Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma

PubMed Central

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-01-01

AIM: To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). METHODS: A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. RESULTS: In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P < 0.001) and objective tumor response (P = 0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P = 0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P < 0.001). Multivariate analysis identified tumor stage (P < 0.001) and tumor type (P = 0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P < 0.001), surgical treatment (P = 0.009), and multi-modal treatment (P = 0.002) were identified as independent post-treatment prognostic factors. CONCLUSION: TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC. PMID:25741147

System Framework for a Multi-Band, Multi-Mode Software Defined Radio

DTIC Science & Technology

2014-06-01

detection, while the VITA Radio Transport ( VRT ) protocol over Gigabit Ethernet (GIGE) is implemented for the data interface. In addition to the SoC...CTRL VGA CTRL C2 GPP C2 CORE SW ARM0 RX SYN CTRL PL MEMORY MAP DR CTRL GENERIC INTERRUPT CONTROLLER DR GPP VITERBI ALGORITHM & VRT INTERFACE ARM1

Producing Multimodal Picture Books and Dramatic Performances in a Core French Classroom: An Exploratory Case Study

ERIC Educational Resources Information Center

Early, Margaret; Yeung, Cindy

2009-01-01

In a Grade 9 core French class, the teacher designed a multi-stage project in which students composed original children's stories in French; illustrated their stories to produce picture books; then, in groups, adapted one group member's story into a play script; and, finally, dramatized the scripts for children from the local French immersion…

Phase congruency map driven brain tumour segmentation

NASA Astrophysics Data System (ADS)

Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

2015-03-01

Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

Multimodal transmission property in a liquid-filled photonic crystal fiber

NASA Astrophysics Data System (ADS)

Lin, Wei; Miao, Yinping; Song, Binbin; Zhang, Hao; Liu, Bo; Liu, Yange; Yan, Donglin

2015-02-01

The multimode interference (MMI) effect in a liquid-filled photonic crystal fiber (PCF) has been experimentally demonstrated by fully infiltrating the air-hole cladding of a solid-core PCF with the refractive index (RI) matching liquid whose RI is close to the silica background. Due to the weak mode confinement capability of the cladding region, several high-order modes are excited to establish the multimode interference effect. The multimode interferometer shows a good temperature tunability of 12.30 nm/K, which makes it a good candidate for a highly tunable optical filtering as well as temperature sensing applications. Furthermore, this MMI effect would have great promise in various applications such as highly sensitive multi-parameter sensing, tunable optically filtering, and surface-enhanced Raman scattering.

Object recognition through a multi-mode fiber

NASA Astrophysics Data System (ADS)

Takagi, Ryosuke; Horisaki, Ryoichi; Tanida, Jun

2017-04-01

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

NASA Astrophysics Data System (ADS)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

Scaling Fiber Lasers to Large Mode Area: An Investigation of Passive Mode-Locking Using a Multi-Mode Fiber

PubMed Central

Ding, Edwin; Lefrancois, Simon; Kutz, Jose Nathan; Wise, Frank W.

2011-01-01

The mode-locking of dissipative soliton fiber lasers using large mode area fiber supporting multiple transverse modes is studied experimentally and theoretically. The averaged mode-locking dynamics in a multi-mode fiber are studied using a distributed model. The co-propagation of multiple transverse modes is governed by a system of coupled Ginzburg–Landau equations. Simulations show that stable and robust mode-locked pulses can be produced. However, the mode-locking can be destabilized by excessive higher-order mode content. Experiments using large core step-index fiber, photonic crystal fiber, and chirally-coupled core fiber show that mode-locking can be significantly disturbed in the presence of higher-order modes, resulting in lower maximum single-pulse energies. In practice, spatial mode content must be carefully controlled to achieve full pulse energy scaling. This paper demonstrates that mode-locking performance is very sensitive to the presence of multiple waveguide modes when compared to systems such as amplifiers and continuous-wave lasers. PMID:21731106

Scaling Fiber Lasers to Large Mode Area: An Investigation of Passive Mode-Locking Using a Multi-Mode Fiber.

PubMed

Ding, Edwin; Lefrancois, Simon; Kutz, Jose Nathan; Wise, Frank W

2011-01-01

The mode-locking of dissipative soliton fiber lasers using large mode area fiber supporting multiple transverse modes is studied experimentally and theoretically. The averaged mode-locking dynamics in a multi-mode fiber are studied using a distributed model. The co-propagation of multiple transverse modes is governed by a system of coupled Ginzburg-Landau equations. Simulations show that stable and robust mode-locked pulses can be produced. However, the mode-locking can be destabilized by excessive higher-order mode content. Experiments using large core step-index fiber, photonic crystal fiber, and chirally-coupled core fiber show that mode-locking can be significantly disturbed in the presence of higher-order modes, resulting in lower maximum single-pulse energies. In practice, spatial mode content must be carefully controlled to achieve full pulse energy scaling. This paper demonstrates that mode-locking performance is very sensitive to the presence of multiple waveguide modes when compared to systems such as amplifiers and continuous-wave lasers.

Multi-Modal Intelligent Traffic Signal Systems (MMITSS) impacts assessment.

DOT National Transportation Integrated Search

2015-08-01

The study evaluates the potential network-wide impacts of the Multi-Modal Intelligent Transportation Signal System (MMITSS) based on a field data analysis utilizing data collected from a MMITSS prototype and a simulation analysis. The Intelligent Tra...

Highly Sensitive Liquid Core Temperature Sensor Based on Multimode Interference Effects

PubMed Central

Fuentes-Fuentes, Miguel A.; May-Arrioja, Daniel A.; Guzman-Sepulveda, José R.; Torres-Cisneros, Miguel; Sánchez-Mondragón, José J.

2015-01-01

A novel fiber optic temperature sensor based on a liquid-core multimode interference device is demonstrated. The advantage of such structure is that the thermo-optic coefficient (TOC) of the liquid is at least one order of magnitude larger than that of silica and this, combined with the fact that the TOC of silica and the liquid have opposite signs, provides a liquid-core multimode fiber (MMF) highly sensitive to temperature. Since the refractive index of the liquid can be easily modified, this allows us to control the modal properties of the liquid-core MMF at will and the sensor sensitivity can be easily tuned by selecting the refractive index of the liquid in the core of the device. The maximum sensitivity measured in our experiments is 20 nm/°C in the low-temperature regime up to 60 °C. To the best of our knowledge, to date, this is the largest sensitivity reported for fiber-based MMI temperature sensors. PMID:26512664

Multifunctional Fe3O4 @ Au core/shell nanostars: a unique platform for multimode imaging and photothermal therapy of tumors

PubMed Central

Hu, Yong; Wang, Ruizhi; Wang, Shige; Ding, Ling; Li, Jingchao; Luo, Yu; Wang, Xiaolin; Shen, Mingwu; Shi, Xiangyang

2016-01-01

We herein report the development of multifunctional folic acid (FA)-targeted Fe3O4 @ Au nanostars (NSs) for targeted multi-mode magnetic resonance (MR)/computed tomography (CT)/photoacoustic (PA) imaging and photothermal therapy (PTT) of tumors. In this present work, citric acid-stabilized Fe3O4/Ag composite nanoparticles prepared by a mild reduction route were utilized as seeds and exposed to the Au growth solution to induce the formation of Fe3O4 @ Au core/shell NSs. Followed by successive decoration of thiolated polyethyleneimine (PEI-SH), FA via a polyethylene glycol spacer, and acetylation of the residual PEI amines, multifunctional Fe3O4 @ Au NSs were formed. The designed multifunctional NSs possess excellent colloidal stability, good cytocompatibility in a given concentration range, and specific recognition to cancer cells overexpressing FA receptors. Due to co-existence of Fe3O4 core and star-shaped Au shell, the NSs can be used for MR and CT imaging of tumors, respectively. Likewise, the near infrared plasmonic absorption feature also enables the NSs to be used for PA imaging and PTT of tumors. Our study clearly demonstrates a unique theranostic nanoplatform that can be used for high performance multi-mode imaging-guided PTT of tumors, which may be extendable for theranostics of different diseases in translational medicine. PMID:27325015

Multi-Modal Hallucinations and Cognitive Function in Parkinson's Disease

PubMed Central

Katzen, Heather; Myerson, Connie; Papapetropoulos, Spiridon; Nahab, Fatta; Gallo, Bruno; Levin, Bonnie

2010-01-01

Background/Aims Hallucinations have been linked to a constellation of cognitive deficits in Parkinson's disease (PD), but it is not known whether multi-modal hallucinations are associated with greater neuropsychological dysfunction. Methods 152 idiopathic PD patients were categorized based on the presence or absence of hallucinations and then were further subdivided into visual-only (VHonly; n = 35) or multi-modal (VHplus; n = 12) hallucination groups. All participants underwent detailed neuropsychological assessment. Results Participants with hallucinations performed more poorly on select neuropsychological measures and exhibited more mood symptoms. There were no differences between VHonly and VHplus groups. Conclusions PD patients with multi-modal hallucinations are not at greater risk for neuropsychological impairment than those with single-modal hallucinations. PMID:20689283

Serum protein measurement using a tapered fluorescent fibre-optic evanescent wave-based biosensor

NASA Astrophysics Data System (ADS)

Preejith, P. V.; Lim, C. S.; Chia, T. F.

2006-12-01

A novel method to measure the total serum protein concentration is described in this paper. The method is based on the principles of fibre-optic evanescent wave spectroscopy. The biosensor applies a fluorescent dye-immobilized porous glass coating on a multi-mode optical fibre. The evanescent wave's intensity at the fibre-optic core-cladding interface is used to monitor the protein-induced changes in the sensor element. The sensor offers a rapid, single-step method for quantifying protein concentrations without destroying the sample. This unique sensing method presents a sensitive and accurate platform for the quantification of protein.

Collaboration of Miniature Multi-Modal Mobile Smart Robots over a Network

DTIC Science & Technology

2015-08-14

theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The views...theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The...independently evolving research directions based on physics-based models of mechanical, electromechanical and electronic devices, operational constraints

Phonetic Variation and Interactional Contingencies in Simultaneous Responses

ERIC Educational Resources Information Center

Walker, Gareth

2016-01-01

An auspicious but unexplored environment for studying phonetic variation in naturalistic interaction is where two or more participants say the same thing at the same time. Working with a core dataset built from the multimodal Augmented Multi-party Interaction corpus, the principles of conversation analysis were followed to analyze the sequential…

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

PubMed

Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

2015-12-01

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

Theory-based transport simulations of TFTR L-mode temperature profiles

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

Bateman, G.

1992-03-01

The temperature profiles from a selection of Tokamak Fusion Test Reactor (TFTR) L-mode discharges (17{ital th} {ital European} {ital Conference} {ital on} {ital Controlled} {ital Fusion} {ital and} {ital Plasma} {ital Heating}, Amsterdam, 1990 (EPS, Petit-Lancy, Switzerland, 1990, p. 114)) are simulated with the 1 (1)/(2) -D baldur transport code (Comput. Phys. Commun. {bold 49}, 275 (1988)) using a combination of theoretically derived transport models, called the Multi-Mode Model (Comments Plasma Phys. Controlled Fusion {bold 11}, 165 (1988)). The present version of the Multi-Mode Model consists of effective thermal diffusivities resulting from trapped electron modes and ion temperature gradient ({eta}{submore » {ital i}}) modes, which dominate in the core of the plasma, together with resistive ballooning modes, which dominate in the periphery. Within the context of this transport model and the TFTR simulations reported here, the scaling of confinement with heating power comes from the temperature dependence of the {eta}{sub {ital i}} and trapped electron modes, while the scaling with current comes mostly from resistive ballooning modes.« less

Rhesus macaques recognize unique multi-modal face-voice relations of familiar individuals and not of unfamiliar ones

PubMed Central

Habbershon, Holly M.; Ahmed, Sarah Z.; Cohen, Yale E.

2013-01-01

Communication signals in non-human primates are inherently multi-modal. However, for laboratory-housed monkeys, there is relatively little evidence in support of the use of multi-modal communication signals in individual recognition. Here, we used a preferential-looking paradigm to test whether laboratory-housed rhesus could “spontaneously” (i.e., in the absence of operant training) use multi-modal communication stimuli to discriminate between known conspecifics. The multi-modal stimulus was a silent movie of two monkeys vocalizing and an audio file of the vocalization from one of the monkeys in the movie. We found that the gaze patterns of those monkeys that knew the individuals in the movie were reliably biased toward the individual that did not produce the vocalization. In contrast, there was not a systematic gaze pattern for those monkeys that did not know the individuals in the movie. These data are consistent with the hypothesis that laboratory-housed rhesus can recognize and distinguish between conspecifics based on auditory and visual communication signals. PMID:23774779

Multi-Modal Performance Measures in Oregon: Developing a Transportation Cost Index Based Upon Multi-Modal Network and Land Use Information

DOT National Transportation Integrated Search

2016-02-01

Transportation Cost Index is a performance measure for transportation and land use systems originally proposed and piloted by Reiff and Gregor (2005). It fills important niches of existing similar measures in term of policy areas covered and type of ...

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

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

Wang, Yin; Wang, Wen; Wysocki, Gerard, E-mail: gwysocki@princeton.edu

In this Letter, we present a method of performing broadband mid-infrared spectroscopy with conventional, free-running, continuous wave Fabry-Perot quantum cascade lasers (FP-QCLs). The measurement method is based on multi-heterodyne down-conversion of optical signals. The sample transmission spectrum probed by one multi-mode FP-QCL is down-converted to the radio-frequency domain through an optical multi-heterodyne process using a second FP-QCL as the local oscillator. Both a broadband multi-mode spectral measurement as well as high-resolution (∼15 MHz) spectroscopy of molecular absorption are demonstrated and show great potential for development of high performance FP-laser-based spectrometers for chemical sensing.

A Review of Intravascular Ultrasound–Based Multimodal Intravascular Imaging: The Synergistic Approach to Characterizing Vulnerable Plaques

PubMed Central

Ma, Teng; Zhou, Bill; Hsiai, Tzung K.; Shung, K. Kirk

2015-01-01

Catheter-based intravascular imaging modalities are being developed to visualize pathologies in coronary arteries, such as high-risk vulnerable atherosclerotic plaques known as thin-cap fibroatheroma, to guide therapeutic strategy at preventing heart attacks. Mounting evidences have shown three distinctive histopathological features—the presence of a thin fibrous cap, a lipid-rich necrotic core, and numerous infiltrating macrophages—are key markers of increased vulnerability in atherosclerotic plaques. To visualize these changes, the majority of catheter-based imaging modalities used intravascular ultrasound (IVUS) as the technical foundation and integrated emerging intravascular imaging techniques to enhance the characterization of vulnerable plaques. However, no current imaging technology is the unequivocal “gold standard” for the diagnosis of vulnerable atherosclerotic plaques. Each intravascular imaging technology possesses its own unique features that yield valuable information although encumbered by inherent limitations not seen in other modalities. In this context, the aim of this review is to discuss current scientific innovations, technical challenges, and prospective strategies in the development of IVUS-based multi-modality intravascular imaging systems aimed at assessing atherosclerotic plaque vulnerability. PMID:26400676

A Standardization Evaluation Potential Study of the Common Multi-Mode Radar Program.

DTIC Science & Technology

1979-11-01

Radar, the RX (RF-16 etc.), Enhanced Tactical Fighter ( ETF ), and A-7. Candidate radar systems applicable to the Common Multi-Mode Radar Program...RSTC R Resupply Time to Overseas Located Bases (hours) RSTO R Depot Stock Safety Factor (standard deviations) DLY R Shipping Time to Depot from CONUS

ITOHealth: a multimodal middleware-oriented integrated architecture for discovering medical entities.

PubMed

Alor-Hernández, Giner; Sánchez-Cervantes, José Luis; Juárez-Martínez, Ulises; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Aguilar-Laserre, Alberto

2012-03-01

Emergency healthcare is one of the emerging application domains for information services, which requires highly multimodal information services. The time of consuming pre-hospital emergency process is critical. Therefore, the minimization of required time for providing primary care and consultation to patients is one of the crucial factors when trying to improve the healthcare delivery in emergency situations. In this sense, dynamic location of medical entities is a complex process that needs time and it can be critical when a person requires medical attention. This work presents a multimodal location-based system for locating and assigning medical entities called ITOHealth. ITOHealth provides a multimodal middleware-oriented integrated architecture using a service-oriented architecture in order to provide information of medical entities in mobile devices and web browsers with enriched interfaces providing multimodality support. ITOHealth's multimodality is based on the use of Microsoft Agent Characters, the integration of natural language voice to the characters, and multi-language and multi-characters support providing an advantage for users with visual impairments.

Analysis and design of fiber-coupled high-power laser diode array

NASA Astrophysics Data System (ADS)

Zhou, Chongxi; Liu, Yinhui; Xie, Weimin; Du, Chunlei

2003-11-01

A conclusion that a single conventional optical system could not realize fiber coupled high-power laser diode array is drawn based on the BPP of laser beam. According to the parameters of coupled fiber, a method to couple LDA beams into a single multi-mode fiber including beams collimating, shaping, focusing and coupling is present. The divergence angles after collimating are calculated and analyzed; the shape equation of the collimating micro-lenses array is deprived. The focusing lens is designed. A fiber coupled LDA result with the core diameter of 800 um and numeric aperture of 0.37 is gotten.

Data fusion algorithm for rapid multi-mode dust concentration measurement system based on MEMS

NASA Astrophysics Data System (ADS)

Liao, Maohao; Lou, Wenzhong; Wang, Jinkui; Zhang, Yan

2018-03-01

As single measurement method cannot fully meet the technical requirements of dust concentration measurement, the multi-mode detection method is put forward, as well as the new requirements for data processing. This paper presents a new dust concentration measurement system which contains MEMS ultrasonic sensor and MEMS capacitance sensor, and presents a new data fusion algorithm for this multi-mode dust concentration measurement system. After analyzing the relation between the data of the composite measurement method, the data fusion algorithm based on Kalman filtering is established, which effectively improve the measurement accuracy, and ultimately forms a rapid data fusion model of dust concentration measurement. Test results show that the data fusion algorithm is able to realize the rapid and exact concentration detection.

[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

Graduate Student Perceptions of Multi-Modal Tablet Use in Academic Environments

ERIC Educational Resources Information Center

Bryant, Ezzard C., Jr.

2016-01-01

The purpose of this study was to explore graduate student perceptions of use and the ease of use of multi-modal tablets to access electronic course materials, and the perceived differences based on students' gender, age, college of enrollment, and previous experience. This study used the Unified Theory of Acceptance and Use of Technology to…

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

PubMed Central

Yin, Shouyi; Dai, Xu; Ouyang, Peng; Liu, Leibo; Wei, Shaojun

2014-01-01

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. PMID:25333290

Enhancing resource coordination for multi-modal evacuation planning.

DOT National Transportation Integrated Search

2013-01-01

This research project seeks to increase knowledge about coordinating effective multi-modal evacuation for disasters. It does so by identifying, evaluating, and assessing : current transportation management approaches for multi-modal evacuation planni...

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

A gantry-based tri-modality system for bioluminescence tomography

PubMed Central

Yan, Han; Lin, Yuting; Barber, William C.; Unlu, Mehmet Burcin; Gulsen, Gultekin

2012-01-01

A gantry-based tri-modality system that combines bioluminescence (BLT), diffuse optical (DOT), and x-ray computed tomography (XCT) into the same setting is presented here. The purpose of this system is to perform bioluminescence tomography using a multi-modality imaging approach. As parts of this hybrid system, XCT and DOT provide anatomical information and background optical property maps. This structural and functional a priori information is used to guide and restrain bioluminescence reconstruction algorithm and ultimately improve the BLT results. The performance of the combined system is evaluated using multi-modality phantoms. In particular, a cylindrical heterogeneous multi-modality phantom that contains regions with higher optical absorption and x-ray attenuation is constructed. We showed that a 1.5 mm diameter bioluminescence inclusion can be localized accurately with the functional a priori information while its source strength can be recovered more accurately using both structural and the functional a priori information. PMID:22559540

Study on multimodal transport route under low carbon background

NASA Astrophysics Data System (ADS)

Liu, Lele; Liu, Jie

2018-06-01

Low-carbon environmental protection is the focus of attention around the world, scientists are constantly researching on production of carbon emissions and living carbon emissions. However, there is little literature about multimodal transportation based on carbon emission at home and abroad. Firstly, this paper introduces the theory of multimodal transportation, the multimodal transport models that didn't consider carbon emissions and consider carbon emissions are analyzed. On this basis, a multi-objective programming 0-1 programming model with minimum total transportation cost and minimum total carbon emission is proposed. The idea of weight is applied to Ideal point method for solving problem, multi-objective programming is transformed into a single objective function. The optimal solution of carbon emission to transportation cost under different weights is determined by a single objective function with variable weights. Based on the model and algorithm, an example is given and the results are analyzed.

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

NASA Astrophysics Data System (ADS)

Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

2015-11-01

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

Enhanced optical fiber fluorometer using a periodic perturbation in the fiber core

NASA Astrophysics Data System (ADS)

Chiniforooshan, Yasser; Bock, Wojtek J.; Ma, Jianjun

2013-10-01

Tracing of the specific chemicals and biological agents in a solution is becoming a vital interest in health, security and safety industries. Although a number of standard laboratory-based testing systems exists for detecting such targets, but the fast, real-time and on-site methods could be more efficient and cost-effective. One of the most common ways to detect a target in the solution is to use the fluorophore molecules which will be selectively attached to the targets and will emit or quench the fluorescence in presence of the target. The fiber-optic fluorometers are developed for inexpensive and portable detection. In this paper, we explain a novel multi-segment fiber structure which uses the periodic perturbation on the side-wall of a highly multi-mode fiber to enhance collecting the fluorescent light. This periodic perturbation is fabricated and optimized on the core of the fiber using a CO2 laser. The theoretical explanation to show the physical principle of the structure is followed by the experimental evidence of its functioning.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

MOVEMENT AND MANEUVER IN DEEP SPACE: A Framework to Leverage Advanced Propulsion

DTIC Science & Technology

2018-04-01

Enterprise, and for this reason alone demands attention in the form of disciplined investment. Furthermore, because the core functional capability...technologies while collaborating with agencies and organizations external to the USAF. Section 2.2 discusses a theoretical organization formed and...engines, signature reduction, and thrust vectoring. AFRL is pursuing the attributes listed above in different forms , particularly via multi-mode

Multi-resonant electromagnetic shunt in base isolation for vibration damping and energy harvesting

NASA Astrophysics Data System (ADS)

Pei, Yalu; Liu, Yilun; Zuo, Lei

2018-06-01

This paper investigates multi-resonant electromagnetic shunts applied to base isolation for dual-function vibration damping and energy harvesting. Two multi-mode shunt circuit configurations, namely parallel and series, are proposed and optimized based on the H2 criteria. The root-mean-square (RMS) value of the relative displacement between the base and the primary structure is minimized. Practically, this will improve the safety of base-isolated buildings subjected the broad bandwidth ground acceleration. Case studies of a base-isolated building are conducted in both the frequency and time domains to investigate the effectiveness of multi-resonant electromagnetic shunts under recorded earthquake signals. It shows that both multi-mode shunt circuits outperform traditional single mode shunt circuits by suppressing the first and the second vibration modes simultaneously. Moreover, for the same stiffness ratio, the parallel shunt circuit is more effective at harvesting energy and suppressing vibration, and can more robustly handle parameter mistuning than the series shunt circuit. Furthermore, this paper discusses experimental validation of the effectiveness of multi-resonant electromagnetic shunts for vibration damping and energy harvesting on a scaled-down base isolation system.

Compact Hybrid Laser Rod and Laser System

NASA Technical Reports Server (NTRS)

Pierrottet, Diego F. (Inventor); Busch, George E. (Inventor); Amzajerdian, Farzin (Inventor)

2017-01-01

A hybrid fiber rod includes a fiber core and inner and outer cladding layers. The core is doped with an active element. The inner cladding layer surrounds the core, and has a refractive index substantially equal to that of the core. The outer cladding layer surrounds the inner cladding layer, and has a refractive index less than that of the core and inner cladding layer. The core length is about 30 to 2000 times the core diameter. A hybrid fiber rod laser system includes an oscillator laser, modulating device, the rod, and pump laser diode(s) energizing the rod from opposite ends. The rod acts as a waveguide for pump radiation but allows for free-space propagation of laser radiation. The rod may be used in a laser resonator. The core length is less than about twice the Rayleigh range. Degradation from single-mode to multi-mode beam propagation is thus avoided.

ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

NASA Astrophysics Data System (ADS)

Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

2018-02-01

Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

Multi-mode of Four and Six Wave Parametric Amplified Process

NASA Astrophysics Data System (ADS)

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-01

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Multi-mode of Four and Six Wave Parametric Amplified Process.

PubMed

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-03

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Single-Step Assembly of Multi-Modal Imaging Nanocarriers: MRI and Long-Wavelength Fluorescence Imaging

PubMed Central

Pinkerton, Nathalie M.; Gindy, Marian E.; Calero-DdelC, Victoria L.; Wolfson, Theodore; Pagels, Robert F.; Adler, Derek; Gao, Dayuan; Li, Shike; Wang, Ruobing; Zevon, Margot; Yao, Nan; Pacheco, Carlos; Therien, Michael J.; Rinaldi, Carlos; Sinko, Patrick J.

2015-01-01

MRI and NIR-active, multi-modal Composite NanoCarriers (CNCs) are prepared using a simple, one-step process, Flash NanoPrecipitation (FNP). The FNP process allows for the independent control of the hydrodynamic diameter, co-core excipient and NIR dye loading, and iron oxide-based nanocrystal (IONC) content of the CNCs. In the controlled precipitation process, 10 nm IONCs are encapsulated into poly(ethylene glycol) stabilized CNCs to make biocompatible T2 contrast agents. By adjusting the formulation, CNC size is tuned between 80 and 360 nm. Holding the CNC size constant at an intensity weighted average diameter of 99 ± 3 nm (PDI width 28 nm), the particle relaxivity varies linearly with encapsulated IONC content ranging from 66 to 533 mM-1s-1 for CNCs formulated with 4 to 16 wt% IONC. To demonstrate the use of CNCs as in vivo MRI contrast agents, CNCs are surface functionalized with liver targeting hydroxyl groups. The CNCs enable the detection of 0.8 mm3 non-small cell lung cancer metastases in mice livers via MRI. Incorporating the hydrophobic, NIR dye PZn3 into CNCs enables complementary visualization with long-wavelength fluorescence at 800 nm. In vivo imaging demonstrates the ability of CNCs to act both as MRI and fluorescent imaging agents. PMID:25925128

Drug-related webpages classification based on multi-modal local decision fusion

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Su, Xiaojing; Liu, Yanxin

2018-03-01

In this paper, multi-modal local decision fusion is used for drug-related webpages classification. First, meaningful text are extracted through HTML parsing, and effective images are chosen by the FOCARSS algorithm. Second, six SVM classifiers are trained for six kinds of drug-taking instruments, which are represented by PHOG. One SVM classifier is trained for the cannabis, which is represented by the mid-feature of BOW model. For each instance in a webpage, seven SVMs give seven labels for its image, and other seven labels are given by searching the names of drug-taking instruments and cannabis in its related text. Concatenating seven labels of image and seven labels of text, the representation of those instances in webpages are generated. Last, Multi-Instance Learning is used to classify those drugrelated webpages. Experimental results demonstrate that the classification accuracy of multi-instance learning with multi-modal local decision fusion is much higher than those of single-modal classification.

Wide range optofluidically tunable multimode interference fiber laser

NASA Astrophysics Data System (ADS)

Antonio-Lopez, J. E.; Sanchez-Mondragon, J. J.; LiKamWa, P.; May-Arrioja, D. A.

2014-08-01

An optofluidically tunable fiber laser based on multimode interference (MMI) effects with a wide tuning range is proposed and demonstrated. The tunable mechanism is based on an MMI fiber filter fabricated using a special fiber known as no-core fiber, which is a multimode fiber (MMF) without cladding. Therefore, when the MMI filter is covered by liquid the optical properties of the no-core fiber are modified, which allow us to tune the peak wavelength response of the MMI filter. Rather than applying the liquid on the entire no-core fiber, we change the liquid level along the no-core fiber, which provides a highly linear tuning response. In addition, by selecting the adequate refractive index of the liquid we can also choose the tuning range. We demonstrate the versatility of the optofluidically tunable MMI filter by wavelength tuning two different gain media, erbium doped fiber and a semiconductor optical amplifier, achieving tuning ranges of 55 and 90 nm respectively. In both cases, we achieve side-mode suppression ratios (SMSR) better than 50 dBm with output power variations of less than 0.76 dBm over the whole tuning range.

Influence of high power 405 nm multi-mode and single-mode diode laser light on the long-term stability of fused silica fibers

NASA Astrophysics Data System (ADS)

Gonschior, C. P.; Klein, K.-F.; Sun, T.; Grattan, K. T. V.

2012-04-01

As the demand for high power fiber-coupled violet laser systems increases existing problems remain. The typical power of commercially available diode lasers around 400 nm is in the order of 100 to 300 mW, depending on the type of laser. But in combination with the small core of single-mode fibers reduced spot sizes are needed for good coupling efficiencies, leading to power densities in the MW/cm2 range. We investigated the influence of 405 nm laser light irradiation on different fused silica fibers and differently treated end-faces. The effect of glued-and-polished, cleaved-and-clamped and of cleaved-and-fusion-arc-treated fiber end-faces on the damage rate and behavior are presented. In addition, effects in the deep ultra-violet were determined spectrally using newest spectrometer technology, allowing the measurement of color centers around 200 nm in small core fibers. Periodic surface structures were found on the proximal end-faces and were investigated concerning generation control parameters and composition. The used fiber types range from low-mode fiber to single-mode and polarization-maintaining fiber. For this investigation 405 nm single-mode or multi-mode diode lasers with 150 mW or 300 mW, respectively, were employed.

Multi-emitter laser multiplexer using a two-mirror beam shaper

NASA Astrophysics Data System (ADS)

Cobb, Joshua M.; Brennan, John; Bhatia, Vikram

2014-12-01

A system was designed and built to spatially multiplex four broad area laser diodes (BALD) and condense the light into a multi-mode fiber with a core diameter of 105 um and an NA of 0.15. The lasers were efficiently combined with an étendue aspect ratio scaler (EARS) optic. The EARS works under the principle of a two mirror beam shaper. We were able to successfully couple more than 87% of the optical energy into the fiber. The design of the optical system and the results of several built systems are discussed.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

NASA Astrophysics Data System (ADS)

Ismail, M. A.; Said, M. N.

2014-06-01

Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled time, directional maps produced to find the quickest, shortest paths, and closest facilities based on either time or distance impedance for multi-mode route analysis.

Upper Mantle Shear Wave Structure Beneath North America From Multi-mode Surface Wave Tomography

NASA Astrophysics Data System (ADS)

Yoshizawa, K.; Ekström, G.

2008-12-01

The upper mantle structure beneath the North American continent has been investigated from measurements of multi-mode phase speeds of Love and Rayleigh waves. To estimate fundamental-mode and higher-mode phase speeds of surface waves from a single seismogram at regional distances, we have employed a method of nonlinear waveform fitting based on a direct model-parameter search using the neighbourhood algorithm (Yoshizawa & Kennett, 2002). The method of the waveform analysis has been fully automated by employing empirical quantitative measures for evaluating the accuracy/reliability of estimated multi-mode phase dispersion curves, and thus it is helpful in processing the dramatically increasing numbers of seismic data from the latest regional networks such as USArray. As a first step toward modeling the regional anisotropic shear-wave velocity structure of the North American upper mantle with extended vertical resolution, we have applied the method to long-period three-component records of seismic stations in North America, which mostly comprise the GSN and US regional networks as well as the permanent and transportable USArray stations distributed by the IRIS DMC. Preliminary multi-mode phase-speed models show large-scale patterns of isotropic heterogeneity, such as a strong velocity contrast between the western and central/eastern United States, which are consistent with the recent global and regional models (e.g., Marone, et al. 2007; Nettles & Dziewonski, 2008). We will also discuss radial anisotropy of shear wave speed beneath North America from multi-mode dispersion measurements of Love and Rayleigh waves.

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

Broadband infrared light emitting waveguides based on UV curable PbS quantum dot composites

NASA Astrophysics Data System (ADS)

Shen, Kai; Baig, Sarfaraz; Jiang, Guomin; Paik, Young-hun; Kim, Sung Jin; Wang, Michael R.

2018-02-01

We present herein the active PbS-photopolymer waveguide fabricated by vacuum assisted microfluidic (VAM) soft lithography technique. The PbS Quantum Dots (QDs) were synthesized using colloidal chemistry methods with tunable sizes and emission wavelengths, resulting in efficient light emission around 1000 nm center wavelength. The PbS QDs have demonstrated much better solubility in our newly synthesized UV curable polymer than SU-8 photoresist, verified by Photoluminescence (PL) testing. Through refractive index control, the PbS QDs-polymer core material and polymer cladding material can efficiently confine the infrared emitting light with a broad spectral bandwidth of 180 nm. Both single-mode and multi-mode light emitting waveguides have been realized.

Viewpoints on Medical Image Processing: From Science to Application

PubMed Central

Deserno (né Lehmann), Thomas M.; Handels, Heinz; Maier-Hein (né Fritzsche), Klaus H.; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-01-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment. PMID:24078804

Viewpoints on Medical Image Processing: From Science to Application.

PubMed

Deserno Né Lehmann, Thomas M; Handels, Heinz; Maier-Hein Né Fritzsche, Klaus H; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-05-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.

Optical fiber curvature sensor based on MMF-SCF-MMF structure

NASA Astrophysics Data System (ADS)

Wang, Qi; Liu, Yu

2018-07-01

A sensitive curvature sensor based on MMF-SCF-MMF (MMF: multimode fiber; SCF: seven core fiber) structure is proposed. The multimode fiber (MMF) are used to improve the light coupling efficiency between the input singlemode fiber (SMF) and the seven-core fiber (SCF), and the seven-core fiber is used as the main element for curvature measurement. Experimental results show that the best curvature sensitivity reaches 41.46453 nm/m-1 in the range of 0.094 m-1-0.567 m-1. The temperature sensitivity is up to 59.02 pm/°C in the range of 20 °C-55 °C. The optical curvature sensors are widely used for buildings structure health monitoring and mechanical engineering due to the advantages of compact structure, anti-electromagnetic interference, and low cost.

Development of magneto-plasmonic nanoparticles for multimodal image-guided therapy to the brain.

PubMed

Tomitaka, Asahi; Arami, Hamed; Raymond, Andrea; Yndart, Adriana; Kaushik, Ajeet; Jayant, Rahul Dev; Takemura, Yasushi; Cai, Yong; Toborek, Michal; Nair, Madhavan

2017-01-05

Magneto-plasmonic nanoparticles are one of the emerging multi-functional materials in the field of nanomedicine. Their potential for targeting and multi-modal imaging is highly attractive. In this study, magnetic core/gold shell (MNP@Au) magneto-plasmonic nanoparticles were synthesized by citrate reduction of Au ions on magnetic nanoparticle seeds. Hydrodynamic size and optical properties of magneto-plasmonic nanoparticles synthesized with the variation of Au ions and reducing agent concentrations were evaluated. The synthesized magneto-plasmonic nanoparticles exhibited superparamagnetic properties, and their magnetic properties contributed to the concentration-dependent contrast in magnetic resonance imaging (MRI). The imaging contrast from the gold shell part of the magneto-plasmonic nanoparticles was also confirmed by X-ray computed tomography (CT). The transmigration study of the magneto-plasmonic nanoparticles using an in vitro blood-brain barrier (BBB) model proved enhanced transmigration efficiency without disrupting the integrity of the BBB, and showed potential to be used for brain diseases and neurological disorders.

Contemporary Multi-Modal Historical Representations and the Teaching of Disciplinary Understandings in History

ERIC Educational Resources Information Center

Donnelly, Debra J.

2018-01-01

Traditional privileging of the printed text has been considerably eroded by rapid technological advancement and in Australia, as elsewhere, many History teaching programs feature an array of multi-modal historical representations. Research suggests that engagement with the visual and multi-modal constructs has the potential to enrich the pedagogy…

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Developing a multimodal biometric authentication system using soft computing methods.

PubMed

Malcangi, Mario

2015-01-01

Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

Multi-Gigabit Fiber Optic Wide Area Network Development.

DTIC Science & Technology

1991-07-01

to propagate, no modal dispersion can occur. In multimode fiber , a parabolic index profile across the core is often used so that mode travel times are...In the fiber plant, such as connectors, splices couplers, splitters, switches, tunable filters , wavelength division multiplexers and demultiplexers...losses are much higher, at around 0.5 dB, and are usually avoided in long-haul systems. 30 Some fiber plant components have a filtering effect on the

Use of Multi-Modal Media and Tools in an Online Information Literacy Course: College Students' Attitudes and Perceptions

ERIC Educational Resources Information Center

Chen, Hsin-Liang; Williams, James Patrick

2009-01-01

This project studies the use of multi-modal media objects in an online information literacy class. One hundred sixty-two undergraduate students answered seven surveys. Significant relationships are found among computer skills, teaching materials, communication tools and learning experience. Multi-modal media objects and communication tools are…

Research on high-temperature sensing characteristics based on modular interference of single-mode multimode single-mode fiber

NASA Astrophysics Data System (ADS)

Peng, Zhaozhuang; Wang, Li; Yan, Huanhuan

2016-11-01

Application of high temperature fiber sensing system is very extensive. It can be mainly used in high temperature test aerospace, such as, materials, chemicals, and energy. In recent years, various on-line optical fiber interferometric sensors based on modular interference of single-mode-multimode-single-mode(SMS) fiber have been largely explored in high temperature fiber sensor. In this paper we use the special fiber of a polyimide coating, its sensor head is composed of a section of multimode fiber spliced in the middle of Single-mode fiber. When the light is launched into the multimode fiber(MMF) through the lead-in single-mode fiber(SMF), the core mode and cladding modes are excited and propagate in the MMF respectively. Then, at the MMF-SMF spliced point, the excited cladding modes coupled back into the core of lead-out SMF interfere with SMF core mode. And the wavelength of the interference dip would shift differently with the variation of the temperature. By this mean, we can achieve the measurement of temperature. The experimental results also show that the fiber sensor based on SMS structure has a highly temperature sensitivity. From 30° to 300°, with the temperature increasing, the interference dip slightly shifts toward longer wavelength and the temperature sensitivity coefficient is 0.0115nm/°. With high sensitivity, simple structure, immunity to electromagnetic interferences and a good linearity of the experimental results, the structure has an excellent application prospect in engineering field.

Multi-modal Patient Cohort Identification from EEG Report and Signal Data

PubMed Central

Goodwin, Travis R.; Harabagiu, Sanda M.

2016-01-01

Clinical electroencephalography (EEG) is the most important investigation in the diagnosis and management of epilepsies. An EEG records the electrical activity along the scalp and measures spontaneous electrical activity of the brain. Because the EEG signal is complex, its interpretation is known to produce moderate inter-observer agreement among neurologists. This problem can be addressed by providing clinical experts with the ability to automatically retrieve similar EEG signals and EEG reports through a patient cohort retrieval system operating on a vast archive of EEG data. In this paper, we present a multi-modal EEG patient cohort retrieval system called MERCuRY which leverages the heterogeneous nature of EEG data by processing both the clinical narratives from EEG reports as well as the raw electrode potentials derived from the recorded EEG signal data. At the core of MERCuRY is a novel multimodal clinical indexing scheme which relies on EEG data representations obtained through deep learning. The index is used by two clinical relevance models that we have generated for identifying patient cohorts satisfying the inclusion and exclusion criteria expressed in natural language queries. Evaluations of the MERCuRY system measured the relevance of the patient cohorts, obtaining MAP scores of 69.87% and a NDCG of 83.21%. PMID:28269938

Model-Driven Useware Engineering

NASA Astrophysics Data System (ADS)

Meixner, Gerrit; Seissler, Marc; Breiner, Kai

User-oriented hardware and software development relies on a systematic development process based on a comprehensive analysis focusing on the users' requirements and preferences. Such a development process calls for the integration of numerous disciplines, from psychology and ergonomics to computer sciences and mechanical engineering. Hence, a correspondingly interdisciplinary team must be equipped with suitable software tools to allow it to handle the complexity of a multimodal and multi-device user interface development approach. An abstract, model-based development approach seems to be adequate for handling this complexity. This approach comprises different levels of abstraction requiring adequate tool support. Thus, in this chapter, we present the current state of our model-based software tool chain. We introduce the use model as the core model of our model-based process, transformation processes, and a model-based architecture, and we present different software tools that provide support for creating and maintaining the models or performing the necessary model transformations.

Multi-Modality Phantom Development

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

Huber, Jennifer S.; Peng, Qiyu; Moses, William W.

2009-03-20

Multi-modality imaging has an increasing role in the diagnosis and treatment of a large number of diseases, particularly if both functional and anatomical information are acquired and accurately co-registered. Hence, there is a resulting need for multi modality phantoms in order to validate image co-registration and calibrate the imaging systems. We present our PET-ultrasound phantom development, including PET and ultrasound images of a simple prostate phantom. We use agar and gelatin mixed with a radioactive solution. We also present our development of custom multi-modality phantoms that are compatible with PET, transrectal ultrasound (TRUS), MRI and CT imaging. We describe bothmore » our selection of tissue mimicking materials and phantom construction procedures. These custom PET-TRUS-CT-MRI prostate phantoms use agargelatin radioactive mixtures with additional contrast agents and preservatives. We show multi-modality images of these custom prostate phantoms, as well as discuss phantom construction alternatives. Although we are currently focused on prostate imaging, this phantom development is applicable to many multi-modality imaging applications.« less

Theory and simulation of multi-channel interference (MCI) widely tunable lasers.

PubMed

Chen, Quanan; Lu, Qiaoyin; Guo, Weihua

2015-07-13

A novel design of an InP-based monolithic widely tunable laser, multi-channel interference (MCI) laser, is proposed and presented for the first time. The device is comprised of a gain section, a common phase section and a multi-channel interference section. The multi-channel interference section contains a 1x8 splitter based on cascaded 1 × 2 multi-mode interferometers (MMIs) and eight arms with unequal length difference. The rear part of each arm is integrated with a one-port multi-mode interference reflector (MIR). Mode selection of the MCI laser is realized by the constructive interference of the lights reflected back by the eight arms. Through optimizing the arm length difference, a tuning range of more than 40 nm covering the whole C band, a threshold current around 11.5 mA and an side-mode-suppression-ratio (SMSR) up to 48 dB have been predicted for this widely tunable laser. Detailed design principle and numerical simulation results are presented.

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

PubMed Central

Kampmann, Peter; Kirchner, Frank

2014-01-01

With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach. PMID:24743158

Complete measurement of spatiotemporally complex multi-spatial-mode ultrashort pulses from multimode optical fibers using delay-scanned wavelength-multiplexed holography.

PubMed

Zhu, Ping; Jafari, Rana; Jones, Travis; Trebino, Rick

2017-10-02

We introduce a simple delay-scanned complete spatiotemporal intensity-and-phase measurement technique based on wavelength-multiplexed holography to characterize long, complex pulses in space and time. We demonstrate it using pulses emerging from multi-mode fiber. This technique extends the temporal range and spectral resolution of the single-frame STRIPED FISH technique without using an otherwise-required expensive ultranarrow-bandpass filter. With this technique, we measured the complete intensity and phase of up to ten fiber modes from a multi-mode fiber (normalized frequency V ≈10) over a ~3ps time range. Spatiotemporal complexities such as intermodal delay, modal dispersion, and material dispersion were also intuitively displayed by the retrieved results. Agreement between the reconstructed color movies and the monitored time-averaged spatial profiles confirms the validity to this delay-scanned STRIPED FISH method.

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

PubMed

Soltaninejad, Mohammadreza; Yang, Guang; Lambrou, Tryphon; Allinson, Nigel; Jones, Timothy L; Barrick, Thomas R; Howe, Franklyn A; Ye, Xujiong

2018-04-01

Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. Copyright © 2018 Elsevier B.V. All rights reserved.

Nanoparticle imaging probes for molecular imaging with computed tomography and application to cancer imaging

NASA Astrophysics Data System (ADS)

Roeder, Ryan K.; Curtis, Tyler E.; Nallathamby, Prakash D.; Irimata, Lisa E.; McGinnity, Tracie L.; Cole, Lisa E.; Vargo-Gogola, Tracy; Cowden Dahl, Karen D.

2017-03-01

Precision imaging is needed to realize precision medicine in cancer detection and treatment. Molecular imaging offers the ability to target and identify tumors, associated abnormalities, and specific cell populations with overexpressed receptors. Nuclear imaging and radionuclide probes provide high sensitivity but subject the patient to a high radiation dose and provide limited spatiotemporal information, requiring combined computed tomography (CT) for anatomic imaging. Therefore, nanoparticle contrast agents have been designed to enable molecular imaging and improve detection in CT alone. Core-shell nanoparticles provide a powerful platform for designing tailored imaging probes. The composition of the core is chosen for enabling strong X-ray contrast, multi-agent imaging with photon-counting spectral CT, and multimodal imaging. A silica shell is used for protective, biocompatible encapsulation of the core composition, volume-loading fluorophores or radionuclides for multimodal imaging, and facile surface functionalization with antibodies or small molecules for targeted delivery. Multi-agent (k-edge) imaging and quantitative molecular imaging with spectral CT was demonstrated using current clinical agents (iodine and BaSO4) and a proposed spectral library of contrast agents (Gd2O3, HfO2, and Au). Bisphosphonate-functionalized Au nanoparticles were demonstrated to enhance sensitivity and specificity for the detection of breast microcalcifications by conventional radiography and CT in both normal and dense mammary tissue using murine models. Moreover, photon-counting spectral CT enabled quantitative material decomposition of the Au and calcium signals. Immunoconjugated Au@SiO2 nanoparticles enabled highly-specific targeting of CD133+ ovarian cancer stem cells for contrast-enhanced detection in model tumors.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Interference of Multi-Mode Gaussian States and "non Appearance" of Quantum Correlations

NASA Astrophysics Data System (ADS)

Olivares, Stefano

2012-01-01

We theoretically investigate bilinear, mode-mixing interactions involving two modes of uncorrelated multi-mode Gaussian states. In particular, we introduce the notion of "locally the same states" (LSS) and prove that two uncorrelated LSS modes are invariant under the mode mixing, i.e. the interaction does not lead to the birth of correlations between the outgoing modes. We also study the interference of orthogonally polarized Gaussian states by means of an interferometric scheme based on a beam splitter, rotators of polarization and polarization filters.

