structures
NASA Astrophysics Data System (ADS)
Jain, Akash; Greve, David W.; Oppenheim, Irving J.
2002-06-01
Ultrasonic methods can be used to monitor crack propagation, weld failure, or section loss at critical locations in steel structures. However, ultrasonic inspection requires a skilled technician, and most commonly the signal obtained at any inspection is not preserved for later use. A preferred technology would use a MEMS device permanently installed at a critical location, polled remotely, and capable of on-chip signal processing using a signal history. We review questions related to wave geometry, signal levels, flaw localization, and electromechanical design issues for microscale transducers, and then describe the design, characterization, and initial testing of a MEMS transducer to function as a detector array. The device is approximately 1-cm square and was fabricated by the MUMPS process. The chip has 23 sensor elements to function in a phased array geometry, each element containing 180 hexagonal polysilicon diaphragms with a typical leg length of 49 microns and an unloaded natural frequency near 3.5 MHz. We first report characterization studies including capacitance-voltage measurements and admittance measurements, and then report initial experiments using a conventional piezoelectric transducer for excitation, with successful detection of signals in an on-axis transmission experiment and successful source localization from phased array performance in an off-axis transmission experiment.
Kim, Junkyeong; Lee, Chaggil; Park, Seunghee
2017-06-07
Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.
Kim, Junkyeong; Lee, Chaggil; Park, Seunghee
2017-01-01
Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process. PMID:28590456
Security Enhancement of Wireless Sensor Networks Using Signal Intervals
Moon, Jaegeun; Jung, Im Y.; Yoo, Jaesoo
2017-01-01
Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users. PMID:28368341
Security Enhancement of Wireless Sensor Networks Using Signal Intervals.
Moon, Jaegeun; Jung, Im Y; Yoo, Jaesoo
2017-04-02
Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users.
NASA Astrophysics Data System (ADS)
Papers are presented on ISDN, mobile radio systems and techniques for digital connectivity, centralized and distributed algorithms in computer networks, communications networks, quality assurance and impact on cost, adaptive filters in communications, the spread spectrum, signal processing, video communication techniques, and digital satellite services. Topics discussed include performance evaluation issues for integrated protocols, packet network operations, the computer network theory and multiple-access, microwave single sideband systems, switching architectures, fiber optic systems, wireless local communications, modulation, coding, and synchronization, remote switching, software quality, transmission, and expert systems in network operations. Consideration is given to wide area networks, image and speech processing, office communications application protocols, multimedia systems, customer-controlled network operations, digital radio systems, channel modeling and signal processing in digital communications, earth station/on-board modems, computer communications system performance evaluation, source encoding, compression, and quantization, and adaptive communications systems.
Astrocytic control of synaptic function.
Papouin, Thomas; Dunphy, Jaclyn; Tolman, Michaela; Foley, Jeannine C; Haydon, Philip G
2017-03-05
Astrocytes intimately interact with synapses, both morphologically and, as evidenced in the past 20 years, at the functional level. Ultrathin astrocytic processes contact and sometimes enwrap the synaptic elements, sense synaptic transmission and shape or alter the synaptic signal by releasing signalling molecules. Yet, the consequences of such interactions in terms of information processing in the brain remain very elusive. This is largely due to two major constraints: (i) the exquisitely complex, dynamic and ultrathin nature of distal astrocytic processes that renders their investigation highly challenging and (ii) our lack of understanding of how information is encoded by local and global fluctuations of intracellular calcium concentrations in astrocytes. Here, we will review the existing anatomical and functional evidence of local interactions between astrocytes and synapses, and how it underlies a role for astrocytes in the computation of synaptic information.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'. © 2017 The Author(s).
2016-01-01
Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269600
Fujita, Ichiro; Doi, Takahiro
2016-06-19
Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).
Molecular Mechanisms of Neuroplasticity: An Expanding Universe.
Gulyaeva, N V
2017-03-01
Biochemical processes in synapses and other neuronal compartments underlie neuroplasticity (functional and structural alterations in the brain enabling adaptation to the environment, learning, memory, as well as rehabilitation after brain injury). This basic molecular level of brain plasticity covers numerous specific proteins (enzymes, receptors, structural proteins, etc.) participating in many coordinated and interacting signal and metabolic processes, their modulation forming a molecular basis for brain plasticity. The articles in this issue are focused on different "hot points" in the research area of biochemical mechanisms supporting neuroplasticity.
Yang, Yiwei; Xu, Yuejin; Miu, Jichang; Zhou, Linghong; Xiao, Zhongju
2012-10-01
To apply the classic leakage integrate-and-fire models, based on the mechanism of the generation of physiological auditory stimulation, in the information processing coding of cochlear implants to improve the auditory result. The results of algorithm simulation in digital signal processor (DSP) were imported into Matlab for a comparative analysis. Compared with CIS coding, the algorithm of membrane potential integrate-and-fire (MPIF) allowed more natural pulse discharge in a pseudo-random manner to better fit the physiological structures. The MPIF algorithm can effectively solve the problem of the dynamic structure of the delivered auditory information sequence issued in the auditory center and allowed integration of the stimulating pulses and time coding to ensure the coherence and relevance of the stimulating pulse time.
NASA Astrophysics Data System (ADS)
Gadsden, S. Andrew; Kirubarajan, T.
2017-05-01
Signal processing techniques are prevalent in a wide range of fields: control, target tracking, telecommunications, robotics, fault detection and diagnosis, and even stock market analysis, to name a few. Although first introduced in the 1950s, the most popular method used for signal processing and state estimation remains the Kalman filter (KF). The KF offers an optimal solution to the estimation problem under strict assumptions. Since this time, a number of other estimation strategies and filters were introduced to overcome robustness issues, such as the smooth variable structure filter (SVSF). In this paper, properties of the SVSF are explored in an effort to detect and diagnosis faults in an electromechanical system. The results are compared with the KF method, and future work is discussed.
NASA Astrophysics Data System (ADS)
Deng, Ning
In recent years, optical phase modulation has attracted much research attention in the field of fiber optic communications. Compared with the traditional optical intensity-modulated signal, one of the main merits of the optical phase-modulated signal is the better transmission performance. For optical phase modulation, in spite of the comprehensive study of its transmission performance, only a little research has been carried out in terms of its functions, applications and signal processing for future optical networks. These issues are systematically investigated in this thesis. The research findings suggest that optical phase modulation and its signal processing can greatly facilitate flexible network functions and high bandwidth which can be enjoyed by end users. In the thesis, the most important physical-layer technology, signal processing and multiplexing, are investigated with optical phase-modulated signals. Novel and advantageous signal processing and multiplexing approaches are proposed and studied. Experimental investigations are also reported and discussed in the thesis. Optical time-division multiplexing and demultiplexing. With the ever-increasing demand on communication bandwidth, optical time division multiplexing (OTDM) is an effective approach to upgrade the capacity of each wavelength channel in current optical systems. OTDM multiplexing can be simply realized, however, the demultiplexing requires relatively complicated signal processing and stringent timing control, and thus hinders its practicability. To tackle this problem, in this thesis a new OTDM scheme with hybrid DPSK and OOK signals is proposed. Experimental investigation shows this scheme can greatly enhance the demultiplexing timing misalignment and improve the demultiplexing performance, and thus make OTDM more practical and cost effective. All-optical signal processing. In current and future optical communication systems and networks, the data rate per wavelength has been approaching the speed limitation of electronics. Thus, all-optical signal processing techniques are highly desirable to support the necessary optical switching functionalities in future ultrahigh-speed optical packet-switching networks. To cope with the wide use of optical phase-modulated signals, in the thesis, an all-optical logic for DPSK or PSK input signals is developed, for the first time. Based on four-wave mixing in semiconductor optical amplifier, the structure of the logic gate is simple, compact, and capable of supporting ultrafast operation. In addition to the general logic processing, a simple label recognition scheme, as a specific signal processing function, is proposed for phase-modulated label signals. The proposed scheme can recognize any incoming label pattern according to the local pattern, and is potentially capable of handling variable-length label patterns. Optical access network with multicast overlay and centralized light sources. In the arena of optical access networks, wavelength division multiplexing passive optical network (WDM-PON) is a promising technology to deliver high-speed data traffic. However, most of proposed WDM-PONs only support conventional point-to-point service, and cannot meet the requirement of increasing demand on broadcast and multicast service. In this thesis, a simple network upgrade is proposed based on the traditional PON architecture to support both point-to-point and multicast service. In addition, the two service signals are modulated on the same lightwave carrier. The upstream signal is also remodulated on the same carrier at the optical network unit, which can significantly relax the requirement on wavelength management at the network unit.
Zhang, Yan; You, Jia; Ren, Wenyan; Lin, Xinhua
2013-01-01
The highly conserved janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway is a well-known signaling system that is involved in many biological processes. In Drosophila, this signaling cascade is activated by ligands of the Unpaired (Upd) family. Therefore, the regulation of Upd distribution is one of the key issues in controlling the JAK/STAT signaling activity and function. Heparan sulfate proteoglycans (HSPGs) are macromolecules that regulate the distribution of many ligand proteins including Wingless, Hedgehog and Decapentaplegic (Dpp). Here we show that during Drosophila eye development, HSPGs are also required in normal Upd distribution and JAK/STAT signaling activity. Loss of HSPG biosynthesis enzyme Brother of tout-velu (Botv), Sulfateless (Sfl), or glypicans Division abnormally delayed (Dally) and Dally-like protein (Dlp) led to reduced levels of extracellular Upd and reduction in JAK/STAT signaling activity. Overexpression of dally resulted in the accumulation of Upd and up-regulation of the signaling activity. Luciferase assay also showed that Dally promotes JAK/STAT signaling activity, and is dependent on its heparin sulfate chains. These data suggest that Dally and Dlp are essential for Upd distribution and JAK/STAT signaling activity. PMID:23313126
NASA Astrophysics Data System (ADS)
Dong, Sunghee; Jeong, Jichai
2018-02-01
Objective. Memory is formed by the interaction of various brain functions at the item and task level. Revealing individual and combined effects of item- and task-related processes on retrieving episodic memory is an unsolved problem because of limitations in existing neuroimaging techniques. To investigate these issues, we analyze fast and slow optical signals measured from a custom-built continuous wave functional near-infrared spectroscopy (CW-fNIRS) system. Approach. In our work, we visually encode the words to the subjects and let them recall the words after a short rest. The hemodynamic responses evoked by the episodic memory are compared with those evoked by the semantic memory in retrieval blocks. In the fast optical signal, we compare the effects of old and new items (previously seen and not seen) to investigate the item-related process in episodic memory. The Kalman filter is simultaneously applied to slow and fast optical signals in different time windows. Main results. A significant task-related HbR decrease was observed in the episodic memory retrieval blocks. Mean amplitude and peak latency of a fast optical signal are dependent upon item types and reaction time, respectively. Moreover, task-related hemodynamic and item-related fast optical responses are correlated in the right prefrontal cortex. Significance. We demonstrate that episodic memory is retrieved from the right frontal area by a functional connectivity between the maintained mental state through retrieval and item-related transient activity. To the best of our knowledge, this demonstration of functional NIRS research is the first to examine the relationship between item- and task-related memory processes in the prefrontal area using single modality.
Dong, Sunghee; Jeong, Jichai
2018-02-01
Memory is formed by the interaction of various brain functions at the item and task level. Revealing individual and combined effects of item- and task-related processes on retrieving episodic memory is an unsolved problem because of limitations in existing neuroimaging techniques. To investigate these issues, we analyze fast and slow optical signals measured from a custom-built continuous wave functional near-infrared spectroscopy (CW-fNIRS) system. In our work, we visually encode the words to the subjects and let them recall the words after a short rest. The hemodynamic responses evoked by the episodic memory are compared with those evoked by the semantic memory in retrieval blocks. In the fast optical signal, we compare the effects of old and new items (previously seen and not seen) to investigate the item-related process in episodic memory. The Kalman filter is simultaneously applied to slow and fast optical signals in different time windows. A significant task-related HbR decrease was observed in the episodic memory retrieval blocks. Mean amplitude and peak latency of a fast optical signal are dependent upon item types and reaction time, respectively. Moreover, task-related hemodynamic and item-related fast optical responses are correlated in the right prefrontal cortex. We demonstrate that episodic memory is retrieved from the right frontal area by a functional connectivity between the maintained mental state through retrieval and item-related transient activity. To the best of our knowledge, this demonstration of functional NIRS research is the first to examine the relationship between item- and task-related memory processes in the prefrontal area using single modality.
Signaling Network of Environmental Sensing and Adaptation in Plants:. Key Roles of Calcium Ion
NASA Astrophysics Data System (ADS)
Kurusu, Takamitsu; Kuchitsu, Kazuyuki
2011-01-01
Considering the important issues concerning food, environment, and energy that humans are facing in the 21st century, humans mostly depend on plants. Unlike animals which move from an inappropriate environment, plants do not move, but rapidly sense diverse environmental changes or invasion by other organisms such as pathogens and insects in the place they root, and adapt themselves by changing their own bodies, through which they developed adaptability. Whole genetic information corresponding to the blueprints of many biological systems has recently been analyzed, and comparative genomic studies facilitated tracing strategies of each organism in their evolutional processes. Comparison of factors involved in intracellular signal transduction between animals and plants indicated diversification of different gene sets. Reversible binding of Ca2+ to sensor proteins play key roles as a molecular switch both in animals and plants. Molecular mechanisms for signaling network of environmental sensing and adaptation in plants will be discussed with special reference to Ca2+ as a key element in information processing.
The design of an adaptive predictive coder using a single-chip digital signal processor
NASA Astrophysics Data System (ADS)
Randolph, M. A.
1985-01-01
A speech coding processor architecture design study has been performed in which Texas Instruments TMS32010 has been selected from among three commercially available digital signal processing integrated circuits and evaluated in an implementation study of real-time Adaptive Predictive Coding (APC). The TMS32010 has been compared with AR&T Bell Laboratories DSP I and Nippon Electric Co. PD7720 and was found to be most suitable for a single chip implementation of APC. A preliminary design system based on TMS32010 has been performed, and several of the hardware and software design issues are discussed. Particular attention was paid to the design of an external memory controller which permits rapid sequential access of external RAM. As a result, it has been determined that a compact hardware implementation of the APC algorithm is feasible based of the TSM32010. Originator-supplied keywords include: vocoders, speech compression, adaptive predictive coding, digital signal processing microcomputers, speech processor architectures, and special purpose processor.
Report to the Congress on the Strategic Defense Initiative, 1991
1991-05-01
ultraviolet, and infrared radiation-hardened charge-coupled device images , step-stare sensor signal processing algorithms , and processor...Demonstration Experiment (LODE) resolved central issues associated with wavefront sensing and control and the 4-meter I Large Advanced Mirror Program (LAMP...21 Figure 4-16 Firepond CO 2 Imaging Radar Demonstration .......................... 4-22 Figure 4-17 IBSS and the Shuttle
Dynamic intervention: pathogen disarmament of mitochondrial-based immune surveillance.
Holland, Robin L; Blanke, Steven R
2014-11-12
In this issue of Cell Host & Microbe, Suzuki et al. (2014) describe a Vibrio cholerae Type-III-secreted effector that targets mitochondrial dynamics to dampen host innate immune signaling. This suggests that mammalian hosts possess surveillance mechanisms to monitor pathogen-mediated alterations in the integrity of normal cellular processes and organelles. Copyright © 2014 Elsevier Inc. All rights reserved.
Interferometric side scan sonar and data fusion
NASA Astrophysics Data System (ADS)
Sintes, Christophe R.; Solaiman, Basel
2000-04-01
This paper concerns the possibilities of sea bottom imaging and altitude determining of each imaged point. The performances of new side scan sonars which are able to image the sea bottom with a high definition and are able to evaluate the relief with the same definition derive from an interferometric multisensor system. The drawbacks concern the precision of the numerical altitude model. One way to improve the measurements precision is to merge all the information issued from the multi-sensors system. This leads to increase the Signal to Noise Ratio (SNR) and the robustness of the used method. The aim of this paper is to clearly demonstrate the ability to derive benefits of all information issued from the three arrays side scan sonar by merging: (1) the three phase signals obtained at the output of the sensors, (2) this same set of data after the application of different processing methods, and (3) the a priori relief contextual information. The key idea the proposed fusion technique is to exploit the strength and the weaknesses of each data element in the fusion of process so that the global SNR will be improved as well as the robustness to hostile noisy environments.
Wang, Dangui; Zhao, Jun; Gao, Zilong; Chen, Na; Wen, Bo; Lu, Wei; Lei, Zhuofan; Chen, Changfeng; Liu, Yahui; Feng, Jing; Wang, Jin-Hui
2015-01-01
Associative learning and memory are essential to logical thinking and cognition. How the neurons are recruited as associative memory cells to encode multiple input signals for their associated storage and distinguishable retrieval remains unclear. We studied this issue in the barrel cortex by in vivo two-photon calcium imaging, electrophysiology, and neural tracing in our mouse model that the simultaneous whisker and olfaction stimulations led to odorant-induced whisker motion. After this cross-modal reflex arose, the barrel and piriform cortices connected. More than 40% of barrel cortical neurons became to encode odor signal alongside whisker signal. Some of these neurons expressed distinct activity patterns in response to acquired odor signal and innate whisker signal, and others encoded similar pattern in response to these signals. In the meantime, certain barrel cortical astrocytes encoded odorant and whisker signals. After associative learning, the neurons and astrocytes in the sensory cortices are able to store the newly learnt signal (cross-modal memory) besides the innate signal (native-modal memory). Such associative memory cells distinguish the differences of these signals by programming different codes and signify the historical associations of these signals by similar codes in information retrievals. PMID:26347609
NASA Astrophysics Data System (ADS)
Tsujimoto, M.; Tashiro, M. S.; Ishisaki, Y.; Yamada, S.; Seta, H.; Mitsuda, K.; Boyce, K. R.; Eckart, M. E.; Kilbourne, C. A.; Leutenegger, M. A.; Porter, F. S.; Kelley, R. L.
2018-03-01
The pulse shape processor is the onboard digital electronics unit of the X-ray microcalorimeter instrument—the soft X-ray spectrometer—onboard the Hitomi satellite. It processes X-ray events using the optimum filtering with limited resources. It was operated for 36 days in orbit continuously without issues and met the requirement of processing a 150 s^{-1} event rate during the observation of bright sources. Here, we present the results obtained in orbit, focusing on its performance as the onboard digital signal processing unit of an X-ray microcalorimeter.
NEET In-Pile Ultrasonic Sensor Enablement-FY 2012 Status Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
JE Daw; JL Rempe; BR Tittmann
2012-09-01
Several Department Of Energy-Nuclear Energy (DOE-NE) programs, such as the Fuel Cycle Research and Development, Advanced Reactor Concepts, Light Water Reactor Sustainability, and Next Generation Nuclear Plant programs, are investigating new fuels and materials for advanced and existing reactors. A key objective of such programs is to understand the performance of these fuels and materials when irradiated. The Nuclear Energy Enabling Technology (NEET) Advanced Sensors and Instrumentation (ASI) in-pile instrumentation development activities are focused upon addressing cross-cutting needs for DOE-NE irradiation testing by providing higher fidelity, real-time data, with increased accuracy and resolution from smaller, compact sensors that are lessmore » intrusive. Ultrasonic technologies offer the potential to measure a range of parameters, including geometry changes, temperature, crack initiation and growth, gas pressure and composition, and microstructural changes, under harsh irradiation test conditions. There are two primary issues associated with in-pile deployment of ultrasonic sensors. The first is transducer survivability. The ability of ultrasonic transducer materials to maintain their useful properties during an irradiation must be demonstrated. The second issue is signal processing. Ultrasonic testing is typically performed in a lab or field environment, where the sensor and sample are accessible. Due to the harsh nature of in-pile testing, and the range of measurements that are desired, an enhanced signal processing capability is needed to make in-pile ultrasonic sensors viable. This project addresses these technology deployment issues.« less
Oxidative Stress, Redox Signaling, and Autophagy: Cell Death Versus Survival
Navarro-Yepes, Juliana; Burns, Michaela; Anandhan, Annadurai; Khalimonchuk, Oleh; del Razo, Luz Maria; Quintanilla-Vega, Betzabet; Pappa, Aglaia; Panayiotidis, Mihalis I.
2014-01-01
Abstract Significance: The molecular machinery regulating autophagy has started becoming elucidated, and a number of studies have undertaken the task to determine the role of autophagy in cell fate determination within the context of human disease progression. Oxidative stress and redox signaling are also largely involved in the etiology of human diseases, where both survival and cell death signaling cascades have been reported to be modulated by reactive oxygen species (ROS) and reactive nitrogen species (RNS). Recent Advances: To date, there is a good understanding of the signaling events regulating autophagy, as well as the signaling processes by which alterations in redox homeostasis are transduced to the activation/regulation of signaling cascades. However, very little is known about the molecular events linking them to the regulation of autophagy. This lack of information has hampered the understanding of the role of oxidative stress and autophagy in human disease progression. Critical Issues: In this review, we will focus on (i) the molecular mechanism by which ROS/RNS generation, redox signaling, and/or oxidative stress/damage alter autophagic flux rates; (ii) the role of autophagy as a cell death process or survival mechanism in response to oxidative stress; and (iii) alternative mechanisms by which autophagy-related signaling regulate mitochondrial function and antioxidant response. Future Directions: Our research efforts should now focus on understanding the molecular basis of events by which autophagy is fine tuned by oxidation/reduction events. This knowledge will enable us to understand the mechanisms by which oxidative stress and autophagy regulate human diseases such as cancer and neurodegenerative disorders. Antioxid. Redox Signal. 21, 66–85. PMID:24483238
Nitric oxide: a multitasked signaling gas in plants.
Domingos, Patricia; Prado, Ana Margarida; Wong, Aloysius; Gehring, Christoph; Feijo, Jose A
2015-04-01
Nitric oxide (NO) is a gaseous reactive oxygen species (ROS) that has evolved as a signaling hormone in many physiological processes in animals. In plants it has been demonstrated to be a crucial regulator of development, acting as a signaling molecule present at each step of the plant life cycle. NO has also been implicated as a signal in biotic and abiotic responses of plants to the environment. Remarkably, despite this plethora of effects and functional relationships, the fundamental knowledge of NO production, sensing, and transduction in plants remains largely unknown or inadequately characterized. In this review we cover the current understanding of NO production, perception, and action in different physiological scenarios. We especially address the issues of enzymatic and chemical generation of NO in plants, NO sensing and downstream signaling, namely the putative cGMP and Ca(2+) pathways, ion-channel activity modulation, gene expression regulation, and the interface with other ROS, which can have a profound effect on both NO accumulation and function. We also focus on the importance of NO in cell-cell communication during developmental processes and sexual reproduction, namely in pollen tube guidance and embryo sac fertilization, pathogen defense, and responses to abiotic stress. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.
Robustness of Representative Signals Relative to Data Loss Using Atlas-Based Parcellations.
Gajdoš, Martin; Výtvarová, Eva; Fousek, Jan; Lamoš, Martin; Mikl, Michal
2018-04-24
Parcellation-based approaches are an important part of functional magnetic resonance imaging data analysis. They are a necessary processing step for sorting data in structurally or functionally homogenous regions. Real functional magnetic resonance imaging datasets usually do not cover the atlas template completely; they are often spatially constrained due to the physical limitations of MR sequence settings, the inter-individual variability in brain shape, etc. When using a parcellation template, many regions are not completely covered by actual data. This paper addresses the issue of the area coverage required in real data in order to reliably estimate the representative signal and the influence of this kind of data loss on network analysis metrics. We demonstrate this issue on four datasets using four different widely used parcellation templates. We used two erosion approaches to simulate data loss on the whole-brain level and the ROI-specific level. Our results show that changes in ROI coverage have a systematic influence on network measures. Based on the results of our analysis, we recommend controlling the ROI coverage and retaining at least 60% of the area in order to ensure at least 80% of explained variance of the original signal.
NASA Astrophysics Data System (ADS)
Esepkina, N. A.; Lavrov, A. P.; Anan'ev, M. N.; Blagodarnyi, V. S.; Ivanov, S. I.; Mansyrev, M. I.; Molodyakov, S. A.
1995-10-01
Two new types of optoelectronic radio-signal processors were investigated. Charge-coupled device (CCD) photodetectors are used in these processors under continuous scanning conditions, i.e. in a time delay and storage mode. One of these processors is based on a CCD photodetector array with a reference-signal amplitude transparency and the other is an adaptive acousto-optical signal processor with linear frequency modulation. The processor with the transparency performs multichannel discrete—analogue convolution of an input signal with a corresponding kernel of the transformation determined by the transparency. If a light source is an array of light-emitting diodes of special (stripe) geometry, the optical stages of the processor can be made from optical fibre components and the whole processor then becomes a rigid 'sandwich' (a compact hybrid optoelectronic microcircuit). A report is given also of a study of a prototype processor with optical fibre components for the reception of signals from a system with antenna aperture synthesis, which forms a radio image of the Earth.
Sawaki, Risa; Luck, Steven J
2010-08-01
There is considerable controversy about whether salient singletons capture attention in a bottom-up fashion, irrespective of top-down control settings. One possibility is that salient singletons always generate an attention capture signal, but this signal can be actively suppressed to avoid capture. In the present study, we investigated this issue by using event-related potential recordings, focusing on N2pc (N2-posterior-contralateral; a measure of attentional deployment) and Pd (distractor positivity; a measure of attentional suppression). Participants searched for a specific letter within one of two regions, and irrelevant color singletons were sometimes present. We found that the irrelevant singletons did not elicit N2pc but instead elicited Pd; this occurred equally within the attended and unattended regions. These findings suggest that salient singletons may automatically produce an attend-to-me signal, irrespective of top-down control settings, but this signal can be overridden by an active suppression process to prevent the actual capture of attention.
Shared performance monitor in a multiprocessor system
Chiu, George; Gara, Alan G.; Salapura, Valentina
2012-07-24
A performance monitoring unit (PMU) and method for monitoring performance of events occurring in a multiprocessor system. The multiprocessor system comprises a plurality of processor devices units, each processor device for generating signals representing occurrences of events in the processor device, and, a single shared counter resource for performance monitoring. The performance monitor unit is shared by all processor cores in the multiprocessor system. The PMU comprises: a plurality of performance counters each for counting signals representing occurrences of events from one or more the plurality of processor units in the multiprocessor system; and, a plurality of input devices for receiving the event signals from one or more processor devices of the plurality of processor units, the plurality of input devices programmable to select event signals for receipt by one or more of the plurality of performance counters for counting, wherein the PMU is shared between multiple processing units, or within a group of processors in the multiprocessing system. The PMU is further programmed to monitor event signals issued from non-processor devices.
Bluetooth-based sensor networks for remotely monitoring the physiological signals of a patient.
Zhang, Ying; Xiao, Hannan
2009-11-01
Integrating intelligent medical microsensors into a wireless communication network makes it possible to remotely collect physiological signals of a patient, release the patient from being tethered to monitoring medical instrumentations, and facilitate the patient's early hospital discharge. This can further improve life quality by providing continuous observation without the need of disrupting the patient's normal life, thus reducing the risk of infection significantly, and decreasing the cost of the hospital and the patient. This paper discusses the implementation issues, and describes the overall system architecture of our developed Bluetooth sensor network for patient monitoring and the corresponding heart activity sensors. It also presents our approach to developing the intelligent physiological sensor nodes involving integration of Bluetooth radio technology, hardware and software organization, and our solutions for onboard signal processing.
ERIC Educational Resources Information Center
McPheron, Benjamin D.; Thangaraj, Charles V.; Thomas, Charles R.
2017-01-01
Laboratory courses can be difficult to fit into an engineering program at a liberal arts-focused university, which requires students to be exposed to appropriate breadth, as well as sufficient depth in their engineering education. One possible solution to this issue is to integrate laboratory exercises with lecture in a "studio" format,…
An Assessment of Behavioral Dynamic Information Processing Measures in Audiovisual Speech Perception
Altieri, Nicholas; Townsend, James T.
2011-01-01
Research has shown that visual speech perception can assist accuracy in identification of spoken words. However, little is known about the dynamics of the processing mechanisms involved in audiovisual integration. In particular, architecture and capacity, measured using response time methodologies, have not been investigated. An issue related to architecture concerns whether the auditory and visual sources of the speech signal are integrated “early” or “late.” We propose that “early” integration most naturally corresponds to coactive processing whereas “late” integration corresponds to separate decisions parallel processing. We implemented the double factorial paradigm in two studies. First, we carried out a pilot study using a two-alternative forced-choice discrimination task to assess architecture, decision rule, and provide a preliminary assessment of capacity (integration efficiency). Next, Experiment 1 was designed to specifically assess audiovisual integration efficiency in an ecologically valid way by including lower auditory S/N ratios and a larger response set size. Results from the pilot study support a separate decisions parallel, late integration model. Results from both studies showed that capacity was severely limited for high auditory signal-to-noise ratios. However, Experiment 1 demonstrated that capacity improved as the auditory signal became more degraded. This evidence strongly suggests that integration efficiency is vitally affected by the S/N ratio. PMID:21980314
An automatic classifier of emotions built from entropy of noise.
Ferreira, Jacqueline; Brás, Susana; Silva, Carlos F; Soares, Sandra C
2017-04-01
The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion. © 2016 Society for Psychophysiological Research.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Adams, C.; et al.
The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of inductionmore » plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.« less
Advanced Communication Processing Techniques
NASA Astrophysics Data System (ADS)
Scholtz, Robert A.
This document contains the proceedings of the workshop Advanced Communication Processing Techniques, held May 14 to 17, 1989, near Ruidoso, New Mexico. Sponsored by the Army Research Office (under Contract DAAL03-89-G-0016) and organized by the Communication Sciences Institute of the University of Southern California, the workshop had as its objective to determine those applications of intelligent/adaptive communication signal processing that have been realized and to define areas of future research. We at the Communication Sciences Institute believe that there are two emerging areas which deserve considerably more study in the near future: (1) Modulation characterization, i.e., the automation of modulation format recognition so that a receiver can reliably demodulate a signal without using a priori information concerning the signal's structure, and (2) the incorporation of adaptive coding into communication links and networks. (Encoders and decoders which can operate with a wide variety of codes exist, but the way to utilize and control them in links and networks is an issue). To support these two new interest areas, one must have both a knowledge of (3) the kinds of channels and environments in which the systems must operate, and of (4) the latest adaptive equalization techniques which might be employed in these efforts.
CHAM: weak signals detection through a new multivariate algorithm for process control
NASA Astrophysics Data System (ADS)
Bergeret, François; Soual, Carole; Le Gratiet, B.
2016-10-01
Derivatives technologies based on core CMOS processes are significantly aggressive in term of design rules and process control requirements. Process control plan is a derived from Process Assumption (PA) calculations which result in a design rule based on known process variability capabilities, taking into account enough margin to be safe not only for yield but especially for reliability. Even though process assumptions are calculated with a 4 sigma known process capability margin, efficient and competitive designs are challenging the process especially for derivatives technologies in 40 and 28nm nodes. For wafer fab process control, PA are declined in monovariate (layer1 CD, layer2 CD, layer2 to layer1 overlay, layer3 CD etc….) control charts with appropriated specifications and control limits which all together are securing the silicon. This is so far working fine but such system is not really sensitive to weak signals coming from interactions of multiple key parameters (high layer2 CD combined with high layer3 CD as an example). CHAM is a software using an advanced statistical algorithm specifically designed to detect small signals, especially when there are many parameters to control and when the parameters can interact to create yield issues. In this presentation we will first present the CHAM algorithm, then the case-study on critical dimensions, with the results, and we will conclude on future work. This partnership between Ippon and STM is part of E450LMDAP, European project dedicated to metrology and lithography development for future technology nodes, especially 10nm.
Enabling Low-Power, Multi-Modal Neural Interfaces Through a Common, Low-Bandwidth Feature Space.
Irwin, Zachary T; Thompson, David E; Schroeder, Karen E; Tat, Derek M; Hassani, Ali; Bullard, Autumn J; Woo, Shoshana L; Urbanchek, Melanie G; Sachs, Adam J; Cederna, Paul S; Stacey, William C; Patil, Parag G; Chestek, Cynthia A
2016-05-01
Brain-Machine Interfaces (BMIs) have shown great potential for generating prosthetic control signals. Translating BMIs into the clinic requires fully implantable, wireless systems; however, current solutions have high power requirements which limit their usability. Lowering this power consumption typically limits the system to a single neural modality, or signal type, and thus to a relatively small clinical market. Here, we address both of these issues by investigating the use of signal power in a single narrow frequency band as a decoding feature for extracting information from electrocorticographic (ECoG), electromyographic (EMG), and intracortical neural data. We have designed and tested the Multi-modal Implantable Neural Interface (MINI), a wireless recording system which extracts and transmits signal power in a single, configurable frequency band. In prerecorded datasets, we used the MINI to explore low frequency signal features and any resulting tradeoff between power savings and decoding performance losses. When processing intracortical data, the MINI achieved a power consumption 89.7% less than a more typical system designed to extract action potential waveforms. When processing ECoG and EMG data, the MINI achieved similar power reductions of 62.7% and 78.8%. At the same time, using the single signal feature extracted by the MINI, we were able to decode all three modalities with less than a 9% drop in accuracy relative to using high-bandwidth, modality-specific signal features. We believe this system architecture can be used to produce a viable, cost-effective, clinical BMI.
Kim, Bongseok; Kim, Sangdong; Lee, Jonghun
2018-01-01
We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment. PMID:29758016
Weak-signal Phase Calibration Strategies for Large DSN Arrays
NASA Technical Reports Server (NTRS)
Jones, Dayton L.
2005-01-01
The NASA Deep Space Network (DSN) is studying arrays of large numbers of small, mass-produced radio antennas as a cost-effective way to increase downlink sensitivity and data rates for future missions. An important issue for the operation of large arrays is the accuracy with which signals from hundreds of small antennas can be combined. This is particularly true at Ka band (32 GHz) where atmospheric phase variations can be large and rapidly changing. A number of algorithms exist to correct the phases of signals from individual antennas in the case where a spacecraft signal provides a useful signal-to-noise ratio (SNR) on time scales shorter than the atmospheric coherence time. However, for very weak spacecraft signals it will be necessary to rely on background natural radio sources to maintain array phasing. Very weak signals could result from a spacecraft emergency or by design, such as direct-to-Earth data transmissions from distant planetary atmospheric or surface probes using only low gain antennas. This paper considers the parameter space where external real-time phase calibration will be necessary, and what this requires in terms of array configuration and signal processing. The inherent limitations of this technique are also discussed.
Flight Test Result for the Ground-Based Radio Navigation System Sensor with an Unmanned Air Vehicle
Jang, Jaegyu; Ahn, Woo-Guen; Seo, Seungwoo; Lee, Jang Yong; Park, Jun-Pyo
2015-01-01
The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study, a periodic pulsed sequence was used instead of the randomized pulse sequence recommended as the RTCM (radio technical commission for maritime services) SC (special committee)-104 pseudolite signal, as a randomized pulse sequence with a long dwell time is not suitable for applications requiring high dynamics. This paper introduces a mathematical model of the post-correlation output in a navigation sensor, showing that the aliasing caused by the additional frequency term of a periodic pulsed signal leads to a false lock (i.e., Doppler frequency bias) during the signal acquisition process or in the carrier tracking loop of the navigation sensor. We suggest algorithms to resolve the frequency false lock issue in this paper, relying on the use of a multi-correlator. A flight test with an unmanned helicopter was conducted to verify the implemented navigation sensor. The results of this analysis show that there were no false locks during the flight test and that outliers stem from bad dilution of precision (DOP) or fluctuations in the received signal quality. PMID:26569251
Scientific bases of human-machine communication by voice.
Schafer, R W
1995-01-01
The scientific bases for human-machine communication by voice are in the fields of psychology, linguistics, acoustics, signal processing, computer science, and integrated circuit technology. The purpose of this paper is to highlight the basic scientific and technological issues in human-machine communication by voice and to point out areas of future research opportunity. The discussion is organized around the following major issues in implementing human-machine voice communication systems: (i) hardware/software implementation of the system, (ii) speech synthesis for voice output, (iii) speech recognition and understanding for voice input, and (iv) usability factors related to how humans interact with machines. PMID:7479802
Upstream paths for Hippo signaling in Drosophila organ development.
Choi, Kwang-Wook
2018-03-01
Organ growth is fundamental to animal development. One of major mechanisms for growth control is mediated by the conserved Hippo signaling pathway initially identified in Drosophila. The core of this pathway in Drosophila consists of a cascade of protein kinases Hippo and Warts that negatively regulate transcriptional coactivator Yorkie (Yki). Activation of Yki promotes cell survival and proliferation to induce organ growth. A key issue in Hippo signaling is to understand how core kinase cascade is activated. Activation of Hippo kinase cascade is regulated in the upstream by at least two transmembrane proteins Crumbs and Fat that act in parallel. These membrane proteins interact with additional factors such as FERM-domain proteins Expanded and Merlin to modulate subcellular localization and function of the Hippo kinase cascade. Hippo signaling is also influenced by cytoskeletal networks and cell tension in epithelia of developing organs. These upstream events in the regulation of Hippo signaling are only partially understood. This review focuses on our current understanding of some upstream processes involved in Hippo signaling in developing Drosophila organs. [BMB Reports 2018; 51(3): 134-142].
Daluwatte, C; Johannesen, L; Galeotti, L; Vicente, J; Strauss, D G; Scully, C G
2016-08-01
False and non-actionable alarms in critical care can be reduced by developing algorithms which assess the trueness of an arrhythmia alarm from a bedside monitor. Computational approaches that automatically identify artefacts in ECG signals are an important branch of physiological signal processing which tries to address this issue. Signal quality indices (SQIs) derived considering differences between artefacts which occur in ECG signals and normal QRS morphology have the potential to discriminate pathologically different arrhythmic ECG segments as artefacts. Using ECG signals from the PhysioNet/Computing in Cardiology Challenge 2015 training set, we studied previously reported ECG SQIs in the scientific literature to differentiate ECG segments with artefacts from arrhythmic ECG segments. We found that the ability of SQIs to discriminate between ECG artefacts and arrhythmic ECG varies based on arrhythmia type since the pathology of each arrhythmic ECG waveform is different. Therefore, to reduce the risk of SQIs classifying arrhythmic events as noise it is important to validate and test SQIs with databases that include arrhythmias. Arrhythmia specific SQIs may also minimize the risk of misclassifying arrhythmic events as noise.
A space-based classification system for RF transients
NASA Astrophysics Data System (ADS)
Moore, K. R.; Call, D.; Johnson, S.; Payne, T.; Ford, W.; Spencer, K.; Wilkerson, J. F.; Baumgart, C.
The FORTE (Fast On-Orbit Recording of Transient Events) small satellite is scheduled for launch in mid 1995. The mission is to measure and classify VHF (30-300 MHz) electromagnetic pulses, primarily due to lightning, within a high noise environment dominated by continuous wave carriers such as TV and FM stations. The FORTE Event Classifier will use specialized hardware to implement signal processing and neural network algorithms that perform onboard classification of RF transients and carriers. Lightning events will also be characterized with optical data telemetered to the ground. A primary mission science goal is to develop a comprehensive understanding of the correlation between the optical flash and the VHF emissions from lightning. By combining FORTE measurements with ground measurements and/or active transmitters, other science issues can be addressed. Examples include the correlation of global precipitation rates with lightning flash rates and location, the effects of large scale structures within the ionosphere (such as traveling ionospheric disturbances and horizontal gradients in the total electron content) on the propagation of broad bandwidth RF signals, and various areas of lightning physics. Event classification is a key feature of the FORTE mission. Neural networks are promising candidates for this application. The authors describe the proposed FORTE Event Classifier flight system, which consists of a commercially available digital signal processing board and a custom board, and discuss work on signal processing and neural network algorithms.
Sebastian, Alexandra; Rössler, Kora; Wibral, Michael; Mobascher, Arian; Lieb, Klaus; Jung, Patrick; Tüscher, Oliver
2017-10-04
In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy). Alternatively, the discrimination process of the critical signal (stop vs attentional capture signal) may interact with the go process (dependent discriminate then stop strategy). Those different strategies might differentially involve attention- and stopping-related processes that might be implemented by divergent neural networks. This should lead to divergent activation patterns and, if disregarded, interfere with analyses in neuroimaging studies. To clarify this crucial issue, we studied 87 human participants of both sexes during a stimulus-selective stop-signal task and performed strategy-dependent functional magnetic resonance imaging analyses. We found that, regardless of the strategy applied, outright stopping displayed indistinguishable brain activation patterns. However, during attentional capture different strategies resulted in divergent neural activation patterns with variable activation of right IFJ and bilateral VLPFC. In conclusion, the neural network involved in outright stopping is ubiquitous and independent of strategy, while different strategies impact on attention-related processes and underlying neural network usage. Strategic differences should therefore be taken into account particularly when studying attention-related processes in stimulus-selective stopping. SIGNIFICANCE STATEMENT Dissociating inhibition from attention has been a major challenge for the cognitive neuroscience of executive functions. Selective stopping tasks have been instrumental in addressing this question. However, recent theoretical, cognitive and behavioral research suggests that different strategies are applied in successful execution of the task. The underlying strategy-dependent neural networks might differ substantially. Here, we show evidence that, regardless of the strategy used, the neural network involved in outright stopping is ubiquitous. However, significant differences can only be found in the attention-related processes underlying those different strategies. Thus, when studying attentional processing of salient stop signals, strategic differences should be considered. In contrast, the neural networks implementing outright stopping seem less or not at all affected by strategic differences. Copyright © 2017 the authors 0270-6474/17/379786-10$15.00/0.
Developments and advances concerning the hyperpolarisation technique SABRE.
Mewis, Ryan E
2015-10-01
To overcome the inherent sensitivity issue in NMR and MRI, hyperpolarisation techniques are used. Signal Amplification By Reversible Exchange (SABRE) is a hyperpolarisation technique that utilises parahydrogen, a molecule that possesses a nuclear singlet state, as the source of polarisation. A metal complex is required to break the singlet order of parahydrogen and, by doing so, facilitates polarisation transfer to analyte molecules ligated to the same complex through the J-coupled network that exists. The increased signal intensities that the analyte molecules possess as a result of this process have led to investigations whereby their potential as MRI contrast agents has been probed and to understand the fundamental processes underpinning the polarisation transfer mechanism. As well as discussing literature relevant to both of these areas, the chemical structure of the complex, the physical constraints of the polarisation transfer process and the successes of implementing SABRE at low and high magnetic fields are discussed. Copyright © 2015 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Arestova, M. L.; Bykovskii, A. Yu
1995-10-01
An architecture is proposed for a specialised optoelectronic multivalued logic processor based on the Allen—Givone algebra. The processor is intended for multiparametric processing of data arriving from a large number of sensors or for tackling spectral analysis tasks. The processor architecture makes it possible to obtain an approximate general estimate of the state of an object being diagnosed on a p-level scale. Optoelectronic systems are proposed for MAXIMUM, MINIMUM, and LITERAL logic gates, based on optical-frequency encoding of logic levels. Corresponding logic gates form a complete set of logic functions in the Allen—Givone algebra.
Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation.
Azami, Hamed; Escudero, Javier
2016-05-01
Signal segmentation and spike detection are two important biomedical signal processing applications. Often, non-stationary signals must be segmented into piece-wise stationary epochs or spikes need to be found among a background of noise before being further analyzed. Permutation entropy (PE) has been proposed to evaluate the irregularity of a time series. PE is conceptually simple, structurally robust to artifacts, and computationally fast. It has been extensively used in many applications, but it has two key shortcomings. First, when a signal is symbolized using the Bandt-Pompe procedure, only the order of the amplitude values is considered and information regarding the amplitudes is discarded. Second, in the PE, the effect of equal amplitude values in each embedded vector is not addressed. To address these issues, we propose a new entropy measure based on PE: the amplitude-aware permutation entropy (AAPE). AAPE is sensitive to the changes in the amplitude, in addition to the frequency, of the signals thanks to it being more flexible than the classical PE in the quantification of the signal motifs. To demonstrate how the AAPE method can enhance the quality of the signal segmentation and spike detection, a set of synthetic and realistic synthetic neuronal signals, electroencephalograms and neuronal data are processed. We compare the performance of AAPE in these problems against state-of-the-art approaches and evaluate the significance of the differences with a repeated ANOVA with post hoc Tukey's test. In signal segmentation, the accuracy of AAPE-based method is higher than conventional segmentation methods. AAPE also leads to more robust results in the presence of noise. The spike detection results show that AAPE can detect spikes well, even when presented with single-sample spikes, unlike PE. For multi-sample spikes, the changes in AAPE are larger than in PE. We introduce a new entropy metric, AAPE, that enables us to consider amplitude information in the formulation of PE. The AAPE algorithm can be used in almost every irregularity-based application in various signal and image processing fields. We also made freely available the Matlab code of the AAPE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed
NASA Astrophysics Data System (ADS)
Kim, H.; Choi, Y.; Yang, Y.
