WorldWideScience

Sample records for event gts-40-3-2 detection

  1. Instant, Visual, and Instrument-Free Method for On-Site Screening of GTS 40-3-2 Soybean Based on Body-Heat Triggered Recombinase Polymerase Amplification.

    Science.gov (United States)

    Wang, Rui; Zhang, Fang; Wang, Liu; Qian, Wenjuan; Qian, Cheng; Wu, Jian; Ying, Yibin

    2017-04-18

    On-site monitoring the plantation of genetically modified (GM) crops is of critical importance in agriculture industry throughout the world. In this paper, a simple, visual and instrument-free method for instant on-site detection of GTS 40-3-2 soybean has been developed. It is based on body-heat recombinase polymerase amplification (RPA) and followed with naked-eye detection via fluorescent DNA dye. Combining with extremely simplified sample preparation, the whole detection process can be accomplished within 10 min and the fluorescent results can be photographed by an accompanied smart phone. Results demonstrated a 100% detection rate for screening of practical GTS 40-3-2 soybean samples by 20 volunteers under different ambient temperatures. This method is not only suitable for on-site detection of GM crops but also demonstrates great potential to be applied in other fields.

  2. Testing the interaction between analytical modules: an example with Roundup Ready® soybean line GTS 40-3-2

    Directory of Open Access Journals (Sweden)

    Bellocchi Gianni

    2010-08-01

    Full Text Available Abstract Background The modular approach to analysis of genetically modified organisms (GMOs relies on the independence of the modules combined (i.e. DNA extraction and GM quantification. The validity of this assumption has to be proved on the basis of specific performance criteria. Results An experiment was conducted using, as a reference, the validated quantitative real-time polymerase chain reaction (PCR module for detection of glyphosate-tolerant Roundup Ready® GM soybean (RRS. Different DNA extraction modules (CTAB, Wizard and Dellaporta, were used to extract DNA from different food/feed matrices (feed, biscuit and certified reference material [CRM 1%] containing the target of the real-time PCR module used for validation. Purity and structural integrity (absence of inhibition were used as basic criteria that a DNA extraction module must satisfy in order to provide suitable template DNA for quantitative real-time (RT PCR-based GMO analysis. When performance criteria were applied (removal of non-compliant DNA extracts, the independence of GMO quantification from the extraction method and matrix was statistically proved, except in the case of Wizard applied to biscuit. A fuzzy logic-based procedure also confirmed the relatively poor performance of the Wizard/biscuit combination. Conclusions For RRS, this study recognises that modularity can be generally accepted, with the limitation of avoiding combining highly processed material (i.e. biscuit with a magnetic-beads system (i.e. Wizard.

  3. Comparison of three DNA extraction methods for the detection and quantification of GMO in Ecuadorian manufactured food.

    Science.gov (United States)

    Pacheco Coello, Ricardo; Pestana Justo, Jorge; Factos Mendoza, Andrés; Santos Ordoñez, Efrén

    2017-12-20

    In Ecuador, food products need to be labeled if exceeded 0.9% of transgenic content in whole products. For the detection of genetically modified organisms (GMOs), three DNA extraction methods were tested in 35 food products commercialized in Ecuador. Samples with positive amplification of endogenous genes were screened for the presence of the Cauliflower mosaic virus 35S-promoter (P35S) and the nopaline synthase-terminator (Tnos). TaqMan™ probes were used for determination of transgenic content of the GTS 40-3-2 and MON810 events through quantitative PCR (qPCR). Twenty-six processed food samples were positive for the P35S alone and eight samples for the Tnos and P35S. Absolute qPCR results indicated that eleven samples were positive for GTS 40-3-2 specific event and two for MON810 specific event. A total of nine samples for events GTS 40-3-2 and MON810 exceeded the umbral allowed of transgenic content in the whole food product with the specific events. Different food products may require different DNA extraction protocols for GMO detection through PCR. Among the three methods tested, the DNeasy mericon food kit DNA extraction method obtained higher proportion of amplified endogenous genes through PCR. Finally, event-specific GMOs were detected in food products in Ecuador.

  4. On-site detection of stacked genetically modified soybean based on event-specific TM-LAMP and a DNAzyme-lateral flow biosensor.