Composition at Washington State University: Building a Multimodal Bricolage

ERIC Educational Resources Information Center

Ericsson, Patricia; Hunter, Leeann Downing; Macklin, Tialitha Michelle; Edwards, Elizabeth Sue

2016-01-01

Multimodal pedagogy is increasingly accepted among composition scholars. However, putting such pedagogy into practice presents significant challenges. In this profile of Washington State University's first-year composition program, we suggest a multi-vocal and multi-theoretical approach to addressing the challenges of multimodal pedagogy. Patricia…

Sensei: A Multi-Modal Framework for Assessing Stress Resiliency

DTIC Science & Technology

2013-04-30

DATE MAY2013 2. REPORT TYPE 4. TITLE AND SUBTITLE Sensei: A Multi-Modal Framework for Assessing Stress Resiliency 6. AUTHOR(S) 7. PERFORMING...Report: Distribution A Page 1 of 3 SRI International (Sarnoff) Document Sensei: A Multi-Modal Framework for Assessing Stress Resiliency (April... Stress Markers in Real-Time in Lab Environment with graded exposure to ICT’s scenarios MAC 1-6 During this reporting period, we established

Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration

PubMed Central

Blinowska, Katarzyna; Müller-Putz, Gernot; Kaiser, Vera; Astolfi, Laura; Vanderperren, Katrien; Van Huffel, Sabine; Lemieux, Louis

2009-01-01

Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship. PMID:19547657

Xi-cam: a versatile interface for data visualization and analysis

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

Pandolfi, Ronald J.; Allan, Daniel B.; Arenholz, Elke

Xi-cam is an extensible platform for data management, analysis and visualization.Xi-camaims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core ofXi-camis an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. WithXi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data.Xi-cam's plugin-based architecture targetsmore » cross-facility and cross-technique collaborative development, in support of multi-modal analysis.Xi-camis open-source and cross-platform, and available for download on GitHub.« less

Xi-cam: a versatile interface for data visualization and analysis

DOE PAGES

Pandolfi, Ronald J.; Allan, Daniel B.; Arenholz, Elke; ...

2018-05-31

Xi-cam is an extensible platform for data management, analysis and visualization.Xi-camaims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core ofXi-camis an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. WithXi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data.Xi-cam's plugin-based architecture targetsmore » cross-facility and cross-technique collaborative development, in support of multi-modal analysis.Xi-camis open-source and cross-platform, and available for download on GitHub.« less

The evolution of gadolinium based contrast agents: from single-modality to multi-modality

NASA Astrophysics Data System (ADS)

Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K.

2016-05-01

Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

A Multi-Modal Digital Game-Based Learning Environment for Hospitalized Children with Chronic Illnesses.

ERIC Educational Resources Information Center

Chin, Jui-Chih; Tsuei, Mengping

2014-01-01

The aim of this study was to explore the digital game-based learning for children with chronic illnesses in the hospital settings. The design-based research and qualitative methods were applied. Three eight-year-old children with leukemia participated in this study. In the first phase, the multi-user game-based learning system was developed and…

A graph-based approach for the retrieval of multi-modality medical images.

PubMed

Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

2014-02-01

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects. Copyright © 2013 Elsevier B.V. All rights reserved.

Multimode optical fiber

DOEpatents

Bigot-Astruc, Marianne; Molin, Denis; Sillard, Pierre

2014-11-04

A depressed graded-index multimode optical fiber includes a central core, an inner depressed cladding, a depressed trench, an outer depressed cladding, and an outer cladding. The central core has an alpha-index profile. The depressed claddings limit the impact of leaky modes on optical-fiber performance characteristics (e.g., bandwidth, core size, and/or numerical aperture).

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Medical image registration based on normalized multidimensional mutual information

NASA Astrophysics Data System (ADS)

Li, Qi; Ji, Hongbing; Tong, Ming

2009-10-01

Registration of medical images is an essential research topic in medical image processing and applications, and especially a preliminary and key step for multimodality image fusion. This paper offers a solution to medical image registration based on normalized multi-dimensional mutual information. Firstly, affine transformation with translational and rotational parameters is applied to the floating image. Then ordinal features are extracted by ordinal filters with different orientations to represent spatial information in medical images. Integrating ordinal features with pixel intensities, the normalized multi-dimensional mutual information is defined as similarity criterion to register multimodality images. Finally the immune algorithm is used to search registration parameters. The experimental results demonstrate the effectiveness of the proposed registration scheme.

A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring.

PubMed

Pantelopoulos, Alexandros; Saldivar, Enrique; Roham, Masoud

2011-01-01

In this paper a wireless modular, multi-modal, multi-node patch platform is described. The platform comprises low-cost semi-disposable patch design aiming at unobtrusive ambulatory monitoring of multiple physiological parameters. Owing to its modular design it can be interfaced with various low-power RF communication and data storage technologies, while the data fusion of multi-modal and multi-node features facilitates measurement of several biosignals from multiple on-body locations for robust feature extraction. Preliminary results of the patch platform are presented which illustrate the capability to extract respiration rate from three different independent metrics, which combined together can give a more robust estimate of the actual respiratory rate.

Failure Analysis of a Complex Learning Framework Incorporating Multi-Modal and Semi-Supervised Learning

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

Pullum, Laura L; Symons, Christopher T

2011-01-01

Machine learning is used in many applications, from machine vision to speech recognition to decision support systems, and is used to test applications. However, though much has been done to evaluate the performance of machine learning algorithms, little has been done to verify the algorithms or examine their failure modes. Moreover, complex learning frameworks often require stepping beyond black box evaluation to distinguish between errors based on natural limits on learning and errors that arise from mistakes in implementation. We present a conceptual architecture, failure model and taxonomy, and failure modes and effects analysis (FMEA) of a semi-supervised, multi-modal learningmore » system, and provide specific examples from its use in a radiological analysis assistant system. The goal of the research described in this paper is to provide a foundation from which dependability analysis of systems using semi-supervised, multi-modal learning can be conducted. The methods presented provide a first step towards that overall goal.« less

Preface to the special issue on ;Optical Communications Exploiting the Space Domain;

NASA Astrophysics Data System (ADS)

Wang, Jian; Yu, Siyuan; Li, Guifang

2018-02-01

The demand for high capacity optical communications will continue to be driven by the exponential growth of global internet traffic. Optical communications are about the exploitation of different physical dimensions of light waves, including complex amplitude, frequency (or wavelength), time, polarization, etc. Conventional techniques such as wavelength-division multiplexing (WDM), time-division multiplexing (TDM) and polarization-division multiplexing (PDM) have almost reached their scalability limits. Space domain is the only known physical dimension left and space-division multiplexing (SDM) seems the only option to further scale the transmission capacity and spectral efficiency of optical communications. In recent years, few-mode fiber (FMF), multi-mode fiber (MMF), multi-core fiber (MCF) and few-mode multi-core fiber (FM-MCF) have been widely explored as promising candidates for fiber-based SDM. The challenges for SDM include efficient (de)multiplexer, amplifiers, and multiple-input multiple-output (MIMO) digital signal processing (DSP) techniques. Photonic integration will also be a key technology to SDM. Meanwhile, free-space and underwater optical communications have also exploited the space domain to increase the transmission capacity and spectral efficiency. The challenges include long-distance transmission limited by propagation loss, divergence, scattering and turbulence. Very recently, helically phased light beams carrying orbital angular momentum (OAM) have also seen potential applications both in free-space, underwater and fiber-based optical communications. Actually, different mode bases such as linearly polarized (LP) modes and OAM modes can be employed for SDM. Additionally, SDM could be used in chip-scale photonic interconnects and data center optical interconnects. Quantum processing exploiting the space domain is of great interest. The information capacity limit and physical layer security in SDM optical communications systems are important issues to be addressed.

Passively stabilized 215-W monolithic CW LMA-fiber laser with innovative transversal mode filter

NASA Astrophysics Data System (ADS)

Stutzki, Fabian; Jauregui, Cesar; Voigtländer, Christian; Thomas, Jens U.; Limpert, Jens; Nolte, Stefan; Tünnermann, Andreas

2010-02-01

We report on the development of a high power monolithic CW fiber oscillator with an output power of 215 W in a 20μm core diameter few-mode Large Mode Area fiber (LMA). The key parameters for stable operation are reviewed. With these optimizations the root mean square of the output power fluctuations can be reduced to less than 0.5 % on a timescale of 20 s, which represents an improvement of more than a factor 5 over a non-optimized fiber laser. With a real-time measurement of the mode content of the fiber laser it can be shown that the few-mode nature of LMA fibers is the main factor for the residual instability of our optimized fiber laser. The root of the problem is that Fiber Bragg Gratings (FBGs) written in multimode fibers exhibit a multi-peak reflexion spectrum in which each resonance corresponds to a different transversal mode. This reflectivity spectrum stimulates multimode laser operation, which results in power and pointing instabilities due to gain competition between the different transversal modes . To stabilize the temporal and spatial behavior of the laser output, we propose an innovative passive in-fiber transversal mode filter based on modified FBG-Fabry Perot structure. This structure provides different reflectivities to the different transversal modes according to the transversal distribution of their intensity profile. Furthermore, this structure can be completely written into the active fiber using fs-laser pulses. Moreover, this concept scales very well with the fiber core diameter, which implies that there is no performance loss in fibers with even larger cores. In consequence this structure is inherently power scalable and can, therefore, be used in kW-level fiber laser systems.

A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

PubMed

Zhang, Qinjin; Liu, Yancheng; Zhao, Youtao; Wang, Ning

2016-03-01

Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Big data sharing and analysis to advance research in post-traumatic epilepsy.

PubMed

Duncan, Dominique; Vespa, Paul; Pitkanen, Asla; Braimah, Adebayo; Lapinlampi, Nina; Toga, Arthur W

2018-06-01

We describe the infrastructure and functionality for a centralized preclinical and clinical data repository and analytic platform to support importing heterogeneous multi-modal data, automatically and manually linking data across modalities and sites, and searching content. We have developed and applied innovative image and electrophysiology processing methods to identify candidate biomarkers from MRI, EEG, and multi-modal data. Based on heterogeneous biomarkers, we present novel analytic tools designed to study epileptogenesis in animal model and human with the goal of tracking the probability of developing epilepsy over time. Copyright © 2017. Published by Elsevier Inc.

Optical characterisation and analysis of multi-mode pixels for use in future far infrared telescopes

NASA Astrophysics Data System (ADS)

McCarthy, Darragh; Trappe, Neil; Murphy, J. Anthony; Doherty, Stephen; Gradziel, Marcin; O'Sullivan, Créidhe; Audley, Michael D.; de Lange, Gert; van der Vorst, Maarten

2016-07-01

In this paper we present the development and verification of feed horn simulation code based on the mode- matching technique to simulate the electromagnetic performance of waveguide based structures of rectangular cross-section. This code is required to model multi-mode pyramidal horns which may be required for future far infrared (far IR) space missions where wavelengths in the range of 30 to 200 µm will be analysed. Multi-mode pyramidal horns can be used effectively to couple radiation to sensitive superconducting devices like Kinetic Inductance Detectors (KIDs) or Transition Edge Sensor (TES) detectors. These detectors could be placed in integrating cavities (to further increase the efficiency) with an absorbing layer used to couple to the radiation. The developed code is capable of modelling each of these elements, and so will allow full optical characterisation of such pixels and allow an optical efficiency to be calculated effectively. As the signals being measured at these short wavelengths are at an extremely low level, the throughput of the system must be maximised and so multi-mode systems are proposed. To this end, the focal planes of future far IR missions may consist of an array of multi-mode rectangular feed horns feeding an array of, for example, TES devices contained in individual integrating cavities. Such TES arrays have been fabricated by SRON Groningen and are currently undergoing comprehensive optical, electrical and thermal verification. In order to fully understand and validate the optical performance of the receiver system, it is necessary to develop comprehensive and robust optical models in parallel. We outline the development and verification of this optical modelling software by means of applying it to a representative multi-mode system operating at 150 GHz in order to obtain sufficiently short execution times so as to comprehensively test the code. SAFARI (SPICA FAR infrared Instrument) is a far infrared imaging grating spectrometer, to be proposed as an ESA M5 mission. It is planned for this mission to be launched on board the proposed SPICA (SPace Infrared telescope for Cosmology and Astrophysics) mission, in collaboration with JAXA. SAFARI is planned to operate in the 1.5-10 THz band, focussing on the formation and evolution of galaxies, stars and planetary systems. The pixel that drove the development of the techniques presented in this paper is typical of one option that could be implemented in the SAFARI focal plane, and so the ability to accurately understand and characterise such pixels is critical in the design phase of the next generation of far IR telescopes.

Fiber comb filters based on UV-writing Bragg gratings in graded-index multimode fibers

NASA Astrophysics Data System (ADS)

Liu, Yu; Lit, John; Gu, Xijia; Wei, Li

2005-10-01

We report a new kind of comb filters based on fiber Bragg gratings in graded-index multimode fibers. It produces two groups of spectra with a total of 36 reflection peaks that correspond to 18 principal modes and cross coupled modes. The mode indices and wavelength spacings have been investigated theoretically and experimentally. This kind of comb filters may be used to construct multi-wavelength light sources for sensing, optical communications, and instrumentations

Measurements of gas temperatures at 100 kHz within the annulus of a rotating detonation engine

NASA Astrophysics Data System (ADS)

Rein, Keith D.; Roy, Sukesh; Sanders, Scott T.; Caswell, Andrew W.; Schauer, Frederick R.; Gord, James R.

2017-03-01

Cycle-resolved measurements of H2O temperatures and number densities taken within the detonation channel of a hydrogen—air rotating detonation engine (RDE) at a 100 kHz repetition rate using laser absorption spectroscopy are presented. The laser source used is an MEMS-tunable Vertical-Cavity Surface Emitting laser which scans from 1330 to 1360 nm. Optical access into and out of the RDE is achieved using a dual-core fiber optic. Light is pitched into the RDE through a sapphire window via a single-mode core, retroreflected off the mirror-polished inner radius of the RDE annulus, and collected with the multi-mode fiber core. The resulting absorption spectra are used to determine gas temperatures as a function of time. These measurements allow characterization of the transient-temperature response of the RDE.

Experimental and numerical study on refractive index sensors based on fibre Bragg gratings inscribed in multimode fibre

NASA Astrophysics Data System (ADS)

Filipe Kuhne, Jean; Rocha, Ana Maria; de Oliveira, Valmir; José Kalinowski, Hypolito; Canute Kamikawachi, Ricardo

2018-02-01

In this work is reported the experimental and numerical results of the refractive index response of etched fibre Bragg gratings written in a graded index multimode fibre. The responses of the modes coupled by the grating inscribed in a multimode fibre are compared with the mode coupled by a grating inscribed in single mode fibre. The results of this study show that the refractive index sensitivity and the dynamical range of etched fibre Bragg gratings written in multimode fibres are higher than the ones verified in single-mode fibres. The determination of oil-biodiesel blend concentrations are also compared as an example of practical applications. It is shown that a greater core diameter of the multimode fibre enables the Bragg gratings to exhibit enhanced sensitivity without requiring further fibre diameter reduction.

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

PubMed

Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

2015-10-01

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley & Sons, Ltd.

A multi-mode manipulator display system for controlling remote robotic systems

NASA Technical Reports Server (NTRS)

Massimino, Michael J.; Meschler, Michael F.; Rodriguez, Alberto A.

1994-01-01

The objective and contribution of the research presented in this paper is to provide a Multi-Mode Manipulator Display System (MMDS) to assist a human operator with the control of remote manipulator systems. Such systems include space based manipulators such as the space shuttle remote manipulator system (SRMS) and future ground controlled teleoperated and telescience space systems. The MMDS contains a number of display modes and submodes which display position control cues position data in graphical formats, based primarily on manipulator position and joint angle data. Therefore the MMDS is not dependent on visual information for input and can assist the operator especially when visual feedback is inadequate. This paper provides descriptions of the new modes and experiment results to date.

Multi-Sensory, Multi-Modal Concepts for Information Understanding

DTIC Science & Technology

2004-04-01

September 20022-2 Outline • The modern dilemma of knowledge acquisition • A vision for information access and understanding • Emerging concepts for...Multi-Sensory, Multi-Modal Concepts for Information Understanding David L. Hall, Ph.D. School of Information Sciences and Technology The... understanding . INTRODUCTION Historically, information displays for display and understanding of data fusion products have focused on the use of vision

Outlook for grid service technologies within the @neurIST eHealth environment.

PubMed

Arbona, A; Benkner, S; Fingberg, J; Frangi, A F; Hofmann, M; Hose, D R; Lonsdale, G; Ruefenacht, D; Viceconti, M

2006-01-01

The aim of the @neurIST project is to create an IT infrastructure for the management of all processes linked to research, diagnosis and treatment development for complex and multi-factorial diseases. The IT infrastructure will be developed for one such disease, cerebral aneurysm and subarachnoid haemorrhage, but its core technologies will be transferable to meet the needs of other medical areas. Since the IT infrastructure for @neurIST will need to encompass data repositories, computational analysis services and information systems handling multi-scale, multi-modal information at distributed sites, the natural basis for the IT infrastructure is a Grid Service middleware. The project will adopt a service-oriented architecture because it aims to provide a system addressing the needs of medical researchers, clinicians and health care specialists (and their IT providers/systems) and medical supplier/consulting industries.

A nonlinear multi-mode wideband piezoelectric vibration-based energy harvester using compliant orthoplanar spring

NASA Astrophysics Data System (ADS)

Dhote, Sharvari; Zu, Jean; Zhu, Yang

2015-04-01

In this paper, a nonlinear wideband multi-mode piezoelectric vibration-based energy harvester (PVEH) is proposed based on a compliant orthoplanar spring (COPS), which has an advantage of providing multiple vibration modes at relatively low frequencies. The PVEH is made of a tri-leg COPS flexible structure, where three fixed-guided beams are capable of generating strong nonlinear oscillations under certain base excitation. A prototype harvester was fabricated and investigated through both finite-element analysis and experiments. The frequency response shows multiple resonance which corresponds to a hardening type of nonlinear resonance. By adding masses at different locations on the COPS structure, the first three vibration modes are brought close to each other, where the three hardening nonlinear resonances provide a wide bandwidth for the PVEH. The proposed PVEH has enhanced performance of the energy harvester in terms of a wide frequency bandwidth and a high-voltage output under base excitations.

Multi-modal trip planning system : Northeastern Illinois Regional Transportation Authority.

DOT National Transportation Integrated Search

2013-01-01

This report evaluates the Multi-Modal Trip Planner System (MMTPS) implemented by the Northeastern Illinois Regional Transportation Authority (RTA) against the specific functional objectives enumerated by the Federal Transit Administration (FTA) in it...

A passively mode locked thulium doped fiber laser using bismuth telluride deposited multimode interference

NASA Astrophysics Data System (ADS)

Jung, M.; Lee, J.; Song, W.; Lee, Y. L.; Lee, J. H.; Shin, W.

2016-05-01

We proposed a multimode interference (MMI) fiber based saturable absorber using bismuth telluride at  ∼2 μm region. Our MMI based saturable absorber was fabricated by fusion splicing with single mode fiber and null core fiber. The MMI functioned as both wavelength fixed filter and saturable absorber. The 3 dB bandwidth and insertion loss of MMI were 42 nm and 3.4 dB at wavelength of 1958 nm, respectively. We have also reported a passively mode locked thulium doped fiber laser operating at a wavelength of 1958 nm using a multimode interference. A temporal bandwidth of  ∼46 ps was experimentally obtained at a repetition rate of 8.58 MHz.

Fiber up-tapering and down-tapering for low-loss coupling between anti-resonant hollow-core fiber and solid-core fiber

NASA Astrophysics Data System (ADS)

Zhang, Naiqian; Wang, Zefeng; Xi, Xiaoming

2017-10-01

In this paper, we demonstrate a novel method for the low-loss coupling between solid-core multi-mode fibers (MMFs) and anti-resonant hollow-core fibers (AR-HCFs). The core/cladding diameter of the MMF is 50/125μm and the mode field diameter of the AR-HCFs are 33.3μm and 71.2μm of the ice-cream type AR-HCFs and the non-node type ARHCFs, respectively. In order to match the mode field diameters of these two specific AR-HCFs, the mode field diameter of the MMFs is increased or decreased by up-tapering or down-tapering the MMFs. Then, according to the principle of coupled fiber mode matching, the optimal diameter of tapered fiber for low-loss coupling is calculated. Based on beam propagation method, the calculated coupling losses without tapering process are 0.31dB and 0.89dB, respectively for a MMF-HCF-MMF structure of the ice-cream type AR-HCFs and the non-node type AR-HCFs. These values can be reduced to 0.096dB and 0.047dB when the outer diameters of the MMF are down-tapered to 116μm and up-tapered to 269μm, respectively. What's more, these results can also be verified by existing experiments.

Hand hygiene and healthcare system change within multi-modal promotion: a narrative review.

PubMed

Allegranzi, B; Sax, H; Pittet, D

2013-02-01

Many factors may influence the level of compliance with hand hygiene recommendations by healthcare workers. Lack of products and facilities as well as their inappropriate and non-ergonomic location represent important barriers. Targeted actions aimed at making hand hygiene practices feasible during healthcare delivery by ensuring that the necessary infrastructure is in place, defined as 'system change', are essential to improve hand hygiene in healthcare. In particular, access to alcohol-based hand rubs (AHRs) enables appropriate and timely hand hygiene performance at the point of care. The feasibility and impact of system change within multi-modal strategies have been demonstrated both at institutional level and on a large scale. The introduction of AHRs overcomes some important barriers to best hand hygiene practices and is associated with higher compliance, especially when integrated within multi-modal strategies. Several studies demonstrated the association between AHR consumption and reduction in healthcare-associated infection, in particular, meticillin-resistant Staphylococcus aureus bacteraemia. Recent reports demonstrate the feasibility and success of system change implementation on a large scale. The World Health Organization and other investigators have reported the challenges and encouraging results of implementing hand hygiene improvement strategies, including AHR introduction, in settings with limited resources. This review summarizes the available evidence demonstrating the need for system change and its importance within multi-modal hand hygiene improvement strategies. This topic is also discussed in a global perspective and highlights some controversial issues. Copyright © 2013 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Method of multi-mode vibration control for the carbody of high-speed electric multiple unit trains

NASA Astrophysics Data System (ADS)

Gong, Dao; Zhou, Jinsong; Sun, Wenjing; Sun, Yu; Xia, Zhanghui

2017-11-01

A method of multi-mode vibration control for the carbody of high-speed electric multiple unit (EMU) trains by using the onboard and suspended equipments as dynamic vibration absorbers (DVAs) is proposed. The effect of the multi-mode vibration on the ride quality of a high-speed EMU train was studied, and the target modes of vibration control were determined. An equivalent mass identification method was used to determine the equivalent mass for the target modes at the device installation positions. To optimize the vibration acceleration response of the carbody, the natural frequencies and damping ratios of the lateral and vertical vibration were designed based on the theory of dynamic vibration absorption. In order to realize the optimized design values of the natural frequencies for the lateral and vertical vibrations simultaneously, a new type of vibration absorber was designed in which a belleville spring and conventional rubber parts are connected in parallel. This design utilizes the negative stiffness of the belleville spring. Results show that, as compared to rigid equipment connections, the proposed method effectively reduces the multi-mode vibration of a carbody in a high-speed EMU train, thereby achieving the control objectives. The ride quality in terms of the lateral and vertical vibration of the carbody is considerably improved. Moreover, the optimal value of the damping ratio is effective in dissipating the vibration energy, which reduces the vibration of both the carbody and the equipment.

Multi-Modal Traveler Information System - Gateway Functional Requirements

DOT National Transportation Integrated Search

1997-11-17

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Multi-Modal Traveler Information System - Gateway Interface Control Requirements

DOT National Transportation Integrated Search

1997-10-30

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Critical Multimodal Literacy and the Common Core: Subversive Curriculum in the Age of Accountability

ERIC Educational Resources Information Center

Perttula, Jill

2017-01-01

The purpose of this case study research was to understand the ways in which an innovative, urban secondary English teacher (Ms. B) approached English Language Arts, when a set, standardized curriculum and testing were in place. The Common Core standards were prescribed within a required module-based presentation format. New literacies pedagogy…

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech.

PubMed

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances.

Capturing molecular multimode relaxation processes in excitable gases based on decomposition of acoustic relaxation spectra

NASA Astrophysics Data System (ADS)

Zhu, Ming; Liu, Tingting; Wang, Shu; Zhang, Kesheng

2017-08-01

Existing two-frequency reconstructive methods can only capture primary (single) molecular relaxation processes in excitable gases. In this paper, we present a reconstructive method based on the novel decomposition of frequency-dependent acoustic relaxation spectra to capture the entire molecular multimode relaxation process. This decomposition of acoustic relaxation spectra is developed from the frequency-dependent effective specific heat, indicating that a multi-relaxation process is the sum of the interior single-relaxation processes. Based on this decomposition, we can reconstruct the entire multi-relaxation process by capturing the relaxation times and relaxation strengths of N interior single-relaxation processes, using the measurements of acoustic absorption and sound speed at 2N frequencies. Experimental data for the gas mixtures CO2-N2 and CO2-O2 validate our decomposition and reconstruction approach.

A novel automated method for doing registration and 3D reconstruction from multi-modal RGB/IR image sequences

NASA Astrophysics Data System (ADS)

Kirby, Richard; Whitaker, Ross

2016-09-01

In recent years, the use of multi-modal camera rigs consisting of an RGB sensor and an infrared (IR) sensor have become increasingly popular for use in surveillance and robotics applications. The advantages of using multi-modal camera rigs include improved foreground/background segmentation, wider range of lighting conditions under which the system works, and richer information (e.g. visible light and heat signature) for target identification. However, the traditional computer vision method of mapping pairs of images using pixel intensities or image features is often not possible with an RGB/IR image pair. We introduce a novel method to overcome the lack of common features in RGB/IR image pairs by using a variational methods optimization algorithm to map the optical flow fields computed from different wavelength images. This results in the alignment of the flow fields, which in turn produce correspondences similar to those found in a stereo RGB/RGB camera rig using pixel intensities or image features. In addition to aligning the different wavelength images, these correspondences are used to generate dense disparity and depth maps. We obtain accuracies similar to other multi-modal image alignment methodologies as long as the scene contains sufficient depth variations, although a direct comparison is not possible because of the lack of standard image sets from moving multi-modal camera rigs. We test our method on synthetic optical flow fields and on real image sequences that we created with a multi-modal binocular stereo RGB/IR camera rig. We determine our method's accuracy by comparing against a ground truth.

Passive athermalization of multimode interference devices for wavelength-locking applications.

PubMed

Ruiz-Perez, Victor I; May-Arrioja, Daniel A; Guzman-Sepulveda, Jose R

2017-03-06

In this paper we demonstrate the passive, material-based athermalization of all-fiber architectures by cascading multimode interference (MMI) devices. In-line thermal compensation is achieved by including a liquid-core multimode section of variable length that allows ensuring temperature-independent operation while preserving the inherent filter-like spectral response of the MMI devices. The design of the temperature compensation unit is straightforward and its fabrication is simple. The applicability of our approach is experimentally verified by fabricating a wavelength-locked MMI laser with sensitivity of only -0.1 pm/°C, which is at least one order of magnitude lower than that achieved with other fiber optics devices.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Multi-Modal Traveler Information System - Alternative GCM Corridor Technologies and Strategies

DOT National Transportation Integrated Search

1997-10-24

The purpose of this working paper is to summarize current and evolving Intelligent Transportation System (ITS) technologies and strategies related to the design, development, and deployment of regional multi-modal traveler information systems. This r...

Prospectus on Multi-Modal Aspects of Human Factors in Transportation

DOT National Transportation Integrated Search

1991-02-01

This prospectus identifies and discusses a series of human factors : issues which are critical to transportation safety and productivity, and : examines the potential benefits that can accrue from taking a multi-modal : approach to human factors rese...

Multi-Modal Traveler Information System - GCM Corridor Architecture Interface Control Requirements

DOT National Transportation Integrated Search

1997-10-31

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Multi-Modal Traveler Information System - GCM Corridor Architecture Functional Requirements

DOT National Transportation Integrated Search

1997-11-17

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

MO-DE-202-03: Image-Guided Surgery and Interventions in the Advanced Multimodality Image-Guided Operating (AMIGO) Suite

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

Kapur, T.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-04: Multimodality Image-Guided Surgery and Intervention: For the Rest of Us

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

Shekhar, R.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Multimode-singlemode-multimode fiber sensor for alcohol sensing application

NASA Astrophysics Data System (ADS)

Rofi'ah, Iftihatur; Hatta, A. M.; Sekartedjo, Sekartedjo

2016-11-01

Alcohol is volatile and flammable liquid which is soluble substances both on polar and non polar substances that has been used in some industrial sectors. Alcohol detection method now widely used one of them is the optical fiber sensor. In this paper used fiber optic sensor based on Multimode-Single-mode-Multimode (MSM) to detect alcohol solution at a concentration range of 0-3%. The working principle of sensor utilizes the modal interference between the core modes and the cladding modes, thus make the sensor sensitive to environmental changes. The result showed that characteristic of the sensor not affect the length of the single-mode fiber (SMF). We obtain that the sensor with a length of 5 mm of single-mode can sensing the alcohol with a sensitivity of 0.107 dB/v%.

Multi-mode sliding mode control for precision linear stage based on fixed or floating stator.

PubMed

Fang, Jiwen; Long, Zhili; Wang, Michael Yu; Zhang, Lufan; Dai, Xufei

2016-02-01

This paper presents the control performance of a linear motion stage driven by Voice Coil Motor (VCM). Unlike the conventional VCM, the stator of this VCM is regulated, which means it can be adjusted as a floating-stator or fixed-stator. A Multi-Mode Sliding Mode Control (MMSMC), including a conventional Sliding Mode Control (SMC) and an Integral Sliding Mode Control (ISMC), is designed to control the linear motion stage. The control is switched between SMC and IMSC based on the error threshold. To eliminate the chattering, a smooth function is adopted instead of a signum function. The experimental results with the floating stator show that the positioning accuracy and tracking performance of the linear motion stage are improved with the MMSMC approach.

A practical salient region feature based 3D multi-modality registration method for medical images

NASA Astrophysics Data System (ADS)

Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

2006-03-01

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

Multicore fibre technology: the road to multimode photonics

NASA Astrophysics Data System (ADS)

Bland-Hawthorn, J.; Min, Seong-Sik; Lindley, Emma; Leon-Saval, Sergio; Ellis, Simon; Lawrence, Jon; Beyrand, Nicolas; Roth, Martin; Löhmannsröben, Hans-Gerd; Veilleux, Sylvain

2016-07-01

For the past forty years, optical fibres have found widespread use in ground-based and space-based instruments. In most applications, these fibres are used in conjunction with conventional optics to transport light. But photonics offers a huge range of optical manipulations beyond light transport that were rarely exploited before 2001. The fundamental obstacle to the broader use of photonics is the difficulty of achieving photonic action in a multimode fibre. The first step towards a general solution was the invention of the photonic lantern1 in 2004 and the delivery of high-efficiency devices (< 1 dB loss) five years on2. Multicore fibres (MCF), used in conjunction with lanterns, are now enabling an even bigger leap towards multimode photonics. Until recently, the single-moded cores in MCFs were not sufficiently uniform to achieve telecom (SMF-28) performance. Now that high-quality MCFs have been realized, we turn our attention to printing complex functions (e.g. Bragg gratings for OH suppression) into their N cores. Our first work in this direction used a Mach-Zehnder interferometer (near-field phase mask) but this approach was only adequate for N=7 MCFs as measured by the grating uniformity3. We have now built a Sagnac interferometer that gives a three-fold increase in the depth of field sufficient to print across N >= 127 cores. We achieved first light this year with our 500mW Sabre FRED laser. These are sophisticated and complex interferometers. We report on our progress to date and summarize our first-year goals which include multimode OH suppression fibres for the Anglo-Australian Telescope/PRAXIS instrument and the Discovery Channel Telescope/MOHSIS instrument under development at the University of Maryland.

Increasing knowledge of best practices for occupational therapists treating post-stroke unilateral spatial neglect: results of a knowledge-translation intervention study.

PubMed

Petzold, Anita; Korner-Bitensky, Nicol; Salbach, Nancy M; Ahmed, Sara; Menon, Anita; Ogourtsova, Tatiana

2012-02-01

The aim of this study was to investigate: (i) the feasibility of delivering a multi-modal knowledge translation intervention specific to the management of acute post-stroke unilateral spatial neglect; and (ii) the impact of the knowledge translation intervention on occupational therapists' knowledge of evidence-based unilateral spatial neglect problem identification, assessment and treatment, and self-efficacy related to evidence-based practice implementation. A 3-period (pre-post) repeated measures design. Acute care occupational therapists treating patients with post-stroke unilateral spatial neglect were recruited from two major Canadian cities. Participants completed two pre-intervention assessments, took part in a day-long interactive multi-modal knowledge translation intervention and a subsequent 8-week follow-up, and completed a post-intervention assessment. Knowledge of evidence-based problem identification, assessment and treatment of unilateral spatial neglect, and self-efficacy to perform evidence-based practice activities were measured using standard scales. The intervention was tested on 20 occupational therapists. Results indicate a significant improvement in knowledge of best practice unilateral spatial neglect management (p < 0.000) and evidence-based practice self-efficacy in carrying out evidence-based practice activities (p < 0.045) post-intervention. Use of a multi-modal knowledge translation intervention is feasible and can significantly improve occupational therapists' knowledge of unilateral spatial neglect best practices and self-efficacy. The findings should help advance best practices specific to the management of post-stroke unilateral spatial neglect as well as informing knowledge translation studies in other areas of practice.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

Experimental investigation on the high-order modes in supercontinuum generation from step-index As-S fibers

NASA Astrophysics Data System (ADS)

Chen, Peng; Xue, Zugang; Tian, Youmei; Zhao, Zheming; Wang, Xunsi; Liu, Zijun; Zhang, Peiqing; Dai, Shixun; Nie, Qiuhua; Wang, Rongping

2018-06-01

Two kinds of step-index As-S fibers have been fabricated by an isolated extrusion method with a numerical aperture (NA) of 0.52, but with different core size of 10 or 50 µm. With a femtosecond laser pumping, their supercontinnum (SC) generation spectra were recorded in order to testify the effect of high-order modes on SC generation. The spectra spanning from 1.0 to 6.7 µm and from 1.5 to 8.6 µm can be obtained in a 16-cm-long fiber with 10 µm-core diameter pumping by central wavelength of 2.9 and 4.0 µm, respectively. The results show that high-order modes would deplete the spectra spanning in red-shifting part. The SC generation in small-core fiber is much more efficient than that in large-core fiber. This is the first comparative investigation on the SC generation from the quasi single- and multi-mode ChG fibers under the same conditions.

Fluorophore-labeling of core-crosslinked polymeric micelles for multimodal in vivo and ex vivo optical imaging

PubMed Central

Shi, Yang; Kunjachan, Sijumon; Wu, Zhuojun; Gremse, Felix; Moeckel, Diana; van Zandvoort, Marc; Kiessling, Fabian; Storm, Gert; van Nostrum, Cornelus F.; Hennink, Wim E.; Lammers, Twan

2015-01-01

Aim To enable multimodal in vivo and ex vivo optical imaging of the biodistribution and tumor accumulation of core-crosslinked polymeric micelles (CCPM). Materials & Methods mPEG-b-p(HPMAm-Lac)-based polymeric micelles, core-crosslinked via cystamine and covalently labeled with two fluorophores (Dy-676/488) were synthesized. The CCPM were intravenously injected in CT26 tumor-bearing mice. Results Upon intravenous injection, the CCPM accumulated in CT26 tumors reasonably efficiently, with values reaching ~4 %ID at 24 hours. Ex vivo TPLSM confirmed efficient extravasation of the iCCPM out of tumor blood vessels and deep penetration into the tumor interstitium. Conclusions CCPM were labeled with multiple fluorophores, and they exemplify that combining different in vivo and ex vivo optical imaging techniques is highly useful for analyzing the biodistribution and tumor accumulation of nanomedicines. PMID:25929568

XML-based scripting of multimodality image presentations in multidisciplinary clinical conferences

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Allada, Vivekanand; Dahlbom, Magdalena; Marcus, Phillip; Fine, Ian; Lapstra, Lorelle

2002-05-01

We developed a multi-modality image presentation software for display and analysis of images and related data from different imaging modalities. The software is part of a cardiac image review and presentation platform that supports integration of digital images and data from digital and analog media such as videotapes, analog x-ray films and 35 mm cine films. The software supports standard DICOM image files as well as AVI and PDF data formats. The system is integrated in a digital conferencing room that includes projections of digital and analog sources, remote videoconferencing capabilities, and an electronic whiteboard. The goal of this pilot project is to: 1) develop a new paradigm for image and data management for presentation in a clinically meaningful sequence adapted to case-specific scenarios, 2) design and implement a multi-modality review and conferencing workstation using component technology and customizable 'plug-in' architecture to support complex review and diagnostic tasks applicable to all cardiac imaging modalities and 3) develop an XML-based scripting model of image and data presentation for clinical review and decision making during routine clinical tasks and multidisciplinary clinical conferences.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2015-10-01

eyes and image choroidal vessels/capillaries using CARS intravital microscopy Subtask 3: Measure oxy-hemoglobin levels in PBI test and control eyes...AWARD NUMBER: W81XWH-14-1-0537 TITLE: Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia...4. TITLE AND SUBTITLE Mobile, Multimodal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia 5a. CONTRACT NUMBER W81XWH

Multimodal Composition and the Common Core State Standards

ERIC Educational Resources Information Center

Dalton, Bridget

2013-01-01

The Common Core State Standards call for an expanded view of literacy instruction, one where children learn to critically consume and produce text using technology and media. This article describes how a Digital Writers' Workshop can be a vehicle for integrating multimodal composition into the classroom. It offers general workshop principles and…

Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

PubMed Central

Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

2012-01-01

When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance. PMID:22778600

Palmprint and face multi-modal biometric recognition based on SDA-GSVD and its kernelization.

PubMed

Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

2012-01-01

When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

Multi-Modal Traveler Information System - Performance Criteria for Evaluating GCM Corridor Strategies & Technologies

DOT National Transportation Integrated Search

1997-07-16

The Gary-Chicago-Milwaukee (GCM) Multi-Modal Traveler Information System (MMTIS) is a complex project involving a wide spectrum of participants. In order to facilitate its implementation it is important to understand the direction of the MMTIS. This ...

Dynamic mobility applications policy analysis : policy and institutional issues for multi-modal intelligent traffic signal system (MMITSS).

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...

Spatial accessibility to healthcare services in Shenzhen, China: improving the multi-modal two-step floating catchment area method by estimating travel time via online map APIs.

PubMed

Tao, Zhuolin; Yao, Zaoxing; Kong, Hui; Duan, Fei; Li, Guicai

2018-05-09

Shenzhen has rapidly grown into a megacity in the recent decades. It is a challenging task for the Shenzhen government to provide sufficient healthcare services. The spatial configuration of healthcare services can influence the convenience for the consumers to obtain healthcare services. Spatial accessibility has been widely adopted as a scientific measurement for evaluating the rationality of the spatial configuration of healthcare services. The multi-modal two-step floating catchment area (2SFCA) method is an important advance in the field of healthcare accessibility modelling, which enables the simultaneous assessment of spatial accessibility via multiple transport modes. This study further develops the multi-modal 2SFCA method by introducing online map APIs to improve the estimation of travel time by public transit or by car respectively. As the results show, the distribution of healthcare accessibility by multi-modal 2SFCA shows significant spatial disparity. Moreover, by dividing the multi-modal accessibility into car-mode and transit-mode accessibility, this study discovers that the transit-mode subgroup is disadvantaged in the competition for healthcare services with the car-mode subgroup. The disparity in transit-mode accessibility is the main reason of the uneven pattern of healthcare accessibility in Shenzhen. The findings suggest improving the public transit conditions for accessing healthcare services to reduce the disparity of healthcare accessibility. More healthcare services should be allocated in the eastern and western Shenzhen, especially sub-districts in Dapeng District and western Bao'an District. As these findings cannot be drawn by the traditional single-modal 2SFCA method, the advantage of the multi-modal 2SFCA method is significant to both healthcare studies and healthcare system planning.

Integrating Iris and Signature Traits for Personal Authentication Using User-Specific Weighting

PubMed Central

Viriri, Serestina; Tapamo, Jules R.

2012-01-01

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. PMID:22666032

Ultra-small, self-holding, optical gate switch using Ge2Sb2Te5 with a multi-mode Si waveguide.

PubMed

Tanaka, Daiki; Shoji, Yuya; Kuwahara, Masashi; Wang, Xiaomin; Kintaka, Kenji; Kawashima, Hitoshi; Toyosaki, Tatsuya; Ikuma, Yuichiro; Tsuda, Hiroyuki

2012-04-23

We report a multi-mode interference-based optical gate switch using a Ge(2)Sb(2)Te(5) thin film with a diameter of only 1 µm. The switching operation was demonstrated by laser pulse irradiation. This switch had a very wide operating wavelength range of 100 nm at around 1575 nm, with an average extinction ratio of 12.6 dB. Repetitive switching over 2,000 irradiation cycles was also successfully demonstrated. In addition, self-holding characteristics were confirmed by observing the dynamic responses, and the rise and fall times were 130 ns and 400 ns, respectively. © 2012 Optical Society of America

Dual spherical single-mode-multimode-single-mode optical fiber temperature sensor based on a Mach–Zehnder interferometer

NASA Astrophysics Data System (ADS)

Tan, Jianchang; Feng, Guoying; Zhang, Shulin; Liang, Jingchuan; Li, Wei; Luo, Yun

2018-07-01

A dual spherical single-mode-multimode-single-mode (DSSMS) optical fiber temperature sensor based on a Mach–Zehnder interferometer (MZI) was designed and implemented in this paper. Theoretical and experimental results indicated that the LP01 mode in the core and the LP09 mode excited by the spherical structure were maintained and transmitted via multimode fiber and interfered at the second spherical structure, resulting in the interference spectrum. An increase or decrease in temperature can cause significant red-shift or blue-shift of the spectrum, respectively. The linearity of the spectral shift due to the temperature change is ~0.999, the sensitivity at 30 °C–540 °C is ~37.372 pm °C‑3, and at  ‑25 °C–25 °C is ~37.28 pm °C‑1. The reproducibility error of this all-fiber temperature sensor at 30 °C–540 °C is less than 0.15%. Compared with the optical fiber sensor with a tapered structure and fiber core offset structure, this MZI-based DSSMS optical fiber temperature sensor has higher mechanical strength. Moreover, benefiting from low-cost and environmentally friendly materials, it is expected to be a novel micro-nano all-fiber sensor.

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

PubMed

Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

A feasibility study of evaluating transportation security systems and associated multi-modal efficiency impacts

DOT National Transportation Integrated Search

2006-08-01

The overall purpose of this research project is to conduct a feasibility study and development of a general methodology to determine the impacts on multi-modal and system efficiency of alternative freight security measures. The methodology to be exam...

Magnetic field sensor based on the magnetic-fluid-clad combined with singlemode-multimode-singlemode fiber and large core-offset splicing structure

NASA Astrophysics Data System (ADS)

Lv, Ri-qing; Qian, Jun-kai; Zhao, Yong

2018-03-01

A simple, compact optical fiber magnetic field sensor is proposed and experimentally demonstrated in this paper. It is based on the magnetic-fluid-clad combined with singlemode-multimode-singlemode fiber structure and large core-offset splicing structure. It was protected by a section of capillary tube and was sealed by UV glue. A sensing property study of the combined optical fiber structure and the proposed sensor were carried out. The experimental results show that the sensitivity of the refractive index of the optical fiber sensing structure is up to 156.63 nm/RIU and the magnetic field sensitivity of the proposed sensor is up to -97.24 pm/Oe in the range from 72.4 Oe to 297.8 Oe. The proposed sensor has several other advantages, such as simple structure, small size, easy fabrication and low cost.

Multi-mode Intravascular RF Coil for MRI-guided Interventions

PubMed Central

Kurpad, Krishna N.; Unal, Orhan

2011-01-01

Purpose To demonstrate the feasibility of using a single intravascular RF probe connected to the external MRI system via a single coaxial cable to perform active tip tracking and catheter visualization, and high SNR intravascular imaging. Materials and Methods A multi-mode intravascular RF coil was constructed on a 6F balloon catheter and interfaced to a 1.5T MRI scanner via a decoupling circuit. Bench measurements of coil impedances were followed by imaging experiments in saline and phantoms. Results The multi-mode coil behaves as an inductively-coupled transmit coil. Forward looking capability of 6mm is measured. Greater than 3-fold increase in SNR compared to conventional imaging using optimized external coil is demonstrated. Simultaneous active tip tracking and catheter visualization is demonstrated. Conclusions It is feasible to perform 1) active tip tracking, 2) catheter visualization, and 3) high SNR imaging using a single multi-mode intravascular RF coil that is connected to the external system via a single coaxial cable. PMID:21448969

Deep features for efficient multi-biometric recognition with face and ear images

NASA Astrophysics Data System (ADS)

Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

2017-07-01

Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

A nonlinear multi-mode wideband piezoelectric vibration-based energy harvester using compliant orthoplanar spring

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

Dhote, Sharvari, E-mail: sharvari.dhote@mail.utoronto.ca; Zu, Jean; Zhu, Yang

2015-04-20

In this paper, a nonlinear wideband multi-mode piezoelectric vibration-based energy harvester (PVEH) is proposed based on a compliant orthoplanar spring (COPS), which has an advantage of providing multiple vibration modes at relatively low frequencies. The PVEH is made of a tri-leg COPS flexible structure, where three fixed-guided beams are capable of generating strong nonlinear oscillations under certain base excitation. A prototype harvester was fabricated and investigated through both finite-element analysis and experiments. The frequency response shows multiple resonance which corresponds to a hardening type of nonlinear resonance. By adding masses at different locations on the COPS structure, the first threemore » vibration modes are brought close to each other, where the three hardening nonlinear resonances provide a wide bandwidth for the PVEH. The proposed PVEH has enhanced performance of the energy harvester in terms of a wide frequency bandwidth and a high-voltage output under base excitations.« less

Key informant interviews test plan : model deployment of a regional, multi-modal 511 traveler information system

DOT National Transportation Integrated Search

2004-01-28

This document presents the detailed plan to conduct the Key Informants Interviews Test, one of several test activities to be conducted as part of the national evaluation of the regional, multi-modal 511 Traveler Information System Model Deployment. T...