In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.
Imaging dynamic redox processes with genetically encoded probes.
Ezeriņa, Daria; Morgan, Bruce; Dick, Tobias P
2014-08-01
Redox signalling plays an important role in many aspects of physiology, including that of the cardiovascular system. Perturbed redox regulation has been associated with numerous pathological conditions; nevertheless, the causal relationships between redox changes and pathology often remain unclear. Redox signalling involves the production of specific redox species at specific times in specific locations. However, until recently, the study of these processes has been impeded by a lack of appropriate tools and methodologies that afford the necessary redox species specificity and spatiotemporal resolution. Recently developed genetically encoded fluorescent redox probes now allow dynamic real-time measurements, of defined redox species, with subcellular compartment resolution, in intact living cells. Here we discuss the available genetically encoded redox probes in terms of their sensitivity and specificity and highlight where uncertainties or controversies currently exist. Furthermore, we outline major goals for future probe development and describe how progress in imaging methodologies will improve our ability to employ genetically encoded redox probes in a wide range of situations. This article is part of a special issue entitled "Redox Signalling in the Cardiovascular System." Copyright © 2014 Elsevier Ltd. All rights reserved.
Electromagnetic Test-Facility characterization: an identification approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zicker, J.E.; Candy, J.V.
The response of an object subjected to high energy, transient electromagnetic (EM) fields sometimes called electromagnetic pulses (EMP), is an important issue in the survivability of electronic systems (e.g., aircraft), especially when the field has been generated by a high altitude nuclear burst. The characterization of transient response information is a matter of national concern. In this report we discuss techniques to: (1) improve signal processing at a test facility; and (2) parameterize a particular object response. First, we discuss the application of identification-based signal processing techniques to improve signal levels at the Lawrence Livermore National Laboratory (LLNL) EM Transientmore » Test Facility. We identify models of test equipment and then use these models to deconvolve the input/output sequences for the object under test. A parametric model of the object is identified from this data. The model can be used to extrapolate the response to these threat level EMP. Also discussed is the development of a facility simulator (EMSIM) useful for experimental design and calibration and a deconvolution algorithm (DECONV) useful for removing probe effects from the measured data.« less
A CMOS ASIC Design for SiPM Arrays
Dey, Samrat; Banks, Lushon; Chen, Shaw-Pin; Xu, Wenbin; Lewellen, Thomas K.; Miyaoka, Robert S.; Rudell, Jacques C.
2012-01-01
Our lab has previously reported on novel board-level readout electronics for an 8×8 silicon photomultiplier (SiPM) array featuring row/column summation technique to reduce the hardware requirements for signal processing. We are taking the next step by implementing a monolithic CMOS chip which is based on the row-column architecture. In addition, this paper explores the option of using diagonal summation as well as calibration to compensate for temperature and process variations. Further description of a timing pickoff signal which aligns all of the positioning (spatial channels) pulses in the array is described. The ASIC design is targeted to be scalable with the detector size and flexible to accommodate detectors from different vendors. This paper focuses on circuit implementation issues associated with the design of the ASIC to interface our Phase II MiCES FPGA board with a SiPM array. Moreover, a discussion is provided for strategies to eventually integrate all the analog and mixed-signal electronics with the SiPM, on either a single-silicon substrate or multi-chip module (MCM). PMID:24825923
NASA Astrophysics Data System (ADS)
Nguyen, Lam
2017-05-01
The U.S. Army Research Laboratory (ARL) recently designed and tested a new prototype radar, the Spectrally Agile Frequency-Incrementing Reconfigurable (SAFIRE) radar system, based on a stepped-frequency architecture to address issues associated with our previous impulse-based radars. This is a low-frequency ultra-wideband (UWB) radar with frequencies spanning from 300 to 2000 MHz. Mounted on a vehicle, the radar can be configured in either sidelooking or forward-looking synthetic aperture radar (SAR) mode. We recently conducted our first experiment at Yuma Proving Grounds (YPG). This paper summarizes the radar configurations, parameters, and SAR geometry. The radar data and other noise sources, to include the self-interference signals and radio-frequency interference (RFI) noise sources, are presented and characterized in both the raw (pre-focus) and SAR imagery domains. This paper also describes our signal processing techniques for extracting noise from radar data, as well as the SAR imaging algorithms for forming SAR imagery in both forward- and side-looking modes. Finally, this paper demonstrates our spectral recovery technique and results for a radar operating in a spectrally restricted environment.
Wang, J Q; Xu, Z H; Liang, W Z; He, J T; Cui, Y; Liu, H Y; Xue, L X; Shi, W; Shao, Y K; Mang, J; Xu, Z X
2016-02-29
Activin A (Act A), a member of transforming growth factor-β (TGF-β) superfamily, is an early gene in response to cerebral ischemia. Growing evidences confirm the neuroprotective effect of Act A in ischemic injury through Act A/Smads signal activation. In this process, regulation networks are involved in modulating the outcomes of Smads signaling. Among these regulators, crosstalk between c-Jun N-terminal kinase (JNK) and Smads signaling has been found in the TGF-β induced epithelial-mesenchymal transition. However, in neural ischemia, the speculative regulation between JNK and Act A/Smads signaling pathways has not been clarified. To explore this issue, an Oxygen Glucose Deprivation (OGD) model was introduced to nerve-like PC12 cells. We found that JNK signal activation occurred at the early time of OGD injury (1 h). Act A administration suppressed JNK phosphorylation. In addition, JNK inhibition could elevate the strength of Smads signaling and attenuate neural apoptosis after OGD injury. Our results indicated a negative regulation effect of JNK on Smads signaling in ischemic injury. Taken together, JNK, as a critical site for neural apoptosis and negative regulator for Act A/Smads signaling, was presumed to be a molecular therapeutic target for ischemia.
Technical solutions for simultaneous MEG and SEEG recordings: towards routine clinical use.
Badier, J M; Dubarry, A S; Gavaret, M; Chen, S; Trébuchon, A S; Marquis, P; Régis, J; Bartolomei, F; Bénar, C G; Carron, R
2017-09-21
The simultaneous recording of intracerebral EEG (stereotaxic EEG, SEEG) and magnetoencephalography (MEG) is a promising strategy that provides both local and global views on brain pathological activity. Yet, acquiring simultaneous signals poses difficult technical issues that hamper their use in clinical routine. Our objective was thus to develop a set of solutions for recording a high number of SEEG channels while preserving signal quality. We recorded data in a patient with drug resistant epilepsy during presurgical evaluation. We used dedicated insertion screws and optically insulated amplifiers. We recorded 137 SEEG contacts on 10 depth electrodes (5-15 contacts each) and 248 MEG channels (magnetometers). Signal quality was assessed by comparing the distribution of RMS values in different frequency bands to a reference set of MEG acquisitions. The quality of signals was excellent for both MEG and SEEG; for MEG, it was comparable to that of MEG signals without concurrent SEEG. Discharges involving several structures on SEEG were visible on MEG, whereas discharges limited in space were not seen at the surface. SEEG can now be recorded simultaneously with whole-head MEG in routine. This opens new avenues, both methodologically for understanding signals and improving signal processing methods, and clinically for future combined analyses.
Rangel-Magdaleno, Jose J; Romero-Troncoso, Rene J; Osornio-Rios, Roque A; Cabal-Yepez, Eduardo
2009-01-01
Jerk monitoring, defined as the first derivative of acceleration, has become a major issue in computerized numeric controlled (CNC) machines. Several works highlight the necessity of measuring jerk in a reliable way for improving production processes. Nowadays, the computation of jerk is done by finite differences of the acceleration signal, computed at the Nyquist rate, which leads to low signal-to-quantization noise ratio (SQNR) during the estimation. The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR. The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator. Simulations and experimental results are presented to show the overall methodology performance.
NASA Astrophysics Data System (ADS)
Schmitz, Arne; Schinnenburg, Marc; Gross, James; Aguiar, Ana
For any communication system the Signal-to-Interference-plus-Noise-Ratio of the link is a fundamental metric. Recall (cf. Chapter 9) that the SINR is defined as the ratio between the received power of the signal of interest and the sum of all "disturbing" power sources (i.e. interference and noise). From information theory it is known that a higher SINR increases the maximum possible error-free transmission rate (referred to as Shannon capacity [417] of any communication system and vice versa). Conversely, the higher the SINR, the lower will be the bit error rate in practical systems. While one aspect of the SINR is the sum of all distracting power sources, another issue is the received power. This depends on the transmitted power, the used antennas, possibly on signal processing techniques and ultimately on the channel gain between transmitter and receiver.
Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anant, K.S.
1997-06-01
In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the Pmore » as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the feature identification methods of Chapter 3, the compression methods of Chapter 4, as well as the wavelet design methods of Chapter 5, are general enough to be easily applied to other transient signals.« less
Racial bias shapes social reinforcement learning.
Lindström, Björn; Selbing, Ida; Molapour, Tanaz; Olsson, Andreas
2014-03-01
Both emotional facial expressions and markers of racial-group belonging are ubiquitous signals in social interaction, but little is known about how these signals together affect future behavior through learning. To address this issue, we investigated how emotional (threatening or friendly) in-group and out-group faces reinforced behavior in a reinforcement-learning task. We asked whether reinforcement learning would be modulated by intergroup attitudes (i.e., racial bias). The results showed that individual differences in racial bias critically modulated reinforcement learning. As predicted, racial bias was associated with more efficiently learned avoidance of threatening out-group individuals. We used computational modeling analysis to quantitatively delimit the underlying processes affected by social reinforcement. These analyses showed that racial bias modulates the rate at which exposure to threatening out-group individuals is transformed into future avoidance behavior. In concert, these results shed new light on the learning processes underlying social interaction with racial-in-group and out-group individuals.
Xue, Bing; Qu, Xiaodong; Fang, Guangyou; Ji, Yicai
2017-01-01
In this paper, the methods and analysis for estimating the location of a three-dimensional (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using information in the covariance matrix obtained by the sensors’ outputs, equations of the source location (azimuth angle, elevation angle, and range) are obtained. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the lossy medium. By analyzing the characteristics of the proposed methods and the multiple signal classification (MUSIC) method, the computational complexity and the valid scope of these methods are given. From the results, whether the loss is known or not, we can choose the best method for processing the issues (localization in lossless medium or lossy medium). PMID:28574467
McBirney, Samantha E; Trinh, Kristy; Wong-Beringer, Annie; Armani, Andrea M
2016-10-01
Optical density (OD) measurements are the standard approach used in microbiology for characterizing bacteria concentrations in culture media. OD is based on measuring the optical absorbance of a sample at a single wavelength, and any error will propagate through all calculations, leading to reproducibility issues. Here, we use the conventional OD technique to measure the growth rates of two different species of bacteria, Pseudomonas aeruginosa and Staphylococcus aureus. The same samples are also analyzed over the entire UV-Vis wavelength spectrum, allowing a distinctly different strategy for data analysis to be performed. Specifically, instead of only analyzing a single wavelength, a multi-wavelength normalization process is implemented. When the OD method is used, the detected signal does not follow the log growth curve. In contrast, the multi-wavelength normalization process minimizes the impact of bacteria byproducts and environmental noise on the signal, thereby accurately quantifying growth rates with high fidelity at low concentrations.
Fetal-to-maternal signaling to initiate parturition
Reinl, Erin L.; England, Sarah K.
2015-01-01
Multiple processes are capable of activating the onset of parturition; however, the specific contributions of the mother and the fetus to this process are not fully understood. In this issue of the JCI, Gao and colleagues present evidence that steroid receptor coactivators 1 and 2 (SRC-1 and SRC-2) regulate surfactant protein-A (SP-A) and platelet-activating factor (PAF) expression, which increases in the developing fetal lung. WT dams crossed with males deficient for both SRC-1 and SRC-2 had suppressed myometrial inflammation, increased serum progesterone, and delayed parturition, which could be reconciled by injection of either SP-A or PAF into the amnion. Together, the results of this study demonstrate that the fetal lungs produce signals to initiate labor in the mouse. This work underscores the importance of the fetus as a contributor to the onset of murine, and potentially human, parturition. PMID:26098207
Energy-efficient neural information processing in individual neurons and neuronal networks.
Yu, Lianchun; Yu, Yuguo
2017-11-01
Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Advanced telemetry systems for payloads. Technology needs, objectives and issues
NASA Technical Reports Server (NTRS)
1990-01-01
The current trends in advanced payload telemetry are the new developments in advanced modulation/coding, the applications of intelligent techniques, data distribution processing, and advanced signal processing methodologies. Concerted efforts will be required to design ultra-reliable man-rated software to cope with these applications. The intelligence embedded and distributed throughout various segments of the telemetry system will need to be overridden by an operator in case of life-threatening situations, making it a real-time integration issue. Suitable MIL standards on physical interfaces and protocols will be adopted to suit the payload telemetry system. New technologies and techniques will be developed for fast retrieval of mass data. Currently, these technology issues are being addressed to provide more efficient, reliable, and reconfigurable systems. There is a need, however, to change the operation culture. The current role of NASA as a leader in developing all the new innovative hardware should be altered to save both time and money. We should use all the available hardware/software developed by the industry and use the existing standards rather than inventing our own.
Yasui, Yutaka; McLerran, Dale; Adam, Bao-Ling; Winget, Marcy; Thornquist, Mark; Feng, Ziding
2003-01-01
Discovery of "signature" protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological specimens and interfering biochemical/physical processes of the measurement procedure. Making sense out of such high-dimensional complex data is challenging and necessitates the use of a systematic data analytic strategy. We propose here a data processing strategy for two major issues in the analysis of such mass-spectrometry-generated proteomic data: (1) separation of protein "signals" from background "noise" in protein intensity measurements and (2) calibration of protein mass/charge measurements across samples. We illustrate the two issues and the utility of the proposed strategy using data from a prostate cancer biomarker discovery project as an example.
Brain potentials predict learning, transmission and modification of an artificial symbolic system.
Lumaca, Massimo; Baggio, Giosuè
2016-12-01
It has recently been argued that symbolic systems evolve while they are being transmitted across generations of learners, gradually adapting to the relevant brain structures and processes. In the context of this hypothesis, little is known on whether individual differences in neural processing capacity account for aspects of 'variation' observed in symbolic behavior and symbolic systems. We addressed this issue in the domain of auditory processing. We conducted a combined behavioral and EEG study on 2 successive days. On day 1, participants listened to standard and deviant five-tone sequences: as in previous oddball studies, an mismatch negativity (MMN) was elicited by deviant tones. On day 2, participants learned an artificial signaling system from a trained confederate of the experimenters in a coordination game in which five-tone sequences were associated to affective meanings (emotion-laden pictures of human faces). In a subsequent game with identical structure, participants transmitted and occasionally changed the signaling system learned during the first game. The MMN latency from day 1 predicted learning, transmission and structural modification of signaling systems on day 2. Our study introduces neurophysiological methods into research on cultural transmission and evolution, and relates aspects of variation in symbolic systems to individual differences in neural information processing. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Enhancing Three-dimensional Movement Control System for Assemblies of Machine-Building Facilities
NASA Astrophysics Data System (ADS)
Kuzyakov, O. N.; Andreeva, M. A.
2018-01-01
Aspects of enhancing three-dimensional movement control system are given in the paper. Such system is to be used while controlling assemblies of machine-building facilities, which is a relevant issue. The base of the system known is three-dimensional movement control device with optical principle of action. The device consists of multi point light emitter and light receiver matrix. The processing of signals is enhanced to increase accuracy of measurements by switching from discrete to analog signals. Light receiver matrix is divided into four areas, and the output value of each light emitter in each matrix area is proportional to its luminance level. Thus, determing output electric signal value of each light emitter in corresponding area leads to determing position of multipoint light emitter and position of object tracked. This is done by using Case-based reasoning method, the precedent in which is described as integral signal value of each matrix area, coordinates of light receivers, which luminance level is high, and decision to be made in this situation.
Moreno, Andrea; Jego, Pierrick; de la Cruz, Feliberto; Canals, Santiago
2013-01-01
Complete understanding of the mechanisms that coordinate work and energy supply of the brain, the so called neurovascular coupling, is fundamental to interpreting brain energetics and their influence on neuronal coding strategies, but also to interpreting signals obtained from brain imaging techniques such as functional magnetic resonance imaging. Interactions between neuronal activity and cerebral blood flow regulation are largely compartmentalized. First, there exists a functional compartmentalization in which glutamatergic peri-synaptic activity and its electrophysiological events occur in close proximity to vascular responses. Second, the metabolic processes that fuel peri-synaptic activity are partially segregated between glycolytic and oxidative compartments. Finally, there is cellular segregation between astrocytic and neuronal compartments, which has potentially important implications on neurovascular coupling. Experimental data is progressively showing a tight interaction between the products of energy consumption and neurotransmission-driven signaling molecules that regulate blood flow. Here, we review some of these issues in light of recent findings with special attention to the neuron-glia interplay on the generation of neuroimaging signals. PMID:23543907
Distributed digital signal processors for multi-body flexible structures
NASA Technical Reports Server (NTRS)
Lee, Gordon K. F.
1992-01-01
Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.
FGF signaling refines Wnt gradients to regulate the patterning of taste papillae.
Prochazkova, Michaela; Häkkinen, Teemu J; Prochazka, Jan; Spoutil, Frantisek; Jheon, Andrew H; Ahn, Youngwook; Krumlauf, Robb; Jernvall, Jukka; Klein, Ophir D
2017-06-15
The patterning of repeated structures is a major theme in developmental biology, and the inter-relationship between spacing and size of such structures is an unresolved issue. Fungiform papillae are repeated epithelial structures that house taste buds on the anterior tongue. Here, we report that FGF signaling is a crucial regulator of fungiform papillae development. We found that mesenchymal FGF10 controls the size of the papillary area, while overall patterning remains unchanged. Our results show that FGF signaling negatively affects the extent of canonical Wnt signaling, which is the main activation pathway during fungiform papillae development; however, this effect does not occur at the level of gene transcription. Rather, our experimental data, together with computational modeling, indicate that FGF10 modulates the range of Wnt effects, likely via induction of Sostdc1 expression. We suggest that modification of the reach of Wnt signaling could be due to local changes in morphogen diffusion, representing a novel mechanism in this tissue context, and we propose that this phenomenon might be involved in a broader array of mammalian developmental processes. © 2017. Published by The Company of Biologists Ltd.
DOA estimation of noncircular signals for coprime linear array via locally reduced-dimensional Capon
NASA Astrophysics Data System (ADS)
Zhai, Hui; Zhang, Xiaofei; Zheng, Wang
2018-05-01
We investigate the issue of direction of arrival (DOA) estimation of noncircular signals for coprime linear array (CLA). The noncircular property enhances the degree of freedom and improves angle estimation performance, but it leads to a more complex angle ambiguity problem. To eliminate ambiguity, we theoretically prove that the actual DOAs of noncircular signals can be uniquely estimated by finding the coincide results from the two decomposed subarrays based on the coprimeness. We propose a locally reduced-dimensional (RD) Capon algorithm for DOA estimation of noncircular signals for CLA. The RD processing is used in the proposed algorithm to avoid two dimensional (2D) spectral peak search, and coprimeness is employed to avoid the global spectral peak search. The proposed algorithm requires one-dimensional locally spectral peak search, and it has very low computational complexity. Furthermore, the proposed algorithm needs no prior knowledge of the number of sources. We also derive the Crámer-Rao bound of DOA estimation of noncircular signals in CLA. Numerical simulation results demonstrate the effectiveness and superiority of the algorithm.
Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals
Zhao, Ming; Lin, Jing; Miao, Yonghao; Xu, Xiaoqiang
2016-01-01
Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox. PMID:27827831
Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals.
Zhao, Ming; Lin, Jing; Miao, Yonghao; Xu, Xiaoqiang
2016-11-02
Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox.
Molecular Mechanisms of Fibroblast Growth Factor Signaling in Physiology and Pathology
Belov, Artur A.; Mohammadi, Moosa
2013-01-01
Fibroblast growth factors (FGFs) signal in a paracrine or endocrine fashion to mediate a myriad of biological activities, ranging from issuing developmental cues, maintaining tissue homeostasis, and regulating metabolic processes. FGFs carry out their diverse functions by binding and dimerizing FGF receptors (FGFRs) in a heparan sulfate (HS) cofactor- or Klotho coreceptor-assisted manner. The accumulated wealth of structural and biophysical data in the past decade has transformed our understanding of the mechanism of FGF signaling in human health and development, and has provided novel concepts in receptor tyrosine kinase (RTK) signaling. Among these contributions are the elucidation of HS-assisted receptor dimerization, delineation of the molecular determinants of ligand–receptor specificity, tyrosine kinase regulation, receptor cis-autoinhibition, and tyrosine trans-autophosphorylation. These structural studies have also revealed how disease-associated mutations highjack the physiological mechanisms of FGFR regulation to contribute to human diseases. In this paper, we will discuss the structurally and biophysically derived mechanisms of FGF signaling, and how the insights gained may guide the development of therapies for treatment of a diverse array of human diseases. PMID:23732477
Molecular mechanisms of fibroblast growth factor signaling in physiology and pathology.
Belov, Artur A; Mohammadi, Moosa
2013-06-01
Fibroblast growth factors (FGFs) signal in a paracrine or endocrine fashion to mediate a myriad of biological activities, ranging from issuing developmental cues, maintaining tissue homeostasis, and regulating metabolic processes. FGFs carry out their diverse functions by binding and dimerizing FGF receptors (FGFRs) in a heparan sulfate (HS) cofactor- or Klotho coreceptor-assisted manner. The accumulated wealth of structural and biophysical data in the past decade has transformed our understanding of the mechanism of FGF signaling in human health and development, and has provided novel concepts in receptor tyrosine kinase (RTK) signaling. Among these contributions are the elucidation of HS-assisted receptor dimerization, delineation of the molecular determinants of ligand-receptor specificity, tyrosine kinase regulation, receptor cis-autoinhibition, and tyrosine trans-autophosphorylation. These structural studies have also revealed how disease-associated mutations highjack the physiological mechanisms of FGFR regulation to contribute to human diseases. In this paper, we will discuss the structurally and biophysically derived mechanisms of FGF signaling, and how the insights gained may guide the development of therapies for treatment of a diverse array of human diseases.
Discriminative Ocular Artifact Correction for Feature Learning in EEG Analysis.
Xinyang Li; Cuntai Guan; Haihong Zhang; Kai Keng Ang
2017-08-01
Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain-computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels available for independent component analysis based ocular artifact removal. It is even more challenging to avoid loss of the signal of interest during the artifact correction process, where the signal of interest can be multiple magnitudes weaker than the artifact. To address these issues, we propose a novel discriminative ocular artifact correction approach for feature learning in EEG analysis. Without extra ocular movement measurements, the artifact is extracted from raw EEG data, which is totally automatic and requires no visual inspection of artifacts. Then, artifact correction is optimized jointly with feature extraction by maximizing oscillatory correlations between trials from the same class and minimizing them between trials from different classes. We evaluate this approach on a real-world EEG dataset comprising 68 subjects performing cognitive tasks. The results showed that the approach is capable of not only suppressing the artifact components but also improving the discriminative power of a classifier with statistical significance. We also demonstrate that the proposed method addresses the confounding issues induced by ocular movements in cognitive EEG study.
García-Gómez, Joaquín; Rosa-Zurera, Manuel; Romero-Camacho, Antonio; Jiménez-Garrido, Jesús Antonio; García-Benavides, Víctor
2018-01-01
Pipeline inspection is a topic of particular interest to the companies. Especially important is the defect sizing, which allows them to avoid subsequent costly repairs in their equipment. A solution for this issue is using ultrasonic waves sensed through Electro-Magnetic Acoustic Transducer (EMAT) actuators. The main advantage of this technology is the absence of the need to have direct contact with the surface of the material under investigation, which must be a conductive one. Specifically interesting is the meander-line-coil based Lamb wave generation, since the directivity of the waves allows a study based in the circumferential wrap-around received signal. However, the variety of defect sizes changes the behavior of the signal when it passes through the pipeline. Because of that, it is necessary to apply advanced techniques based on Smart Sound Processing (SSP). These methods involve extracting useful information from the signals sensed with EMAT at different frequencies to obtain nonlinear estimations of the depth of the defect, and to select the features that better estimate the profile of the pipeline. The proposed technique has been tested using both simulated and real signals in steel pipelines, obtaining good results in terms of Root Mean Square Error (RMSE). PMID:29518927
Managing the cellular redox hub in photosynthetic organisms.
Foyer, Christine H; Noctor, Graham
2012-02-01
Light-driven redox chemistry is a powerful source of redox signals that has a decisive input into transcriptional control within the cell nucleus. Like photosynthetic electron transport pathways, the respiratory electron transport chain exerts a profound control over gene function, in order to balance energy (reductant and ATP) supply with demand, while preventing excessive over-reduction or over-oxidation that would be adversely affect metabolism. Photosynthetic and respiratory redox chemistries are not merely housekeeping processes but they exert a controlling influence over every aspect of plant biology, participating in the control of gene transcription and translation, post-translational modifications and the regulation of assimilatory reactions, assimilate partitioning and export. The number of processes influenced by redox controls and signals continues to increase as do the components that are recognized participants in the associated signalling pathways. A step change in our understanding of the overall importance of the cellular redox hub to plant cells has occurred in recent years as the complexity of the management of the cellular redox hub in relation to metabolic triggers and environmental cues has been elucidated. This special issue describes aspects of redox regulation and signalling at the cutting edge of current research in this dynamic and rapidly expanding field. © 2011 Blackwell Publishing Ltd.
Study for new hardmask process scheme
NASA Astrophysics Data System (ADS)
Lee, Daeyoup; Tatti, Phillip; Lee, Richard; Chang, Jack; Cho, Winston; Bae, Sanggil
2017-03-01
Hardmask processes are a key technique to enable low-k semiconductors, but they can have an impact on patterning control, influencing defectivity, alignment, and overlay. Specifically, amorphous carbon layer (ACL) hardmask schemes can negatively affect overlay by creating distorted alignment signals. A new scheme needs to be developed that can be inserted where amorphous carbon is used but provide better alignment performance. Typical spin-on carbon (SOC) materials used in other hardmask schemes have issues with DCD-FCD skew. In this paper we will evaluate new spin-on carbon material with a higher carbon content that could be a candidate to replace amorphous carbon.
Experimental studies of breaking of elastic tired wheel under variable normal load
NASA Astrophysics Data System (ADS)
Fedotov, A. I.; Zedgenizov, V. G.; Ovchinnikova, N. I.
2017-10-01
The paper analyzes the braking of a vehicle wheel subjected to disturbances of normal load variations. Experimental tests and methods for developing test modes as sinusoidal force disturbances of the normal wheel load were used. Measuring methods for digital and analogue signals were used as well. Stabilization of vehicle wheel braking subjected to disturbances of normal load variations is a topical issue. The paper suggests a method for analyzing wheel braking processes under disturbances of normal load variations. A method to control wheel baking processes subjected to disturbances of normal load variations was developed.
Rapid prototyping of update algorithm of discrete Fourier transform for real-time signal processing
NASA Astrophysics Data System (ADS)
Kakad, Yogendra P.; Sherlock, Barry G.; Chatapuram, Krishnan V.; Bishop, Stephen
2001-10-01
An algorithm is developed in the companion paper, to update the existing DFT to represent the new data series that results when a new signal point is received. Updating the DFT in this way uses less computation than directly evaluating the DFT using the FFT algorithm, This reduces the computational order by a factor of log2 N. The algorithm is able to work in the presence of data window function, for use with rectangular window, the split triangular, Hanning, Hamming, and Blackman windows. In this paper, a hardware implementation of this algorithm, using FPGA technology, is outlined. Unlike traditional fully customized VLSI circuits, FPGAs represent a technical break through in the corresponding industry. The FPGA implements thousands of gates of logic in a single IC chip and it can be programmed by users at their site in a few seconds or less depending on the type of device used. The risk is low and the development time is short. The advantages have made FPGAs very popular for rapid prototyping of algorithms in the area of digital communication, digital signal processing, and image processing. Our paper addresses the related issues of implementation using hardware descriptive language in the development of the design and the subsequent downloading on the programmable hardware chip.
Research on APD-based non-line-of-sight UV communication system
NASA Astrophysics Data System (ADS)
Wang, Rongyang; Wang, Ling; Li, Chao; Zhang, Wenjing; Yuan, Yonggang; Xu, Jintong; Zhang, Yan; Li, Xiangyang
2010-10-01
In this paper, specific issues in designing an avalanche photodiode (APD)-based non-line-of-sight (NLOS) ultraviolet (UV) communication system are investigated. A proper wavelength of the UV LEDs and a system configuration should be considered carefully to assure the feasibility of this system. Using the single scattering model, the received optical power at the sensitive area of the APD can be calculated. According to the calculation, it revealed that the scattered ultraviolet signal level was very low; therefore, a post signal processing circuit was necessary. The authors put forward the key components of the circuit based on the compromise between signal bandwidth and gain. The performance of this circuit was evaluated by means of software simulation, and continued work was involved to improve its signal noise ratio (SNR). The transmitter used in this system was 365 nm UV LED array. Strictly speaking, this was not the practical outdoor UV communication system. Since the scattering coefficient of 365 nm UV only drops a little compared with solar blind UV, the research-grade UV communication could be carried out in a darkroom without a great influence. By combining an APD with a compound parabolic concentrator (CPC) optical system, the effective collection area and field of view (FOV) of the detector could be adjusted. Several issues were also raised to improve the performance of UV communication system, including using more powerful UV LEDs and choosing suitable modulation schemes.
DOT National Transportation Integrated Search
2002-10-01
The success of automation for intelligent transportation systems is ultimately contingent upon the Interface between the users (humans) and the system (ITS). The issues of variable message signs (VMS) and traffic signal device (TSD) design were studi...
Huang, Ming-Xiong; Anderson, Bill; Huang, Charles W.; Kunde, Gerd J.; Vreeland, Erika C.; Huang, Jeffrey W.; Matlashov, Andrei N.; Karaulanov, Todor; Nettles, Christopher P.; Gomez, Andrew; Minser, Kayla; Weldon, Caroline; Paciotti, Giulio; Harsh, Michael; Lee, Roland R.; Flynn, Edward R.
2017-01-01
Superparamagnetic Relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using Super-conducting Quantum Interference Device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: 1) remove trials contaminated with artifacts, 2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, 3) automatically detect and correct flux jumps, and 4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings. PMID:28072579
A comparison of earthquake backprojection imaging methods for dense local arrays
NASA Astrophysics Data System (ADS)
Beskardes, G. D.; Hole, J. A.; Wang, K.; Michaelides, M.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Brown, L. D.; Quiros, D. A.
2018-03-01
Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-term averaging/long-term averaging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveform method to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.
Single-Event Transient Testing of Low Dropout PNP Series Linear Voltage Regulators
NASA Technical Reports Server (NTRS)
Adell, Philippe; Allen, Gregory
2013-01-01
As demand for high-speed, on-board, digital-processing integrated circuits on spacecraft increases (field-programmable gate arrays and digital signal processors in particular), the need for the next generation point-of-load (POL) regulator becomes a prominent design issue. Shrinking process nodes have resulted in core rails dropping to values close to 1.0 V, drastically reducing margin to standard switching converters or regulators that power digital ICs. The goal of this task is to perform SET characterization of several commercial POL converters, and provide a discussion of the impact of these results to state-of-the-art digital processing IC through laser and heavy ion testing
Tracer SWIW tests in propped and un-propped fractures: parameter sensitivity issues, revisited
NASA Astrophysics Data System (ADS)
Ghergut, Julia; Behrens, Horst; Sauter, Martin
2017-04-01
Single-well injection-withdrawal (SWIW) or 'push-then-pull' tracer methods appear attractive for a number of reasons: less uncertainty on design and dimensioning, and lower tracer quantities required than for inter-well tests; stronger tracer signals, enabling easier and cheaper metering, and shorter metering duration required, reaching higher tracer mass recovery than in inter-well tests; last not least: no need for a second well. However, SWIW tracer signal inversion faces a major issue: the 'push-then-pull' design weakens the correlation between tracer residence times and georeservoir transport parameters, inducing insensitivity or ambiguity of tracer signal inversion w. r. to some of those georeservoir parameters that are supposed to be the target of tracer tests par excellence: pore velocity, transport-effective porosity, fracture or fissure aperture and spacing or density (where applicable), fluid/solid or fluid/fluid phase interface density. Hydraulic methods cannot measure the transport-effective values of such parameters, because pressure signals correlate neither with fluid motion, nor with material fluxes through (fluid-rock, or fluid-fluid) phase interfaces. The notorious ambiguity impeding parameter inversion from SWIW test signals has nourished several 'modeling attitudes': (i) regard dispersion as the key process encompassing whatever superposition of underlying transport phenomena, and seek a statistical description of flow-path collectives enabling to characterize dispersion independently of any other transport parameter, as proposed by Gouze et al. (2008), with Hansen et al. (2016) offering a comprehensive analysis of the various ways dispersion model assumptions interfere with parameter inversion from SWIW tests; (ii) regard diffusion as the key process, and seek for a large-time, asymptotically advection-independent regime in the measured tracer signals (Haggerty et al. 2001), enabling a dispersion-independent characterization of multiple-scale diffusion; (iii) attempt to determine both advective and non-advective transport parameters from one and the same conservative-tracer signal (relying on 'third-party' knowledge), or from twin signals of a so-called 'dual' tracer pair, e. g.: using tracers with contrasting reactivity and partitioning behavior to determine residual saturation in depleted oilfields (Tomich et al. 1973), or to determine advective parameters (Ghergut et al. 2014); using early-time signals of conservative and sorptive tracers for propped-fracture characterization (Karmakar et al. 2015); using mid-time signals of conservative tracers for a reservoir-borne inflow profiling in multi-frac systems (Ghergut et al. 2016), etc. The poster describes new uses of type-(iii) techniques for the specific purposes of shale-gas reservoir characterization, productivity monitoring, diagnostics and engineering of 're-frac' treatments, based on parameter sensitivity findings from German BMWi research project "TRENDS" (Federal Ministry for Economic Affairs and Energy, FKZ 0325515) and from the EU-H2020 project "FracRisk" (grant no. 640979).
Evaluating the Safety Profile of Non-Active Implantable Medical Devices Compared with Medicines.
Pane, Josep; Coloma, Preciosa M; Verhamme, Katia M C; Sturkenboom, Miriam C J M; Rebollo, Irene
2017-01-01
Recent safety issues involving non-active implantable medical devices (NAIMDs) have highlighted the need for better pre-market and post-market evaluation. Some stakeholders have argued that certain features of medicine safety evaluation should also be applied to medical devices. Our objectives were to compare the current processes and methodologies for the assessment of NAIMD safety profiles with those for medicines, identify potential gaps, and make recommendations for the adoption of new methodologies for the ongoing benefit-risk monitoring of these devices throughout their entire life cycle. A literature review served to examine the current tools for the safety evaluation of NAIMDs and those for medicines. We searched MEDLINE using these two categories. We supplemented this search with Google searches using the same key terms used in the MEDLINE search. Using a comparative approach, we summarized the new product design, development cycle (preclinical and clinical phases), and post-market phases for NAIMDs and drugs. We also evaluated and compared the respective processes to integrate and assess safety data during the life cycle of the products, including signal detection, signal management, and subsequent potential regulatory actions. The search identified a gap in NAIMD safety signal generation: no global program exists that collects and analyzes adverse events and product quality issues. Data sources in real-world settings, such as electronic health records, need to be effectively identified and explored as additional sources of safety information, particularly in some areas such as the EU and USA where there are plans to implement the unique device identifier (UDI). The UDI and other initiatives will enable more robust follow-up and assessment of long-term patient outcomes. The safety evaluation system for NAIMDs differs in many ways from those for drugs, but both systems face analogous challenges with respect to monitoring real-world usage. Certain features of the drug safety evaluation process could, if adopted and adapted for NAIMDs, lead to better and more systematic evaluations of the latter.
Timing issues for traffic signals interconnected with highway-railroad grade crossings.
DOT National Transportation Integrated Search
2013-02-01
The coordination of highway-railroad grade crossing warning signals with nearby traffic signals is of vital : importance due to potential safety consequences. Interconnections between traffic signals in close : proximity to railroad crossings provide...
The technology on noise reduction of the APD detection circuit
NASA Astrophysics Data System (ADS)
Wu, Xue-ying; Zheng, Yong-chao; Cui, Jian-yong
2013-09-01
The laser pulse detection is widely used in the field of laser range finders, laser communications, laser radar, laser Identification Friend or Foe, et al, for the laser pulse detection has the advantage of high accuracy, high sensitivity and strong anti-interference. The avalanche photodiodes (APD) has the advantage of high quantum efficiency, high response speed and huge gain. The APD is particularly suitable for weak signal detection. The technology that APD acts as the photodetector for weak signal reception and amplification is widely used in laser pulse detection. The APD will convert the laser signal to weak electrical signal. The weak signal is amplified, processed and exported by the circuit. In the circuit design, the optimal signal detection is one key point in photoelectric detection system. The issue discusses how to reduce the noise of the photoelectric signal detection circuit and how to improve the signal-to-noise ratio, related analysis and practice included. The essay analyzes the mathematical model of the signal-to-noise ratio for photoelectric conversion and the noise of the APD photoelectric detection system. By analysis the bandwidth of the detection system is determined, and the circuit devices are selected that match the APD. In the circuit design separated devices with low noise are combined with integrated operational amplifier for the purpose of noise reduction. The methods can effectively suppress the noise, and improve the detection sensitivity.
Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.
Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein
2017-12-13
As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms 1D wavelet.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martino, Mikaël M.; Briquez, Priscilla S.; Maruyama, Kenta
Growth factors are very promising molecules to enhance bone regeneration. However, their translation to clinical use has been seriously limited, facing issues related to safety and cost-effectiveness. These problems derive from the vastly supra-physiological doses of growth factor used without optimized delivery systems. Therefore, these issues have motivated the development of new delivery systems allowing better control of the spatio-temporal release and signaling of growth factors. Because the extracellular matrix (ECM) naturally plays a fundamental role in coordinating growth factor activity in vivo, a number of novel delivery systems have been inspired by the growth factor regulatory function of themore » ECM. After introducing the role of growth factors during the bone regeneration process, this review exposes different issues that growth factor-based therapies have encountered in the clinic and highlights recent delivery approaches based on the natural interaction between growth factor and the ECM.« less
1990-04-01
tiltmeters and a few electric field sensors would be useful. Ancillary environmental measurements will also be needed. These should include sensors to...Applied research issues such as sensor development, technological improvements, and signal processing needs are not specifically addressed. This is... sensors of increased sensitivity. A submarine may have static magnetic and electric dipole moments caused by residual mag- netization of the machinery and
A near death experience: Shigella manipulates host death machinery to silence innate immunity.
Bronner, Denise N; O'Riordan, Mary Xd
2014-10-01
Release of mitochondrial contents often triggers inflammation and cell death, and modulating this process can be advantageous to invading pathogens. In this issue of The EMBO Journal, Andree and colleagues reveal new findings that an intracellular bacterial pathogen exploits apoptotic machinery to suppress host immune signaling, yet avoids cell death. This study emphasizes the need to expand our understanding of the roles played by pro‐apoptotic proteins in non‐death scenarios.
Turuk, Mousami; Dhande, Ashwin
2018-04-01
The recent innovations in information and communication technologies have appreciably changed the panorama of health information system (HIS). These advances provide new means to process, handle, and share medical images and also augment the medical image security issues in terms of confidentiality, reliability, and integrity. Digital watermarking has emerged as new era that offers acceptable solutions to the security issues in HIS. Texture is a significant feature to detect the embedding sites in an image, which further leads to substantial improvement in the robustness. However, considering the perspective of digital watermarking, this feature has received meager attention in the reported literature. This paper exploits the texture property of an image and presents a novel hybrid texture-quantization-based approach for reversible multiple watermarking. The watermarked image quality has been accessed by peak signal to noise ratio (PSNR), structural similarity measure (SSIM), and universal image quality index (UIQI), and the obtained results are superior to the state-of-the-art methods. The algorithm has been evaluated on a variety of medical imaging modalities (CT, MRA, MRI, US) and robustness has been verified, considering various image processing attacks including JPEG compression. The proposed scheme offers additional security using repetitive embedding of BCH encoded watermarks and ADM encrypted ECG signal. Experimental results achieved a maximum of 22,616 bits hiding capacity with PSNR of 53.64 dB.
NASA Astrophysics Data System (ADS)
Huang, Weilin; Wang, Runqiu; Chen, Yangkang
2018-05-01
Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.
Effects of subconscious and conscious emotions on human cue–reward association learning
Watanabe, Noriya; Haruno, Masahiko
2015-01-01
Life demands that we adapt our behaviour continuously in situations in which much of our incoming information is emotional and unrelated to our immediate behavioural goals. Such information is often processed without our consciousness. This poses an intriguing question of whether subconscious exposure to irrelevant emotional information (e.g. the surrounding social atmosphere) affects the way we learn. Here, we addressed this issue by examining whether the learning of cue-reward associations changes when an emotional facial expression is shown subconsciously or consciously prior to the presentation of a reward-predicting cue. We found that both subconscious (0.027 s and 0.033 s) and conscious (0.047 s) emotional signals increased the rate of learning, and this increase was smallest at the border of conscious duration (0.040 s). These data suggest not only that the subconscious and conscious processing of emotional signals enhances value-updating in cue–reward association learning, but also that the computational processes underlying the subconscious enhancement is at least partially dissociable from its conscious counterpart. PMID:25684237
Fourier-based classification of protein secondary structures.
Shu, Jian-Jun; Yong, Kian Yan
2017-04-15
The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to classify protein secondary structures, but are faced with a significant number of misclassifications. The paper presents a technique for the classification of protein secondary structures based on protein "signal-plotting" and the use of the Fourier technique for digital signal processing. New indices are proposed to classify protein secondary structures by analyzing hydrophobicity profiles. The approach is simple and straightforward. Results show that the more types of protein secondary structures can be classified by means of these newly-proposed indices. Copyright © 2017 Elsevier Inc. All rights reserved.
Climate Change, CO2, and Defense: The Metabolic, Redox, and Signaling Perspectives.
Noctor, Graham; Mhamdi, Amna
2017-10-01
Ongoing human-induced changes in the composition of the atmosphere continue to stimulate interest in the effects of high CO 2 on plants, but its potential impact on inducible plant defense pathways remains poorly defined. Recently, several studies have reported that growth at elevated CO 2 is sufficient to induce defenses such as the salicylic acid pathway, thereby increasing plant resistance to pathogens. These reports contrast with evidence that defense pathways can be promoted by photorespiration, which is inhibited at high CO 2 . Here, we review signaling, metabolic, and redox processes modulated by CO 2 levels and discuss issues to be resolved in elucidating the relationships between primary metabolism, inducible defense, and biotic stress resistance. Copyright © 2017 Elsevier Ltd. All rights reserved.
Near DC force measurement using PVDF sensors
NASA Astrophysics Data System (ADS)
Ramanathan, Arun Kumar; Headings, Leon M.; Dapino, Marcelo J.
2018-03-01
There is a need for high-performance force sensors capable of operating at frequencies near DC while producing a minimal mass penalty. Example application areas include steering wheel sensors, powertrain torque sensors, robotic arms, and minimally invasive surgery. The beta crystallographic phase polyvinylidene fluoride (PVDF) films are suitable for this purpose owing to their large piezoelectric constant. Unlike conventional capacitive sensors, beta crystallographic phase PVDF films exhibit a broad linear range and can potentially be designed to operate without complex electronics or signal processing. A fundamental challenge that prevents the implementation of PVDF in certain high-performance applications is their inability to measure static signals, which results from their first-order electrical impedance. Charge readout algorithms have been implemented which address this issue only partially, as they often require integration of the output signal to obtain the applied force profile, resulting in signal drift and signal processing complexities. In this paper, we propose a straightforward real time drift compensation strategy that is applicable to high output impedance PVDF films. This strategy makes it possible to utilize long sample times with a minimal loss of accuracy; our measurements show that the static output remains within 5% of the original value during half-hour measurements. The sensitivity and full-scale range are shown to be determined by the feedback capacitance of the charge amplifier. A linear model of the PVDF sensor system is developed and validated against experimental measurements, along with benchmark tests against a commercial load cell.
Signalling mechanisms in autophagy: an introduction to the issue.