    Science.gov (United States)

    Cheng, Nan; Shang, Ying; Xu, Yuancong; Zhang, Li; Luo, Yunbo; Huang, Kunlun; Xu, Wentao

    2017-05-15

    Stacked genetically modified organisms (GMO) are becoming popular for their enhanced production efficiency and improved functional properties, and on-site detection of stacked GMO is an urgent challenge to be solved. In this study, we developed a cascade system combining event-specific tag-labeled multiplex LAMP with a DNAzyme-lateral flow biosensor for reliable detection of stacked events (DP305423× GTS 40-3-2). Three primer sets, both event-specific and soybean species-specific, were newly designed for the tag-labeled multiplex LAMP system. A trident-like lateral flow biosensor displayed amplified products simultaneously without cross contamination, and DNAzyme enhancement improved the sensitivity effectively. After optimization, the limit of detection was approximately 0.1% (w/w) for stacked GM soybean, which is sensitive enough to detect genetically modified content up to a threshold value established by several countries for regulatory compliance. The entire detection process could be shortened to 120min without any large-scale instrumentation. This method may be useful for the in-field detection of DP305423× GTS 40-3-2 soybean on a single kernel basis and on-site screening tests of stacked GM soybean lines and individual parent GM soybean lines in highly processed foods. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Quantitative detection method for Roundup Ready soybean in food using duplex real-time PCR MGB chemistry.

    Science.gov (United States)

    Samson, Maria Cristina; Gullì, Mariolina; Marmiroli, Nelson

    2010-07-01

    Methodologies that enable the detection of genetically modified organisms (GMOs) (authorized and non-authorized) in food and feed strongly influence the potential for adequate updating and implementation of legislation together with labeling requirements. Quantitative polymerase chain reaction (qPCR) systems were designed to boost the sensitivity and specificity on the identification of GMOs in highly degraded DNA samples; however, such testing will become economically difficult to cope with due to increasing numbers of approved genetically modified (GM) lines. Multiplexing approaches are therefore in development to provide cost-efficient solution. Construct-specific primers and probe were developed for quantitative analysis of Roundup Ready soybean (RRS) event glyphosate-tolerant soybean (GTS) 40-3-2. The lectin gene (Le1) was used as a reference gene, and its specificity was verified. RRS- and Le1-specific quantitative real-time PCR (qRTPCR) were optimized in a duplex platform that has been validated with respect to limit of detection (LOD) and limit of quantification (LOQ), as well as accuracy. The analysis of model processed food samples showed that the degradation of DNA has no adverse or little effects on the performance of quantification assay. In this study, a duplex qRTPCR using TaqMan minor groove binder-non-fluorescent quencher (MGB-NFQ) chemistry was developed for specific detection and quantification of RRS event GTS 40-3-2 that can be used for practical monitoring in processed food products.

  6. Detection of solar events

    Science.gov (United States)

    Fischbach, Ephraim; Jenkins, Jere

    2013-08-27

    A flux detection apparatus can include a radioactive sample having a decay rate capable of changing in response to interaction with a first particle or a field, and a detector associated with the radioactive sample. The detector is responsive to a second particle or radiation formed by decay of the radioactive sample. The rate of decay of the radioactive sample can be correlated to flux of the first particle or the field. Detection of the first particle or the field can provide an early warning for an impending solar event.

  7. State-based Event Detection Optimization for Complex Event Processing

    Directory of Open Access Journals (Sweden)

    Shanglian PENG

    2014-02-01

    Full Text Available Detection of patterns in high speed, large volume of event streams has been an important paradigm in many application areas of Complex Event Processing (CEP including security monitoring, financial markets analysis and health-care monitoring. To assure real-time responsive complex pattern detection over high volume and speed event streams, efficient event detection techniques have to be designed. Unfortunately evaluation of the Nondeterministic Finite Automaton (NFA based event detection model mainly considers single event query and its optimization. In this paper, we propose multiple event queries evaluation on event streams. In particular, we consider scalable multiple event detection model that shares NFA transfer states of different event queries. For each event query, the event query is parse into NFA and states of the NFA are partitioned into different units. With this partition, the same individual state of NFA is run on different processing nodes, providing states sharing and reducing partial matches maintenance. We compare our state-based approach with Stream-based And Shared Event processing (SASE. Our experiments demonstrate that state-based approach outperforms SASE both on CPU time usage and memory consumption.