Hyperspectral tomography based on multi-mode absorption spectroscopy (MUMAS)

NASA Astrophysics Data System (ADS)

Dai, Jinghang; O'Hagan, Seamus; Liu, Hecong; Cai, Weiwei; Ewart, Paul

2017-10-01

This paper demonstrates a hyperspectral tomographic technique that can recover the temperature and concentration field of gas flows based on multi-mode absorption spectroscopy (MUMAS). This method relies on the recently proposed concept of nonlinear tomography, which can take full advantage of the nonlinear dependency of MUMAS signals on temperature and enables 2D spatial resolution of MUMAS which is naturally a line-of-sight technique. The principles of MUMAS and nonlinear tomography, as well as the mathematical formulation of the inversion problem, are introduced. Proof-of-concept numerical demonstrations are presented using representative flame phantoms and assuming typical laser parameters. The results show that faithful reconstruction of temperature distribution is achievable when a signal-to-noise ratio of 20 is assumed. This method can potentially be extended to simultaneously reconstructing distributions of temperature and the concentration of multiple flame species.

Multi-modality image registration for effective thermographic fever screening

NASA Astrophysics Data System (ADS)

Dwith, C. Y. N.; Ghassemi, Pejhman; Pfefer, Joshua; Casamento, Jon; Wang, Quanzeng

2017-02-01

Fever screening based on infrared thermographs (IRTs) is a viable mass screening approach during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome (SARS), for temperature monitoring in public places like hospitals and airports. IRTs have been found to be powerful, quick and non-invasive methods for detecting elevated temperatures. Moreover, regions medially adjacent to the inner canthi (called the canthi regions in this paper) are preferred sites for fever screening. Accurate localization of the canthi regions can be achieved through multi-modality registration of infrared (IR) and white-light images. Here we propose a registration method through a coarse-fine registration strategy using different registration models based on landmarks and edge detection on eye contours. We have evaluated the registration accuracy to be within +/- 2.7 mm, which enables accurate localization of the canthi regions.

Simultaneous strain and temperature measure based on a single suspended core photonic crystal fiber

NASA Astrophysics Data System (ADS)

Rota-Rodrigo, S.; López-Amo, M.; Kobelke, J.; Schuster, K.; Santos, J. L.; Frazão, O.

2014-05-01

In this work a simultaneous strain and temperature sensor based on a suspended core fiber is proposed. The sensor comprises a 3mm suspended core PCF between SMFs and is based on the combination of two multimodal interferences with different frequency fringe patterns. The interference of the both signal has different sensitivity responses to strain and temperature. Thought a low-pass frequency filtering of the detected spectrum, the wavelength shift of the two interferences can be measured allowing the discrimination of strain and temperature simultaneously. The resolutions of this sensor are 0.45 ºC and 4.02 μɛ.

High-energy and high-peak-power nanosecond pulse generation with beam quality control in 200-µm core highly multimode Yb-doped fiberamplifiers

NASA Astrophysics Data System (ADS)

Cheng, Ming-Yuan; Chang, Yu-Chung; Galvanauskas, Almantas; Mamidipudi, Pri; Changkakoti, Rupak; Gatchell, Peter

2005-02-01

We explored high-energy and high-peak-power pulse generation in large-core multimode fiber amplifiers, achieving what is to our knowledge the highest reported energies, up to 82 mJ for 500-ns pulses, 27 mJ for 50-ns pulses, and 2.4-MW peak power for 4-ns pulses at 1064 nm, using 200-µm-diameter and 0.062-N.A. core Yb-doped double-clad fiber amplifiers. The highly multimode nature of the fiber core was mitigated by use of a coiling-induced mode-filtering effect to yield a significant improvement in output-beam quality from M^2 = 25 from an uncoiled fiber to M^2 = 6.5 from a properly coiled fiber, with the corresponding reduction in number of propagating transverse modes from >or=200 to <or=20.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

PubMed

Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

NASA Astrophysics Data System (ADS)

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

2018-05-01

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech

PubMed Central

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. PMID:26925010

The Connectome Viewer Toolkit: An Open Source Framework to Manage, Analyze, and Visualize Connectomes

PubMed Central

Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit – a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/ PMID:21713110

Towards an intelligent framework for multimodal affective data analysis.

PubMed

Poria, Soujanya; Cambria, Erik; Hussain, Amir; Huang, Guang-Bin

2015-03-01

An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-modal analysis framework that can effectively extract information from multiple modalities. In this paper, we propose a novel multimodal information extraction agent, which infers and aggregates the semantic and affective information associated with user-generated multimodal data in contexts such as e-learning, e-health, automatic video content tagging and human-computer interaction. In particular, the developed intelligent agent adopts an ensemble feature extraction approach by exploiting the joint use of tri-modal (text, audio and video) features to enhance the multimodal information extraction process. In preliminary experiments using the eNTERFACE dataset, our proposed multi-modal system is shown to achieve an accuracy of 87.95%, outperforming the best state-of-the-art system by more than 10%, or in relative terms, a 56% reduction in error rate. Copyright © 2014 Elsevier Ltd. All rights reserved.

(In)Flexibility of Constituency in Japanese in Multi-Modal Categorial Grammar with Structured Phonology

ERIC Educational Resources Information Center

Kubota, Yusuke

2010-01-01

This dissertation proposes a theory of categorial grammar called Multi-Modal Categorial Grammar with Structured Phonology. The central feature that distinguishes this theory from the majority of contemporary syntactic theories is that it decouples (without completely segregating) two aspects of syntax--hierarchical organization (reflecting…

Alternative Fuels Data Center: Multi-Modal Transportation

Science.gov Websites

examples of resources to help travelers use multi-modal transportation. OpenTripPlanner Map - an online transportation modes including transit (bus or train), walking, and bicycling 511 - a one-stop source from the of alternative transportation modes. A 2010 evaluation by the Oregon Transportation Research and

Utilizing Multi-Modal Literacies in Middle Grades Science

ERIC Educational Resources Information Center

Saurino, Dan; Ogletree, Tamra; Saurino, Penelope

2010-01-01

The nature of literacy is changing. Increased student use of computer-mediated, digital, and visual communication spans our understanding of adolescent multi-modal capabilities that reach beyond the traditional conventions of linear speech and written text in the science curriculum. Advancing technology opens doors to learning that involve…

Delivery of ultrashort spatially focused pulses through a multimode fiber

NASA Astrophysics Data System (ADS)

Morales-Delgado, Edgar E.; Papadopoulos, Ioannis N.; Farahi, Salma; Psaltis, Demetri; Moser, Christophe

2015-08-01

Multimode optical fibers potentially allow the transmission of larger amounts of information than their single mode counterparts because of their high number of supported modes. However, propagation of a light pulse through a multimode fiber suffers from spatial distortions due to the superposition of the various exited modes and from time broadening due to modal dispersion. We present a method based on digital phase conjugation to selectively excite in a multimode fiber specific optical fiber modes that follow similar optical paths as they travel through the fiber. The excited modes interfere constructively at the fiber output generating an ultrashort spatially focused pulse. The excitation of a limited number of modes following similar optical paths limits modal dispersion, allowing the transmission of the ultrashort pulse. We have experimentally demonstrated the delivery of a focused spot of pulse width equal to 500 fs through a 30 cm, 200 micrometer core step index multimode fiber. The results of this study show that two-photon imaging capability can be added to ultra-thin lensless endoscopy using commercial multimode fibers.

Delivery of an ultrashort spatially focused pulse to the other end of a multimode fiber using digital phase conjugation

NASA Astrophysics Data System (ADS)

Morales Delgado, Edgar E.; Papadopoulos, Ioannis N.; Farahi, Salma; Psaltis, Demetri; Moser, Christophe

2015-03-01

Multimode optical fibers potentially allow the transmission of larger amounts of information than their single mode counterparts because of their high number of supported modes. However, propagation of a light pulse through a multimode fiber suffers from spatial distortions due to the superposition of the various exited modes and from time broadening due to modal dispersion. We present a method based on digital phase conjugation to selectively excite in a multimode fiber specific optical fiber modes that follow similar optical paths as they travel through the fiber. The excited modes interfere constructively at the fiber output generating an ultrashort spatially focused pulse. The excitation of a limited number of modes following similar optical paths limits modal dispersion, allowing the transmission of the ultrashort pulse. We have experimentally demonstrated the delivery of a focused spot of pulse width equal to 500 fs through a 30 cm, 200 micrometer core step-index multimode fiber. The results of this study show that two-photon imaging capability can be added to ultra-thin lensless endoscopy using commercial multimode fibers.

The new frontiers of multimodality and multi-isotope imaging

NASA Astrophysics Data System (ADS)

Behnam Azad, Babak; Nimmagadda, Sridhar

2014-06-01

Technological advances in imaging systems and the development of target specific imaging tracers has been rapidly growing over the past two decades. Recent progress in "all-in-one" imaging systems that allow for automated image coregistration has significantly added to the growth of this field. These developments include ultra high resolution PET and SPECT scanners that can be integrated with CT or MR resulting in PET/CT, SPECT/CT, SPECT/PET and PET/MRI scanners for simultaneous high resolution high sensitivity anatomical and functional imaging. These technological developments have also resulted in drastic enhancements in image quality and acquisition time while eliminating cross compatibility issues between modalities. Furthermore, the most cutting edge technology, though mostly preclinical, also allows for simultaneous multimodality multi-isotope image acquisition and image reconstruction based on radioisotope decay characteristics. These scientific advances, in conjunction with the explosion in the development of highly specific multimodality molecular imaging agents, may aid in realizing simultaneous imaging of multiple biological processes and pave the way towards more efficient diagnosis and improved patient care.

Multimodal Trip Planner System final evaluation report.

DOT National Transportation Integrated Search

2011-05-01

This evaluation of the Multimodal Trip Planning System (MMTPS) is the culmination of a multi-year project evaluating the development and deployment of a multimodal trip planner in the Chicagoland area between 2004 and 2010. The report includes an ove...

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

Barstow, Del R; Patlolla, Dilip Reddy; Mann, Christopher J

Abstract The data captured by existing standoff biometric systems typically has lower biometric recognition performance than their close range counterparts due to imaging challenges, pose challenges, and other factors. To assist in overcoming these limitations systems typically perform in a multi-modal capacity such as Honeywell s Combined Face and Iris (CFAIRS) [21] system. While this improves the systems performance, standoff systems have yet to be proven as accurate as their close range equivalents. We will present a standoff system capable of operating up to 7 meters in range. Unlike many systems such as the CFAIRS our system captures high qualitymore » 12 MP video allowing for a multi-sample as well as multi-modal comparison. We found that for standoff systems multi-sample improved performance more than multi-modal. For a small test group of 50 subjects we were able to achieve 100% rank one recognition performance with our system.« less

A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling.

PubMed

Asif, Umar; Bennamoun, Mohammed; Sohel, Ferdous

2017-08-30

While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i.e., imageand pixel-levels), and fused into a Conditional Random Field (CRF)- based inference hypothesis, the optimization of which produces consistent class labels in RGB-D images. Extensive experimental evaluations on RGB-D object and scene datasets, and live video streams (acquired from Kinect) show that our framework produces superior object and scene classification results compared to the state-of-the-art methods.

MO-DE-202-00: Image-Guided Interventions: Advances in Intraoperative Imaging, Guidance, and An Emerging Role for Medical Physics in Surgery

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

NONE

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-01: Image-Guided Focused Ultrasound Surgery and Therapy

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

Farahani, K.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-02: Advances in Image Registration and Reconstruction for Image-Guided Neurosurgery

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

Siewerdsen, J.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Development of a new multi-modal Monte-Carlo radiotherapy planning system.

PubMed

Kumada, H; Nakamura, T; Komeda, M; Matsumura, A

2009-07-01

A new multi-modal Monte-Carlo radiotherapy planning system (developing code: JCDS-FX) is under development at Japan Atomic Energy Agency. This system builds on fundamental technologies of JCDS applied to actual boron neutron capture therapy (BNCT) trials in JRR-4. One of features of the JCDS-FX is that PHITS has been applied to particle transport calculation. PHITS is a multi-purpose particle Monte-Carlo transport code. Hence application of PHITS enables to evaluate total doses given to a patient by a combined modality therapy. Moreover, JCDS-FX with PHITS can be used for the study of accelerator based BNCT. To verify calculation accuracy of the JCDS-FX, dose evaluations for neutron irradiation of a cylindrical water phantom and for an actual clinical trial were performed, then the results were compared with calculations by JCDS with MCNP. The verification results demonstrated that JCDS-FX is applicable to BNCT treatment planning in practical use.

APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies.

PubMed

Kanbar, Lara J; Shalish, Wissam; Precup, Doina; Brown, Karen; Sant'Anna, Guilherme M; Kearney, Robert E

2017-07-01

In multi-disciplinary studies, different forms of data are often collected for analysis. For example, APEX, a study on the automated prediction of extubation readiness in extremely preterm infants, collects clinical parameters and cardiorespiratory signals. A variety of cardiorespiratory metrics are computed from these signals and used to assign a cardiorespiratory pattern at each time. In such a situation, exploratory analysis requires a visualization tool capable of displaying these different types of acquired and computed signals in an integrated environment. Thus, we developed APEX_SCOPE, a graphical tool for the visualization of multi-modal data comprising cardiorespiratory signals, automated cardiorespiratory metrics, automated respiratory patterns, manually classified respiratory patterns, and manual annotations by clinicians during data acquisition. This MATLAB-based application provides a means for collaborators to view combinations of signals to promote discussion, generate hypotheses and develop features.

Example based lesion segmentation

NASA Astrophysics Data System (ADS)

Roy, Snehashis; He, Qing; Carass, Aaron; Jog, Amod; Cuzzocreo, Jennifer L.; Reich, Daniel S.; Prince, Jerry; Pham, Dzung

2014-03-01

Automatic and accurate detection of white matter lesions is a significant step toward understanding the progression of many diseases, like Alzheimer's disease or multiple sclerosis. Multi-modal MR images are often used to segment T2 white matter lesions that can represent regions of demyelination or ischemia. Some automated lesion segmentation methods describe the lesion intensities using generative models, and then classify the lesions with some combination of heuristics and cost minimization. In contrast, we propose a patch-based method, in which lesions are found using examples from an atlas containing multi-modal MR images and corresponding manual delineations of lesions. Patches from subject MR images are matched to patches from the atlas and lesion memberships are found based on patch similarity weights. We experiment on 43 subjects with MS, whose scans show various levels of lesion-load. We demonstrate significant improvement in Dice coefficient and total lesion volume compared to a state of the art model-based lesion segmentation method, indicating more accurate delineation of lesions.

Aging, training, and the brain: A review and future directions

PubMed Central

Lustig, Cindy; Shah, Priti; Seidler, Rachael; Reuter-Lorenz, Patricia A.

2010-01-01

As the population ages, the need for effective methods to maintain or even improve older adults’ cognitive performance becomes increasingly pressing. Here we provide a brief review of the major intervention approaches that have been the focus of past research with healthy older adults (strategy training, multi-modal interventions, cardiovascular exercise, and process-based training), and new approaches that incorporate neuroimaging. As outcome measures, neuroimaging data on intervention-related changes in volume, structural integrity, and functional activation can provide important insights into the nature and duration of an intervention's effects. Perhaps even more intriguingly, several recent studies have used neuroimaging data as a guide to identify core cognitive processes that can be trained in one task with effective transfer to other tasks that share the same underlying processes. Although many open questions remain, this research has greatly increased our understanding of how to promote successful aging of cognition and the brain. PMID:19876740

Design of miniaturized illumination for transvaginal co-registered photoacoustic and ultrasound imaging.

PubMed

Salehi, Hassan S; Wang, Tianheng; Kumavor, Patrick D; Li, Hai; Zhu, Quing

2014-09-01

A novel lens-array based illumination design for a compact co-registered photoacoustic/ultrasound transvaginal probe has been demonstrated. The lens array consists of four cylindrical lenses that couple the laser beams into four 1-mm-core multi-mode optical fibers with optical coupling efficiency of ~87%. The feasibility of our lens array was investigated by simulating the lenses and laser beam profiles using Zemax. The laser fluence on the tissue surface was experimentally measured and was below the American National Standards Institute (ANSI) safety limit. Spatial distribution of hemoglobin oxygen saturation (sO2) of a mouse tumor was obtained in vivo using photoacoustic measurements at multiple wavelengths. Furthermore, benign and malignant ovaries were imaged ex vivo and evaluated histologically. The co-registered images clearly showed different patterns of blood vasculature. These results highlight the clinical potential of our system for noninvasive photoacoustic and ultrasound imaging of ovarian tissue and cancer detection and diagnosis.

Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware.

PubMed

Levin, David; Aladl, Usaf; Germano, Guido; Slomka, Piotr

2005-09-01

We exploit consumer graphics hardware to perform real-time processing and visualization of high-resolution, 4D cardiac data. We have implemented real-time, realistic volume rendering, interactive 4D motion segmentation of cardiac data, visualization of multi-modality cardiac data and 3D display of multiple series cardiac MRI. We show that an ATI Radeon 9700 Pro can render a 512x512x128 cardiac Computed Tomography (CT) study at 0.9 to 60 frames per second (fps) depending on rendering parameters and that 4D motion based segmentation can be performed in real-time. We conclude that real-time rendering and processing of cardiac data can be implemented on consumer graphics cards.

MIMI: multimodality, multiresource, information integration environment for biomedical core facilities.

PubMed

Szymanski, Jacek; Wilson, David L; Zhang, Guo-Qiang

2009-10-01

The rapid expansion of biomedical research has brought substantial scientific and administrative data management challenges to modern core facilities. Scientifically, a core facility must be able to manage experimental workflow and the corresponding set of large and complex scientific data. It must also disseminate experimental data to relevant researchers in a secure and expedient manner that facilitates collaboration and provides support for data interpretation and analysis. Administratively, a core facility must be able to manage the scheduling of its equipment and to maintain a flexible and effective billing system to track material, resource, and personnel costs and charge for services to sustain its operation. It must also have the ability to regularly monitor the usage and performance of its equipment and to provide summary statistics on resources spent on different categories of research. To address these informatics challenges, we introduce a comprehensive system called MIMI (multimodality, multiresource, information integration environment) that integrates the administrative and scientific support of a core facility into a single web-based environment. We report the design, development, and deployment experience of a baseline MIMI system at an imaging core facility and discuss the general applicability of such a system in other types of core facilities. These initial results suggest that MIMI will be a unique, cost-effective approach to addressing the informatics infrastructure needs of core facilities and similar research laboratories.

Students' Multi-Modal Re-Presentations of Scientific Knowledge and Creativity

ERIC Educational Resources Information Center

Koren, Yitzhak; Klavir, Rama; Gorodetsky, Malka

2005-01-01

The paper brings the results of a project that passed on to students the opportunity for re-presenting their acquired knowledge via the construction of multi-modal "learning resources". These "learning resources" substituted for lectures and books and became the official learning sources in the classroom. The rational for the…

A Multi-Modal Active Learning Experience for Teaching Social Categorization

ERIC Educational Resources Information Center

Schwarzmueller, April

2011-01-01

This article details a multi-modal active learning experience to help students understand elements of social categorization. Each student in a group dynamics course observed two groups in conflict and identified examples of in-group bias, double-standard thinking, out-group homogeneity bias, law of small numbers, group attribution error, ultimate…

Hybrid PD and effective multi-mode positive position feedback control for slewing and vibration suppression of a smart flexible manipulator

NASA Astrophysics Data System (ADS)

Lou, Jun-qiang; Wei, Yan-ding; Yang, Yi-ling; Xie, Feng-ran

2015-03-01

A hybrid control strategy for slewing and vibration suppression of a smart flexible manipulator is presented in this paper. It consists of a proportional derivative controller to realize motion control, and an effective multi-mode positive position feedback (EMPPF) controller to suppress the multi-mode vibration. Rather than treat each mode equally as the standard multi-mode PPF, the essence of the EMPPF is that control forces of different modes are applied according to the mode parameters of the respective modes, so the vibration modes with less vibration energy receive fewer control forces. Stability conditions for the close loop system are established through stability analysis. Optimal parameters of the EMPPF controller are obtained using the method of root locus analysis. The performance of the proposed strategy is demonstrated by simulation and experiments. Experimental results show that the first two vibration modes of the manipulator are effectively suppressed. The setting time of the setup descends approximately 55%, reaching 3.12 s from 5.67 s.

Efficient pump module coupling >1kW from a compact detachable fiber

NASA Astrophysics Data System (ADS)

Dogan, M.; Chin, R. H.; Fulghum, S.; Jacob, J. H.; Chin, A. K.

2018-02-01

In the most developed fiber amplifiers, optical pump power is introduced into the 400μm-diameter, 0.46NA first cladding of the double-clad, Yb-doped, gain fiber, using a (6+1):1 multi-mode fiber combiner. For this configuration, the core diameter and numerical aperture of the pump delivery fibers have maximum values of 225μm and 0.22, respectively. This paper presents the first fiber-coupled laser-diode pump module emitting more than 1kW of claddingmode- stripped power from a detachable 225μm, 0.22NA delivery fiber at 976nm. The electrical-to-optical power conversion efficiency at 1kW is 50%. The FWHM spectral width at 1kW output is 4nm and has an excellent overlap with the narrow absorption spectrum of ytterbium in glass. Six of these pump modules attached to a (6+1):1 multimode combiner enable a 5-6kW, single-mode, Yb-doped fiber amplifier.

Doxorubicin loaded dual pH- and thermo-responsive magnetic nanocarrier for combined magnetic hyperthermia and targeted controlled drug delivery applications

NASA Astrophysics Data System (ADS)

Hervault, Aziliz; Dunn, Alexander E.; Lim, May; Boyer, Cyrille; Mott, Derrick; Maenosono, Shinya; Thanh, Nguyen T. K.

2016-06-01

Magnetic nanocarriers have attracted increasing attention for multimodal cancer therapy due to the possibility to deliver heat and drugs locally. The present study reports the development of magnetic nanocomposites (MNCs) made of an iron oxide core and a pH- and thermo-responsive polymer shell, that can be used as both hyperthermic agent and drug carrier. The conjugation of anticancer drug doxorubicin (DOX) to the pH- and thermo-responsive MNCs via acid-cleavable imine linker provides advanced features for the targeted delivery of DOX molecules via the combination of magnetic targeting, and dual pH- and thermo-responsive behaviour which offers spatial and temporal control over the release of DOX. The iron oxide cores exhibit a superparamagnetic behaviour with a saturation magnetization around 70 emu g-1. The MNCs contained 8.1 wt% of polymer and exhibit good heating properties in an alternating magnetic field. The drug release experiments confirmed that only a small amount of DOX was released at room temperature and physiological pH, while the highest drug release of 85.2% was obtained after 48 h at acidic tumour pH under hyperthermia conditions (50 °C). The drug release kinetic followed Korsmeyer-Peppas model and displayed Fickian diffusion mechanism. From the results obtained it can be concluded that this smart magnetic nanocarrier is promising for applications in multi-modal cancer therapy, to target and efficiently deliver heat and drug specifically to the tumour.Magnetic nanocarriers have attracted increasing attention for multimodal cancer therapy due to the possibility to deliver heat and drugs locally. The present study reports the development of magnetic nanocomposites (MNCs) made of an iron oxide core and a pH- and thermo-responsive polymer shell, that can be used as both hyperthermic agent and drug carrier. The conjugation of anticancer drug doxorubicin (DOX) to the pH- and thermo-responsive MNCs via acid-cleavable imine linker provides advanced features for the targeted delivery of DOX molecules via the combination of magnetic targeting, and dual pH- and thermo-responsive behaviour which offers spatial and temporal control over the release of DOX. The iron oxide cores exhibit a superparamagnetic behaviour with a saturation magnetization around 70 emu g-1. The MNCs contained 8.1 wt% of polymer and exhibit good heating properties in an alternating magnetic field. The drug release experiments confirmed that only a small amount of DOX was released at room temperature and physiological pH, while the highest drug release of 85.2% was obtained after 48 h at acidic tumour pH under hyperthermia conditions (50 °C). The drug release kinetic followed Korsmeyer-Peppas model and displayed Fickian diffusion mechanism. From the results obtained it can be concluded that this smart magnetic nanocarrier is promising for applications in multi-modal cancer therapy, to target and efficiently deliver heat and drug specifically to the tumour. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07773g

Development of an instrumentation system for measurement of degradation of lubricating oil using optical fiber sensor

NASA Astrophysics Data System (ADS)

Laskar, S.; Bordoloi, S.

2016-01-01

This paper presents an instrumentation system to measure the degradation in lubricating oil using a bare, tapered and bent multi-mode optical fiber (BTBMOF) sensor probe and a temperature probe. The sensor system consists of (i) a bare, tapered and bent multi-mode optical fiber (BTBMOF) as optical sensor along with a laser source and a LDR (Light Dependent Resistor) as detector (ii) a temperature sensor (iii) a ATmega microcontroller based data acquisition system and (iv) a trained ANN for processing and calibration. The BTBMOF sensor and the temperature sensor are used to provide the measure of refractive index (RI) and the temperature of a lubricating oil sample. A microcontroller based instrumentation system with trained ANN algorithm has been developed to determine the degradation of the lubricating oil sample by sampling the readings of the optical fiber sensor, and the temperature sensor.

Tumor Lysing Genetically Engineered T Cells Loaded with Multi-Modal Imaging Agents

NASA Astrophysics Data System (ADS)

Bhatnagar, Parijat; Alauddin, Mian; Bankson, James A.; Kirui, Dickson; Seifi, Payam; Huls, Helen; Lee, Dean A.; Babakhani, Aydin; Ferrari, Mauro; Li, King C.; Cooper, Laurence J. N.

2014-03-01

Genetically-modified T cells expressing chimeric antigen receptors (CAR) exert anti-tumor effect by identifying tumor-associated antigen (TAA), independent of major histocompatibility complex. For maximal efficacy and safety of adoptively transferred cells, imaging their biodistribution is critical. This will determine if cells home to the tumor and assist in moderating cell dose. Here, T cells are modified to express CAR. An efficient, non-toxic process with potential for cGMP compliance is developed for loading high cell number with multi-modal (PET-MRI) contrast agents (Super Paramagnetic Iron Oxide Nanoparticles - Copper-64; SPION-64Cu). This can now be potentially used for 64Cu-based whole-body PET to detect T cell accumulation region with high-sensitivity, followed by SPION-based MRI of these regions for high-resolution anatomically correlated images of T cells. CD19-specific-CAR+SPIONpos T cells effectively target in vitro CD19+ lymphoma.

Multi-mode clustering model for hierarchical wireless sensor networks

NASA Astrophysics Data System (ADS)

Hu, Xiangdong; Li, Yongfu; Xu, Huifen

2017-03-01

The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

Design of a Multi-mode Flight Deck Decision Support System for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Krishnamurthy, Karthik

2004-01-01

NASA Langley has developed a multi-mode decision support system for pilots operating in a Distributed Air-Ground Traffic Management (DAG-TM) environment. An Autonomous Operations Planner (AOP) assists pilots in performing separation assurance functions, including conflict detection, prevention, and resolution. Ongoing AOP design has been based on a comprehensive human factors analysis and evaluation results from previous human-in-the-loop experiments with airline pilot test subjects. AOP considers complex flight mode interactions and provides flight guidance to pilots consistent with the current aircraft control state. Pilots communicate goals to AOP by setting system preferences and actively probing potential trajectories for conflicts. To minimize training requirements and improve operational use, AOP design leverages existing alerting philosophies, displays, and crew interfaces common on commercial aircraft. Future work will consider trajectory prediction uncertainties, integration with the TCAS collision avoidance system, and will incorporate enhancements based on an upcoming air-ground coordination experiment.

A guided wave dispersion compensation method based on compressed sensing

NASA Astrophysics Data System (ADS)

Xu, Cai-bin; Yang, Zhi-bo; Chen, Xue-feng; Tian, Shao-hua; Xie, Yong

2018-03-01

The ultrasonic guided wave has emerged as a promising tool for structural health monitoring (SHM) and nondestructive testing (NDT) due to their capability to propagate over long distances with minimal loss and sensitivity to both surface and subsurface defects. The dispersion effect degrades the temporal and spatial resolution of guided waves. A novel ultrasonic guided wave processing method for both single mode and multi-mode guided waves dispersion compensation is proposed in this work based on compressed sensing, in which a dispersion signal dictionary is built by utilizing the dispersion curves of the guided wave modes in order to sparsely decompose the recorded dispersive guided waves. Dispersion-compensated guided waves are obtained by utilizing a non-dispersion signal dictionary and the results of sparse decomposition. Numerical simulations and experiments are implemented to verify the effectiveness of the developed method for both single mode and multi-mode guided waves.

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

NASA Astrophysics Data System (ADS)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Multi-mode optical fibers for connecting space-based spectrometers

NASA Astrophysics Data System (ADS)

Roberts, W. T.; Lindenmisth, C. A.; Bender, S.; Miller, E. A.; Motts, E.; Ott, M.; LaRocca, F.; Thomes, J.

2017-11-01

Laser spectral analysis systems are increasingly being considered for in situ analysis of the atomic and molecular composition of selected rock and soil samples on other planets [1][2][3]. Both Laser Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy are used to identify the constituents of soil and rock samples in situ. LIBS instruments use a high peak-power laser to ablate a minute area of the surface of a sample. The resulting plasma is observed with an optical head, which collects the emitted light for analysis by one or more spectrometers. By identifying the ion emission lines observed in the plasma, the constituent elements and their abundance can be deduced. In Raman spectroscopy, laser photons incident on the sample surface are scattered and experience a Raman shift, exchanging small amounts of energy with the molecules scattering the light. By observing the spectrum of the scattered light, it is possible to determine the molecular composition of the sample. For both types of instruments, there are advantages to physically separating the light collecting optics from the spectroscopy optics. The light collection system will often have articulating or rotating elements to facilitate the interrogation of multiple samples with minimum expenditure of energy and motion. As such, the optical head is often placed on a boom or an appendage allowing it to be pointed in different directions or easily positioned in different locations. By contrast, the spectrometry portion of the instrument is often well-served by placing it in a more static location. The detectors often operate more consistently in a thermally-controlled environment. Placing them deep within the spacecraft structure also provides some shielding from ionizing radiation, extending the instrument's useful life. Finally, the spectrometry portion of the instrument often contains significant mass, such that keeping it off of the moving portion of the platform, allowing that portion to be significantly smaller, less massive and less robust. Large core multi-mode optical fibers are often used to accommodate the optical connection of the two separated portions of such instrumentation. In some cases, significant throughput efficiency improvement can be realized by judiciously orienting the strands of multi-fiber cable, close-bunching them to accommodate a tight focus of the optical system on the optical side of the connection, and splaying them out linearly along a spectrometer slit on the other end. For such instrumentation to work effectively in identifying elements and molecules, and especially to produce accurate quantitative results, the spectral throughput of the optical fiber connection must be consistent over varying temperatures, over the range of motion of the optical head (and it's implied optical cable stresses), and over angle-aperture invariant of the total system. While the first two of these conditions have been demonstrated[4], spectral observations of the latter present a cause for concern, and may have an impact on future design of fiber-connected LIBS and Raman spectroscopy instruments. In short, we have observed that the shape of the spectral efficiency curve of a large multi-mode core optical fiber changes as a function of input angle.

Real English: A Translator to Enable Natural Language Man-Machine Conversation.

ERIC Educational Resources Information Center

Gautin, Harvey

This dissertation presents a pragmatic interpreter/translator called Real English to serve as a natural language man-machine communication interface in a multi-mode on-line information retrieval system. This multi-mode feature affords the user a library-like searching tool by giving him access to a dictionary, lexicon, thesaurus, synonym table,…

Multi-Modal Traveler Information System - Lessons Learned

DOT National Transportation Integrated Search

1997-05-19

The purpose of this working paper is to provide an information base of lessons learned from activities similar to the design of the Gary Chicago Milwaukee (GCM) Corridor Architecture and the Gateway Traveler Information System (TIS). Many similar act...

Multi-Modal Traveler Information System - Cellular 911-State of the Practice

DOT National Transportation Integrated Search

1997-05-19

Working paper evaluates the implemented public 911 and private non-911 cellular : based emergency centers around the country, and within the : Gary-Chicago-Milwaukee (GCM) Corridor and documents the impact, implications and : experiences of switching...

Introducing the Geneva Multimodal expression corpus for experimental research on emotion perception.

PubMed

Bänziger, Tanja; Mortillaro, Marcello; Scherer, Klaus R

2012-10-01

Research on the perception of emotional expressions in faces and voices is exploding in psychology, the neurosciences, and affective computing. This article provides an overview of some of the major emotion expression (EE) corpora currently available for empirical research and introduces a new, dynamic, multimodal corpus of emotion expressions, the Geneva Multimodal Emotion Portrayals Core Set (GEMEP-CS). The design features of the corpus are outlined and justified, and detailed validation data for the core set selection are presented and discussed. Finally, an associated database with microcoded facial, vocal, and body action elements, as well as observer ratings, is introduced.

Comparison of multi-modal early oral nutrition for the tolerance of oral nutrition with conventional care after major abdominal surgery: a prospective, randomized, single-blind trial.

PubMed

Sun, Da-Li; Li, Wei-Ming; Li, Shu-Min; Cen, Yun-Yun; Xu, Qing-Wen; Li, Yi-Jun; Sun, Yan-Bo; Qi, Yu-Xing; Lin, Yue-Ying; Yang, Ting; Lu, Qi-Ping; Xu, Peng-Yuan

2017-02-10

Early oral nutrition (EON) has been shown to improve recovery of gastrointestinal function, length of stay and mortality after abdominal surgery; however, early oral nutrition often fails during the first week after surgery. Here, a multi-modal early oral nutrition program is introduced to promote recovery of gastrointestinal function and tolerance of oral nutrition. Consecutive patients scheduled for abdominal surgery were randomized to the multimodal EON group or a group receiving conventional care. The primary endpoint was the time of first defecation. The secondary endpoints were outcomes and the cost-effectiveness ratio in treating infectious complications. The rate of infectious-free patients was regarded as the index of effectiveness. One hundred seven patients were randomly assigned to groups. Baseline characteristics were similar for both groups. In intention-to-treat analysis, the success rate of oral nutrition during the first week after surgery in the multimodal EON group was 44 (83.0%) versus 31 (57.4%) in the conventional care group (P = 0.004). Time to first defecation, time to flatus, recovery time of bowel sounds, and prolonged postoperative ileus were all less in the multimodal EON group (P < 0.05). The median postoperative length of stay in the multimodal EON group was 8 days (6, 12) versus 10 days (7, 18) in the conventional care group (P < 0.001). The total cost of treatment and nutritional support were also less in the multi-modal early oral nutrition group (P < 0.001). The effectiveness was 84.9 and 79.9% in the multimodal EON and conventional care group, respectively (P = 0.475). However, the cost-effectiveness ratio was USD 537.6 (506.1, 589.3) and USD 637.8 (593.9, 710.3), respectively (P < 0.001). The multi-modal early oral nutrition program was an effective way to improve tolerance of oral nutrition during the first week after surgery, decrease the length of stay and improve cost-effectiveness after abdominal surgery. Registration number: ChiCTR-TRC-14004395 . Registered 15 March 2014.

Comparison of the application of B-mode and strain elastography ultrasound in the estimation of lymph node metastasis of papillary thyroid carcinoma based on a radiomics approach.

PubMed

Liu, Tongtong; Ge, Xifeng; Yu, Jinhua; Guo, Yi; Wang, Yuanyuan; Wang, Wenping; Cui, Ligang

2018-06-21

B-mode ultrasound (B-US) and strain elastography ultrasound (SE-US) images have a potential to distinguish thyroid tumor with different lymph node (LN) status. The purpose of our study is to investigate whether the application of multi-modality images including B-US and SE-US can improve the discriminability of thyroid tumor with LN metastasis based on a radiomics approach. Ultrasound (US) images including B-US and SE-US images of 75 papillary thyroid carcinoma (PTC) cases were retrospectively collected. A radiomics approach was developed in this study to estimate LNs status of PTC patients. The approach included image segmentation, quantitative feature extraction, feature selection and classification. Three feature sets were extracted from B-US, SE-US, and multi-modality containing B-US and SE-US. They were used to evaluate the contribution of different modalities. A total of 684 radiomics features have been extracted in our study. We used sparse representation coefficient-based feature selection method with 10-bootstrap to reduce the dimension of feature sets. Support vector machine with leave-one-out cross-validation was used to build the model for estimating LN status. Using features extracted from both B-US and SE-US, the radiomics-based model produced an area under the receiver operating characteristic curve (AUC) [Formula: see text] 0.90, accuracy (ACC) [Formula: see text] 0.85, sensitivity (SENS) [Formula: see text] 0.77 and specificity (SPEC) [Formula: see text] 0.88, which was better than using features extracted from B-US or SE-US separately. Multi-modality images provided more information in radiomics study. Combining use of B-US and SE-US could improve the LN metastasis estimation accuracy for PTC patients.

Organisation of services for managing ADHD.

PubMed

Coghill, D R

2017-10-01

There is considerable variation in practice, both between and with different countries in the management of attention deficit hyperactivity disorder (ADHD). Whilst there is no one optimal model of service organisation there are general principles of care that can be introduced to reduce this variability. There are frequent debates and discussions about which professional group is best placed to manage ADHD at different points in the life cycle. Who delivers care is however less important than ensuring that training schemes provide adequate exposure, training and experience to both the core and non-core skills required to provide a comprehensive package of care. Most evidence-based guidelines recommend a multi-modal, multi-professional and multi-agency approach. Many also promote the use of both stepped care and shared care approaches for the management of ADHD. As most of those with ADHD continue to have ADHD-related problems into adulthood, it is important to consider how best to transition care into adulthood and think about who should deliver care to adults with ADHD. Young people with ADHD should generally be transferred to adult mental health services if they continue to have significant symptoms of ADHD or other coexisting conditions that require treatment. Unfortunately services for adults with ADHD remain relatively scarce across much of the world and some adult psychiatrists remain unsure of the diagnosis and uncertain about the appropriate use of ADHD medications in adults, but there is a strong case for increased services for adults. ADHD is on the one hand easy to treat; it is much more difficult to treat well. Although optimised care for ADHD requires routine measurement of outcomes, this often does not happen in routine clinical practice. Focusing on optimising symptoms and minimising adverse effects can significantly improve both short- and long-term outcomes.

Multi-mode reliability-based design of horizontal curves.

PubMed

Essa, Mohamed; Sayed, Tarek; Hussein, Mohamed

2016-08-01

Recently, reliability analysis has been advocated as an effective approach to account for uncertainty in the geometric design process and to evaluate the risk associated with a particular design. In this approach, a risk measure (e.g. probability of noncompliance) is calculated to represent the probability that a specific design would not meet standard requirements. The majority of previous applications of reliability analysis in geometric design focused on evaluating the probability of noncompliance for only one mode of noncompliance such as insufficient sight distance. However, in many design situations, more than one mode of noncompliance may be present (e.g. insufficient sight distance and vehicle skidding at horizontal curves). In these situations, utilizing a multi-mode reliability approach that considers more than one failure (noncompliance) mode is required. The main objective of this paper is to demonstrate the application of multi-mode (system) reliability analysis to the design of horizontal curves. The process is demonstrated by a case study of Sea-to-Sky Highway located between Vancouver and Whistler, in southern British Columbia, Canada. Two noncompliance modes were considered: insufficient sight distance and vehicle skidding. The results show the importance of accounting for several noncompliance modes in the reliability model. The system reliability concept could be used in future studies to calibrate the design of various design elements in order to achieve consistent safety levels based on all possible modes of noncompliance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-Modal Nano-Probes for Radionuclide and 5-color Near Infrared Optical Lymphatic Imaging

PubMed Central

Kobayashi, Hisataka; Koyama, Yoshinori; Barrett, Tristan; Hama, Yukihiro; Regino, Celeste A. S.; Shin, In Soo; Jang, Beom-Su; Le, Nhat; Paik, Chang H.; Choyke, Peter L.; Urano, Yasuteru

2008-01-01

Current contrast agents generally have one function and can only be imaged in monochrome, therefore, the majority of imaging methods can only impart uniparametric information. A single nano-particle has the potential to be loaded with multiple payloads. Such multi-modality probes have the ability to be imaged by more than one imaging technique, which could compensate for the weakness or even combine the advantages of each individual modality. Furthermore, optical imaging using different optical probes enables us to achieve multi-color in vivo imaging, wherein multiple parameters can be read from a single image. To allow differentiation of multiple optical signals in vivo, each probe should have a close but different near infrared emission. To this end, we synthesized nano-probes with multi-modal and multi-color potential, which employed a polyamidoamine dendrimer platform linked to both radionuclides and optical probes, permitting dual-modality scintigraphic and 5-color near infrared optical lymphatic imaging using a multiple excitation spectrally-resolved fluorescence imaging technique. PMID:19079788

Sparse Representation Based Frequency Detection and Uncertainty Reduction in Blade Tip Timing Measurement for Multi-Mode Blade Vibration Monitoring

PubMed Central

Pan, Minghao; Yang, Yongmin; Guan, Fengjiao; Hu, Haifeng; Xu, Hailong

2017-01-01

The accurate monitoring of blade vibration under operating conditions is essential in turbo-machinery testing. Blade tip timing (BTT) is a promising non-contact technique for the measurement of blade vibrations. However, the BTT sampling data are inherently under-sampled and contaminated with several measurement uncertainties. How to recover frequency spectra of blade vibrations though processing these under-sampled biased signals is a bottleneck problem. A novel method of BTT signal processing for alleviating measurement uncertainties in recovery of multi-mode blade vibration frequency spectrum is proposed in this paper. The method can be divided into four phases. First, a single measurement vector model is built by exploiting that the blade vibration signals are sparse in frequency spectra. Secondly, the uniqueness of the nonnegative sparse solution is studied to achieve the vibration frequency spectrum. Thirdly, typical sources of BTT measurement uncertainties are quantitatively analyzed. Finally, an improved vibration frequency spectra recovery method is proposed to get a guaranteed level of sparse solution when measurement results are biased. Simulations and experiments are performed to prove the feasibility of the proposed method. The most outstanding advantage is that this method can prevent the recovered multi-mode vibration spectra from being affected by BTT measurement uncertainties without increasing the probe number. PMID:28758952

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Multi-modal measurement of the myelin-to-axon diameter g-ratio in preterm-born neonates and adult controls.

PubMed

Melbourne, Andrew; Eaton-Rosen, Zach; De Vita, Enrico; Bainbridge, Alan; Cardoso, Manuel Jorge; Price, David; Cady, Ernest; Kendall, Giles S; Robertson, Nicola J; Marlow, Neil; Ourselin, Sébastien

2014-01-01

Infants born prematurely are at increased risk of adverse functional outcome. The measurement of white matter tissue composition and structure can help predict functional performance and this motivates the search for new multi-modal imaging biomarkers. In this work we develop a novel combined biomarker from diffusion MRI and multi-component T2 relaxation measurements in a group of infants born very preterm and scanned between 30 and 40 weeks equivalent gestational age. We also investigate this biomarker on a group of seven adult controls, using a multi-modal joint model-fitting strategy. The proposed emergent biomarker is tentatively related to axonal energetic efficiency (in terms of axonal membrane charge storage) and conduction velocity and is thus linked to the tissue electrical properties, giving it a good theoretical justification as a predictive measurement of functional outcome.

Investigating the Strain, Temperature and Humidity Sensitivity of a Multimode Graded-Index Perfluorinated Polymer Optical Fiber with Bragg Grating

PubMed Central

Zheng, Yulong; Bremer, Kort

2018-01-01

In this work we investigate the strain, temperature and humidity sensitivity of a Fiber Bragg Grating (FBG) inscribed in a near infrared low-loss multimode perfluorinated polymer optical fiber based on cyclic transparent optical polymer (CYTOP). For this purpose, FBGs were inscribed into the multimode CYTOP fiber with a core diameter of 50 µm by using a krypton fluoride (KrF) excimer laser and the phase mask method. The evolution of the reflection spectrum of the FBG detected with a multimode interrogation technique revealed a single reflection peak with a full width at half maximum (FHWM) bandwidth of about 9 nm. Furthermore, the spectral envelope of the single FBG reflection peak can be optimized depending on the KrF excimer laser irradiation time. A linear shift of the Bragg wavelength due to applied strain, temperature and humidity was measured. Furthermore, depending on irradiation time of the KrF excimer laser, both the failure strain and strain sensitivity of the multimode fiber with FBG can be controlled. The inherent low light attenuation in the near infrared wavelength range (telecommunication window) of the multimode CYTOP fiber and the single FBG reflection peak when applying the multimode interrogation set-up will allow for new applications in the area of telecommunication and optical sensing. PMID:29734734

Investigating the Strain, Temperature and Humidity Sensitivity of a Multimode Graded-Index Perfluorinated Polymer Optical Fiber with Bragg Grating.

PubMed

Zheng, Yulong; Bremer, Kort; Roth, Bernhard

2018-05-05

In this work we investigate the strain, temperature and humidity sensitivity of a Fiber Bragg Grating (FBG) inscribed in a near infrared low-loss multimode perfluorinated polymer optical fiber based on cyclic transparent optical polymer (CYTOP). For this purpose, FBGs were inscribed into the multimode CYTOP fiber with a core diameter of 50 µm by using a krypton fluoride (KrF) excimer laser and the phase mask method. The evolution of the reflection spectrum of the FBG detected with a multimode interrogation technique revealed a single reflection peak with a full width at half maximum (FHWM) bandwidth of about 9 nm. Furthermore, the spectral envelope of the single FBG reflection peak can be optimized depending on the KrF excimer laser irradiation time. A linear shift of the Bragg wavelength due to applied strain, temperature and humidity was measured. Furthermore, depending on irradiation time of the KrF excimer laser, both the failure strain and strain sensitivity of the multimode fiber with FBG can be controlled. The inherent low light attenuation in the near infrared wavelength range (telecommunication window) of the multimode CYTOP fiber and the single FBG reflection peak when applying the multimode interrogation set-up will allow for new applications in the area of telecommunication and optical sensing.