Lane, Jon D; Korolchuk, Viktor I; Murray, James T
2017-12-12
Essays in Biochemistry volume 61 (issue 6), entitled Signalling Mechanisms in Autophagy , covers a range of topics in autophagy signalling, touching on emerging new details on the mechanisms of autophagy regulation, novel aspects of selective autophagy and how autophagy functions in organelle homeostasis. It also looks at how autophagy research is leading to better understanding of human disease and plant biology that can be exploited for the benefit of society. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
Real-time processing of radar return on a parallel computer
NASA Technical Reports Server (NTRS)
Aalfs, David D.
1992-01-01
NASA is working with the FAA to demonstrate the feasibility of pulse Doppler radar as a candidate airborne sensor to detect low altitude windshears. The need to provide the pilot with timely information about possible hazards has motivated a demand for real-time processing of a radar return. Investigated here is parallel processing as a means of accommodating the high data rates required. A PC based parallel computer, called the transputer, is used to investigate issues in real time concurrent processing of radar signals. A transputer network is made up of an array of single instruction stream processors that can be networked in a variety of ways. They are easily reconfigured and software development is largely independent of the particular network topology. The performance of the transputer is evaluated in light of the computational requirements. A number of algorithms have been implemented on the transputers in OCCAM, a language specially designed for parallel processing. These include signal processing algorithms such as the Fast Fourier Transform (FFT), pulse-pair, and autoregressive modelling, as well as routing software to support concurrency. The most computationally intensive task is estimating the spectrum. Two approaches have been taken on this problem, the first and most conventional of which is to use the FFT. By using table look-ups for the basis function and other optimizing techniques, an algorithm has been developed that is sufficient for real time. The other approach is to model the signal as an autoregressive process and estimate the spectrum based on the model coefficients. This technique is attractive because it does not suffer from the spectral leakage problem inherent in the FFT. Benchmark tests indicate that autoregressive modeling is feasible in real time.
Stochastic characterization of small-scale algorithms for human sensory processing
NASA Astrophysics Data System (ADS)
Neri, Peter
2010-12-01
Human sensory processing can be viewed as a functional H mapping a stimulus vector s into a decisional variable r. We currently have no direct access to r; rather, the human makes a decision based on r in order to drive subsequent behavior. It is this (typically binary) decision that we can measure. For example, there may be two external stimuli s[0] and s[1], mapped onto r[0] and r[1] by the sensory apparatus H; the human chooses the stimulus associated with largest r. This kind of decisional transduction poses a major challenge for an accurate characterization of H. In this article, we explore a specific approach based on a behavioral variant of reverse correlation techniques, where the input s contains a target signal corrupted by a controlled noisy perturbation. The presence of the target signal poses an additional challenge because it distorts the otherwise unbiased nature of the noise source. We consider issues arising from both the decisional transducer and the target signal, their impact on system identification, and ways to handle them effectively for system characterizations that extend to second-order functional approximations with associated small-scale cascade models.
A joint signal processing and cryptographic approach to multimedia encryption.
Mao, Yinian; Wu, Min
2006-07-01
In recent years, there has been an increasing trend for multimedia applications to use delegate service providers for content distribution, archiving, search, and retrieval. These delegate services have brought new challenges to the protection of multimedia content confidentiality. This paper discusses the importance and feasibility of applying a joint signal processing and cryptographic approach to multimedia encryption, in order to address the access control issues unique to multimedia applications. We propose two atomic encryption operations that can preserve standard compliance and are friendly to delegate processing. Quantitative analysis for these operations is presented to demonstrate that a good tradeoff can be made between security and bitrate overhead. In assisting the design and evaluation of media security systems, we also propose a set of multimedia-oriented security scores to quantify the security against approximation attacks and to complement the existing notion of generic data security. Using video as an example, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. The resulting system can provide superior performance over both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and friendliness to delegate processing.
DOT National Transportation Integrated Search
2015-03-01
This report concerns two issues: 1) whether color vision is necessary for locomotive crews who work on railroads where the signal system is either completely redundant with regard to signal color and signal orientation or the signal system only uses ...
Imaging the cell surface and its organization down to the level of single molecules.
Klenerman, David; Shevchuk, Andrew; Novak, Pavel; Korchev, Yuri E; Davis, Simon J
2013-02-05
Determining the organization of key molecules on the surface of live cells in two dimensions and how this changes during biological processes, such as signalling, is a major challenge in cell biology and requires methods with nanoscale spatial resolution and high temporal resolution. Here, we review biophysical tools, based on scanning ion conductance microscopy and single-molecule fluorescence and the combination of both of these methods, which have recently been developed to address these issues. We then give examples of how these methods have been be applied to provide new insights into cell membrane organization and function, and discuss some of the issues that will need to be addressed to further exploit these methods in the future.
Neuronal basis of speech comprehension.
Specht, Karsten
2014-01-01
Verbal communication does not rely only on the simple perception of auditory signals. It is rather a parallel and integrative processing of linguistic and non-linguistic information, involving temporal and frontal areas in particular. This review describes the inherent complexity of auditory speech comprehension from a functional-neuroanatomical perspective. The review is divided into two parts. In the first part, structural and functional asymmetry of language relevant structures will be discus. The second part of the review will discuss recent neuroimaging studies, which coherently demonstrate that speech comprehension processes rely on a hierarchical network involving the temporal, parietal, and frontal lobes. Further, the results support the dual-stream model for speech comprehension, with a dorsal stream for auditory-motor integration, and a ventral stream for extracting meaning but also the processing of sentences and narratives. Specific patterns of functional asymmetry between the left and right hemisphere can also be demonstrated. The review article concludes with a discussion on interactions between the dorsal and ventral streams, particularly the involvement of motor related areas in speech perception processes, and outlines some remaining unresolved issues. This article is part of a Special Issue entitled Human Auditory Neuroimaging. Copyright © 2013 Elsevier B.V. All rights reserved.
Transit signal priority research tools
DOT National Transportation Integrated Search
2008-05-01
This report presents the results of a research project that addresses Transit Signal Priority (TSP) deployment issues. The report reviews National Transportation Communications for ITS Protocol (NTCIP) 1211 Signal Control and Prioritization (SCP) sta...
Analog nonlinear MIMO receiver for optical mode division multiplexing transmission.
Spalvieri, Arnaldo; Boffi, Pierpaolo; Pecorino, Simone; Barletta, Luca; Magarini, Maurizio; Gatto, Alberto; Martelli, Paolo; Martinelli, Mario
2013-10-21
The complexity and the power consumption of digital signal processing are crucial issues in optical transmission systems based on mode division multiplexing and coherent multiple-input multiple-output (MIMO) processing at the receiver. In this paper the inherent characteristic of spatial separation between fiber modes is exploited, getting a MIMO system where joint demultiplexing and detection is based on spatially separated photodetectors. After photodetection, one has a MIMO system with nonlinear crosstalk between modes. The paper shows that the nonlinear crosstalk can be dealt with by a low-complexity and non-adaptive detection scheme, at least in the cases presented in the paper.
Hardy, Chris J D; Agustus, Jennifer L; Marshall, Charles R; Clark, Camilla N; Russell, Lucy L; Bond, Rebecca L; Brotherhood, Emilie V; Thomas, David L; Crutch, Sebastian J; Rohrer, Jonathan D; Warren, Jason D
2017-07-27
Non-verbal auditory impairment is increasingly recognised in the primary progressive aphasias (PPAs) but its relationship to speech processing and brain substrates has not been defined. Here we addressed these issues in patients representing the non-fluent variant (nfvPPA) and semantic variant (svPPA) syndromes of PPA. We studied 19 patients with PPA in relation to 19 healthy older individuals. We manipulated three key auditory parameters-temporal regularity, phonemic spectral structure and prosodic predictability (an index of fundamental information content, or entropy)-in sequences of spoken syllables. The ability of participants to process these parameters was assessed using two-alternative, forced-choice tasks and neuroanatomical associations of task performance were assessed using voxel-based morphometry of patients' brain magnetic resonance images. Relative to healthy controls, both the nfvPPA and svPPA groups had impaired processing of phonemic spectral structure and signal predictability while the nfvPPA group additionally had impaired processing of temporal regularity in speech signals. Task performance correlated with standard disease severity and neurolinguistic measures. Across the patient cohort, performance on the temporal regularity task was associated with grey matter in the left supplementary motor area and right caudate, performance on the phoneme processing task was associated with grey matter in the left supramarginal gyrus, and performance on the prosodic predictability task was associated with grey matter in the right putamen. Our findings suggest that PPA syndromes may be underpinned by more generic deficits of auditory signal analysis, with a distributed cortico-subcortical neuraoanatomical substrate extending beyond the canonical language network. This has implications for syndrome classification and biomarker development.
Signal amplification of microRNAs with modified strand displacement-based cycling probe technology.
Jia, Huning; Bu, Ying; Zou, Bingjie; Wang, Jianping; Kumar, Shalen; Pitman, Janet L; Zhou, Guohua; Song, Qinxin
2016-10-24
Micro ribose nucleic acids (miRNAs) play an important role in biological processes such as cell differentiation, proliferation and apoptosis. Therefore, miRNAs are potentially a powerful marker for monitoring cancer and diagnosis. Here, we present sensitive signal amplification for miRNAs based on modified cycling probe technology with strand displacement amplification. miRNA was captured by the template coupled with beads, and then the first cycle based on SDA was repeatedly extended to the nicking end, which was produced by the extension reaction of miRNA. The products generated by SDA are captured by a molecular beacon (MB), which is designed to initiate the second amplification cycle, with a similar principle to the cycling probe technology (CPT), which is based on repeated digestion of the DNA-RNA hybrid by the RNase H. After one sample enrichment and two steps of signal amplification, 0.1 pM of let-7a can be detected. The miRNA assay exhibits a great dynamic range of over 100 orders of magnitude and high specificity to clearly discriminate a single base difference in miRNA sequences. This isothermal amplification does not require any special temperature control instrument. The assay is also about signal amplification rather than template amplification, therefore minimising contamination issues. In addition, there is no need for the reverse transcription (RT) process. Thus the amplification is suitable for miRNA detection.
A CWT-based methodology for piston slap experimental characterization
NASA Astrophysics Data System (ADS)
Buzzoni, M.; Mucchi, E.; Dalpiaz, G.
2017-03-01
Noise and vibration control in mechanical systems has become ever more significant for automotive industry where the comfort of the passenger compartment represents a challenging issue for car manufacturers. The reduction of piston slap noise is pivotal for a good design of IC engines. In this scenario, a methodology has been developed for the vibro-acoustic assessment of IC diesel engines by means of design changes in piston to cylinder bore clearance. Vibration signals have been analysed by means of advanced signal processing techniques taking advantage of cyclostationarity theory. The procedure departs from the analysis of the Continuous Wavelet Transform (CWT) in order to identify a representative frequency band of piston slap phenomenon. Such a frequency band has been exploited as the input data in the further signal processing analysis that involves the envelope analysis of the second order cyclostationary component of the signal. The second order harmonic component has been used as the benchmark parameter of piston slap noise. An experimental procedure of vibrational benchmarking is proposed and verified at different operational conditions in real IC engines actually equipped on cars. This study clearly underlines the crucial role of the transducer positioning when differences among real piston-to-cylinder clearances are considered. In particular, the proposed methodology is effective for the sensors placed on the outer cylinder wall in all the tested conditions.
Diwakar, Prasoon K.; Harilal, Sivanandan S.; LaHaye, Nicole L.; Hassanein, Ahmed; Kulkarni, Pramod
2015-01-01
Laser parameters, typically wavelength, pulse width, irradiance, repetition rate, and pulse energy, are critical parameters which influence the laser ablation process and thereby influence the LA-ICP-MS signal. In recent times, femtosecond laser ablation has gained popularity owing to the reduction in fractionation related issues and improved analytical performance which can provide matrix-independent sampling. The advantage offered by fs-LA is due to shorter pulse duration of the laser as compared to the phonon relaxation time and heat diffusion time. Hence the thermal effects are minimized in fs-LA. Recently, fs-LA-ICP-MS demonstrated improved analytical performance as compared to ns-LA-ICP-MS, but detailed mechanisms and processes are still not clearly understood. Improvement of fs-LA-ICP-MS over ns-LA-ICP-MS elucidates the importance of laser pulse duration and related effects on the ablation process. In this study, we have investigated the influence of laser pulse width (40 fs to 0.3 ns) and energy on LA-ICP-MS signal intensity and repeatability using a brass sample. Experiments were performed in single spot ablation mode as well as rastering ablation mode to monitor the Cu/Zn ratio. The recorded ICP-MS signal was correlated with total particle counts generated during laser ablation as well as particle size distribution. Our results show the importance of pulse width effects in the fs regime that becomes more pronounced when moving from femtosecond to picosecond and nanosecond regimes. PMID:26664120
Status of the Signals of Opportunity Airborne Demonstrator (SoOp-AD)
NASA Technical Reports Server (NTRS)
Garrison, Jim; Lin, Yao-Cheng; Piepmeier, Jeff; Knuble, Joe; Hersey, Ken; Du Toit, Cornelus; Joseph, Alicia; Deshpande, Manohar; Alikakos, George; O'Brien, Steve;
2016-01-01
Root zone soil moisture (RZSM) is not directly measured by any current satellite instrument, despite its importance as a key link between surface hydrology and deeper processes. Presently, model assimilation of surface measurements or indirect estimates using other methods must be used to estimate this value. Signals of Opportunity (SoOp) methods, exploiting reflected P- and S-band communication satellite signals, have many of the benefits of both active and passive microwave remote sensing. Reutilization of active transmitters, with forward-scattering geometry, presents a strong reflected signal even at orbital altitudes. Microwave radiometry is advantageous as it measures emissivity, which is directly related to dielectric constant and sensitive to water content of soil. Synthetic aperture radar (SAR) is used in P-band (400 MHz) for soil moisture and biomass, but faces issues in obtaining permission to transmit due to spectrum regulations, particularly over North America and Europe. A primary advantage of SAR is excellent spatial resolution. Signals-of-opportunity (SoOp) reflectometry provides a good compromise between radiometry and SAR by providing decent sensitivity and special resolution for RZSM measurements without issues of spectrum access. Further, a SoOp instrument would not be limited to operating in only a few protected frequencies and is also expected to have less susceptibility to radio-frequency interference (RFI). Although advantageous if available, SoOp techniques do not require the ability to demodulate or decode the communication signals. The SoOp instrument is receive only and therefore requires much less electrical power than a SAR and is more similar to a radiometer in receiver architecture. These unique features of SoOp circumvent past obstacles to a spaceborne P-band remote sensing mission and have the potential to enable new RZSM measurements that are not possible with present technology. We will present the latest development status of a SoOp reflectometer airborne demonstrator (SoOp-AD) operating at 250 MHz to take advantage of existing communication satellite. The instrument is currently in laboratory integration and test.
Foreman, Brady Z; Straub, Kyle M
2017-09-01
Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.
Open the gates: vascular neurocrine signaling mobilizes hematopoietic stem and progenitor cells.
Itkin, Tomer; Gómez-Salinero, Jesús María; Rafii, Shahin
2017-12-01
Mobilization of hematopoietic stem and progenitor cells (HSPCs) from the bone marrow (BM) into the peripheral blood is a complex process that is enhanced dramatically under stress-induced conditions. A better understanding of how the mobilization process is regulated will likely facilitate the development of improved clinical protocols for stem cell harvesting and transplantation. In this issue of the JCI, Singh et al. (1) showed that the truncated cleaved form of neurotransmitter neuropeptide Y (NPY) actively promotes a breach of BM vascular sinusoidal portals, thereby augmenting HSPC trafficking to the circulation. The authors report a previously unrecognized axis, in which expression of the enzyme dipeptidylpeptidase-4 (DPP4)/CD26 by endothelial cells activates NPY-mediated signaling by increasing the bioavailability of the truncated form of NPY. These findings underscore the importance of and urgency to develop pharmacological therapies that target the vasculature and regulate diverse aspects of hematopoiesis, such as HSPC trafficking, in steady-state and stress-induced conditions.
Foreman, Brady Z.; Straub, Kyle M.
2017-01-01
Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607
Changes in interoceptive processes following brain stimulation
Mai, Sandra
2016-01-01
The processing and perception of individual internal bodily signals (interoception) has been differentiated to comprise different levels and processes involved. The so-called heartbeat-evoked potential (HEP) offers an additional possibility to examine automatic processing of cardiac signals. Knowledge on neural structures potentially supporting different facets of interoception is still sparse. One way to get insights into neuroanatomical function is to manipulate the activity of different brain structures. In this study, we used repetitive transcranial magnetic stimulation (rTMS) and a continuous theta-burst protocol to inhibit specific central locations of the interoceptive network including the right anterior insula and the right somatosensory cortices and assessed effects on interoceptive facets and the HEP in 18 male participants. Main results were that inhibiting anterior insula resulted in a significant decline in cardiac and respiratory interoceptive accuracy (IAc) and in a consistent decrease in perception confidence. Continuous theta-burst stimulation (cTBS) over somatosensory cortices reduced only cardiac IAc and affected perception confidence. Inhibiting right anterior insula and right somatosensory cortices increased interoceptive sensibility and reduced the HEP amplitude over frontocentral locations. Our findings strongly suggest that cTBS is an effective tool to investigate the neural network supporting interoceptive processes. This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’. PMID:28080973
Multi-purpose ECG telemetry system.
Marouf, Mohamed; Vukomanovic, Goran; Saranovac, Lazar; Bozic, Miroslav
2017-06-19
The Electrocardiogram ECG is one of the most important non-invasive tools for cardiac diseases diagnosis. Taking advantage of the developed telecommunication infrastructure, several approaches that address the development of telemetry cardiac devices were introduced recently. Telemetry ECG devices allow easy and fast ECG monitoring of patients with suspected cardiac issues. Choosing the right device with the desired working mode, signal quality, and the device cost are still the main obstacles to massive usage of these devices. In this paper, we introduce design, implementation, and validation of a multi-purpose telemetry system for recording, transmission, and interpretation of ECG signals in different recording modes. The system consists of an ECG device, a cloud-based analysis pipeline, and accompanied mobile applications for physicians and patients. The proposed ECG device's mechanical design allows laypersons to easily record post-event short-term ECG signals, using dry electrodes without any preparation. Moreover, patients can use the device to record long-term signals in loop and holter modes, using wet electrodes. In order to overcome the problem of signal quality fluctuation due to using different electrodes types and different placements on subject's chest, customized ECG signal processing and interpretation pipeline is presented for each working mode. We present the evaluation of the novel short-term recorder design. Recording of an ECG signal was performed for 391 patients using a standard 12-leads golden standard ECG and the proposed patient-activated short-term post-event recorder. In the validation phase, a sample of validation signals followed peer review process wherein two experts annotated the signals in terms of signal acceptability for diagnosis.We found that 96% of signals allow detecting arrhythmia and other signal's abnormal changes. Additionally, we compared and presented the correlation coefficient and the automatic QRS delineation results of both short-term post-event recorder and 12-leads golden standard ECG recorder. The proposed multi-purpose ECG device allows physicians to choose the working mode of the same device according to the patient status. The proposed device was designed to allow patients to manage the technical requirements of both working modes. Post-event short-term ECG recording using the proposed design provide physicians reliable three ECG leads with direct symptom-rhythm correlation.
Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System
NASA Technical Reports Server (NTRS)
Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.
2006-01-01
Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion
Tacholess order-tracking approach for wind turbine gearbox fault detection
NASA Astrophysics Data System (ADS)
Wang, Yi; Xie, Yong; Xu, Guanghua; Zhang, Sicong; Hou, Chenggang
2017-09-01
Monitoring of wind turbines under variable-speed operating conditions has become an important issue in recent years. The gearbox of a wind turbine is the most important transmission unit; it generally exhibits complex vibration signatures due to random variations in operating conditions. Spectral analysis is one of the main approaches in vibration signal processing. However, spectral analysis is based on a stationary assumption and thus inapplicable to the fault diagnosis of wind turbines under variable-speed operating conditions. This constraint limits the application of spectral analysis to wind turbine diagnosis in industrial applications. Although order-tracking methods have been proposed for wind turbine fault detection in recent years, current methods are only applicable to cases in which the instantaneous shaft phase is available. For wind turbines with limited structural spaces, collecting phase signals with tachometers or encoders is difficult. In this study, a tacholess order-tracking method for wind turbines is proposed to overcome the limitations of traditional techniques. The proposed method extracts the instantaneous phase from the vibration signal, resamples the signal at equiangular increments, and calculates the order spectrum for wind turbine fault identification. The effectiveness of the proposed method is experimentally validated with the vibration signals of wind turbines.
A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions
Nazmi, Nurhazimah; Abdul Rahman, Mohd Azizi; Yamamoto, Shin-Ichiroh; Ahmad, Siti Anom; Zamzuri, Hairi; Mazlan, Saiful Amri
2016-01-01
In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:27548165
About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm
Peyraud, Sébastien; Bétaille, David; Renault, Stéphane; Ortiz, Miguel; Mougel, Florian; Meizel, Dominique; Peyret, François
2013-01-01
Reliable GPS positioning in city environment is a key issue actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results. PMID:23344379
NASA Astrophysics Data System (ADS)
Naumov, N. V.; Petrovskii, V. N.; Protsenko, E. D.; Shananin, R. A.
1995-10-01
Various information transmission systems, based on two-mode lasers with controlled emission frequencies, are proposed. It is suggested that these systems can be implemented by modulation of the intermode spacing of a two-mode laser. An experimental investigation is reported of frequency control methods. It is shown that these methods should make it possible to construct information transmission systems with high transmission rates subject to weak nonlinear distortions of the information-carrying signal.
Averaging Bias Correction for Future IPDA Lidar Mission MERLIN
NASA Astrophysics Data System (ADS)
Tellier, Yoann; Pierangelo, Clémence; Wirth, Martin; Gibert, Fabien
2018-04-01
The CNES/DLR
Ultrasonic sensing for noninvasive characterization of oil-water-gas flow in a pipe
NASA Astrophysics Data System (ADS)
Chillara, Vamshi Krishna; Sturtevant, Blake T.; Pantea, Cristian; Sinha, Dipen N.
2017-02-01
A technique for noninvasive ultrasonic characterization of multiphase crude oil-water-gas flow is discussed. The proposed method relies on determining the sound speed in the mixture. First, important issues associated with making real-time noninvasive measurements are discussed. Then, signal processing approach adopted to determine the sound speed in the multiphase mixture is presented. Finally, results from controlled experiments on crude oil-water mixture in both the presence and absence of gas are presented.
Combinatorial FSK modulation for power-efficient high-rate communications
NASA Technical Reports Server (NTRS)
Wagner, Paul K.; Budinger, James M.; Vanderaar, Mark J.
1991-01-01
Deep-space and satellite communications systems must be capable of conveying high-rate data accurately with low transmitter power, often through dispersive channels. A class of noncoherent Combinatorial Frequency Shift Keying (CFSK) modulation schemes is investigated which address these needs. The bit error rate performance of this class of modulation formats is analyzed and compared to the more traditional modulation types. Candidate modulator, demodulator, and digital signal processing (DSP) hardware structures are examined in detail. System-level issues are also discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, J.R.; Netrologic, Inc., San Diego, CA)
1988-01-01
Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.
Human factors research problems in electronic voice warning system design
NASA Technical Reports Server (NTRS)
Simpson, C. A.; Williams, D. H.
1975-01-01
The speech messages issued by voice warning systems must be carefully designed in accordance with general principles of human decision making processes, human speech comprehension, and the conditions in which the warnings can occur. The operator's effectiveness must not be degraded by messages that are either inappropriate or difficult to comprehend. Important experimental variables include message content, linguistic redundancy, signal/noise ratio, interference with concurrent tasks, and listener expectations generated by the pragmatic or real world context in which the messages are presented.
Making useful gadgets with miniaturized G proteins
Martemyanov, Kirill A.; Garcia-Marcos, Mikel
2018-01-01
G protein–coupled receptors (GPCRs) relay information from extracellular stimuli to intracellular responses in a wide range of physiological and pathological processes, but understanding their complex effects in live cells is a daunting task. In this issue of JBC, Wan et al. repurpose “mini G proteins”—previously used as affinity tools for structural studies—to develop a suite of probes to visualize GPCR activation in live cells. The approach is expected to revolutionize our understanding of the spatiotemporal control and mechanisms of GPCR signaling. PMID:29752421
Detecting and Quantifying Paleoseasonality in Stalagmites using Geochemical and Modelling Approaches
NASA Astrophysics Data System (ADS)
Baldini, J. U. L.
2017-12-01
Stalagmites are now well established sources of terrestrial paleoclimate information, providing insights into climate change on a variety of timescales. One of the most exciting aspects of stalagmites as climate archives is their ability to provide information regarding seasonality, a notoriously difficult component of climate change to characterise. However, stalagmite geochemistry may reflect not only the most apparent seasonal signal in external climate parameters, but also cave-specific signals such as seasonal changes in cave air carbon dioxide concentrations, sudden shifts in ventilation, and stochastic hydrological processes. Additionally, analytical bias may dampen or completely obfuscate any paleoseasonality, highlighting the need for appropriate quantification of this issue using simple models. Evidence from stalagmites now suggests that a seasonal signal is extractable from many samples, and that this signal can provide an important extra dimension to paleoclimate interpretations. Additionally, lower resolution annual- to decadal-scale isotope ratio records may also reflect shifts in seasonality, but identifying these is often challenging. Integrating geochemical datasets with models and cave monitoring data can greatly increase the accuracy of climate reconstructions, and yield the most robust records.
δ-Generalized Labeled Multi-Bernoulli Filter Using Amplitude Information of Neighboring Cells
Liu, Chao; Lei, Peng; Qi, Yaolong
2018-01-01
The amplitude information (AI) of echoed signals plays an important role in radar target detection and tracking. A lot of research shows that the introduction of AI enables the tracking algorithm to distinguish targets from clutter better and then improves the performance of data association. The current AI-aided tracking algorithms only consider the signal amplitude in the range-azimuth cell where measurement exists. However, since radar echoes always contain backscattered signals from multiple cells, the useful information of neighboring cells would be lost if directly applying those existing methods. In order to solve this issue, a new δ-generalized labeled multi-Bernoulli (δ-GLMB) filter is proposed. It exploits the AI of radar echoes from neighboring cells to construct a united amplitude likelihood ratio, and then plugs it into the update process and the measurement-track assignment cost matrix of the δ-GLMB filter. Simulation results show that the proposed approach has better performance in target’s state and number estimation than that of the δ-GLMB only using single-cell AI in low signal-to-clutter-ratio (SCR) environment. PMID:29642595
Regional operations : one approach to improve traffic signal timing.
DOT National Transportation Integrated Search
2016-11-11
In the 2014 Texas Transportation Poll, survey participants identified more effective traffic signal timing as the highest-rated strategy for resolving regional transportation issues (1). One way traffic engineers optimize traffic signal performance i...
Joint Bearing and Range Estimation of Multiple Objects from Time-Frequency Analysis.
Liu, Jeng-Cheng; Cheng, Yuang-Tung; Hung, Hsien-Sen
2018-01-19
Direction-of-arrival (DOA) and range estimation is an important issue of sonar signal processing. In this paper, a novel approach using Hilbert-Huang transform (HHT) is proposed for joint bearing and range estimation of multiple targets based on a uniform linear array (ULA) of hydrophones. The structure of this ULA based on micro-electro-mechanical systems (MEMS) technology, and thus has attractive features of small size, high sensitivity and low cost, and is suitable for Autonomous Underwater Vehicle (AUV) operations. This proposed target localization method has the following advantages: only a single snapshot of data is needed and real-time processing is feasible. The proposed algorithm transforms a very complicated nonlinear estimation problem to a simple nearly linear one via time-frequency distribution (TFD) theory and is verified with HHT. Theoretical discussions of resolution issue are also provided to facilitate the design of a MEMS sensor with high sensitivity. Simulation results are shown to verify the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Wang, Hongyan
2017-04-01
This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.
Advanced integrated enhanced vision systems
NASA Astrophysics Data System (ADS)
Kerr, J. R.; Luk, Chiu H.; Hammerstrom, Dan; Pavel, Misha
2003-09-01
In anticipation of its ultimate role in transport, business and rotary wing aircraft, we clarify the role of Enhanced Vision Systems (EVS): how the output data will be utilized, appropriate architecture for total avionics integration, pilot and control interfaces, and operational utilization. Ground-map (database) correlation is critical, and we suggest that "synthetic vision" is simply a subset of the monitor/guidance interface issue. The core of integrated EVS is its sensor processor. In order to approximate optimal, Bayesian multi-sensor fusion and ground correlation functionality in real time, we are developing a neural net approach utilizing human visual pathway and self-organizing, associative-engine processing. In addition to EVS/SVS imagery, outputs will include sensor-based navigation and attitude signals as well as hazard detection. A system architecture is described, encompassing an all-weather sensor suite; advanced processing technology; intertial, GPS and other avionics inputs; and pilot and machine interfaces. Issues of total-system accuracy and integrity are addressed, as well as flight operational aspects relating to both civil certification and military applications in IMC.
Development of NTCIP-based portable traffic signal evaluation system.
DOT National Transportation Integrated Search
2014-10-01
The objective of this project was to develop a custom toolbox for monitoring and troubleshooting operational : issues and faults at signalized intersections and diamond interchanges, and for providing a mechanism to : facilitate signal timing optimiz...
Johnson Hamlet, M R; Perkins, L A
2001-11-01
The Drosophila nonreceptor protein tyrosine phosphatase, Corkscrew (Csw), functions positively in multiple receptor tyrosine kinase (RTK) pathways, including signaling by the epidermal growth factor receptor (EGFR). Detailed phenotypic analyses of csw mutations have revealed that Csw activity is required in many of the same developmental processes that require EGFR function. However, it is still unclear where in the signaling hierarchy Csw functions relative to other proteins whose activities are also required downstream of the receptor. To address this issue, genetic interaction experiments were performed to place csw gene activity relative to the EGFR, spitz (spi), rhomboid (rho), daughter of sevenless (DOS), kinase-suppressor of ras (ksr), ras1, D-raf, pointed (pnt), and moleskin. We followed the EGFR-dependent formation of VA2 muscle precursor cells as a sensitive assay for these genetic interaction studies. First, we established that Csw has a positive function during mesoderm development. Second, we found that tissue-specific expression of a gain-of-function csw construct rescues loss-of-function mutations in other positive signaling genes upstream of rolled (rl)/MAPK in the EGFR pathway. Third, we were able to infer levels of EGFR signaling in various mutant backgrounds during myogenesis. This work extends previous studies of Csw during Torso and Sevenless RTK signaling to include an in-depth analysis of the role of Csw in the EGFR signaling pathway.
Johnson Hamlet, M R; Perkins, L A
2001-01-01
The Drosophila nonreceptor protein tyrosine phosphatase, Corkscrew (Csw), functions positively in multiple receptor tyrosine kinase (RTK) pathways, including signaling by the epidermal growth factor receptor (EGFR). Detailed phenotypic analyses of csw mutations have revealed that Csw activity is required in many of the same developmental processes that require EGFR function. However, it is still unclear where in the signaling hierarchy Csw functions relative to other proteins whose activities are also required downstream of the receptor. To address this issue, genetic interaction experiments were performed to place csw gene activity relative to the EGFR, spitz (spi), rhomboid (rho), daughter of sevenless (DOS), kinase-suppressor of ras (ksr), ras1, D-raf, pointed (pnt), and moleskin. We followed the EGFR-dependent formation of VA2 muscle precursor cells as a sensitive assay for these genetic interaction studies. First, we established that Csw has a positive function during mesoderm development. Second, we found that tissue-specific expression of a gain-of-function csw construct rescues loss-of-function mutations in other positive signaling genes upstream of rolled (rl)/MAPK in the EGFR pathway. Third, we were able to infer levels of EGFR signaling in various mutant backgrounds during myogenesis. This work extends previous studies of Csw during Torso and Sevenless RTK signaling to include an in-depth analysis of the role of Csw in the EGFR signaling pathway. PMID:11729154
Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John
2017-01-01
Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go/no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time–based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time–based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations. PMID:29276390
Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John
2017-01-01
Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go / no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time-based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time-based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations.
Signal and noise extraction from analog memory elements for neuromorphic computing.
Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T
2018-05-29
Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.
NASA Astrophysics Data System (ADS)
Bykovskii, Yurii A.; Markilov, A. A.; Rodin, V. G.; Starikov, S. N.
1995-10-01
A description is given of systems with spatially incoherent illumination, intended for spectral and correlation analysis, and for the recording of Fourier holograms. These systems make use of transformation of the degree of the spatial coherence of light. The results are given of the processing of images and signals, including those transmitted by a bundle of fibre-optic waveguides both as monochromatic light and as quasimonochromatic radiation from a cathode-ray tube. The feasibility of spatial frequency filtering and of correlation analysis of images with a bipolar impulse response is considered for systems with spatially incoherent illumination where these tasks are performed by double transformation of the spatial coherence of light. A description is given of experimental systems and the results of image processing are reported.
Chuang, Pao-Tien; Kawcak, T'Nay; McMahon, Andrew P.
2003-01-01
Hedgehog (Hh) signaling plays a major role in multiple aspects of embryonic development. A key issue is how negative regulation of Hh signaling might contribute to generating differential responses over tens of cell diameters. In cells that respond to Hh, two proteins that are up-regulated are Patched1 (Ptch1), the Hh receptor, a general target in both invertebrate and vertebrate organisms, and Hip1, a Hh-binding protein that is vertebrate specific. To address the developmental role of Hip1 in the context of Hh signaling, we generated Hip1 mutants in the mouse. Loss of Hip1 function results in specific defects in two Hh target issues, the lung, a target of Sonic hedgehog (Shh) signaling, and the endochondral skeleton, a target of Indian hedgehog (Ihh) signaling. Hh signaling was up-regulated in Hip1 mutants, substantiating Hip1's general role in negatively regulating Hh signaling. Our studies focused on Hip1 in the lung. Here, a dynamic interaction between Hh and fibroblast growth factor (Fgf) signaling, modulated at least in part by Hip1, controls early lung branching. PMID:12569124
Chuang, Pao-Tien; Kawcak, T'Nay; McMahon, Andrew P
2003-02-01
Hedgehog (Hh) signaling plays a major role in multiple aspects of embryonic development. A key issue is how negative regulation of Hh signaling might contribute to generating differential responses over tens of cell diameters. In cells that respond to Hh, two proteins that are up-regulated are Patched1 (Ptch1), the Hh receptor, a general target in both invertebrate and vertebrate organisms, and Hip1, a Hh-binding protein that is vertebrate specific. To address the developmental role of Hip1 in the context of Hh signaling, we generated Hip1 mutants in the mouse. Loss of Hip1 function results in specific defects in two Hh target issues, the lung, a target of Sonic hedgehog (Shh) signaling, and the endochondral skeleton, a target of Indian hedgehog (Ihh) signaling. Hh signaling was up-regulated in Hip1 mutants, substantiating Hip1's general role in negatively regulating Hh signaling. Our studies focused on Hip1 in the lung. Here, a dynamic interaction between Hh and fibroblast growth factor (Fgf) signaling, modulated at least in part by Hip1, controls early lung branching.
The intersection between DNA damage response and cell death pathways.
Nowsheen, S; Yang, E S
2012-10-01
Apoptosis is a finely regulated process that serves to determine the fate of cells in response to various stresses. One such stress is DNA damage, which not only can signal repair processes but is also intimately involved in regulating cell fate. In this review we examine the relationship between the DNA damage/repair response in cell survival and apoptosis following insults to the DNA. Elucidating these pathways and the crosstalk between them is of great importance, as they eventually contribute to the etiology of human disease such as cancer and may play key roles in determining therapeutic response. This article is part of a Special Issue entitled "Apoptosis: Four Decades Later".
Video Analytics for Indexing, Summarization and Searching of Video Archives
DOE Office of Scientific and Technical Information (OSTI.GOV)
Trease, Harold E.; Trease, Lynn L.
This paper will be submitted to the proceedings The Eleventh IASTED International Conference on. Signal and Image Processing. Given a video or video archive how does one effectively and quickly summarize, classify, and search the information contained within the data? This paper addresses these issues by describing a process for the automated generation of a table-of-contents and keyword, topic-based index tables that can be used to catalogue, summarize, and search large amounts of video data. Having the ability to index and search the information contained within the videos, beyond just metadata tags, provides a mechanism to extract and identify "useful"more » content from image and video data.« less
Mitochondrial dysfunction and sarcopenia of aging: from signaling pathways to clinical trials
Marzetti, Emanuele; Calvani, Riccardo; Cesari, Matteo; Buford, Thomas W.; Lorenzi, Maria; Behnke, Bradley J.; Leeuwenburgh, Christiaan
2013-01-01
Sarcopenia, the age-related loss of muscle mass and function, imposes a dramatic burden on individuals and society. The development of preventive and therapeutic strategies against sarcopenia is therefore perceived as an urgent need by health professionals and has instigated intensive research on the pathophysiology of this syndrome. The pathogenesis of sarcopenia is multifaceted and encompasses lifestyle habits, systemic factors (e.g., chronic inflammation and hormonal alterations), local environment perturbations (e.g., vascular dysfunction), and intramuscular specific processes. In this scenario, derangements in skeletal myocyte mitochondrial function are recognized as major factors contributing to the age-dependent muscle degeneration. In this review, we summarize prominent findings and controversial issues on the contribution of specific mitochondrial processes – including oxidative stress, quality control mechanisms and apoptotic signaling – on the development of sarcopenia. Extramuscular alterations accompanying the aging process with a potential impact on myocyte mitochondrial function are also discussed. We conclude with presenting methodological and safety considerations for the design of clinical trials targeting mitochondrial dysfunction to treat sarcopenia. Special emphasis is placed on the importance of monitoring the effects of an intervention on muscle mitochondrial function and identifying the optimal target population for the trial. PMID:23845738
Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks
Richter, Philipp; Toledano-Ayala, Manuel
2015-01-01
Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996
Auditory conflict and congruence in frontotemporal dementia.
Clark, Camilla N; Nicholas, Jennifer M; Agustus, Jennifer L; Hardy, Christopher J D; Russell, Lucy L; Brotherhood, Emilie V; Dick, Katrina M; Marshall, Charles R; Mummery, Catherine J; Rohrer, Jonathan D; Warren, Jason D
2017-09-01
Impaired analysis of signal conflict and congruence may contribute to diverse socio-emotional symptoms in frontotemporal dementias, however the underlying mechanisms have not been defined. Here we addressed this issue in patients with behavioural variant frontotemporal dementia (bvFTD; n = 19) and semantic dementia (SD; n = 10) relative to healthy older individuals (n = 20). We created auditory scenes in which semantic and emotional congruity of constituent sounds were independently probed; associated tasks controlled for auditory perceptual similarity, scene parsing and semantic competence. Neuroanatomical correlates of auditory congruity processing were assessed using voxel-based morphometry. Relative to healthy controls, both the bvFTD and SD groups had impaired semantic and emotional congruity processing (after taking auditory control task performance into account) and reduced affective integration of sounds into scenes. Grey matter correlates of auditory semantic congruity processing were identified in distributed regions encompassing prefrontal, parieto-temporal and insular areas and correlates of auditory emotional congruity in partly overlapping temporal, insular and striatal regions. Our findings suggest that decoding of auditory signal relatedness may probe a generic cognitive mechanism and neural architecture underpinning frontotemporal dementia syndromes. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Olama, Mohammed M; Matalgah, Mustafa M; Bobrek, Miljko
Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subjectmore » to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).« less
Roehl, Edwin A.; Conrads, Paul
2010-01-01
This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.
The 6th International Conference on Computer Science and Computational Mathematics (ICCSCM 2017)
NASA Astrophysics Data System (ADS)
2017-09-01
The ICCSCM 2017 (The 6th International Conference on Computer Science and Computational Mathematics) has aimed to provide a platform to discuss computer science and mathematics related issues including Algebraic Geometry, Algebraic Topology, Approximation Theory, Calculus of Variations, Category Theory; Homological Algebra, Coding Theory, Combinatorics, Control Theory, Cryptology, Geometry, Difference and Functional Equations, Discrete Mathematics, Dynamical Systems and Ergodic Theory, Field Theory and Polynomials, Fluid Mechanics and Solid Mechanics, Fourier Analysis, Functional Analysis, Functions of a Complex Variable, Fuzzy Mathematics, Game Theory, General Algebraic Systems, Graph Theory, Group Theory and Generalizations, Image Processing, Signal Processing and Tomography, Information Fusion, Integral Equations, Lattices, Algebraic Structures, Linear and Multilinear Algebra; Matrix Theory, Mathematical Biology and Other Natural Sciences, Mathematical Economics and Financial Mathematics, Mathematical Physics, Measure Theory and Integration, Neutrosophic Mathematics, Number Theory, Numerical Analysis, Operations Research, Optimization, Operator Theory, Ordinary and Partial Differential Equations, Potential Theory, Real Functions, Rings and Algebras, Statistical Mechanics, Structure Of Matter, Topological Groups, Wavelets and Wavelet Transforms, 3G/4G Network Evolutions, Ad-Hoc, Mobile, Wireless Networks and Mobile Computing, Agent Computing & Multi-Agents Systems, All topics related Image/Signal Processing, Any topics related Computer Networks, Any topics related ISO SC-27 and SC- 17 standards, Any topics related PKI(Public Key Intrastructures), Artifial Intelligences(A.I.) & Pattern/Image Recognitions, Authentication/Authorization Issues, Biometric authentication and algorithms, CDMA/GSM Communication Protocols, Combinatorics, Graph Theory, and Analysis of Algorithms, Cryptography and Foundation of Computer Security, Data Base(D.B.) Management & Information Retrievals, Data Mining, Web Image Mining, & Applications, Defining Spectrum Rights and Open Spectrum Solutions, E-Comerce, Ubiquitous, RFID, Applications, Fingerprint/Hand/Biometrics Recognitions and Technologies, Foundations of High-performance Computing, IC-card Security, OTP, and Key Management Issues, IDS/Firewall, Anti-Spam mail, Anti-virus issues, Mobile Computing for E-Commerce, Network Security Applications, Neural Networks and Biomedical Simulations, Quality of Services and Communication Protocols, Quantum Computing, Coding, and Error Controls, Satellite and Optical Communication Systems, Theory of Parallel Processing and Distributed Computing, Virtual Visions, 3-D Object Retrievals, & Virtual Simulations, Wireless Access Security, etc. The success of ICCSCM 2017 is reflected in the received papers from authors around the world from several countries which allows a highly multinational and multicultural idea and experience exchange. The accepted papers of ICCSCM 2017 are published in this Book. Please check http://www.iccscm.com for further news. A conference such as ICCSCM 2017 can only become successful using a team effort, so herewith we want to thank the International Technical Committee and the Reviewers for their efforts in the review process as well as their valuable advices. We are thankful to all those who contributed to the success of ICCSCM 2017. The Secretary
Testing local anisotropy using the method of smoothed residuals I — methodology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Appleby, Stephen; Shafieloo, Arman, E-mail: stephen.appleby@apctp.org, E-mail: arman@apctp.org
2014-03-01
We discuss some details regarding the method of smoothed residuals, which has recently been used to search for anisotropic signals in low-redshift distance measurements (Supernovae). In this short note we focus on some details regarding the implementation of the method, particularly the issue of effectively detecting signals in data that are inhomogeneously distributed on the sky. Using simulated data, we argue that the original method proposed in Colin et al. [1] will not detect spurious signals due to incomplete sky coverage, and that introducing additional Gaussian weighting to the statistic as in [2] can hinder its ability to detect amore » signal. Issues related to the width of the Gaussian smoothing are also discussed.« less
Wireless sleep monitoring headband to identify sleep and track fatigue
NASA Astrophysics Data System (ADS)
Ramasamy, Mouli; Oh, Sechang; Varadan, Vijay K.
2014-04-01
Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Commonly, the rudimentary bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper proposes the design of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the dry gold wire nano-sensors fabricated on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through WCDMA/GSM communication. This module is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the experienced fatigue level. The novel approach of using a wireless, real time, dry sensor on a flexible substrate reduces the obtrusiveness, and techniques adopted in the electronics and software facilitates and substantial increase in efficiency, accuracy and precision.