  8. A simple strategy for fall events detection

    KAUST Repository

    Harrou, Fouzi

    2017-01-20

    The paper concerns the detection of fall events based on human silhouette shape variations. The detection of fall events is addressed from the statistical point of view as an anomaly detection problem. Specifically, the paper investigates the multivariate exponentially weighted moving average (MEWMA) control chart to detect fall events. Towards this end, a set of ratios for five partial occupancy areas of the human body for each frame are collected and used as the input data to MEWMA chart. The MEWMA fall detection scheme has been successfully applied to two publicly available fall detection databases, the UR fall detection dataset (URFD) and the fall detection dataset (FDD). The monitoring strategy developed was able to provide early alert mechanisms in the event of fall situations.

  9. Semantic Context Detection Using Audio Event Fusion

    Directory of Open Access Journals (Sweden)

    Cheng Wen-Huang

    2006-01-01

    Full Text Available Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model and discriminative (support vector machine (SVM approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.

  10. Detection of comfortable temperature based on thermal events detection indoors

    Science.gov (United States)

    Szczurek, Andrzej; Maciejewska, Monika; Uchroński, Mariusz

    2017-11-01

    This work focussed on thermal comfort as the basis to control indoor conditions. Its objective is a method to determine thermal preferences of office occupants. The method is based on detection of thermal events. They occur when indoor conditions are under control of occupants. Thermal events are associated with the use of local heating/cooling sources which have user-adjustable settings. The detection is based on Fourier analysis of indoor temperature time series. The relevant data is collected by temperature sensor. We achieved thermal events recognition rate of 86 %. Conditions when indoor conditions were beyond control were detected with 95.6 % success rate. Using experimental data it was demonstrated that the method allows to reproduce key elements of temperature statistics associated with conditions when occupants are in control of thermal comfort.

  11. Detection of transient events on planetary bodies .

    Science.gov (United States)

    Di Martino, M.; Carbognani, A.

    Transient phenomena on planetary bodies are defined as luminous events of different intensities, which occur in planetary atmospheres and surfaces, their duration spans from about 0.1 s to some hours. They consist of meteors, bolides, lightning, impact flashes on solid surfaces, auroras, etc. So far, the study of these phenomena has been very limited, due to the lack of an ad hoc instrumentation, and their detection has been performed mainly on a serendipitous basis. Recently, ESA has issued an announcement of opportunity for the development of systems devoted to the detection of transient events in the Earth atmosphere and/or on the dark side of other planetary objects. One of such a detector as been designed and a prototype (\\textit{Smart Panoramic Optical Sensor Head}, SPOSH) has been constructed at Galileo Avionica S.p.A (Florence, Italy). For sake of clarity, in what follows, we classify the transient phenomena in ``Earth phenomena'' and ``Planetary phenomena'', even though some of them originate in a similar physical context.

  12. Fault detection based on microseismic events

    Science.gov (United States)

    Yin, Chen

    2017-09-01

    In unconventional reservoirs, small faults allow the flow of oil and gas as well as act as obstacles to exploration; for, (1) fracturing facilitates fluid migration, (2) reservoir flooding, and (3) triggering of small earthquakes. These small faults are not generally detected because of the low seismic resolution. However, such small faults are very active and release sufficient energy to initiate a large number of microseismic events (MEs) during hydraulic fracturing. In this study, we identified microfractures (MF) from hydraulic fracturing and natural small faults based on microseismicity characteristics, such as the time-space distribution, source mechanism, magnitude, amplitude, and frequency. First, I identified the mechanism of small faults and MF by reservoir stress analysis and calibrated the ME based on the microseismic magnitude. The dynamic characteristics (frequency and amplitude) of MEs triggered by natural faults and MF were analyzed; moreover, the geometry and activity types of natural fault and MF were grouped according to the source mechanism. Finally, the differences among time-space distribution, magnitude, source mechanism, amplitude, and frequency were used to differentiate natural faults and manmade fractures.

  13. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

    OpenAIRE

    Zhangbing Zhou; Riliang Xing; Yucong Duan; Yueqin Zhu; Jianming Xiang

    2015-01-01

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sour...

  14. Detection of bubble nucleation event in superheated drop detector ...

    Indian Academy of Sciences (India)

    The present work demonstrates the detection of bubble nucleation events by using the pressure sensor. The associated circuits for the measurement are described in this article. The detection of events is verified by measuring the events with the acoustic sensor. The measurement was done using drops of various sizes to ...