Revolution of Alzheimer Precision Neurology Passageway of Systems Biology and Neurophysiology.

PubMed

Hampel, Harald; Toschi, Nicola; Babiloni, Claudio; Baldacci, Filippo; Black, Keith L; Bokde, Arun L W; Bun, René S; Cacciola, Francesco; Cavedo, Enrica; Chiesa, Patrizia A; Colliot, Olivier; Coman, Cristina-Maria; Dubois, Bruno; Duggento, Andrea; Durrleman, Stanley; Ferretti, Maria-Teresa; George, Nathalie; Genthon, Remy; Habert, Marie-Odile; Herholz, Karl; Koronyo, Yosef; Koronyo-Hamaoui, Maya; Lamari, Foudil; Langevin, Todd; Lehéricy, Stéphane; Lorenceau, Jean; Neri, Christian; Nisticò, Robert; Nyasse-Messene, Francis; Ritchie, Craig; Rossi, Simone; Santarnecchi, Emiliano; Sporns, Olaf; Verdooner, Steven R; Vergallo, Andrea; Villain, Nicolas; Younesi, Erfan; Garaci, Francesco; Lista, Simone

2018-03-16

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Revolution of Alzheimer Precision Neurology: Passageway of Systems Biology and Neurophysiology

PubMed Central

Hampel, Harald; Toschi, Nicola; Babiloni, Claudio; Baldacci, Filippo; Black, Keith L.; Bokde, Arun L.W.; Bun, René S.; Cacciola, Francesco; Cavedo, Enrica; Chiesa, Patrizia A.; Colliot, Olivier; Coman, Cristina-Maria; Dubois, Bruno; Duggento, Andrea; Durrleman, Stanley; Ferretti, Maria-Teresa; George, Nathalie; Genthon, Remy; Habert, Marie-Odile; Herholz, Karl; Koronyo, Yosef; Koronyo-Hamaoui, Maya; Lamari, Foudil; Langevin, Todd; Lehéricy, Stéphane; Lorenceau, Jean; Neri, Christian; Nisticò, Robert; Nyasse-Messene, Francis; Ritchie, Craig; Rossi, Simone; Santarnecchi, Emiliano; Sporns, Olaf; Verdooner, Steven R.; Vergallo, Andrea; Villain, Nicolas; Younesi, Erfan; Garaci, Francesco; Lista, Simone

2018-01-01

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an “omics”-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer’s disease (AD). The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group “Alzheimer Precision Medicine” (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development towards breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND. PMID:29562524

TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

NASA Astrophysics Data System (ADS)

Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

2014-06-01

The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

DOE PAGES

Logan, Nikolas; Cui, L.; Wang, Hui -Hui; ...

2018-04-30

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized.more » Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.« less

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

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

Logan, Nikolas; Cui, L.; Wang, Hui -Hui

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized.more » Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.« less

A Single Session of rTMS Enhances Small-Worldness in Writer's Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph.

PubMed

Bharath, Rose D; Panda, Rajanikant; Reddam, Venkateswara Reddy; Bhaskar, M V; Gohel, Suril; Bhardwaj, Sujas; Prajapati, Arvind; Pal, Pramod Kumar

2017-01-01

Background and Purpose : Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method : Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result : A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI ( p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion : Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo . Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise".

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

3D hierarchical spatial representation and memory of multimodal sensory data

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine/robot degrees of freedom, the desired movements and action can be computed from these different levels in the hierarchy. The most basic embodiment of this machine could be a pan-tilt camera system, an array of microphones, a machine with arm/hand like structure or/and a robot with some or all of the above capabilities. We describe the approach, system and present preliminary results on a real-robotic platform.

Sex in the Curriculum: The Effect of a Multi-Modal Sexual History-Taking Module on Medical Student Skills

ERIC Educational Resources Information Center

Lindau, Stacy Tessler; Goodrich, Katie G.; Leitsch, Sara A.; Cook, Sandy

2008-01-01

Purpose: The objective of this study was to determine the effect of a multi-modal curricular intervention designed to teach sexual history-taking skills to medical students. The Association of Professors of Gynecology and Obstetrics, the National Board of Medical Examiners, and others, have identified sexual history-taking as a learning objective…

Final Technical Report

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

Rasure, John, et. al.

Through past DOE funding, the MIND Research network has funded a national consortium effort that used multi-modal neuroimaging, genetics, and clinical assessment of subjects to study schizophrenia in both first episode and persistently ill patients. Although active recruitment of research participants is complete, this consortium remains active and productive in terms of analysis of this unique multi-modal data collected on over 320 subjects.

Multi-Modal Interaction for Robotic Mules

DTIC Science & Technology

2014-02-26

Multi-Modal Interaction for Robotic Mules Glenn Taylor, Mike Quist, Matt Lanting, Cory Dunham , Patrick Theisen, Paul Muench Abstract...Taylor, Mike Quist, Matt Lanting, Cory Dunham , and Patrick Theisen are with Soar Technology, Inc. (corresponding author: 734-887- 7620; email: glenn...soartech.com; quist@soartech.com; matt.lanting@soartech.com; dunham @soartech.com; patrick.theisen@soartech.com Paul Muench is with US Army TARDEC

Ships/Trains/Planes/Automobiles: A Renaissance of their Interface

NASA Technical Reports Server (NTRS)

Allan, Stanley N.

1974-01-01

This paper highlights some of the major multi-modal interface problems created by technological advances, socio-political individualism and the flexibility of choices we expect from our transportation modes. The emphasis is on the need for a comprehensive national network of multi-modal priorities to enhance the movement of people and goods within the changing physical shape of our cities.

The sweet spot: FDG and other 2-carbon glucose analogs for multi-modal metabolic imaging of tumor metabolism

PubMed Central

Cox, Benjamin L; Mackie, Thomas R; Eliceiri, Kevin W

2015-01-01

Multi-modal imaging approaches of tumor metabolism that provide improved specificity, physiological relevance and spatial resolution would improve diagnosing of tumors and evaluation of tumor progression. Currently, the molecular probe FDG, glucose fluorinated with 18F at the 2-carbon, is the primary metabolic approach for clinical diagnostics with PET imaging. However, PET lacks the resolution necessary to yield intratumoral distributions of deoxyglucose, on the cellular level. Multi-modal imaging could elucidate this problem, but requires the development of new glucose analogs that are better suited for other imaging modalities. Several such analogs have been created and are reviewed here. Also reviewed are several multi-modal imaging studies that have been performed that attempt to shed light on the cellular distribution of glucose analogs within tumors. Some of these studies are performed in vitro, while others are performed in vivo, in an animal model. The results from these studies introduce a visualization gap between the in vitro and in vivo studies that, if solved, could enable the early detection of tumors, the high resolution monitoring of tumors during treatment, and the greater accuracy in assessment of different imaging agents. PMID:25625022

Multi-mode ultra-strong coupling (I): spectroscopic experiments using a vacuum-gap transmon circuit architecture

NASA Astrophysics Data System (ADS)

Bosman, Sal J.; Gely, Mario F.; Singh, Vibhor; Bruno, Alessandro; Bothner, Daniel; Steele, Gary A.

In circuit QED, multi-mode extensions of the quantum Rabi model suffer from divergence problems. Here, we spectroscopically study multi-mode ultra-strong coupling using a transmon circuit architecture, which provides no clear guidelines on how many modes play a role in the dynamics of the system. As our transmon qubit, we employ a suspended island above the voltage anti-node of a λ / 4 coplanar microwave resonator, thereby realising a circuit where 88% of the qubit capacitance is formed by a vacuum-gap capacitor with the center conductor of the resonator. We measure vacuum Rabi splitting over multiple modes up to 2 GHz, reaching coupling ratios of g / ω = 0 . 18 , well within the ultra-strong coupling regime. We observe a qubit-mediated mode coupling, measurable up to the fifth mode at 38 GHz. Using a novel analytical quantum circuit model of this architecture, which includes all modes without introducing divergencies, we are able to fit the full spectrum and extract a vacuum fluctuations induced Bloch-Siegert shift of up to 62 MHz. This circuit architecture expands the versatility of the transmon technology platform and opens many possibilities in multi-mode physics in the ultra-strong coupling regime.

Combined multi-modal photoacoustic tomography, optical coherence tomography (OCT) and OCT angiography system with an articulated probe for in vivo human skin structure and vasculature imaging

PubMed Central

Liu, Mengyang; Chen, Zhe; Zabihian, Behrooz; Sinz, Christoph; Zhang, Edward; Beard, Paul C.; Ginner, Laurin; Hoover, Erich; Minneman, Micheal P.; Leitgeb, Rainer A.; Kittler, Harald; Drexler, Wolfgang

2016-01-01

Cutaneous blood flow accounts for approximately 5% of cardiac output in human and plays a key role in a number of a physiological and pathological processes. We show for the first time a multi-modal photoacoustic tomography (PAT), optical coherence tomography (OCT) and OCT angiography system with an articulated probe to extract human cutaneous vasculature in vivo in various skin regions. OCT angiography supplements the microvasculature which PAT alone is unable to provide. Co-registered volumes for vessel network is further embedded in the morphologic image provided by OCT. This multi-modal system is therefore demonstrated as a valuable tool for comprehensive non-invasive human skin vasculature and morphology imaging in vivo. PMID:27699106

Monolithic optofluidic mode coupler for broadband thermo- and piezo-optical characterization of liquids.

PubMed

Pumpe, Sebastian; Chemnitz, Mario; Kobelke, Jens; Schmidt, Markus A

2017-09-18

We present a monolithic fiber device that enables investigation of the thermo- and piezo-optical properties of liquids using straightforward broadband transmission measurements. The device is a directional mode coupler consisting of a multi-mode liquid core and a single-mode glass core with pronounced coupling resonances whose wavelength strongly depend on the operation temperature. We demonstrated the functionality and flexibility of our device for carbon disulfide, extending the current knowledge of the thermo-optic coefficient by 200 nm at 20 °C and uniquely for high temperatures. Moreover, our device allows measuring the piezo-optic coefficient of carbon disulfide, confirming results first obtained by Röntgen in 1891. Finally, we applied our approach to obtain the dispersion of the thermo-optic coefficients of benzene and tetrachloroethylene between 450 and 800 nm, whereas no data was available for the latter so far.

Economic Analysis Framework for Freight Transportation Based on Florida Statewide Multi-Modal Freight Model

DOT National Transportation Integrated Search

2018-02-01

Freight transportation plays a vital role in local and regional economy. The markets and businesses from different regions and locations can be connected through freight movements. But it is difficult to quantify the economic contribution of freight ...

A Multi-D-Shaped Optical Fiber for Refractive Index Sensing

PubMed Central

Chen, Chien-Hsing; Tsao, Tzu-Chein; Tang, Jaw-Luen; Wu, Wei-Te

2010-01-01

A novel class of multi-D-shaped optical fiber suited for refractive index measurements is presented. The multi-D-shaped optical fiber was constructed by forming several D-sections in a multimode optical fiber at localized regions with femtosecond laser pulses. The total number of D-shaped zones fabricated could range from three to seven. Each D-shaped zone covered a sensor volume of 100 μm depth, 250 μm width, and 1 mm length. The mean roughness of the core surface obtained by the AFM images was 231.7 nm, which is relatively smooth. Results of the tensile test indicated that the fibers have sufficient mechanical strength to resist damage from further processing. The multi-D-shaped optical fiber as a high sensitive refractive-index sensor to detect changes in the surrounding refractive index was studied. The results for different concentrations of sucrose solution show that a resolution of 1.27 × 10−3–3.13 × 10−4 RIU is achieved for refractive indices in the range of 1.333 to 1.403, suggesting that the multi-D-shaped fibers are attractive for chemical, biological, and biochemical sensing with aqueous solutions. PMID:22399908

TiO2 -coated fluoride nanoparticles for dental multimodal optical imaging.

PubMed

Braz, Ana K S; Moura, Diógenes S; Gomes, Anderson S L; Ohulchanskyy, Tymish Y; Chen, Guanying; Liu, Maixian; Damasco, Jossana; de Araujo, Renato E; Prasad, Paras N

2018-04-01

Core-shell nanostructures associated with photonics techniques have found innumerous applications in diagnostics and therapy. In this work, we introduce a novel core-shell nanostructure design that serves as a multimodal optical imaging contrast agent for dental adhesion evaluation. This nanostructure consists of a rare-earth-doped (NaYF 4 :Yb 60%, Tm 0.5%)/NaYF 4 particle as the core (hexagonal prism, ~51 nm base side length) and the highly refractive TiO 2 material as the shell (~thickness of 15 nm). We show that the TiO 2 shell provides enhanced contrast for optical coherence tomography (OCT), while the rare-earth-doped core upconverts excitation light from 975 nm to an emission peaked at 800 nm for photoluminescence imaging. The OCT and the photoluminescence wide-field images of human tooth were demonstrated with this nanoparticle core-shell contrast agent. In addition, the described core-shell nanoparticles (CSNps) were dispersed in the primer of a commercially available dental bonding system, allowing clear identification of dental adhesive layers with OCT. We evaluated that the presence of the CSNp in the adhesive induced an enhancement of 67% scattering coefficient to significantly increase the OCT contrast. Moreover, our results highlight that the upconversion photoluminescence in the near-infrared spectrum region is suitable for image of deep dental tissue. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors.

PubMed

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-07-08

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Pre-Motor Response Time Benefits in Multi-Modal Displays

DTIC Science & Technology

2013-11-12

when animals are presented with stimuli from two sensory modalities as compared with stimulation from only one modality. The combinations of two...modality attention and orientation behaviors (see also Wallace, Meredith, & Stein, 609 !998). Multi-modal stimulation in the world is not always...perceptually when the stimuli are congruent. In another study, Craig (2006) had participants judge the direction of apparent motion by stimulating

Effective Beginning Handwriting Instruction: Multi-Modal, Consistent Format for 2 Years, and Linked to Spelling and Composing

ERIC Educational Resources Information Center

Wolf, Beverly; Abbott, Robert D.; Berninger, Virginia W.

2017-01-01

In Study 1, the treatment group (N = 33 first graders, M = 6 years 10 months, 16 girls) received Slingerland multi-modal (auditory, visual, tactile, motor through hand, and motor through mouth) manuscript (unjoined) handwriting instruction embedded in systematic spelling, reading, and composing lessons; and the control group (N = 16 first graders,…

Providing University Education in Physical Geography across the South Pacific Islands: Multi-Modal Course Delivery and Student Grade Performance

ERIC Educational Resources Information Center

Terry, James P.; Poole, Brian

2012-01-01

Enormous distances across the vast South Pacific hinder student access to the main Fiji campus of the regional tertiary education provider, the University of the South Pacific (USP). Fortunately, USP has been a pioneer in distance education (DE) and promotes multi-modal delivery of programmes. Geography has embraced DE, but doubts remain about…

Multiplexed single-mode wavelength-to-time mapping of multimode light

PubMed Central

Chandrasekharan, Harikumar K; Izdebski, Frauke; Gris-Sánchez, Itandehui; Krstajić, Nikola; Walker, Richard; Bridle, Helen L.; Dalgarno, Paul A.; MacPherson, William N.; Henderson, Robert K.; Birks, Tim A.; Thomson, Robert R.

2017-01-01

When an optical pulse propagates along an optical fibre, different wavelengths travel at different group velocities. As a result, wavelength information is converted into arrival-time information, a process known as wavelength-to-time mapping. This phenomenon is most cleanly observed using a single-mode fibre transmission line, where spatial mode dispersion is not present, but the use of such fibres restricts possible applications. Here we demonstrate that photonic lanterns based on tapered single-mode multicore fibres provide an efficient way to couple multimode light to an array of single-photon avalanche detectors, each of which has its own time-to-digital converter for time-correlated single-photon counting. Exploiting this capability, we demonstrate the multiplexed single-mode wavelength-to-time mapping of multimode light using a multicore fibre photonic lantern with 121 single-mode cores, coupled to 121 detectors on a 32 × 32 detector array. This work paves the way to efficient multimode wavelength-to-time mapping systems with the spectral performance of single-mode systems. PMID:28120822

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Who acquires infection from whom and how? Disentangling multi-host and multi-mode transmission dynamics in the ‘elimination’ era

PubMed Central

Borlase, Anna; Rudge, James W.

2017-01-01

Multi-host infectious agents challenge our abilities to understand, predict and manage disease dynamics. Within this, many infectious agents are also able to use, simultaneously or sequentially, multiple modes of transmission. Furthermore, the relative importance of different host species and modes can itself be dynamic, with potential for switches and shifts in host range and/or transmission mode in response to changing selective pressures, such as those imposed by disease control interventions. The epidemiology of such multi-host, multi-mode infectious agents thereby can involve a multi-faceted community of definitive and intermediate/secondary hosts or vectors, often together with infectious stages in the environment, all of which may represent potential targets, as well as specific challenges, particularly where disease elimination is proposed. Here, we explore, focusing on examples from both human and animal pathogen systems, why and how we should aim to disentangle and quantify the relative importance of multi-host multi-mode infectious agent transmission dynamics under contrasting conditions, and ultimately, how this can be used to help achieve efficient and effective disease control. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289259

Multi-modality PET-CT imaging of breast cancer in an animal model using nanoparticle x-ray contrast agent and 18F-FDG

NASA Astrophysics Data System (ADS)

Badea, C. T.; Ghaghada, K.; Espinosa, G.; Strong, L.; Annapragada, A.

2011-03-01

Multi-modality PET-CT imaging is playing an important role in the field of oncology. While PET imaging facilitates functional interrogation of tumor status, the use of CT imaging is primarily limited to anatomical reference. In an attempt to extract comprehensive information about tumor cells and its microenvironment, we used a nanoparticle xray contrast agent to image tumor vasculature and vessel 'leakiness' and 18F-FDG to investigate the metabolic status of tumor cells. In vivo PET/CT studies were performed in mice implanted with 4T1 mammary breast cancer cells.Early-phase micro-CT imaging enabled visualization 3D vascular architecture of the tumors whereas delayedphase micro-CT demonstrated highly permeable vessels as evident by nanoparticle accumulation within the tumor. Both imaging modalities demonstrated the presence of a necrotic core as indicated by a hypo-enhanced region in the center of the tumor. At early time-points, the CT-derived fractional blood volume did not correlate with 18F-FDG uptake. At delayed time-points, the tumor enhancement in 18F-FDG micro-PET images correlated with the delayed signal enhanced due to nanoparticle extravasation seen in CT images. The proposed hybrid imaging approach could be used to better understand tumor angiogenesis and to be the basis for monitoring and evaluating anti-angiogenic and nano-chemotherapies.

Thermoresponsive core-shell magnetic nanoparticles for combined modalities of cancer therapy.

PubMed

Purushotham, S; Chang, P E J; Rumpel, H; Kee, I H C; Ng, R T H; Chow, P K H; Tan, C K; Ramanujan, R V

2009-07-29

Thermoresponsive polymer-coated magnetic nanoparticles loaded with anti-cancer drugs are of considerable interest for novel multi-modal cancer therapies. Such nanoparticles can be used for magnetic drug targeting followed by simultaneous hyperthermia and drug release. Gamma-Fe(2)O(3) iron oxide magnetic nanoparticles (MNP) with average sizes of 14, 19 and 43 nm were synthesized by high temperature decomposition. Composite magnetic nanoparticles (CNP) of 43 nm MNP coated with the thermoresponsive polymer poly-n-isopropylacrylamide (PNIPAM) were prepared by dispersion polymerization of n-isopropylacrylamide monomer in the presence of the MNP. In vitro drug release of doxorubicin-(dox) loaded dehydrated CNP at temperatures below and above the lower critical solution temperature of PNIPAM (34 degrees C) revealed a weak dependence of drug release on swelling behavior. The particles displayed Fickian diffusion release kinetics; the maximum dox release at 42 degrees C after 101 h was 41%. In vitro simultaneous hyperthermia and drug release of therapeutically relevant quantities of dox was achieved, 14.7% of loaded dox was released in 47 min at hyperthermia temperatures. In vivo magnetic targeting of dox-loaded CNP to hepatocellular carcinoma (HCC) in a buffalo rat model was studied by magnetic resonance imaging (MRI) and histology. In summary, the good in vitro and in vivo performance of the doxorubicin-loaded thermoresponsive polymer-coated magnetic nanoparticles suggests considerable promise for applications in multi-modal treatment of cancer.

Magnetic polarization measurements of the multi-modal plasma response to 3D fields in the EAST tokamak

NASA Astrophysics Data System (ADS)

Logan, N. C.; Cui, L.; Wang, H.; Sun, Y.; Gu, S.; Li, G.; Nazikian, R.; Paz-Soldan, C.

2018-07-01

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n  =  2 fields in the same plasma for which the n  =  1 responses are well synchronized. Neither the maximum radial nor the maximum poloidal field response to n  =  2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n  =  1 and n  =  2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.

Multimodal freight investment criteria.

DOT National Transportation Integrated Search

2010-07-01

Literature was reviewed on multi-modal investment criteria for freight projects, examining measures and techniques for quantifying project benefits and costs, as well as ways to describe the economic importance of freight transportation. : A limited ...

High-beam quality, high-efficiency laser based on fiber with heavily Yb(3+)-doped phosphate core and silica cladding.

PubMed

Egorova, O N; Semjonov, S L; Medvedkov, O I; Astapovich, M S; Okhrimchuk, A G; Galagan, B I; Denker, B I; Sverchkov, S E; Dianov, E M

2015-08-15

We have fabricated and tested a composite fiber with an Yb(3+)-doped phosphate glass core and silica cladding. Oscillation with a slope efficiency of 74% was achieved using core pumping at 976 nm with fiber lengths of 48-90 mm in a simple laser configuration, where the cavity was formed by a high-reflectivity Bragg grating and the cleaved fiber end. The measured M(2) factors were as low as 1.05-1.22 even though the fiber was multimode at the lasing wavelength.

Cross-Discipline Bio-Nanostructured Enhanced Photonic Multimode-Sensor Science

DTIC Science & Technology

2017-05-23

experimental study aimed to combine soft material science with nanotechnology and multi-physics modeling to produce adaptable bio-nanostructure based on...degradation through optical analysis and tracking programs Protein and DNA engineering . - The properties of proteins to be used in sensors were studies

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Refractive index sensors based on the fused tapered special multi-mode fiber

NASA Astrophysics Data System (ADS)

Fu, Xing-hu; Xiu, Yan-li; Liu, Qin; Xie, Hai-yang; Yang, Chuan-qing; Zhang, Shun-yang; Fu, Guang-wei; Bi, Wei-hong

2016-01-01

In this paper, a novel refractive index (RI) sensor is proposed based on the fused tapered special multi-mode fiber (SMMF). Firstly, a section of SMMF is spliced between two single-mode fibers (SMFs). Then, the SMMF is processed by a fused tapering machine, and a tapered fiber structure is fabricated. Finally, a fused tapered SMMF sensor is obtained for measuring external RI. The RI sensing mechanism of tapered SMMF sensor is analyzed in detail. For different fused tapering lengths, the experimental results show that the RI sensitivity can be up to 444.517 81 nm/RIU in the RI range of 1.334 9—1.347 0. The RI sensitivity is increased with the increase of fused tapering length. Moreover, it has many advantages, including high sensitivity, compact structure, fast response and wide application range. So it can be used to measure the solution concentration in the fields of biochemistry, health care and food processing.

Hierarchical patch-based co-registration of differently stained histopathology slides

NASA Astrophysics Data System (ADS)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

PubMed Central

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-01-01

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. PMID:24335727

Demonstration of glass-based photonic interposer for mid-board-optical engines and electrical-optical circuit board (EOCB) integration strategy

NASA Astrophysics Data System (ADS)

Schröder, H.; Neitz, M.; Schneider-Ramelow, M.

2018-02-01

Due to its optical transparency and superior dielectric properties glass is regarded as a promising candidate for advanced applications as active photonic interposer for mid-board-optics and optical PCB waveguide integration. The concepts for multi-mode and single-mode photonic system integration are discussed and related demonstration project results will be presented. A hybrid integrated photonic glass body interposer with integrated optical lenses for multi-mode data communication wavelength of 850 nm have been realized. The paper summarizes process developments which allow cost efficient metallization of TGV. Electro-optical elements like photodiodes and VCSELs can be directly flip-chip mounted on the glass substrate according to the desired lens positions. Furthermore results for a silicon photonic based single-mode active interposer integration onto a single mode glass made EOCB will be compared in terms of packaging challenges. The board level integration strategy for both of these technological approaches and general next generation board level integration concepts for photonic interposer will be introductorily discussed.

Fall risk assessment and early-warning for toddler behaviors at home.

PubMed

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-12-10

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second.

Sensor-Based Human Activity Recognition in a Multi-user Scenario

NASA Astrophysics Data System (ADS)

Wang, Liang; Gu, Tao; Tao, Xianping; Lu, Jian

Existing work on sensor-based activity recognition focuses mainly on single-user activities. However, in real life, activities are often performed by multiple users involving interactions between them. In this paper, we propose Coupled Hidden Markov Models (CHMMs) to recognize multi-user activities from sensor readings in a smart home environment. We develop a multimodal sensing platform and present a theoretical framework to recognize both single-user and multi-user activities. We conduct our trace collection done in a smart home, and evaluate our framework through experimental studies. Our experimental result shows that we achieve an average accuracy of 85.46% with CHMMs.

Diagnostic for two-mode variable valve activation device

DOEpatents

Fedewa, Andrew M

2014-01-07

A method is provided for diagnosing a multi-mode valve train device which selectively provides high lift and low lift to a combustion valve of an internal combustion engine having a camshaft phaser actuated by an electric motor. The method includes applying a variable electric current to the electric motor to achieve a desired camshaft phaser operational mode and commanding the multi-mode valve train device to a desired valve train device operational mode selected from a high lift mode and a low lift mode. The method also includes monitoring the variable electric current and calculating a first characteristic of the parameter. The method also includes comparing the calculated first characteristic against a predetermined value of the first characteristic measured when the multi-mode valve train device is known to be in the desired valve train device operational mode.

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

2011-06-01

We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

Reconstructing multi-mode networks from multivariate time series

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Yang, Yu-Xuan; Dang, Wei-Dong; Cai, Qing; Wang, Zhen; Marwan, Norbert; Boccaletti, Stefano; Kurths, Jürgen

2017-09-01

Unveiling the dynamics hidden in multivariate time series is a task of the utmost importance in a broad variety of areas in physics. We here propose a method that leads to the construction of a novel functional network, a multi-mode weighted graph combined with an empirical mode decomposition, and to the realization of multi-information fusion of multivariate time series. The method is illustrated in a couple of successful applications (a multi-phase flow and an epileptic electro-encephalogram), which demonstrate its powerfulness in revealing the dynamical behaviors underlying the transitions of different flow patterns, and enabling to differentiate brain states of seizure and non-seizure.

Revealing Spatial Variation and Correlation of Urban Travels from Big Trajectory Data

NASA Astrophysics Data System (ADS)

Li, X.; Tu, W.; Shen, S.; Yue, Y.; Luo, N.; Li, Q.

2017-09-01

With the development of information and communication technology, spatial-temporal data that contain rich human mobility information are growing rapidly. However, the consistency of multi-mode human travel behind multi-source spatial-temporal data is not clear. To this aim, we utilized a week of taxies' and buses' GPS trajectory data and smart card data in Shenzhen, China to extract city-wide travel information of taxi, bus and metro and tested the correlation of multi-mode travel characteristics. Both the global correlation and local correlation of typical travel indicator were examined. The results show that: (1) Significant differences exist in of urban multi-mode travels. The correlation between bus travels and taxi travels, metro travel and taxi travels are globally low but locally high. (2) There are spatial differences of the correlation relationship between bus, metro and taxi travel. These findings help us understanding urban travels deeply therefore facilitate both the transport policy making and human-space interaction research.

A Multi-Mode Blade Damping Control using Shunted Piezoelectric Transducers with Active Feedback Structure

NASA Technical Reports Server (NTRS)

Choi, Benjamin; Morrison, Carlos; Min, James

2009-01-01

The Structural Dynamics and. Mechanics branch (RXS) is developing smart adaptive structures to improve fan blade damping at resonances using piezoelectric (PE) transducers. In this presentation, only one shunted PE transducer was used to demonstrate active control of multi-mode blade resonance damping on a titanium alloy (Ti-6A1-4V) flat plate model, regardless of bending, torsion, and 2-stripe modes. This work would have a significant impact on the conventional passive shunt damping world because the standard feedback control design tools can now be used to design and implement electric shunt for vibration control. In other words, the passive shunt circuit components using massive inductors and. resistors for multi-mode resonance control can be replaced with digital codes. Furthermore, this active approach with multi patches can simultaneously control several modes in the engine operating range. Dr. Benjamin Choi presented the analytical and experimental results from this work at the Propulsion-Safety and. Affordable Readiness (P-SAR) Conference in March, 2009.

Prussian blue nanocubes: multi-functional nanoparticles for multimodal imaging and image-guided therapy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cook, Jason R.; Dumani, Diego S.; Kubelick, Kelsey P.; Luci, Jeffrey; Emelianov, Stanislav Y.

2017-03-01

Imaging modalities utilize contrast agents to improve morphological visualization and to assess functional and molecular/cellular information. Here we present a new type of nanometer scale multi-functional particle that can be used for multi-modal imaging and therapeutic applications. Specifically, we synthesized monodisperse 20 nm Prussian Blue Nanocubes (PBNCs) with desired optical absorption in the near-infrared region and superparamagnetic properties. PBNCs showed excellent contrast in photoacoustic (700 nm wavelength) and MR (3T) imaging. Furthermore, photostability was assessed by exposing the PBNCs to nearly 1,000 laser pulses (5 ns pulse width) with up to 30 mJ/cm2 laser fluences. The PBNCs exhibited insignificant changes in photoacoustic signal, demonstrating enhanced robustness compared to the commonly used gold nanorods (substantial photodegradation with fluences greater than 5 mJ/cm2). Furthermore, the PBNCs exhibited superparamagnetism with a magnetic saturation of 105 emu/g, a 5x improvement over superparamagnetic iron-oxide (SPIO) nanoparticles. PBNCs exhibited enhanced T2 contrast measured using 3T clinical MRI. Because of the excellent optical absorption and magnetism, PBNCs have potential uses in other imaging modalities including optical tomography, microscopy, magneto-motive OCT/ultrasound, etc. In addition to multi-modal imaging, the PBNCs are multi-functional and, for example, can be used to enhance magnetic delivery and as therapeutic agents. Our initial studies show that stem cells can be labeled with PBNCs to perform image-guided magnetic delivery. Overall, PBNCs can act as imaging/therapeutic agents in diverse applications including cancer, cardiovascular disease, ophthalmology, and tissue engineering. Furthermore, PBNCs are based on FDA approved Prussian Blue thus potentially easing clinical translation of PBNCs.

Development of a Hybrid Optical Biopsy Probe to Improve Prostate Cancer Diagnosis

DTIC Science & Technology

2012-06-01

can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for the study are (1) light...which collect light scattering and auto-fluorescence from the prostate tissue, into a transrectal- ultrasound , needle - biopsy probe. In the...probe can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for the study were

Development of a Hybrid Optical Biopsy Probe to Improve Prostate Cancer Diagnosis

DTIC Science & Technology

2011-06-01

integrated needle probe can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for... needle probe can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for the study...tissue, into a transrectal- ultrasound , needle - biopsy probe. In the development phase, documentation to obtain IRB approval for ex vivo human prostate

Identification of multi-modal plasma responses to applied magnetic perturbations using the plasma reluctance

DOE PAGES

Logan, Nikolas C.; Paz-Soldan, Carlos; Park, Jong-Kyu; ...

2016-05-03

Using the plasma reluctance, the Ideal Perturbed Equilibrium Code is able to efficiently identify the structure of multi-modal magnetic plasma response measurements and the corresponding impact on plasma performance in the DIII-D tokamak. Recent experiments demonstrated that multiple kink modes of comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n = 2. This multi-modal response is in good agreement with ideal magnetohydrodynamic models, but detailed decompositions presented here show that the mode structures are not fully described by either the least stable modes or the resonant plasma response. This paper identifies the measured response fieldsmore » as the first eigenmodes of the plasma reluctance, enabling clear diagnosis of the plasma modes and their impact on performance from external sensors. The reluctance shows, for example, how very stable modes compose a significant portion of the multi-modal plasma response field and that these stable modes drive significant resonant current. Finally, this work is an overview of the first experimental applications using the reluctance to interpret the measured response and relate it to multifaceted physics, aimed towards providing the foundation of understanding needed to optimize nonaxisymmetric fields for independent control of stability and transport.« less

Nanomaterials for regulating cancer and stem cell fate

NASA Astrophysics Data System (ADS)

Shah, Birju P.

The realm of nanomedicine has grown exponentially over the past few decades. However, there are several obstacles that need to be overcome, prior to the wide-spread clinical applications of these nanoparticles, such as (i) developing well-defined nanoparticles of varying size, morphology and composition to enable various clinical applications; (ii) overcome various physiological barriers encountered in order to deliver the therapeutics to the target location; and (iii) real-time monitoring of the nano-therapeutics within the human body for tracking their uptake, localization and effect. Hence, this dissertation focuses on developing multimodal nanotechnology-based approaches to overcome the above-mentioned challenges and thus enable regulation of cancer and stem cell fate. The initial part of this dissertation describes the development of multimodal magnetic core-shell nanoparticles (MCNPs), comprised of a highly magnetic core surrounded by a thin gold shell, thus combining magnetic and plasmonic properties. These nanoparticles were utilized for mainly two applications: (i) Magnetically-facilitated delivery of siRNA and plasmid DNA for effective stem cell differentiation and imaging and (ii) Combined hyperthermia and targeted delivery of a mitochondria-targeting peptide for enhancing apoptosis in cancer cells. The following part of this dissertation presents the generation of a multi-functional cyclodextrin-conjugated polymeric delivery platform (known as DexAMs), for co-delivery of anticancer drugs and siRNAs in a target-specific manner to brain tumor cells. This combined delivery of chemotherapeutics and siRNA resulted in a synergistic effect on the apoptosis of brain tumor cells, as compared to the individual treatments. The final part of this thesis presents development of stimuli-responsive uorescence resonance energy transfer (FRET)-based mesoporous silica nanoparticles for real-time monitoring of drug release in cells. The stimuli-responsive behavior of these nanoparticles resulted in change in the FRET signal, thus allowing for real time monitoring of drug release. Taken together, these nanomaterial-based approaches combine therapeutic and imaging modalities within a single nanoplatform and as a result have the potential for regulating cancer and stem cell fate such as proliferation, differentiation and apoptosis as well as allowing for real-time monitoring of these events in a non-invasive manner.

Silicon-on-insulator multimode-interference waveguide-based arrayed optical tweezers (SMART) for two-dimensional microparticle trapping and manipulation.

PubMed

Lei, Ting; Poon, Andrew W

2013-01-28

We demonstrate two-dimensional optical trapping and manipulation of 1 μm and 2.2 μm polystyrene particles in an 18 μm-thick fluidic cell at a wavelength of 1565 nm using the recently proposed Silicon-on-insulator Multimode-interference (MMI) waveguide-based ARrayed optical Tweezers (SMART) technique. The key component is a 100 μm square-core silicon waveguide with mm length. By tuning the fiber-coupling position at the MMI waveguide input facet, we demonstrate various patterns of arrayed optical tweezers that enable optical trapping and manipulation of particles. We numerically simulate the physical mechanisms involved in the arrayed trap, including the optical force, the heat transfer and the thermal-induced microfluidic flow.

Dynamic configuration management of a multi-standard and multi-mode reconfigurable multi-ASIP architecture for turbo decoding

NASA Astrophysics Data System (ADS)

Lapotre, Vianney; Gogniat, Guy; Baghdadi, Amer; Diguet, Jean-Philippe

2017-12-01

The multiplication of connected devices goes along with a large variety of applications and traffic types needing diverse requirements. Accompanying this connectivity evolution, the last years have seen considerable evolutions of wireless communication standards in the domain of mobile telephone networks, local/wide wireless area networks, and Digital Video Broadcasting (DVB). In this context, intensive research has been conducted to provide flexible turbo decoder targeting high throughput, multi-mode, multi-standard, and power consumption efficiency. However, flexible turbo decoder implementations have not often considered dynamic reconfiguration issues in this context that requires high speed configuration switching. Starting from this assessment, this paper proposes the first solution that allows frame-by-frame run-time configuration management of a multi-processor turbo decoder without compromising the decoding performances.

Multi-Modal Treatment of Nocturnal Enuresis.

ERIC Educational Resources Information Center

Mohr, Caroline; Sharpley, Christopher F.

1988-01-01

The article reports a multimodal treatment of nocturnal enuresis and anxious behavior in a mildly mentally retarded woman. Behavioral treatment and removal of caffeine from the subject's diet eliminated both nocturnal enuresis and anxious behavior. (Author/DB)

Calibration of microsimulation models for multimodal freight networks.

DOT National Transportation Integrated Search

2012-06-01

This research presents a framework for incorporating the unique operating characteristics of multi-modal freight networks : into the calibration process for microscopic traffic simulation models. Because of the nature of heavy freight movements : in ...

The Impact Of Multimode Fiber Chromatic Dispersion On Data Communications

NASA Astrophysics Data System (ADS)

Hackert, Michael J.

1990-01-01

Capability for the lowest cost is the goal of contemporary communications managers. With all of the competitive pressures that modern businesses are experiencing these days, communications needs must be met with the most information carrying capacity for the lowest cost. Optical fiber communication systems meet these requirements while providing reliability, system integrity, and potential future upgradability. Consequently, optical fiber is finding numerous applications in addition to its traditional telephony plant. Fiber based systems are meeting these requirements in building networks and computer interconnects at a lower cost than copper based systems. A fiber type being chosen by industry to meet these needs in standard systems such as FDDI, is multimode fiber. Multimode fiber systems offer cost advantages over single-mode fiber through lower fiber connection costs. Also, system designers can gain savings by using low cost, high reliability, wide spectral width sources such as LEDs instead of lasers and by operating at higher bit rates than used for multimode systems in the past. However, in order to maximize the cost savings while ensuring the system will operate as intended, the chromatic dispersion of the fiber must be taken into account. This paper explains how to do that and shows how to calculate multimode chromatic dispersion for each of the standard fiber sizes (50 μm, 62.5 μm, 85 μm, and 100μm core diameter).

Multimodality imaging of ovarian cystic lesions: Review with an imaging based algorithmic approach

PubMed Central

Wasnik, Ashish P; Menias, Christine O; Platt, Joel F; Lalchandani, Usha R; Bedi, Deepak G; Elsayes, Khaled M

2013-01-01

Ovarian cystic masses include a spectrum of benign, borderline and high grade malignant neoplasms. Imaging plays a crucial role in characterization and pretreatment planning of incidentally detected or suspected adnexal masses, as diagnosis of ovarian malignancy at an early stage is correlated with a better prognosis. Knowledge of differential diagnosis, imaging features, management trends and an algorithmic approach of such lesions is important for optimal clinical management. This article illustrates a multi-modality approach in the diagnosis of a spectrum of ovarian cystic masses and also proposes an algorithmic approach for the diagnosis of these lesions. PMID:23671748

Rapid multi-modality preregistration based on SIFT descriptor.

PubMed

Chen, Jian; Tian, Jie

2006-01-01

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

Multi-Sensor Based State Prediction for Personal Mobility Vehicles

PubMed Central

Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

2016-01-01

This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of “loss of controllability”, change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given. PMID:27732589

Multi-Sensor Based State Prediction for Personal Mobility Vehicles.

PubMed

Abdur-Rahim, Jamilah; Morales, Yoichi; Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

2016-01-01

This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of "loss of controllability", change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given.

Design of miniaturized illumination for transvaginal co-registered photoacoustic and ultrasound imaging

PubMed Central

Salehi, Hassan S.; Wang, Tianheng; Kumavor, Patrick D.; Li, Hai; Zhu, Quing

2014-01-01

A novel lens-array based illumination design for a compact co-registered photoacoustic/ultrasound transvaginal probe has been demonstrated. The lens array consists of four cylindrical lenses that couple the laser beams into four 1-mm-core multi-mode optical fibers with optical coupling efficiency of ~87%. The feasibility of our lens array was investigated by simulating the lenses and laser beam profiles using Zemax. The laser fluence on the tissue surface was experimentally measured and was below the American National Standards Institute (ANSI) safety limit. Spatial distribution of hemoglobin oxygen saturation (sO2) of a mouse tumor was obtained in vivo using photoacoustic measurements at multiple wavelengths. Furthermore, benign and malignant ovaries were imaged ex vivo and evaluated histologically. The co-registered images clearly showed different patterns of blood vasculature. These results highlight the clinical potential of our system for noninvasive photoacoustic and ultrasound imaging of ovarian tissue and cancer detection and diagnosis. PMID:25401021

Multimodal treatment in children and adolescents with attention-deficit/hyperactivity disorder: a 6-month follow-up.

PubMed

Duric, Nezla S; Assmus, Jørg; Gundersen, Doris; Duric Golos, Alisa; Elgen, Irene B

2017-07-01

Different treatment approaches aimed at reducing attention-deficit/hyperactivity disorder (ADHD) core symptoms are available. However, factors such as intolerance, side-effects, lack of efficacy, high new technology costs, and placebo effect have spurred on an increasing interest in alternative or complementary treatment. The aim of this study is to explore efficacy of multimodal treatment consisting of standard stimulant medication (methylphenidate) and neurofeedback (NF) in combination, and to compare it with the single treatment in 6-month follow-up in ADHD children and adolescents. This randomized controlled trial with 6-month follow-up comprised three treatment arms: multimodal treatment (NF + MED), MED alone, and NF alone. A total of 130 ADHD children/adolescents participated, and 62% completed the study. ADHD core symptoms were recorded pre-/post-treatment, using parents' and teachers' forms taken from Barkley's Defiant Children: A Clinician's Manual for Assessment and Parent Training, and a self-report questionnaire. Significant ADHD core symptom improvements were reported 6 months after treatment completion by parents, teachers, and participants in all three groups, with marked improvement in inattention in all groups. However, no significant improvements in hyperactivity or academic performance were reported by teachers or self-reported by children/adolescents, respectively, in the three groups. Changes obtained with multimodal treatment at 6-month follow-up were comparable to those with single medication treatment, as reported by all participants. Multimodal treatment using combined stimulant medication and NF showed 6-month efficacy in ADHD treatment. More research is needed to explore whether multimodal treatment is suitable for ADHD children and adolescents who showed a poor response to single medication treatment, and for those who want to reduce the use of stimulant medication.

Integrated cladding-pumped multicore few-mode erbium-doped fibre amplifier for space-division-multiplexed communications

NASA Astrophysics Data System (ADS)

Chen, H.; Jin, C.; Huang, B.; Fontaine, N. K.; Ryf, R.; Shang, K.; Grégoire, N.; Morency, S.; Essiambre, R.-J.; Li, G.; Messaddeq, Y.; Larochelle, S.

2016-08-01

Space-division multiplexing (SDM), whereby multiple spatial channels in multimode and multicore optical fibres are used to increase the total transmission capacity per fibre, is being investigated to avert a data capacity crunch and reduce the cost per transmitted bit. With the number of channels employed in SDM transmission experiments continuing to rise, there is a requirement for integrated SDM components that are scalable. Here, we demonstrate a cladding-pumped SDM erbium-doped fibre amplifier (EDFA) that consists of six uncoupled multimode erbium-doped cores. Each core supports three spatial modes, which enables the EDFA to amplify a total of 18 spatial channels (six cores × three modes) simultaneously with a single pump diode and a complexity similar to a single-mode EDFA. The amplifier delivers >20 dBm total output power per core and <7 dB noise figure over the C-band. This cladding-pumped EDFA enables combined space-division and wavelength-division multiplexed transmission over multiple multimode fibre spans.

Mission Capability Gains from Multi-Mode Propulsion Thrust Profile Variations for a Plane Change Maneuver

DTIC Science & Technology

2010-12-29

propellant mass [kg] msc = mass of the spacecraft [kg] MMP = multi-mode propulsion   = position in the Geocentric Equatorial Reference...thrust burn time [s] Tsc = thrust of the spacecraft [N] = vector between current and final velocity vector   = velocity vector in the Geocentric ...Equatorial Reference Frame of spacecraft in intended orbit [km/s]   = velocity vector in the Geocentric Equatorial Reference Frame of spacecraft in

Mode synthesizing atomic force microscopy and mode-synthesizing sensing

DOEpatents

Passian, Ali; Thundat, Thomas George; Tetard, Laurene

2013-05-17

A method of analyzing a sample that includes applying a first set of energies at a first set of frequencies to a sample and applying, simultaneously with the applying the first set of energies, a second set of energies at a second set of frequencies, wherein the first set of energies and the second set of energies form a multi-mode coupling. The method further includes detecting an effect of the multi-mode coupling.

Mode-synthesizing atomic force microscopy and mode-synthesizing sensing

DOEpatents

Passain, Ali; Thundat, Thomas George; Tetard, Laurene

2014-07-22

A method of analyzing a sample that includes applying a first set of energies at a first set of frequencies to a sample and applying, simultaneously with the applying the first set of energies, a second set of energies at a second set of frequencies, wherein the first set of energies and the second set of energies form a multi-mode coupling. The method further includes detecting an effect of the multi-mode coupling.

A collaborative interaction and visualization multi-modal environment for surgical planning.

PubMed

Foo, Jung Leng; Martinez-Escobar, Marisol; Peloquin, Catherine; Lobe, Thom; Winer, Eliot

2009-01-01

The proliferation of virtual reality visualization and interaction technologies has changed the way medical image data is analyzed and processed. This paper presents a multi-modal environment that combines a virtual reality application with a desktop application for collaborative surgical planning. Both visualization applications can function independently but can also be synced over a network connection for collaborative work. Any changes to either application is immediately synced and updated to the other. This is an efficient collaboration tool that allows multiple teams of doctors with only an internet connection to visualize and interact with the same patient data simultaneously. With this multi-modal environment framework, one team working in the VR environment and another team from a remote location working on a desktop machine can both collaborate in the examination and discussion for procedures such as diagnosis, surgical planning, teaching and tele-mentoring.