General anesthesia selectively disrupts astrocyte calcium signaling in the awake mouse cortex
Thrane, Alexander Stanley; Zeppenfeld, Douglas; Lou, Nanhong; Xu, Qiwu; Nagelhus, Erlend Arnulf; Nedergaard, Maiken
2012-01-01
Calcium signaling represents the principle pathway by which astrocytes respond to neuronal activity. General anesthetics are routinely used in clinical practice to induce a sleep-like state, allowing otherwise painful procedures to be performed. Anesthetic drugs are thought to mainly target neurons in the brain and act by suppressing synaptic activity. However, the direct effect of general anesthesia on astrocyte signaling in awake animals has not previously been addressed. This is a critical issue, because calcium signaling may represent an essential mechanism through which astrocytes can modulate synaptic activity. In our study, we performed calcium imaging in awake head-restrained mice and found that three commonly used anesthetic combinations (ketamine/xylazine, isoflurane, and urethane) markedly suppressed calcium transients in neocortical astrocytes. Additionally, all three anesthetics masked potentially important features of the astrocyte calcium signals, such as synchronized widespread transients that appeared to be associated with arousal in awake animals. Notably, anesthesia affected calcium transients in both processes and soma and depressed spontaneous signals, as well as calcium responses, evoked by whisker stimulation or agonist application. We show that these calcium transients are inositol 1,4,5-triphosphate type 2 receptor (IP3R2)-dependent but resistant to a local blockade of glutamatergic or purinergic signaling. Finally, we found that doses of anesthesia insufficient to affect neuronal responses to whisker stimulation selectively suppressed astrocyte calcium signals. Taken together, these data suggest that general anesthesia may suppress astrocyte calcium signals independently of neuronal activity. We propose that these glial effects may constitute a nonneuronal mechanism for sedative action of anesthetic drugs. PMID:23112168
SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iliopoulos, AS; Sun, X; Floros, D
Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less
2014-01-01
Background This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. Results An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. Conclusions The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues. PMID:24708668
Menegaldo, Luciano Luporini; de Oliveira, Liliam Fernandes; Minato, Kin K
2014-04-04
This paper describes the "EMG Driven Force Estimator (EMGD-FE)", a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. An example of the application's functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.
Robust real-time extraction of respiratory signals from PET list-mode data
NASA Astrophysics Data System (ADS)
Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas
2018-06-01
Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.
MEASURING TRANSIT SIGNAL RECOVERY IN THE KEPLER PIPELINE. I. INDIVIDUAL EVENTS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Christiansen, Jessie L.; Clarke, Bruce D.; Burke, Christopher J.
The Kepler mission was designed to measure the frequency of Earth-size planets in the habitable zone of Sun-like stars. A crucial component for recovering the underlying planet population from a sample of detected planets is understanding the completeness of that sample-the fraction of the planets that could have been discovered in a given data set that actually were detected. Here, we outline the information required to determine the sample completeness, and describe an experiment to address a specific aspect of that question, i.e., the issue of transit signal recovery. We investigate the extent to which the Kepler pipeline preserves individualmore » transit signals by injecting simulated transits into the pixel-level data, processing the modified pixels through the pipeline, and comparing the measured transit signal-to-noise ratio (S/N) to that expected without perturbation by the pipeline. We inject simulated transit signals across the full focal plane for a set of observations for a duration of 89 days. On average, we find that the S/N of the injected signal is recovered at MS = 0.9973({+-} 0.0012) Multiplication-Sign BS - 0.0151({+-} 0.0049), where MS is the measured S/N and BS is the baseline, or expected, S/N. The 1{sigma} width of the distribution around this correlation is {+-}2.64%. This indicates an extremely high fidelity in reproducing the expected detection statistics for single transit events, and provides teams performing their own periodic transit searches the confidence that there is no systematic reduction in transit signal strength introduced by the pipeline. We discuss the pipeline processes that cause the measured S/N to deviate significantly from the baseline S/N for a small fraction of targets; these are primarily the handling of data adjacent to spacecraft re-pointings and the removal of harmonics prior to the measurement of the S/N. Finally, we outline the further work required to characterize the completeness of the Kepler pipeline.« less
An Architecture for SCADA Network Forensics
NASA Astrophysics Data System (ADS)
Kilpatrick, Tim; Gonzalez, Jesus; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet
Supervisory control and data acquisition (SCADA) systems are widely used in industrial control and automation. Modern SCADA protocols often employ TCP/IP to transport sensor data and control signals. Meanwhile, corporate IT infrastructures are interconnecting with previously isolated SCADA networks. The use of TCP/IP as a carrier protocol and the interconnection of IT and SCADA networks raise serious security issues. This paper describes an architecture for SCADA network forensics. In addition to supporting forensic investigations of SCADA network incidents, the architecture incorporates mechanisms for monitoring process behavior, analyzing trends and optimizing plant performance.
Stuart Gatehouse: The International Perspective
Van Tasell, Dianne J.; Levitt, Harry
2008-01-01
The international contributions of Stuart Gatehouse are reviewed in three areas: as a scientist, as an advisor to health policy makers, and as a participant in international conferences. He was able, as no other auditory scientist of his time, to bridge the gap between scientific and clinical research. His ability to apply sound scientific principles to issues of clinical importance was most apparent in his work in three main areas of his research: acclimatization to amplified speech, auditory disability and hearing aid benefit, and candidature for linear and nonlinear signal processing. PMID:18567589
Emes, Michael J
2009-08-13
In response to biotic and abiotic stresses, plants induce a complex array of pathways and protein phosphorylation cascades which generally lead to a response aimed at mitigating the particular insult. In many cases, H2O2 has been implicated as the signalling molecule, but, although progress has been made in assembling the downstream components of these signalling pathways, far less is known about the mechanism by which the signal is perceived. In this issue of the Biochemical Journal, Hardin et al. provide evidence for a plausible mechanism by which plants perceive H2O2. Evidence is presented for chemical oxidation of methionine residues by H2O2 at critical hydrophobic positions within the canonical motifs that define the phosphorylation sites of a number of enzymes, thus inhibiting binding of protein kinases. This process is reversible by MSR (methionine sulfoxide reductase) activity in vivo. Using synthetic peptides for a number of enzymes which are phosphorylated by families of protein kinases, including the CDPK (calcium-dependent protein kinase) and AMPK (AMP-activated protein kinase) families, coupled with in vivo studies of assimilatory plant nitrate reductase, the authors demonstrate that this mechanism regulates the ability of kinases to bind the target protein, directly linking oxidative signals to changes in protein phosphorylation. These results may have widespread implications for the perception of redox signalling in plants and animals.
Hu, Pan; Yang, Bin
2016-01-15
Due to its unique features such as high sensitivity, homogeneous format, and independence on fluorescent intensity, fluorescence anisotropy (FA) assay has become a hotspot of study in oligonucleotide-based bioassays. However, until now most FA probes require carefully customized structure designs, and thus are neither generalizable for different sensing systems nor effective to obtain sufficient signal response. To address this issue, a cleavable DNA-protein hybrid molecular beacon was successfully engineered for signal amplified FA bioassay, via combining the unique stable structure of molecular beacon and the large molecular mass of streptavidin. Compared with single DNA strand probe or conventional molecular beacon, the DNA-protein hybrid molecular beacon exhibited a much higher FA value, which was potential to obtain high signal-background ratio in sensing process. As proof-of-principle, this novel DNA-protein hybrid molecular beacon was further applied for FA bioassay using DNAzyme-Pb(2+) as a model sensing system. This FA assay approach could selectively detect as low as 0.5nM Pb(2+) in buffer solution, and also be successful for real samples analysis with good recovery values. Compatible with most of oligonucleotide probes' designs and enzyme-based signal amplification strategies, the molecular beacon can serve as a novel signal translator to expand the application prospect of FA technology in various bioassays. Copyright © 2015 Elsevier B.V. All rights reserved.
Sun, Junfeng; Li, Zhijun; Tong, Shanbao
2012-01-01
Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470
Integration of planar cell polarity and ECM signaling in elongation of the vertebrate body plan.
Skoglund, Paul; Keller, Ray
2010-10-01
The shaping of the vertebrate embryonic body plan depends heavily on the narrowing and lengthening (convergence and extension) of embryonic tissues by cell intercalation, a process by which cells actively crawl between one another along the axis of convergence to produce a narrower, longer array. We discuss recent evidence that the vertebrate non-canonical Wnt/Planar Cell Polarity (PCP) pathway, known to directly function in polarizing the movements of intercalating cells, is also involved in the localized assembly of extracellular matrix (ECM). These cell-ECM interactions, in turn, are necessary for expression of the oriented, polarized cell intercalation. The mechanism of PCP/ECM interactions, their molecular signaling, and their mechanical consequences for morphogenesis are discussed with the goal of identifying important unsolved issues. Copyright © 2010 Elsevier Ltd. All rights reserved.
The Complexities of Using Direct-Input Hearing Aids with FM Systems.
ERIC Educational Resources Information Center
Thibodeau, Linda M.; McCaffrey, Helen A.
1992-01-01
This article reviews issues to be considered in the selection and monitoring of direct-input personal Frequency Modulation (FM) systems for individuals with hearing impairments. The article discusses boot configurations, signal options, ordering issues, and maintenance issues. (Author/JDD)
Environmental Scanning and the Information Manager.
ERIC Educational Resources Information Center
Newsome, James; McInerney, Claire
1990-01-01
Discusses nine components of an environmental scanning model: selecting the scanning team; selecting resources to scan; choosing criteria for scanning; scanning the resources; identifying signals of new issues; selecting key events/issues; monitoring and analyzing events/issues; disseminating information; and deciding on appropriate organizational…
Border effect-based precise measurement of any frequency signal
NASA Astrophysics Data System (ADS)
Bai, Li-Na; Ye, Bo; Xuan, Mei-Na; Jin, Yu-Zhen; Zhou, Wei
2015-12-01
Limited detection resolution leads to fuzzy areas during the measurement, and the discrimination of the border of a fuzzy area helps to use the resolution stability. In this way, measurement precision is greatly improved, hence this phenomenon is named the border effect. The resolution fuzzy area and its application should be studied to realize high-resolution measurement. During the measurement of any frequency signal, the fuzzy areas of phase-coincidence detection are always discrete and irregular. In this paper the difficulty in capturing the border information of discrete fuzzy areas is overcome and extra-high resolution measurement is implemented. Measurement precision of any frequency-signal can easily reach better than 1 × 10-11/s in a wide range of frequencies, showing the great importance of the border effect. An in-depth study of this issue has great significance for frequency standard comparison, signal processing, telecommunication, and fundamental subjects. Project supported by the National Natural Science Foundation of China (Grant Nos. 10978017 and 61201288), the Natural Science Foundation of Research Plan Projects of Shaanxi Province, China (Grant No. 2014JM2-6128), and the Sino-Poland Science and Technology Cooperation Projects (Grant No. 36-33).
REV, A BRET-Based Sensor of ERK Activity
Xu, Chanjuan; Peter, Marion; Bouquier, Nathalie; Ollendorff, Vincent; Villamil, Ignacio; Liu, Jianfeng; Fagni, Laurent; Perroy, Julie
2013-01-01
Networks of signaling molecules are activated in response to environmental changes. How are these signaling networks dynamically integrated in space and time to process particular information? To tackle this issue, biosensors of single signaling pathways have been engineered. Bioluminescence resonance energy transfer (BRET)-based biosensors have proven to be particularly efficient in that matter due to the high sensitivity of this technology to monitor protein–protein interactions or conformational changes in living cells. Extracellular signal-regulated kinases (ERK) are ubiquitously expressed and involved in many diverse cellular functions that might be encoded by the strength and spatio-temporal pattern of ERK activation. We developed a BRET-based sensor of ERK activity, called Rluc8-ERKsubstrate-Venus (REV). As expected, BRET changes of REV were correlated with ERK phosphorylation, which is required for its kinase activity. In neurons, the nature of the stimuli determines the strength, the location, or the moment of ERK activation, thus highlighting how acute modulation of ERK may encode the nature of initial stimulus to specify the consequences of this activation. This study provides evidence for suitability of REV as a new biosensor to address biological questions. PMID:23908646
Plasma membrane order and fluidity are diversely triggered by elicitors of plant defence
Sandor, Roman; Der, Christophe; Grosjean, Kevin; Anca, Iulia; Noirot, Elodie; Leborgne-Castel, Nathalie; Lochman, Jan; Simon-Plas, Françoise; Gerbeau-Pissot, Patricia
2016-01-01
Although plants are exposed to a great number of pathogens, they usually defend themselves by triggering mechanisms able to limit disease development. Alongside signalling events common to most such incompatible interactions, modifications of plasma membrane (PM) physical properties could be new players in the cell transduction cascade. Different pairs of elicitors (cryptogein, oligogalacturonides, and flagellin) and plant cells (tobacco and Arabidopsis) were used to address the issue of possible modifications of plant PM biophysical properties induced by elicitors and their links to other events of the defence signalling cascade. We observed an increase of PM order whatever the elicitor/plant cell pair used, provided that a signalling cascade was induced. Such membrane modification is dependent on the NADPH oxidase-mediated reactive oxygen species production. Moreover, cryptogein, which is the sole elicitor able to trap sterols, is also the only one able to trigger an increase in PM fluidity. The use of cryptogein variants with altered sterol-binding properties confirms the strong correlation between sterol removal from the PM and PM fluidity enhancement. These results propose PM dynamics as a player in early signalling processes triggered by elicitors of plant defence. PMID:27604805
Applying matching pursuit decomposition time-frequency processing to UGS footstep classification
NASA Astrophysics Data System (ADS)
Larsen, Brett W.; Chung, Hugh; Dominguez, Alfonso; Sciacca, Jacob; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Allee, David R.
2013-06-01
The challenge of rapid footstep detection and classification in remote locations has long been an important area of study for defense technology and national security. Also, as the military seeks to create effective and disposable unattended ground sensors (UGS), computational complexity and power consumption have become essential considerations in the development of classification techniques. In response to these issues, a research project at the Flexible Display Center at Arizona State University (ASU) has experimented with footstep classification using the matching pursuit decomposition (MPD) time-frequency analysis method. The MPD provides a parsimonious signal representation by iteratively selecting matched signal components from a pre-determined dictionary. The resulting time-frequency representation of the decomposed signal provides distinctive features for different types of footsteps, including footsteps during walking or running activities. The MPD features were used in a Bayesian classification method to successfully distinguish between the different activities. The computational cost of the iterative MPD algorithm was reduced, without significant loss in performance, using a modified MPD with a dictionary consisting of signals matched to cadence temporal gait patterns obtained from real seismic measurements. The classification results were demonstrated with real data from footsteps under various conditions recorded using a low-cost seismic sensor.
Theta signal as the neural signature of social exclusion.
Cristofori, Irene; Moretti, Laura; Harquel, Sylvain; Posada, Andres; Deiana, Gianluca; Isnard, Jean; Mauguière, François; Sirigu, Angela
2013-10-01
The feeling of being excluded from a social interaction triggers social pain, a sensation as intense as actual physical pain. Little is known about the neurophysiological underpinnings of social pain. We addressed this issue using intracranial electroencephalography in 15 patients performing a ball game where inclusion and exclusion blocks were alternated. Time-frequency analyses showed an increase in power of theta-band oscillations during exclusion in the anterior insula (AI) and posterior insula, the subgenual anterior cingulate cortex (sACC), and the fusiform "face area" (FFA). Interestingly, the AI showed an initial fast response to exclusion but the signal rapidly faded out. Activity in the sACC gradually increased and remained significant thereafter. This suggests that the AI may signal social pain by detecting emotional distress caused by the exclusion, whereas the sACC may be linked to the learning aspects of social pain. Theta activity in the FFA was time-locked to the observation of a player poised to exclude the participant, suggesting that the FFA encodes the social value of faces. Taken together, our findings suggest that theta activity represents the neural signature of social pain. The time course of this signal varies across regions important for processing emotional features linked to social information.
NASA Astrophysics Data System (ADS)
Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang
2010-12-01
A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.
Chip Design Process Optimization Based on Design Quality Assessment
NASA Astrophysics Data System (ADS)
Häusler, Stefan; Blaschke, Jana; Sebeke, Christian; Rosenstiel, Wolfgang; Hahn, Axel
2010-06-01
Nowadays, the managing of product development projects is increasingly challenging. Especially the IC design of ASICs with both analog and digital components (mixed-signal design) is becoming more and more complex, while the time-to-market window narrows at the same time. Still, high quality standards must be fulfilled. Projects and their status are becoming less transparent due to this complexity. This makes the planning and execution of projects rather difficult. Therefore, there is a need for efficient project control. A main challenge is the objective evaluation of the current development status. Are all requirements successfully verified? Are all intermediate goals achieved? Companies often develop special solutions that are not reusable in other projects. This makes the quality measurement process itself less efficient and produces too much overhead. The method proposed in this paper is a contribution to solve these issues. It is applied at a German design house for analog mixed-signal IC design. This paper presents the results of a case study and introduces an optimized project scheduling on the basis of quality assessment results.
The mechanics behind plant development.
Hamant, Olivier; Traas, Jan
2010-01-01
Morphogenesis in living organisms relies on the integration of both biochemical and mechanical signals. During the last decade, attention has been mainly focused on the role of biochemical signals in patterning and morphogenesis, leaving the contribution of mechanics largely unexplored. Fortunately, the development of new tools and approaches has made it possible to re-examine these processes. In plants, shape is defined by two local variables: growth rate and growth direction. At the level of the cell, these variables depend on both the cell wall and turgor pressure. Multidisciplinary approaches have been used to understand how these cellular processes are integrated in the growing tissues. These include quantitative live imaging to measure growth rate and direction in tissues with cellular resolution. In parallel, stress patterns have been artificially modified and their impact on strain and cell behavior been analysed. Importantly, computational models based on analogies with continuum mechanics systems have been useful in interpreting the results. In this review, we will discuss these issues focusing on the shoot apical meristem, a population of stem cells that is responsible for the initiation of the aerial organs of the plant.
Plant sphingolipids: Their importance in cellular organization and adaption.
Michaelson, Louise V; Napier, Johnathan A; Molino, Diana; Faure, Jean-Denis
2016-09-01
Sphingolipids and their phosphorylated derivatives are ubiquitous bio-active components of cells. They are structural elements in the lipid bilayer and contribute to the dynamic nature of the membrane. They have been implicated in many cellular processes in yeast and animal cells, including aspects of signaling, apoptosis, and senescence. Although sphingolipids have a better defined role in animal systems, they have been shown to be central to many essential processes in plants including but not limited to, pollen development, signal transduction and in the response to biotic and abiotic stress. A fuller understanding of the roles of sphingolipids within plants has been facilitated by classical biochemical studies and the identification of mutants of model species. Recently the development of powerful mass spectrometry techniques hailed the advent of the emerging field of lipidomics enabling more accurate sphingolipid detection and quantitation. This review will consider plant sphingolipid biosynthesis and function in the context of these new developments. This article is part of a Special Issue entitled: Plant Lipid Biology edited by Kent D. Chapman and Ivo Feussner. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
A Review on Potential Issues and Challenges in MR Imaging
Kanakaraj, Jagannathan
2013-01-01
Magnetic resonance imaging is a noninvasive technique that has been developed for its excellent depiction of soft tissue contrasts. Instruments capable of ultra-high field strengths, ≥7 Tesla, were recently engineered and have resulted in higher signal-to-noise and higher resolution images. This paper presents various subsystems of the MR imaging systems like the magnet subsystem, gradient subsystem, and also various issues which arise due to the magnet. Further, it also portrays finer details about the RF coils and transceiver and also various limitations of the RF coils and transceiver. Moreover, the concept behind the data processing system and the challenges related to it were also depicted. Finally, the various artifacts associated with the MR imaging were clearly pointed out. It also presents a brief overview about all the challenges related to MR imaging systems. PMID:24381523
Evolutionary approaches to cultural and linguistic diversity.
Steele, James; Jordan, Peter; Cochrane, Ethan
2010-12-12
Evolutionary approaches to cultural change are increasingly influential, and many scientists believe that a 'grand synthesis' is now in sight. The papers in this Theme Issue, which derives from a symposium held by the AHRC Centre for the Evolution of Cultural Diversity (University College London) in December 2008, focus on how the phylogenetic tree-building and network-based techniques used to estimate descent relationships in biology can be adapted to reconstruct cultural histories, where some degree of inter-societal diffusion will almost inevitably be superimposed on any deeper signal of a historical branching process. The disciplines represented include the three most purely 'cultural' fields from the four-field model of anthropology (cultural anthropology, archaeology and linguistic anthropology). In this short introduction, some context is provided from the history of anthropology, and key issues raised by the papers are highlighted.
Evolutionary approaches to cultural and linguistic diversity
Steele, James; Jordan, Peter; Cochrane, Ethan
2010-01-01
Evolutionary approaches to cultural change are increasingly influential, and many scientists believe that a ‘grand synthesis’ is now in sight. The papers in this Theme Issue, which derives from a symposium held by the AHRC Centre for the Evolution of Cultural Diversity (University College London) in December 2008, focus on how the phylogenetic tree-building and network-based techniques used to estimate descent relationships in biology can be adapted to reconstruct cultural histories, where some degree of inter-societal diffusion will almost inevitably be superimposed on any deeper signal of a historical branching process. The disciplines represented include the three most purely ‘cultural’ fields from the four-field model of anthropology (cultural anthropology, archaeology and linguistic anthropology). In this short introduction, some context is provided from the history of anthropology, and key issues raised by the papers are highlighted. PMID:21041203
Steroid promiscuity: Diversity of enzyme action. Preface.
Lathe, Richard; Kotelevtsev, Yuri; Mason, J Ian
2015-07-01
This Special Issue on the topic of Steroid and Sterol Signaling: Promiscuity and Diversity, dwells on the growing realization that the 'one ligand, one binding site' and 'one enzyme, one reaction' concepts are out of date. Focusing on cytochromes P450 (CYP), hydroxysteroid dehydrogenases (HSDs), and related enzymes, the Special Issue highlights that a single enzyme can bind to diverse substrates, and in different conformations, and can catalyze multiple different conversions (and in different directions), thereby, generating an unexpectedly wide spectrum of ligands that can have subtly different biological actions. This article is part of a Special Issue entitled 'Steroid/Sterol Signaling' . Copyright © 2015 Elsevier Ltd. All rights reserved.
Montezano, Augusto C.
2014-01-01
Abstract Significance: Reactive oxygen species (ROS) are signaling molecules that are important in physiological processes, including host defense, aging, and cellular homeostasis. Increased ROS bioavailability and altered redox signaling (oxidative stress) have been implicated in the onset and/or progression of chronic diseases, including hypertension. Recent Advances: Although oxidative stress may not be the only cause of hypertension, it amplifies blood pressure elevation in the presence of other pro-hypertensive factors, such as salt loading, activation of the renin-angiotensin-aldosterone system, and sympathetic hyperactivity, at least in experimental models. A major source for ROS in the cardiovascular-renal system is a family of nicotinamide adenine dinucleotide phosphate oxidases (Noxs), including the prototypic Nox2-based Nox, and Nox family members: Nox1, Nox4, and Nox5. Critical Issues: Although extensive experimental data support a role for increased ROS levels and altered redox signaling in the pathogenesis of hypertension, the role in clinical hypertension is unclear, as a direct causative role of ROS in blood pressure elevation has yet to be demonstrated in humans. Nevertheless, what is becoming increasingly evident is that abnormal ROS regulation and aberrant signaling through redox-sensitive pathways are important in the pathophysiological processes which is associated with vascular injury and target-organ damage in hypertension. Future Directions: There is a paucity of clinical information related to the mechanisms of oxidative stress and blood pressure elevation, and a few assays accurately measure ROS directly in patients. Such further ROS research is needed in humans and in the development of adequately validated analytical methods to accurately assess oxidative stress in the clinic. Antioxid. Redox Signal. 20, 164–182. PMID:23600794
The Chemical Biology of S-Nitrosothiols
Broniowska, Katarzyna A.
2012-01-01
Abstract Significance: S-nitrosothiol formation and protein S-nitrosation is an important nitric oxide (NO)-dependent signaling paradigm that is relevant to almost all aspects of cell biology, from proliferation, to homeostasis, to programmed cell death. However, the mechanisms by which S-nitrosothiols are formed are still largely unknown, and there are gaps of understanding between the known chemical biology of S-nitrosothiols and their reported functions. Recent Advances: This review attempts to describe the biological chemistry of S-nitrosation and to point out where the challenges lie in matching the known chemical biology of these compounds with their reported functions. The review will detail new discoveries concerning the mechanisms of the formation of S-nitrosothiols in biological systems. Critical Issues: Although S-nitrosothiols may be formed with some degree of specificity on particular protein thiols, through un-catalyzed chemistry, and mechanisms for their degradation and redistribution are present, these processes are not sufficient to explain the vast array of specific and targeted responses of NO that have been attributed to S-nitrosation. Elements of catalysis have been discovered in the formation, distribution, and metabolism of S-nitrosothiols, but it is less clear whether these represent a specific network for targeted NO-dependent signaling. Future Directions: Much recent work has uncovered new targets for S-nitrosation through either targeted or proteome-wide approaches There is a need to understand which of these modifications represent concerted and targeted signaling processes and which is an inevitable consequence of living with NO. There is still much to be learned about how NO transduces signals in cells and the role played by protein S-nitrosation. Antioxid. Redox Signal. 17, 969–980. PMID:22468855
An evaluation of federal order reform.
Bailey, K; Tozer, P
2001-04-01
The Federal Agricultural Improvement and Reform Act of 1996 required the Secretary of Agriculture to reform federal milk marketing orders. The Secretary carried out this task and issued a final rule on March 31, 1999, that was eventually approved by dairy farmers in a national referendum. However, a temporary restraining order (TRO) was issued on September 28, 1999, that halted the reform process. The TRO was effectively overturned and the reform process restarted when President Bill Clinton signed the Consolidated Appropriations Act of 2000 on November 29, 1999. The final rule as amended consolidates the number of orders, develops a multiple component pricing system that determines new formulas for class prices, and provides a new system for pricing fluid milk based on county-level price differentials. The impact of these changes is to provide more transparency in pricing and improved market signals to farmers. But the new system is also much more vulnerable to changes in dairy commodity prices. The objective of this report is to provide a comprehensive overview of federal order reform and to analyze the impact of recent changes in class price formulas.
Pictorial Review of Digital Radiography Artifacts.
Walz-Flannigan, Alisa I; Brossoit, Kimberly J; Magnuson, Dayne J; Schueler, Beth A
2018-01-01
Visual familiarity with the variety of digital radiographic artifacts is needed to identify, resolve, or prevent image artifacts from creating issues with patient imaging. Because the mechanism for image creation is different between flat-panel detectors and computed radiography, the causes and appearances of some artifacts can be unique to these different modalities. Examples are provided of artifacts that were found on clinical images or during quality control testing with flat-panel detectors. The examples are meant to serve as learning tools for future identification and troubleshooting of artifacts and as a reminder for steps that can be taken for prevention. The examples of artifacts provided are classified according to their causal connection in the imaging chain, including an equipment defect as a result of an accident or mishandling, debris or gain calibration flaws, a problematic acquisition technique, signal transmission failures, and image processing issues. Specific artifacts include those that are due to flat-panel detector drops, backscatter, debris in the x-ray field during calibration, detector saturation or underexposure, or collimation detection errors, as well as a variety of artifacts that are processing induced. © RSNA, 2018.
NASA Astrophysics Data System (ADS)
Bykovskii, Yurii A.; Eloev, E. N.; Kukharenko, K. L.; Panin, A. M.; Solodovnikov, N. P.; Torgashin, A. N.; Arestova, E. L.
1995-10-01
An acousto-optical system for input, display, and coherent-optical processing of information was implemented experimentally. The information transmission capacity, the structure of the information fluxes, and the efficiency of spaceborne telemetric systems were taken into account. The number of equivalent frequency-resolved channels corresponded to the structure of a telemetric frame of a two-step switch. The number of intensity levels of laser radiation corresponded to the scale of changes in the parameters. Use was made of the technology of a liquid optical contact between a wedge-shaped piezoelectric transducer made of lithium niobate and an anisotropic light-and-sound guide made of paratellurite with asymmetric scattering geometry. The simplest technique for optical filtering of multiparameter signals was analysed.
Photo-oxidation of Polymers Synthesized by Plasma and Initiated CVD
Baxamusa, Salmaan H.; Suresh, Aravind; Ehrmann, Paul; ...
2015-11-09
Plasma polymers are often limited by their susceptibility to spontaneous and photo-oxidation. We show that the unusual photoluminescence (PL) behavior of a plasma polymer of trans-2-butene is correlated with its photoluminescence strength. These photo-processes occur under blue light illumination (λ=405 nm), distinguishing them from traditional ultraviolet degradation of polymers. These photo-active defects are likely formed during the plasma deposition process and we show that a polymer synthesized using initiated (i)CVD, non-plasma method, has 1000× lower PL signal and enhanced photo-stability. In conclusion, non-plasma methods such as iCVD may therefore be a route to overcoming material aging issues that limit themore » adoption of plasma polymers.« less
FIND: difFerential chromatin INteractions Detection using a spatial Poisson process
Chen, Yang; Zhang, Michael Q.
2018-01-01
Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. PMID:29440282
Parallel interactive retrieval of item and associative information from event memory.
Cox, Gregory E; Criss, Amy H
2017-09-01
Memory contains information about individual events (items) and combinations of events (associations). Despite the fundamental importance of this distinction, it remains unclear exactly how these two kinds of information are stored and whether different processes are used to retrieve them. We use both model-independent qualitative properties of response dynamics and quantitative modeling of individuals to address these issues. Item and associative information are not independent and they are retrieved concurrently via interacting processes. During retrieval, matching item and associative information mutually facilitate one another to yield an amplified holistic signal. Modeling of individuals suggests that this kind of facilitation between item and associative retrieval is a ubiquitous feature of human memory. Copyright © 2017 Elsevier Inc. All rights reserved.
Mobility and orientation aid for blind persons using artificial vision
NASA Astrophysics Data System (ADS)
Costa, Gustavo; Gusberti, Adrián; Graffigna, Juan Pablo; Guzzo, Martín; Nasisi, Oscar
2007-11-01
Blind or vision-impaired persons are limited in their normal life activities. Mobility and orientation of blind persons is an ever-present research subject because no total solution has yet been reached for these activities that pose certain risks for the affected persons. The current work presents the design and development of a device conceived on capturing environment information through stereoscopic vision. The images captured by a couple of video cameras are transferred and processed by configurable and sequential FPGA and DSP devices that issue action signals to a tactile feedback system. Optimal processing algorithms are implemented to perform this feedback in real time. The components selected permit portability; that is, to readily get used to wearing the device.
Sort entropy-based for the analysis of EEG during anesthesia
NASA Astrophysics Data System (ADS)
Ma, Liang; Huang, Wei-Zhi
2010-08-01
The monitoring of anesthetic depth is an absolutely necessary procedure in the process of surgical operation. To judge and control the depth of anesthesia has become a clinical issue which should be resolved urgently. EEG collected wiil be processed by sort entrop in this paper. Signal response of the surface of the cerebral cortex is determined for different stages of patients in the course of anesthesia. EEG is simulated and analyzed through the fast algorithm of sort entropy. The results show that discipline of phasic changes for EEG is very detected accurately,and it has better noise immunity in detecting the EEG anaesthetized than approximate entropy. In conclusion,the computing of Sort entropy algorithm requires shorter time. It has high efficiency and strong anti-interference.
Intracortical signal processing of periodontal ligament sensations in rat.
Minoda, Aoi; Mizoguchi, Naoko; Kobayashi, Masayuki; Suda, Naoto; Muramoto, Kazuyo
2017-07-04
The somatosensory information from the orofacial region, including the periodontal ligament (PDL), is processed in a manner that differs from that used for other body somatosensory information in the related cortices. It was reported that electrical stimulation to rat PDL elicited activation of the insular oral region (IOR) and the primary (S1) and secondary (S2) somatosensory cortices. However, the physiological relationship between S1 and S2/IOR is not well understood. To address this issue, we performed in vivo optical imaging using a voltage-sensitive dye. Our results demonstrated that the electrical stimulation to the PDL of the mandibular incisor evoked the simultaneous activation of S1 and the S2/IOR. The stimulation to the initial response area of the S1 evoked responses in the S2/IOR, and vice versa. An injection of tetrodotoxin (TTX) to the cortical region between S1 and S2/IOR attenuated such elicited responses only in the non-stimulated cortical partner site. The cortico-cortical interaction between S1 and S2/IOR was suppressed by the application of TTX, indicating that these two cortical regions bi-directionally communicate the signal processing of PDL sensations. An injection of FluoroGold™ (FG) to the initial response area in S1 or the S2/IOR showed that FG-positive cells were scattered in the non-injected cortical counterpart. This morphological result demonstrated the presence of a bi-directional intracortical connection between the initial response areas in S1 and the S2/IOR. These findings suggest the presence of a mutual connection between S1 and the S2/IOR as an intracortical signal processing network for orofacial nociception. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
Gray Matter NG2 Cells Display Multiple Ca2+-Signaling Pathways and Highly Motile Processes
Haseleu, Julia; Pohle, Jörg; Karram, Khalad; Trotter, Jacqueline; Seifert, Gerald; Frotscher, Michael; Steinhäuser, Christian; Jabs, Ronald
2011-01-01
NG2 cells, the fourth type of glia in the mammalian CNS, receive synaptic input from neurons. The function of this innervation is unknown yet. Postsynaptic changes in intracellular Ca2+-concentration ([Ca2+]i) might be a possible consequence. We employed transgenic mice with fluorescently labeled NG2 cells to address this issue. To identify Ca2+-signaling pathways we combined patch-clamp recordings, Ca2+-imaging, mRNA-transcript analysis and focal pressure-application of various substances to identified NG2-cells in acute hippocampal slices. We show that activation of voltage-gated Ca2+-channels, Ca2+-permeable AMPA-receptors, and group I metabotropic glutamate-receptors provoke [Ca2+]i-elevations in NG2 cells. The Ca2+-influx is amplified by Ca2+-induced Ca2+-release. Minimal electrical stimulation of presynaptic neurons caused postsynaptic currents but no somatic [Ca2+]i elevations, suggesting that [Ca2+]i elevations in NG2 cells might be restricted to their processes. Local Ca2+-signaling might provoke transmitter release or changes in cell motility. To identify structural prerequisites for such a scenario, we used electron microscopy, immunostaining, mRNA-transcript analysis, and time lapse imaging. We found that NG2 cells form symmetric and asymmetric synapses with presynaptic neurons and show immunoreactivity for vesicular glutamate transporter 1. The processes are actin-based, contain ezrin but not glial filaments, microtubules or endoplasmic reticulum. Furthermore, we demonstrate that NG2 cell processes in situ are highly motile. Our findings demonstrate that gray matter NG2 cells are endowed with the cellular machinery for two-way communication with neighboring cells. PMID:21455301
On recursive least-squares filtering algorithms and implementations. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Hsieh, Shih-Fu
1990-01-01
In many real-time signal processing applications, fast and numerically stable algorithms for solving least-squares problems are necessary and important. In particular, under non-stationary conditions, these algorithms must be able to adapt themselves to reflect the changes in the system and take appropriate adjustments to achieve optimum performances. Among existing algorithms, the QR-decomposition (QRD)-based recursive least-squares (RLS) methods have been shown to be useful and effective for adaptive signal processing. In order to increase the speed of processing and achieve high throughput rate, many algorithms are being vectorized and/or pipelined to facilitate high degrees of parallelism. A time-recursive formulation of RLS filtering employing block QRD will be considered first. Several methods, including a new non-continuous windowing scheme based on selectively rejecting contaminated data, were investigated for adaptive processing. Based on systolic triarrays, many other forms of systolic arrays are shown to be capable of implementing different algorithms. Various updating and downdating systolic algorithms and architectures for RLS filtering are examined and compared in details, which include Householder reflector, Gram-Schmidt procedure, and Givens rotation. A unified approach encompassing existing square-root-free algorithms is also proposed. For the sinusoidal spectrum estimation problem, a judicious method of separating the noise from the signal is of great interest. Various truncated QR methods are proposed for this purpose and compared to the truncated SVD method. Computer simulations provided for detailed comparisons show the effectiveness of these methods. This thesis deals with fundamental issues of numerical stability, computational efficiency, adaptivity, and VLSI implementation for the RLS filtering problems. In all, various new and modified algorithms and architectures are proposed and analyzed; the significance of any of the new method depends crucially on specific application.
NASA Astrophysics Data System (ADS)
Dawidowicz, Karol
2014-12-01
The integration of GPS with GLONASS is very important in satellite-based positioning because it can clearly improve reliability and availability. However, unlike GPS, GLONASS satellites transmit signals at different frequencies. This results in significant difficulties in modeling and ambiguity resolution for integrated GNSS positioning. There are also some difficulties related to the antenna Phase Center Variations (PCV) problem because, as is well known, the PCV is dependent on the received signal frequency dependent. Thus, processing simultaneous observations from different positioning systems, e.g. GPS and GLONASS, we can expect complications resulting from the different structure of signals and differences in satellite constellations. The ASG-EUPOS multifunctional system for precise satellite positioning is a part of the EUPOS project involving countries of Central and Eastern Europe. The number of its users is increasing rapidly. Currently 31 of 101 reference stations are equipped with GPS/GLONASS receivers and the number is still increasing. The aim of this paper is to study the height solution differences caused by using different PCV calibration models in integrated GPS/GLONASS observation processing. Studies were conducted based on the datasets from the ASG-EUPOS network. Since the study was intended to evaluate the impact on height determination from the users' point of view, a so-called "commercial" software was chosen for post-processing. The analysis was done in a baseline mode: 3 days of GNSS data collected with three different receivers and antennas were used. For the purposes of research the daily observations were divided into different sessions with a session length of one hour. The results show that switching between relative and absolute PCV models may cause an obvious effect on height determination. This issue is particularly important when mixed GPS/GLONASS observations are post-processed.
Ultrasonic guided wave interpretation for structural health inspections
NASA Astrophysics Data System (ADS)
Bingham, Jill Paisley
Structural Health Management (SHM) combines the use of onboard sensors with artificial intelligence algorithms to automatically identify and monitor structural health issues. A fully integrated approach to SHM systems demands an understanding of the sensor output relative to the structure, along with sophisticated prognostic systems that automatically draw conclusions about structural integrity issues. Ultrasonic guided wave methods allow us to examine the interaction of multimode signals within key structural components. Since they propagate relatively long distances within plate- and shell-like structures, guided waves allow inspection of greater areas with fewer sensors, making this technique attractive for a variety of applications. This dissertation describes the experimental development of automatic guided wave interpretation for three real world applications. Using the guided wave theories for idealized plates we have systematically developed techniques for identifying the mass loading of underwater limpet mines on US Navy ship hulls, characterizing type and bonding of protective coatings on large diameter pipelines, and detecting the thinning effects of corrosion on aluminum aircraft structural stringers. In each of these circumstances the signals received are too complex for interpretation without knowledge of the guided wave physics. We employ a signal processing technique called the Dynamic Wavelet Fingerprint Technique (DFWT) in order to render the guided wave mode information in two-dimensional binary images. The use of wavelets allows us to keep track of both time and scale features from the original signals. With simple image processing we have developed automatic extraction algorithms for features that correspond to the arrival times of the guided wave modes of interest for each of the applications. Due to the dispersive nature of the guided wave modes, the mode arrival times give details of the structure in the propagation path. For further understanding of how the guided wave modes propagate through the real structures, we have developed parallel processing, 3D elastic wave simulations using the finite integration technique (EFIT). This full field, numeric simulation technique easily examines models too complex for analytical solutions. We have developed the algorithm to handle built up 3D structures as well as layers with different material properties and surface detail. The simulations produce informative visualizations of the guided wave modes in the structures as well as the output from sensors placed in the simulation space to mimic the placement from experiment. Using the previously developed mode extraction algorithms we were then able to compare our 3D EFIT data to their experimental counterparts with consistency.
Imaging Reactive Oxygen Species-Induced Modifications in Living Systems
Maulucci, Giuseppe; Bačić, Goran; Bridal, Lori; Schmidt, Harald H.H.W.; Tavitian, Bertrand; Viel, Thomas; Utsumi, Hideo; Yalçın, A. Süha
2016-01-01
Abstract Significance: Reactive Oxygen Species (ROS) may regulate signaling, ion channels, transcription factors, and biosynthetic processes. ROS-related diseases can be due to either a shortage or an excess of ROS. Recent Advances: Since the biological activity of ROS depends on not only concentration but also spatiotemporal distribution, real-time imaging of ROS, possibly in vivo, has become a need for scientists, with potential for clinical translation. New imaging techniques as well as new contrast agents in clinically established modalities were developed in the previous decade. Critical Issues: An ideal imaging technique should determine ROS changes with high spatio-temporal resolution, detect physiologically relevant variations in ROS concentration, and provide specificity toward different redox couples. Furthermore, for in vivo applications, bioavailability of sensors, tissue penetration, and a high signal-to-noise ratio are additional requirements to be satisfied. Future Directions: None of the presented techniques fulfill all requirements for clinical translation. The obvious way forward is to incorporate anatomical and functional imaging into a common hybrid-imaging platform. Antioxid. Redox Signal. 24, 939–958. PMID:27139586
Liu, Ting-Wu; Niu, Li; Fu, Bin; Chen, Juan; Wu, Fei-Hua; Chen, Juan; Wang, Wen-Hua; Hu, Wen-Jun; He, Jun-Xian; Zheng, Hai-Lei
2013-01-01
Acid rain, as a worldwide environmental issue, can cause serious damage to plants. In this study, we provided the first case study on the systematic responses of arabidopsis (Arabidopsis thaliana (L.) Heynh.) to simulated acid rain (SiAR) by transcriptome approach. Transcriptomic analysis revealed that the expression of a set of genes related to primary metabolisms, including nitrogen, sulfur, amino acid, photosynthesis, and reactive oxygen species metabolism, were altered under SiAR. In addition, transport and signal transduction related pathways, especially calcium-related signaling pathways, were found to play important roles in the response of arabidopsis to SiAR stress. Further, we compared our data set with previously published data sets on arabidopsis transcriptome subjected to various stresses, including wound, salt, light, heavy metal, karrikin, temperature, osmosis, etc. The results showed that many genes were overlapped in several stresses, suggesting that plant response to SiAR is a complex process, which may require the participation of multiple defense-signaling pathways. The results of this study will help us gain further insights into the response mechanisms of plants to acid rain stress.
Unsolved mysteries of Rag GTPase signaling in yeast.
Hatakeyama, Riko; De Virgilio, Claudio
2016-10-01
The target of rapamycin complex 1 (TORC1) plays a central role in controlling eukaryotic cell growth by fine-tuning anabolic and catabolic processes to the nutritional status of organisms and individual cells. Amino acids represent essential and primordial signals that modulate TORC1 activity through the conserved Rag family GTPases. These assemble, as part of larger lysosomal/vacuolar membrane-associated complexes, into heterodimeric sub-complexes, which typically comprise two paralogous Rag GTPases of opposite GTP-/GDP-loading status. The TORC1-stimulating/inhibiting states of these heterodimers are controlled by various guanine nucleotide exchange factor (GEF) and GTPase-activating protein (GAP) complexes, which are remarkably conserved in various eukaryotic model systems. Among the latter, the budding yeast Saccharomyces cerevisiae has been instrumental for the elucidation of basic aspects of Rag GTPase regulation and function. Here, we discuss the current state of the respective research, focusing on the major unsolved issues regarding the architecture, regulation, and function of the Rag GTPase containing complexes in yeast. Decoding these mysteries will undoubtedly further shape our understanding of the conserved and divergent principles of nutrient signaling in eukaryotes.
Unsolved mysteries of Rag GTPase signaling in yeast
Hatakeyama, Riko; De Virgilio, Claudio
2016-01-01
ABSTRACT The target of rapamycin complex 1 (TORC1) plays a central role in controlling eukaryotic cell growth by fine-tuning anabolic and catabolic processes to the nutritional status of organisms and individual cells. Amino acids represent essential and primordial signals that modulate TORC1 activity through the conserved Rag family GTPases. These assemble, as part of larger lysosomal/vacuolar membrane-associated complexes, into heterodimeric sub-complexes, which typically comprise two paralogous Rag GTPases of opposite GTP-/GDP-loading status. The TORC1-stimulating/inhibiting states of these heterodimers are controlled by various guanine nucleotide exchange factor (GEF) and GTPase-activating protein (GAP) complexes, which are remarkably conserved in various eukaryotic model systems. Among the latter, the budding yeast Saccharomyces cerevisiae has been instrumental for the elucidation of basic aspects of Rag GTPase regulation and function. Here, we discuss the current state of the respective research, focusing on the major unsolved issues regarding the architecture, regulation, and function of the Rag GTPase containing complexes in yeast. Decoding these mysteries will undoubtedly further shape our understanding of the conserved and divergent principles of nutrient signaling in eukaryotes. PMID:27400376
Behavioural and physiological limits to vision in mammals
Field, Greg D.