Efficient implementation of arbitrary quantum state engineering in four-state system by counterdiabatic driving

NASA Astrophysics Data System (ADS)

Wang, Song-Bai; Chen, Ye-Hong; Wu, Qi-Cheng; Shi, Zhi-Cheng; Huang, Bi-Hua; Song, Jie; Xia, Yan

2018-07-01

A scheme is proposed to implement quantum state engineering (QSE) in a four-state system via counterdiabatic driving. In the scheme, single- and multi-mode driving methods are used respectively to drive the system to a target state at a predefined time. It is found that a fast QSE can be realized by utilizing simply designed pulses. In addition, a beneficial discussion on the energy consumption between the single- and multi-mode driving protocols shows that the multi-mode driving method seems to have a wider range of applications than the single-mode driving method with respect to different parameters. Finally, the scheme is also helpful for implementing the generalization QSE in high-dimensional systems via the concept of a dressed state. Therefore, the scheme can be implemented with the present experimental technology, which is useful in quantum information processing.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

PubMed Central

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-01-01

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction. PMID:27399722

Multimodal biometric approach for cancelable face template generation

NASA Astrophysics Data System (ADS)

Paul, Padma Polash; Gavrilova, Marina

2012-06-01

Due to the rapid growth of biometric technology, template protection becomes crucial to secure integrity of the biometric security system and prevent unauthorized access. Cancelable biometrics is emerging as one of the best solutions to secure the biometric identification and verification system. We present a novel technique for robust cancelable template generation algorithm that takes advantage of the multimodal biometric using feature level fusion. Feature level fusion of different facial features is applied to generate the cancelable template. A proposed algorithm based on the multi-fold random projection and fuzzy communication scheme is used for this purpose. In cancelable template generation, one of the main difficulties is keeping interclass variance of the feature. We have found that interclass variations of the features that are lost during multi fold random projection can be recovered using fusion of different feature subsets and projecting in a new feature domain. Applying the multimodal technique in feature level, we enhance the interclass variability hence improving the performance of the system. We have tested the system for classifier fusion for different feature subset and different cancelable template fusion. Experiments have shown that cancelable template improves the performance of the biometric system compared with the original template.

Multi-modal molecular diffuse optical tomography system for small animal imaging

PubMed Central

Guggenheim, James A.; Basevi, Hector R. A.; Frampton, Jon; Styles, Iain B.; Dehghani, Hamid

2013-01-01

A multi-modal optical imaging system for quantitative 3D bioluminescence and functional diffuse imaging is presented, which has no moving parts and uses mirrors to provide multi-view tomographic data for image reconstruction. It is demonstrated that through the use of trans-illuminated spectral near infrared measurements and spectrally constrained tomographic reconstruction, recovered concentrations of absorbing agents can be used as prior knowledge for bioluminescence imaging within the visible spectrum. Additionally, the first use of a recently developed multi-view optical surface capture technique is shown and its application to model-based image reconstruction and free-space light modelling is demonstrated. The benefits of model-based tomographic image recovery as compared to 2D planar imaging are highlighted in a number of scenarios where the internal luminescence source is not visible or is confounding in 2D images. The results presented show that the luminescence tomographic imaging method produces 3D reconstructions of individual light sources within a mouse-sized solid phantom that are accurately localised to within 1.5mm for a range of target locations and depths indicating sensitivity and accurate imaging throughout the phantom volume. Additionally the total reconstructed luminescence source intensity is consistent to within 15% which is a dramatic improvement upon standard bioluminescence imaging. Finally, results from a heterogeneous phantom with an absorbing anomaly are presented demonstrating the use and benefits of a multi-view, spectrally constrained coupled imaging system that provides accurate 3D luminescence images. PMID:24954977

Cloudwave: distributed processing of "big data" from electrophysiological recordings for epilepsy clinical research using Hadoop.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical "big data" consisting of more than 100 multi-channel signals with recordings from each patient generating 5-10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a "private cloud". Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with "montages" for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave).

Cloudwave: Distributed Processing of “Big Data” from Electrophysiological Recordings for Epilepsy Clinical Research Using Hadoop

PubMed Central

Jayapandian, Catherine P.; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D.; Zhang, Guo-Qiang; Sahoo, Satya S.

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50–60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical “big data” consisting of more than 100 multi-channel signals with recordings from each patient generating 5–10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a “private cloud”. Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with “montages” for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave) PMID:24551370

Multi-species sensing using multi-mode absorption spectroscopy with mid-infrared interband cascade lasers

NASA Astrophysics Data System (ADS)

O'Hagan, S.; Northern, J. H.; Gras, B.; Ewart, P.; Kim, C. S.; Kim, M.; Merritt, C. D.; Bewley, W. W.; Canedy, C. L.; Vurgaftman, I.; Meyer, J. R.

2016-06-01

The application of an interband cascade laser, ICL, to multi-mode absorption spectroscopy, MUMAS, in the mid-infrared region is reported. Measurements of individual mode linewidths of the ICL, derived from the pressure dependence of lineshapes in MUMAS signatures of single, isolated, lines in the spectrum of HCl, were found to be in the range 10-80 MHz. Multi-line spectra of methane were recorded using spectrally limited bandwidths, of approximate width 27 cm-1, defined by an interference filter, and consist of approximately 80 modes at spectral locations spanning the 100 cm-1 bandwidth of the ICL output. Calibration of the methane pressures derived from MUMAS data using a capacitance manometer provided measurements with an uncertainty of 1.1 %. Multi-species sensing is demonstrated by the simultaneous detection of methane, acetylene and formaldehyde in a gas mixture. Individual partial pressures of the three gases are derived from best fits of model MUMAS signatures to the data with an experimental error of 10 %. Using an ICL, with an inter-mode interval of ~10 GHz, MUMAS spectra were recorded at pressures in the range 1-10 mbar, and, based on the data, a potential minimum detection limit of the order of 100 ppmv is estimated for MUMAS at atmospheric pressure using an inter-mode interval of 80 GHz.

Coherence properties of spontaneous parametric down-conversion pumped by a multi-mode cw diode laser.

PubMed

Kwon, Osung; Ra, Young-Sik; Kim, Yoon-Ho

2009-07-20

Coherence properties of the photon pair generated via spontaneous parametric down-conversion pumped by a multi-mode cw diode laser are studied with a Mach-Zehnder interferometer. Each photon of the pair enters a different input port of the interferometer and the biphoton coherence properties are studied with a two-photon detector placed at one output port. When the photon pair simultaneously enters the interferometer, periodic recurrence of the biphoton de Broglie wave packet is observed, closely resembling the coherence properties of the pump diode laser. With non-zero delays between the photons at the input ports, biphoton interference exhibits the same periodic recurrence but the wave packet shapes are shown to be dependent on both the input delay as well as the interferometer delay. These properties could be useful for building engineered entangled photon sources based on diode laser-pumped spontaneous parametric down-conversion.

Storage and retrieval of electromagnetic waves with orbital angular momentum via plasmon-induced transparency.

PubMed

Bai, Zhengyang; Xu, Datang; Huang, Guoxiang

2017-01-23

We propose a scheme to realize the storage and retrieval of high-dimensional electromagnetic waves with orbital angular momentum (OAM) via plasmon-induced transparency (PIT) in a metamaterial, which consists of an array of meta-atoms constructed by a metallic structure loaded with two varactors. We show that due to PIT effect the system allows the existence of shape-preserving dark-mode plasmonic polaritons, which are mixture of electromagnetic-wave modes and dark oscillatory modes of the meta-atoms and may carry various OAMs. We demonstrate that the slowdown, storage and retrieval of multi-mode electromagnetic waves with OAMs can be achieved through the active manipulation of a control field. Our work raises the possibility for realizing PIT-based spatial multi-mode memory of electromagnetic waves and is promising for practical application of information processing with large capacity by using room-temperature metamaterials.

Nonlinear dynamics of magnetically coupled beams for multi-modal vibration energy harvesting

NASA Astrophysics Data System (ADS)

Abed, I.; Kacem, N.; Bouhaddi, N.; Bouazizi, M. L.

2016-04-01

We investigate the nonlinear dynamics of magnetically coupled beams for multi-modal vibration energy harvesting. A multi-physics model for the proposed device is developed taking into account geometric and magnetic nonlinearities. The coupled nonlinear equations of motion are solved using the Galerkin discretization coupled with the harmonic balance method and the asymptotic numerical method. Several numerical simulations have been performed showing that the expected performances of the proposed vibration energy harvester are significantly promising with up to 130 % in term of bandwidth and up to 60 μWcm-3g-2 in term of normalized harvested power.

Multi/demulti-plexer based on transverse mode conversion in photonic crystal waveguides.

PubMed

Zhou, Wen; Zhuang, Yuyang; Ji, Ke; Chen, He-ming

2015-09-21

A novel mode multiplexer and demultiplexer (MMUX/DEMMUX) based on 2-D photonic crystal (PC) at 1550 nm is proposed. The PC-based mode MMUX/DEMMUX including mode conversion function with a single-mode and multi-mode waveguides can be realized by quasi phase-matching TE(0) & TE(1) modes of two waveguides. 2DFinite-Difference-Time-Domain and beam propagation methods are used for simulation. The results show that PC-based mode MMUX/DEMMUX has the potential for high-capacity MDM optical communication systems with a low insertion loss (<0.36dB), low mode crosstalk (< -20.9 dB) and wide bandwidth (~100 nm).

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

The dynamics of multimodal integration: The averaging diffusion model.

PubMed

Turner, Brandon M; Gao, Juan; Koenig, Scott; Palfy, Dylan; L McClelland, James

2017-12-01

We combine extant theories of evidence accumulation and multi-modal integration to develop an integrated framework for modeling multimodal integration as a process that unfolds in real time. Many studies have formulated sensory processing as a dynamic process where noisy samples of evidence are accumulated until a decision is made. However, these studies are often limited to a single sensory modality. Studies of multimodal stimulus integration have focused on how best to combine different sources of information to elicit a judgment. These studies are often limited to a single time point, typically after the integration process has occurred. We address these limitations by combining the two approaches. Experimentally, we present data that allow us to study the time course of evidence accumulation within each of the visual and auditory domains as well as in a bimodal condition. Theoretically, we develop a new Averaging Diffusion Model in which the decision variable is the mean rather than the sum of evidence samples and use it as a base for comparing three alternative models of multimodal integration, allowing us to assess the optimality of this integration. The outcome reveals rich individual differences in multimodal integration: while some subjects' data are consistent with adaptive optimal integration, reweighting sources of evidence as their relative reliability changes during evidence integration, others exhibit patterns inconsistent with optimality.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions

NASA Astrophysics Data System (ADS)

Ziegler, Benjamin; Rauhut, Guntram

2016-03-01

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions.

PubMed

Ziegler, Benjamin; Rauhut, Guntram

2016-03-21

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Multimodal Deep Autoencoder for Human Pose Recovery.

PubMed

Hong, Chaoqun; Yu, Jun; Wan, Jian; Tao, Dacheng; Wang, Meng

2015-12-01

Video-based human pose recovery is usually conducted by retrieving relevant poses using image features. In the retrieving process, the mapping between 2D images and 3D poses is assumed to be linear in most of the traditional methods. However, their relationships are inherently non-linear, which limits recovery performance of these methods. In this paper, we propose a novel pose recovery method using non-linear mapping with multi-layered deep neural network. It is based on feature extraction with multimodal fusion and back-propagation deep learning. In multimodal fusion, we construct hypergraph Laplacian with low-rank representation. In this way, we obtain a unified feature description by standard eigen-decomposition of the hypergraph Laplacian matrix. In back-propagation deep learning, we learn a non-linear mapping from 2D images to 3D poses with parameter fine-tuning. The experimental results on three data sets show that the recovery error has been reduced by 20%-25%, which demonstrates the effectiveness of the proposed method.

Design of Open Content Social Learning That Increases Learning Efficiency and Engagement Based on Open Pedagogy

ERIC Educational Resources Information Center

John, Benneaser; Thavavel, V.; Jayaraj, Jayakumar; Muthukumar, A.; Jeevanandam, Poornaselvan Kittu

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Multi-Threaded DNA Tag/Anti-Tag Library Generator for Multi-Core Platforms

DTIC Science & Technology

2009-05-01

base pair)  Watson ‐ Crick  strand pairs that bind perfectly within pairs, but poorly across pairs. A variety  of  DNA  strand hybridization metrics...AFRL-RI-RS-TR-2009-131 Final Technical Report May 2009 MULTI-THREADED DNA TAG/ANTI-TAG LIBRARY GENERATOR FOR MULTI-CORE PLATFORMS...TYPE Final 3. DATES COVERED (From - To) Jun 08 – Feb 09 4. TITLE AND SUBTITLE MULTI-THREADED DNA TAG/ANTI-TAG LIBRARY GENERATOR FOR MULTI-CORE

Ex vivo catheter-based imaging of coronary atherosclerosis using multimodality OCT and NIRAF excited at 633 nm

PubMed Central

Wang, Hao; Gardecki, Joseph A.; Ughi, Giovanni J.; Jacques, Paulino Vacas; Hamidi, Ehsan; Tearney, Guillermo J.

2015-01-01

While optical coherence tomography (OCT) has been shown to be capable of imaging coronary plaque microstructure, additional chemical/molecular information may be needed in order to determine which lesions are at risk of causing an acute coronary event. In this study, we used a recently developed imaging system and double-clad fiber (DCF) catheter capable of simultaneously acquiring both OCT and red excited near-infrared autofluorescence (NIRAF) images (excitation: 633 nm, emission: 680nm to 900nm). We found that NIRAF is elevated in lesions that contain necrotic core – a feature that is critical for vulnerable plaque diagnosis and that is not readily discriminated by OCT alone. We first utilized a DCF ball lens probe and a bench top setup to acquire en face NIRAF images of aortic plaques ex vivo (n = 20). In addition, we used the OCT-NIRAF system and fully assembled catheters to acquire multimodality images from human coronary arteries (n = 15) prosected from human cadaver hearts (n = 5). Comparison of these images with corresponding histology demonstrated that necrotic core plaques exhibited significantly higher NIRAF intensity than other plaque types. These results suggest that multimodality intracoronary OCT-NIRAF imaging technology may be used in the future to provide improved characterization of coronary artery disease in human patients. PMID:25909020

The design of multi-core DSP parallel model based on message passing and multi-level pipeline

NASA Astrophysics Data System (ADS)

Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong

2017-10-01

Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.

Method and apparatus for operating a powertrain system upon detecting a stuck-closed clutch

DOEpatents

Hansen, R. Anthony

2014-02-18

A powertrain system includes a multi-mode transmission having a plurality of torque machines. A method for controlling the powertrain system includes identifying all presently applied clutches including commanded applied clutches and the stuck-closed clutch upon detecting one of the torque-transfer clutches is in a stuck-closed condition. A closed-loop control system is employed to control operation of the multi-mode transmission accounting for all the presently applied clutches.

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Obstacle traversal and self-righting of bio-inspired robots reveal the physics of multi-modal locomotion

NASA Astrophysics Data System (ADS)

Li, Chen; Fearing, Ronald; Full, Robert

Most animals move in nature in a variety of locomotor modes. For example, to traverse obstacles like dense vegetation, cockroaches can climb over, push across, reorient their bodies to maneuver through slits, or even transition among these modes forming diverse locomotor pathways; if flipped over, they can also self-right using wings or legs to generate body pitch or roll. By contrast, most locomotion studies have focused on a single mode such as running, walking, or jumping, and robots are still far from capable of life-like, robust, multi-modal locomotion in the real world. Here, we present two recent studies using bio-inspired robots, together with new locomotion energy landscapes derived from locomotor-environment interaction physics, to begin to understand the physics of multi-modal locomotion. (1) Our experiment of a cockroach-inspired legged robot traversing grass-like beam obstacles reveals that, with a terradynamically ``streamlined'' rounded body like that of the insect, robot traversal becomes more probable by accessing locomotor pathways that overcome lower potential energy barriers. (2) Our experiment of a cockroach-inspired self-righting robot further suggests that body vibrations are crucial for exploring locomotion energy landscapes and reaching lower barrier pathways. Finally, we posit that our new framework of locomotion energy landscapes holds promise to better understand and predict multi-modal biological and robotic movement.

MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

NASA Astrophysics Data System (ADS)

Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A.

2017-06-01

Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data.

Multimode electromagnetic target discriminator: preliminary data results

NASA Astrophysics Data System (ADS)

Black, Christopher J.; McMichael, Ian T.; Nelson, Carl V.

2004-09-01

This paper describes the Multi-mode Electromagnetic Target Discriminator (METD) sensor and presents preliminary results from recent field experiments. The METD sensor was developed for the US Army RDECOM NVESD by The Johns Hopkins University Applied Physics Laboratory. The METD, based on the technology of the previously developed Electromagnetic Target Discriminator (ETD), is a spatial scanning electromagnetic induction (EMI) sensor that uses both the time-domain (TD) and the frequency-domain (FD) for target detection and classification. Data is collected with a custom data acquisition system and wirelessly transmitted to a base computer. We show that the METD has a high signal-to-noise ratio (SNR), the ability to detect voids created by plastic anti-tank (AT) mines, and is practical for near real-time data processing.

Fuzzy decoupling controller based on multimode control algorithm of PI-single neuron and its application

NASA Astrophysics Data System (ADS)

Zhang, Xianxia; Wang, Jian; Qin, Tinggao

2003-09-01

Intelligent control algorithms are introduced into the control system of temperature and humidity. A multi-mode control algorithm of PI-Single Neuron is proposed for single loop control of temperature and humidity. In order to remove the coupling between temperature and humidity, a new decoupling method is presented, which is called fuzzy decoupling. The decoupling is achieved by using a fuzzy controller that dynamically modifies the static decoupling coefficient. Taking the control algorithm of PI-Single Neuron as the single loop control of temperature and humidity, the paper provides the simulated output response curves with no decoupling control, static decoupling control and fuzzy decoupling control. Those control algorithms are easily implemented in singlechip-based hardware systems.

SU-F-BRF-10: Deformable MRI to CT Validation Employing Same Day Planning MRI for Surrogate Analysis

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

Padgett, K; Stoyanova, R; Johnson, P

Purpose: To compare rigid and deformable registrations of the prostate in the multi-modality setting (diagnostic-MRI to planning-CT) by utilizing a planning-MRI as a surrogate. The surrogate allows for the direct quantitative analysis which can be difficult in the multi-modality domain where intensity mapping differs. Methods: For ten subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day in which the planning CT was collected (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets.more » The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. The deformed MRI was then rigidly aligned to the planning MRI which was used as the surrogate for the planning-CT. Agreement between the two MRI datasets was scored using intensity based metrics including Pearson correlation and normalized mutual information, NMI. A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb and combined areas. A similar method was used to assess a rigid registration between the diagnostic-MRI and planning-CT. Results: Utilizing the NMI, the deformable registrations were superior to the rigid registrations in 9 of 10 cases demonstrating a 15.94% improvement (p-value < 0.001) within the combined area. The Pearson correlation showed similar results with the deformable registration superior in the same number of cases and demonstrating a 6.97% improvement (p-value <0.011). Conclusion: Validating deformable multi-modality registrations using spatial intensity based metrics is difficult due to the inherent differences in intensity mapping. This population provides an ideal testing ground for MRI to CT deformable registrations by obviating the need for multi-modality comparisons which are inherently more challenging. Deformable registrations generated in this work significantly outperformed rigid alignments. Research reported in this abstract was supported by the NIH National Cancer Institute R21CA153826 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer” and Bankhead-Coley Cancer Research Program 10BT-03 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer”.« less

Visual tracking for multi-modality computer-assisted image guidance

NASA Astrophysics Data System (ADS)

Basafa, Ehsan; Foroughi, Pezhman; Hossbach, Martin; Bhanushali, Jasmine; Stolka, Philipp

2017-03-01

With optical cameras, many interventional navigation tasks previously relying on EM, optical, or mechanical guidance can be performed robustly, quickly, and conveniently. We developed a family of novel guidance systems based on wide-spectrum cameras and vision algorithms for real-time tracking of interventional instruments and multi-modality markers. These navigation systems support the localization of anatomical targets, support placement of imaging probe and instruments, and provide fusion imaging. The unique architecture - low-cost, miniature, in-hand stereo vision cameras fitted directly to imaging probes - allows for an intuitive workflow that fits a wide variety of specialties such as anesthesiology, interventional radiology, interventional oncology, emergency medicine, urology, and others, many of which see increasing pressure to utilize medical imaging and especially ultrasound, but have yet to develop the requisite skills for reliable success. We developed a modular system, consisting of hardware (the Optical Head containing the mini cameras) and software (components for visual instrument tracking with or without specialized visual features, fully automated marker segmentation from a variety of 3D imaging modalities, visual observation of meshes of widely separated markers, instant automatic registration, and target tracking and guidance on real-time multi-modality fusion views). From these components, we implemented a family of distinct clinical and pre-clinical systems (for combinations of ultrasound, CT, CBCT, and MRI), most of which have international regulatory clearance for clinical use. We present technical and clinical results on phantoms, ex- and in-vivo animals, and patients.

Integration of Sparse Multi-modality Representation and Anatomical Constraint for Isointense Infant Brain MR Image Segmentation

PubMed Central

Wang, Li; Shi, Feng; Gao, Yaozong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to poor spatial resolution, severe partial volume effect, and the ongoing maturation and myelination process. During the first year of life, the brain image contrast between white and gray matters undergoes dramatic changes. In particular, the image contrast inverses around 6–8 months of age, where the white and gray matter tissues are isointense in T1 and T2 weighted images and hence exhibit the extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a general framework that adopts sparse representation to fuse the multi-modality image information and further incorporate the anatomical constraints for brain tissue segmentation. Specifically, we first derive an initial segmentation from a library of aligned images with ground-truth segmentations by using sparse representation in a patch-based fashion for the multi-modality T1, T2 and FA images. The segmentation result is further iteratively refined by integration of the anatomical constraint. The proposed method was evaluated on 22 infant brain MR images acquired at around 6 months of age by using a leave-one-out cross-validation, as well as other 10 unseen testing subjects. Our method achieved a high accuracy for the Dice ratios that measure the volume overlap between automated and manual segmentations, i.e., 0.889±0.008 for white matter and 0.870±0.006 for gray matter. PMID:24291615

Ultrafast Narrow Band Modulation of VCSELs

NASA Technical Reports Server (NTRS)

Ning, Cun-Zheng; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Multimode beating was greatly enhanced by taking output from part (e.g., half) of the output facet. Simpler sources of microwaves and millimeter waves of various frequencies were generated by varying the VCSEL diameter in a single multimode VCSEL our coupling of a few VCSELs. Breathing frequency in multi-mode operations affects modulation response and bandwidth. Optimizing RO frequency and mode beating frequency could potentially expand bandwidths suitable for wide band digital communications.

Nonlinear dynamics and control of a vibrating rectangular plate

NASA Technical Reports Server (NTRS)

Shebalin, J. V.

1983-01-01

The von Karman equations of nonlinear elasticity are solved for the case of a vibrating rectangular plate by meams of a Fourier spectral transform method. The amplification of a particular Fourier mode by nonlinear transfer of energy is demonstrated for this conservative system. The multi-mode system is reduced to a minimal (two mode) system, retaining the qualitative features of the multi-mode system. The effect of a modal control law on the dynamics of this minimal nonlinear elastic system is examined.

Design, Simulation, Fabrication and Testing of a Bio-Inspired Amphibious Robot with Multiple Modes of Mobility

DTIC Science & Technology

2012-01-01

performance. Ob- stacle climbing using the tail is compared to results from a previous robot with a posterior body segment and body flexion joint. Actual...3. Mechanisms of Locomotion for Multi-Modal Mobility 3.1. Gate and Tail Design Demands of multi-modal locomotion motivated a quadruped design for...tail instead of a rear body segment simplifies waterproofing design requirements and adds stability both on land and in water. This new morphology is

Pedagogical Comparison of Five Reactions Performed under Microwave Heating in Multi-Mode versus Mono-Mode Ovens: Diels-Alder Cycloaddition, Wittig Salt Formation, E2 Dehydrohalogenation to Form an Alkyne, Williamson Ether Synthesis, and Fischer Esterification

ERIC Educational Resources Information Center

Baar, Marsha R.; Gammerdinger, William; Leap, Jennifer; Morales, Erin; Shikora, Jonathan; Weber, Michael H.

2014-01-01

Five reactions were rate-accelerated relative to the standard reflux workup in both multi-mode and mono-mode microwave ovens, and the results were compared to determine whether the sequential processing of a mono-mode unit could provide for better lab logistics and pedagogy. Conditions were optimized so that yields matched in both types of…

Percolated microstructures for multi-modal transport enhancement in porous active materials

DOEpatents

McKay, Ian Salmon; Yang, Sungwoo; Wang, Evelyn N.; Kim, Hyunho

2018-03-13

A method of forming a composite material for use in multi-modal transport includes providing three-dimensional graphene having hollow channels, enabling a polymer to wick into the hollow channels of the three-dimensional graphene, curing the polymer to form a cured three-dimensional graphene, adding an active material to the cured three-dimensional graphene to form a composite material, and removing the polymer from within the hollow channels. A composite material formed according to the method is also provided.

Access-enabling architectures : new hybrid multi-modal spatial prototypes towards resource and social sustainability : USDOT Region V Regional University Transportation Center final report.

DOT National Transportation Integrated Search

2016-12-19

The efforts of this project aim to capture and engage these potentials through a design-research method that incorporates a top down, data-driven approach with bottom-up stakeholder perspectives to develop prototypical scenario-based design solutions...

Integrating Traditional Learning and Games on Large Displays: An Experimental Study

ERIC Educational Resources Information Center

Ardito, Carmelo; Lanzilotti, Rosa; Costabile, Maria F.; Desolda, Giuseppe

2013-01-01

Current information and communication technology (ICT) has the potential to bring further changes to education. New learning techniques must be identified to take advantage of recent technological tools, such as smartphones, multimodal interfaces, multi-touch displays, etc. Game-based techniques that capitalize on ICT have proven to be very…

Designing a Website to Support Students' Academic Writing Process

ERIC Educational Resources Information Center

Åberg, Eva Svärdemo; Ståhle, Ylva; Engdahl, Ingrid; Knutes-Nyqvist, Helen

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Continuity and Change in Literacy Practices: A Move towards Multiliteracies

ERIC Educational Resources Information Center

Kitson, Lisbeth; Fletcher, Margaret; Kearney, Judith

2007-01-01

In this paper we present findings from an empirical study-in-progress that investigates how a teacher integrates technology, specifically an Interactive Whiteboard (IWB), to teach multiliterate practices when reading multi-modal texts. This research was a collaboration between a teacher and a team of university-based researchers as they used…

Multi-species detection using multi-mode absorption spectroscopy (MUMAS)

NASA Astrophysics Data System (ADS)

Northern, J. H.; Thompson, A. W. J.; Hamilton, M. L.; Ewart, P.

2013-06-01

The detection of multiple species using a single laser and single detector employing multi-mode absorption spectroscopy (MUMAS) is reported. An in-house constructed, diode-pumped, Er:Yb:glass micro-laser operating at 1,565 nm with 10 modes separated by 18 GHz was used to record MUMAS signals in a gas mixture containing C2H2, N2O and CO. The components of the mixture were detected simultaneously by identifying multiple transitions in each of the species. By using temperature- and pressure-dependent modelled spectral fits to the data, partial pressures of each species in the mixture were determined with an uncertainty of ±2 %.

Assessment of Closed-Loop Control Using Multi-Mode Sensor Fusion For a High Reynolds Number Transonic Jet

NASA Astrophysics Data System (ADS)

Low, Kerwin; Elhadidi, Basman; Glauser, Mark

2009-11-01

Understanding the different noise production mechanisms caused by the free shear flows in a turbulent jet flow provides insight to improve ``intelligent'' feedback mechanisms to control the noise. Towards this effort, a control scheme is based on feedback of azimuthal pressure measurements in the near field of the jet at two streamwise locations. Previous studies suggested that noise reduction can be achieved by azimuthal actuators perturbing the shear layer at the jet lip. The closed-loop actuation will be based on a low-dimensional Fourier representation of the hydrodynamic pressure measurements. Preliminary results show that control authority and reduction in the overall sound pressure level was possible. These results provide motivation to move forward with the overall vision of developing innovative multi-mode sensing methods to improve state estimation and derive dynamical systems. It is envisioned that estimating velocity-field and dynamic pressure information from various locations both local and in the far-field regions, sensor fusion techniques can be utilized to ascertain greater overall control authority.

Hybrid parameter identification of a multi-modal underwater soft robot.

PubMed

Giorgio-Serchi, F; Arienti, A; Corucci, F; Giorelli, M; Laschi, C

2017-02-28

We introduce an octopus-inspired, underwater, soft-bodied robot capable of performing waterborne pulsed-jet propulsion and benthic legged-locomotion. This vehicle consists for as much as 80% of its volume of rubber-like materials so that structural flexibility is exploited as a key element during both modes of locomotion. The high bodily softness, the unconventional morphology and the non-stationary nature of its propulsion mechanisms require dynamic characterization of this robot to be dealt with by ad hoc techniques. We perform parameter identification by resorting to a hybrid optimization approach where the characterization of the dual ambulatory strategies of the robot is performed in a segregated fashion. A least squares-based method coupled with a genetic algorithm-based method is employed for the swimming and the crawling phases, respectively. The outcomes bring evidence that compartmentalized parameter identification represents a viable protocol for multi-modal vehicles characterization. However, the use of static thrust recordings as the input signal in the dynamic determination of shape-changing self-propelled vehicles is responsible for the critical underestimation of the quadratic drag coefficient.

All-fiber 7x1 signal combiner for incoherent laser beam combining

NASA Astrophysics Data System (ADS)

Noordegraaf, D.; Maack, M. D.; Skovgaard, P. M. W.; Johansen, J.; Becker, F.; Belke, S.; Blomqvist, M.; Laegsgaard, J.

2011-02-01

We demonstrate an all-fiber 7x1 signal combiner for incoherent laser beam combining. This is a potential key component for reaching several kW of stabile laser output power. The combiner couples the output from 7 single-mode (SM) fiber lasers into a single multi-mode (MM) fiber. The input signal fibers have a core diameter of 17 μm and the output MM fiber has a core diameter of 100 μm. In a tapered section light gradually leaks out of the SM fibers and is captured by a surrounding fluorine-doped cladding. The combiner is tested up to 2.5 kW of combined output power and only a minor increase in device temperature is observed. At an intermediate power level of 600 W a beam parameter product (BPP) of 2.22 mm x mrad is measured, corresponding to an M2 value of 6.5. These values are approaching the theoretical limit dictated by brightness conservation.

Improved Numerical Calculation of the Single-Mode-No-Core-Single-Mode Fiber Structure Using the Fields Far from Cutoff Approximation

PubMed Central

Yang, Xianchao; Xu, Degang; Rong, Feng; Zhao, Junfa; Yao, Jianquan

2017-01-01

Multimode interferometers based on the single-mode-no-core-single-mode fiber (SNCS) structure have been widely investigated as functional devices and sensors. However, the theoretical support for the sensing mechanism is still imperfect, especially for the cladding refractive index response. In this paper, a modified model of no-core fiber (NCF) based on far from cut-off approximation is proposed to investigate the spectrum characteristic and sensing mechanism of the SNCS structure. Guided-mode propagation analysis (MPA) is used to analyze the self-image effect and spectrum response to the cladding refractive index and temperature. Verified by experiments, the performance of the SNCS structure can be estimated specifically and easily by the proposed method. PMID:28961174

Thermoluminescence characteristics of Ge-doped optical fibers with different dimensions for radiation dosimetry.

PubMed

Begum, Mahfuza; Rahman, A K M Mizanur; Abdul-Rashid, H A; Yusoff, Z; Begum, Mahbuba; Mat-Sharif, K A; Amin, Y M; Bradley, D A

2015-06-01

Important thermoluminescence (TL) properties of five (5) different core sizes Ge-doped optical fibers have been studied to develop new TL material with better response. These are drawn from same preform applying different speed and tension during drawing phase to produce Ge-doped optical fibers with five (5) different core sizes. The results of the investigations are also compared with most commonly used standard TLD-100 chips (LiF:Mg,Ti) and commercial multimode Ge-doped optical fiber (Yangtze Optical Fiber, China). Scanning Electron Microscope (SEM) and EDX analysis of the fibers are also performed to map Ge distribution across the deposited region. Standard Gamma radiation source in Secondary Standard Dosimetry Lab (SSDL) was used for irradiation covering dose range from 1Gy to 10Gy. The essential dosimetric parameters that have been studied are TL linearity, reproducibility and fading. Prior to irradiation all samples ∼0.5cm length are annealed at temperature of 400°C for 1h period to standardize their sensitivities and background. Standard TLD-100 chips are also annealed for 1h at 400°C and subsequently 2h at 100°C to yield the highest sensitivity. TL responses of these fibers show linearity over a wide gamma radiation dose that is an important property for radiation dosimetry. Among all fibers used in this study, 100μm core diameter fiber provides highest response that is 2.6 times than that of smallest core (20μm core) optical fiber. These fiber-samples demonstrate better response than commercial multi-mode optical fiber and also provide low degree of fading about 20% over a period of fifteen days for gamma radiation. Effective atomic number (Zeff) is found in the range (13.25-13.69) which is higher than soft tissue (7.5) however within the range of human-bone (11.6-13.8). All the fibers can also be re-used several times as a detector after annealing. TL properties of the Ge-doped optical fibers indicate promising applications in ionizing radiation dosimetry. Copyright © 2014 Elsevier Ltd. All rights reserved.

Realization of optical multimode TSV waveguides for Si-Interposer in 3D-chip-stacks

NASA Astrophysics Data System (ADS)

Killge, S.; Charania, S.; Richter, K.; Neumann, N.; Al-Husseini, Z.; Plettemeier, D.; Bartha, J. W.

2017-05-01

Optical connectivity has the potential to outperform copper-based TSVs in terms of bandwidth at the cost of more complexity due to the required electro-optical and opto-electrical conversion. The continuously increasing demand for higher bandwidth pushes the breakeven point for a profitable operation to shorter distances. To integrate an optical communication network in a 3D-chip-stack optical through-silicon vertical VIAs (TSV) are required. While the necessary effort for the electrical/optical and vice versa conversion makes it hard to envision an on-chip optical interconnect, a chip-to-chip optical link appears practicable. In general, the interposer offers the potential advantage to realize electro-optical transceivers on affordable expense by specific, but not necessarily CMOS technology. We investigated the realization and characterization of optical interconnects as a polymer based waveguide in high aspect ratio (HAR) TSVs proved on waferlevel. To guide the optical field inside a TSV as optical-waveguide or fiber, its core has to have a higher refractive index than the surrounding material. Comparing different material / technology options it turned out that thermal grown silicon dioxide (SiO2) is a perfect candidate for the cladding (nSiO2 = 1.4525 at 850 nm). In combination with SiO2 as the adjacent polymer layer, the negative resist SU-8 is very well suited as waveguide material (nSU-8 = 1.56) for the core. Here, we present the fabrication of an optical polymer based multimode waveguide in TSVs proved on waferlevel using SU-8 as core and SiO2 as cladding. The process resulted in a defect-free filling of waveguide TSVs with SU-8 core and SiO2 cladding up to aspect ratio (AR) 20:1 and losses less than 3 dB.

α-Information Based Registration of Dynamic Scans for Magnetic Resonance Cystography

PubMed Central

Han, Hao; Lin, Qin; Li, Lihong; Duan, Chaijie; Lu, Hongbing; Li, Haifang; Yan, Zengmin; Fitzgerald, John

2015-01-01

To continue our effort on developing magnetic resonance (MR) cystography, we introduce a novel non–rigid 3D registration method to compensate for bladder wall motion and deformation in dynamic MR scans, which are impaired by relatively low signal–to–noise ratio in each time frame. The registration method is developed on the similarity measure of α–information, which has the potential of achieving higher registration accuracy than the commonly-used mutual information (MI) measure for either mono-modality or multi-modality image registration. The α–information metric was also demonstrated to be superior to both the mean squares and the cross-correlation metrics in multi-modality scenarios. The proposed α–registration method was applied for bladder motion compensation via real patient studies, and its effect to the automatic and accurate segmentation of bladder wall was also evaluated. Compared with the prevailing MI-based image registration approach, the presented α–information based registration was more effective to capture the bladder wall motion and deformation, which ensured the success of the following bladder wall segmentation to achieve the goal of evaluating the entire bladder wall for detection and diagnosis of abnormality. PMID:26087506

Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

PubMed Central

Fuerst, Bernhard; Tateno, Keisuke; Johnson, Alex; Fotouhi, Javad; Osgood, Greg; Tombari, Federico; Navab, Nassir

2017-01-01

Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red–green–blue–depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion. PMID:29184659

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

Quality models for audiovisual streaming

NASA Astrophysics Data System (ADS)

Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

2006-01-01

Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

Molecular Medicine II: Hormone Dependent Cancers

DTIC Science & Technology

2005-04-01

multimode, live-cell videomicroscopy - we are analyzing the cycles of centrosome amplification in living S-phase arrested cells. Finally, we will directly...living cells by time-lapse multi-mode videomicroscopy . The key construct for our work is the generation of a mammalian somatic cell line stably expressing

Computational Assessment of Blood Flow Heterogeneity in Peritoneal Dialysis Patients' Cardiac Ventricles

PubMed Central

Kharche, Sanjay R.; So, Aaron; Salerno, Fabio; Lee, Ting-Yim; Ellis, Chris; Goldman, Daniel; McIntyre, Christopher W.

2018-01-01

Dialysis prolongs life but augments cardiovascular mortality. Imaging data suggests that dialysis increases myocardial blood flow (BF) heterogeneity, but its causes remain poorly understood. A biophysical model of human coronary vasculature was used to explain the imaging observations, and highlight causes of coronary BF heterogeneity. Post-dialysis CT images from patients under control, pharmacological stress (adenosine), therapy (cooled dialysate), and adenosine and cooled dialysate conditions were obtained. The data presented disparate phenotypes. To dissect vascular mechanisms, a 3D human vasculature model based on known experimental coronary morphometry and a space filling algorithm was implemented. Steady state simulations were performed to investigate the effects of altered aortic pressure and blood vessel diameters on myocardial BF heterogeneity. Imaging showed that stress and therapy potentially increased mean and total BF, while reducing heterogeneity. BF histograms of one patient showed multi-modality. Using the model, it was found that total coronary BF increased as coronary perfusion pressure was increased. BF heterogeneity was differentially affected by large or small vessel blocking. BF heterogeneity was found to be inversely related to small blood vessel diameters. Simulation of large artery stenosis indicates that BF became heterogeneous (increase relative dispersion) and gave multi-modal histograms. The total transmural BF as well as transmural BF heterogeneity reduced due to large artery stenosis, generating large patches of very low BF regions downstream. Blocking of arteries at various orders showed that blocking larger arteries results in multi-modal BF histograms and large patches of low BF, whereas smaller artery blocking results in augmented relative dispersion and fractal dimension. Transmural heterogeneity was also affected. Finally, the effects of augmented aortic pressure in the presence of blood vessel blocking shows differential effects on BF heterogeneity as well as transmural BF. Improved aortic blood pressure may improve total BF. Stress and therapy may be effective if they dilate small vessels. A potential cause for the observed complex BF distributions (multi-modal BF histograms) may indicate existing large vessel stenosis. The intuitive BF heterogeneity methods used can be readily used in clinical studies. Further development of the model and methods will permit personalized assessment of patient BF status. PMID:29867555

Powder metallurgy processing and deformation characteristics of bulk multimodal nickel

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

Farbaniec, L., E-mail: lfarban1@jhu.edu; Dirras, G., E-mail: dirras@univ-paris13.fr; Krawczynska, A.

2014-08-15

Spark plasma sintering was used to process bulk nickel samples from a blend of three powder types. The resulting multimodal microstructure was made of coarse (average size ∼ 135 μm) spherical microcrystalline entities (the core) surrounded by a fine-grained matrix (average grain size ∼ 1.5 μm) or a thick rim (the shell) distinguishable from the matrix. Tensile tests revealed yield strength of ∼ 470 MPa that was accompanied by limited ductility (∼ 2.8% plastic strain). Microstructure observation after testing showed debonding at interfaces between the matrix and the coarse entities, but in many instances, shallow dimples within the rim weremore » observed indicating local ductile events in the shell. Dislocation emission and annihilation at grain boundaries and twinning at crack tip were the main deformation mechanisms taking place within the fine-grained matrix as revealed by in-situ transmission electron microscopy. Estimation of the stress from loop's curvature and dislocation pile-up indicates that dislocation emission from grain boundaries and grain boundary overcoming largely contributes to the flow stress. - Highlights: • Bulk multi-modal Ni was processed by SPS from a powder blend. • Ultrafine-grained matrix or rim observed around spherical microcrystalline entities • Yield strength (470 MPa) and ductility (2.8% plastic strain) were measured. • Debonding was found at the matrix/microcrystalline entity interfaces. • In-situ TEM showed twinning, dislocation emission and annihilation at grain boundaries.« less

Effects of Restricted Launch Conditions for the Enhancement of Bandwidth-Distance Product of Multimode Fiber Links

NASA Technical Reports Server (NTRS)

Andrawis, Alfred S.

2000-01-01

Several techniques had been proposed to enhance multimode fiber bandwidth-distance product. Single mode-to-multimode offset launch condition technique had been experimented with at Kennedy Space Center. Significant enhancement in multimode fiber link bandwidth is achieved using this technique. It is found that close to three-fold bandwidth enhancement can be achieved compared to standard zero offset launch technique. Moreover, significant reduction in modal noise has been observed as a function of offset launch displacement. However, significant reduction in the overall signal-to-noise ratio is also observed due to signal attenuation due to mode radiation from fiber core to its cladding.

Multi-Core Processors: An Enabling Technology for Embedded Distributed Model-Based Control (Postprint)

DTIC Science & Technology

2008-07-01

generation of process partitioning, a thread pipelining becomes possible. In this paper we briefly summarize the requirements and trends for FADEC based... FADEC environment, presenting a hypothetical realization of an example application. Finally we discuss the application of Time-Triggered...based control applications of the future. 15. SUBJECT TERMS Gas turbine, FADEC , Multi-core processing technology, disturbed based control

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

PubMed

Bakas, Spyridon; Zeng, Ke; Sotiras, Aristeidis; Rathore, Saima; Akbari, Hamed; Gaonkar, Bilwaj; Rozycki, Martin; Pati, Sarthak; Davatzikos, Christos

2016-01-01

We present an approach for segmenting low- and high-grade gliomas in multimodal magnetic resonance imaging volumes. The proposed approach is based on a hybrid generative-discriminative model. Firstly, a generative approach based on an Expectation-Maximization framework that incorporates a glioma growth model is used to segment the brain scans into tumor, as well as healthy tissue labels. Secondly, a gradient boosting multi-class classification scheme is used to refine tumor labels based on information from multiple patients. Lastly, a probabilistic Bayesian strategy is employed to further refine and finalize the tumor segmentation based on patient-specific intensity statistics from the multiple modalities. We evaluated our approach in 186 cases during the training phase of the BRAin Tumor Segmentation (BRATS) 2015 challenge and report promising results. During the testing phase, the algorithm was additionally evaluated in 53 unseen cases, achieving the best performance among the competing methods.

Breaking the glass ceiling: hollow OmniGuide fibers

NASA Astrophysics Data System (ADS)

Johnson, Steven G.; Ibanescu, Mihai; Skorobogatiy, Maksim A.; Weisberg, Ori; Engeness, Torkel D.; Soljacic, Marin; Jacobs, Steven A.; Joannopoulos, John D.; Fink, Yoel

2002-04-01

We argue that OmniGuide fibers, which guide light within a hollow core by concentric multilayer films having the property of omnidirectional reflection, have the potential to lift several physical limitations of silica fibers. We show how the strong confinement in OmniGuide fibers greatly suppresses the properties of the cladding materials: even if highly lossy and nonlinear materials are employed, both the intrinsic losses and nonlinearities of silica fibers can be surpassed by orders of magnitude. This feat, impossible to duplicate in an index-guided fiber with existing materials, would open up new regimes for long-distance propagation and dense wavelength-division multiplexing (DWDM). The OmniGuide-fiber modes bear a strong analogy to those of hollow metallic waveguides; from this analogy, we are able to derive several general scaling laws with core radius. Moreover, there is strong loss discrimination between guided modes, depending upon their degree of confinement in the hollow core: this allows large, ostensibly multi-mode cores to be used, with the lowest-loss TE01 mode propagating in an effectively single-mode fashion. Finally, because this TE01 mode is a cylindrically symmetrical ('azimuthally' polarized) singlet state, it is immune to polarization-mode dispersion (PMD), unlike the doubly-degenerate linearly-polarized modes in silica fibers that are vulnerable to birefringence.

Neurocognitive insights on conceptual knowledge and its breakdown

PubMed Central

Lambon Ralph, Matthew A.

2014-01-01

Conceptual knowledge reflects our multi-modal ‘semantic database’. As such, it brings meaning to all verbal and non-verbal stimuli, is the foundation for verbal and non-verbal expression and provides the basis for computing appropriate semantic generalizations. Multiple disciplines (e.g. philosophy, cognitive science, cognitive neuroscience and behavioural neurology) have striven to answer the questions of how concepts are formed, how they are represented in the brain and how they break down differentially in various neurological patient groups. A long-standing and prominent hypothesis is that concepts are distilled from our multi-modal verbal and non-verbal experience such that sensation in one modality (e.g. the smell of an apple) not only activates the intramodality long-term knowledge, but also reactivates the relevant intermodality information about that item (i.e. all the things you know about and can do with an apple). This multi-modal view of conceptualization fits with contemporary functional neuroimaging studies that observe systematic variation of activation across different modality-specific association regions dependent on the conceptual category or type of information. A second vein of interdisciplinary work argues, however, that even a smorgasbord of multi-modal features is insufficient to build coherent, generalizable concepts. Instead, an additional process or intermediate representation is required. Recent multidisciplinary work, which combines neuropsychology, neuroscience and computational models, offers evidence that conceptualization follows from a combination of modality-specific sources of information plus a transmodal ‘hub’ representational system that is supported primarily by regions within the anterior temporal lobe, bilaterally. PMID:24324236

An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes - the MID-Frail study: study protocol for a randomised controlled trial

PubMed Central

2014-01-01

Background Diabetes, a highly prevalent, chronic disease, is associated with increasing frailty and functional decline in older people, with concomitant personal, social, and public health implications. We describe the rationale and methods of the multi-modal intervention in diabetes in frailty (MID-Frail) study. Methods/Design The MID-Frail study is an open, randomised, multicentre study, with random allocation by clusters (each trial site) to a usual care group or an intervention group. A total of 1,718 subjects will be randomised with each site enrolling on average 14 or 15 subjects. The primary objective of the study is to evaluate, in comparison with usual clinical practice, the effectiveness of a multi-modal intervention (specific clinical targets, education, diet, and resistance training exercise) in frail and pre-frail subjects aged ≥70 years with type 2 diabetes in terms of the difference in function 2 years post-randomisation. Difference in function will be measured by changes in a summary ordinal score on the short physical performance battery (SPPB) of at least one point. Secondary outcomes include daily activities, economic evaluation, and quality of life. Discussion The MID-Frail study will provide evidence on the clinical, functional, social, and economic impact of a multi-modal approach in frail and pre-frail older people with type 2 diabetes. Trial registration ClinicalTrials.gov: NCT01654341. PMID:24456998

An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes--the MID-Frail study: study protocol for a randomised controlled trial.

PubMed

Rodríguez-Mañas, Leocadio; Bayer, Antony J; Kelly, Mark; Zeyfang, Andrej; Izquierdo, Mikel; Laosa, Olga; Hardman, Timothy C; Sinclair, Alan J; Moreira, Severina; Cook, Justin

2014-01-24

Diabetes, a highly prevalent, chronic disease, is associated with increasing frailty and functional decline in older people, with concomitant personal, social, and public health implications. We describe the rationale and methods of the multi-modal intervention in diabetes in frailty (MID-Frail) study. The MID-Frail study is an open, randomised, multicentre study, with random allocation by clusters (each trial site) to a usual care group or an intervention group. A total of 1,718 subjects will be randomised with each site enrolling on average 14 or 15 subjects. The primary objective of the study is to evaluate, in comparison with usual clinical practice, the effectiveness of a multi-modal intervention (specific clinical targets, education, diet, and resistance training exercise) in frail and pre-frail subjects aged ≥70 years with type 2 diabetes in terms of the difference in function 2 years post-randomisation. Difference in function will be measured by changes in a summary ordinal score on the short physical performance battery (SPPB) of at least one point. Secondary outcomes include daily activities, economic evaluation, and quality of life. The MID-Frail study will provide evidence on the clinical, functional, social, and economic impact of a multi-modal approach in frail and pre-frail older people with type 2 diabetes. ClinicalTrials.gov: NCT01654341.

Development of a multi-modal Monte-Carlo radiation treatment planning system combined with PHITS

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

Kumada, Hiroaki; Nakamura, Takemi; Komeda, Masao

A new multi-modal Monte-Carlo radiation treatment planning system is under development at Japan Atomic Energy Agency. This system (developing code: JCDS-FX) builds on fundamental technologies of JCDS. JCDS was developed by JAEA to perform treatment planning of boron neutron capture therapy (BNCT) which is being conducted at JRR-4 in JAEA. JCDS has many advantages based on practical accomplishments for actual clinical trials of BNCT at JRR-4, the advantages have been taken over to JCDS-FX. One of the features of JCDS-FX is that PHITS has been applied to particle transport calculation. PHITS is a multipurpose particle Monte-Carlo transport code, thus applicationmore » of PHITS enables to evaluate doses for not only BNCT but also several radiotherapies like proton therapy. To verify calculation accuracy of JCDS-FX with PHITS for BNCT, treatment planning of an actual BNCT conducted at JRR-4 was performed retrospectively. The verification results demonstrated the new system was applicable to BNCT clinical trials in practical use. In framework of R and D for laser-driven proton therapy, we begin study for application of JCDS-FX combined with PHITS to proton therapy in addition to BNCT. Several features and performances of the new multimodal Monte-Carlo radiotherapy planning system are presented.« less

Improvement of Speckle Contrast Image Processing by an Efficient Algorithm.

PubMed

Steimers, A; Farnung, W; Kohl-Bareis, M

2016-01-01

We demonstrate an efficient algorithm for the temporal and spatial based calculation of speckle contrast for the imaging of blood flow by laser speckle contrast analysis (LASCA). It reduces the numerical complexity of necessary calculations, facilitates a multi-core and many-core implementation of the speckle analysis and enables an independence of temporal or spatial resolution and SNR. The new algorithm was evaluated for both spatial and temporal based analysis of speckle patterns with different image sizes and amounts of recruited pixels as sequential, multi-core and many-core code.

Efficient single-mode operation of a cladding-pumped ytterbium-doped helical-core fiber laser.

PubMed

Wang, P; Cooper, L J; Sahu, J K; Clarkson, W A

2006-01-15

A novel approach to achieving robust single-spatial-mode operation of cladding-pumped fiber lasers with multimode cores is reported. The approach is based on the use of a fiber geometry in which the core has a helical trajectory within the inner cladding to suppress laser oscillation on higher-order modes. In a preliminary proof-of-principle study, efficient single-mode operation of a cladding-pumped ytterbium-doped helical-core fiber laser with a 30 microm diameter core and a numerical aperture of 0.087 has been demonstrated. The laser yielded 60.4 W of output at 1043 nm in a beam with M2 < 1.4 for 92.6 W launched pump power from a diode stack at 976 nm. The slope efficiency at pump powers well above threshold was approximately 84%, which compares favorably with the slope efficiencies achievable with conventional straight-core Yb-doped double-clad fiber lasers.

VLBI-resolution radio-map algorithms: Performance analysis of different levels of data-sharing on multi-socket, multi-core architectures

NASA Astrophysics Data System (ADS)

Tabik, S.; Romero, L. F.; Mimica, P.; Plata, O.; Zapata, E. L.

2012-09-01

A broad area in astronomy focuses on simulating extragalactic objects based on Very Long Baseline Interferometry (VLBI) radio-maps. Several algorithms in this scope simulate what would be the observed radio-maps if emitted from a predefined extragalactic object. This work analyzes the performance and scaling of this kind of algorithms on multi-socket, multi-core architectures. In particular, we evaluate a sharing approach, a privatizing approach and a hybrid approach on systems with complex memory hierarchy that includes shared Last Level Cache (LLC). In addition, we investigate which manual processes can be systematized and then automated in future works. The experiments show that the data-privatizing model scales efficiently on medium scale multi-socket, multi-core systems (up to 48 cores) while regardless of algorithmic and scheduling optimizations, the sharing approach is unable to reach acceptable scalability on more than one socket. However, the hybrid model with a specific level of data-sharing provides the best scalability over all used multi-socket, multi-core systems.

Optical properties of core-shell and multi-shell nanorods

NASA Astrophysics Data System (ADS)

Mokkath, Junais Habeeb; Shehata, Nader

2018-05-01

We report a first-principles time dependent density functional theory study of the optical response modulations in bimetallic core-shell (Na@Al and Al@Na) and multi-shell (Al@Na@Al@Na and Na@Al@Na@Al: concentric shells of Al and Na alternate) nanorods. All of the core-shell and multi-shell configurations display highly enhanced absorption intensity with respect to the pure Al and Na nanorods, showing sensitivity to both composition and chemical ordering. Remarkably large spectral intensity enhancements were found in a couple of core-shell configurations, indicative that optical response averaging based on the individual components can not be considered as true as always in the case of bimetallic core-shell nanorods. We believe that our theoretical results would be useful in promising applications depending on Aluminum-based plasmonic materials such as solar cells and sensors.

Multi-tiered S-SOA, Parameter-Driven New Islamic Syariah Products of Holistic Islamic Banking System (HiCORE): Virtual Banking Environment

NASA Astrophysics Data System (ADS)

Halimah, B. Z.; Azlina, A.; Sembok, T. M.; Sufian, I.; Sharul Azman, M. N.; Azuraliza, A. B.; Zulaiha, A. O.; Nazlia, O.; Salwani, A.; Sanep, A.; Hailani, M. T.; Zaher, M. Z.; Azizah, J.; Nor Faezah, M. Y.; Choo, W. O.; Abdullah, Chew; Sopian, B.

The Holistic Islamic Banking System (HiCORE), a banking system suitable for virtual banking environment, created based on universityindustry collaboration initiative between Universiti Kebangsaan Malaysia (UKM) and Fuziq Software Sdn Bhd. HiCORE was modeled on a multitiered Simple - Services Oriented Architecture (S-SOA), using the parameterbased semantic approach. HiCORE's existence is timely as the financial world is looking for a new approach to creating banking and financial products that are interest free or based on the Islamic Syariah principles and jurisprudence. An interest free banking system has currently caught the interest of bankers and financiers all over the world. HiCORE's Parameter-based module houses the Customer-information file (CIF), Deposit and Financing components. The Parameter based module represents the third tier of the multi-tiered Simple SOA approach. This paper highlights the multi-tiered parameter- driven approach to the creation of new Islamiic products based on the 'dalil' (Quran), 'syarat' (rules) and 'rukun' (procedures) as required by the syariah principles and jurisprudence reflected by the semantic ontology embedded in the parameter module of the system.

“RaMassays”: Synergistic Enhancement of Plasmon-Free Raman Scattering and Mass Spectrometry for Multimodal Analysis of Small Molecules

NASA Astrophysics Data System (ADS)

Alessandri, Ivano; Vassalini, Irene; Bertuzzi, Michela; Bontempi, Nicolò; Memo, Maurizio; Gianoncelli, Alessandra

2016-10-01

SiO2/TiO2 core/shell (T-rex) beads were exploited as “all-in-one” building-block materials to create analytical assays that combine plasmon-free surface enhanced Raman scattering (SERS) and surface assisted laser desorption/ionization (SALDI) mass spectrometry (RaMassays). Such a multi-modal approach relies on the unique optical properties of T-rex beads, which are able to harvest and manage light in both UV and Vis range, making ionization and Raman scattering more efficient. RaMassays were successfully applied to the detection of small (molecular weight, M.W. <400 Da) molecules with a key relevance in biochemistry and pharmaceutical analysis. Caffeine and cocaine were utilized as molecular probes to test the combined SERS/SALDI response of RaMassays, showing excellent sensitivity and reproducibility. The differentiation between amphetamine/ephedrine and theophylline/theobromine couples demonstrated the synergistic reciprocal reinforcement of SERS and SALDI. Finally, the conversion of L-tyrosine in L-DOPA was utilized to probe RaMassays as analytical tools for characterizing reaction intermediates without introducing any spurious effects. RaMassays exhibit important advantages over plasmonic nanoparticles in terms of reproducibility, absence of interference and potential integration in multiplexed devices.

Data Parallel Bin-Based Indexing for Answering Queries on Multi-Core Architectures

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

Gosink, Luke; Wu, Kesheng; Bethel, E. Wes

2009-06-02

The multi-core trend in CPUs and general purpose graphics processing units (GPUs) offers new opportunities for the database community. The increase of cores at exponential rates is likely to affect virtually every server and client in the coming decade, and presents database management systems with a huge, compelling disruption that will radically change how processing is done. This paper presents a new parallel indexing data structure for answering queries that takes full advantage of the increasing thread-level parallelism emerging in multi-core architectures. In our approach, our Data Parallel Bin-based Index Strategy (DP-BIS) first bins the base data, and then partitionsmore » and stores the values in each bin as a separate, bin-based data cluster. In answering a query, the procedures for examining the bin numbers and the bin-based data clusters offer the maximum possible level of concurrency; each record is evaluated by a single thread and all threads are processed simultaneously in parallel. We implement and demonstrate the effectiveness of DP-BIS on two multi-core architectures: a multi-core CPU and a GPU. The concurrency afforded by DP-BIS allows us to fully utilize the thread-level parallelism provided by each architecture--for example, our GPU-based DP-BIS implementation simultaneously evaluates over 12,000 records with an equivalent number of concurrently executing threads. In comparing DP-BIS's performance across these architectures, we show that the GPU-based DP-BIS implementation requires significantly less computation time to answer a query than the CPU-based implementation. We also demonstrate in our analysis that DP-BIS provides better overall performance than the commonly utilized CPU and GPU-based projection index. Finally, due to data encoding, we show that DP-BIS accesses significantly smaller amounts of data than index strategies that operate solely on a column's base data; this smaller data footprint is critical for parallel processors that possess limited memory resources (e.g., GPUs).« less

Quantitative multi-modal NDT data analysis

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

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Sensor chip and apparatus for tactile and/or flow sensing

NASA Technical Reports Server (NTRS)

Liu, Chang (Inventor); Chen, Jack (Inventor); Engel, Jonathan (Inventor)

2008-01-01

A sensor chip, comprising a flexible, polymer-based substrate, and at least one microfabricated sensor disposed on the substrate and including a conductive element. The at least one sensor comprises at least one of a tactile sensor and a flow sensor. Other embodiments of the present invention include sensors and/or multi-modal sensor nodes.

49 CFR Appendix A to Part 611 - Description of Measures Used for Project Evaluation.

Code of Federal Regulations, 2012 CFR

2012-10-01

... alternative, travelers projected to shift to transit because of the new start project, and non-transit users... measure will be based on a multi-modal measure of perceived travel times faced by all users of the..., and level of commitment of each proposed source of local match, including inter-governmental grants...

Information Systems for Subject Specialists: A Multi-Modal Approach to Indexing and Classification.

ERIC Educational Resources Information Center

Swift, D.F.; And Others

A fundamental problem in the two broad approaches to indexing in the social sciences--providing structure using preferred terms, cross references, and groupings of sets of materials, or compiling a concordance of an author's terms based on occurrence, leaving users free to impose their own structure--is that different indexers and users focus on…

Sensor chip and apparatus for tactile and/or flow sensing

NASA Technical Reports Server (NTRS)

Liu, Chang (Inventor); Chen, Jack (Inventor); Engel, Jonathan (Inventor)

2009-01-01

A sensor chip, comprising a flexible, polymer-based substrate, and at least one microfabricated sensor disposed on the substrate and including a conductive element. The at least one sensor comprises at least one of a tactile sensor and a flow sensor. Other embodiments of the present invention include sensors and/or multi-modal sensor nodes.

Business Intelligence Basics: Multi-Modal Means of Analyzing Data Can Produce Actionable Results

ERIC Educational Resources Information Center

Mills, Lane

2008-01-01

School systems face many decisions in developing and maintaining learning environments that create success for all students. From district operations to the classroom, district leaders implement solutions and take action based on the information they have at hand. While there is no shortage of data, turning that data into useful information is as…

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

Multi-Mode Estimation for Small Fixed Wing Unmanned Aerial Vehicle Localization Based on a Linear Matrix Inequality Approach

PubMed Central

Elzoghby, Mostafa; Li, Fu; Arafa, Ibrahim. I.; Arif, Usman

2017-01-01

Information fusion from multiple sensors ensures the accuracy and robustness of a navigation system, especially in the absence of global positioning system (GPS) data which gets degraded in many cases. A way to deal with multi-mode estimation for a small fixed wing unmanned aerial vehicle (UAV) localization framework is proposed, which depends on utilizing a Luenberger observer-based linear matrix inequality (LMI) approach. The proposed estimation technique relies on the interaction between multiple measurement modes and a continuous observer. The state estimation is performed in a switching environment between multiple active sensors to exploit the available information as much as possible, especially in GPS-denied environments. Luenberger observer-based projection is implemented as a continuous observer to optimize the estimation performance. The observer gain might be chosen by solving a Lyapunov equation by means of a LMI algorithm. Convergence is achieved by utilizing the linear matrix inequality (LMI), based on Lyapunov stability which keeps the dynamic estimation error bounded by selecting the observer gain matrix (L). Simulation results are presented for a small UAV fixed wing localization problem. The results obtained using the proposed approach are compared with a single mode Extended Kalman Filter (EKF). Simulation results are presented to demonstrate the viability of the proposed strategy. PMID:28420214

Pancreatic tissue assessment using fluorescence and reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Chandra, Malavika; Heidt, David; Simeone, Diane; McKenna, Barbara; Scheiman, James; Mycek, Mary-Ann

2007-07-01

The ability of multi-modal optical spectroscopy to detect signals from pancreatic tissue was demonstrated by studying human pancreatic cancer xenografts in mice and freshly excised human pancreatic tumor tissue. Measured optical spectra and fluorescence decays were correlated with tissue morphological and biochemical properties. The measured spectral features and decay times correlated well with expected pathological differences in normal, pancreatitis and adenocarcinoma tissue states. The observed differences between the fluorescence and reflectance properties of normal, pancreatitis and adenocarcinoma tissue indicate a possible application of multi-modal optical spectroscopy to differentiating between the three tissue classifications.

Optimal rail container shipment planning problem in multimodal transportation

NASA Astrophysics Data System (ADS)

Cao, Chengxuan; Gao, Ziyou; Li, Keping

2012-09-01

The optimal rail container shipment planning problem in multimodal transportation is studied in this article. The characteristics of the multi-period planning problem is presented and the problem is formulated as a large-scale 0-1 integer programming model, which maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited capacities. Two heuristic algorithms are proposed to obtain an approximate optimal solution of the problem. Finally, numerical experiments are conducted to demonstrate the proposed formulation and heuristic algorithms.

VCSEL-based optical transceiver module operating at 25 Gb/s and using a single CMOS IC

NASA Astrophysics Data System (ADS)

Afriat, Gil; Horwitz, Lior; Lazar, Dror; Issachar, Assaf; Pogrebinsky, Alexander; Ran, Adee; Shoor, Ehud; Bar, Roi; Saba, Rushdy

2012-01-01

We present here a low cost, small form factor, optical transceiver module composed of a CMOS IC transceiver, 850 nm emission wavelength VCSEL modulated at 25 Gb/s, and an InGaAs/InP PIN Photo Diode (PD). The transceiver IC is fabricated in a standard 28 nm CMOS process and integrates the analog circuits interfacing the VCSEL and PD, namely the VCSEL driver and Transimpedance Amplifier (TIA), as well as all other required transmitter and receiver circuits like Phase Locked Loop (PLL), Post Amplifier and Clock & Data Recovery (CDR). The transceiver module couples into a 62.5/125 um multi-mode (OM1) TX/RX fiber pair via a low cost plastic cover realizing the transmitter and receiver lens systems and demonstrates BER < 10-12 at the 25 Gb/s data rate over a distance of 3 meters. Using a 50/125 um laser optimized multi-mode fiber (OM3), the same performance was achieved over a distance of 30 meters.

Blade tip clearance measurement of the turbine engines based on a multi-mode fiber coupled laser ranging system

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

Guo, Haotian; Duan, Fajie; Wu, Guoxiu

2014-11-15

The blade tip clearance is a parameter of great importance to guarantee the efficiency and safety of the turbine engines. In this article, a laser ranging system designed for blade tip clearance measurement is presented. Multi-mode fiber is utilized for optical transmission to guarantee that enough optical power is received by the sensor probe. The model of the tiny sensor probe is presented. The error brought by the optical path difference of different modes of the fiber is estimated and the length of the fiber is limited to reduce this error. The measurement range in which the optical power receivedmore » by the probe remains essentially unchanged is analyzed. Calibration experiments and dynamic experiments are conducted. The results of the calibration experiments indicate that the resolution of the system is about 0.02 mm and the range of the system is about 9 mm.« less

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

PubMed Central

Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.

2014-01-01

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA.

PubMed

Mitrea, Diana M; Cika, Jaclyn A; Guy, Clifford S; Ban, David; Banerjee, Priya R; Stanley, Christopher B; Nourse, Amanda; Deniz, Ashok A; Kriwacki, Richard W

2016-02-02

The nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identify multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus.

Terahertz imaging using photomixers based on quantum well photodetectors

NASA Astrophysics Data System (ADS)

Zhou, T.; Li, H.; Wan, W. J.; Fu, Z. L.; Cao, J. C.

2017-10-01

Due to the fast intersubband transitions, the terahertz (THz) quantum well photodetector (QWP) is supposed to work fast. Recently it has been demonstrated that the THz QWP can detect the THz light modulated at 6.2 GHz and therefore it can be used as a photomixer [H. Li et al., Sci. Rep. 7, 3452 (2017)]. In this work, the authors report a novel active THz imaging using THz QWP photomixers. The THz radiation source used for this imaging application is a multi-mode THz quantum cascade laser (QCL) operating in continuous wave mode. When the fast THz QWP is illuminated by the multi-mode THz radiation, the intermediate frequency signal that is resulted from the frequency beating between the neighbouring THz modes of the QCL can be extracted from the QWP mesa for imaging applications. Employing the technique, the frequency can be down-converted from the THz range to the microwave regime. And therefore, the signal can then be amplified, filtered, and detected using the mature microwave technology.

Bi-orthogonality relations for fluid-filled elastic cylindrical shells: Theory, generalisations and application to construct tailored Green's matrices

NASA Astrophysics Data System (ADS)

Ledet, Lasse S.; Sorokin, Sergey V.

2018-03-01

The paper addresses the classical problem of time-harmonic forced vibrations of a fluid-filled cylindrical shell considered as a multi-modal waveguide carrying infinitely many waves. The forced vibration problem is solved using tailored Green's matrices formulated in terms of eigenfunction expansions. The formulation of Green's matrix is based on special (bi-)orthogonality relations between the eigenfunctions, which are derived here for the fluid-filled shell. Further, the relations are generalised to any multi-modal symmetric waveguide. Using the orthogonality relations the transcendental equation system is converted into algebraic modal equations that can be solved analytically. Upon formulation of Green's matrices the solution space is studied in terms of completeness and convergence (uniformity and rate). Special features and findings exposed only through this modal decomposition method are elaborated and the physical interpretation of the bi-orthogonality relation is discussed in relation to the total energy flow which leads to derivation of simplified equations for the energy flow components.

Topology optimized design of functionally graded piezoelectric ultrasonic transducers

NASA Astrophysics Data System (ADS)

Rubio, Wilfredo Montealegre; Buiochi, Flávio; Adamowski, Julio Cezar; Silva, Emílio C. N.

2010-01-01

This work presents a new approach to systematically design piezoelectric ultrasonic transducers based on Topology Optimization Method (TOM) and Functionally Graded Material (FGM) concepts. The main goal is to find the optimal material distribution of Functionally Graded Piezoelectric Ultrasonic Transducers, to achieve the following requirements: (i) the transducer must be designed to have a multi-modal or uni-modal frequency response, which defines the kind of generated acoustic wave, either short pulse or continuous wave, respectively; (ii) the transducer is required to oscillate in a thickness extensional mode or piston-like mode, aiming at acoustic wave generation applications. Two kinds of piezoelectric materials are mixed for producing the FGM transducer. Material type 1 represents a PZT-5A piezoelectric ceramic and material type 2 represents a PZT-5H piezoelectric ceramic. To illustrate the proposed method, two Functionally Graded Piezoelectric Ultrasonic Transducers are designed. The TOM has shown to be a useful tool for designing Functionally Graded Piezoelectric Ultrasonic Transducers with uni-modal or multi-modal dynamic behavior.

Mesomorphic properties of multi-arm chenodeoxycholic acid-derived liquid crystals

NASA Astrophysics Data System (ADS)

Dong, Liang; Yao, Miao; Wu, Shuang-jie; Yao, Dan-Shu; Hu, Jian-She; He, Xiao-zhi; Tian, Mei

2017-12-01

Four multi-arm liquid crystals (LCs) based on chenodeoxycholic acid, termed as 2G-PD, 2G-IB, 2G-BD and 5G-GC, respectively, have been synthesised by convergent method, which nematic LC, 6-(4-((4-ethoxybenzoyl)oxy)phenoxy)-6-oxohexanoic acid, was used as side arm, and chenodeoxycholic acid (CDCA) was used as the first core, 1,2-propanediol (PD), isosorbide (IB), 4,4‧-biphenyldiol (BD) and glucose (GC) were used as the second core, respectively. The first generation product, CDCA2EA, displayed cholesteric phase. The second generation products 2G-BD and 5G-GC displayed cholesteric phase, while 2G-PD and 2G-IB exhibited nematic phase. The multi-arm LC, 2G-IB, did not display cholesteric phase although the two cores were all chiral ones. The result indicated that chirality of the second core sometimes made the multi-arm LCs display nematic phase when cholesteric CDCA-derivative were introduced into the second core. Some attention should be paid on molecular conformation besides the introduction of chiral cores for multi-chiral-core LCs to obtain cholesteric phase.

The biometric recognition on contactless multi-spectrum finger images

NASA Astrophysics Data System (ADS)

Kang, Wenxiong; Chen, Xiaopeng; Wu, Qiuxia

2015-01-01

This paper presents a novel multimodal biometric system based on contactless multi-spectrum finger images, which aims to deal with the limitations of unimodal biometrics. The chief merits of the system are the richness of the permissible texture and the ease of data access. We constructed a multi-spectrum instrument to simultaneously acquire three different types of biometrics from a finger: contactless fingerprint, finger vein, and knuckleprint. On the basis of the samples with these characteristics, a moderate database was built for the evaluation of our system. Considering the real-time requirements and the respective characteristics of the three biometrics, the block local binary patterns algorithm was used to extract features and match for the fingerprints and finger veins, while the Oriented FAST and Rotated BRIEF algorithm was applied for knuckleprints. Finally, score-level fusion was performed on the matching results from the aforementioned three types of biometrics. The experiments showed that our proposed multimodal biometric recognition system achieves an equal error rate of 0.109%, which is 88.9%, 94.6%, and 89.7% lower than the individual fingerprint, knuckleprint, and finger vein recognitions, respectively. Nevertheless, our proposed system also satisfies the real-time requirements of the applications.

Multi-focus beam shaping of high power multimode lasers

NASA Astrophysics Data System (ADS)

Laskin, Alexander; Volpp, Joerg; Laskin, Vadim; Ostrun, Aleksei

2017-08-01

Beam shaping of powerful multimode fiber lasers, fiber-coupled solid-state and diode lasers is of great importance for improvements of industrial laser applications. Welding, cladding with millimetre scale working spots benefit from "inverseGauss" intensity profiles; performance of thick metal sheet cutting, deep penetration welding can be enhanced when distributing the laser energy along the optical axis as more efficient usage of laser energy, higher edge quality and reduction of the heat affected zone can be achieved. Building of beam shaping optics for multimode lasers encounters physical limitations due to the low beam spatial coherence of multimode fiber-coupled lasers resulting in big Beam Parameter Products (BPP) or M² values. The laser radiation emerging from a multimode fiber presents a mixture of wavefronts. The fiber end can be considered as a light source which optical properties are intermediate between a Lambertian source and a single mode laser beam. Imaging of the fiber end, using a collimator and a focusing objective, is a robust and widely used beam delivery approach. Beam shaping solutions are suggested in form of optics combining fiber end imaging and geometrical separation of focused spots either perpendicular to or along the optical axis. Thus, energy of high power lasers is distributed among multiple foci. In order to provide reliable operation with multi-kW lasers and avoid damages the optics are designed as refractive elements with smooth optical surfaces. The paper presents descriptions of multi-focus optics as well as examples of intensity profile measurements of beam caustics and application results.

Determination of bacterial activity by use of an evanescent-wave fiber-optic sensor

NASA Astrophysics Data System (ADS)

John, M. Shelly; Kishen, Anil; Sing, Lim Chu; Asundi, Anand

2002-12-01

A novel technique based on fiber-optic evanescent-wave spectroscopy is proposed for the detection of bacterial activity in human saliva. The sensor determines the specific concentration of Streptococcus mutans in saliva, which is a major causative factor in dental caries. In this design, one prepares the fiber-optic bacterial sensor by replacing a portion of the cladding region of a multimode fiber with a dye-encapsulated xerogel, using the solgel technique. The exponential decay of the evanescent wave at the core-cladding interface of a multimode fiber is utilized for the determination of bacterial activity in saliva. The acidogenic profile of Streptococcus mutans is estimated by use of evanescent-wave absorption spectra at various levels of bacterial activity.

Xi-CAM v1.2.3

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

PANDOLFI, RONALD; KUMAR, DINESH; VENKATAKRISHNAN, SINGANALLUR

Xi-CAM aims to provide a community driven platform for multimodal analysis in synchrotron science. The platform core provides a robust plugin infrastructure for extensibility, allowing continuing development to simply add further functionality. Current modules include tools for characterization with (GI)SAXS, Tomography, and XAS. This will continue to serve as a development base as algorithms for multimodal analysis develop. Seamless remote data access, visualization and analysis are key elements of Xi-CAM, and will become critical to synchrotron data infrastructure as expectations for future data volume and acquisition rates rise with continuously increasing throughputs. The highly interactive design elements of Xi-cam willmore » similarly support a generation of users which depend on immediate data quality feedback during high-throughput or burst acquisition modes.« less

Mid-infrared supercontinuum generation in multimode step index chalcogenide fiber

NASA Astrophysics Data System (ADS)

Ben Khalifa, Ameni; Ben Salem, Amine; Cherif, Rim; Zghal, Mourad

2016-09-01

In this paper, we propose a design of a high numerical aperture multimode hybrid step-index fiber for mid-infrared (mid- IR) supercontinuum generation (SCG) where two chalcogenide glass compositions As40Se60 and Ge10As23.4Se66.6 for the core and the cladding are selected, respectively. Aiming to get accurate modeling of the SCG by the fundamental mode, we solve the multimode generalized nonlinear Schrödinger equations and demonstrate nonlinear coupling and energy transfer between high order modes. The proposed study points out the impact of nonlinear mode coupling that should be taken into account in order to successfully predict the mid-infrared supercontinuum generation in highly nonlinear multimode fibers.

A correlative optical microscopy and scanning electron microscopy approach to locating nanoparticles in brain tumors.

PubMed

Kempen, Paul J; Kircher, Moritz F; de la Zerda, Adam; Zavaleta, Cristina L; Jokerst, Jesse V; Mellinghoff, Ingo K; Gambhir, Sanjiv S; Sinclair, Robert

2015-01-01

The growing use of nanoparticles in biomedical applications, including cancer diagnosis and treatment, demands the capability to exactly locate them within complex biological systems. In this work a correlative optical and scanning electron microscopy technique was developed to locate and observe multi-modal gold core nanoparticle accumulation in brain tumor models. Entire brain sections from mice containing orthotopic brain tumors injected intravenously with nanoparticles were imaged using both optical microscopy to identify the brain tumor, and scanning electron microscopy to identify the individual nanoparticles. Gold-based nanoparticles were readily identified in the scanning electron microscope using backscattered electron imaging as bright spots against a darker background. This information was then correlated to determine the exact location of the nanoparticles within the brain tissue. The nanoparticles were located only in areas that contained tumor cells, and not in the surrounding healthy brain tissue. This correlative technique provides a powerful method to relate the macro- and micro-scale features visible in light microscopy with the nanoscale features resolvable in scanning electron microscopy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Osteo-cise: Strong Bones for Life: Protocol for a community-based randomised controlled trial of a multi-modal exercise and osteoporosis education program for older adults at risk of falls and fractures

PubMed Central

2012-01-01

Background Osteoporosis affects over 220 million people worldwide, and currently there is no ‘cure’ for the disease. Thus, there is a need to develop evidence-based, safe and acceptable prevention strategies at the population level that target multiple risk factors for fragility fractures to reduce the health and economic burden of the condition. Methods/design The Osteo-cise: Strong Bones for Life study will investigate the effectiveness and feasibility of a multi-component targeted exercise, osteoporosis education/awareness and behavioural change program for improving bone health and muscle function and reducing falls risk in community-dwelling older adults at an increased risk of fracture. Men and women aged ≥60 years will participate in an 18-month randomised controlled trial comprising a 12-month structured and supervised community-based program and a 6-month ‘research to practise’ translational phase. Participants will be randomly assigned to either the Osteo-cise intervention or a self-management control group. The intervention will comprise a multi-modal exercise program incorporating high velocity progressive resistance training, moderate impact weight-bearing exercise and high challenging balance exercises performed three times weekly at local community-based fitness centres. A behavioural change program will be used to enhance exercise adoption and adherence to the program. Community-based osteoporosis education seminars will be conducted to improve participant knowledge and understanding of the risk factors and preventative measures for osteoporosis, falls and fractures. The primary outcomes measures, to be collected at baseline, 6, 12, and 18 months, will include DXA-derived hip and spine bone mineral density measurements and functional muscle power (timed stair-climb test). Secondary outcomes measures include: MRI-assessed distal femur and proximal tibia trabecular bone micro-architecture, lower limb and back maximal muscle strength, balance and function (four square step test, functional reach test, timed up-and-go test and 30-second sit-to-stand), falls incidence and health-related quality of life. Cost-effectiveness will also be assessed. Discussion The findings from the Osteo-cise: Strong Bones for Life study will provide new information on the efficacy of a targeted multi-modal community-based exercise program incorporating high velocity resistance training, together with an osteoporosis education and behavioural change program for improving multiple risk factors for falls and fracture in older adults at risk of fragility fracture. Trial registration Australian New Zealand Clinical Trials Registry reference ACTRN12609000100291 PMID:22640372

Observation, Identification, and Impact of Multi-Modal Plasma Responses to Applied Magnetic Perturbations

NASA Astrophysics Data System (ADS)

Logan, Nikolas

2015-11-01

Experiments on DIII-D have demonstrated that multiple kink modes with comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n=2, in good agreement with ideal MHD models. In contrast to a single-mode model, the structure of the response measured using poloidally distributed magnetic sensors changes when varying the applied poloidal spectrum. This is most readily evident in that different spectra of applied fields can independently excite inboard and outboard magnetic responses, which are identified as distinct plasma modes by IPEC modeling. The outboard magnetic response is correlated with the plasma pressure and consistent with the long wavelength perturbations of the least stable, pressure driven kinks calculated by DCON and used in IPEC. The models show the structure of the pressure driven modes extends throughout the bad curvature region and into the plasma core. The inboard plasma response is correlated with the edge current profile and requires the inclusion of multiple kink modes with greater stability, including opposite helicity modes, to replicate the experimental observations in the models. IPEC reveals the resulting mode structure to be highly localized in the plasma edge. Scans of the applied spectrum show this response induces the transport that influences the density pump-out, as well as the toroidal rotation drag observed in experiment and modeled using PENT. The classification of these two mode types establishes a new multi-modal paradigm for n=2 plasma response and guides the understanding needed to optimize 3D fields for independent control of stability and transport. Supported by US DOE contract DE-AC02-09CH11466.

Efficiency of static core turn-off in a system-on-a-chip with variation

DOEpatents

Cher, Chen-Yong; Coteus, Paul W; Gara, Alan; Kursun, Eren; Paulsen, David P; Schuelke, Brian A; Sheets, II, John E; Tian, Shurong

2013-10-29

A processor-implemented method for improving efficiency of a static core turn-off in a multi-core processor with variation, the method comprising: conducting via a simulation a turn-off analysis of the multi-core processor at the multi-core processor's design stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's design stage includes a first output corresponding to a first multi-core processor core to turn off; conducting a turn-off analysis of the multi-core processor at the multi-core processor's testing stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's testing stage includes a second output corresponding to a second multi-core processor core to turn off; comparing the first output and the second output to determine if the first output is referring to the same core to turn off as the second output; outputting a third output corresponding to the first multi-core processor core if the first output and the second output are both referring to the same core to turn off.

Robust Nonrigid Multimodal Image Registration using Local Frequency Maps*

PubMed Central

Jian, Bing; Vemuri, Baba C.; Marroquin, José L.

2008-01-01

Automatic multi-modal image registration is central to numerous tasks in medical imaging today and has a vast range of applications e.g., image guidance, atlas construction, etc. In this paper, we present a novel multi-modal 3D non-rigid registration algorithm where in 3D images to be registered are represented by their corresponding local frequency maps efficiently computed using the Riesz transform as opposed to the popularly used Gabor filters. The non-rigid registration between these local frequency maps is formulated in a statistically robust framework involving the minimization of the integral squared error a.k.a. L2E (L2 error). This error is expressed as the squared difference between the true density of the residual (which is the squared difference between the non-rigidly transformed reference and the target local frequency representations) and a Gaussian or mixture of Gaussians density approximation of the same. The non-rigid transformation is expressed in a B-spline basis to achieve the desired smoothness in the transformation as well as computational efficiency. The key contributions of this work are (i) the use of Riesz transform to achieve better efficiency in computing the local frequency representation in comparison to Gabor filter-based approaches, (ii) new mathematical model for local-frequency based non-rigid registration, (iii) analytic computation of the gradient of the robust non-rigid registration cost function to achieve efficient and accurate registration. The proposed non-rigid L2E-based registration is a significant extension of research reported in literature to date. We present experimental results for registering several real data sets with synthetic and real non-rigid misalignments. PMID:17354721

Learning through Story: A Collaborative, Multimodal Arts Approach

ERIC Educational Resources Information Center

Barton, Georgina; Baguley, Margaret

2014-01-01

Literate practice in the arts encompasses both aesthetics and creativity. It is also multimodal in nature and often collaborative. This article presents data collected from a small multi-age school, with children from Prep to Year 7, during their preparation for an end-of-year show. The children had studied the topics of conservation and…

Interaction and dispersion of waveguide modes in an optical fiber with microirregularities of the core surface

NASA Astrophysics Data System (ADS)

Zadorin, A. S.; Kruglov, R. S.; Surkova, G. A.

2012-08-01

A self-consistent linear model is proposed for the transformation of the average intensity of the mode spectrum I( z) of the waveguide field in a multimode optical fiber with a stepped refractive index profile and the core having a rough surface. The model is based on the concept of the intermodal dispersion matrix of an elementary segment of the fiber, ∆, whose elements characterize the mutual transfer of energy between the waveguide modes, as well as their conversion to radiation modes on the specified interval. On this basis, the features of the transformation of the mode spectrum I( z) in a multimode optical fiber with a stepped refractive index profile are considered that is due to the effects of multiple dispersion of the signal by the stochastic irregularities of the duct. The effect of self-filtering of I( z) is described that results in the formation of a stable (normalized) distribution I*. The features of the normalization of the radiative damping of a group of modes I i ( z) in an optical fiber are considered.

Performance evaluation of throughput computing workloads using multi-core processors and graphics processors

NASA Astrophysics Data System (ADS)

Dave, Gaurav P.; Sureshkumar, N.; Blessy Trencia Lincy, S. S.

2017-11-01

Current trend in processor manufacturing focuses on multi-core architectures rather than increasing the clock speed for performance improvement. Graphic processors have become as commodity hardware for providing fast co-processing in computer systems. Developments in IoT, social networking web applications, big data created huge demand for data processing activities and such kind of throughput intensive applications inherently contains data level parallelism which is more suited for SIMD architecture based GPU. This paper reviews the architectural aspects of multi/many core processors and graphics processors. Different case studies are taken to compare performance of throughput computing applications using shared memory programming in OpenMP and CUDA API based programming.

Multi-modal porous microstructure for high temperature fuel cell application

NASA Astrophysics Data System (ADS)

Wejrzanowski, T.; Haj Ibrahim, S.; Cwieka, K.; Loeffler, M.; Milewski, J.; Zschech, E.; Lee, C.-G.

2018-01-01

In this study, the effect of microstructure of porous nickel electrode on the performance of high temperature fuel cell is investigated and presented based on a molten carbonate fuel cell (MCFC) cathode. The cathode materials are fabricated from slurry consisting of nickel powder and polymeric binder/solvent mixture, using the tape casting method. The final pore structure is shaped through modifying the slurry composition - with or without the addition of porogen(s). The manufactured materials are extensively characterized by various techniques involving: micro-computed tomography (micro-XCT), scanning electron microscopy (SEM), mercury porosimetry, BET and Archimedes method. Tomographic images are also analyzed and quantified to reveal the evolution of pore space due to nickel in situ oxidation to NiO, and infiltration by the electrolyte. Single-cell performance tests are carried out under MCFC operation conditions to estimate the performance of the manufactured materials. It is found that the multi-modal microstructure of MCFC cathode results in a significant enhancement of the power density generated by the reference cell. To give greater insight into the understanding of the effect of microstructure on the properties of the cathode, a model based on 3D tomography image transformation is proposed.

Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain Segmentation

PubMed Central

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H.; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6–8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods. PMID:24505729

Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation.

PubMed

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2013-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6-8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods.

Accurate Learning with Few Atlases (ALFA): an algorithm for MRI neonatal brain extraction and comparison with 11 publicly available methods.

PubMed

Serag, Ahmed; Blesa, Manuel; Moore, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Wilkinson, A G; Macnaught, Gillian; Semple, Scott I; Boardman, James P

2016-03-24

Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.

Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

2017-09-01

This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

Evidence-based development and first usability testing of a social serious game based multi-modal system for early screening for atypical socio-cognitive development.

PubMed

Gyori, Miklos; Borsos, Zsófia; Stefanik, Krisztina

2015-01-01

At current, screening for, and diagnosis of, autism spectrum disorders (ASD) are based on purely behavioral data; established screening tools rely on human observation and ratings of relevant behaviors. The research and development project in the focus of this paper is aimed at designing, creating and evaluating a social serious game based multi-modal, interactive software system for screening for high functioning cases of ASD at kindergarten age. The aims of this paper are (1) to summarize the evidence-based design process and (2) to present results from the first usability test of the system. Game topic, candidate responses, and candidate game contents were identified via an iterative literature review. On this basis, the 1^st partial prototype of the fully playable game has been created, with complete data recording functionality but without the decision making component. A first usability test was carried out on this prototype (n=13). Overall results were unambiguously promising. Although sporadic difficulties in, and slightly negative attitudes towards, using the game occasionally arose, these were confined to non-target-group children only. The next steps of development include (1) completing the game design; (2) carrying out first large-n field test; (3) creating the first prototype of the decision making component.

Biocompatible magnetofluorescent probes: luminescent silicon quantum dots coupled with superparamagnetic iron(III) oxide.

PubMed

Erogbogbo, Folarin; Yong, Ken-Tye; Hu, Rui; Law, Wing-Cheung; Ding, Hong; Chang, Ching-Wen; Prasad, Paras N; Swihart, Mark T

2010-09-28

Luminescent silicon quantum dots (SiQDs) are gaining momentum in bioimaging applications, based on their unique combination of optical properties and biocompatibility. Here, we report the development of a multimodal probe that combines the optical properties of silicon quantum dots with the superparamagnetic properties of iron oxide nanoparticles to create biocompatible magnetofluorescent nanoprobes. Multiple nanoparticles of each type are coencapsulated within the hydrophobic core of biocompatible phospholipid-polyethyleneglycol (DSPE-PEG) micelles. The size distribution and composition of the magnetofluorescent nanoprobes were characterized by transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy (EDS). Enhanced cellular uptake of these probes in the presence of a magnetic field was demonstrated in vitro. Their luminescence stability in a prostate cancer tumor model microenvironment was demonstrated in vivo. This paves the way for multimodal silicon quantum-dot-based nanoplatforms for a variety of imaging and delivery applications.

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

2010-01-01

Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922

Multi-mode horn antenna simulation

NASA Technical Reports Server (NTRS)

Dod, L. R.; Wolf, J. D.

1980-01-01

Radiation patterns were computed for a circular multimode horn antenna using waveguide electric field radiation expressions. The circular multimode horn was considered as a possible reflector feed antenna for the Large Antenna Multifrequency Microwave Radiometer (LAMMR). This horn antenna uses a summation of the TE sub 11 deg and TM sub 11 deg modes to generate far field primary radiation patterns with equal E and H plane beamwidths and low sidelobes. A computer program for the radiation field expressions using the summation of waveguide radiation modes is described. The sensitivity of the multimode horn antenna radiation patterns to phase variations between the two modes is given. Sample radiation pattern calculations for a reflector feed horn for LAMMR are shown. The multimode horn antenna provides a low noise feed suitable for radiometric applications.

VIGAN: Missing View Imputation with Generative Adversarial Networks.

PubMed

Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

2017-01-01

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

Quantitative reconstructions in multi-modal photoacoustic and optical coherence tomography imaging

NASA Astrophysics Data System (ADS)

Elbau, P.; Mindrinos, L.; Scherzer, O.

2018-01-01

In this paper we perform quantitative reconstruction of the electric susceptibility and the Grüneisen parameter of a non-magnetic linear dielectric medium using measurement of a multi-modal photoacoustic and optical coherence tomography system. We consider the mathematical model presented in Elbau et al (2015 Handbook of Mathematical Methods in Imaging ed O Scherzer (New York: Springer) pp 1169-204), where a Fredholm integral equation of the first kind for the Grüneisen parameter was derived. For the numerical solution of the integral equation we consider a Galerkin type method.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Asymmetric competition causes multimodal size distributions in spatially structured populations

PubMed Central

Velázquez, Jorge; Allen, Robert B.; Coomes, David A.; Eichhorn, Markus P.

2016-01-01

Plant sizes within populations often exhibit multimodal distributions, even when all individuals are the same age and have experienced identical conditions. To establish the causes of this, we created an individual-based model simulating the growth of trees in a spatially explicit framework, which was parametrized using data from a long-term study of forest stands in New Zealand. First, we demonstrate that asymmetric resource competition is a necessary condition for the formation of multimodal size distributions within cohorts. By contrast, the legacy of small-scale clustering during recruitment is transient and quickly overwhelmed by density-dependent mortality. Complex multi-layered size distributions are generated when established individuals are restricted in the spatial domain within which they can capture resources. The number of modes reveals the effective number of direct competitors, while the separation and spread of modes are influenced by distances among established individuals. Asymmetric competition within local neighbourhoods can therefore generate a range of complex size distributions within even-aged cohorts. PMID:26817778

Microscopy with multimode fibers

NASA Astrophysics Data System (ADS)

Moser, Christophe; Papadopoulos, Ioannis; Farahi, Salma; Psaltis, Demetri

2013-04-01

Microscopes are usually thought of comprising imaging elements such as objectives and eye-piece lenses. A different type of microscope, used for endoscopy, consists of waveguiding elements such as fiber bundles, where each fiber in the bundle transports the light corresponding to one pixel in the image. Recently a new type of microscope has emerged that exploits the large number of propagating modes in a single multimode fiber. We have successfully produced fluorescence images of neural cells with sub-micrometer resolution via a 200 micrometer core multimode fiber. The method for achieving imaging consists of using digital phase conjugation to reproduce a focal spot at the tip of the multimode fiber. The image is formed by scanning the focal spot digitally and collecting the fluorescence point by point.