2017-01-01
Human vision is exquisitely sensitive—a dark-adapted observer is capable of reliably detecting the absorption of a few quanta of light. Such sensitivity requires that the sensory receptors of the retina, rod photoreceptors, generate a reliable signal when single photons are absorbed. In addition, the retina must be able to extract this information and relay it to higher visual centres under conditions where very few rods signal single-photon responses while the majority generate only noise. Critical to signal transmission are mechanistic optimizations within rods and their dedicated retinal circuits that enhance the discriminability of single-photon responses by mitigating photoreceptor and synaptic noise. We describe behavioural experiments over the past century that have led to the appreciation of high sensitivity near absolute visual threshold. We further consider mechanisms within rod photoreceptors and dedicated rod circuits that act to extract single-photon responses from cellular noise. We highlight how these studies have shaped our understanding of brain function and point out several unresolved questions in the processing of light near the visual threshold. This article is part of the themed issue ‘Vision in dim light’. PMID:28193817
The upgrade of the Thomson scattering system for measurement on the C-2/C-2U devices.
Zhai, K; Schindler, T; Kinley, J; Deng, B; Thompson, M C
2016-11-01
The C-2/C-2U Thomson scattering system has been substantially upgraded during the latter phase of C-2/C-2U program. A Rayleigh channel has been added to each of the three polychromators of the C-2/C-2U Thomson scattering system. Onsite spectral calibration has been applied to avoid the issue of different channel responses at different spots on the photomultiplier tube surface. With the added Rayleigh channel, the absolute intensity response of the system is calibrated with Rayleigh scattering in argon gas from 0.1 to 4 Torr, where the Rayleigh scattering signal is comparable to the Thomson scattering signal at electron densities from 1 × 10 13 to 4 × 10 14 cm -3 . A new signal processing algorithm, using a maximum likelihood method and including detailed analysis of different noise contributions within the system, has been developed to obtain electron temperature and density profiles. The system setup, spectral and intensity calibration procedure and its outcome, data analysis, and the results of electron temperature/density profile measurements will be presented.
X-chromosome dosage as a modulator of pluripotency, signalling and differentiation?
Schulz, Edda G
2017-11-05
Already during early embryogenesis, before sex-specific hormone production is initiated, sex differences in embryonic development have been observed in several mammalian species. Typically, female embryos develop more slowly than their male siblings. A similar phenotype has recently been described in differentiating murine embryonic stem cells, where a double dose of the X-chromosome halts differentiation until dosage-compensation has been achieved through X-chromosome inactivation. On the molecular level, several processes associated with early differentiation of embryonic stem cells have been found to be affected by X-chromosome dosage, such as the transcriptional state of the pluripotency network, the activity pattern of several signal transduction pathways and global levels of DNA-methylation. This review provides an overview of the sex differences described in embryonic stem cells from mice and discusses a series of X-linked genes that are associated with pluripotency, signalling and differentiation and their potential involvement in mediating the observed X-dosage-dependent effects.This article is part of the themed issue 'X-chromosome inactivation: a tribute to Mary Lyon'. © 2017 The Author(s).
Electromagnetic spectrum management system
Seastrand, Douglas R.
2017-01-31
A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process the unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.
NASA Technical Reports Server (NTRS)
Liu, Kuojuey Ray
1990-01-01
Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.
2017-01-01
Visually guided behaviour at its sensitivity limit relies on single-photon responses originating in a small number of rod photoreceptors. For decades, researchers have debated the neural mechanisms and noise sources that underlie this striking sensitivity. To address this question, we need to understand the constraints arising from the retinal output signals provided by distinct retinal ganglion cell types. It has recently been shown in the primate retina that On and Off parasol ganglion cells, the cell types likely to underlie light detection at the absolute visual threshold, differ fundamentally not only in response polarity, but also in the way they handle single-photon responses originating in rods. The On pathway provides the brain with a thresholded, low-noise readout and the Off pathway with a noisy, linear readout. We outline the mechanistic basis of these different coding strategies and analyse their implications for detecting the weakest light signals. We show that high-fidelity, nonlinear signal processing in the On pathway comes with costs: more single-photon responses are lost and their propagation is delayed compared with the Off pathway. On the other hand, the responses of On ganglion cells allow better intensity discrimination compared with the Off ganglion cell responses near visual threshold. This article is part of the themed issue ‘Vision in dim light’. PMID:28193818
Takeshita, Daisuke; Smeds, Lina; Ala-Laurila, Petri
2017-04-05
Visually guided behaviour at its sensitivity limit relies on single-photon responses originating in a small number of rod photoreceptors. For decades, researchers have debated the neural mechanisms and noise sources that underlie this striking sensitivity. To address this question, we need to understand the constraints arising from the retinal output signals provided by distinct retinal ganglion cell types. It has recently been shown in the primate retina that On and Off parasol ganglion cells, the cell types likely to underlie light detection at the absolute visual threshold, differ fundamentally not only in response polarity, but also in the way they handle single-photon responses originating in rods. The On pathway provides the brain with a thresholded, low-noise readout and the Off pathway with a noisy, linear readout. We outline the mechanistic basis of these different coding strategies and analyse their implications for detecting the weakest light signals. We show that high-fidelity, nonlinear signal processing in the On pathway comes with costs: more single-photon responses are lost and their propagation is delayed compared with the Off pathway. On the other hand, the responses of On ganglion cells allow better intensity discrimination compared with the Off ganglion cell responses near visual threshold.This article is part of the themed issue 'Vision in dim light'. © 2017 The Authors.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ishikawa, M.; Shinohara, K.; Itoga, T.
2008-03-12
Neutron emission profiles are routinely measured in JT-60U Tokamak. Stinbene neuron detectors (SNDs), which combine a Stilbene organic crystal scintillation detector (Stilbene detector) with an analog neutron-gamma pulse shape discrimination (PSD) circuit, have been used to measure neutron flux efficiently. Although the SND has many advantages as a neutron detector, the maximum count rate is limited up to {approx}1x 10{sup 5} counts/s due to the dead time of the analog PSD circuit. To overcome this issue, a digital signal processing (DSP) system using a Flash-ADC has been developed. In this system, anode signals from the photomultiplier of the Stilbene detectormore » are fed to the Flash ADC and digitized. Then, the PSD between neutrons and gamma-rays are performed using software. The photomultiplier tube is also modified to suppress and correct gain fluctuation of the photomultiplier. The DSP system has been installed in the center channel of the vertical neutron collimator system in JT-60U and applied to measurements of neutron flux in JT-60U experiments. Neutron flux are successfully measured with count rate up to {approx}1x 10{sup 6} counts/s without the effect of pile up of detected pulses. The performance of the DSP system as a neutron detector is demonstrated.« less
Modeling Guidelines for Code Generation in the Railway Signaling Context
NASA Technical Reports Server (NTRS)
Ferrari, Alessio; Bacherini, Stefano; Fantechi, Alessandro; Zingoni, Niccolo
2009-01-01
Modeling guidelines constitute one of the fundamental cornerstones for Model Based Development. Their relevance is essential when dealing with code generation in the safety-critical domain. This article presents the experience of a railway signaling systems manufacturer on this issue. Introduction of Model-Based Development (MBD) and code generation in the industrial safety-critical sector created a crucial paradigm shift in the development process of dependable systems. While traditional software development focuses on the code, with MBD practices the focus shifts to model abstractions. The change has fundamental implications for safety-critical systems, which still need to guarantee a high degree of confidence also at code level. Usage of the Simulink/Stateflow platform for modeling, which is a de facto standard in control software development, does not ensure by itself production of high-quality dependable code. This issue has been addressed by companies through the definition of modeling rules imposing restrictions on the usage of design tools components, in order to enable production of qualified code. The MAAB Control Algorithm Modeling Guidelines (MathWorks Automotive Advisory Board)[3] is a well established set of publicly available rules for modeling with Simulink/Stateflow. This set of recommendations has been developed by a group of OEMs and suppliers of the automotive sector with the objective of enforcing and easing the usage of the MathWorks tools within the automotive industry. The guidelines have been published in 2001 and afterwords revisited in 2007 in order to integrate some additional rules developed by the Japanese division of MAAB [5]. The scope of the current edition of the guidelines ranges from model maintainability and readability to code generation issues. The rules are conceived as a reference baseline and therefore they need to be tailored to comply with the characteristics of each industrial context. Customization of these recommendations has been performed for the automotive control systems domain in order to enforce code generation [7]. The MAAB guidelines have been found profitable also in the aerospace/avionics sector [1] and they have been adopted by the MathWorks Aerospace Leadership Council (MALC). General Electric Transportation Systems (GETS) is a well known railway signaling systems manufacturer leading in Automatic Train Protection (ATP) systems technology. Inside an effort of adopting formal methods within its own development process, GETS decided to introduce system modeling by means of the MathWorks tools [2], and in 2008 chose to move to code generation. This article reports the experience performed by GETS in developing its own modeling standard through customizing the MAAB rules for the railway signaling domain and shows the result of this experience with a successful product development story.
Involvement of Redox State in the Aging of Drosophila melanogaster
Radyuk, Svetlana N.; Sohal, Rajindar S.
2013-01-01
Abstract Significance: The main objective of this review was to provide an exposition of investigations, conducted in Drosophila melanogaster, on the role of reactive oxygen species and redox state in the aging process. While early transgenic studies did not clearly support the validity of the oxidative stress hypothesis of aging, predicated on the accumulation of structural damage, they spawned a broader search for redox-related effects that might impact the aging process. Recent Advances: Initial evidence implicating the thiol redox state as a possible causative factor in aging has been obtained in Drosophila. Overexpression of genes, such as GCL, G6PD, Prx2, and Prx5, which are involved in the maintenance of thiol redox homeostasis, has strong positive effects on longevity. Further, the depletion of peroxiredoxin activity in the mitochondria through the double knockdown of Prx5 and Prx3 not only results in a redox crisis but also elicits a rapid aging phenotype. Critical Issues: Herein, we summarize the present status of knowledge about the main components of the machinery controlling thiol redox homeostasis and describe how age-related redox fluctuations might impact aging more acutely through disruption of the redox-sensitive signaling mechanisms rather than via the simple accumulation of structural damage. Future Directions: Based on these initial insights into the plausible impact of redox fluctuations on redox signaling, future studies should focus on the pathways that have been explicitly implicated in aging, such as insulin signaling, TOR, and JNK/FOXO, with particular attention to elements that are redox sensitive. Antioxid. Redox Signal. 19, 788–803. PMID:23458359
Hydrogen Sulfide as an Oxygen Sensor
2015-01-01
Abstract Significance Although oxygen (O2)-sensing cells and tissues have been known for decades, the identity of the O2-sensing mechanism has remained elusive. Evidence is accumulating that O2-dependent metabolism of hydrogen sulfide (H2S) is this enigmatic O2 sensor. Recent Advances The elucidation of biochemical pathways involved in H2S synthesis and metabolism have shown that reciprocal H2S/O2 interactions have been inexorably linked throughout eukaryotic evolution; there are multiple foci by which O2 controls H2S inactivation, and the effects of H2S on downstream signaling events are consistent with those activated by hypoxia. H2S-mediated O2 sensing has been demonstrated in a variety of O2-sensing tissues in vertebrate cardiovascular and respiratory systems, including smooth muscle in systemic and respiratory blood vessels and airways, carotid body, adrenal medulla, and other peripheral as well as central chemoreceptors. Critical Issues Information is now needed on the intracellular location and stoichometry of these signaling processes and how and which downstream effectors are activated by H2S and its metabolites. Future Directions Development of specific inhibitors of H2S metabolism and effector activation as well as cellular organelle-targeted compounds that release H2S in a time- or environmentally controlled way will not only enhance our understanding of this signaling process but also provide direction for future therapeutic applications. Antioxid. Redox Signal. 22, 377–397. “Nothing in Biology Makes Sense Except in the Light of Evolution” —Theodosius Dobzhansky (29) PMID:24801248
Intelligence Reform and Implications for North Korea’s Weapons of Mass Destruction Program
2005-09-01
August 2005). 36 Desmond Ball, “Signals Intelligence in North Korea,” Jane’s Intelligence Review 8, Issue 1 (January 1996 ), 1. 26...Ball, “Signals Intelligence in North Korea,” Jane’s Intelligence Review 8, Issue 1 (January 1996 ), 10. 38 Jeremy Kirk, “Intel Experts: N. Korea a...www.wmd.gov/report/index.html (accessed August 2005). Hereafter referred to as WMD Commission Report. 47 Michael Warner and J. Kenneth McDonald, “U.S
Spatial acoustic signal processing for immersive communication
NASA Astrophysics Data System (ADS)
Atkins, Joshua
Computing is rapidly becoming ubiquitous as users expect devices that can augment and interact naturally with the world around them. In these systems it is necessary to have an acoustic front-end that is able to capture and reproduce natural human communication. Whether the end point is a speech recognizer or another human listener, the reduction of noise, reverberation, and acoustic echoes are all necessary and complex challenges. The focus of this dissertation is to provide a general method for approaching these problems using spherical microphone and loudspeaker arrays.. In this work, a theory of capturing and reproducing three-dimensional acoustic fields is introduced from a signal processing perspective. In particular, the decomposition of the spatial part of the acoustic field into an orthogonal basis of spherical harmonics provides not only a general framework for analysis, but also many processing advantages. The spatial sampling error limits the upper frequency range with which a sound field can be accurately captured or reproduced. In broadband arrays, the cost and complexity of using multiple transducers is an issue. This work provides a flexible optimization method for determining the location of array elements to minimize the spatial aliasing error. The low frequency array processing ability is also limited by the SNR, mismatch, and placement error of transducers. To address this, a robust processing method is introduced and used to design a reproduction system for rendering over arbitrary loudspeaker arrays or binaurally over headphones. In addition to the beamforming problem, the multichannel acoustic echo cancellation (MCAEC) issue is also addressed. A MCAEC must adaptively estimate and track the constantly changing loudspeaker-room-microphone response to remove the sound field presented over the loudspeakers from that captured by the microphones. In the multichannel case, the system is overdetermined and many adaptive schemes fail to converge to the true impulse response. This forces the need to track both the near and far end room responses. A transform domain method that mitigates this problem is derived and implemented. Results with a real system using a 16-channel loudspeaker array and 32-channel microphone array are presented.
Urban Infrasound Observations - Examples from July 4th 2012
NASA Astrophysics Data System (ADS)
McComas, S.; Hayward, C.; Golden, P.; McKenna, M.; Simpson, C.
2012-12-01
Historical observations indicate that urban environments are rich in infrasound signals and thus provide the opportunity to characterize sources, monitor propagation path effects, and document diurnal and seasonal variability in the urban acoustical noise environment. If infrasound is to be used as viable signal for monitoring the urban environment and for identifying human and natural activities, the following key scientific issues must be examined: (1) What are the typical infrastructural sources of infrasound and their levels? (2) How saturated is the urban environment with infrasonic signals, i.e., do many signals propagate over long distances to reach a given sensor, or can individual sources be well differentiated? (3) Does infrasound provide new information to characterize rapidly evolving physical, cultural, economic, and military actions of interest? Each of these issues will be addressed with the acquisition and analysis of data from this observational study, including an analysis of the seasonal variation in infrasound noise and propagation effects. Such studies differ from typical infrasound work in that the propagation paths are short, i.e. ~1- 100 km, and signal frequencies can extend from the infrasound band to the low frequency acoustic band (100 Hz). We have begun a study to address some of the unique infrasound research questions and sources found in an urban environment. Our initial investigation of the data and a description of the identified noise and source signals are reported here. Three seismo-acoustic arrays were deployed on rooftops across the Southern Methodist University campus in Dallas, Texas, to characterize the urban infrasound environment. The first rooftop array, the Moody Coliseum, includes four elements at the corners of a 38m square and one element in the center. A seismometer is included at the central element. The second Multi-rooftop Array is spread across multiple building rooftops and has a 140m aperture. The third array, the Heroy Building Rooftop Array, is a two-element 30m line on a single rooftop. Large-scale fireworks displays in Dallas on 4 July 2012 provided an opportunity to identify and characterize known signals in an urban setting. The identified events were associated with one of these fireworks displays about 2 km from the arrays. Signals from these sources were used to tune processing parameters for an automatic coherent detection process, Progressive Multichannel Correlation Method (PMCC). PMCC was then used to scan the data for all possible firework sources in the urban environment and determine temporal, back azimuth, apparent velocity, and frequency information about the sources. The signal frequencies seen were 10-80 Hz and documented the details of the nearly 30 minute firework show. The resulting PMCC analysis showed potential to effectively identify other, lower frequency sources in the urban environment. These data were also is used to characterize the noise environment. Significant roof-to-roof noise differences may be related to the building configurations and mechanical equipment, as well as the interactions of the winds with the structures. During the evening of July 4th , additional ground deployed infrasound gauges provided a comparison of free surface and rooftop measurements. Permission to publish was granted by Director, Geotechnical and Structures Laboratory.
Digital tanlock loop architecture with no delay
NASA Astrophysics Data System (ADS)
Al-Kharji AL-Ali, Omar; Anani, Nader; Al-Araji, Saleh; Al-Qutayri, Mahmoud; Ponnapalli, Prasad
2012-02-01
This article proposes a new architecture for a digital tanlock loop which eliminates the time-delay block. The ? (rad) phase shift relationship between the two channels, which is generated by the delay block in the conventional time-delay digital tanlock loop (TDTL), is preserved using two quadrature sampling signals for the loop channels. The proposed system outperformed the original TDTL architecture, when both systems were tested with frequency shift keying input signal. The new system demonstrated better linearity and acquisition speed as well as improved noise performance compared with the original TDTL architecture. Furthermore, the removal of the time-delay block enables all processing to be digitally performed, which reduces the implementation complexity. Both the original TDTL and the new architecture without the delay block were modelled and simulated using MATLAB/Simulink. Implementation issues, including complexity and relation to simulation of both architectures, are also addressed.
Jordan, Timothy R; Abedipour, Lily
2010-01-01
Hearing the sound of laughter is important for social communication, but processes contributing to the audibility of laughter remain to be determined. Production of laughter resembles production of speech in that both involve visible facial movements accompanying socially significant auditory signals. However, while it is known that speech is more audible when the facial movements producing the speech sound can be seen, similar visual enhancement of the audibility of laughter remains unknown. To address this issue, spontaneously occurring laughter was edited to produce stimuli comprising visual laughter, auditory laughter, visual and auditory laughter combined, and no laughter at all (either visual or auditory), all presented in four levels of background noise. Visual laughter and no-laughter stimuli produced very few reports of auditory laughter. However, visual laughter consistently made auditory laughter more audible, compared to the same auditory signal presented without visual laughter, resembling findings reported previously for speech.
Demetris, A J; III, John G Lunz; Specht, Susan; Nozaki, Isao
2006-01-01
Basic and translational wound healing research in the biliary tree lag significantly behind similar studies on the skin and gastrointestinal tract. This is at least partly attributable to lack of easy access to the biliary tract for study. But clinical relevance, more interest in biliary epithelial cell (BEC) pathophysiology, and widespread availability of BEC cultures are factors reversing this trend. In the extra-hepatic biliary tree, ineffectual wound healing, scarring and stricture development are pressing issues. In the smallest intra-hepatic bile ducts either impaired BEC proliferation or an exuberant response can contribute to liver disease. Chronic inflammation and persistent wound healing reactions in large and small bile ducts often lead to liver cancer. General concepts of wound healing as they apply to the biliary tract, importance of cellular processes dependent on IL-6/gp130/STAT3 signaling pathways, unanswered questions, and future directions are discussed. PMID:16773708
Workshop on Algorithms for Time-Series Analysis
NASA Astrophysics Data System (ADS)
Protopapas, Pavlos
2012-04-01
abstract-type="normal">SummaryThis Workshop covered the four major subjects listed below in two 90-minute sessions. Each talk or tutorial allowed questions, and concluded with a discussion. Classification: Automatic classification using machine-learning methods is becoming a standard in surveys that generate large datasets. Ashish Mahabal (Caltech) reviewed various methods, and presented examples of several applications. Time-Series Modelling: Suzanne Aigrain (Oxford University) discussed autoregressive models and multivariate approaches such as Gaussian Processes. Meta-classification/mixture of expert models: Karim Pichara (Pontificia Universidad Católica, Chile) described the substantial promise which machine-learning classification methods are now showing in automatic classification, and discussed how the various methods can be combined together. Event Detection: Pavlos Protopapas (Harvard) addressed methods of fast identification of events with low signal-to-noise ratios, enlarging on the characterization and statistical issues of low signal-to-noise ratios and rare events.
Regulation of PLCβ2 by the electrostatic and mechanical properties of lipid bilayers
Arduin, Alessia; Gaffney, Piers R. J.; Ces, Oscar
2015-01-01
Phosphoinositide-specific phospholipase C (PLC) is an important family of enzymes constituting a junction between phosphoinositide lipid signaling and the trans-membrane signal transduction processes that are crucial to many living cells. However, the regulatory mechanism of PLC is not yet understood in detail. To address this issue, activity studies were carried out using lipid vesicles in a model system that was specifically designed to study protein-protein and lipid-protein interactions in concert. Evidence was found for a direct interaction between PLC and the GTPases that mediate phospholipase activation. Furthermore, for the first time, the relationships between PLC activity and substrate presentation in lipid vesicles of various sizes, as well as lipid composition and membrane mechanical properties, were analyzed. PLC activity was found to depend upon the electrostatic potential and the stored curvature elastic stress of the lipid membranes. PMID:26243281
Hu, Jianping; Lee, Dianne; Hu, Sien; Zhang, Sheng; Chao, Herta; Li, Chiang-Shan R
2016-06-01
Personality traits contribute to variation in human behavior, including the propensity to take risk. Extant work targeted risk-taking processes with an explicit manipulation of reward, but it remains unclear whether personality traits influence simple decisions such as speeded versus delayed responses during cognitive control. We explored this issue in an fMRI study of the stop signal task, in which participants varied in response time trial by trial, speeding up and risking a stop error or slowing down to avoid errors. Regional brain activations to speeded versus delayed motor responses (risk-taking) were correlated to novelty seeking (NS), harm avoidance (HA) and reward dependence (RD), with age and gender as covariates, in a whole brain regression. At a corrected threshold, the results showed a positive correlation between NS and risk-taking responses in the dorsomedial prefrontal, bilateral orbitofrontal, and frontopolar cortex, and between HA and risk-taking responses in the parahippocampal gyrus and putamen. No regional activations varied with RD. These findings demonstrate that personality traits influence the neural processes of executive control beyond behavioral tasks that involve explicit monetary reward. The results also speak broadly to the importance of characterizing inter-subject variation in studies of cognition and brain functions.
GPS Data Filtration Method for Drive Cycle Analysis Applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Duran, A.; Earleywine, M.
2013-02-01
When employing GPS data acquisition systems to capture vehicle drive-cycle information, a number of errors often appear in the raw data samples, such as sudden signal loss, extraneous or outlying data points, speed drifting, and signal white noise, all of which limit the quality of field data for use in downstream applications. Unaddressed, these errors significantly impact the reliability of source data and limit the effectiveness of traditional drive-cycle analysis approaches and vehicle simulation software. Without reliable speed and time information, the validity of derived metrics for drive cycles, such as acceleration, power, and distance, become questionable. This study exploresmore » some of the common sources of error present in raw onboard GPS data and presents a detailed filtering process designed to correct for these issues. Test data from both light and medium/heavy duty applications are examined to illustrate the effectiveness of the proposed filtration process across the range of vehicle vocations. Graphical comparisons of raw and filtered cycles are presented, and statistical analyses are performed to determine the effects of the proposed filtration process on raw data. Finally, an evaluation of the overall benefits of data filtration on raw GPS data and present potential areas for continued research is presented.« less
Rabasa, Cristina; Delgado-Morales, Raúl; Muñoz-Abellán, Cristina; Nadal, Roser; Armario, Antonio
2011-02-02
Repeated exposure to the same stressor very often results in a reduction of some prototypical stress responses, namely those related to the hypothalamic-pituitary-adrenal (HPA) and sympatho-medullo-adrenal (SMA) axes. This reduced response to repeated exposure to the same (homotypic) stressor (adaptation) is usually considered as a habituation-like process, and therefore, a non-associative type of learning. However, there is some evidence that contextual cues and therefore associative processes could contribute to adaptation. In the present study we demonstrated in two experiments using adult male rats that repeated daily exposure to restraint (REST) or immobilization on boards (IMO) reduced the HPA (plasma levels of ACTH and corticosterone) and glucose responses to the homotypic stressor and such reduced responses remained intact when all putative cues associated to the procedure (experimenter, way of transporting to the stress room, stress boxes, stress room and colour of the restrainer in the case of REST) were modified on the next day. Therefore, the present results do not favour the view that adaptation after repeated exposure to a stressor may involve associative processes related to signals predicting the imminence of the stressors, but more studies are needed on this issue. Copyright © 2010 Elsevier B.V. All rights reserved.
Robust real-time extraction of respiratory signals from PET list-mode data.
Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas
2018-05-01
Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.
Addressing multi-use issues in sustainable forest management with signal-transfer modeling
Robert J. Luxmoore; William W. Hargrove; M. Lynn Tharp; W. Mac Post; Michael W. Berry; Karen S. Minser; Wendell P. Cropper; Dale W. Johnson; Boris Zeide; Ralph L. Amateis; Harold E. Burkhart; V. Clark Baldwin; Kelly D. Peterson
2002-01-01
Management decisions concerning impacts of projected changes in environmental and social conditions on multi-use forest products and services, such as productivity, water supply or carbon sequestration, may be facilitated with signal-transfer modeling. This simulation method utilizes a hierarchy of simulators in which the integrated responses (signals) from smaller-...
Safety Signals as Instrumental Reinforcers during Free-Operant Avoidance
ERIC Educational Resources Information Center
Fernando, Anushka B. P.; Urcelay, Gonzalo P.; Mar, Adam C.; Dickinson, Anthony; Robbins, Trevor W.
2014-01-01
Safety signals provide "relief" through predicting the absence of an aversive event. At issue is whether these signals also act as instrumental reinforcers. Four experiments were conducted using a free-operant lever-press avoidance paradigm in which each press avoided shock and was followed by the presentation of a 5-sec auditory safety…
Wavelet analysis of poorly-focused ultrasonic signal of pressure tube inspection in nuclear industry
NASA Astrophysics Data System (ADS)
Zhao, Huan; Gachagan, Anthony; Dobie, Gordon; Lardner, Timothy
2018-04-01
Pressure tube fabrication and installment challenges combined with natural sagging over time can produce issues with probe alignment for pressure tube inspection of the primary circuit of CANDU reactors. The ability to extract accurate defect depth information from poorly focused ultrasonic signals would reduce additional inspection procedures, which leads to a significant time and cost saving. Currently, the defect depth measurement protocol is to simply calculate the time difference between the peaks of the echo signals from the tube surface and the defect from a single element probe focused at the back-wall depth. When alignment issues are present, incorrect focusing results in interference within the returning echo signal. This paper proposes a novel wavelet analysis method that employs the Haar wavelet to decompose the original poorly focused A-scan signal and reconstruct detailed information based on a selected high frequency component range within the bandwidth of the transducer. Compared to the original signal, the wavelet analysis method provides additional characteristic defect information and an improved estimate of defect depth with errors less than 5%.
Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals
NASA Astrophysics Data System (ADS)
Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin
How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.
Fundamentals of image acquisition and processing in the digital era.
Farman, A G
2003-01-01
To review the historic context for digital imaging in dentistry and to outline the fundamental issues related to digital imaging modalities. Digital dental X-ray images can be achieved by scanning analog film radiographs (secondary capture), with photostimulable phosphors, or using solid-state detectors (e.g. charge-coupled device and complementary metal oxide semiconductor). There are four characteristics that are basic to all digital image detectors; namely, size of active area, signal-to-noise ratio, contrast resolution and the spatial resolution. To perceive structure in a radiographic image, there needs to be sufficient difference between contrasting densities. This primarily depends on the differences in the attenuation of the X-ray beam by adjacent tissues. It is also depends on the signal received; therefore, contrast tends to increase with increased exposure. Given adequate signal and sufficient differences in radiodensity, contrast will be sufficient to differentiate between adjacent structures, irrespective of the recording modality and processing used. Where contrast is not sufficient, digital images can sometimes be post-processed to disclose details that would otherwise go undetected. For example, cephalogram isodensity mapping can improve soft tissue detail. It is concluded that it could be a further decade or two before three-dimensional digital imaging systems entirely replace two-dimensional analog films. Such systems need not only to produce prettier images, but also to provide a demonstrable evidence-based higher standard of care at a cost that is not economically prohibitive for the practitioner or society, and which allows efficient and effective workflow within the business of dental practice.
Real-time monitoring of drowsiness through wireless nanosensor systems
NASA Astrophysics Data System (ADS)
Ramasamy, Mouli; Varadan, Vijay K.
2016-04-01
Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Generally, the bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper reviews the design aspects of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the textile based nanosensors mounted on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through ZigBee communication. This system is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the fatigue level. This approach of using a wireless, real time, dry sensor on a flexible substrate mitigates obtrusiveness that is expected from a wearable system. We have previously presented the results of the aforementioned wearable systems. This paper aims to extend our work conceptually through a review of engineering and medical techniques involved in wearable systems to detect drowsiness.
Guo, Shuxiang; Pang, Muye; Gao, Baofeng; Hirata, Hideyuki; Ishihara, Hidenori
2015-01-01
The surface electromyography (sEMG) technique is proposed for muscle activation detection and intuitive control of prostheses or robot arms. Motion recognition is widely used to map sEMG signals to the target motions. One of the main factors preventing the implementation of this kind of method for real-time applications is the unsatisfactory motion recognition rate and time consumption. The purpose of this paper is to compare eight combinations of four feature extraction methods (Root Mean Square (RMS), Detrended Fluctuation Analysis (DFA), Weight Peaks (WP), and Muscular Model (MM)) and two classifiers (Neural Networks (NN) and Support Vector Machine (SVM)), for the task of mapping sEMG signals to eight upper-limb motions, to find out the relation between these methods and propose a proper combination to solve this issue. Seven subjects participated in the experiment and six muscles of the upper-limb were selected to record sEMG signals. The experimental results showed that NN classifier obtained the highest recognition accuracy rate (88.7%) during the training process while SVM performed better in real-time experiments (85.9%). For time consumption, SVM took less time than NN during the training process but needed more time for real-time computation. Among the four feature extraction methods, WP had the highest recognition rate for the training process (97.7%) while MM performed the best during real-time tests (94.3%). The combination of MM and NN is recommended for strict real-time applications while a combination of MM and SVM will be more suitable when time consumption is not a key requirement. PMID:25894941
Space Debris Detection on the HPDP, a Coarse-Grained Reconfigurable Array Architecture for Space
NASA Astrophysics Data System (ADS)
Suarez, Diego Andres; Bretz, Daniel; Helfers, Tim; Weidendorfer, Josef; Utzmann, Jens
2016-08-01
Stream processing, widely used in communications and digital signal processing applications, requires high- throughput data processing that is achieved in most cases using Application-Specific Integrated Circuit (ASIC) designs. Lack of programmability is an issue especially in space applications, which use on-board components with long life-cycles requiring applications updates. To this end, the High Performance Data Processor (HPDP) architecture integrates an array of coarse-grained reconfigurable elements to provide both flexible and efficient computational power suitable for stream-based data processing applications in space. In this work the capabilities of the HPDP architecture are demonstrated with the implementation of a real-time image processing algorithm for space debris detection in a space-based space surveillance system. The implementation challenges and alternatives are described making trade-offs to improve performance at the expense of negligible degradation of detection accuracy. The proposed implementation uses over 99% of the available computational resources. Performance estimations based on simulations show that the HPDP can amply match the application requirements.
Evaluation of Vehicle Detection Systems for Traffic Signal Operations
DOT National Transportation Integrated Search
2016-10-16
Typical vehicle detection systems used in traffic signal operations are comprised of inductive loop detectors. Because of costs, installation challenges, and operation and maintenance issues, many alternative non-intrusive systems have been dev...
Engelberg, David; Perlman, Riki; Levitzki, Alexander
2014-12-01
In the very first article that appeared in Cellular Signalling, published in its inaugural issue in October 1989, we reviewed signal transduction pathways in Saccharomyces cerevisiae. Although this yeast was already a powerful model organism for the study of cellular processes, it was not yet a valuable instrument for the investigation of signaling cascades. In 1989, therefore, we discussed only two pathways, the Ras/cAMP and the mating (Fus3) signaling cascades. The pivotal findings concerning those pathways undoubtedly contributed to the realization that yeast is a relevant model for understanding signal transduction in higher eukaryotes. Consequently, the last 25 years have witnessed the discovery of many signal transduction pathways in S. cerevisiae, including the high osmotic glycerol (Hog1), Stl2/Mpk1 and Smk1 mitogen-activated protein (MAP) kinase pathways, the TOR, AMPK/Snf1, SPS, PLC1 and Pkr/Gcn2 cascades, and systems that sense and respond to various types of stress. For many cascades, orthologous pathways were identified in mammals following their discovery in yeast. Here we review advances in the understanding of signaling in S. cerevisiae over the last 25 years. When all pathways are analyzed together, some prominent themes emerge. First, wiring of signaling cascades may not be identical in all S. cerevisiae strains, but is probably specific to each genetic background. This situation complicates attempts to decipher and generalize these webs of reactions. Secondly, the Ras/cAMP and the TOR cascades are pivotal pathways that affect all processes of the life of the yeast cell, whereas the yeast MAP kinase pathways are not essential. Yeast cells deficient in all MAP kinases proliferate normally. Another theme is the existence of central molecular hubs, either as single proteins (e.g., Msn2/4, Flo11) or as multisubunit complexes (e.g., TORC1/2), which are controlled by numerous pathways and in turn determine the fate of the cell. It is also apparent that lipid signaling is less developed in yeast than in higher eukaryotes. Finally, feedback regulatory mechanisms seem to be at least as important and powerful as the pathways themselves. In the final chapter of this essay we dare to imagine the essence of our next review on signaling in yeast, to be published on the 50th anniversary of Cellular Signalling in 2039. Copyright © 2014 Elsevier Inc. All rights reserved.
Research in speech communication.
Flanagan, J
1995-10-24
Advances in digital speech processing are now supporting application and deployment of a variety of speech technologies for human/machine communication. In fact, new businesses are rapidly forming about these technologies. But these capabilities are of little use unless society can afford them. Happily, explosive advances in microelectronics over the past two decades have assured affordable access to this sophistication as well as to the underlying computing technology. The research challenges in speech processing remain in the traditionally identified areas of recognition, synthesis, and coding. These three areas have typically been addressed individually, often with significant isolation among the efforts. But they are all facets of the same fundamental issue--how to represent and quantify the information in the speech signal. This implies deeper understanding of the physics of speech production, the constraints that the conventions of language impose, and the mechanism for information processing in the auditory system. In ongoing research, therefore, we seek more accurate models of speech generation, better computational formulations of language, and realistic perceptual guides for speech processing--along with ways to coalesce the fundamental issues of recognition, synthesis, and coding. Successful solution will yield the long-sought dictation machine, high-quality synthesis from text, and the ultimate in low bit-rate transmission of speech. It will also open the door to language-translating telephony, where the synthetic foreign translation can be in the voice of the originating talker.
Iqbal, Waqas; Alkarim, Saleh; AlHejin, Ahmed; Mukhtar, Hasan; Saini, Kulvinder S
2016-11-15
Tumor comprises of heterogeneous population of cells where not all the disseminated cancer cells have the prerogative and "in-build genetic cues" to form secondary tumors. Cells with stem like properties complemented by key signaling molecules clearly have shown to exhibit selective growth advantage to form tumors at distant metastatic sites. Thus, defining the role of cancer stem cells (CSC) in tumorigenesis and metastasis is emerging as a major thrust area for therapeutic intervention. Precise relationship and regulatory mechanisms operating in various signal transduction pathways during cancer dissemination, extravasation and angiogenesis still remain largely enigmatic. How the crosstalk amongst circulating tumor cells (CTC), epithelial mesenchymal transition (EMT) process and CSC is coordinated for initiating the metastasis at secondary tissues, and during cancer relapse could be of great therapeutic interest. The signal transduction mechanisms facilitating the dissemination, infiltration of CSC into blood stream, extravasations, progression of metastasis phenotype and angiogenesis, at distant organs, are the key pathologically important vulnerabilities being elucidated. Therefore, current new drug discovery focus has shifted towards finding "key driver genes" operating in parallel signaling pathways, during quiescence, survival and maintenance of stemness in CSC. Understanding these mechanisms could open new horizons for tackling the issue of cancer recurrence and metastasis-the cause of ~90% cancer associated mortality. To design futuristic & targeted therapies, we propose a multi-pronged strategy involving small molecules, RNA interference, vaccines, antibodies and other biotechnological modalities against CSC and the metastatic signal transduction cascade.
Electromagnetic spectrum management system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seastrand, Douglas R.
A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process themore » unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.« less
NASA Astrophysics Data System (ADS)
Parekh, Ankit
Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal decomposition technique for an important biomedical signal processing problem: the detection of sleep spindles and K-complexes in human sleep electroencephalography (EEG). We propose a non-linear model for the EEG consisting of three components: (1) a transient (sparse piecewise constant) component, (2) a low-frequency component, and (3) an oscillatory component. The oscillatory component admits a sparse time-frequency representation. Using a convex objective function, we propose a fast non-linear optimization algorithm to estimate the three components in the proposed signal model. The low-frequency and oscillatory components are then used to estimate the K-complexes and sleep spindles respectively. The proposed detection method is shown to outperform several state-of-the-art automated sleep spindles detection methods.
Exponential Modelling for Mutual-Cohering of Subband Radar Data
NASA Astrophysics Data System (ADS)
Siart, U.; Tejero, S.; Detlefsen, J.
2005-05-01
Increasing resolution and accuracy is an important issue in almost any type of radar sensor application. However, both resolution and accuracy are strongly related to the available signal bandwidth and energy that can be used. Nowadays, often several sensors operating in different frequency bands become available on a sensor platform. It is an attractive goal to use the potential of advanced signal modelling and optimization procedures by making proper use of information stemming from different frequency bands at the RF signal level. An important prerequisite for optimal use of signal energy is coherence between all contributing sensors. Coherent multi-sensor platforms are greatly expensive and are thus not available in general. This paper presents an approach for accurately estimating object radar responses using subband measurements at different RF frequencies. An exponential model approach allows to compensate for the lack of mutual coherence between independently operating sensors. Mutual coherence is recovered from the a-priori information that both sensors have common scattering centers in view. Minimizing the total squared deviation between measured data and a full-range exponential signal model leads to more accurate pole angles and pole magnitudes compared to single-band optimization. The model parameters (range and magnitude of point scatterers) after this full-range optimization process are also more accurate than the parameters obtained from a commonly used super-resolution procedure (root-MUSIC) applied to the non-coherent subband data.
NASA Astrophysics Data System (ADS)
Ushakov, V. N.
1995-10-01
A video-frequency acousto-optical correlator with spatial integration, which widens the functional capabilities of correlation-type acousto-optical processors, is described. The correlator is based on a two-dimensional reference transparency and it can filter arbitrary video signals of spectral width limited by the pass band of an acousto-optical modulator. The calculated pulse characteristic is governed by the structure of the reference transparency. A procedure for the synthesis of this transparency is considered and experimental results are reported.
Advances in biomedical engineering and biotechnology during 2013-2014.
Liu, Feng; Wang, Ying; Burkhart, Timothy A; González Penedo, Manuel Francisco; Ma, Shaodong
2014-01-01
The 3rd International Conference on Biomedical Engineering and Biotechnology (iCBEB 2014), held in Beijing from the 25th to the 28th of September 2014, is an annual conference that intends to provide an opportunity for researchers and practitioners around the world to present the most recent advances and future challenges in the fields of biomedical engineering, biomaterials, bioinformatics and computational biology, biomedical imaging and signal processing, biomechanical engineering and biotechnology, amongst others. The papers published in this issue are selected from this conference, which witnesses the advances in biomedical engineering and biotechnology during 2013-2014.
Preface: Special Topic on Single-Molecule Biophysics
NASA Astrophysics Data System (ADS)
Makarov, Dmitrii E.; Schuler, Benjamin
2018-03-01
Single-molecule measurements are now almost routinely used to study biological systems and processes. The scope of this special topic emphasizes the physics side of single-molecule observations, with the goal of highlighting new developments in physical techniques as well as conceptual insights that single-molecule measurements bring to biophysics. This issue also comprises recent advances in theoretical physical models of single-molecule phenomena, interpretation of single-molecule signals, and fundamental areas of statistical mechanics that are related to single-molecule observations. A particular goal is to illustrate the increasing synergy between theory, simulation, and experiment in single-molecule biophysics.
A survey of decision tree classifier methodology
NASA Technical Reports Server (NTRS)
Safavian, S. R.; Landgrebe, David
1991-01-01
Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.
Development of dual sensor hand-held detector
NASA Astrophysics Data System (ADS)
Sezgin, Mehmet
2010-04-01
In this paper hand-held dual sensor detector development requirements are considered dedicated to buried object detection. Design characteristics of such a system are categorized and listed. Hardware and software structures, ergonomics, user interface, environmental and EMC/EMI tests to be applied and performance test issues are studied. Main properties of the developed system (SEZER) are presented, which contains Metal Detector (MD) and Ground Penetrating Radar (GPR). The realized system has ergonomic structure and can detect both metallic and non-metallic buried objects. Moreover classification of target is possible if it was defined to the signal processing software in learning phase.
A survey of decision tree classifier methodology
NASA Technical Reports Server (NTRS)
Safavian, S. Rasoul; Landgrebe, David
1990-01-01
Decision Tree Classifiers (DTC's) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps, the most important feature of DTC's is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issue. After considering potential advantages of DTC's over single stage classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.
Piezoelectric Sol-Gel Composite Film Fabrication by Stencil Printing.
Kaneko, Tsukasa; Iwata, Kazuki; Kobayashi, Makiko
2015-09-01
Piezoelectric films using sol-gel composites could be useful as ultrasonic transducers in various industrial fields. For sol-gel composite film fabrication, the spray coating technique has been used often because of its adaptability for various substrates. However, the spray technique requires multiple spray coating processes and heating processes and this is an issue of concern, especially for on-site fabrication in controlled areas. Stencil printing has been developed to solve this issue because this method can be used to fabricate thick sol-gel composite films with one coating process. In this study, PbTiO3 (PT)/Pb(Zr,Ti)O3 (PZT) films, PZT/PZT films, and Bi4Ti3O12 (BiT)/PZT films were fabricated by stencil printing, and PT/ PZT films were also fabricated using the spray technique. After fabrication, a thermal cycle test was performed for the samples to compare their ultrasonic performance. The sensitivity and signal-to-noise-ratio (SNR) of the ultrasonic response of PT/PZT fabricated by stencil printing were equivalent to those of PT/PZT fabricated by the spray technique, and better than those of other samples between room temperature and 300°C. Therefore, PT/PZT films fabricated by stencil printing could be a good candidate for nondestructive testing (NDT) ultrasonic transducers from room temperature to 300°C.
Miller, Brett; O’Donnell, Carol
2013-01-01
The cumulative body of eye movement research provides significant insight into how readers process text. The heart of this work spans roughly 40 years reflecting the maturity of both the topics under study and experimental approaches used to investigate reading. Recent technological advancements offer increased flexibility to the field providing the potential to more concertedly study reading and literacy from an individual differences perspective. Historically, eye movement research focused far less on developmental issues related to individual differences in reading; however, this issue and the broader change it represents signal a meaningful transition inclusive of individual differences. The six papers in this special issue signify the recent, increased attention to and recognition of eye movement research’s transition to emphasize individual differences in reading while appreciating early contributions (e.g., Rayner, 1986) in this direction. We introduce these six papers and provide some historical context for the use of eye movement methodology to examine reading and context for the eye movement field’s early transition to examining individual differences, culminating in future research recommendations. PMID:24391304
Miller, Brett; O'Donnell, Carol
2013-01-01
The cumulative body of eye movement research provides significant insight into how readers process text. The heart of this work spans roughly 40 years reflecting the maturity of both the topics under study and experimental approaches used to investigate reading. Recent technological advancements offer increased flexibility to the field providing the potential to more concertedly study reading and literacy from an individual differences perspective. Historically, eye movement research focused far less on developmental issues related to individual differences in reading; however, this issue and the broader change it represents signal a meaningful transition inclusive of individual differences. The six papers in this special issue signify the recent, increased attention to and recognition of eye movement research's transition to emphasize individual differences in reading while appreciating early contributions (e.g., Rayner, 1986) in this direction. We introduce these six papers and provide some historical context for the use of eye movement methodology to examine reading and context for the eye movement field's early transition to examining individual differences, culminating in future research recommendations.
Garnett, K; Lickorish, F A; Rocks, S A; Prpich, G; Rathe, A A; Pollard, S J T
2016-08-01
Poor connection between data on emerging issues and credible policy decisions continues to challenge governments, and is only likely to grow as demands on time and resources increase. Here we summarise recent efforts to integrate horizon scanning and risk prioritisation approaches to better connect emerging issues to the political discourse on environmental and food-related issues. Our categorisation of insights including potential future risks and opportunities to inform policy discussions has emerged from a structured three-year programme of horizon scanning for a UK pan-governmental futures partnership led by the Department for Environment, Food and Rural Affairs (Defra). Our efforts to integrate horizon scanning and risk prioritisation, utilising a qualitative weight of evidence framework, has created a systematic process for identifying all signals of potential future change with significant impact for the strategic mission and underlying values of policy actors. Our approach encourages an exploration of factors out of the control of organisations, recognising that resilience depends on the flexibility of management strategies and the preparedness to deal with a variety of unexpected outcomes. We discuss how this approach addresses key cultural and evaluative challenges that policy actors have had in embedding horizon scanning in evidence-based policy processes, and suggest further developments to build confidence in the use of horizon scanning for strategic planning. Copyright © 2016 Elsevier B.V. All rights reserved.
Focus issue: series on computational and systems biology.
Gough, Nancy R
2011-09-06
The application of computational biology and systems biology is yielding quantitative insight into cellular regulatory phenomena. For the month of September, Science Signaling highlights research featuring computational approaches to understanding cell signaling and investigation of signaling networks, a series of Teaching Resources from a course in systems biology, and various other articles and resources relevant to the application of computational biology and systems biology to the study of signal transduction.
Exercise redox biochemistry: Conceptual, methodological and technical recommendations.
Cobley, James N; Close, Graeme L; Bailey, Damian M; Davison, Gareth W
2017-08-01
Exercise redox biochemistry is of considerable interest owing to its translational value in health and disease. However, unaddressed conceptual, methodological and technical issues complicate attempts to unravel how exercise alters redox homeostasis in health and disease. Conceptual issues relate to misunderstandings that arise when the chemical heterogeneity of redox biology is disregarded: which often complicates attempts to use redox-active compounds and assess redox signalling. Further, that oxidised macromolecule adduct levels reflect formation and repair is seldom considered. Methodological and technical issues relate to the use of out-dated assays and/or inappropriate sample preparation techniques that confound biochemical redox analysis. After considering each of the aforementioned issues, we outline how each issue can be resolved and provide a unifying set of recommendations. We specifically recommend that investigators: consider chemical heterogeneity, use redox-active compounds judiciously, abandon flawed assays, carefully prepare samples and assay buffers, consider repair/metabolism, use multiple biomarkers to assess oxidative damage and redox signalling. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
System for monitoring an industrial or biological process
Gross, Kenneth C.; Wegerich, Stephan W.; Vilim, Rick B.; White, Andrew M.
1998-01-01
A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.
System for monitoring an industrial or biological process
Gross, K.C.; Wegerich, S.W.; Vilim, R.B.; White, A.M.
1998-06-30
A method and apparatus are disclosed for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT. 49 figs.
Multicast Routing of Hierarchical Data
NASA Technical Reports Server (NTRS)
Shacham, Nachum
1992-01-01
The issue of multicast of broadband, real-time data in a heterogeneous environment, in which the data recipients differ in their reception abilities, is considered. Traditional multicast schemes, which are designed to deliver all the source data to all recipients, offer limited performance in such an environment, since they must either force the source to overcompress its signal or restrict the destination population to those who can receive the full signal. We present an approach for resolving this issue by combining hierarchical source coding techniques, which allow recipients to trade off reception bandwidth for signal quality, and sophisticated routing algorithms that deliver to each destination the maximum possible signal quality. The field of hierarchical coding is briefly surveyed and new multicast routing algorithms are presented. The algorithms are compared in terms of network utilization efficiency, lengths of paths, and the required mechanisms for forwarding packets on the resulting paths.
Signalling crosstalk in plants: emerging issues.
Taylor, Jane E; McAinsh, Martin R
2004-01-01
The Oxford English Dictionary defines crosstalk as 'unwanted transfer of signals between communication channels'. How does this definition relate to the way in which we view the organization and function of signalling pathways? Recent advances in the field of plant signalling have challenged the traditional view of a signalling transduction cascade as isolated linear pathways. Instead the picture emerging of the mechanisms by which plants transduce environmental signals is of the interaction between transduction chains. The manner in which these interactions occur (and indeed whether the transfer of these signals is 'unwanted' or beneficial) is currently the topic of intense research.
Thorn, Stephanie R; Giesy, Sarah L; Myers, Martin G; Boisclair, Yves R
2010-08-01
Mice lacking leptin (ob/ob) or its full-length receptor (db/db) are obese and reproductively incompetent. Fertility, pregnancy, and lactation are restored, respectively, in ob/ob mice treated with leptin through mating, d 6.5 post coitum, and pregnancy. Therefore, leptin signaling is needed for lactation, but the timing of its action and the affected mammary process remain unknown. To address this issue, we used s/s mice lacking only leptin-dependent signal transducer and activator of transcription (STAT)3 signaling. These mice share many features with db/db mice, including obesity, but differ by retaining sufficient activity of the hypothalamic-pituitary-ovarian axis to support reproduction. The s/s mammary epithelium was normal at 3 wk of age but failed to expand through the mammary fat pad (MFP) during the subsequent pubertal period. Ductal growth failure was not corrected by estrogen therapy and did not relate to inadequate IGF-I production by the MFP or to the need for epithelial or stromal leptin-STAT3 signaling. Ductal growth failure coincided with adipocyte hypertrophy and increased MFP production of leptin, TNFalpha, and IL6. These cytokines, however, were unable to inhibit the proliferation of a collection of mouse mammary epithelial cell lines. In conclusion, the very first step of postnatal mammary development fails in s/s mice despite sufficient estrogen IGF-I and an hypothalamic-pituitary-ovarian axis capable of supporting reproduction. This failure is not caused by mammary loss of leptin-dependent STAT3 signaling or by the development of inflammation. These data imply the existence of an unknown mechanism whereby leptin-dependent STAT3 signaling and obesity alter mammary ductal development.
sAC as a model for understanding the impact of endosymbiosis on cell signaling.
Blackstone, Neil W
2014-12-01
As signaling pathways evolve, selection for new functions guides the co-option of existing material. Major transitions in the history of life, including the evolution of eukaryotes and multicellularity, exemplify this process. These transitions provided both strong selection and a plenitude of available material for the evolution of signaling pathways. Mechanisms that evolved to mediate conflict during the evolution of eukaryotes may subsequently have been co-opted during the many independent derivations of multicellularity. The soluble adenylyl cyclase (sAC) signaling pathway illustrates this hypothesis. Class III adenylyl cyclases, which include sAC, are found in bacteria, including the α-proteobacteria. These adenylyl cyclases are the only ones present in eukaryotes but appear to be absent in archaeans. This pattern suggests that the mitochondrial endosymbiosis brought sAC signaling to eukaryotes as part of an intact module. After transfer to the proto-nuclear genome, this module was then co-opted into numerous new functions. In the evolution of eukaryotes, sAC signaling may have mediated conflicts by maintaining metabolic homeostasis. In the evolution of multicellularity, in different lineages sAC may have been co-opted into parallel tasks originally related to conflict mediation. Elucidating the history of the sAC pathway may be relatively straightforward because it is ubiquitous and linked to near universal metabolic by-products (CO₂/HCO(3)(-)). Other signaling pathways (e.g., those involving STAT and VEGF) present a greater challenge but may suggest a complementary pattern. The impact of the mitochondrial endosymbiosis on cell signaling may thus have been profound. This article is part of a Special Issue entitled: The role of soluble adenylyl cyclase in health and disease. Copyright © 2014 Elsevier B.V. All rights reserved.
Discrete Dynamics Model for the Speract-Activated Ca2+ Signaling Network Relevant to Sperm Motility
Espinal, Jesús; Aldana, Maximino; Guerrero, Adán; Wood, Christopher
2011-01-01
Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca]) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated channel in the determination of the period of the fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted to have developed throughout evolution. PMID:21857937
Statistical issues in signal extraction from microarrays
NASA Astrophysics Data System (ADS)
Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping
2001-06-01
Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.
NASA Astrophysics Data System (ADS)
Ferriere, Alain; Volut, Mikael; Perez, Antoine; Volut, Yann
2016-05-01
A flux mapping system has been designed, implemented and experimented at the top of the Themis solar tower in France. This system features a moving bar associated to a CCD video camera and a flux gauge mounted onto the bar used as reference measurement for calibration purpose. Images and flux signal are acquired separately. The paper describes the equipment and focus on the data processing to issue the distribution of flux density and concentration at the aperture of the solar receiver. Finally, the solar power entering into the receiver is estimated by integration of flux density. The processing is largely automated in the form of a dedicated software with fast execution. A special attention is paid to the accuracy of the results, to the robustness of the algorithm and to the velocity of the processing.
Plasma membrane order and fluidity are diversely triggered by elicitors of plant defence.
Sandor, Roman; Der, Christophe; Grosjean, Kevin; Anca, Iulia; Noirot, Elodie; Leborgne-Castel, Nathalie; Lochman, Jan; Simon-Plas, Françoise; Gerbeau-Pissot, Patricia
2016-09-01
Although plants are exposed to a great number of pathogens, they usually defend themselves by triggering mechanisms able to limit disease development. Alongside signalling events common to most such incompatible interactions, modifications of plasma membrane (PM) physical properties could be new players in the cell transduction cascade. Different pairs of elicitors (cryptogein, oligogalacturonides, and flagellin) and plant cells (tobacco and Arabidopsis) were used to address the issue of possible modifications of plant PM biophysical properties induced by elicitors and their links to other events of the defence signalling cascade. We observed an increase of PM order whatever the elicitor/plant cell pair used, provided that a signalling cascade was induced. Such membrane modification is dependent on the NADPH oxidase-mediated reactive oxygen species production. Moreover, cryptogein, which is the sole elicitor able to trap sterols, is also the only one able to trigger an increase in PM fluidity. The use of cryptogein variants with altered sterol-binding properties confirms the strong correlation between sterol removal from the PM and PM fluidity enhancement. These results propose PM dynamics as a player in early signalling processes triggered by elicitors of plant defence. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.
Acoustic/seismic signal propagation and sensor performance modeling
NASA Astrophysics Data System (ADS)
Wilson, D. Keith; Marlin, David H.; Mackay, Sean
2007-04-01
Performance, optimal employment, and interpretation of data from acoustic and seismic sensors depend strongly and in complex ways on the environment in which they operate. Software tools for guiding non-expert users of acoustic and seismic sensors are therefore much needed. However, such tools require that many individual components be constructed and correctly connected together. These components include the source signature and directionality, representation of the atmospheric and terrain environment, calculation of the signal propagation, characterization of the sensor response, and mimicking of the data processing at the sensor. Selection of an appropriate signal propagation model is particularly important, as there are significant trade-offs between output fidelity and computation speed. Attenuation of signal energy, random fading, and (for array systems) variations in wavefront angle-of-arrival should all be considered. Characterization of the complex operational environment is often the weak link in sensor modeling: important issues for acoustic and seismic modeling activities include the temporal/spatial resolution of the atmospheric data, knowledge of the surface and subsurface terrain properties, and representation of ambient background noise and vibrations. Design of software tools that address these challenges is illustrated with two examples: a detailed target-to-sensor calculation application called the Sensor Performance Evaluator for Battlefield Environments (SPEBE) and a GIS-embedded approach called Battlefield Terrain Reasoning and Awareness (BTRA).
A new statistical PCA-ICA algorithm for location of R-peaks in ECG.
Chawla, M P S; Verma, H K; Kumar, Vinod
2008-09-16
The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.
Spacewire on Earth orbiting scatterometers
NASA Technical Reports Server (NTRS)
Bachmann, Alex; Lang, Minh; Lux, James; Steffke, Richard
2002-01-01
The need for a high speed, reliable and easy to implement communication link has led to the development of a space flight oriented version of IEEE 1355 called SpaceWire. SpaceWire is based on high-speed (200 Mbps) serial point-to-point links using Low Voltage Differential Signaling (LVDS). SpaceWIre has provisions for routing messages between a large network of processors, using wormhole routing for low overhead and latency. {additionally, there are available space qualified hybrids, which provide the Link layer to the user's bus}. A test bed of multiple digital signal processor breadboards, demonstrating the ability to meet signal processing requirements for an orbiting scatterometer has been implemented using three Astrium MCM-DSPs, each breadboard consists of a Multi Chip Module (MCM) that combines a space qualified Digital Signal Processor and peripherals, including IEEE-1355 links. With the addition of appropriate physical layer interfaces and software on the DSP, the SpaceWire link is used to communicate between processors on the test bed, e.g. sending timing references, commands, status, and science data among the processors. Results are presented on development issues surrounding the use of SpaceWire in this environment, from physical layer implementation (cables, connectors, LVDS drivers) to diagnostic tools, driver firmware, and development methodology. The tools, methods, and hardware, software challenges and preliminary performance are investigated and discussed.
Processing emotion from abstract art in frontotemporal lobar degeneration
Cohen, Miriam H.; Carton, Amelia M.; Hardy, Christopher J.; Golden, Hannah L.; Clark, Camilla N.; Fletcher, Phillip D.; Jaisin, Kankamol; Marshall, Charles R.; Henley, Susie M.D.; Rohrer, Jonathan D.; Crutch, Sebastian J.; Warren, Jason D.
2016-01-01
Abstract art may signal emotions independently of a biological or social carrier: it might therefore constitute a test case for defining brain mechanisms of generic emotion decoding and the impact of disease states on those mechanisms. This is potentially of particular relevance to diseases in the frontotemporal lobar degeneration (FTLD) spectrum. These diseases are often led by emotional impairment despite retained or enhanced artistic interest in at least some patients. However, the processing of emotion from art has not been studied systematically in FTLD. Here we addressed this issue using a novel emotional valence matching task on abstract paintings in patients representing major syndromes of FTLD (behavioural variant frontotemporal dementia, n=11; sematic variant primary progressive aphasia (svPPA), n=7; nonfluent variant primary progressive aphasia (nfvPPA), n=6) relative to healthy older individuals (n=39). Performance on art emotion valence matching was compared between groups taking account of perceptual matching performance and assessed in relation to facial emotion matching using customised control tasks. Neuroanatomical correlates of art emotion processing were assessed using voxel-based morphometry of patients' brain MR images. All patient groups had a deficit of art emotion processing relative to healthy controls; there were no significant interactions between syndromic group and emotion modality. Poorer art emotion valence matching performance was associated with reduced grey matter volume in right lateral occopitotemporal cortex in proximity to regions previously implicated in the processing of dynamic visual signals. Our findings suggest that abstract art may be a useful model system for investigating mechanisms of generic emotion decoding and aesthetic processing in neurodegenerative diseases. PMID:26748236
NASA Technical Reports Server (NTRS)
Casasent, D.
1978-01-01
The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.
Donegan, Katherine; Owen, Rebecca; Bird, Helena; Burch, Brian; Smith, Alex; Tregunno, Phil
2018-05-03
Electronic healthcare record (EHR) databases are used within pharmacoepidemiology studies to confirm or refute safety signals arising from spontaneous adverse event reports. However, there has been limited routine use of such data earlier in the signal management process, to help rapidly contextualise signals and strengthen preliminary assessment or to inform decisions regarding action including the need for further studies. This study explores the value of EHR used in this way within a regulatory environment via an automated analysis platform. Safety signals raised at the UK Medicines and Healthcare products Regulatory Agency (MHRA) between July 2014 and June 2015 were individually reviewed by a multi-disciplinary team. They assessed the feasibility of identifying the exposure and event of interest using primary care data from the Clinical Practice Research Datalink (CPRD) within the Commonwealth Vigilance Workbench (CVW) Longitudinal Module platform, which was designed to facilitate routine descriptive analysis of signals using EHR. Three signals, where exposure and event could be well identified, were retrospectively analysed using the platform. Of 69 unique new signals, 20 were for drugs prescribed predominately in secondary care or available without prescription, which would not be identified in primary care. A further 17 were brand, formulation, or dose-specific issues, were related to mortality, were relevant only to a subgroup of patients, or were drug interactions, and hence could not be reviewed using the platform given its limitations. Analyses of exposure and incidence of the adverse event could be produced using CPRD within the CMV Longitudinal Module for 32 (46%) signals. The case studies demonstrated that the data provided supporting evidence for confirming initial assessment of the signal and deciding upon the need for further action. CPRD can routinely provide useful early insights into clinical context when assessing a large proportion of safety signals within a regulatory environment provided that a flexible approach is adopted within the analysis platform.
FIND: difFerential chromatin INteractions Detection using a spatial Poisson process.
Djekidel, Mohamed Nadhir; Chen, Yang; Zhang, Michael Q
2018-02-12
Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. © 2018 Djekidel et al.; Published by Cold Spring Harbor Laboratory Press.
Age-related Deterioration of Hematopoietic Stem Cells.
Kim, Mi Jung; Kim, Min Hwan; Kim, Seung Ah; Chang, Jae Suk
2008-11-01
Aging is the process of system deterioration over time in the whole body. Stem cells are self-renewing and therefore have been considered exempt from the aging process. Earlier studies by Hayflick showed that there is an intrinsic limit to the number of divisions that mammalian somatic cells can undergo, and cycling kinetics and ontogeny-related studies strongly suggest that even the most primitive stem cell functions exhibit a certain degree of aging. Despite these findings, studies on the effects of aging on stem cell functions are inconclusive. Here we review the age-related properties of hematopoietic stem cells in terms of intrinsic and extrinsic alterations, proliferative potential, signaling molecules, telomere and telomerase, senescence and cancer issues, regenerative potential and other indications of stem cell aging are discussed in detail.
Age-related Deterioration of Hematopoietic Stem Cells
Kim, Mi Jung; Kim, Min Hwan; Kim, Seung Ah; Chang, Jae Suk
2008-01-01
Aging is the process of system deterioration over time in the whole body. Stem cells are self-renewing and therefore have been considered exempt from the aging process. Earlier studies by Hayflick showed that there is an intrinsic limit to the number of divisions that mammalian somatic cells can undergo, and cycling kinetics and ontogeny-related studies strongly suggest that even the most primitive stem cell functions exhibit a certain degree of aging. Despite these findings, studies on the effects of aging on stem cell functions are inconclusive. Here we review the age-related properties of hematopoietic stem cells in terms of intrinsic and extrinsic alterations, proliferative potential, signaling molecules, telomere and telomerase, senescence and cancer issues, regenerative potential and other indications of stem cell aging are discussed in detail. PMID:24855509
Fast neutron-gamma discrimination on neutron emission profile measurement on JT-60U.
Ishii, K; Shinohara, K; Ishikawa, M; Baba, M; Isobe, M; Okamoto, A; Kitajima, S; Sasao, M
2010-10-01
A digital signal processing (DSP) system is applied to stilbene scintillation detectors of the multichannel neutron emission profile monitor in JT-60U. Automatic analysis of the neutron-γ pulse shape discrimination is a key issue to diminish the processing time in the DSP system, and it has been applied using the two-dimensional (2D) map. Linear discriminant function is used to determine the dividing line between neutron events and γ-ray events on a 2D map. In order to verify the validity of the dividing line determination, the pulse shape discrimination quality is evaluated. As a result, the γ-ray contamination in most of the beam heating phase was negligible compared with the statistical error with 10 ms time resolution.
Fast neutron-gamma discrimination on neutron emission profile measurement on JT-60U
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ishii, K.; Okamoto, A.; Kitajima, S.
2010-10-15
A digital signal processing (DSP) system is applied to stilbene scintillation detectors of the multichannel neutron emission profile monitor in JT-60U. Automatic analysis of the neutron-{gamma} pulse shape discrimination is a key issue to diminish the processing time in the DSP system, and it has been applied using the two-dimensional (2D) map. Linear discriminant function is used to determine the dividing line between neutron events and {gamma}-ray events on a 2D map. In order to verify the validity of the dividing line determination, the pulse shape discrimination quality is evaluated. As a result, the {gamma}-ray contamination in most of themore » beam heating phase was negligible compared with the statistical error with 10 ms time resolution.« less
Applied digital signal processing systems for vortex flowmeter with digital signal processing.
Xu, Ke-Jun; Zhu, Zhi-Hai; Zhou, Yang; Wang, Xiao-Fen; Liu, San-Shan; Huang, Yun-Zhi; Chen, Zhi-Yuan
2009-02-01
The spectral analysis is combined with digital filter to process the vortex sensor signal for reducing the effect of disturbance at low frequency from pipe vibrations and increasing the turndown ratio. Using digital signal processing chip, two kinds of digital signal processing systems are developed to implement these algorithms. One is an integrative system, and the other is a separated system. A limiting amplifier is designed in the input analog condition circuit to adapt large amplitude variation of sensor signal. Some technique measures are taken to improve the accuracy of the output pulse, speed up the response time of the meter, and reduce the fluctuation of the output signal. The experimental results demonstrate the validity of the digital signal processing systems.
DOT National Transportation Integrated Search
2012-04-01
This report addresses communications to support safety applications specifically aimed at improving safety for mobile entities (vehicles, pedestrians, bicycles etc.) at signalized intersections. Collectively these applications are referred to as Sign...
Empirical observations of red light running at arterial signalized intersection.
DOT National Transportation Integrated Search
2008-12-01
Red Light Running (RLR) has become an increasely national safety issue at signalized intersections. : Significant efforts have been made to understand the RLR related driver behaviors and develop : countermeasures to reduce RLR and its related crashe...
NASA Astrophysics Data System (ADS)
Zhang, Guang-Ming; Harvey, David M.
2012-03-01
Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some specific problems, such as penetration, echo overlap, high attenuation and low signal-to-noise ratio. The signals recorded from a multilayered structure are a class of very special signals comprised of limited echoes. Such signals can be assumed to have a sparse representation in a proper signal dictionary. Recently, a number of digital signal processing techniques have been developed by exploiting the sparse constraint. This paper presents a review of research to date, showing the up-to-date developments of signal processing techniques made in ultrasonic NDE. A few typical ultrasonic signal processing techniques used for NDE of multilayered structures are elaborated. The practical applications and limitations of different signal processing methods in ultrasonic NDE of multilayered structures are analysed.
AOD furnace splash soft-sensor in the smelting process based on improved BP neural network
NASA Astrophysics Data System (ADS)
Ma, Haitao; Wang, Shanshan; Wu, Libin; Yu, Ying
2017-11-01
In view of argon oxygen refining low carbon ferrochrome production process, in the splash of smelting process as the research object, based on splash mechanism analysis in the smelting process , using multi-sensor information fusion and BP neural network modeling techniques is proposed in this paper, using the vibration signal, the audio signal and the flame image signal in the furnace as the characteristic signal of splash, the vibration signal, the audio signal and the flame image signal in the furnace integration and modeling, and reconstruct splash signal, realize the splash soft measurement in the smelting process, the simulation results show that the method can accurately forecast splash type in the smelting process, provide a new method of measurement for forecast splash in the smelting process, provide more accurate information to control splash.
Condition-dependent chemosignals in reproductive behavior of lizards.
Martín, José; López, Pilar
2015-02-01
This article is part of a Special Issue "Chemosignals and Reproduction". Many lizards have diverse glands that produce chemosignals used in intraspecific communication and that can have reproductive consequences. For example, information in chemosignals of male lizards can be used in intrasexual competition to identify and assess the fighting potential or dominance status of rival males either indirectly through territorial scent-marks or during agonistic encounters. Moreover, females of several lizard species "prefer" to establish or spend more time on areas scent-marked by males with compounds signaling a better health or body condition or a higher genetic compatibility, which can have consequences for their mating success and inter-sexual selection processes. We review here recent studies that suggest that the information content of chemosignals of lizards may be reliable because several physiological and endocrine processes would regulate the proportions of chemical compounds available for gland secretions. Because chemosignals are produced by the organism or come from the diet, they should reflect physiological changes, such as different hormonal levels (e.g. testosterone or corticosterone) or different health states (e.g. parasitic infections, immune response), and reflect the quality of the diet of an individual. More importantly, some compounds that may function as chemosignals also have other important functions in the organism (e.g. as antioxidants or regulating the immune system), so there could be trade-offs between allocating these compounds to attending physiological needs or to produce costly sexual "chemical ornaments". All these factors may contribute to maintain chemosignals as condition-dependent sexual signals, which can inform conspecifics on the characteristics and state of the sender and allow making behavioral decisions with reproductive consequences. To understand the evolution of chemical secretions of lizards as sexual signals and their relevance in reproduction, future studies should examine what information the signals are carrying, the physiological processes that can maintain the reliability of the message and how diverse behavioral responses to chemosignals may influence reproductive success. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Masiello, C. A.; Silberg, J. J.; Cheng, H. Y.; Del Valle, I.; Fulk, E. M.; Gao, X.; Bennett, G. N.
2017-12-01
Microbes can be programmed through synthetic biology to report on their behavior, informing researchers when their environment has triggered changes in their gene expression (e.g. in response to shifts in O2 or H2O), or when they have participated in a specific step of an elemental cycle (e.g. denitrification). This use of synthetic biology has the potential to significantly improve our understanding of microbes' roles in elemental and water cycling, because it allows reporting on the environment from the perspective of a microbe, matching the measurement scale exactly to the scale that a microbe experiences. However, synthetic microbes have not yet seen wide use in soil and sediment laboratory experiments because synthetic organisms typically report by fluorescing, making their signals difficult to detect outside the petri dish. We are developing a new suite of microbial programs that report instead by releasing easily-detected gases, allowing the real-time, noninvasive monitoring of behaviors in sediments and soils. Microbial biosensors can, in theory, be programmed to detect dynamic processes that contribute to a wide range of geobiological processes, including C cycling (biofilm production, methanogenesis, and synthesis of extracellular enzymes that degrade organic matter), N cycling (expression of enzymes that underlie different steps of the N cycle) and potentially S cycling. We will provide an overview of the potential uses of gas-reporting biosensors in soil and sediment lab experiments, and will report the development of the systematics of these sensors. Successful development of gas biosensors for laboratory use will require addressing issues including: engineering the intensity and selectivity of microbial gas production to maximize the signal to noise ratio; normalizing the gas reporter signal to cell population size, managing gas diffusion effects on signal shape; and developing multiple gases that can be used in parallel.
Domestication of the Cardiac Mitochondrion for Energy Conversion
Balaban, Robert S.
2009-01-01
The control of mitochondria energy conversion by cytosolic processes is reviewed. The nature of the cytosolic and mitochondrial potential energy homeostasis over wide ranges of energy utilization is reviewed and the consequences of this homeostasis in the control network are discussed. An analysis of the major candidate cytosolic signaling molecules ADP, Pi and Ca2+ are reviewed based on the magnitude and source of the cytosolic concentration changes as well as the potential targets of action within the mitochondrial energy conversion system. Based on this analysis, Ca2+ is the best candidate as a cytosolic signaling molecule for this process based on its ability to act as both a feed-forward and feed-back indicator of ATP hydrolysis and numerous targets within the matrix to provide a balanced activation of ATP production. These targets include numerous dehydrogenases and the F1-F0-ATPase. Pi is also a good candidate since it is an early signal of a mismatch between cytosolic ATP production and ATP synthesis in the presence of creatine kinase and has multiple targets within oxidative phosphorylation including NADH generation, electron flux in the cytochrome chain and a substrate for the F1-F0-ATPase. The mechanism of the coordinated activation of oxidative phosphorylation by these signaling molecules in discussed in light of the recent discoveries of extensive protein phosphorylation sites and other post-translational modifications. From this review it is clear that the control network associated with the maintenance of the cytosolic potential energy homeostasis is extremely complex with multiple pathways orchestrated to balance the sinks and sources in this system. New tools are needed to image and monitor metabolites within subcellular compartments to resolve many of these issues as well as the functional characterization of the numerous matrix post-translational events being discovered along with the enzymatic processes generating and removing these protein modifications. PMID:19265699
Granados-Lieberman, David; Valtierra-Rodriguez, Martin; Morales-Hernandez, Luis A; Romero-Troncoso, Rene J; Osornio-Rios, Roque A
2013-04-25
Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively.
Filter bank common spatial patterns in mental workload estimation.
Arvaneh, Mahnaz; Umilta, Alberto; Robertson, Ian H
2015-01-01
EEG-based workload estimation technology provides a real time means of assessing mental workload. Such technology can effectively enhance the performance of the human-machine interaction and the learning process. When designing workload estimation algorithms, a crucial signal processing component is the feature extraction step. Despite several studies on this field, the spatial properties of the EEG signals were mostly neglected. Since EEG inherently has a poor spacial resolution, features extracted individually from each EEG channel may not be sufficiently efficient. This problem becomes more pronounced when we use low-cost but convenient EEG sensors with limited stability which is the case in practical scenarios. To address this issue, in this paper, we introduce a filter bank common spatial patterns algorithm combined with a feature selection method to extract spatio-spectral features discriminating different mental workload levels. To evaluate the proposed algorithm, we carry out a comparative analysis between two representative types of working memory tasks using data recorded from an Emotiv EPOC headset which is a mobile low-cost EEG recording device. The experimental results showed that the proposed spatial filtering algorithm outperformed the state-of-the algorithms in terms of the classification accuracy.
Hyperbaric Oxygen, Vasculogenic Stem Cells, and Wound Healing
Fosen, Katina M.
2014-01-01
Abstract Significance: Oxidative stress is recognized as playing a role in stem cell mobilization from peripheral sites and also cell function. Recent Advances: This review focuses on the impact of hyperoxia on vasculogenic stem cells and elements of wound healing. Critical Issues: Components of the wound-healing process in which oxidative stress has a positive impact on the various cells involved in wound healing are highlighted. A slightly different view of wound-healing physiology is adopted by departing from the often used notion of sequential stages: hemostatic, inflammatory, proliferative, and remodeling and instead organizes the cascade of wound healing as overlapping events or waves pertaining to reactive oxygen species, lactate, and nitric oxide. This was done because hyperoxia has effects of a number of cell signaling events that converge to influence cell recruitment/chemotaxis and gene regulation/protein synthesis responses which mediate wound healing. Future Directions: Our alternative perspective of the stages of wound healing eases recognition of the multiple sites where oxidative stress has an impact on wound healing. This aids the focus on mechanistic events and the interplay among various cell types and biochemical processes. It also highlights the areas where additional research is needed. Antioxid. Redox Signal. 21, 1634–1647. PMID:24730726
Parallel processing for digital picture comparison
NASA Technical Reports Server (NTRS)
Cheng, H. D.; Kou, L. T.
1987-01-01
In picture processing an important problem is to identify two digital pictures of the same scene taken under different lighting conditions. This kind of problem can be found in remote sensing, satellite signal processing and the related areas. The identification can be done by transforming the gray levels so that the gray level histograms of the two pictures are closely matched. The transformation problem can be solved by using the packing method. Researchers propose a VLSI architecture consisting of m x n processing elements with extensive parallel and pipelining computation capabilities to speed up the transformation with the time complexity 0(max(m,n)), where m and n are the numbers of the gray levels of the input picture and the reference picture respectively. If using uniprocessor and a dynamic programming algorithm, the time complexity will be 0(m(3)xn). The algorithm partition problem, as an important issue in VLSI design, is discussed. Verification of the proposed architecture is also given.
Cellular signaling identifiability analysis: a case study.
Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo
2010-05-21
Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Single-channel mixed signal blind source separation algorithm based on multiple ICA processing
NASA Astrophysics Data System (ADS)
Cheng, Xiefeng; Li, Ji
2017-01-01
Take separating the fetal heart sound signal from the mixed signal that get from the electronic stethoscope as the research background, the paper puts forward a single-channel mixed signal blind source separation algorithm based on multiple ICA processing. Firstly, according to the empirical mode decomposition (EMD), the single-channel mixed signal get multiple orthogonal signal components which are processed by ICA. The multiple independent signal components are called independent sub component of the mixed signal. Then by combining with the multiple independent sub component into single-channel mixed signal, the single-channel signal is expanded to multipath signals, which turns the under-determined blind source separation problem into a well-posed blind source separation problem. Further, the estimate signal of source signal is get by doing the ICA processing. Finally, if the separation effect is not very ideal, combined with the last time's separation effect to the single-channel mixed signal, and keep doing the ICA processing for more times until the desired estimated signal of source signal is get. The simulation results show that the algorithm has good separation effect for the single-channel mixed physiological signals.
Neural and behavioral correlates of selective stopping: Evidence for a different strategy adoption.
Sánchez-Carmona, Alberto J; Albert, Jacobo; Hinojosa, José A
2016-10-01
The present study examined the neural and behavioral correlates of selective stopping, a form of inhibition that has scarcely been investigated. The selectivity of the inhibitory process is needed when individuals have to deal with an environment filled with multiple stimuli, some of which require inhibition and some of which do not. The stimulus-selective stop-signal task has been used to explore this issue assuming that all participants interrupt their ongoing responses selectively to stop but not to ignore signals. However, recent behavioral evidence suggests that some individuals do not carry out the task as experimenters expect, since they seemed to interrupt their response non-selectively to both signals. In the present study, we detected and controlled the cognitive strategy adopted by participants (n=57) when they performed a stimulus-selective stop-signal task before comparing brain activation between conditions. In order to determine both the onset and the end of the response cancellation process underlying each strategy and to fully take advantage of the precise temporal resolution of event-related potentials, we used a mass univariate approach. Source localization techniques were also employed to estimate the neural underpinnings of the effects observed at the scalp level. Our results from scalp and source level analysis support the behavioral-based strategy classification. Specific effects were observed depending on the strategy adopted by participants. Thus, when contrasting successful stop versus ignore conditions, increased activation was only evident for subjects who were classified as using a strategy whereby the response interruption process was selective to stop trials. This increased activity was observed during the P3 time window in several left-lateralized brain regions, including middle and inferior frontal gyri, as well as parietal and insular cortices. By contrast, in those participants who used a strategy characterized by stopping non-selectively, no activation differences between successful stop and ignore conditions were observed at the estimated time at which response interruption process occurs. Overall, results from the current study highlight the importance of controlling for the different strategies adopted by participants to perform selective stopping tasks before analyzing brain activation patterns. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Yoo, Byungseok
2011-12-01
In almost all industries of mechanical, aerospace, and civil engineering fields, structural health monitoring (SHM) technology is essentially required for providing the reliable information of structural integrity of safety-critical structures, which can help reduce the risk of unexpected and sometimes catastrophic failures, and also offer cost-effective inspection and maintenance of the structures. State of the art SHM research on structural damage diagnosis is focused on developing global and real-time technologies to identify the existence, location, extent, and type of damage. In order to detect and monitor the structural damage in plate-like structures, SHM technology based on guided Lamb wave (GLW) interrogation is becoming more attractive due to its potential benefits such as large inspection area coverage in short time, simple inspection mechanism, and sensitivity to small damage. However, the GLW method has a few critical issues such as dispersion nature, mode conversion and separation, and multiple-mode existence. Phased array technique widely used in all aspects of civil, military, science, and medical industry fields may be employed to resolve the drawbacks of the GLW method. The GLW-based phased array approach is able to effectively examine and analyze complicated structural vibration responses in thin plate structures. Because the phased sensor array operates as a spatial filter for the GLW signals, the array signal processing method can enhance a desired signal component at a specific direction while eliminating other signal components from other directions. This dissertation presents the development, the experimental validation, and the damage detection applications of an innovative signal processing algorithm based on two-dimensional (2-D) spiral phased array in conjunction with the GLW interrogation technique. It starts with general backgrounds of SHM and the associated technology including the GLW interrogation method. Then, it is focused on the fundamentals of the GLW-based phased array approach and the development of an innovative signal processing algorithm associated with the 2-D spiral phased sensor array. The SHM approach based on array responses determined by the proposed phased array algorithm implementation is addressed. The experimental validation of the GLW-based 2-D spiral phased array technology and the associated damage detection applications to thin isotropic plate and anisotropic composite plate structures are presented.
FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing
NASA Technical Reports Server (NTRS)
Berner, Stephan; DeLeon, Phillip
1999-01-01
One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.
NASA Astrophysics Data System (ADS)
Li, Zhixiong; Yan, Xinping; Wang, Xuping; Peng, Zhongxiao
2016-06-01
In the complex gear transmission systems, in wind turbines a crack is one of the most common failure modes and can be fatal to the wind turbine power systems. A single sensor may suffer with issues relating to its installation position and direction, resulting in the collection of weak dynamic responses of the cracked gear. A multi-channel sensor system is hence applied in the signal acquisition and the blind source separation (BSS) technologies are employed to optimally process the information collected from multiple sensors. However, literature review finds that most of the BSS based fault detectors did not address the dependence/correlation between different moving components in the gear systems; particularly, the popular used independent component analysis (ICA) assumes mutual independence of different vibration sources. The fault detection performance may be significantly influenced by the dependence/correlation between vibration sources. In order to address this issue, this paper presents a new method based on the supervised order tracking bounded component analysis (SOTBCA) for gear crack detection in wind turbines. The bounded component analysis (BCA) is a state of art technology for dependent source separation and is applied limitedly to communication signals. To make it applicable for vibration analysis, in this work, the order tracking has been appropriately incorporated into the BCA framework to eliminate the noise and disturbance signal components. Then an autoregressive (AR) model built with prior knowledge about the crack fault is employed to supervise the reconstruction of the crack vibration source signature. The SOTBCA only outputs one source signal that has the closest distance with the AR model. Owing to the dependence tolerance ability of the BCA framework, interfering vibration sources that are dependent/correlated with the crack vibration source could be recognized by the SOTBCA, and hence, only useful fault information could be preserved in the reconstructed signal. The crack failure thus could be precisely identified by the cyclic spectral correlation analysis. A series of numerical simulations and experimental tests have been conducted to illustrate the advantages of the proposed SOTBCA method for fatigue crack detection. Comparisons to three representative techniques, i.e. Erdogan's BCA (E-BCA), joint approximate diagonalization of eigen-matrices (JADE), and FastICA, have demonstrated the effectiveness of the SOTBCA. Hence the proposed approach is suitable for accurate gear crack detection in practical applications.
Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K; Birch, Gary E
2007-06-01
Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?
NASA Astrophysics Data System (ADS)
Bashashati, Ali; Fatourechi, Mehrdad; Ward, Rabab K.; Birch, Gary E.
2007-06-01
Brain computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?
2018-01-01
Metacognition is the capacity to evaluate the success of one's own cognitive processes in various domains; for example, memory and perception. It remains controversial whether metacognition relies on a domain-general resource that is applied to different tasks or if self-evaluative processes are domain specific. Here, we investigated this issue directly by examining the neural substrates engaged when metacognitive judgments were made by human participants of both sexes during perceptual and memory tasks matched for stimulus and performance characteristics. By comparing patterns of fMRI activity while subjects evaluated their performance, we revealed both domain-specific and domain-general metacognitive representations. Multivoxel activity patterns in anterior prefrontal cortex predicted levels of confidence in a domain-specific fashion, whereas domain-general signals predicting confidence and accuracy were found in a widespread network in the frontal and posterior midline. The demonstration of domain-specific metacognitive representations suggests the presence of a content-rich mechanism available to introspection and cognitive control. SIGNIFICANCE STATEMENT We used human neuroimaging to investigate processes supporting memory and perceptual metacognition. It remains controversial whether metacognition relies on a global resource that is applied to different tasks or if self-evaluative processes are specific to particular tasks. Using multivariate decoding methods, we provide evidence that perceptual- and memory-specific metacognitive representations coexist with generic confidence signals. Our findings reconcile previously conflicting results on the domain specificity/generality of metacognition and lay the groundwork for a mechanistic understanding of metacognitive judgments. PMID:29519851
Prototyping scalable digital signal processing systems for radio astronomy using dataflow models
NASA Astrophysics Data System (ADS)
Sane, N.; Ford, J.; Harris, A. I.; Bhattacharyya, S. S.
2012-05-01
There is a growing trend toward using high-level tools for design and implementation of radio astronomy digital signal processing (DSP) systems. Such tools, for example, those from the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER), are usually platform-specific, and lack high-level, platform-independent, portable, scalable application specifications. This limits the designer's ability to experiment with designs at a high-level of abstraction and early in the development cycle. We address some of these issues using a model-based design approach employing dataflow models. We demonstrate this approach by applying it to the design of a tunable digital downconverter (TDD) used for narrow-bandwidth spectroscopy. Our design is targeted toward an FPGA platform, called the Interconnect Break-out Board (IBOB), that is available from the CASPER. We use the term TDD to refer to a digital downconverter for which the decimation factor and center frequency can be reconfigured without the need for regenerating the hardware code. Such a design is currently not available in the CASPER DSP library. The work presented in this paper focuses on two aspects. First, we introduce and demonstrate a dataflow-based design approach using the dataflow interchange format (DIF) tool for high-level application specification, and we integrate this approach with the CASPER tool flow. Secondly, we explore the trade-off between the flexibility of TDD designs and the low hardware cost of fixed-configuration digital downconverter (FDD) designs that use the available CASPER DSP library. We further explore this trade-off in the context of a two-stage downconversion scheme employing a combination of TDD or FDD designs.
Advanced Data Acquisition Systems
NASA Technical Reports Server (NTRS)
Perotti, J.
2003-01-01
Current and future requirements of the aerospace sensors and transducers field make it necessary for the design and development of new data acquisition devices and instrumentation systems. New designs are sought to incorporate self-health, self-calibrating, self-repair capabilities, allowing greater measurement reliability and extended calibration cycles. With the addition of power management schemes, state-of-the-art data acquisition systems allow data to be processed and presented to the users with increased efficiency and accuracy. The design architecture presented in this paper displays an innovative approach to data acquisition systems. The design incorporates: electronic health self-check, device/system self-calibration, electronics and function self-repair, failure detection and prediction, and power management (reduced power consumption). These requirements are driven by the aerospace industry need to reduce operations and maintenance costs, to accelerate processing time and to provide reliable hardware with minimum costs. The project's design architecture incorporates some commercially available components identified during the market research investigation like: Field Programmable Gate Arrays (FPGA) Programmable Analog Integrated Circuits (PAC IC) and Field Programmable Analog Arrays (FPAA); Digital Signal Processing (DSP) electronic/system control and investigation of specific characteristics found in technologies like: Electronic Component Mean Time Between Failure (MTBF); and Radiation Hardened Component Availability. There are three main sections discussed in the design architecture presented in this document. They are the following: (a) Analog Signal Module Section, (b) Digital Signal/Control Module Section and (c) Power Management Module Section. These sections are discussed in detail in the following pages. This approach to data acquisition systems has resulted in the assignment of patent rights to Kennedy Space Center under U.S. patent # 6,462,684. Furthermore, NASA KSC commercialization office has issued licensing rights to Circuit Avenue Netrepreneurs, LLC , a minority-owned business founded in 1999 located in Camden, NJ.
Fiftieth Anniversary of the First Incoherent Scatter Radar Experiment
NASA Astrophysics Data System (ADS)
Robinson, Robert M.; van Eyken, Anthony; Farley, Donald
2009-08-01
In the 11 November 2008 issue of Eos (89(46), 458), Henry Rishbeth asked whether the years 2008-2010 feature any important anniversaries in solar-terrestrial physics other than those he mentioned. One such milestone is the fiftieth anniversary of the first incoherent scatter radar (ISR) experiment. At a Cornell University (Ithaca, N. Y.) departmental seminar in the spring of 1958, William Gordon showed that a powerful radar system could detect the uncorrelated and extremely weak scattered signals from individual ionospheric electrons. This process is called incoherent scatter, and studying the properties of the resulting radar echoes can reveal information about the density, temperature, and velocity of ionospheric particles. Gordon discussed this idea with Ken Bowles, a recent Ph.D. graduate of Cornell, and in a few weeks Bowles built a large but inexpensive antenna array that he connected to an existing transmitter near Havana, Ill. Using this crude radar (the data processing consisted of taking a time exposure photograph of the signal amplitude displayed on an oscilloscope), Bowles successfully measured an incoherently scattered signal on 21 October 1958. By a happy coincidence, 21 October was also the day that Gordon gave his first formal talk on the ISR concept at an International Union of Radio Science (URSI) conference at Pennsylvania State University. After calling Bowles for an update on his experiment, Gordon presented his research and added the dramatic and newsworthy note to the end of his talk on the success of the first ISR experiment!
Field test of monitoring of urban vehicle operations using non-intrusive technologies : final report
DOT National Transportation Integrated Search
2000-01-01
This document describes institutional issues associated with the retiming of traffic signals along the Scottsdale/Rural Road Corridor in Scottsdale and Tempe, Arizona in order to provide for coordinated traffic signal control in both jurisdictions. A...