Synthesis and functionalization of NaGdF4:Yb,Er@NaGdF4 core-shell nanoparticles for possible application as multimodal contrast agents.

PubMed

Baziulyte-Paulaviciene, Dovile; Karabanovas, Vitalijus; Stasys, Marius; Jarockyte, Greta; Poderys, Vilius; Sakirzanovas, Simas; Rotomskis, Ricardas

2017-01-01

Upconverting nanoparticles (UCNPs) are promising, new imaging probes capable of serving as multimodal contrast agents. In this study, monodisperse and ultrasmall core and core-shell UCNPs were synthesized via a thermal decomposition method. Furthermore, it was shown that the epitaxial growth of a NaGdF 4 optical inert layer covering the NaGdF 4 :Yb,Er core effectively minimizes surface quenching due to the spatial isolation of the core from the surroundings. The mean diameter of the synthesized core and core-shell nanoparticles was ≈8 and ≈16 nm, respectively. Hydrophobic UCNPs were converted into hydrophilic ones using a nonionic surfactant Tween 80. The successful coating of the UCNPs by Tween 80 has been confirmed by Fourier transform infrared (FTIR) spectroscopy. Scanning electron microscopy (SEM), powder X-ray diffraction (XRD), photoluminescence (PL) spectra and magnetic resonance (MR) T1 relaxation measurements were used to characterize the size, crystal structure, optical and magnetic properties of the core and core-shell nanoparticles. Moreover, Tween 80-coated core-shell nanoparticles presented enhanced optical and MR signal intensity, good colloidal stability, low cytotoxicity and nonspecific internalization into two different breast cancer cell lines, which indicates that these nanoparticles could be applied as an efficient, dual-modal contrast probe for in vivo bioimaging.

Advanced and flexible multi-carrier receiver architecture for high-count multi-core fiber based space division multiplexed applications

PubMed Central

Asif, Rameez

2016-01-01

Space division multiplexing (SDM), incorporating multi-core fibers (MCFs), has been demonstrated for effectively maximizing the data capacity in an impending capacity crunch. To achieve high spectral-density through multi-carrier encoding while simultaneously maintaining transmission reach, benefits from inter-core crosstalk (XT) and non-linear compensation must be utilized. In this report, we propose a proof-of-concept unified receiver architecture that jointly compensates optical Kerr effects, intra- and inter-core XT in MCFs. The architecture is analysed in multi-channel 512 Gbit/s dual-carrier DP-16QAM system over 800 km 19-core MCF to validate the digital compensation of inter-core XT. Through this architecture: (a) we efficiently compensates the inter-core XT improving Q-factor by 4.82 dB and (b) achieve a momentous gain in transmission reach, increasing the maximum achievable distance from 480 km to 1208 km, via analytical analysis. Simulation results confirm that inter-core XT distortions are more relentless for cores fabricated around the central axis of cladding. Predominantly, XT induced Q-penalty can be suppressed to be less than 1 dB up-to −11.56 dB of inter-core XT over 800 km MCF, offering flexibility to fabricate dense core structures with same cladding diameter. Moreover, this report outlines the relationship between core pitch and forward-error correction (FEC). PMID:27270381

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Multimodal exercise training in multiple sclerosis: A randomized controlled trial in persons with substantial mobility disability.

PubMed

Sandroff, Brian M; Bollaert, Rachel E; Pilutti, Lara A; Peterson, Melissa L; Baynard, Tracy; Fernhall, Bo; McAuley, Edward; Motl, Robert W

2017-10-01

Mobility disability is a common, debilitating feature of multiple sclerosis (MS). Exercise training has been identified as an approach to improve MS-related mobility disability. However, exercise randomized controlled trials (RCTs) on mobility in MS have generally not selectively targeted those with the onset of irreversible mobility disability. The current multi-site RCT compared the efficacy of 6-months of supervised, multimodal exercise training with an active control condition for improving mobility, gait, physical fitness, and cognitive outcomes in persons with substantial MS-related mobility disability. 83 participants with substantial MS-related mobility disability underwent initial mobility, gait, fitness, and cognitive processing speed assessments and were randomly assigned to 6-months of supervised multimodal (progressive aerobic, resistance, and balance) exercise training (intervention condition) or stretching-and-toning activities (control condition). Participants completed the same outcome assessments halfway through and immediately following the 6-month study period. There were statistically significant improvements in six-minute walk performance (F(2158)=3.12, p=0.05, η p 2 =0.04), peak power output (F(2150)=8.16, p<0.01, η p 2 =0.10), and Paced Auditory Serial Addition Test performance (F(2162)=4.67, p=0.01, η p 2 =0.05), but not gait outcomes, for those who underwent the intervention compared with those who underwent the control condition. This RCT provides novel, preliminary evidence that multimodal exercise training may improve endurance walking performance and cognitive processing speed, perhaps based on improvements in cardiorespiratory capacity, in persons with MS with substantial mobility disability. This is critical for informing the development of multi-site exercise rehabilitation programs in larger samples of persons with MS-related mobility disability. Copyright © 2017 Elsevier Inc. All rights reserved.

High sensitivity optical fiber liquid level sensor based on a compact MMF-HCF-FBG structure

NASA Astrophysics Data System (ADS)

Zhang, Yunshan; Zhang, Weigang; Chen, Lei; Zhang, Yanxin; Wang, Song; Yan, Tieyi

2018-05-01

An ultra-high sensitivity fiber liquid level sensor based on wavelength demodulation is proposed and demonstrated. The sensor is composed of a segment of multimode fiber and a large aperture hollow-core fiber assisted by a fiber Bragg grating (FBG). Interference occurs due to core mismatching and different modes with different effective refractive indices. The experimental results show that the liquid level sensitivity of the sensor is 1.145 nm mm‑1, and the linearity is up to 0.996. The dynamic temperature compensation of the sensor can be achieved by cascading an FBG. Considering the high sensitivity and compact structure of the sensor, it can be used for real-time intelligent monitoring of tiny changes in liquid level.

Effectiveness of core stability exercises and recovery myofascial release massage on fatigue in breast cancer survivors: a randomized controlled clinical trial.

PubMed

Cantarero-Villanueva, Irene; Fernández-Lao, Carolina; Del Moral-Avila, Rosario; Fernández-de-Las-Peñas, César; Feriche-Fernández-Castanys, María Belén; Arroyo-Morales, Manuel

2012-01-01

The purpose of the present paper was to evaluate the effects of an 8-week multimodal program focused on core stability exercises and recovery massage with DVD support for a 6-month period in physical and psychological outcomes in breast cancer survivors. A randomized controlled clinical trial was performed. Seventy-eight (n = 78) breast cancer survivors were assigned to experimental (core stability exercises plus massage-myofascial release) and control (usual health care) groups. The intervention period was 8 weeks. Mood state, fatigue, trunk curl endurance, and leg strength were determined at baseline, after the last treatment session, and at 6 months of followup. Immediately after treatment and at 6 months, fatigue, mood state, trunk curl endurance, and leg strength exhibited greater improvement within the experimental group compared to placebo group. This paper showed that a multimodal program focused on core stability exercises and massage reduced fatigue, tension, depression, and improved vigor and muscle strength after intervention and 6 months after discharge.

Efficiently Scheduling Multi-core Guest Virtual Machines on Multi-core Hosts in Network Simulation

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

Yoginath, Srikanth B; Perumalla, Kalyan S

2011-01-01

Virtual machine (VM)-based simulation is a method used by network simulators to incorporate realistic application behaviors by executing actual VMs as high-fidelity surrogates for simulated end-hosts. A critical requirement in such a method is the simulation time-ordered scheduling and execution of the VMs. Prior approaches such as time dilation are less efficient due to the high degree of multiplexing possible when multiple multi-core VMs are simulated on multi-core host systems. We present a new simulation time-ordered scheduler to efficiently schedule multi-core VMs on multi-core real hosts, with a virtual clock realized on each virtual core. The distinguishing features of ourmore » approach are: (1) customizable granularity of the VM scheduling time unit on the simulation time axis, (2) ability to take arbitrary leaps in virtual time by VMs to maximize the utilization of host (real) cores when guest virtual cores idle, and (3) empirically determinable optimality in the tradeoff between total execution (real) time and time-ordering accuracy levels. Experiments show that it is possible to get nearly perfect time-ordered execution, with a slight cost in total run time, relative to optimized non-simulation VM schedulers. Interestingly, with our time-ordered scheduler, it is also possible to reduce the time-ordering error from over 50% of non-simulation scheduler to less than 1% realized by our scheduler, with almost the same run time efficiency as that of the highly efficient non-simulation VM schedulers.« less

Polinsar Experiments of Multi-Mode X-Band Data Over South Area of China

NASA Astrophysics Data System (ADS)

Lu, L.; Yan, Q.; Duan, M.; Zhang, Y.

2012-08-01

This paper makes the polarimetric and polarimetric interferometric synthetic aperture radar (PolInSAR) experiments with the high-resolution X-band data acquired by Multi-mode airborne SAR system over an area around Linshui, south of China containing tropic vegetation and urban areas. Polarimetric analysis for typical tropic vegetations and man-made objects are presented, some polarimetric descriptors sensitive to vegetations and man-made objects are selected. Then, the PolInSAR information contained in the data is investigated, considering characteristics of the Multi-mode-XSAR dataset, a dual-baseline polarimetric interferometry method is proposed in this paper. The method both guarantees the high coherence on fully polarimetric data and combines the benefits of short and long baseline that helpful to the phase unwrapping and height sensitivity promotion. PolInSAR experiment results displayed demonstrates Multi-mode-XSAR datasets have intuitive capabilities for amount of application of land classification, objects detection and DSM mapping.

WE-H-206-02: Recent Advances in Multi-Modality Molecular Imaging of Small Animals

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

Tsui, B.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

High-resolution low-frequency fluctuation map of a multimode laser diode subject to filtered optical feedback via a fiber Bragg grating.

PubMed

Baladi, Fadwa; Lee, Min Won; Burie, Jean-René; Bettiati, Mauro A; Boudrioua, Azzedine; Fischer, Alexis P A

2016-07-01

A highly detailed and extended map of low-frequency fluctuations is established for a high-power multi-mode 980 nm laser diode subject to filtered optical feedback from a fiber Bragg grating. The low-frequency fluctuations limits and substructures exhibit substantial differences with previous works.

Logistics, Multimodal, and Shipper Partner 2.0.15 Tools: Guide to Importing Carrier Data Using the Outside Data Import Function 2015 Data Year - United States Version

EPA Pesticide Factsheets

This document provides guidance for Logistics, Multi-modal, and Shippers on how to use outside data collection systems to populate the SmartWay tools carrier data and activity sections using an automated method. (EPA publication # EPA-420-B-16-057a)

Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

PubMed

Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

2011-01-01

In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

Balancing Cohesion and Tension in Multimodal Rhetoric. An Interdisciplinary Approach to the Study of Semiotic Complexity

ERIC Educational Resources Information Center

Engebretsen, Martin

2012-01-01

What patterns of multimodal rhetoric characterizes the most successful texts meant for learning--inside or outside school? This article argues that the balance between cohesion and tension in the interplay between modes is an issue at the core of this challenging question. Texts meant for learning need both cohesion and tension in order to be both…

Targeted delivery of cancer-specific multimodal contrast agents for intraoperative detection of tumor boundaries and therapeutic margins

NASA Astrophysics Data System (ADS)

Xu, Ronald X.; Xu, Jeff S.; Huang, Jiwei; Tweedle, Michael F.; Schmidt, Carl; Povoski, Stephen P.; Martin, Edward W.

2010-02-01

Background: Accurate assessment of tumor boundaries and intraoperative detection of therapeutic margins are important oncologic principles for minimal recurrence rates and improved long-term outcomes. However, many existing cancer imaging tools are based on preoperative image acquisition and do not provide real-time intraoperative information that supports critical decision-making in the operating room. Method: Poly lactic-co-glycolic acid (PLGA) microbubbles (MBs) and nanobubbles (NBs) were synthesized by a modified double emulsion method. The MB and NB surfaces were conjugated with CC49 antibody to target TAG-72 antigen, a human glycoprotein complex expressed in many epithelial-derived cancers. Multiple imaging agents were encapsulated in MBs and NBs for multimodal imaging. Both one-step and multi-step cancer targeting strategies were explored. Active MBs/NBs were also fabricated for therapeutic margin assessment in cancer ablation therapies. Results: The multimodal contrast agents and the cancer-targeting strategies were tested on tissue simulating phantoms, LS174 colon cancer cell cultures, and cancer xenograft nude mice. Concurrent multimodal imaging was demonstrated using fluorescence and ultrasound imaging modalities. Technical feasibility of using active MBs and portable imaging tools such as ultrasound for intraoperative therapeutic margin assessment was demonstrated in a biological tissue model. Conclusion: The cancer-specific multimodal contrast agents described in this paper have the potential for intraoperative detection of tumor boundaries and therapeutic margins.

Development and reliability of a multi-modality scoring system for evaluation of disease progression in pre-clinical models of osteoarthritis: celecoxib may possess disease-modifying properties.

PubMed

Panahifar, A; Jaremko, J L; Tessier, A G; Lambert, R G; Maksymowych, W P; Fallone, B G; Doschak, M R

2014-10-01

We sought to develop a comprehensive scoring system for evaluation of pre-clinical models of osteoarthritis (OA) progression, and use this to evaluate two different classes of drugs for management of OA. Post-traumatic OA (PTOA) was surgically induced in skeletally mature rats. Rats were randomly divided in three groups receiving either glucosamine (high dose of 192 mg/kg) or celecoxib (clinical dose) or no treatment. Disease progression was monitored utilizing micro-magnetic resonance imaging (MRI), micro-computed tomography (CT) and histology. Pertinent features such as osteophytes, subchondral sclerosis, joint effusion, bone marrow lesion (BML), cysts, loose bodies and cartilage abnormalities were included in designing a sensitive multi-modality based scoring system, termed the rat arthritis knee scoring system (RAKSS). Overall, an inter-observer correlation coefficient (ICC) of greater than 0.750 was achieved for each scored feature. None of the treatments prevented cartilage loss, synovitis, joint effusion, or sclerosis. However, celecoxib significantly reduced osteophyte development compared to placebo. Although signs of inflammation such as synovitis and joint effusion were readily identified at 4 weeks post-operation, we did not detect any BML. We report the development of a sensitive and reliable multi-modality scoring system, the RAKSS, for evaluation of OA severity in pre-clinical animal models. Using this scoring system, we found that celecoxib prevented enlargement of osteophytes in this animal model of PTOA, and thus it may be useful in preventing OA progression. However, it did not show any chondroprotective effect using the recommended dose. In contrast, high dose glucosamine had no measurable effects. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

All-optical logic gates and wavelength conversion via the injection locking of a Fabry-Perot semiconductor laser

NASA Astrophysics Data System (ADS)

Harvey, E.; Pochet, M.; Schmidt, J.; Locke, T.; Naderi, N.; Usechak, N. G.

2013-03-01

This work investigates the implementation of all-optical logic gates based on optical injection locking (OIL). All-optical inverting, NOR, and NAND gates are experimentally demonstrated using two distributed feedback (DFB) lasers, a multi-mode Fabry-Perot laser diode, and an optical band-pass filter. The DFB lasers are externally modulated to represent logic inputs into the cavity of the multi-mode Fabry-Perot slave laser. The input DFB (master) lasers' wavelengths are aligned with the longitudinal modes of the Fabry-Perot slave laser and their optical power is used to modulate the injection conditions in the Fabry-Perot slave laser. The optical band-pass filter is used to select a Fabry- Perot mode that is either suppressed or transmitted given the logic state of the injecting master laser signals. When the input signal(s) is (are) in the on state, injection locking, and thus the suppression of the non-injected Fabry-Perot modes, is induced, yielding a dynamic system that can be used to implement photonic logic functions. Additionally, all-optical photonic processing is achieved using the cavity-mode shift produced in the injected slave laser under external optical injection. The inverting logic case can also be used as a wavelength converter — a key component in advanced wavelength-division multiplexing networks. As a result of this experimental investigation, a more comprehensive understanding of the locking parameters involved in injecting multiple lasers into a multi-mode cavity and the logic transition time is achieved. The performance of optical logic computations and wavelength conversion has the potential for ultrafast operation, limited primarily by the photon decay rate in the slave laser.

State deadbeat response and observability in multi-modal systems

NASA Technical Reports Server (NTRS)

Conner, L. T., Jr.; Stanford, D. P.

1984-01-01

Two aspects of multimodal systems are examined. It is shown that any completely controllable system with state dimension n not exceeding three allows a choice of feedback matrices resulting in a state deadbeat response. Some of the results presented here are valid for arbitrary n, and it is suggested that for all n the state deadbeat response can be obtained under the hypothesis of complete controllability. The controllability canonical form for a multimodal system is refined by introducing a notion of observability which is dual to controllability for these systems.

Primary prevention of cannabis use: a systematic review of randomized controlled trials.

PubMed

Norberg, Melissa M; Kezelman, Sarah; Lim-Howe, Nicholas

2013-01-01

A systematic review of primary prevention was conducted for cannabis use outcomes in youth and young adults. The aim of the review was to develop a comprehensive understanding of prevention programming by assessing universal, targeted, uni-modal, and multi-modal approaches as well as individual program characteristics. Twenty-eight articles, representing 25 unique studies, identified from eight electronic databases (EMBASE, MEDLINE, CINAHL, ERIC, PsycINFO, DRUG, EBM Reviews, and Project CORK), were eligible for inclusion. Results indicated that primary prevention programs can be effective in reducing cannabis use in youth populations, with statistically significant effect sizes ranging from trivial (0.07) to extremely large (5.26), with the majority of significant effect sizes being trivial to small. Given that the preponderance of significant effect sizes were trivial to small and that percentages of statistically significant and non-statistically significant findings were often equivalent across program type and individual components, the effectiveness of primary prevention for cannabis use should be interpreted with caution. Universal multi-modal programs appeared to outperform other program types (i.e, universal uni-modal, targeted multi-modal, targeted unimodal). Specifically, universal multi-modal programs that targeted early adolescents (10-13 year olds), utilised non-teacher or multiple facilitators, were short in duration (10 sessions or less), and implemented boosters sessions were associated with large median effect sizes. While there were studies in these areas that contradicted these results, the results highlight the importance of assessing the interdependent relationship of program components and program types. Finally, results indicated that the overall quality of included studies was poor, with an average quality rating of 4.64 out of 9. Thus, further quality research and reporting and the development of new innovative programs are required.

Primary Prevention of Cannabis Use: A Systematic Review of Randomized Controlled Trials

PubMed Central

Norberg, Melissa M.; Kezelman, Sarah; Lim-Howe, Nicholas

2013-01-01

A systematic review of primary prevention was conducted for cannabis use outcomes in youth and young adults. The aim of the review was to develop a comprehensive understanding of prevention programming by assessing universal, targeted, uni-modal, and multi-modal approaches as well as individual program characteristics. Twenty-eight articles, representing 25 unique studies, identified from eight electronic databases (EMBASE, MEDLINE, CINAHL, ERIC, PsycINFO, DRUG, EBM Reviews, and Project CORK), were eligible for inclusion. Results indicated that primary prevention programs can be effective in reducing cannabis use in youth populations, with statistically significant effect sizes ranging from trivial (0.07) to extremely large (5.26), with the majority of significant effect sizes being trivial to small. Given that the preponderance of significant effect sizes were trivial to small and that percentages of statistically significant and non-statistically significant findings were often equivalent across program type and individual components, the effectiveness of primary prevention for cannabis use should be interpreted with caution. Universal multi-modal programs appeared to outperform other program types (i.e, universal uni-modal, targeted multi-modal, targeted unimodal). Specifically, universal multi-modal programs that targeted early adolescents (10–13 year olds), utilised non-teacher or multiple facilitators, were short in duration (10 sessions or less), and implemented boosters sessions were associated with large median effect sizes. While there were studies in these areas that contradicted these results, the results highlight the importance of assessing the interdependent relationship of program components and program types. Finally, results indicated that the overall quality of included studies was poor, with an average quality rating of 4.64 out of 9. Thus, further quality research and reporting and the development of new innovative programs are required. PMID:23326396

Development of a Multi-modal Tissue Diagnostic System Combining High Frequency Ultrasound and Photoacoustic Imaging with Lifetime Fluorescence Spectroscopy

PubMed Central

Sun, Yang; Stephens, Douglas N.; Park, Jesung; Sun, Yinghua; Marcu, Laura; Cannata, Jonathan M.; Shung, K. Kirk

2010-01-01

We report the development and validate a multi-modal tissue diagnostic technology, which combines three complementary techniques into one system including ultrasound backscatter microscopy (UBM), photoacoustic imaging (PAI), and time-resolved laser-induced fluorescence spectroscopy (TR-LIFS). UBM enables the reconstruction of the tissue microanatomy. PAI maps the optical absorption heterogeneity of the tissue associated with structure information and has the potential to provide functional imaging of the tissue. Examination of the UBM and PAI images allows for localization of regions of interest for TR-LIFS evaluation of the tissue composition. The hybrid probe consists of a single element ring transducer with concentric fiber optics for multi-modal data acquisition. Validation and characterization of the multi-modal system and ultrasonic, photoacoustic, and spectroscopic data coregistration were conducted in a physical phantom with properties of ultrasound scattering, optical absorption, and fluorescence. The UBM system with the 41 MHz ring transducer can reach the axial and lateral resolution of 30 and 65 μm, respectively. The PAI system with 532 nm excitation light from a Nd:YAG laser shows great contrast for the distribution of optical absorbers. The TR-LIFS system records the fluorescence decay with the time resolution of ~300 ps and a high sensitivity of nM concentration range. Biological phantom constructed with different types of tissues (tendon and fat) was used to demonstrate the complementary information provided by the three modalities. Fluorescence spectra and lifetimes were compared to differentiate chemical composition of tissues at the regions of interest determined by the coregistered high resolution UBM and PAI image. Current results demonstrate that the fusion of these techniques enables sequentially detection of functional, morphological, and compositional features of biological tissue, suggesting potential applications in diagnosis of tumors and atherosclerotic plaques. PMID:21894259

Development of a Multi-modal Tissue Diagnostic System Combining High Frequency Ultrasound and Photoacoustic Imaging with Lifetime Fluorescence Spectroscopy.

PubMed

Sun, Yang; Stephens, Douglas N; Park, Jesung; Sun, Yinghua; Marcu, Laura; Cannata, Jonathan M; Shung, K Kirk

2008-01-01

We report the development and validate a multi-modal tissue diagnostic technology, which combines three complementary techniques into one system including ultrasound backscatter microscopy (UBM), photoacoustic imaging (PAI), and time-resolved laser-induced fluorescence spectroscopy (TR-LIFS). UBM enables the reconstruction of the tissue microanatomy. PAI maps the optical absorption heterogeneity of the tissue associated with structure information and has the potential to provide functional imaging of the tissue. Examination of the UBM and PAI images allows for localization of regions of interest for TR-LIFS evaluation of the tissue composition. The hybrid probe consists of a single element ring transducer with concentric fiber optics for multi-modal data acquisition. Validation and characterization of the multi-modal system and ultrasonic, photoacoustic, and spectroscopic data coregistration were conducted in a physical phantom with properties of ultrasound scattering, optical absorption, and fluorescence. The UBM system with the 41 MHz ring transducer can reach the axial and lateral resolution of 30 and 65 μm, respectively. The PAI system with 532 nm excitation light from a Nd:YAG laser shows great contrast for the distribution of optical absorbers. The TR-LIFS system records the fluorescence decay with the time resolution of ~300 ps and a high sensitivity of nM concentration range. Biological phantom constructed with different types of tissues (tendon and fat) was used to demonstrate the complementary information provided by the three modalities. Fluorescence spectra and lifetimes were compared to differentiate chemical composition of tissues at the regions of interest determined by the coregistered high resolution UBM and PAI image. Current results demonstrate that the fusion of these techniques enables sequentially detection of functional, morphological, and compositional features of biological tissue, suggesting potential applications in diagnosis of tumors and atherosclerotic plaques.

Reactivity-controlled compression ignition drive cycle emissions and fuel economy estimations using vehicle system simulations

DOE PAGES

Curran, Scott J.; Gao, Zhiming; Wagner, Robert M.

2014-12-22

In-cylinder blending of gasoline and diesel to achieve reactivity-controlled compression ignition has been shown to reduce NO X and soot emissions while maintaining or improving brake thermal efficiency as compared with conventional diesel combustion. The reactivity-controlled compression ignition concept has an advantage over many advanced combustion strategies in that the fuel reactivity can be tailored to the engine speed and load, allowing stable low-temperature combustion to be extended over more of the light-duty drive cycle load range. In this paper, a multi-mode reactivity-controlled compression ignition strategy is employed where the engine switches from reactivity-controlled compression ignition to conventional diesel combustionmore » when speed and load demand are outside of the experimentally determined reactivity-controlled compression ignition range. The potential for reactivity-controlled compression ignition to reduce drive cycle fuel economy and emissions is not clearly understood and is explored here by simulating the fuel economy and emissions for a multi-mode reactivity-controlled compression ignition–enabled vehicle operating over a variety of US drive cycles using experimental engine maps for multi-mode reactivity-controlled compression ignition, conventional diesel combustion, and a 2009 port-fuel injected gasoline engine. Drive cycle simulations are completed assuming a conventional mid-size passenger vehicle with an automatic transmission. Multi-mode reactivity-controlled compression ignition fuel economy simulation results are compared with the same vehicle powered by a representative 2009 port-fuel injected gasoline engine over multiple drive cycles. Finally, engine-out drive cycle emissions are compared with conventional diesel combustion, and observations regarding relative gasoline and diesel tank sizes needed for the various drive cycles are also summarized.« less

Evaluating the efficacy of an integrated motivational interviewing and multi-modal exercise intervention for youth with major depression: Healthy Body, Healthy Mind randomised controlled trial protocol.

PubMed

Nasstasia, Yasmina; Baker, Amanda L; Halpin, Sean A; Hides, Leanne; Lewin, Terry J; Kelly, Brian J; Callister, Robin

2018-03-01

Recent meta-analytic reviews suggest exercise can reduce depression severity among adults with major depressive disorder (MDD); however, efficacy studies with depressed youth are limited. Few studies have investigated the efficacy of multi-modal exercise interventions in this population, addressed treatment engagement, or explored the differential effects of exercise on depressive symptom profiles. This paper describes the study protocol and recruitment pattern for an assessor blinded, two-arm randomised controlled trial investigating the efficacy of an integrated motivational interviewing (MI) and multi-modal exercise intervention in youth diagnosed with MDD. Associations between depressive symptom profiles (cognitive, somatic and affective) and psychological, physiological (fitness), and biological (blood biomarker) outcomes will also be examined. Participants aged 15-25 years with current MDD were recruited. Eligible participants were randomised and stratified according to gender and depression severity to either an immediate or delayed (control) group. The immediate group received a brief MI intervention followed by a 12-week small group exercise intervention (3 times per week for 1 h), all delivered by personal trainers. The delayed control group received the same intervention 12-weeks later. Both groups were reassessed at mid-treatment or mid-control, post-treatment or post-control, and follow-up (12 weeks post-treatment). 68 participants were recruited and randomly allocated to an intervention group. This trial will increase our understanding of the efficacy of multi-modal exercise interventions for depression and the specific effects of exercise on depressive symptom profiles. It also offers a novel contribution by addressing treatment engagement in exercise efficacy trials in youth with MDD.

A Module-Based Approach to Foster and Document the Intercultural Process before and during the Residence Abroad

ERIC Educational Resources Information Center

Penman, C.; Ratz, S.

2015-01-01

This article contributes to the debate on what form of preparation and support can enhance the intercultural student experience during a Year Abroad. It presents a credit-bearing and multi-modal module at a UK university designed to both prepare students prior to departure through a series of workshops and activities on an e-portfolio and help…

Beyond Attendance: A Multi-Modal Understanding of Arts Participation. Based on the 2008 Survey of Public Participation in the Arts. Research Report #54

ERIC Educational Resources Information Center

Novak-Leonard, Jennifer L.; Brown, Alan S.

2011-01-01

First conducted in 1982, the National Endowment for the Arts' (NEA's) Survey of Public Participation in the Arts (SPPA) serves as the longest-standing resource for studying U.S. adult levels of arts attendance, personal arts creation and performance, and arts participation through electronic media. The environment in which arts organizations…

Unexpected Self-Expression and the Limits of Narrative Inquiry: Exploring Unconscious Dynamics in a Community-Based Digital Storytelling Workshop

ERIC Educational Resources Information Center

Brushwood Rose, Chloe; Granger, Colette A.

2013-01-01

This study explores the tension between self-knowledge and self-expression, and how it manifests in the processes of storytelling that unfold in digital storytelling workshops offered to new immigrant women living in Toronto, Canada. Both in their multi-modal complexity and in the significant shifts from their original telling, the digital stories…

Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks

NASA Astrophysics Data System (ADS)

Le, Minh Hung; Chen, Jingyu; Wang, Liang; Wang, Zhiwei; Liu, Wenyu; (Tim Cheng, Kwang-Ting; Yang, Xin

2017-08-01

Automated methods for prostate cancer (PCa) diagnosis in multi-parametric magnetic resonance imaging (MP-MRIs) are critical for alleviating requirements for interpretation of radiographs while helping to improve diagnostic accuracy (Artan et al 2010 IEEE Trans. Image Process. 19 2444-55, Litjens et al 2014 IEEE Trans. Med. Imaging 33 1083-92, Liu et al 2013 SPIE Medical Imaging (International Society for Optics and Photonics) p 86701G, Moradi et al 2012 J. Magn. Reson. Imaging 35 1403-13, Niaf et al 2014 IEEE Trans. Image Process. 23 979-91, Niaf et al 2012 Phys. Med. Biol. 57 3833, Peng et al 2013a SPIE Medical Imaging (International Society for Optics and Photonics) p 86701H, Peng et al 2013b Radiology 267 787-96, Wang et al 2014 BioMed. Res. Int. 2014). This paper presents an automated method based on multimodal convolutional neural networks (CNNs) for two PCa diagnostic tasks: (1) distinguishing between cancerous and noncancerous tissues and (2) distinguishing between clinically significant (CS) and indolent PCa. Specifically, our multimodal CNNs effectively fuse apparent diffusion coefficients (ADCs) and T2-weighted MP-MRI images (T2WIs). To effectively fuse ADCs and T2WIs we design a new similarity loss function to enforce consistent features being extracted from both ADCs and T2WIs. The similarity loss is combined with the conventional classification loss functions and integrated into the back-propagation procedure of CNN training. The similarity loss enables better fusion results than existing methods as the feature learning processes of both modalities are mutually guided, jointly facilitating CNN to ‘see’ the true visual patterns of PCa. The classification results of multimodal CNNs are further combined with the results based on handcrafted features using a support vector machine classifier. To achieve a satisfactory accuracy for clinical use, we comprehensively investigate three critical factors which could greatly affect the performance of our multimodal CNNs but have not been carefully studied previously. (1) Given limited training data, how can these be augmented in sufficient numbers and variety for fine-tuning deep CNN networks for PCa diagnosis? (2) How can multimodal MP-MRI information be effectively combined in CNNs? (3) What is the impact of different CNN architectures on the accuracy of PCa diagnosis? Experimental results on extensive clinical data from 364 patients with a total of 463 PCa lesions and 450 identified noncancerous image patches demonstrate that our system can achieve a sensitivity of 89.85% and a specificity of 95.83% for distinguishing cancer from noncancerous tissues and a sensitivity of 100% and a specificity of 76.92% for distinguishing indolent PCa from CS PCa. This result is significantly superior to the state-of-the-art method relying on handcrafted features.

Magnetic Nanoparticles for Multi-Imaging and Drug Delivery

PubMed Central

Lee, Jae-Hyun; Kim, Ji-wook; Cheon, Jinwoo

2013-01-01

Various bio-medical applications of magnetic nanoparticles have been explored during the past few decades. As tools that hold great potential for advancing biological sciences, magnetic nanoparticles have been used as platform materials for enhanced magnetic resonance imaging (MRI) agents, biological separation and magnetic drug delivery systems, and magnetic hyperthermia treatment. Furthermore, approaches that integrate various imaging and bioactive moieties have been used in the design of multi-modality systems, which possess synergistically enhanced properties such as better imaging resolution and sensitivity, molecular recognition capabilities, stimulus responsive drug delivery with on-demand control, and spatio-temporally controlled cell signal activation. Below, recent studies that focus on the design and synthesis of multi-mode magnetic nanoparticles will be briefly reviewed and their potential applications in the imaging and therapy areas will be also discussed. PMID:23579479

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Concentric core optical fiber with multiple-mode signal transmission

DOEpatents

Muhs, J.D.

1997-05-06

A concentric core optical fiber provides for the simultaneous but independent transmission of signals over a single optical fiber. The concentric optical fiber is constructed of a single-mode or multimode inner optical fiber defined by a core and a cladding of a lower index of refraction than the core and an outer optical fiber defined by additional cladding concentrically disposed around the cladding and of an index of refraction lower than the first mentioned cladding whereby the latter functions as the core of the outer optical fiber. By employing such an optical fiber construction with a single-mode inner core or optical fiber, highly sensitive interferometric and stable less sensitive amplitude based sensors can be placed along the same length of a concentric core optical fiber. Also, by employing the concentric core optical fiber secure telecommunications can be achieved via the inner optical fiber since an intrusion of the concentric optical fiber will first cause a variation in the light being transmitted through the outer optical fiber and this variation of light being used to trigger a suitable alarm indicative of the intrusion. 3 figs.

Concentric core optical fiber with multiple-mode signal transmission

DOEpatents

Muhs, Jeffrey D.

1997-01-01

A concentric core optical fiber provides for the simultaneous but independent transmission of signals over a single optical fiber. The concentric optical fiber is constructed of a single-mode or multimode inner optical fiber defined by a core and a cladding of a lower index of refraction than the core and an outer optical fiber defined by additional cladding concentrically disposed around the cladding and of an index of refraction lower than the first mentioned cladding whereby the latter functions as the core of the outer optical fiber. By employing such an optical fiber construction with a single-mode inner core or optical fiber, highly sensitive interferometric and stable less sensitive amplitude based sensors can be placed along the same length of a concentric core optical fiber. Also, by employing the concentric core optical fiber secure telecommunications can be achieved via the inner optical fiber since an intrusion of the concentric optical fiber will first cause a variation in the light being transmitted through the outer optical fiber and this variation of light being used to trigger a suitable alarm indicative of the intrusion.

Detail-enhanced multimodality medical image fusion based on gradient minimization smoothing filter and shearing filter.

PubMed

Liu, Xingbin; Mei, Wenbo; Du, Huiqian

2018-02-13

In this paper, a detail-enhanced multimodality medical image fusion algorithm is proposed by using proposed multi-scale joint decomposition framework (MJDF) and shearing filter (SF). The MJDF constructed with gradient minimization smoothing filter (GMSF) and Gaussian low-pass filter (GLF) is used to decompose source images into low-pass layers, edge layers, and detail layers at multiple scales. In order to highlight the detail information in the fused image, the edge layer and the detail layer in each scale are weighted combined into a detail-enhanced layer. As directional filter is effective in capturing salient information, so SF is applied to the detail-enhanced layer to extract geometrical features and obtain directional coefficients. Visual saliency map-based fusion rule is designed for fusing low-pass layers, and the sum of standard deviation is used as activity level measurement for directional coefficients fusion. The final fusion result is obtained by synthesizing the fused low-pass layers and directional coefficients. Experimental results show that the proposed method with shift-invariance, directional selectivity, and detail-enhanced property is efficient in preserving and enhancing detail information of multimodality medical images. Graphical abstract The detailed implementation of the proposed medical image fusion algorithm.

“RaMassays”: Synergistic Enhancement of Plasmon-Free Raman Scattering and Mass Spectrometry for Multimodal Analysis of Small Molecules

PubMed Central

Alessandri, Ivano; Vassalini, Irene; Bertuzzi, Michela; Bontempi, Nicolò; Memo, Maurizio; Gianoncelli, Alessandra

2016-01-01

SiO2/TiO2 core/shell (T-rex) beads were exploited as “all-in-one” building-block materials to create analytical assays that combine plasmon-free surface enhanced Raman scattering (SERS) and surface assisted laser desorption/ionization (SALDI) mass spectrometry (RaMassays). Such a multi-modal approach relies on the unique optical properties of T-rex beads, which are able to harvest and manage light in both UV and Vis range, making ionization and Raman scattering more efficient. RaMassays were successfully applied to the detection of small (molecular weight, M.W. <400 Da) molecules with a key relevance in biochemistry and pharmaceutical analysis. Caffeine and cocaine were utilized as molecular probes to test the combined SERS/SALDI response of RaMassays, showing excellent sensitivity and reproducibility. The differentiation between amphetamine/ephedrine and theophylline/theobromine couples demonstrated the synergistic reciprocal reinforcement of SERS and SALDI. Finally, the conversion of L-tyrosine in L-DOPA was utilized to probe RaMassays as analytical tools for characterizing reaction intermediates without introducing any spurious effects. RaMassays exhibit important advantages over plasmonic nanoparticles in terms of reproducibility, absence of interference and potential integration in multiplexed devices. PMID:27698368

Understanding transit ridership demand for a multi-destination, multimodal transit network in an American metropolitan area : lessons for increasing choice ridership while maintaining transit dependent ridership.

DOT National Transportation Integrated Search

2012-01-01

This study examines the factors underlying transit demand in the multi-destination, integrated bus and rail transit network for Atlanta, Georgia. Atlanta provides an opportunity to explore the consequences of a multi-destination transit network for b...

Understanding transit ridership demand for a multi-destination, multimodal transit network in an American metropolitan area : lessons for increasing choice ridership while maintaining transit dependent ridership : [research brief].

DOT National Transportation Integrated Search

2012-01-01

Recent research indicates that multi-destination transit systems are far more effective in attracting passengers than central business district (CBD)-focused systems. However, the same research suggests that multi-destination systems appeal largely t...

Using Multi-Media Projects to Foster Teacher Candidates' Multiple Literacy Skills

ERIC Educational Resources Information Center

Lawrence, Salika A.

2010-01-01

This article describes the strategies used to incorporate multi-modal technology literacy experiences into a graduate level course for literacy specialists. The candidates created a multi-media project in response to literature. Their projects revealed that the teacher candidates used a variety of sources to create the project but the Internet was…

Multipoint to multipoint routing and wavelength assignment in multi-domain optical networks

NASA Astrophysics Data System (ADS)

Qin, Panke; Wu, Jingru; Li, Xudong; Tang, Yongli

2018-01-01

In multi-point to multi-point (MP2MP) routing and wavelength assignment (RWA) problems, researchers usually assume the optical networks to be a single domain. However, the optical networks develop toward to multi-domain and larger scale in practice. In this context, multi-core shared tree (MST)-based MP2MP RWA are introduced problems including optimal multicast domain sequence selection, core nodes belonging in which domains and so on. In this letter, we focus on MST-based MP2MP RWA problems in multi-domain optical networks, mixed integer linear programming (MILP) formulations to optimally construct MP2MP multicast trees is presented. A heuristic algorithm base on network virtualization and weighted clustering algorithm (NV-WCA) is proposed. Simulation results show that, under different traffic patterns, the proposed algorithm achieves significant improvement on network resources occupation and multicast trees setup latency in contrast with the conventional algorithms which were proposed base on a single domain network environment.

High-brightness power delivery for fiber laser pumping: simulation and measurement of low-NA fiber guiding

NASA Astrophysics Data System (ADS)

Yanson, Dan; Levy, Moshe; Peleg, Ophir; Rappaport, Noam; Shamay, Moshe; Dahan, Nir; Klumel, Genady; Berk, Yuri; Baskin, Ilya

2015-02-01

Fiber laser manufacturers demand high-brightness laser diode pumps delivering optical pump energy in both a compact fiber core and narrow angular content. A pump delivery fiber of a 105 μm core and 0.22 numerical aperture (NA) is typically used, where the fiber NA is under-filled to ease the launch of laser diode emission into the fiber and make the fiber tolerant to bending. At SCD, we have developed multi-emitter fiber-coupled pump modules that deliver 50 W output from a 105 μm, 0.15 NA fiber at 915, 950 and 976 nm wavelengths enabling low-NA power delivery to a customer's fiber laser network. In this work, we address the challenges of coupling and propagating high optical powers from laser diode sources in weakly guiding step-index multimode fibers. We present simulations of light propagation inside the low-NA multimode fiber for different launch conditions and fiber bend diameters using a ray-racing tool and demonstrate how these affect the injection of light into cladding-bounded modes. The mode filling at launch and source NA directly limit the bend radius at which the fiber can be coiled. Experimentally, we measure the fiber bend loss using our 50 W fiber-coupled module and establish a critical bend diameter in agreement with our simulation results. We also employ thermal imaging to investigate fiber heating caused by macro-bends and angled cleaving. The low mode filling of the 0.15 NA fiber by our brightness-enhanced laser diodes allows it to be coiled with diameters down to 70 mm at full operating power despite the low NA and further eliminates the need for mode-stripping at fiber combiners and splices downstream from our pump modules.

Efficient Heat Dissipation of Uncooled 400-Gbps (16×25-Gbps) Optical Transceiver Employing Multimode VCSEL and PD Arrays

NASA Astrophysics Data System (ADS)

Shih, Tien-Tsorng; Chi, Yu-Chieh; Wang, Ruei-Nian; Wu, Chao-Hsin; Huang, Jian-Jang; Jou, Jau-Ji; Lee, Tai-Cheng; Kuo, Hao-Chung; Lin, Gong-Ru; Cheng, Wood-Hi

2017-04-01

An effective heat dissipation of uncooled 400-Gbps (16×25-Gbps) form-factor pluggable (CDFP) optical transceiver module employing chip-on-board multimode 25-Gbps vertical-surface-emitting-laser (VCSEL) and 25-Gbps photodiode (PD) arrays mounted on a brass metal core embedded within a printed circuit board (PCB) is proposed and demonstrated. This new scheme of the hollow PCB filling with thermally-dissipated brass metal core was simulated and used for high temperature and long term stability operation of the proposed 400-Gbps CDFP transceiver. During one-hour testing, a red-shift of central wavelength by 0.4-nm corresponding temperature increment of 6.7 °C was observed with the brass core assisted cooler module. Such a temperature change was significantly lower than that of 28.3 °C for the optical transceiver driven with conventional circuit board. After 100-m distance transmission over a multimode fiber (OM4), the 400-Gbps CDFP transceiver exhibited dispersion penalty of 2.6-dB, power budget of ≧ 3-dB, link loss of ≦ 0.63-dB, mask margin of 20%, and bit error rate (BER) of <10-12 with maintained stability more than one hour. The developed 400-Gbps CDFP transceiver module employing low-power consumption VCSEL and PD arrays, effective coupling lens arrays, and well thermal-dissipation brass metal core is suitable for use in the low-cost and high-performance data center applications.

Hybrid Core-Shell (HyCoS) Nanoparticles produced by Complex Coacervation for Multimodal Applications

NASA Astrophysics Data System (ADS)

Vecchione, D.; Grimaldi, A. M.; Forte, E.; Bevilacqua, Paolo; Netti, P. A.; Torino, E.

2017-03-01

Multimodal imaging probes can provide diagnostic information combining different imaging modalities. Nanoparticles (NPs) can contain two or more imaging tracers that allow several diagnostic techniques to be used simultaneously. In this work, a complex coacervation process to produce core-shell completely biocompatible polymeric nanoparticles (HyCoS) for multimodal imaging applications is described. Innovations on the traditional coacervation process are found in the control of the reaction temperature, allowing a speeding up of the reaction itself, and the production of a double-crosslinked system to improve the stability of the nanostructures in the presence of a clinically relevant contrast agent for MRI (Gd-DTPA). Through the control of the crosslinking behavior, an increase up to 6 times of the relaxometric properties of the Gd-DTPA is achieved. Furthermore, HyCoS can be loaded with a high amount of dye such as ATTO 633 or conjugated with a model dye such as FITC for in vivo optical imaging. The results show stable core-shell polymeric nanoparticles that can be used both for MRI and for optical applications allowing detection free from harmful radiation. Additionally, preliminary results about the possibility to trigger the release of a drug through a pH effect are reported.

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA

PubMed Central

Mitrea, Diana M; Cika, Jaclyn A; Guy, Clifford S; Ban, David; Banerjee, Priya R; Stanley, Christopher B; Nourse, Amanda; Deniz, Ashok A; Kriwacki, Richard W

2016-01-01

The nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identify multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus. DOI: http://dx.doi.org/10.7554/eLife.13571.001 PMID:26836305

Using online modules is a multi-modality teaching system: a high-touch high-tech approach to geriatric education.

PubMed

Gainor, Sara Jane; Goins, R Turner; Miller, Lee Ann

2004-01-01

Making geriatric education available to rural faculty/preceptors, students, and practitioners presents many challenges. Often the only options considered for educating those in the health professions about geriatrics are either traditional face-to-face courses or distance education programs. The purpose of this paper was to examine the use of Web-based modules or courses and other distance learning technology in concert with traditional learning modalities. The Mountain State Geriatric Education Center explored the use of a multi-modal approach within a high-touch, high-tech framework. Our findings indicate the following: it is important to start where participants are ready to begin; flexibility and variety are needed; soliciting evaluative feedback from participants is valuable; there is a need to integrate distance learning with more traditional modalities; and a high-tech, high-touch approach provides a format which participants find acceptable, accessible, and attractive. This assertion does not rule out the use of technology for distance education but rather encourages educators to take advantage of a wide range of modalities, traditional and technological, to reach rural practitioners, faculty, and students.