ERIC Educational Resources Information Center
Love, Nigel
2007-01-01
Language use is commonly understood to involve digital signalling, which imposes certain constraints and restrictions on linguistic communication. Two papers by Ross [Ross, D., 2004. "Metalinguistic signalling for coordination amongst social agents." "Language Sciences" 26, 621-642; Ross, D., this issue. "'H. sapiens' as ecologically special: what…
Human factors considerations in the evaluation of processor-based signal and train control systems
DOT National Transportation Integrated Search
2007-06-01
In August 2001, the Federal Railroad Administration issued the notice of proposed rulemaking: Standards for Development and : Use of Processor-Based Signal and Train Control Systems (49 Code of Federal Regulations Part 236). This proposed rule addres...
DOT National Transportation Integrated Search
2015-03-01
The Connected Vehicle Mobility Policy team (herein, policy team) developed this report to document policy considerations for the Multi-Modal Intelligent Traffic Signal System, or MMITSS. MMITSS comprises a bundle of dynamic mobility application...
Bürstenbinder, Katharina; Mitra, Dipannita; Quegwer, Jakob
2017-06-03
Calcium (Ca 2+ ) ions play pivotal roles as second messengers in intracellular signal transduction, and coordinate many biological processes. Changes in intracellular Ca 2+ levels are perceived by Ca 2+ sensors such as calmodulin (CaM) and CaM-like (CML) proteins, which transduce Ca 2+ signals into cellular responses by regulation of diverse target proteins. Insights into molecular functions of CaM targets are thus essential to understand the molecular and cellular basis of Ca 2+ signaling. During the last decade, IQ67-domain (IQD) proteins emerged as the largest class of CaM targets in plants with mostly unknown functions. In the March issue of Plant Physiology, we presented the first comprehensive characterization of the 33-membered IQD family in Arabidopsis thaliana. We showed, by analysis of the subcellular localization of translational green fluorescent protein (GFP) fusion proteins, that most IQD members label microtubules (MTs), and additionally often localize to the cell nucleus or to membranes, where they recruit CaM Ca 2+ sensors. Important functions at MTs are supported by altered MT organization and plant growth in IQD gain-of-function lines. Because IQD proteins share structural hallmarks of scaffold proteins, we propose roles of IQDs in the assembly of macromolecular complexes to orchestrate Ca 2+ CaM signaling from membranes to the nucleus. Interestingly, expression of several IQDs is regulated by auxin, which suggests functions of IQDs as hubs in cellular auxin and calcium signaling to regulate plant growth and development.
[A New Distance Metric between Different Stellar Spectra: the Residual Distribution Distance].
Liu, Jie; Pan, Jing-chang; Luo, A-li; Wei, Peng; Liu, Meng
2015-12-01
Distance metric is an important issue for the spectroscopic survey data processing, which defines a calculation method of the distance between two different spectra. Based on this, the classification, clustering, parameter measurement and outlier data mining of spectral data can be carried out. Therefore, the distance measurement method has some effect on the performance of the classification, clustering, parameter measurement and outlier data mining. With the development of large-scale stellar spectral sky surveys, how to define more efficient distance metric on stellar spectra has become a very important issue in the spectral data processing. Based on this problem and fully considering of the characteristics and data features of the stellar spectra, a new distance measurement method of stellar spectra named Residual Distribution Distance is proposed. While using this method to measure the distance, the two spectra are firstly scaled and then the standard deviation of the residual is used the distance. Different from the traditional distance metric calculation methods of stellar spectra, when used to calculate the distance between stellar spectra, this method normalize the two spectra to the same scale, and then calculate the residual corresponding to the same wavelength, and the standard error of the residual spectrum is used as the distance measure. The distance measurement method can be used for stellar classification, clustering and stellar atmospheric physical parameters measurement and so on. This paper takes stellar subcategory classification as an example to test the distance measure method. The results show that the distance defined by the proposed method is more effective to describe the gap between different types of spectra in the classification than other methods, which can be well applied in other related applications. At the same time, this paper also studies the effect of the signal to noise ratio (SNR) on the performance of the proposed method. The result show that the distance is affected by the SNR. The smaller the signal-to-noise ratio is, the greater impact is on the distance; While SNR is larger than 10, the signal-to-noise ratio has little effect on the performance for the classification.
Zhang, Yan; Bhamber, Ranjeet; Riba-Garcia, Isabel; Liao, Hanqing; Unwin, Richard D; Dowsey, Andrew W
2015-01-01
As data rates rise, there is a danger that informatics for high-throughput LC-MS becomes more opaque and inaccessible to practitioners. It is therefore critical that efficient visualisation tools are available to facilitate quality control, verification, validation, interpretation, and sharing of raw MS data and the results of MS analyses. Currently, MS data is stored as contiguous spectra. Recall of individual spectra is quick but panoramas, zooming and panning across whole datasets necessitates processing/memory overheads impractical for interactive use. Moreover, visualisation is challenging if significant quantification data is missing due to data-dependent acquisition of MS/MS spectra. In order to tackle these issues, we leverage our seaMass technique for novel signal decomposition. LC-MS data is modelled as a 2D surface through selection of a sparse set of weighted B-spline basis functions from an over-complete dictionary. By ordering and spatially partitioning the weights with an R-tree data model, efficient streaming visualisations are achieved. In this paper, we describe the core MS1 visualisation engine and overlay of MS/MS annotations. This enables the mass spectrometrist to quickly inspect whole runs for ionisation/chromatographic issues, MS/MS precursors for coverage problems, or putative biomarkers for interferences, for example. The open-source software is available from http://seamass.net/viz/. PMID:25663356
NASA Astrophysics Data System (ADS)
Hong, Liu; Qu, Yongzhi; Dhupia, Jaspreet Singh; Sheng, Shuangwen; Tan, Yuegang; Zhou, Zude
2017-09-01
The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is often unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speed estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. The results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hong, Liu; Qu, Yongzhi; Dhupia, Jaspreet Singh
The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is oftenmore » unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speed estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. Lastly, the results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.« less
Hong, Liu; Qu, Yongzhi; Dhupia, Jaspreet Singh; ...
2017-02-27
The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is oftenmore » unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speed estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. Lastly, the results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.« less
Fully Passive Wireless Acquisition of Neuropotentials
NASA Astrophysics Data System (ADS)
Schwerdt, Helen N.
The ability to monitor electrophysiological signals from the sentient brain is requisite to decipher its enormously complex workings and initiate remedial solutions for the vast amount of neurologically-based disorders. Despite immense advancements in creating a variety of instruments to record signals from the brain, the translation of such neurorecording instrumentation to real clinical domains places heavy demands on their safety and reliability, both of which are not entirely portrayed by presently existing implantable recording solutions. In an attempt to lower these barriers, alternative wireless radar backscattering techniques are proposed to render the technical burdens of the implant chip to entirely passive neurorecording processes that transpire in the absence of formal integrated power sources or powering schemes along with any active circuitry. These radar-like wireless backscattering mechanisms are used to conceive of fully passive neurorecording operations of an implantable microsystem. The fully passive device potentially manifests inherent advantages over current wireless implantable and wired recording systems: negligible heat dissipation to reduce risks of brain tissue damage and minimal circuitry for long term reliability as a chronic implant. Fully passive neurorecording operations are realized via intrinsic nonlinear mixing properties of the varactor diode. These mixing and recording operations are directly activated by wirelessly interrogating the fully passive device with a microwave carrier signal. This fundamental carrier signal, acquired by the implant antenna, mixes through the varactor diode along with the internal targeted neuropotential brain signals to produce higher frequency harmonics containing the targeted neuropotential signals. These harmonics are backscattered wirelessly to the external interrogator that retrieves and recovers the original neuropotential brain signal. The passive approach removes the need for internal power sources and may alleviate heat trauma and reliability issues that limit practical implementation of existing implantable neurorecorders.
Giammarioli, Anna Maria; Chiandotto, Sergio; Spoletini, Ilaria
2014-01-01
Abstract Significance: Skeletal muscle is a highly plastic tissue. Exercise evokes signaling pathways that strongly modify myofiber metabolism and physiological and contractile properties of skeletal muscle. Regular physical activity is beneficial for health and is highly recommended for the prevention of several chronic conditions. In this review, we have focused our attention on the pathways that are known to mediate physical training-induced plasticity. Recent Advances: An important role for redox signaling has recently been proposed in exercise-mediated muscle remodeling and peroxisome proliferator-activated receptor γ (PPARγ) coactivator-1α (PGC-1α) activation. Still more currently, autophagy has also been found to be involved in metabolic adaptation to exercise. Critical Issues: Both redox signaling and autophagy are processes with ambivalent effects; they can be detrimental and beneficial, depending on their delicate balance. As such, understanding their role in the chain of events induced by exercise and leading to skeletal muscle remodeling is a very complicated matter. Moreover, the study of the signaling induced by exercise is made even more difficult by the fact that exercise can be performed with several different modalities, with this having different repercussions on adaptation. Future Directions: Unraveling the complexity of the molecular signaling triggered by exercise on skeletal muscle is crucial in order to define the therapeutic potentiality of physical training and to identify new pharmacological compounds that are able to reproduce some beneficial effects of exercise. In evaluating the effect of new “exercise mimetics,” it will also be necessary to take into account the involvement of reactive oxygen species, reactive nitrogen species, and autophagy and their controversial effects. Antioxid. Redox Signal. 21, 154–176. PMID:24450966
Redox homeostasis: The Golden Mean of healthy living
Ursini, Fulvio; Maiorino, Matilde; Forman, Henry Jay
2016-01-01
The notion that electrophiles serve as messengers in cell signaling is now widely accepted. Nonetheless, major issues restrain acceptance of redox homeostasis and redox signaling as components of maintenance of a normal physiological steady state. The first is that redox signaling requires sudden switching on of oxidant production and bypassing of antioxidant mechanisms rather than a continuous process that, like other signaling mechanisms, can be smoothly turned up or down. The second is the misperception that reactions in redox signaling involve “reactive oxygen species” rather than reaction of specific electrophiles with specific protein thiolates. The third is that hormesis provides protection against oxidants by increasing cellular defense or repair mechanisms rather than by specifically addressing the offset of redox homeostasis. Instead, we propose that both oxidant and antioxidant signaling are main features of redox homeostasis. As the redox shift is rapidly reversed by feedback reactions, homeostasis is maintained by continuous signaling for production and elimination of electrophiles and nucleophiles. Redox homeostasis, which is the maintenance of nucleophilic tone, accounts for a healthy physiological steady state. Electrophiles and nucleophiles are not intrinsically harmful or protective, and redox homeostasis is an essential feature of both the response to challenges and subsequent feedback. While the balance between oxidants and nucleophiles is preserved in redox homeostasis, oxidative stress provokes the establishment of a new radically altered redox steady state. The popular belief that scavenging free radicals by antioxidants has a beneficial effect is wishful thinking. We propose, instead, that continuous feedback preserves nucleophilic tone and that this is supported by redox active nutritional phytochemicals. These nonessential compounds, by activating Nrf2, mimic the effect of endogenously produced electrophiles (parahormesis). In summary, while hormesis, although globally protective, results in setting up of a new phenotype, parahormesis contributes to health by favoring maintenance of homeostasis. PMID:26820564
Is complex signal processing for bone conduction hearing aids useful?
Kompis, Martin; Kurz, Anja; Pfiffner, Flurin; Senn, Pascal; Arnold, Andreas; Caversaccio, Marco
2014-05-01
To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.
Digital Signal Processing Based Biotelemetry Receivers
NASA Technical Reports Server (NTRS)
Singh, Avtar; Hines, John; Somps, Chris
1997-01-01
This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.
NASA Astrophysics Data System (ADS)
Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor
2004-07-01
Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.
Physiological mechanisms underlying animal social behaviour.
Seebacher, Frank; Krause, Jens
2017-08-19
Many species of animal live in groups, and the group represents the organizational level within which ecological and evolutionary processes occur. Understanding these processes, therefore, relies on knowledge of the mechanisms that permit or constrain group formation. We suggest that physiological capacities and differences in physiology between individuals modify fission-fusion dynamics. Differences between individuals in locomotor capacity and metabolism may lead to fission of groups and sorting of individuals into groups with similar physiological phenotypes. Environmental impacts such as hypoxia can influence maximum group sizes and structure in fish schools by altering access to oxygenated water. The nutritional environment determines group cohesion, and the increase in information collected by the group means that individuals should rely more on social information and form more cohesive groups in uncertain environments. Changing environmental contexts require rapid responses by individuals to maintain group coordination, which are mediated by neuroendocrine signalling systems such as nonapeptides and steroid hormones. Brain processing capacity may constrain social complexity by limiting information processing. Failure to evaluate socially relevant information correctly limits social interactions, which is seen, for example, in autism. Hence, functioning of a group relies to a large extent on the perception and appropriate processing of signals from conspecifics. Many if not all physiological systems are mechanistically linked, and therefore have synergistic effects on social behaviour. A challenge for the future lies in understanding these interactive effects, which will improve understanding of group dynamics, particularly in changing environments.This article is part of the themed issue 'Physiological determinants of social behaviour in animals'. © 2017 The Author(s).
Physiological mechanisms underlying animal social behaviour
2017-01-01
Many species of animal live in groups, and the group represents the organizational level within which ecological and evolutionary processes occur. Understanding these processes, therefore, relies on knowledge of the mechanisms that permit or constrain group formation. We suggest that physiological capacities and differences in physiology between individuals modify fission–fusion dynamics. Differences between individuals in locomotor capacity and metabolism may lead to fission of groups and sorting of individuals into groups with similar physiological phenotypes. Environmental impacts such as hypoxia can influence maximum group sizes and structure in fish schools by altering access to oxygenated water. The nutritional environment determines group cohesion, and the increase in information collected by the group means that individuals should rely more on social information and form more cohesive groups in uncertain environments. Changing environmental contexts require rapid responses by individuals to maintain group coordination, which are mediated by neuroendocrine signalling systems such as nonapeptides and steroid hormones. Brain processing capacity may constrain social complexity by limiting information processing. Failure to evaluate socially relevant information correctly limits social interactions, which is seen, for example, in autism. Hence, functioning of a group relies to a large extent on the perception and appropriate processing of signals from conspecifics. Many if not all physiological systems are mechanistically linked, and therefore have synergistic effects on social behaviour. A challenge for the future lies in understanding these interactive effects, which will improve understanding of group dynamics, particularly in changing environments. This article is part of the themed issue ‘Physiological determinants of social behaviour in animals’. PMID:28673909
Device and method to enhance availability of cluster-based processing systems
NASA Technical Reports Server (NTRS)
Lupia, David J. (Inventor); Ramos, Jeremy (Inventor); Samson, Jr., John R. (Inventor)
2010-01-01
An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.
SNIa detection in the SNLS photometric analysis using Morphological Component Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Möller, A.; Ruhlmann-Kleider, V.; Neveu, J.
2015-04-01
Detection of supernovae (SNe) and, more generally, of transient events in large surveys can provide numerous false detections. In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources. Optimizing the detection of transient events is thus an important issue for both present and future surveys. We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation. The 3-year analysis provided 300,000more » detections dominated by signals of bright objects that were not perfectly subtracted. Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination. We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis. This technique exploits the morphological diversity of objects to be detected to extract the signal of interest. At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes. A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction. We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal. SNIa Monte-Carlo (MC) generated images were used to study detection efficiency and coordinate resolution. When tested on SNLS 3-year data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint ones. MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.« less
Redox Regulation of Plant Development
Considine, Michael J.
2014-01-01
Abstract Significance: We provide a conceptual framework for the interactions between the cellular redox signaling hub and the phytohormone signaling network that controls plant growth and development to maximize plant productivity under stress-free situations, while limiting growth and altering development on exposure to stress. Recent Advances: Enhanced cellular oxidation plays a key role in the regulation of plant growth and stress responses. Oxidative signals or cycles of oxidation and reduction are crucial for the alleviation of dormancy and quiescence, activating the cell cycle and triggering genetic and epigenetic control that underpin growth and differentiation responses to changing environmental conditions. Critical Issues: The redox signaling hub interfaces directly with the phytohormone network in the synergistic control of growth and its modulation in response to environmental stress, but a few components have been identified. Accumulating evidence points to a complex interplay of phytohormone and redox controls that operate at multiple levels. For simplicity, we focus here on redox-dependent processes that control root growth and development and bud burst. Future Directions: The multiple roles of reactive oxygen species in the control of plant growth and development have been identified, but increasing emphasis should now be placed on the functions of redox-regulated proteins, along with the central roles of reductants such as NAD(P)H, thioredoxins, glutathione, glutaredoxins, peroxiredoxins, ascorbate, and reduced ferredoxin in the regulation of the genetic and epigenetic factors that modulate the growth and vigor of crop plants, particularly within an agricultural context. Antioxid. Redox Signal. 21, 1305–1326. PMID:24180689
NASA Astrophysics Data System (ADS)
Georgiou, Harris
2009-10-01
Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.
NASA Astrophysics Data System (ADS)
Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu
2018-05-01
The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.
Research in speech communication.
Flanagan, J
1995-01-01
Advances in digital speech processing are now supporting application and deployment of a variety of speech technologies for human/machine communication. In fact, new businesses are rapidly forming about these technologies. But these capabilities are of little use unless society can afford them. Happily, explosive advances in microelectronics over the past two decades have assured affordable access to this sophistication as well as to the underlying computing technology. The research challenges in speech processing remain in the traditionally identified areas of recognition, synthesis, and coding. These three areas have typically been addressed individually, often with significant isolation among the efforts. But they are all facets of the same fundamental issue--how to represent and quantify the information in the speech signal. This implies deeper understanding of the physics of speech production, the constraints that the conventions of language impose, and the mechanism for information processing in the auditory system. In ongoing research, therefore, we seek more accurate models of speech generation, better computational formulations of language, and realistic perceptual guides for speech processing--along with ways to coalesce the fundamental issues of recognition, synthesis, and coding. Successful solution will yield the long-sought dictation machine, high-quality synthesis from text, and the ultimate in low bit-rate transmission of speech. It will also open the door to language-translating telephony, where the synthetic foreign translation can be in the voice of the originating talker. Images Fig. 1 Fig. 2 Fig. 5 Fig. 8 Fig. 11 Fig. 12 Fig. 13 PMID:7479806
Bioengineering of Artificial Lymphoid Organs.
Nosenko, M A; Drutskaya, M S; Moisenovich, M M; Nedospasov, S A
2016-01-01
This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cytokine signaling pathways regulating these processes. We describe various polymeric materials, as scaffolds, for artificial tissue engineering. Finally, published studies in which artificial lymphoid organs were generated are reviewed and possible future directions in the field are discussed.
Bioengineering of Artificial Lymphoid Organs
Nosenko, M. A.; Drutskaya, M. S.; Moisenovich, M. M.; Nedospasov, S. A.
2016-01-01
This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cytokine signaling pathways regulating these processes. We describe various polymeric materials, as scaffolds, for artificial tissue engineering. Finally, published studies in which artificial lymphoid organs were generated are reviewed and possible future directions in the field are discussed. PMID:27437136
Gamma-Ray Bursts and Fast Transients. Multi-wavelength Observations and Multi-messenger Signals
NASA Astrophysics Data System (ADS)
Willingale, R.; Mészáros, P.
2017-07-01
The current status of observations and theoretical models of gamma-ray bursts and some other related transients, including ultra-long bursts and tidal disruption events, is reviewed. We consider the impact of multi-wavelength data on the formulation and development of theoretical models for the prompt and afterglow emission including the standard fireball model utilizing internal shocks and external shocks, photospheric emission, the role of the magnetic field and hadronic processes. In addition, we discuss some of the prospects for non-photonic multi-messenger detection and for future instrumentation, and comment on some of the outstanding issues in the field.
Cryogenic and radiation hard ASIC design for large format NIR/SWIR detector
NASA Astrophysics Data System (ADS)
Gao, Peng; Dupont, Benoit; Dierickx, Bart; Müller, Eric; Verbruggen, Geert; Gielis, Stijn; Valvekens, Ramses
2014-10-01
An ASIC is developed to control and data quantization for large format NIR/SWIR detector arrays. Both cryogenic and space radiation environment issue are considered during the design. Therefore it can be integrated in the cryogenic chamber, which reduces significantly the vast amount of long wires going in and out the cryogenic chamber, i.e. benefits EMI and noise concerns, as well as the power consumption of cooling system and interfacing circuits. In this paper, we will describe the development of this prototype ASIC for image sensor driving and signal processing as well as the testing in both room and cryogenic temperature.
Siggers, Keri A; Lesser, Cammie F
2008-07-17
Microbial pathogens utilize complex secretion systems to deliver proteins into host cells. These effector proteins target and usurp host cell processes to promote infection and cause disease. While secretion systems are conserved, each pathogen delivers its own unique set of effectors. The identification and characterization of these effector proteins has been difficult, often limited by the lack of detectable signal sequences and functional redundancy. Model systems including yeast, worms, flies, and fish are being used to circumvent these issues. This technical review details the versatility and utility of yeast Saccharomyces cerevisiae as a system to identify and characterize bacterial effectors.
New low noise CCD cameras for Pi-of-the-Sky project
NASA Astrophysics Data System (ADS)
Kasprowicz, G.; Czyrkowski, H.; Dabrowski, R.; Dominik, W.; Mankiewicz, L.; Pozniak, K.; Romaniuk, R.; Sitek, P.; Sokolowski, M.; Sulej, R.; Uzycki, J.; Wrochna, G.
2006-10-01
Modern research trends require observation of fainter and fainter astronomical objects on large areas of the sky. This implies usage of systems with high temporal and optical resolution with computer based data acquisition and processing. Therefore Charge Coupled Devices (CCD) became so popular. They offer quick picture conversion with much better quality than film based technologies. This work is theoretical and practical study of the CCD based picture acquisition system. The system was optimized for "Pi of The Sky" project. But it can be adapted to another professional astronomical researches. The work includes issue of picture conversion, signal acquisition, data transfer and mechanical construction of the device.
Linking Smads and transcriptional activation.
Inman, Gareth J
2005-02-15
TGF-beta1 (transforming growth factor-beta1) is the prototypical member of a large family of pleiotropic cytokines that regulate diverse biological processes during development and adult tissue homoeostasis. TGF-beta signals via membrane bound serine/threonine kinase receptors which transmit their signals via the intracellular signalling molecules Smad2, Smad3 and Smad4. These Smads contain conserved MH1 and MH2 domains separated by a flexible linker domain. Smad2 and Smad3 act as kinase substrates for the receptors, and, following phosphorylation, they form complexes with Smad4 and translocate to the nucleus. These Smad complexes regulate gene expression and ultimately determine the biological response to TGF-beta. In this issue of the Biochemical Journal, Wang et al. have shown that, like Smad4, the linker domain of Smad3 contains a Smad transcriptional activation domain. This is capable of recruiting the p300 transcriptional co-activator and is required for Smad3-dependent transcriptional activation. This study raises interesting questions about the nature and regulation of Smad-regulated gene activation and elevates the status of the linker domain to rival that of the much-lauded MH1 and MH2 domains.
GPS Signal Feature Analysis to Detect Volcanic Plume on Mount Etna
NASA Astrophysics Data System (ADS)
Cannavo', Flavio; Aranzulla, Massimo; Scollo, Simona; Puglisi, Giuseppe; Imme', Giuseppina
2014-05-01
Volcanic ash produced during explosive eruptions can cause disruptions to aviation operations and to population living around active volcanoes. Thus, detection of volcanic plume becomes a crucial issue to reduce troubles connected to its presence. Nowadays, the volcanic plume detection is carried out by using different approaches such as satellites, radars and lidars. Recently, the capability of GPS to retrieve volcanic plumes has been also investigated and some tests applied to explosive activity of Etna have demonstrated that also the GPS may give useful information. In this work, we use the permanent and continuous GPS network of the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (Italy) that consists of 35 stations located all around volcano flanks. Data are processed by the GAMIT package developed by Massachusetts Institute of Technology. Here we investigate the possibility to quantify the volcanic plume through the GPS signal features and to estimate its spatial distribution by means of a tomographic inversion algorithm. The method is tested on volcanic plumes produced during the lava fountain of 4-5 September 2007, already used to confirm if weak explosive activity may or may not affect the GPS signals.
Wnt signal transduction pathways: modules, development and evolution.
Nayak, Losiana; Bhattacharyya, Nitai P; De, Rajat K
2016-08-01
Wnt signal transduction pathway (Wnt STP) is a crucial intracellular pathway mainly due to its participation in important biological processes, functions, and diseases, i.e., embryonic development, stem-cell management, and human cancers among others. This is why Wnt STP is one of the highest researched signal transduction pathways. Study and analysis of its origin, expansion and gradual development to the present state as found in humans is one aspect of Wnt research. The pattern of development and evolution of the Wnt STP among various species is not clear till date. A phylogenetic tree created from Wnt STPs of multiple species may address this issue. In this respect, we construct a phylogenetic tree from modules of Wnt STPs of diverse species. We term it as the 'Module Tree'. A module is nothing but a self-sufficient minimally-dependent subset of the original Wnt STP. Authenticity of the module tree is tested by comparing it with the two reference trees. The module tree performs better than an alternative phylogenetic tree constructed from pathway topology of Wnt STPs. Moreover, an evolutionary emergence pattern of the Wnt gene family is created and the module tree is tallied with it to showcase the significant resemblances.
Lipoxygenases and their metabolites in formation of plant stress tolerance.
Babenko, L M; Shcherbatiuk, M M; Skaterna, T D; Kosakivska, I V
2017-01-01
The review focuses on the analysis of new information concerning molecular enzymology of lipoxygenases – proteins involved in lipid peroxidation and found in animals and plants. Modern concept of structural features, catalytic characteristics and functions of lipoxygenase family enzymes as well as products of their catalytic activity in plants have been discussed and summarized. Issues of enzyme localization in plant cells and tissues, evolution and distribution of lipoxygenases, involvement in production of signaling substances involved in formation of adaptation response to abiotic and biotic stress factors and in regulation of lipoxygenase signal system activity are highlighted. Participants of the elements signaling of LOX-pathway reception and transduction into genome are considered. Special attention is given to jasmonates, metabolites of the allene oxide synthase branch of the lipoxygenase cascade, because these metabolites have high biological activity, are ubiquitously present in all plant organisms, and are involved in regulation of vitally important processes. Data concerning lipoxygenase phylogeny, possible occurrence of a common predecessor for modern isoforms of the enzyme in pro- and eukaryote have been examined. Some results of our studies that open up possibilities of using the lipoxygenase catalytic activity characteristics as biological markers in plant stress tolerance researches are given.
Secretome profiling of primary human skeletal muscle cells.
Hartwig, Sonja; Raschke, Silja; Knebel, Birgit; Scheler, Mika; Irmler, Martin; Passlack, Waltraud; Muller, Stefan; Hanisch, Franz-Georg; Franz, Thomas; Li, Xinping; Dicken, Hans-Dieter; Eckardt, Kristin; Beckers, Johannes; de Angelis, Martin Hrabe; Weigert, Cora; Häring, Hans-Ulrich; Al-Hasani, Hadi; Ouwens, D Margriet; Eckel, Jürgen; Kotzka, Jorg; Lehr, Stefan
2014-05-01
The skeletal muscle is a metabolically active tissue that secretes various proteins. These so-called myokines have been proposed to affect muscle physiology and to exert systemic effects on other tissues and organs. Yet, changes in the secretory profile may participate in the pathophysiology of metabolic diseases. The present study aimed at characterizing the secretome of differentiated primary human skeletal muscle cells (hSkMC) derived from healthy, adult donors combining three different mass spectrometry based non-targeted approaches as well as one antibody based method. This led to the identification of 548 non-redundant proteins in conditioned media from hSkmc. For 501 proteins, significant mRNA expression could be demonstrated. Applying stringent consecutive filtering using SignalP, SecretomeP and ER_retention signal databases, 305 proteins were assigned as potential myokines of which 12 proteins containing a secretory signal peptide were not previously described. This comprehensive profiling study of the human skeletal muscle secretome expands our knowledge of the composition of the human myokinome and may contribute to our understanding of the role of myokines in multiple biological processes. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.
Adenosine receptor desensitization and trafficking.
Mundell, Stuart; Kelly, Eamonn
2011-05-01
As with the majority of G-protein-coupled receptors, all four of the adenosine receptor subtypes are known to undergo agonist-induced regulation in the form of desensitization and trafficking. These processes can limit the ability of adenosine receptors to couple to intracellular signalling pathways and thus reduce the ability of adenosine receptor agonists as well as endogenous adenosine to produce cellular responses. In addition, since adenosine receptors couple to multiple signalling pathways, these pathways may desensitize differentially, while the desensitization of one pathway could even trigger signalling via another. Thus, the overall picture of adenosine receptor regulation can be complex. For all adenosine receptor subtypes, there is evidence to implicate arrestins in agonist-induced desensitization and trafficking, but there is also evidence for other possible forms of regulation, including second messenger-dependent kinase regulation, heterologous effects involving G proteins, and the involvement of non-clathrin trafficking pathways such as caveolae. In this review, the evidence implicating these mechanisms is summarized for each adenosine receptor subtype, and we also discuss those issues of adenosine receptor regulation that remain to be resolved as well as likely directions for future research in this field. Copyright © 2010 Elsevier B.V. All rights reserved.
The upgrade of the Thomson scattering system for measurement on the C-2/C-2U devices
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhai, K.; Schindler, T.; Kinley, J.
The C-2/C-2U Thomson scattering system has been substantially upgraded during the latter phase of C-2/C-2U program. A Rayleigh channel has been added to each of the three polychromators of the C-2/C-2U Thomson scattering system. Onsite spectral calibration has been applied to avoid the issue of different channel responses at different spots on the photomultiplier tube surface. With the added Rayleigh channel, the absolute intensity response of the system is calibrated with Rayleigh scattering in argon gas from 0.1 to 4 Torr, where the Rayleigh scattering signal is comparable to the Thomson scattering signal at electron densities from 1 × 10{supmore » 13} to 4 × 10{sup 14} cm{sup −3}. A new signal processing algorithm, using a maximum likelihood method and including detailed analysis of different noise contributions within the system, has been developed to obtain electron temperature and density profiles. The system setup, spectral and intensity calibration procedure and its outcome, data analysis, and the results of electron temperature/density profile measurements will be presented.« less
Emerging Importance of Phytochemicals in Regulation of Stem Cells Fate via Signaling Pathways.
Dadashpour, Mehdi; Pilehvar-Soltanahmadi, Younes; Zarghami, Nosratollah; Firouzi-Amandi, Akram; Pourhassan-Moghaddam, Mohammad; Nouri, Mohammad
2017-11-01
To reach ideal therapeutic potential of stem cells for regenerative medicine purposes, it is essential to retain their self-renewal and differentiation capacities. Currently, biological factors are extensively used for stemness maintaining and differentiation induction of stem cells. However, low stability, high cost, complicated production process, and risks associated with viral/endotoxin infection hamper the widespread use of biological factors in the stem cell biology. Moreover, regarding the modulation of several signaling cascades, which lead to a distinct fate, phytochemicals are preferable in the stem cells biology because of their efficiency. Considering the issues related to the application of biological factors and potential advantages of phytochemicals in stem cell engineering, there is a considerable increasing trend in studies associated with the application of novel alternative molecules in the stem cell biology. In support of this statement, we aimed to highlight the various effects of phytochemicals on signaling cascades involved in commitment of stem cells. Hence, in this review, the current trends in the phytochemicals-based modulation of stem cell fate have been addressed. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
49 CFR 236.921 - Training and qualification program, general.
Code of Federal Regulations, 2010 CFR
2010-10-01
... INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Standards for Processor-Based Signal and Train Control Systems § 236.921 Training and qualification program..., wayside, or onboard subsystems; (2) Persons who dispatch train operations (issue or communicate any...
Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A; Guyer, Robert; Ten Cate, James A; Le Bas, Pierre-Yves; Larmat, Carene S
2014-12-30
A system and a method for investigating rock formations includes generating, by a first acoustic source, a first acoustic signal comprising a first plurality of pulses, each pulse including a first modulated signal at a central frequency; and generating, by a second acoustic source, a second acoustic signal comprising a second plurality of pulses. A receiver arranged within the borehole receives a detected signal including a signal being generated by a non-linear mixing process from the first-and-second acoustic signal in a non-linear mixing zone within the intersection volume. The method also includes-processing the received signal to extract the signal generated by the non-linear mixing process over noise or over signals generated by a linear interaction process, or both.
Signal Transduction: From the Atomic Age to the Post-Genomic Era
Thorner, Jeremy; Hunter, Tony; Cantley, Lewis C.; Sever, Richard
2014-01-01
We have come a long way in the 55 years since Edmond Fischer and the late Edwin Krebs discovered that the activity of glycogen phosphorylase is regulated by reversible protein phosphorylation. Many of the fundamental molecular mechanisms that operate in biological signaling have since been characterized and the vast web of interconnected pathways that make up the cellular signaling network has been mapped in considerable detail. Nonetheless, it is important to consider how fast this field is still moving and the issues at the current boundaries of our understanding. One must also appreciate what experimental strategies have allowed us to attain our present level of knowledge. We summarize here some key issues (both conceptual and methodological), raise unresolved questions, discuss potential pitfalls, and highlight areas in which our understanding is still rudimentary. We hope these wide-ranging ruminations will be useful to investigators who carry studies of signal transduction forward during the rest of the 21st century. PMID:25359498
Intelligent processing of acoustic emission signals
NASA Astrophysics Data System (ADS)
Sachse, Wolfgang; Grabec, Igor
1992-07-01
Recent developments in applying neural-like signal-processing procedures for analyzing acoustic emission signals are summarized. These procedures employ a set of learning signals to develop a memory that can subsequently be utilized to process other signals to recover information about an unknown source. A majority of the current applications to process ultrasonic waveforms are based on multilayered, feed-forward neural networks, trained with some type of back-error propagation rule.
NASA Astrophysics Data System (ADS)
Newchurch, M.; Al-Saadi, J. A.; Alvarez, R. J.; Burris, J.; Cantrell, W.; Chen, G.; De Young, R.; Hardesty, R.; Hoff, R. M.; Kaye, J. A.; kuang, S.; Langford, A. O.; LeBlanc, T.; McDermid, I. S.; McGee, T. J.; Pierce, R.; Senff, C. J.; Sullivan, J. T.; Szykman, J.; Tonnesen, G.; Wang, L.
2012-12-01
An interagency research initiative for ground-based ozone and aerosol lidar profiling recently funded by NASA has important applications to air-quality studies in addition to the goal of serving the GEO-CAPE and other air-quality missions. Ozone is a key trace-gas species, a greenhouse gas, and an important pollutant in the troposphere. High spatial and temporal variability of ozone affected by various physical and photochemical processes motivates the high spatio-temporal lidar profiling of tropospheric ozone for improving the simulation and forecasting capability of the photochemical/air-quality models, especially in the boundary layer where the resolution and precision of satellite retrievals are fundamentally limited. It is well known that there are large discrepancies between the surface and upper-air ozone due to titration, surface deposition, diurnal processes, free-tropospheric transport, and other processes. Near-ground ozone profiling has been technically challenging for lidars due to some engineering difficulties, such as near-range saturation, field-of-view overlap, and signal processing issues. This initiative provides an opportunity for us to solve those engineering issues and redesign the lidars aimed at long-term, routine ozone/aerosol observations from the near surface to the top of the troposphere at multiple stations (i.e., NASA/GSFC, NASA/LaRC, NASA/JPL, NOAA/ESRL, UAHuntsville) for addressing the needs of NASA, NOAA, EPA and State/local AQ agencies. We will present the details of the science investigations, current status of the instrumentation development, data access/protocol, and the future goals of this lidar network. Ozone lidar/RAQMS comparison of laminar structures.
Determining Aliasing in Isolated Signal Conditioning Modules
NASA Technical Reports Server (NTRS)
2009-01-01
The basic concept of aliasing is this: Converting analog data into digital data requires sampling the signal at a specific rate, known as the sampling frequency. The result of this conversion process is a new function, which is a sequence of digital samples. This new function has a frequency spectrum, which contains all the frequency components of the original signal. The Fourier transform mathematics of this process show that the frequency spectrum of the sequence of digital samples consists of the original signal s frequency spectrum plus the spectrum shifted by all the harmonics of the sampling frequency. If the original analog signal is sampled in the conversion process at a minimum of twice the highest frequency component contained in the analog signal, and if the reconstruction process is limited to the highest frequency of the original signal, then the reconstructed signal accurately duplicates the original analog signal. It is this process that can give birth to aliasing.
The spiral ganglion: connecting the peripheral and central auditory systems
Nayagam, Bryony A; Muniak, Michael A; Ryugo, David K
2011-01-01
In mammals, the initial bridge between the physical world of sound and perception of that sound is established by neurons of the spiral ganglion. The cell bodies of these neurons give rise to peripheral processes that contact acoustic receptors in the organ of Corti, and the central processes collect together to form the auditory nerve that projects into the brain. In order to better understand hearing at this initial stage, we need to know the following about spiral ganglion neurons: (1) their cell biology including cytoplasmic, cytoskeletal, and membrane properties, (2) their peripheral and central connections including synaptic structure; (3) the nature of their neural signaling; and (4) their capacity for plasticity and rehabilitation. In this report, we will update the progress on these topics and indicate important issues still awaiting resolution. PMID:21530629
Improved method of step length estimation based on inverted pendulum model.
Zhao, Qi; Zhang, Boxue; Wang, Jingjing; Feng, Wenquan; Jia, Wenyan; Sun, Mingui
2017-04-01
Step length estimation is an important issue in areas such as gait analysis, sport training, or pedestrian localization. In this article, we estimate the step length of walking using a waist-worn wearable computer named eButton. Motion sensors within this device are used to record body movement from the trunk instead of extremities. Two signal-processing techniques are applied to our algorithm design. The direction cosine matrix transforms vertical acceleration from the device coordinates to the topocentric coordinates. The empirical mode decomposition is used to remove the zero- and first-order skew effects resulting from an integration process. Our experimental results show that our algorithm performs well in step length estimation. The effectiveness of the direction cosine matrix algorithm is improved from 1.69% to 3.56% while the walking speed increased.
Technology-enhanced human interaction in psychotherapy.
Imel, Zac E; Caperton, Derek D; Tanana, Michael; Atkins, David C
2017-07-01
Psychotherapy is on the verge of a technology-inspired revolution. The concurrent maturation of communication, signal processing, and machine learning technologies begs an earnest look at how these technologies may be used to improve the quality of psychotherapy. Here, we discuss 3 research domains where technology is likely to have a significant impact: (1) mechanism and process, (2) training and feedback, and (3) technology-mediated treatment modalities. For each domain, we describe current and forthcoming examples of how new technologies may change established applications. Moreover, for each domain we present research questions that touch on theoretical, systemic, and implementation issues. Ultimately, psychotherapy is a decidedly human endeavor, and thus the application of modern technology to therapy must capitalize on-and enhance-our human capacities as counselors, students, and supervisors. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Processing emotion from abstract art in frontotemporal lobar degeneration.
Cohen, Miriam H; Carton, Amelia M; Hardy, Christopher J; Golden, Hannah L; Clark, Camilla N; Fletcher, Phillip D; Jaisin, Kankamol; Marshall, Charles R; Henley, Susie M D; Rohrer, Jonathan D; Crutch, Sebastian J; Warren, Jason D
2016-01-29
art may signal emotions independently of a biological or social carrier: it might therefore constitute a test case for defining brain mechanisms of generic emotion decoding and the impact of disease states on those mechanisms. This is potentially of particular relevance to diseases in the frontotemporal lobar degeneration (FTLD) spectrum. These diseases are often led by emotional impairment despite retained or enhanced artistic interest in at least some patients. However, the processing of emotion from art has not been studied systematically in FTLD. Here we addressed this issue using a novel emotional valence matching task on abstract paintings in patients representing major syndromes of FTLD (behavioural variant frontotemporal dementia, n=11; sematic variant primary progressive aphasia (svPPA), n=7; nonfluent variant primary progressive aphasia (nfvPPA), n=6) relative to healthy older individuals (n=39). Performance on art emotion valence matching was compared between groups taking account of perceptual matching performance and assessed in relation to facial emotion matching using customised control tasks. Neuroanatomical correlates of art emotion processing were assessed using voxel-based morphometry of patients' brain MR images. All patient groups had a deficit of art emotion processing relative to healthy controls; there were no significant interactions between syndromic group and emotion modality. Poorer art emotion valence matching performance was associated with reduced grey matter volume in right lateral occopitotemporal cortex in proximity to regions previously implicated in the processing of dynamic visual signals. Our findings suggest that abstract art may be a useful model system for investigating mechanisms of generic emotion decoding and aesthetic processing in neurodegenerative diseases. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Informational approach to the analysis of acoustic signals
NASA Astrophysics Data System (ADS)
Senkevich, Yuriy; Dyuk, Vyacheslav; Mishchenko, Mikhail; Solodchuk, Alexandra
2017-10-01
The example of linguistic processing of acoustic signals of a seismic event would be an information approach to the processing of non-stationary signals. The method for converting an acoustic signal into an information message is described by identifying repetitive self-similar patterns. The definitions of the event selection indicators in the symbolic recording of the acoustic signal are given. The results of processing an acoustic signal by a computer program realizing the processing of linguistic data are shown. Advantages and disadvantages of using software algorithms are indicated.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Polese, Luigi Gentile; Brackney, Larry
An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generatesmore » an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.« less
A novel low-complexity digital filter design for wearable ECG devices
Mehrnia, Alireza
2017-01-01
Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters. PMID:28384272
Aircraft Operations Classification System
NASA Technical Reports Server (NTRS)
Harlow, Charles; Zhu, Weihong
2001-01-01
Accurate data is important in the aviation planning process. In this project we consider systems for measuring aircraft activity at airports. This would include determining the type of aircraft such as jet, helicopter, single engine, and multiengine propeller. Some of the issues involved in deploying technologies for monitoring aircraft operations are cost, reliability, and accuracy. In addition, the system must be field portable and acceptable at airports. A comparison of technologies was conducted and it was decided that an aircraft monitoring system should be based upon acoustic technology. A multimedia relational database was established for the study. The information contained in the database consists of airport information, runway information, acoustic records, photographic records, a description of the event (takeoff, landing), aircraft type, and environmental information. We extracted features from the time signal and the frequency content of the signal. A multi-layer feed-forward neural network was chosen as the classifier. Training and testing results were obtained. We were able to obtain classification results of over 90 percent for training and testing for takeoff events.
Savage, Emilia Elizabeth; Wootten, Denise; Christopoulos, Arthur; Sexton, Patrick Michael; Furness, Sebastian George Barton
2013-04-01
Transient protein-protein interactions form the basis of signal transduction pathways in addition to many other biological processes. One tool for studying these interactions is bioluminescence resonance energy transfer (BRET). This technique has been widely applied to study signaling pathways, in particular those initiated by G protein-coupled receptors (GPCRs). These assays are routinely performed using transient transfection, a technique that has limitations in terms of assay cost and variability, overexpression of interacting proteins, vector uptake limited to cycling cells, and non-homogenous expression across cells within the assay. To address these issues, we developed bicistronic vectors for use with Life Technology's Gateway and flpIN systems. These vectors provide a means to generate isogenic cell lines for comparison of interacting proteins. They have the advantage of stable, single copy, isogenic, homogeneous expression with low inter-assay variation. We demonstrate their utility by assessing ligand-induced interactions between GPCRs and arrestin proteins.
Effects of High-Rate Pulse Trains on Electrode Discrimination in Cochlear Implant Users
Runge-Samuelson, Christina L.
2009-01-01
Overcoming issues related to abnormally high neural synchrony in response to electrical stimulation is one aspect in improving hearing with a cochlear implant. Desynchronization of electrical stimuli have shown benefits in neural encoding of electrical signals and improvements in psychophysical tasks. In the present study, 10 participants with either CII or HiRes 90k Advanced Bionics devices were tested for the effects of desynchronizing constant-amplitude high-rate (5,000 Hz) pulse trains on electrode discrimination of sinusoidal stimuli (1,000 Hz). When averaged across the sinusoidal dynamic range, overall improvements in electrode discrimination with high-rate pulses were found for 8 of 10 participants. This effect was significant for the group (p = .003). Nonmonotonic patterns of electrode discrimination as a function of sinusoidal stimulation level were observed. By providing additional spectral channels, it is possible that clinical implementation of constant-amplitude high-rate pulse trains in a signal processing strategy may improve performance with the device. PMID:19447763
A novel low-complexity digital filter design for wearable ECG devices.
Asgari, Shadnaz; Mehrnia, Alireza
2017-01-01
Wearable and implantable Electrocardiograph (ECG) devices are becoming prevailing tools for continuous real-time personal health monitoring. The ECG signal can be contaminated by various types of noise and artifacts (e.g., powerline interference, baseline wandering) that must be removed or suppressed for accurate ECG signal processing. Limited device size, power consumption and cost are critical issues that need to be carefully considered when designing any portable health monitoring device, including a battery-powered ECG device. This work presents a novel low-complexity noise suppression reconfigurable finite impulse response (FIR) filter structure for wearable ECG and heart monitoring devices. The design relies on a recently introduced optimally-factored FIR filter method. The new filter structure and several of its useful features are presented in detail. We also studied the hardware complexity of the proposed structure and compared it with the state-of-the-art. The results showed that the new ECG filter has a lower hardware complexity relative to the state-of-the-art ECG filters.
BPSK Demodulation Using Digital Signal Processing
NASA Technical Reports Server (NTRS)
Garcia, Thomas R.
1996-01-01
A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.
Stemming Colorectal Cancer Growth and Metastasis: HOXA5 Forces Cancer Stem Cells to Differentiate.
Tan, Si Hui; Barker, Nick
2015-12-14
Wnt signaling drives colorectal cancer stem cells, but effective therapeutics targeting these cells and their signaling pathways are lacking. In this issue of Cancer Cell, Ordóñez-Morán and colleagues describe a promising therapeutic intervention for colorectal cancers that selectively induces cancer stem cell differentiation through HOXA5 expression and Wnt signaling inhibition. Copyright © 2015 Elsevier Inc. All rights reserved.
Regulation of brain insulin signaling: A new function for tau
Gratuze, Maud; Planel, Emmanuel
2017-01-01
In this issue of JEM, Marciniak et al. (https://doi.org/10.1084/jem.20161731) identify a putative novel function of tau protein as a regulator of insulin signaling in the brain. They find that tau deletion impairs hippocampal response to insulin through IRS-1 and PTEN dysregulation and suggest that, in Alzheimer’s disease, impairment of brain insulin signaling might occur via tau loss of function. PMID:28652305
Gas turbine engine control system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Idelchik, M.S.
1991-02-19
This paper describes a method for controlling a gas turbine engine. It includes receiving an error signal and processing the error signal to form a primary control signal; receiving at least one anticipatory demand signal and processing the signal to form an anticipatory fuel control signal.
10 CFR 431.223 - Materials incorporated by reference.
Code of Federal Regulations, 2011 CFR
2011-01-01
... AND INDUSTRIAL EQUIPMENT Traffic Signal Modules and Pedestrian Modules Test Procedures § 431.223... for Traffic Signals,” Version 1.1 issued February 4, 2003. (2) Institute of Transportation Engineers...) 272-0167 or at http://www.epa.gov. (ii) Institute of Transportation Engineers, 1099 14th Street, NW...
10 CFR 431.223 - Materials incorporated by reference.
Code of Federal Regulations, 2010 CFR
2010-01-01
... AND INDUSTRIAL EQUIPMENT Traffic Signal Modules and Pedestrian Modules Test Procedures § 431.223... for Traffic Signals,” Version 1.1 issued February 4, 2003. (2) Institute of Transportation Engineers...) 272-0167 or at http://www.epa.gov. (ii) Institute of Transportation Engineers, 1099 14th Street, NW...
DOT National Transportation Integrated Search
2013-11-01
Red light running has become a serious safety issue at signalized intersections throughout the : United States. One objective of this study was to identify the characteristics of red-light-running (RLR) : crashes and the drivers involved in those cra...
DOT National Transportation Integrated Search
1993-05-01
This study has been conducted with the goal of gaining an insight into the issues of maintaining vital signal systems implemented with microprocessor chips and of making field changes to the application of such systems. To relate these abstract topic...
Skills Certificates Signal Competencies in a Demand-Driven Economy.
ERIC Educational Resources Information Center
WorkAmerica, 2000
2000-01-01
This issue focuses on the National Alliance of Business's work with employers to sort out how certificates can most effectively indicate workplace skills and requirements and confirm that certified individuals possess them. "Skills Certificates Signal Competencies in a Demand-Driven Economy" discusses the needs to which certificates respond; how…
Casson, Alexander J.
2015-01-01
Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via gmC circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans. PMID:26694414
Casson, Alexander J
2015-12-17
Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via g(m)C circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans.
NASA Astrophysics Data System (ADS)
Shen, Yan; Ge, Jin-ming; Zhang, Guo-qing; Yu, Wen-bin; Liu, Rui-tong; Fan, Wei; Yang, Ying-xuan
2018-01-01
This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.
K-mean clustering algorithm for processing signals from compound semiconductor detectors
NASA Astrophysics Data System (ADS)
Tada, Tsutomu; Hitomi, Keitaro; Wu, Yan; Kim, Seong-Yun; Yamazaki, Hiromichi; Ishii, Keizo
2011-12-01
The K-mean clustering algorithm was employed for processing signal waveforms from TlBr detectors. The signal waveforms were classified based on its shape reflecting the charge collection process in the detector. The classified signal waveforms were processed individually to suppress the pulse height variation of signals due to the charge collection loss. The obtained energy resolution of a 137Cs spectrum measured with a 0.5 mm thick TlBr detector was 1.3% FWHM by employing 500 clusters.
Signal processing in ultrasound. [for diagnostic medicine
NASA Technical Reports Server (NTRS)
Le Croissette, D. H.; Gammell, P. M.
1978-01-01
Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.
Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI.
Koush, Yury; Zvyagintsev, Mikhail; Dyck, Miriam; Mathiak, Krystyna A; Mathiak, Klaus
2012-01-02
Real-time fMRI allows analysis and visualization of the brain activity online, i.e. within one repetition time. It can be used in neurofeedback applications where subjects attempt to control an activation level in a specified region of interest (ROI) of their brain. The signal derived from the ROI is contaminated with noise and artifacts, namely with physiological noise from breathing and heart beat, scanner drift, motion-related artifacts and measurement noise. We developed a Bayesian approach to reduce noise and to remove artifacts in real-time using a modified Kalman filter. The system performs several signal processing operations: subtraction of constant and low-frequency signal components, spike removal and signal smoothing. Quantitative feedback signal quality analysis was used to estimate the quality of the neurofeedback time series and performance of the applied signal processing on different ROIs. The signal-to-noise ratio (SNR) across the entire time series and the group event-related SNR (eSNR) were significantly higher for the processed time series in comparison to the raw data. Applied signal processing improved the t-statistic increasing the significance of blood oxygen level-dependent (BOLD) signal changes. Accordingly, the contrast-to-noise ratio (CNR) of the feedback time series was improved as well. In addition, the data revealed increase of localized self-control across feedback sessions. The new signal processing approach provided reliable neurofeedback, performed precise artifacts removal, reduced noise, and required minimal manual adjustments of parameters. Advanced and fast online signal processing algorithms considerably increased the quality as well as the information content of the control signal which in turn resulted in higher contingency in the neurofeedback loop. Copyright © 2011 Elsevier Inc. All rights reserved.
Issues Management Process Course # 38401
DOE Office of Scientific and Technical Information (OSTI.GOV)
Binion, Ula Marie
The purpose of this training it to advise Issues Management Coordinators (IMCs) on the revised Contractor Assurance System (CAS) Issues Management (IM) process. Terminal Objectives: Understand the Laboratory’s IM process; Understand your role in the Laboratory’s IM process. Learning Objectives: Describe the IM process within the context of the CAS; Describe the importance of implementing an institutional IM process at LANL; Describe the process flow for the Laboratory’s IM process; Apply the definition of an issue; Use available resources to determine initial screening risk levels for issues; Describe the required major process steps for each risk level; Describe the personnelmore » responsibilities for IM process implementation; Access available resources to support IM process implementation.« less
Legal Challenges and Opportunities
ERIC Educational Resources Information Center
Heyward, Salome
2011-01-01
For legal issues in the field of disability compliance, this is an exciting time in postsecondary education. The twentieth anniversary of the Americans with Disabilities Act (ADA) signals a reawakening of the commitment to provide equal access to individuals with disabilities. This chapter explores three of the compliance issues that will be of…
Pacurariu, Alexandra C; Coloma, Preciosa M; van Haren, Anja; Genov, Georgy; Sturkenboom, Miriam C J M; Straus, Sabine M J M
2014-12-01
New pharmacovigilance legislation in the European Union has underlined the importance of signal management, giving the European Medicines Agency's newly established Pharmacovigilance Risk Assessment Committee (PRAC) the mandate to oversee all aspects of the use of medicinal products including detection, assessment, minimization, and communication relating to the risk of adverse reactions. In this study, we describe the signals as brought to the PRAC during the first 18 months of its operation and the ensuing regulatory actions. Data were collected from publicly available sources, for the period July 2012-December 2013, classified according to predefined rules, and described using the appropriate descriptive statistics. Suspected adverse drug reactions were categorized into the Medical Dictionary for Regulatory Affairs and drug names were mapped to the Anatomical Therapeutic Chemical codes. During the study period, 125 signals concerning 96 medicinal products were discussed by the PRAC. The majority of signals were triggered by spontaneous reports (62%) and the median drug age (since marketing authorization) for drugs that prompted a signal was 12 years, significantly less compared with drugs that had no signal within the same period (20 years). The mean time until a decision was reached by the PRAC was 75 days (median 30 days, range 0-273) with 43% of all decisions taken during the first meeting. The decisions to start a referral and to send a direct healthcare professional communication took the least amount of time [54 days (median 27 days, range 0-186) and 51 days (median 0 days, range 0-153)]. The importance of spontaneous reporting in signal detection and monitoring of safety issues throughout the entire life cycle of a medicinal product is confirmed in this study. The amount of time a drug has been on the market is correlated with the number of signals detected. The PRAC decision-making process seems efficient particularly with respect to serious concerns; its role in improving signal prioritization and real-time signal management will be further clarified in its subsequent years of operation.
Regulation of brain insulin signaling: A new function for tau.
Gratuze, Maud; Planel, Emmanuel
2017-08-07
In this issue of JEM, Marciniak et al. (https://doi.org/10.1084/jem.20161731) identify a putative novel function of tau protein as a regulator of insulin signaling in the brain. They find that tau deletion impairs hippocampal response to insulin through IRS-1 and PTEN dysregulation and suggest that, in Alzheimer's disease, impairment of brain insulin signaling might occur via tau loss of function. © 2017 Gratuze and Planel.
Barraza, Paulo; Chavez, Mario; Rodríguez, Eugenio
2016-01-01
Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing. Copyright © 2015 Elsevier Inc. All rights reserved.
Storm, Benjamin C; Bui, Dung C
2016-11-01
Retrieving a subset of items from memory can cause forgetting of other items in memory, a phenomenon referred to as retrieval-induced forgetting (RIF). Individuals who exhibit greater amounts of RIF have been shown to also exhibit superior working memory capacity (WMC) and faster stop-signal reaction times (SSRTs), results which have been interpreted as suggesting that RIF reflects an inhibitory process that is mediated by the processes of executive control. Across four experiments, we sought to further elucidate this issue by manipulating the way in which participants retrieved items during retrieval practice and examining how the resulting effects of forgetting correlated with WMC (Experiments 1-3) and SSRT (Experiment 4). Significant correlations were observed when participants retrieved items from an earlier study phase (within-list retrieval practice), but not when participants generated items from semantic memory (extra-list retrieval practice). These results provide important new insight into the role of executive-control processes in RIF.
Directional dual-tree rational-dilation complex wavelet transform.
Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin
2014-01-01
Dyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced.
Subband-Based Group Delay Segmentation of Spontaneous Speech into Syllable-Like Units
NASA Astrophysics Data System (ADS)
Nagarajan, T.; Murthy, H. A.
2004-12-01
In the development of a syllable-centric automatic speech recognition (ASR) system, segmentation of the acoustic signal into syllabic units is an important stage. Although the short-term energy (STE) function contains useful information about syllable segment boundaries, it has to be processed before segment boundaries can be extracted. This paper presents a subband-based group delay approach to segment spontaneous speech into syllable-like units. This technique exploits the additive property of the Fourier transform phase and the deconvolution property of the cepstrum to smooth the STE function of the speech signal and make it suitable for syllable boundary detection. By treating the STE function as a magnitude spectrum of an arbitrary signal, a minimum-phase group delay function is derived. This group delay function is found to be a better representative of the STE function for syllable boundary detection. Although the group delay function derived from the STE function of the speech signal contains segment boundaries, the boundaries are difficult to determine in the context of long silences, semivowels, and fricatives. In this paper, these issues are specifically addressed and algorithms are developed to improve the segmentation performance. The speech signal is first passed through a bank of three filters, corresponding to three different spectral bands. The STE functions of these signals are computed. Using these three STE functions, three minimum-phase group delay functions are derived. By combining the evidence derived from these group delay functions, the syllable boundaries are detected. Further, a multiresolution-based technique is presented to overcome the problem of shift in segment boundaries during smoothing. Experiments carried out on the Switchboard and OGI-MLTS corpora show that the error in segmentation is at most 25 milliseconds for 67% and 76.6% of the syllable segments, respectively.
Granados-Lieberman, David; Valtierra-Rodriguez, Martin; Morales-Hernandez, Luis A.; Romero-Troncoso, Rene J.; Osornio-Rios, Roque A.
2013-01-01
Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively. PMID:23698264
Inseparable tandem: evolution chooses ATP and Ca2+ to control life, death and cellular signalling
Verkhratsky, Alexei
2016-01-01
From the very dawn of biological evolution, ATP was selected as a multipurpose energy-storing molecule. Metabolism of ATP required intracellular free Ca2+ to be set at exceedingly low concentrations, which in turn provided the background for the role of Ca2+ as a universal signalling molecule. The early-eukaryote life forms also evolved functional compartmentalization and vesicle trafficking, which used Ca2+ as a universal signalling ion; similarly, Ca2+ is needed for regulation of ciliary and flagellar beat, amoeboid movement, intracellular transport, as well as of numerous metabolic processes. Thus, during evolution, exploitation of atmospheric oxygen and increasingly efficient ATP production via oxidative phosphorylation by bacterial endosymbionts were a first step for the emergence of complex eukaryotic cells. Simultaneously, Ca2+ started to be exploited for short-range signalling, despite restrictions by the preset phosphate-based energy metabolism, when both phosphates and Ca2+ interfere with each other because of the low solubility of calcium phosphates. The need to keep cytosolic Ca2+ low forced cells to restrict Ca2+ signals in space and time and to develop energetically favourable Ca2+ signalling and Ca2+ microdomains. These steps in tandem dominated further evolution. The ATP molecule (often released by Ca2+-regulated exocytosis) rapidly grew to be the universal chemical messenger for intercellular communication; ATP effects are mediated by an extended family of purinoceptors often linked to Ca2+ signalling. Similar to atmospheric oxygen, Ca2+ must have been reverted from a deleterious agent to a most useful (intra- and extracellular) signalling molecule. Invention of intracellular trafficking further increased the role for Ca2+ homeostasis that became critical for regulation of cell survival and cell death. Several mutually interdependent effects of Ca2+ and ATP have been exploited in evolution, thus turning an originally unholy alliance into a fascinating success story. This article is part of the themed issue ‘Evolution brings Ca2+ and ATP together to control life and death’. PMID:27377729
Towards the understanding of network information processing in biology
NASA Astrophysics Data System (ADS)
Singh, Vijay
Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.
Laser doppler blood flow imaging using a CMOS imaging sensor with on-chip signal processing.
He, Diwei; Nguyen, Hoang C; Hayes-Gill, Barrie R; Zhu, Yiqun; Crowe, John A; Gill, Cally; Clough, Geraldine F; Morgan, Stephen P
2013-09-18
The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.
A novel digital pulse processing architecture for nuclear instrumentation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moline, Yoann; Thevenin, Mathieu; Corre, Gwenole
The field of nuclear instrumentation covers a wide range of applications, including counting, spectrometry, pulse shape discrimination and multi-channel coincidence. These applications are the topic of many researches, new algorithms and implementations are constantly proposed thanks to advances in digital signal processing. However, these improvements are not yet implemented in instrumentation devices. This is especially true for neutron-gamma discrimination applications which traditionally use charge comparison method while literature proposes other algorithms based on frequency domain or wavelet theory which show better performances. Another example is pileups which are generally rejected while pileup correction algorithms also exist. These processes are traditionallymore » performed offline due to two issues. The first is the Poissonian characteristic of the signal, composed of random arrival pulses which requires to current architectures to work in data flow. The second is the real-time requirement, which implies losing pulses when the pulse rate is too high. Despite the possibility of treating the pulses independently from each other, current architectures paralyze the acquisition of the signal during the processing of a pulse. This loss is called dead-time. These two issues have led current architectures to use dedicated solutions based on re-configurable components like Field Programmable Gate Arrays (FPGAs) to overcome the need of performance necessary to deal with dead-time. However, dedicated hardware algorithm implementations on re-configurable technologies are complex and time-consuming. For all these reasons, a programmable Digital pulse Processing (DPP) architecture in a high level language such as Cor C++ which can reduce dead-time would be worthwhile for nuclear instrumentation. This would reduce prototyping and test duration by reducing the level of hardware expertise to implement new algorithms. However, today's programmable solutions do not meet the need of performance to operate online and not allow scaling with the increase in the number of measurement channel. That is why an innovative DPP architecture is proposed in this paper. This architecture is able to overcome dead-time while being programmable and is flexible with the number of measurement channel. Proposed architecture is based on an innovative execution model for pulse processing applications which can be summarized as follow. The signal is not composed of pulses only, consequently, pulses processing does not have to operate on the entire signal. Therefore, the first step of our proposal is pulse extraction by the use of dedicated components named pulse extractors. The triggering step can be achieved after the analog-to-digital conversion without any signal shaping or filtering stages. Pileup detection and accurate pulse time stamping are done at this stage. Any application downstream this step can work on adaptive variable-sized array of samples simplifying pulse processing methods. Then, once the data flow is broken, it is possible to distribute pulses on Functional Units (FUs) which perform processing. As the date of each pulse is known, they can be processed individually out-of-order to provide the results. To manage the pulses distribution, a scheduler and an interconnection network are used. pulses are distributed on the first FU which is not busy without congesting the interconnection network. For this reason, the process duration does not result anymore in dead-time if there are enough FUs. FUs are designed to be standalone and to comprises at least a programmable general purpose processor (ARM, Microblaze) allowing the implementation of complex algorithms without any modification of the hardware. An acquisition chain is composed of a succession of algorithms which lead to organize our FUs as a software macro-pipeline, A simple approach consists in assigning one algorithm per FU. Consequently, the global latency becomes the worst latency of algorithms execution on FU. Moreover, as algorithms are executed locally - i.e. on a FU - this approach limits shared memory requirement. To handle multichannel, we propose FUs sharing, this approach maximize the chance to find a non-busy FU to process an incoming pulse. This is possible since each channel receive random event independently, the pulse extractors associated to them do not necessarily need to access simultaneously to all Computing resources at the same time to distribute their pulses. The major contribution of this paper is the proposition of an execution model and its associated hardware programmable architecture for digital pulse processing that can handle multiple acquisition channels while maintaining the scalability thanks to the use of shared resources. This execution model and associated architecture are validated by simulation of a cycle accurate architecture SystemC model. Proposed architecture shows promising results in terms of scalability while maintaining zero dead-time. This work also permit the sizing of hardware resources requirement required for a predefined set of applications. Future work will focus on the interconnection network and a scheduling policy that can exploit the variable-length of pulses. Then, the hardware implementation of this architecture will be performed and tested for a representative set of application.« less
Patterson, Susan L
2015-09-01
Older individuals often experience declines in cognitive function after events (e.g. infection, or injury) that trigger activation of the immune system. This occurs at least in part because aging sensitizes the response of microglia (the brain's resident immune cells) to signals triggered by an immune challenge. In the aging brain, microglia respond to these signals by producing more pro-inflammatory cytokines (e.g. interleukin-1beta or IL-1β) and producing them for longer than microglia in younger brains. This exaggerated inflammatory response can compromise processes critical for optimal cognitive functioning. Interleukin-1β is central to the inflammatory response and is a key mediator and modulator of an array of associated biological functions; thus its production and release is usually very tightly regulated. This review will focus on the impact of dysregulated production of IL-1β on hippocampus dependent-memory systems and associated synaptic plasticity processes. The neurotrophin brain-derived neurotrophic factor (BNDF) helps to protect neurons from damage caused by infection or injury, and it plays a critical role in many of the same memory and hippocampal plasticity processes compromised by dysregulated production of IL-1β. This suggests that an exaggerated brain inflammatory response, arising from aging and a secondary immune challenge, may erode the capacity to provide the BDNF needed for memory-related plasticity processes at hippocampal synapses. This article is part of a Special Issue entitled 'Neuroimmunology and Synaptic Function'. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Saponara, Sergio; Donati, Massimiliano; Fanucci, Luca; Odendahl, Maximilian; Leupers, Reiner; Errico, Walter
2013-02-01
The on-board data processing is a vital task for any satellite and spacecraft due to the importance of elaborate the sensing data before sending them to the Earth, in order to exploit effectively the bandwidth to the ground station. In the last years the amount of sensing data collected by scientific and commercial space missions has increased significantly, while the available downlink bandwidth is comparatively stable. The increasing demand of on-board real-time processing capabilities represents one of the critical issues in forthcoming European missions. Faster and faster signal and image processing algorithms are required to accomplish planetary observation, surveillance, Synthetic Aperture Radar imaging and telecommunications. The only available space-qualified Digital Signal Processor (DSP) free of International Traffic in Arms Regulations (ITAR) restrictions faces inadequate performance, thus the development of a next generation European DSP is well known to the space community. The DSPACE space-qualified DSP architecture fills the gap between the computational requirements and the available devices. It leverages a pipelined and massively parallel core based on the Very Long Instruction Word (VLIW) paradigm, with 64 registers and 8 operational units, along with cache memories, memory controllers and SpaceWire interfaces. Both the synthesizable VHDL and the software development tools are generated from the LISA high-level model. A Xilinx-XC7K325T FPGA is chosen to realize a compact PCI demonstrator board. Finally first synthesis results on CMOS standard cell technology (ASIC 180 nm) show an area of around 380 kgates and a peak performance of 1000 MIPS and 750 MFLOPS at 125MHz.
Plyler, Patrick N; Reber, Monika Bertges; Kovach, Amanda; Galloway, Elisabeth; Humphrey, Elizabeth
2013-02-01
Multichannel wide dynamic range compression (WDRC) and ChannelFree processing have similar goals yet differ significantly in terms of signal processing. Multichannel WDRC devices divide the input signal into separate frequency bands; a separate level is determined within each frequency band; and compression in each band is based on the level within each band. ChannelFree processing detects the wideband level, and gain adjustments are based on the wideband signal level and adjusted up to 20,000 times per second. Although both signal processing strategies are currently available in hearing aids, it is unclear if differences in these signal processing strategies affect the performance and/or preference of the end user. The purpose of the research was to determine the effects of multichannel wide dynamic range compression and ChannelFree processing on performance and/or preference of listeners using open-canal hearing instruments. An experimental study in which subjects were exposed to a repeated measures design was utilized. Fourteen adult listeners with mild sloping to moderately severe sensorineural hearing loss participated (mean age 67 yr). Participants completed two 5 wk trial periods for each signal processing strategy. Probe microphone, behavioral and subjective measures were conducted unaided and aided at the end of each trial period. Behavioral and subjective results for both signal processing strategies were significantly better than unaided results; however, behavioral and subjective results were not significantly different between the signal processing strategies. Multichannel WDRC and ChannelFree processing are both effective signal processing strategies that provide significant benefit for hearing instrument users. Overall preference between the strategies may be related to the degree of hearing loss of the user, high-frequency in-situ levels, and/or acceptance of background noise. American Academy of Audiology.
The Free Radical Theory of Aging Revisited: The Cell Signaling Disruption Theory of Aging
Borras, Consuelo; Abdelaziz, Kheira M.; Garcia-Valles, Rebeca; Gomez-Cabrera, Mari Carmen
2013-01-01
Abstract Significance: The free radical theory of aging has provided a theoretical framework for an enormous amount of work leading to significant advances in our understanding of aging. Up to the turn of the century, the theory received abundant support from observations coming from fields as far apart as comparative physiology or molecular biology. Recent Advances: Work from many laboratories supports the theory, for instance showing that overexpression of antioxidant enzymes results in increases in life-span. But other labs have shown that in some cases, there is an increased oxidative stress and increased longevity. The discovery that free radicals can not only cause molecular damage to cells, but also serve as signals; led to the proposal that they act as modulators of physiological processes. For instance, reactive oxygen species (ROS) stimulate physiological adaptations to physical exercise. Critical Issues: A critical blow to the free radical theory of aging came from epidemiological studies showing that antioxidant supplementation did not lower the incidence of many age-associated diseases but, in some cases, increased the risk of death. Moreover, recent molecular evidence has shown that increasing generation of ROS, in some cases, increases longevity. Future Directions: Gerontologists interested in free radical biology are at a crossroads and clearly new insights are required to clarify the role of ROS in the process of aging. The hurdles are, no doubt, very high, but the intellectual and practical promise of these studies is of such magnitude that we feel that all efforts will be generously rewarding. Antioxid. Redox Signal. 19, 779–787. PMID:23841595
Endoplasmic Reticulum Stress and Oxidative Stress in Cell Fate Decision and Human Disease
Cao, Stewart Siyan
2014-01-01
Abstract Significance: The endoplasmic reticulum (ER) is a specialized organelle for the folding and trafficking of proteins, which is highly sensitive to changes in intracellular homeostasis and extracellular stimuli. Alterations in the protein-folding environment cause accumulation of misfolded proteins in the ER that profoundly affect a variety of cellular signaling processes, including reduction–oxidation (redox) homeostasis, energy production, inflammation, differentiation, and apoptosis. The unfolded protein response (UPR) is a collection of adaptive signaling pathways that evolved to resolve protein misfolding and restore an efficient protein-folding environment. Recent Advances: Production of reactive oxygen species (ROS) has been linked to ER stress and the UPR. ROS play a critical role in many cellular processes and can be produced in the cytosol and several organelles, including the ER and mitochondria. Studies suggest that altered redox homeostasis in the ER is sufficient to cause ER stress, which could, in turn, induce the production of ROS in the ER and mitochondria. Critical Issues: Although ER stress and oxidative stress coexist in many pathologic states, whether and how these stresses interact is unknown. It is also unclear how changes in the protein-folding environment in the ER cause oxidative stress. In addition, how ROS production and protein misfolding commit the cell to an apoptotic death and contribute to various degenerative diseases is unknown. Future Directions: A greater fundamental understanding of the mechanisms that preserve protein folding homeostasis and redox status will provide new information toward the development of novel therapeutics for many human diseases. Antioxid. Redox Signal. 21, 396–413. PMID:24702237
S-nitrosylation in the regulation of gene transcription☆
Sha, Yonggang; Marshall, Harvey E.
2015-01-01
Background Post-translational modification of proteins by S-nitrosylation serves as a major mode of signaling in mammalian cells and a growing body of evidence has shown that transcription factors and their activating pathways are primary targets. S-nitrosylation directly modifies a number of transcription factors, including NF-κB, HIF-1, and AP-1. In addition, S-nitrosylation can indirectly regulate gene transcription by modulating other cell signaling pathways, in particular JNK kinase and ras. Scope of review The evolution of S-nitrosylation as a signaling mechanism in the regulation of gene transcription, physiological advantages of protein S-nitrosylation in the control of gene transcription, and discussion of the many transcriptional proteins modulated by S-nitrosylation is summarized. Major conclusions S-nitrosylation plays a crucial role in the control of mammalian gene transcription with numerous transcription factors regulated by this modification. Many of these proteins serve as immunomodulators, and inducible nitric oxide synthase (iNOS) is regarded as a principal mediatiator of NO-dependent S-nitrosylation. However, additional targets within the nucleus (e.g. histone deacetylases) and alternative mechanisms of S-nitrosylation (e.g. GAPDH-mediated trans-nitrosylation) are thought to play a role in NOS-dependent transcriptional regulation. General significance Derangement of SNO-regulated gene transcription is an important factor in a variety of pathological conditions including neoplasia and sepsis. A better understanding of protein S-nitrosylation as it relates to gene transcription and the physiological mechanisms behind this process is likely to lead to novel therapies for these disorders. This article is part of a Special Issue entitled Regulation of Cellular Processes by S-nitrosylation. PMID:21640163
Kotiadis, Vassilios N.; Duchen, Michael R.; Osellame, Laura D.
2014-01-01
Background The maintenance of cell metabolism and homeostasis is a fundamental characteristic of living organisms. In eukaryotes, mitochondria are the cornerstone of these life supporting processes, playing leading roles in a host of core cellular functions, including energy transduction, metabolic and calcium signalling, and supporting roles in a number of biosynthetic pathways. The possession of a discrete mitochondrial genome dictates that the maintenance of mitochondrial ‘fitness’ requires quality control mechanisms which involve close communication with the nucleus. Scope of review This review explores the synergistic mechanisms that control mitochondrial quality and function and ensure cellular bioenergetic homeostasis. These include antioxidant defence mechanisms that protect against oxidative damage caused by reactive oxygen species, while regulating signals transduced through such free radicals. Protein homeostasis controls import, folding, and degradation of proteins underpinned by mechanisms that regulate bioenergetic capacity through the mitochondrial unfolded protein response. Autophagic machinery is recruited for mitochondrial turnover through the process of mitophagy. Mitochondria also communicate with the nucleus to exact specific transcriptional responses through retrograde signalling pathways. Major conclusions The outcome of mitochondrial quality control is not only reliant on the efficient operation of the core homeostatic mechanisms but also in the effective interaction of mitochondria with other cellular components, namely the nucleus. General significance Understanding mitochondrial quality control and the interactions between the organelle and the nucleus will be crucial in developing therapies for the plethora of diseases in which the pathophysiology is determined by mitochondrial dysfunction. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. PMID:24211250
Multichannel heterodyning for wideband interferometry, correlation and signal processing
Erskine, David J.
1999-01-01
A method of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized.
Multichannel heterodyning for wideband interferometry, correlation and signal processing
Erskine, D.J.
1999-08-24
A method is disclosed of signal processing a high bandwidth signal by coherently subdividing it into many narrow bandwidth channels which are individually processed at lower frequencies in a parallel manner. Autocorrelation and correlations can be performed using reference frequencies which may drift slowly with time, reducing cost of device. Coordinated adjustment of channel phases alters temporal and spectral behavior of net signal process more precisely than a channel used individually. This is a method of implementing precision long coherent delays, interferometers, and filters for high bandwidth optical or microwave signals using low bandwidth electronics. High bandwidth signals can be recorded, mathematically manipulated, and synthesized. 50 figs.
Phasic dopamine signals: from subjective reward value to formal economic utility
Schultz, Wolfram; Carelli, Regina M; Wightman, R Mark
2015-01-01
Although rewards are physical stimuli and objects, their value for survival and reproduction is subjective. The phasic, neurophysiological and voltammetric dopamine reward prediction error response signals subjective reward value. The signal incorporates crucial reward aspects such as amount, probability, type, risk, delay and effort. Differences of dopamine release dynamics with temporal delay and effort in rodents may derive from methodological issues and require further study. Recent designs using concepts and behavioral tools from experimental economics allow to formally characterize the subjective value signal as economic utility and thus to establish a neuronal value function. With these properties, the dopamine response constitutes a utility prediction error signal. PMID:26719853
System and Method for Multi-Wavelength Optical Signal Detection
NASA Technical Reports Server (NTRS)
McGlone, Thomas D. (Inventor)
2017-01-01
The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.
Analysis of acoustic emission signals and monitoring of machining processes
Govekar; Gradisek; Grabec
2000-03-01
Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.
Specificity in ROS Signaling and Transcript Signatures
Vaahtera, Lauri; Brosché, Mikael; Wrzaczek, Michael
2014-01-01
Abstract Significance: Reactive oxygen species (ROS), important signaling molecules in plants, are involved in developmental control and stress adaptation. ROS production can trigger broad transcriptional changes; however, it is not clear how specificity in transcriptional regulation is achieved. Recent Advances: A large collection of public transcriptome data from the model plant Arabidopsis thaliana is available for analysis. These data can be used for the analysis of biological processes that are associated with ROS signaling and for the identification of suitable transcriptional indicators. Several online tools, such as Genevestigator and Expression Angler, have simplified the task to analyze, interpret, and visualize this wealth of data. Critical Issues: The analysis of the exact transcriptional responses to ROS requires the production of specific ROS in distinct subcellular compartments with precise timing, which is experimentally difficult. Analyses are further complicated by the effect of ROS production in one subcellular location on the ROS accumulation in other compartments. In addition, even subtle differences in the method of ROS production or treatment can lead to significantly different outcomes when various stimuli are compared. Future Directions: Due to the difficulty of inducing ROS production specifically with regard to ROS type, subcellular localization, and timing, we propose that the concept of a “ROS marker gene” should be re-evaluated. We suggest guidelines for the analysis of transcriptional data in ROS signaling. The use of “ROS signatures,” which consist of a set of genes that together can show characteristic and indicative responses, should be preferred over the use of individual marker genes. Antioxid. Redox Signal. 21, 1422–1441. PMID:24180661
Technical Note: Kinect V2 surface filtering during gantry motion for radiotherapy applications.
Nazir, Souha; Rihana, Sandy; Visvikis, Dimitris; Fayad, Hadi
2018-04-01
In radiotherapy, the Kinect V2 camera, has recently received a lot of attention concerning many clinical applications including patient positioning, respiratory motion tracking, and collision detection during the radiotherapy delivery phase. However, issues associated with such applications are related to some materials and surfaces reflections generating an offset in depth measurements especially during gantry motion. This phenomenon appears in particular when the collimator surface is observed by the camera; resulting in erroneous depth measurements, not only in Kinect surfaces itself, but also as a large peak when extracting a 1D respiratory signal from these data. In this paper, we proposed filtering techniques to reduce the noise effect in the Kinect-based 1D respiratory signal, using a trend removal filter, and in associated 2D surfaces, using a temporal median filter. Filtering process was validated using a phantom, in order to simulate a patient undergoing radiotherapy treatment while having the ground truth. Our results indicate a better correlation between the reference respiratory signal and its corresponding filtered signal (Correlation coefficient of 0.76) than that of the nonfiltered signal (Correlation coefficient of 0.13). Furthermore, surface filtering results show a decrease in the mean square distance error (85%) between the reference and the measured point clouds. This work shows a significant noise compensation and surface restitution after surface filtering and therefore a potential use of the Kinect V2 camera for different radiotherapy-based applications, such as respiratory tracking and collision detection. © 2018 American Association of Physicists in Medicine.
Ouyang, Kesai; Lu, Siliang; Zhang, Shangbin; Zhang, Haibin; He, Qingbo; Kong, Fanrang
2015-01-01
The railway occupies a fairly important position in transportation due to its high speed and strong transportation capability. As a consequence, it is a key issue to guarantee continuous running and transportation safety of trains. Meanwhile, time consumption of the diagnosis procedure is of extreme importance for the detecting system. However, most of the current adopted techniques in the wayside acoustic defective bearing detector system (ADBD) are offline strategies, which means that the signal is analyzed after the sampling process. This would result in unavoidable time latency. Besides, the acquired acoustic signal would be corrupted by the Doppler effect because of high relative speed between the train and the data acquisition system (DAS). Thus, it is difficult to effectively diagnose the bearing defects immediately. In this paper, a new strategy called online Doppler effect elimination (ODEE) is proposed to remove the Doppler distortion online by the introduced unequal interval sampling scheme. The steps of proposed strategy are as follows: The essential parameters are acquired in advance. Then, the introduced unequal time interval sampling strategy is used to restore the Doppler distortion signal, and the amplitude of the signal is demodulated as well. Thus, the restored Doppler-free signal is obtained online. The proposed ODEE method has been employed in simulation analysis. Ultimately, the ODEE method is implemented in the embedded system for fault diagnosis of the train bearing. The results are in good accordance with the bearing defects, which verifies the good performance of the proposed strategy. PMID:26343657
Advanced signal processing based on support vector regression for lidar applications
NASA Astrophysics Data System (ADS)
Gelfusa, M.; Murari, A.; Malizia, A.; Lungaroni, M.; Peluso, E.; Parracino, S.; Talebzadeh, S.; Vega, J.; Gaudio, P.
2015-10-01
The LIDAR technique has recently found many applications in atmospheric physics and remote sensing. One of the main issues, in the deployment of systems based on LIDAR, is the filtering of the backscattered signal to alleviate the problems generated by noise. Improvement in the signal to noise ratio is typically achieved by averaging a quite large number (of the order of hundreds) of successive laser pulses. This approach can be effective but presents significant limitations. First of all, it implies a great stress on the laser source, particularly in the case of systems for automatic monitoring of large areas for long periods. Secondly, this solution can become difficult to implement in applications characterised by rapid variations of the atmosphere, for example in the case of pollutant emissions, or by abrupt changes in the noise. In this contribution, a new method for the software filtering and denoising of LIDAR signals is presented. The technique is based on support vector regression. The proposed new method is insensitive to the statistics of the noise and is therefore fully general and quite robust. The developed numerical tool has been systematically compared with the most powerful techniques available, using both synthetic and experimental data. Its performances have been tested for various statistical distributions of the noise and also for other disturbances of the acquired signal such as outliers. The competitive advantages of the proposed method are fully documented. The potential of the proposed approach to widen the capability of the LIDAR technique, particularly in the detection of widespread smoke, is discussed in detail.
Gong, Guohua; Wang, Xianhua; Wei-LaPierre, Lan; Cheng, Heping; Dirksen, Robert
2016-01-01
Abstract Significance: Recent breakthroughs in mitochondrial research have advanced, reshaped, and revolutionized our view of the role of mitochondria in health and disease. These discoveries include the development of novel tools to probe mitochondrial biology, the molecular identification of mitochondrial functional proteins, and the emergence of new concepts and mechanisms in mitochondrial function regulation. The discovery of “mitochondrial flash” activity has provided unique insights not only into real-time visualization of individual mitochondrial redox and pH dynamics in live cells but has also advanced understanding of the excitability, autonomy, and integration of mitochondrial function in vivo. Recent Advances: The mitochondrial flash is a transient and stochastic event confined within an individual mitochondrion and is observed in a wide range of organisms from plants to Caenorhabditis elegans to mammals. As flash events involve multiple transient concurrent changes within the mitochondrion (e.g., superoxide, pH, and membrane potential), a number of different mitochondrial targeted fluorescent indicators can detect flash activity. Accumulating evidence indicates that flash events reflect integrated snapshots of an intermittent mitochondrial process arising from mitochondrial respiration chain activity associated with the transient opening of the mitochondrial permeability transition pore. Critical Issues: We review the history of flash discovery, summarize current understanding of flash biology, highlight controversies regarding the relative roles of superoxide and pH signals during a flash event, and bring forth the integration of both signals in flash genesis. Future Directions: Investigations using flash as a biomarker and establishing its role in cell signaling pathway will move the field forward. Antioxid. Redox Signal. 25, 534–549. PMID:27245241
Real-time processing of EMG signals for bionic arm purposes
NASA Astrophysics Data System (ADS)
Olid Dominguez, Ferran; Wawrzyniak, Zbigniew M.
2016-09-01
This paper is connected with the problem of prostheses, that have always been a necessity for the human being. Bio-physiological signals from muscles, electromyographic signals have been collected, analyzed and processed in order to implement a real-time algorithm which is capable of differentiation of two different states of a bionic hand: open and closed. An algorithm for real-time electromyographic signal processing with almost no false positives is presented and it is explained that in bio-physiological experiments proper signal processing is of great importance.
Intelligent Signal Processing for Active Control
1992-06-17
FUNDING NUMSI Intelligent Signal Processing for Active Control C-NO001489-J-1633 G. AUTHOR(S) P.A. Ramamoorthy 7. P2RFORMING ORGANIZATION NAME(S) AND...unclassified .unclassified unclassified L . I mu-. W UNIVERSITY OF CINCINNATI COLLEGE OF ENGINEERING Intelligent Signal Processing For Rctiue Control...NAURI RESEARCH Conkact No: NO1489-J-1633 P.L: P.A.imoodh Intelligent Signal Processing For Active Control 1 Executive Summary The thrust of this
Capture of Fluorescence Decay Times by Flow Cytometry
Naivar, Mark A.; Jenkins, Patrick; Freyer, James P.
2012-01-01
In flow cytometry, the fluorescence decay time of an excitable species has been largely underutilized and is not likely found as a standard parameter on any imaging cytometer, sorting, or analyzing system. Most cytometers lack fluorescence lifetime hardware mainly owing to two central issues. Foremost, research and development with lifetime techniques has lacked proper exploitation of modern laser systems, data acquisition boards, and signal processing techniques. Secondly, a lack of enthusiasm for fluorescence lifetime applications in cells and with bead-based assays has persisted among the greater cytometry community. In this unit, we describe new approaches that address these issues and demonstrate the simplicity of digitally acquiring fluorescence relaxation rates in flow. The unit is divided into protocol and commentary sections in order to provide a most comprehensive discourse on acquiring the fluorescence lifetime with frequency-domain methods. The unit covers (i) standard fluorescence lifetime acquisition (protocol-based) with frequency-modulated laser excitation, (ii) digital frequency-domain cytometry analyses, and (iii) interfacing fluorescence lifetime measurements onto sorting systems. Within the unit is also a discussion on how digital methods are used for aliasing in order to harness higher frequency ranges. Also, a final discussion is provided on heterodyning and processing of waveforms for multi-exponential decay extraction. PMID:25419263
Design, modeling, and analysis of multi-channel demultiplexer/demodulator
NASA Technical Reports Server (NTRS)
Lee, David D.; Woo, K. T.
1991-01-01
Traditionally, satellites have performed the function of a simple repeater. Newer data distribution satellite architectures, however, require demodulation of many frequency division multiplexed uplink channels by a single demultiplexer/demodulator unit, baseband processing and routing of individual voice/data circuits, and remodulation into time division multiplexed (TDM) downlink carriers. The TRW MCDD (Multichannel Demultiplexer/Multirate Demodulator) operates on a 37.4 MHz composite input signal. Individual channel data rates are either 64 Kbps or 2.048 Mbps. The wideband demultiplexer divides the input signal into 1.44 MHz segments containing either a single 2.048 Mbps channel or thirty two 64 Kbps channels. In the latter case, the narrowband demultiplexer further divides the single 1.44 MHz wideband channel into thirty two 45 KHz narrowband channels. With this approach the time domain Fast Fourier Transformation (FFT) channelizer processing capacity is matched well to the bandwidth and number of channels to be demultiplexed. By using a multirate demodulator fewer demodulators are required while achieving greater flexibility. Each demodulator can process a wideband channel or thirty two narrowband channels. Either all wideband channels, a mixture of wideband and narrowband channels, or all narrowband channels can be demodulated. The multirate demodulator approach also has lower nonrecurring costs since only one design and development effort is needed. TRW has developed a proof of concept (POC) model which fully demonstrates the signal processing fuctions of MCDD. It is capable of processing either three 2.048 Mbps channels or two 2.048 Mbps channels and thirty two 64 Kbps channels. An overview of important MCDD system engineering issues is presented as well as discussion on some of the Block Oriented System Simulation analyses performed for design verification and selection of operational parameters of the POC model. Systems engineering analysis of the POC model confirmed that the MCDD concepts are not only achievable but also balance the joint goals of minimizing on-board complexity and cost of ground equipment, while retaining the flexibility needed to meet a wide range of system requirements.
NASA Technical Reports Server (NTRS)
Stevens, G. H.; Anzic, G.
1979-01-01
Issues and results in a NASA study of the potential concepts and markets for a multibeam 30/20 GHz domestic satellite system in the 1990s are presented. Issues considered include the reduction of signal attenuation due to rain, beam-beam interference isolation in the multibeam system, the method of access/modulation (FDMA, TDMA or hybrid) and the market for reduced reliability and wideband services. A hypothetical demonstration payload configuration which would attempt to resolve these issues is illustrated. The communications payload would employ a system of seven contiguous coverage spots in order to demonstrate a typical cell in a contiguous beam system having extensive frequency re-use, as in a direct-to-user system, and a single spot, typical of a trunking system, to determine signal isolation. The payload could be carried on several existing buses and is illustrated on an MMS bus.
Traffic Light Geography: A Fifth Grade Community Project.
ERIC Educational Resources Information Center
Zirschky, E. Dwight
1989-01-01
Describes a community study project that uses history and the five fundamental themes of geography as a framework. The project involves organizing committees to study the need for a traffic signal in a small town. By studying various dimensions of the issue, the committees are able to demonstrate the need for a signal. (KO)
Stress Can Be a Good Thing for Blood Formation.
Speck, Nancy A
2016-09-01
Like politics, most developmental signals are local. However, in this issue of Cell Stem Cell, Kwan et al. (2016) and colleagues describe how a stress-induced signal that originates in the zebrafish brain promotes the formation of blood at a distant site, the dorsal aorta. Copyright © 2016 Elsevier Inc. All rights reserved.