Multi-mode sensor processing on a dynamically reconfigurable massively parallel processor array

NASA Astrophysics Data System (ADS)

Chen, Paul; Butts, Mike; Budlong, Brad; Wasson, Paul

2008-04-01

This paper introduces a novel computing architecture that can be reconfigured in real time to adapt on demand to multi-mode sensor platforms' dynamic computational and functional requirements. This 1 teraOPS reconfigurable Massively Parallel Processor Array (MPPA) has 336 32-bit processors. The programmable 32-bit communication fabric provides streamlined inter-processor connections with deterministically high performance. Software programmability, scalability, ease of use, and fast reconfiguration time (ranging from microseconds to milliseconds) are the most significant advantages over FPGAs and DSPs. This paper introduces the MPPA architecture, its programming model, and methods of reconfigurability. An MPPA platform for reconfigurable computing is based on a structural object programming model. Objects are software programs running concurrently on hundreds of 32-bit RISC processors and memories. They exchange data and control through a network of self-synchronizing channels. A common application design pattern on this platform, called a work farm, is a parallel set of worker objects, with one input and one output stream. Statically configured work farms with homogeneous and heterogeneous sets of workers have been used in video compression and decompression, network processing, and graphics applications.

Experimental Investigation of Multi-mode Fiber Laser Cutting of Cement Mortar.

PubMed

Lee, Dongkyoung; Pyo, Sukhoon

2018-02-10

This study successfully applied multi-mode laser cutting with the variation of the laser cutting speed to cement mortar for the first time. The effects of the amount of silica sand in the cement mortar on laser cutting are tested and analyzed. The kerf width and penetration depth of the specimens after laser cutting are investigated. As the laser cutting speed increases, the penetration depth decreases for both cement paste and cement mortar, whereas the kerf width becomes saturated and increases, respectively, for cement paste and cement mortar. Cross sections of the specimens are compared with illustrations. Top-view images of the cement mortar with indicators of the physical characteristics, such as re-solidification, burning, and cracks are examined, and the possible causes of these characteristics are explained. The optical absorption rates of cement-based materials are quantified at wide ranges of wavelength to compare the absorption rates in accordance with the materials compositions. The chemical composition variation before and after laser cutting is also compared by EDX (Energy Dispersive X-Ray) analysis. In addition to these observations, material removal mechanisms for cement mortar are proposed.

Experimental Investigation of Multi-mode Fiber Laser Cutting of Cement Mortar

PubMed Central

2018-01-01

This study successfully applied multi-mode laser cutting with the variation of the laser cutting speed to cement mortar for the first time. The effects of the amount of silica sand in the cement mortar on laser cutting are tested and analyzed. The kerf width and penetration depth of the specimens after laser cutting are investigated. As the laser cutting speed increases, the penetration depth decreases for both cement paste and cement mortar, whereas the kerf width becomes saturated and increases, respectively, for cement paste and cement mortar. Cross sections of the specimens are compared with illustrations. Top-view images of the cement mortar with indicators of the physical characteristics, such as re-solidification, burning, and cracks are examined, and the possible causes of these characteristics are explained. The optical absorption rates of cement-based materials are quantified at wide ranges of wavelength to compare the absorption rates in accordance with the materials compositions. The chemical composition variation before and after laser cutting is also compared by EDX (Energy Dispersive X-Ray) analysis. In addition to these observations, material removal mechanisms for cement mortar are proposed. PMID:29439431

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA

DOE PAGES

Mitrea, Diana M.; Cika, Jaclyn A.; Guy, Clifford S.; ...

2016-02-02

In this study, the nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identifymore » multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus.« less

Orbital angular momentum mode groups multiplexing transmission over 2.6-km conventional multi-mode fiber.

PubMed

Zhu, Long; Wang, Andong; Chen, Shi; Liu, Jun; Mo, Qi; Du, Cheng; Wang, Jian

2017-10-16

Twisted light carrying orbital angular momentum (OAM) is a special kind of structured light that has a helical phase front, a phase singularity, and a doughnut intensity profile. Beyond widespread developments in manipulation, microscopy, metrology, astronomy, nonlinear and quantum optics, OAM-carrying twisted light has seen emerging application of optical communications in free space and specially designed fibers. Instead of specialty fibers, here we show the direct use of a conventional graded-index multi-mode fiber (MMF) for OAM communications. By exploiting fiber-compatible mode exciting and filtering elements, we excite the first four OAM mode groups in an MMF. We demonstrate 2.6-km MMF transmission using four data-carrying OAM mode groups (OAM 0,1 , OAM +1,1 /OAM -1,1 , OAM +2,1 , OAM +3,1 ). Moreover, we demonstrate two data-carrying OAM mode groups multiplexing transmission over the 2.6-km MMF with low-level crosstalk free of multiple-input multiple-output digital signal processing (MIMO-DSP). The demonstrations may open up new perspectives to fiber-based OAM communication/non-communication applications using already existing conventional fibers.

Development and implementation of an integrated, multi-modality, user-centered interactive dietary change program

PubMed Central

Glasgow, Russell E.; Christiansen, Steve; Smith, K. Sabina; Stevens, Victor J.; Toobert, Deborah J.

2009-01-01

Computer-tailored behavior change programs offer the potential for reaching large populations at a much lower cost than individual or group-based programs. However, few of these programs to date appear to integrate behavioral theory with user choice, or combine different electronic modalities. We describe the development of an integrated CD-ROM and interactive voice response dietary change intervention that combines behavioral problem-solving theory with a high degree of user choice. The program, WISE CHOICES, is being evaluated as part of an ongoing trial. This paper describes the program development, emphasizing how user preferences are accommodated, and presents implementation and user satisfaction data. The program was successfully implemented; the linkages among the central database, the CD-ROM and the automated telephone components were robust, and participants liked the program almost as well as a counselor-delivered dietary change condition. Multi-modality programs that emphasize the strengths of each approach appear to be feasible. Future research is needed to determine the program impact and cost-effectiveness compared with counselor-delivered intervention. PMID:18711204

Neural simulations on multi-core architectures.

PubMed

Eichner, Hubert; Klug, Tobias; Borst, Alexander

2009-01-01

Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i.e. user-transparent load balancing.

Neural Simulations on Multi-Core Architectures

PubMed Central

Eichner, Hubert; Klug, Tobias; Borst, Alexander

2009-01-01

Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i.e. user-transparent load balancing. PMID:19636393

Sequencing Embedded Multimodal Representations in a Writing to Learn Approach to the Teaching of Electricity

ERIC Educational Resources Information Center

Hand, Brian; Gunel, Murat; Ulu, Cuneyt

2009-01-01

In the study of science topics especially in physics students are expected to move between different modes of representation when dealing with a particular concept as any science concept can be represented in several different modes. The difficulty for students is that they are often unable to move between these multi-modal representations and…

Optofluidic devices for biomolecule sensing and multiplexing

NASA Astrophysics Data System (ADS)

Ozcelik, Damla

Optofluidics which integrates photonics and microfluidics, has led to highly compact, sensitive and adaptable biomedical sensors. Optofluidic biosensors based on liquid-core anti-resonant reflecting optical waveguides (LC-ARROWs), have proven to be a highly sensitive, portable, and reconfigurable platform for fluorescence spectroscopy and detection of single biomolecules such as proteins, nucleic acids, and virus particles. However, continued improvements in sensitivity remain a major goal as we approach the ultimate limit of detecting individual bio-particles labeled by single or few fluorophores. Additionally, the ability to simultaneously detect and identify multiple biological particles or biomarkers is one of the key requirements for molecular diagnostic tests. The compactness and adaptability of these platforms can further be advanced by introducing tunability, integrating off-chip components, designing reconfigurable and customizable devices, which makes these platforms very good candidates for many different applications. The goal of this thesis was to introduce new elements in these LC-ARROW optofluidics platforms that provide major enhancements in their functionality, making them more sensitive, compact, customizable and multiplexed. First, a novel integrated tunable spectral filter that achieves effective elimination of background noise on the ARROW platform was demonstrated. A unique dual liquid-core design enabled the independent multi-wavelength tuning of the spectral filter by adjusting the refractive index and chemical properties of the liquid. In order to enhance the detection sensitivity of the platform, Y-splitter waveguides were integrated to create multiple excitation spots for each target molecule. A powerful signal processing algorithm was used to analyze the data to improve the signal-to-noise ratio (SNR) of the collected data. Next, the design, optimization and characterization of the Y-splitter waveguides are presented; and single influenza virus detection with an improved SNR was demonstrated using this platform. Finally, multiplexing capacity is introduced to the ARROW detection platform by integrating multi-mode interference (MMI) waveguides. MMI waveguides create wavelength dependent multiple excitation spots at the excitation region, allowing the spectral multiplexed detection of multiple different target molecules based on the excitation pattern, without the need for additional spectral filters. Successful spectral multiplexed detection of three different types of influenza viruses is achieved by using separate wavelengths and combination of wavelengths. This multiplexing capacity is further enhanced by taking advantage of the spatial properties of the MMI pattern, designing triple liquid-core waveguides that intersect the MMI waveguide in different locations. Furthermore, the spectral and spatial multiplexing capacities are combined in these triple liquid-core MMI platforms, allowing these devices to distinguish multiple different targets and samples simultaneously.

Multi-modal spectroscopic imaging with synchrotron light to study mechanisms of brain disease

NASA Astrophysics Data System (ADS)

Summers, Kelly L.; Fimognari, Nicholas; Hollings, Ashley; Kiernan, Mitchell; Lam, Virginie; Tidy, Rebecca J.; Takechi, Ryu; George, Graham N.; Pickering, Ingrid J.; Mamo, John C.; Harris, Hugh H.; Hackett, Mark J.

2017-04-01

The international health care costs associated with Alzheimer's disease (AD) and dementia have been predicted to reach $2 trillion USD by 2030. As such, there is urgent need to develop new treatments and diagnostic methods to stem an international health crisis. A major limitation to therapy and diagnostic development is the lack of complete understanding about the disease mechanisms. Spectroscopic methods at synchrotron light sources, such as FTIR, XRF, and XAS, offer a "multi-modal imaging platform" to reveal a wealth of important biochemical information in situ within ex vivo tissue sections, to increase our understanding of disease mechanisms.

Composite PET and MRI for accurate localization and metabolic modeling: a very useful tool for research and clinic

NASA Astrophysics Data System (ADS)

Bidaut, Luc M.

1991-06-01

In order to help in analyzing PET data and really take advantage of their metabolic content, a system was designed and implemented to align and process data from various medical imaging modalities, particularly (but not only) for brain studies. Although this system is for now mostly used for anatomical localization, multi-modality ROIs and pharmaco-kinetic modeling, more multi-modality protocols will be implemented in the future, not only to help in PET reconstruction data correction and semi-automated ROI definition, but also for helping in improving diagnostic accuracy along with surgery and therapy planning.

Results from the commissioning of a multi-modal endoscope for ultrasound and time of flight PET

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

Bugalho, Ricardo

2015-07-01

The EndoTOFPET-US collaboration has developed a multi-modal imaging system combining Ultrasound with Time-of-Flight Positron Emission Tomography into an endoscopic imaging device. The objective of the project is to obtain a coincidence time resolution of about 200 ps FWHM and to achieve about 1 mm spatial resolution of the PET system, while integrating all the components in a very compact detector suitable for endoscopic use. This scanner aims to be exploited for diagnostic and surgical oncology, as well as being instrumental in the clinical test of new biomarkers especially targeted for prostate and pancreatic cancer. (authors)

The multi-mode polarization modulation spectrometer: part 1: simultaneous detection of absorption, turbidity, and optical activity.

PubMed

Arvinte, Tudor; Bui, Tam T T; Dahab, Ali A; Demeule, Barthélemy; Drake, Alex F; Elhag, Dhia; King, Peter

2004-09-01

Circular dichroism (CD) is an important spectroscopic technique for monitoring chirality and biological macromolecule conformation. However, during a CD measurement, absorbance, light scattering/turbidity, and fluorescence can also be detected. The simultaneous measurement of these different spectral features for a single sample is the basis of a multi-mode optical spectrometer. This allows time-efficient gathering of complementary information and provides a scheme to ensure that CD measurements are reliable. Aspects of circular polarization differential light scattering, pH, and temperature variation of a protein (antibody) solution are described. A procedure to help ensure that CD measurements are reliable is described.

Efficient multi-mode to single-mode coupling in a photonic lantern.

PubMed

Noordegraaf, Danny; Skovgaard, Peter M W; Nielsen, Martin D; Bland-Hawthorn, Joss

2009-02-02

We demonstrate the fabrication of a high performance multi-mode (MM) to single-mode (SM) splitter or "photonic lantern", first described by Leon-Saval et al. (2005). Our photonic lantern is a solid all-glass version, and we show experimentally that this device can be used to achieve efficient and reversible coupling between a MM fiber and a number of SM fibers, when perfectly matched launch conditions into the MM fiber are ensured. The fabricated photonic lantern has a coupling loss for a MM to SM tapered transition of only 0.32 dB which proves the feasibility of the technology.

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

PubMed Central

Kim, Youngmin; Lee, Chan-Gun

2017-01-01

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods. PMID:29240695

A multi-modal training programme to improve physical activity, physical fitness and perceived physical ability in obese children.

PubMed

Morano, Milena; Colella, Dario; Rutigliano, Irene; Fiore, Pietro; Pettoello-Mantovani, Massimo; Campanozzi, Angelo

2014-01-01

Actual and perceived physical abilities are important correlates of physical activity (PA) and fitness, but little research has explored these relationships over time in obese children. This study was designed: (a) to assess the feasibility of a multi-modal training programme promoting changes in PA, fundamental motor skills and real and perceived physical abilities of obese children; and (b) to explore cross-sectional and longitudinal relationships between real and perceived physical competence in boys and girls. Forty-one participants (9.2 ± 1.2 years) were assessed before and after an 8-month intervention with respect to body composition, physical fitness, self-reported PA and perceived physical ability. After treatment, obese children reported improvements in the body mass index, PA levels, gross motor performance and actual and perceived physical abilities. Real and perceived physical competence was correlated in boys, but not in girls. Results indicate that a multi-modal programme focused on actual and perceived physical competence as associated with the gradual increase in the volume of activity might be an effective strategy to improve adherence of the participants and to increase the lifelong exercise skills of obese children.

Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology.

PubMed

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery.

Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

PubMed Central

Joshi, Bishnu P.; Wang, Thomas D.

2010-01-01

Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research. PMID:22180839

Differences in Multi-Modal Ultrasound Imaging between Triple Negative and Non-Triple Negative Breast Cancer.

PubMed

Li, Ziyao; Tian, Jiawei; Wang, Xiaowei; Wang, Ying; Wang, Zhenzhen; Zhang, Lei; Jing, Hui; Wu, Tong

2016-04-01

The objective of this study was to identify multi-modal ultrasound imaging parameters that could potentially help to differentiate between triple negative breast cancer (TNBC) and non-TNBC. Conventional ultrasonography, ultrasound strain elastography and 3-D ultrasound (3-D-US) findings from 50 TNBC and 179 non-TNBC patients were retrospectively reviewed. Immunohistochemical examination was used as the reference gold standard for cancer subtyping. Different ultrasound modalities were initially analyzed to define TNBC-related features. Subsequently, logistic regression analysis was applied to TNBC-related features to establish models for predicting TNBC. TNBCs often presented as micro-lobulated, markedly hypo-echoic masses with an abrupt interface (p = 0.015, 0.0015 and 0.004, compared with non-TNBCs, respectively) on conventional ultrasound, and showed a diminished retraction pattern phenomenon in the coronal plane (p = 0.035) on 3-D-US. Our findings suggest that B-mode ultrasound and 3-D-US in multi-modality ultrasonography could be a useful non-invasive technique for differentiating TNBCs from non-TNBCs. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology

PubMed Central

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery. PMID:25250092

Enhancing image classification models with multi-modal biomarkers

NASA Astrophysics Data System (ADS)

Caban, Jesus J.; Liao, David; Yao, Jianhua; Mollura, Daniel J.; Gochuico, Bernadette; Yoo, Terry

2011-03-01

Currently, most computer-aided diagnosis (CAD) systems rely on image analysis and statistical models to diagnose, quantify, and monitor the progression of a particular disease. In general, CAD systems have proven to be effective at providing quantitative measurements and assisting physicians during the decision-making process. As the need for more flexible and effective CADs continues to grow, questions about how to enhance their accuracy have surged. In this paper, we show how statistical image models can be augmented with multi-modal physiological values to create more robust, stable, and accurate CAD systems. In particular, this paper demonstrates how highly correlated blood and EKG features can be treated as biomarkers and used to enhance image classification models designed to automatically score subjects with pulmonary fibrosis. In our results, a 3-5% improvement was observed when comparing the accuracy of CADs that use multi-modal biomarkers with those that only used image features. Our results show that lab values such as Erythrocyte Sedimentation Rate and Fibrinogen, as well as EKG measurements such as QRS and I:40, are statistically significant and can provide valuable insights about the severity of the pulmonary fibrosis disease.

LapTrain: multi-modality training curriculum for laparoscopic cholecystectomy-results of a randomized controlled trial.

PubMed

Kowalewski, K F; Garrow, C R; Proctor, T; Preukschas, A A; Friedrich, M; Müller, P C; Kenngott, H G; Fischer, L; Müller-Stich, B P; Nickel, F

2018-02-12

Multiple training modalities for laparoscopy have different advantages, but little research has been conducted on the benefit of a training program that includes multiple different training methods compared to one method only. This study aimed to evaluate benefits of a combined multi-modality training program for surgical residents. Laparoscopic cholecystectomy (LC) was performed on a porcine liver as the pre-test. Randomization was stratified for experience to the multi-modality Training group (12 h of training on Virtual Reality (VR) and box trainer) or Control group (no training). The post-test consisted of a VR LC and porcine LC. Performance was rated with the Global Operative Assessment of Laparoscopic Skills (GOALS) score by blinded experts. Training (n = 33) and Control (n = 31) were similar in the pre-test (GOALS: 13.7 ± 3.4 vs. 14.7 ± 2.6; p = 0.198; operation time 57.0 ± 18.1 vs. 63.4 ± 17.5 min; p = 0.191). In the post-test porcine LC, Training had improved GOALS scores (+ 2.84 ± 2.85 points, p < 0.001), while Control did not (+ 0.55 ± 2.34 points, p = 0.154). Operation time in the post-test was shorter for Training vs. Control (40.0 ± 17.0 vs. 55.0 ± 22.2 min; p = 0.012). Junior residents improved GOALS scores to the level of senior residents (pre-test: 13.7 ± 2.7 vs. 18.3 ± 2.9; p = 0.010; post-test: 15.5 ± 3.4 vs. 18.8 ± 3.8; p = 0.120) but senior residents remained faster (50.1 ± 20.6 vs. 25.0 ± 1.9 min; p < 0.001). No differences were found between groups on the post-test VR trainer. Structured multi-modality training is beneficial for novices to improve basics and overcome the initial learning curve in laparoscopy as well as to decrease operation time for LCs in different stages of experience. Future studies should evaluate multi-modality training in comparison with single modalities. German Clinical Trials Register DRKS00011040.

Fully-elastic multi-granular network with space/frequency/time switching using multi-core fibres and programmable optical nodes.

PubMed

Amaya, N; Irfan, M; Zervas, G; Nejabati, R; Simeonidou, D; Sakaguchi, J; Klaus, W; Puttnam, B J; Miyazawa, T; Awaji, Y; Wada, N; Henning, I

2013-04-08

We present the first elastic, space division multiplexing, and multi-granular network based on two 7-core MCF links and four programmable optical nodes able to switch traffic utilising the space, frequency and time dimensions with over 6000-fold bandwidth granularity. Results show good end-to-end performance on all channels with power penalties between 0.75 dB and 3.7 dB.

Experimental Study of the Richtmyer-Meshkov Instability of Incompressible Fluids

NASA Technical Reports Server (NTRS)

Niederhaus, Charles; Jacobs, Jeffrey W.

2002-01-01

The Richtmyer-Meshkov instability of a low Atwood number, miscible, two-liquid system is investigated experimentally. The initially stratified fluids are contained within a rectangular tank mounted to a sled that rides on a vertical set of rails. The instability is generated by dropping the sled onto a coil spring, producing a nearly impulsive upward acceleration. The subsequent freefall that occurs as the container travels upward and then downward on the rails allows the instability to evolve in the absence of gravity. The interface separating the two liquids initially has a well-defined, sinusoidal perturbation that quickly inverts and then grows in amplitude after undergoing the impulsive acceleration. Disturbance amplitudes are measured and compared to theoretical predictions. Linear stability theory gives excellent agreement with the measured initial growth rate, a(sub 0), for single-mode perturbations with the predicted amplitudes differing by less than 10% from experimental measurements up to a nondimensional time ka(sub 0)t = 0.7, where k is the wavenumber. Linear stability theory also provides excellent agreement for the individual mode amplitudes of multi-mode initial perturbations up until the interface becomes multi-valued. Comparison with previously published weakly nonlinear single-mode models shows good agreement up to ka(sub 0)t = 3, while published nonlinear single-mode models provide good agreement up to ka(sub 0)t = 30. The effects of Reynolds number on the vortex core evolution and overall growth rate of the interface are also investigated. Measurements of the overall amplitude are found to be unaffected by the Reynolds number for the range of values studied here. However, experiments carried out at lower values of Reynolds numbers were found to have decreased vortex core rotation rates. In addition, an instability in the vortex cores is observed.

Construction of a multimodal CT-video chest model

NASA Astrophysics Data System (ADS)

Byrnes, Patrick D.; Higgins, William E.

2014-03-01

Bronchoscopy enables a number of minimally invasive chest procedures for diseases such as lung cancer and asthma. For example, using the bronchoscope's continuous video stream as a guide, a physician can navigate through the lung airways to examine general airway health, collect tissue samples, or administer a disease treatment. In addition, physicians can now use new image-guided intervention (IGI) systems, which draw upon both three-dimensional (3D) multi-detector computed tomography (MDCT) chest scans and bronchoscopic video, to assist with bronchoscope navigation. Unfortunately, little use is made of the acquired video stream, a potentially invaluable source of information. In addition, little effort has been made to link the bronchoscopic video stream to the detailed anatomical information given by a patient's 3D MDCT chest scan. We propose a method for constructing a multimodal CT-video model of the chest. After automatically computing a patient's 3D MDCT-based airway-tree model, the method next parses the available video data to generate a positional linkage between a sparse set of key video frames and airway path locations. Next, a fusion/mapping of the video's color mucosal information and MDCT-based endoluminal surfaces is performed. This results in the final multimodal CT-video chest model. The data structure constituting the model provides a history of those airway locations visited during bronchoscopy. It also provides for quick visual access to relevant sections of the airway wall by condensing large portions of endoscopic video into representative frames containing important structural and textural information. When examined with a set of interactive visualization tools, the resulting fused data structure provides a rich multimodal data source. We demonstrate the potential of the multimodal model with both phantom and human data.

Rat experimental model of myocardial ischemia/reperfusion injury: an ethical approach to set up the analgesic management of acute post-surgical pain.

PubMed

Ciuffreda, Maria Chiara; Tolva, Valerio; Casana, Renato; Gnecchi, Massimiliano; Vanoli, Emilio; Spazzolini, Carla; Roughan, John; Calvillo, Laura

2014-01-01

During the past 30 years, myocardial ischemia/reperfusion injury in rodents became one of the most commonly used model in cardiovascular research. Appropriate pain-prevention appears critical since it may influence the outcome and the results obtained with this model. However, there are no proper guidelines for pain management in rats undergoing thoracic surgery. Accordingly, we evaluated three analgesic regimens in cardiac ischemia/reperfusion injury. This study was strongly focused on 3R's ethic principles, in particular the principle of Reduction. Rats undergoing surgery were treated with pre-surgical tramadol (45 mg/kg intra-peritoneal), or carprofen (5 mg/kg sub-cutaneous), or with pre-surgical administration of carprofen followed by 2 post-surgery tramadol injections (multi-modal group). We assessed behavioral signs of pain and made a subjective evaluation of stress and suffering one and two hours after surgery. Multi-modal treatment significantly reduced the number of signs of pain compared to carprofen alone at both the first hour (61±42 vs 123±47; p<0.05) and the second hour (43±21 vs 74±24; p<0.05) post-surgery. Tramadol alone appeared as effective as multi-modal treatment during the first hour, but signs of pain significantly increased one hour later (from 66±72 to 151±86, p<0.05). Carprofen alone was more effective at the second hour post-surgery when signs of pain reduced to 74±24 from 113±40 in the first hour (p<0.05). Stress behaviors during the second hour were observed in only 20% of rats in the multimodal group compared to 75% and 86% in the carprofen and tramadol groups, respectively (p<0.05). Multi-modal treatment with carprofen and tramadol was more effective in preventing pain during the second hour after surgery compared with both tramadol or carprofen. Our results suggest that the combination of carprofen and tramadol represent the best therapy to prevent animal pain after myocardial ischemia/reperfusion. We obtained our results accordingly with the ethical principle of Reduction.

Rat Experimental Model of Myocardial Ischemia/Reperfusion Injury: An Ethical Approach to Set up the Analgesic Management of Acute Post-Surgical Pain

PubMed Central

Ciuffreda, Maria Chiara; Tolva, Valerio; Casana, Renato; Gnecchi, Massimiliano; Vanoli, Emilio; Spazzolini, Carla; Roughan, John; Calvillo, Laura

2014-01-01

Rationale During the past 30 years, myocardial ischemia/reperfusion injury in rodents became one of the most commonly used model in cardiovascular research. Appropriate pain-prevention appears critical since it may influence the outcome and the results obtained with this model. However, there are no proper guidelines for pain management in rats undergoing thoracic surgery. Accordingly, we evaluated three analgesic regimens in cardiac ischemia/reperfusion injury. This study was strongly focused on 3R’s ethic principles, in particular the principle of Reduction. Methods Rats undergoing surgery were treated with pre-surgical tramadol (45 mg/kg intra-peritoneal), or carprofen (5 mg/kg sub-cutaneous), or with pre-surgical administration of carprofen followed by 2 post-surgery tramadol injections (multi-modal group). We assessed behavioral signs of pain and made a subjective evaluation of stress and suffering one and two hours after surgery. Results Multi-modal treatment significantly reduced the number of signs of pain compared to carprofen alone at both the first hour (61±42 vs 123±47; p<0.05) and the second hour (43±21 vs 74±24; p<0.05) post-surgery. Tramadol alone appeared as effective as multi-modal treatment during the first hour, but signs of pain significantly increased one hour later (from 66±72 to 151±86, p<0.05). Carprofen alone was more effective at the second hour post-surgery when signs of pain reduced to 74±24 from 113±40 in the first hour (p<0.05). Stress behaviors during the second hour were observed in only 20% of rats in the multimodal group compared to 75% and 86% in the carprofen and tramadol groups, respectively (p<0.05). Conclusions Multi-modal treatment with carprofen and tramadol was more effective in preventing pain during the second hour after surgery compared with both tramadol or carprofen. Our results suggest that the combination of carprofen and tramadol represent the best therapy to prevent animal pain after myocardial ischemia/reperfusion. We obtained our results accordingly with the ethical principle of Reduction. PMID:24756074

Unsupervised Segmentation of Head Tissues from Multi-modal MR Images for EEG Source Localization.

PubMed

Mahmood, Qaiser; Chodorowski, Artur; Mehnert, Andrew; Gellermann, Johanna; Persson, Mikael

2015-08-01

In this paper, we present and evaluate an automatic unsupervised segmentation method, hierarchical segmentation approach (HSA)-Bayesian-based adaptive mean shift (BAMS), for use in the construction of a patient-specific head conductivity model for electroencephalography (EEG) source localization. It is based on a HSA and BAMS for segmenting the tissues from multi-modal magnetic resonance (MR) head images. The evaluation of the proposed method was done both directly in terms of segmentation accuracy and indirectly in terms of source localization accuracy. The direct evaluation was performed relative to a commonly used reference method brain extraction tool (BET)-FMRIB's automated segmentation tool (FAST) and four variants of the HSA using both synthetic data and real data from ten subjects. The synthetic data includes multiple realizations of four different noise levels and several realizations of typical noise with a 20% bias field level. The Dice index and Hausdorff distance were used to measure the segmentation accuracy. The indirect evaluation was performed relative to the reference method BET-FAST using synthetic two-dimensional (2D) multimodal magnetic resonance (MR) data with 3% noise and synthetic EEG (generated for a prescribed source). The source localization accuracy was determined in terms of localization error and relative error of potential. The experimental results demonstrate the efficacy of HSA-BAMS, its robustness to noise and the bias field, and that it provides better segmentation accuracy than the reference method and variants of the HSA. They also show that it leads to a more accurate localization accuracy than the commonly used reference method and suggest that it has potential as a surrogate for expert manual segmentation for the EEG source localization problem.

Numerical analysis of a 3D optical sensor based on single mode fiber to multimode interference graphene design

NASA Astrophysics Data System (ADS)

Mutter, Kussay N.; Jafri, Zubir M.; Tan, Kok Chooi

2016-04-01

In this paper, the simulation and design of a waveguide for water turbidity sensing are presented. The structure of the proposed sensor uses a 2x2 array of multimode interference (MMI) coupler based on micro graphene waveguide for high sensitivity. The beam propagation method (BPM) are used to efficiently design the sensor structure. The structure is consist of an array of two by two elements of sensors. Each element has three sections of single mode for field input tapered to MMI as the main core sensor without cladding which is graphene based material, and then a single mode fiber as an output. In this configuration MMI responses to any change in the environment. We validate and present the results by implementing the design on a set of sucrose solution and showing how these samples lead to a sensitivity change in the sensor based on the MMI structures. Overall results, the 3D design has a feasible and effective sensing by drawing topographical distribution of suspended particles in the water.

Simulation of the novel compact structure of an interferometric biosensor based on multimode interference waveguides

NASA Astrophysics Data System (ADS)

Xhoxhi, Moisi; Dudia, Alma; Ymeti, Aurel

2017-05-01

We propose the novel structure of an interferometric biosensor based on multimode interference (MMI) waveguides. We present the design of the biosensor using eigenmode expansion (EME) method in accordance with the requirements and standards of today's photonic technology. The MMI structures with a 90 nm Si3N4 core are used as power splitters with 5 outputs. The 5 high-resolution images at the end of the multimode region show high power balance. We analyze the coupling efficiency of the laser source with the structure, the excess loss and power imbalance for different compact MMI waveguides with widths ranging from 45 μm to 15 μm. For a laser source with a tolerance of +/-1mm in linearization we could achieve a coupling efficiency of 52%. MMI waveguides with tapered channels show excess loss values under 0.5 dB and power imbalance values under 0.08 dB. In addition, we show that for a 10 nm deviation of the source wavelength from its optimal value and for a 10 μm deviation of the MMI length from its optimal value, the performance of the MMI waveguides remains acceptable. Finally, we analyze the power budget of the whole biosensor structure and show that it is sufficient for the proper operation of this device.

InP-based compact transversal filter for monolithically integrated light source array.

PubMed

Ueda, Yuta; Fujisawa, Takeshi; Takahata, Kiyoto; Kohtoku, Masaki; Ishii, Hiroyuki

2014-04-07

We developed an InP-based 4x1 transversal filter (TF) with multi-mode interference couplers (MMIs) as a compact wavelength multiplexer (MUX) 1700 μm x 400 μm in size. Furthermore, we converted the MMI-based TF to a reflection type to obtain an ultra-compact MUX of only 900 μm x 50 μm. These MUXs are made with a simple fabrication process and show a satisfactory wavelength filtering operation as MUXs of monolithically integrated light source arrays, for example, for 100G bit Ethernet.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2016-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Coherent anti-stokes Raman spectroscopy ( CARS ) can be used to detect differences in the oxygen content...oxygen, eye, retina, photoreceptor, neuron, TRPM7, neurodegeneration, neurotoxicity, coherent anti-Stokes Raman spectroscopy, CARS , mouse 16...ANSI Std. Z39.18 Section 1: Introduction The study is based on the premise that Coherent Anti-Stokes Raman scattering ( CARS ) imaging provides a

Two Novel Methods and Multi-Mode Periodic Solutions for the Fermi-Pasta-Ulam Model

NASA Astrophysics Data System (ADS)

Arioli, Gianni; Koch, Hans; Terracini, Susanna

2005-04-01

We introduce two novel methods for studying periodic solutions of the FPU β-model, both numerically and rigorously. One is a variational approach, based on the dual formulation of the problem, and the other involves computer-assisted proofs. These methods are used e.g. to construct a new type of solutions, whose energy is spread among several modes, associated with closely spaced resonances.

Android Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2014-06-12

such as the way he or she uses the mouse, or interacts with the Graphical User Interface (GUI) [9]. Described simply, standard biometrics is determined...as a login screen on a standard computer. Active authentication is authentication that occurs dynamically throughout interaction with the device. A...because they are higher level constructs in themselves. The Android framework was specifically used for capturing the multitouch gestures: pinch and zoom

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

NASA Astrophysics Data System (ADS)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Noncontact Sleep Study by Multi-Modal Sensor Fusion.

PubMed

Chung, Ku-Young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-07-21

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

Noncontact Sleep Study by Multi-Modal Sensor Fusion

PubMed Central

Chung, Ku-young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-01-01

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner. PMID:28753994

Implementation and flight-test of a multi-mode rotorcraft flight-control system for single-pilot use in poor visibility

NASA Technical Reports Server (NTRS)

Hindson, William S.

1987-01-01

A flight investigation was conducted to evaluate a multi-mode flight control system designed according to the most recent recommendations for handling qualities criteria for new military helicopters. The modes and capabilities that were included in the system are those considered necessary to permit divided-attention (single-pilot) lowspeed and hover operations near the ground in poor visibility conditions. Design features included mode-selection and mode-blending logic, the use of an automatic position-hold mode that employed precision measurements of aircraft position, and a hover display which permitted manually-controlled hover flight tasks in simulated instrument conditions. Pilot evaluations of the system were conducted using a multi-segment evaluation task. Pilot comments concerning the use of the system are provided, and flight-test data are presented to show system performance.

Direct visualization of gastrointestinal tract with lanthanide-doped BaYbF5 upconversion nanoprobes.

PubMed

Liu, Zhen; Ju, Enguo; Liu, Jianhua; Du, Yingda; Li, Zhengqiang; Yuan, Qinghai; Ren, Jinsong; Qu, Xiaogang

2013-10-01

Nanoparticulate contrast agents have attracted a great deal of attention along with the rapid development of modern medicine. Here, a binary contrast agent based on PAA modified BaYbF5:Tm nanoparticles for direct visualization of gastrointestinal (GI) tract has been designed and developed via a one-pot solvothermal route. By taking advantages of excellent colloidal stability, low cytotoxicity, and neglectable hemolysis of these well-designed nanoparticles, their feasibility as a multi-modal contrast agent for GI tract was intensively investigated. Significant enhancement of contrast efficacy relative to clinical barium meal and iodine-based contrast agent was evaluated via X-ray imaging and CT imaging in vivo. By doping Tm(3+) ions into these nanoprobes, in vivo NIR-NIR imaging was then demonstrated. Unlike some invasive imaging modalities, non-invasive imaging strategy including X-ray imaging, CT imaging, and UCL imaging for GI tract could extremely reduce the painlessness to patients, effectively facilitate imaging procedure, as well as rationality economize diagnostic time. Critical to clinical applications, long-term toxicity of our contrast agent was additionally investigated in detail, indicating their overall safety. Based on our results, PAA-BaYbF5:Tm nanoparticles were the excellent multi-modal contrast agent to integrate X-ray imaging, CT imaging, and UCL imaging for direct visualization of GI tract with low systemic toxicity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-modal intelligent seizure acquisition (MISA) system--a new approach towards seizure detection based on full body motion measures.

PubMed

Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Terney, Daniella; Sams, Thomas; Sorensen, Helge B D

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG) and audio and video recording. The results showed that a non-subject specific MISA system developed on data from the modalities: accelerometer (ACM), gyroscope and EMG is able to detect 98% of the simulated seizures and at the same time mistakes only 4 of the normal movements for seizures. If the system is individualized (subject specific) it is able to detect all simulated seizures with a maximum of 1 false positive. Based on the results from the simulated seizures and normal movements the MISA system seems to be a promising approach to seizure detection.

Facile preparation of multifunctional uniform magnetic microspheres for T1-T2 dual modal magnetic resonance and optical imaging.

PubMed

Zhang, Li; Liang, Shuang; Liu, Ruiqing; Yuan, Tianmeng; Zhang, Shulai; Xu, Zushun; Xu, Haibo

2016-08-01

Molecular imaging is of significant importance for early detection and diagnosis of cancer. Herein, a novel core-shell magnetic microsphere for dual modal magnetic resonance imaging (MRI) and optical imaging was produced by one-pot emulsifier-free emulsion polymerization, which could provide high resolution rate of histologic structure information and realize high sensitive detection at the same time. The synthesized magnetic microspheres composed of cores containing oleic acid (OA) and sodium undecylenate (NaUA) modified Fe3O4 nanoparticles and styrene (St), Glycidyl methacrylate (GMA), and polymerizable lanthanide complexes (Gd(AA)3Phen and Eu(AA)3Phen) polymerized on the surface for outer shells. Fluorescence spectra show characteristic emission peaks from Eu(3+) at 590nm and 615nm and vivid red fluorescence luminescence can be observed by 2-photon confocal scanning laser microscopy (CLSM). In vitro cytotoxicity tests based on the MTT assay demonstrate good cytocompatibility, the composites have longitudinal relaxivity value (r1) of 8.39mM(-1)s(-1) and also have transverse relaxivity value (r2) of 71.18mM(-1)s(-1) at clinical 3.0 T MR scanner. In vitro and in vivo MRI studies exhibit high signal enhancement on both T1- and T2-weighted MR images. These fascinating multifunctional properties suggest that the polymer microspheres have large clinical potential as multi-modal MRI/optical probes. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

Side-detecting optical fiber coated with Zn(OH)2 nanorods for ultraviolet sensing applications

NASA Astrophysics Data System (ADS)

Azad, S.; Parvizi, R.; Sadeghi, E.

2017-09-01

This paper presents an improved coupling efficiency and side detecting of UV radiation induced by light scattering and luminescent features of Zn(OH)2 nanorods coated multimode optical fibers. Uniform and high density Zn(OH)2 nanorods were grown hydrothermally on the core of chemically etched multimode optical fibers. The prepared samples were characterized through x-ray diffraction patterns, scanning electron microscopy and photoluminescence spectroscopy. The detecting technique was based on the intensity modulation of the side coupled light through the Zn(OH)2 nanorods. A simple and cost-effective UV radiation detecting setup has been designed. Experimentally estimated coupling efficiency of the proposed setup was obtained near 11%. The proposed device exhibited stable and reversible responses with a fast rising and decaying time of about 1.4 s and 0.85 s, respectively.

Helical Fiber Amplifier

DOEpatents

Koplow, Jeffrey P.; Kliner, Dahy; Goldberg, Lew

2002-12-17

A multi-mode gain fiber is provided which affords substantial improvements in the maximum pulse energy, peak power handling capabilities, average output power, and/or pumping efficiency of fiber amplifier and laser sources while maintaining good beam quality (comparable to that of a conventional single-mode fiber source). These benefits are realized by coiling the multimode gain fiber to induce significant bend loss for all but the lowest-order mode(s).

A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

PubMed

Lu, Pei; Xia, Jun; Li, Zhicheng; Xiong, Jing; Yang, Jian; Zhou, Shoujun; Wang, Lei; Chen, Mingyang; Wang, Cheng

2016-11-08

Accurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images. To overcome these limitations, a flexible segmentation method with a fixed mixture model has been proposed for various angiography modalities. Our method mainly consists of three parts. Firstly, multi-scale filtering algorithm was used on the original images to enhance vessels and suppress noises. As a result, the filtered data achieved a new statistical characteristic. Secondly, a mixture model formed by three probabilistic distributions (two Exponential distributions and one Gaussian distribution) was built to fit the histogram curve of the filtered data, where the expectation maximization (EM) algorithm was used for parameters estimation. Finally, three-dimensional (3D) Markov random field (MRF) were employed to improve the accuracy of pixel-wise classification and posterior probability estimation. To quantitatively evaluate the performance of the proposed method, two phantoms simulating blood vessels with different tubular structures and noises have been devised. Meanwhile, four clinical angiographic data sets from different human organs have been used to qualitatively validate the method. To further test the performance, comparison tests between the proposed method and the traditional ones have been conducted on two different brain magnetic resonance angiography (MRA) data sets. The results of the phantoms were satisfying, e.g., the noise was greatly suppressed, the percentages of the misclassified voxels, i.e., the segmentation error ratios, were no more than 0.3%, and the Dice similarity coefficients (DSCs) were above 94%. According to the opinions of clinical vascular specialists, the vessels in various data sets were extracted with high accuracy since complete vessel trees were extracted while lesser non-vessels and background were falsely classified as vessel. In the comparison experiments, the proposed method showed its superiority in accuracy and robustness for extracting vascular structures from multi-modality angiographic images with complicated background noises. The experimental results demonstrated that our proposed method was available for various angiographic data. The main reason was that the constructed mixture probability model could unitarily classify vessel object from the multi-scale filtered data of various angiography images. The advantages of the proposed method lie in the following aspects: firstly, it can extract the vessels with poor angiography quality, since the multi-scale filtering algorithm can improve the vessel intensity in the circumstance such as uneven contrast media and bias field; secondly, it performed well for extracting the vessels in multi-modality angiographic images despite various signal-noises; and thirdly, it was implemented with better accuracy, and robustness than the traditional methods. Generally, these traits declare that the proposed method would have significant clinical application.

Decision-Level Fusion of Spatially Scattered Multi-Modal Data for Nondestructive Inspection of Surface Defects

PubMed Central

Heideklang, René; Shokouhi, Parisa

2016-01-01

This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique’s robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate. PMID:26784200

Multi-mode phase speed measurements with array-based analysis: Application to the North American continent

NASA Astrophysics Data System (ADS)

Matsuzawa, H.; Yoshizawa, K.

2017-12-01

Recent high-density broad-band seismic networks allow us to construct improved 3-D upper mantle models with unprecedented horizontal resolution using surface waves. Such dispersion measurements have been primarily based on the analysis of fundamental mode. Higher-mode information can be of help in enhancing vertical resolution of 3-D models, but their dispersion analysis is intrinsically difficult, since wave-packets of several modes are overlapped each other in an observed seismogram. In this study, we measure phase dispersion of multi-mode surface waves with an array-based analysis. Our method is modeled on a one-dimensional frequency-wavenumber method originally developed by Nolet (1975, GRL), which can be applied to a set of broadband seismic records observed in a linear array along a great circle path. Through this analysis, we can obtain a spectrogram in c-T (phase speed - period) domain, which is characterized by mode-branch dispersion curves and relative spectral powers for each mode. Synthetic experiments indicate that we can separate the modal contribution using a long linear array with typical array length of about 2000 to 4000 km. The method is applied to a large data set from USArray using nearly 400 seismic events in 2007 - 2014 with Mw 6.5 or greater. Our phase-speed maps for the fundamental-mode Love and Rayleigh waves and the first higher-mode Rayleigh waves match well with the earlier models. The phase speed maps reflect typical large-scale features of regional seismic structure in North America, but smaller-scale variations are less constrained in our model, since our measured phase speeds represent path-average features over a long path (about a few thousands kilometers). Our multi-mode dispersion measurements can also be used for the extraction of mode-branch waveforms for the first a few modes. This can be done by applying a narrow filter around the dispersion curves of a target mode in c-T spectrogram. The mode-branch waveforms can then be reconstructed based on a linear Radon transform (e.g., Luo et al., 2015, GJI). Synthetic experiments suggest that we can successfully retrieve the mode-branch waveforms for several mode branches, which can be used in the secondary analysis for constraining local-scale heterogeneity with enhanced depth resolution.

Theoretical study of mode evolution in active long tapered multimode fiber.

PubMed

Shi, Chen; Wang, Xiaolin; Zhou, Pu; Xu, Xiaojun; Lu, Qisheng

2016-08-22

A concise and effective model based on coupled mode theory to describe mode evolution in long tapered active fiber is presented in this manuscript. The mode coupling due to variation of core radius and slight perturbation have been analyzed and local gain with transverse spatial hole burning (TSHB) effect, loss and curvature have been taken into consideration in our model. On the base of this model, the mode evolution behaviors under different factors have been numerically investigated. Our model and results can provide instructive suggestions when designing long tapered fiber based laser and amplifiers.

Dual-core optical fiber based strain sensor for remote sensing in hard-to-reach areas

NASA Astrophysics Data System (ADS)

MÄ kowska, Anna; Szostkiewicz, Łukasz; Kołakowska, Agnieszka; Budnicki, Dawid; Bieńkowska, Beata; Ostrowski, Łukasz; Murawski, Michał; Napierała, Marek; Mergo, Paweł; Nasiłowski, Tomasz

2017-10-01

We present research on optical fiber sensors based on microstructured multi-core fiber. Elaborated sensor can be advantageously used in hard-to-reach areas by taking advantage of the fact, that optical fibers can play both the role of sensing elements and they can realize signal delivery. By using the sensor, it is possible to increase the level of the safety in the explosive endangered areas, e.g. in mine-like objects. As a base for the strain remote sensor we use dual-core fibers. The multi-core fibers possess a characteristic parameter called crosstalk, which is a measure of the amount of signal which can pass to the adjacent core. The strain-sensitive area is made by creating the tapered section, in which the level of crosstalk is changed. Due to this fact, we present broadened conception of fiber optic sensor designing. Strain measurement is realized thanks to the fact, that depending on the strain applied, the power distribution between the cores of dual-core fibers changes. Principle of operation allows realization of measurements both in wavelength and power domain.

Fiber optic laser-induced breakdown spectroscopy sensor for molten material analysis

DOEpatents

Zhang, Hansheng; Rai, Awadesh K.; Singh, Jagdish P.; Yueh, Fang-Yu

2004-07-13

A fiber optic laser-induced breakdown spectroscopy (LIBS) sensor, including a laser light source, a harmonic separator for directing the laser light, a dichroic mirror for reflecting the laser light, a coupling lens for coupling the laser light at an input of a multimode optical fiber, a connector for coupling the laser light from an output of the multimode optical fiber to an input of a high temperature holder, such as a holder made of stainless steel, and a detector portion for receiving emission signal and analyzing LIBS intensities. In one variation, the multimode optical fiber has silica core and silica cladding. The holder includes optical lenses for collimating and focusing the laser light in a molten alloy to produce a plasma, and for collecting and transmitting an emission signal to the multimode optical fiber.