  15. Non-Linguistic Vocal Event Detection Using Online Random

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

    2014-01-01

    Accurate detection of non-linguistic vocal events in social signals can have a great impact on the applicability of speech enabled interactive systems. In this paper, we investigate the use of random forest for vocal event detection. Random forest technique has been successfully employed in many...... areas such as object detection, face recognition, and audio event detection. This paper proposes to use online random forest technique for detecting laughter and filler and for analyzing the importance of various features for non-linguistic vocal event classification through permutation. The results...

  16. Detection and identification of transgenic elements by fluorescent-PCR-based capillary gel electrophoresis in genetically modified cotton and soybean.

    Science.gov (United States)

    Basak, Sanjay; Ehtesham, Nasreen Z; Sesikeran, Boindala; Ghosh, Sudip

    2014-01-01

    A detection method for genetically modified foods is an essential regulatory requirement for many countries. The present study is aimed at developing a qualitative method for detection of genetically modified organisms by combining PCR methodology with capillary gel electrophoresis (PCR-CGE) in a sequencing platform to detect Bacillus thuringiensis (Bt)-cotton (MON 531) and Roundup Ready (RR) soybean (GTS 40-3-2). A sensitive duplex PCR-CGE method was developed in which target DNA sequences (35S and Nos) were separated both by size and color to detect 0.01% Cry1Ac DNA (w/w) in Bt-cotton. A multiplex PCR-CGE method was developed to simultaneously detect four targets such as Sad1, Cry1Ac, 35S, and Nos in Bt-cotton. Four novel PCR primers were designed to customize amplicon size for multiplexing for better visualization of multiple peaks. The LOD for CrylAc DNA specific PCR was 0.01% for Bt-cotton. The LOD for multiplex PCR assay was 0.05% for Bt-cotton. A singleplex PCR-CGE method was developed to detect Lec, 35S and Nos in a trace sample of RR soybean grain powder (0.1%, w/w). This study demonstrates a PCR-CGE-based method for the qualitative detection of 35S, Nos and Cry1Ac targets associated with genetically modified products.

  17. Modeling Concept Dependencies for Event Detection

    Science.gov (United States)

    2014-04-04

    late fusion– as a competi- tor to early and late fusion. Althoff et al. [1], Izidinia and Shah [7], and Habibian et al. [5] focus on event recognition...and Harpreet Sawhney- for providing us the rank lists for DTF-HOG, DTF-MBH, and STIP. 8. REFERENCES [1] T. Althoff , H. O. Song, and T. Darrell

  18. Detection of hypoglycemic events through wearable sensors

    OpenAIRE

    Ranvier, Jean-Eudes; Dubosson, Fabien; Calbimonte, Jean-Paul; Aberer, Karl

    2016-01-01

    Diabetic patients are dependent on external substances to balance their blood glucose level. In order to control this level, they historically needed to sample a drop a blood from their hand and have it analyzed. Recently, other directions emerged to offer alternative ways to estimate glucose level. In this paper, we present our ongoing work on a framework for inferring semantically annotated glycemic events on the patient, which leverages mobile wearable sensors on a sport-belt.

  19. Detecting surface events at the COBRA experiment

    Energy Technology Data Exchange (ETDEWEB)

    Tebruegge, Jan [Exp. Physik IV, TU Dortmund (Germany); Collaboration: COBRA-Collaboration

    2015-07-01

    The aim of the COBRA experiment is to prove the existence of neutrinoless double-beta-decay and to measure its half-life. For this purpose the COBRA demonstrator, a prototype for a large-scale experiment, is operated at the Gran Sasso Underground Laboratory (LNGS) in Italy. The demonstrator is a detector array made of 64 Cadmium-Zinc-Telluride (CdZnTe) semiconductor detectors in the coplanar grid anode configuration. Each detector is 1**1 ccm in size. This setup is used to investigate the experimental issues of operating CdZnTe detectors in low background mode and identify potential background components. As the ''detector=source'' principle is used, the neutrinoless double beta decay COBRA searches for happens within the whole detector volume. Consequently, events on the surface of the detectors are considered as background. These surface events are a main background component, stemming mainly from the natural radioactivity, especially radon. This talk explains to what extent surface events occur and shows how these are recognized and vetoed in the analysis using pulse shape discrimination algorithms.

  20. Abnormal Event Detection Using Local Sparse Representation

    DEFF Research Database (Denmark)

    Ren, Huamin; Moeslund, Thomas B.

    2014-01-01

    measurement based on the difference between the normal space and local space. Specifically, we provide a reasonable normal bases through repeated K spectral clustering. Then for each testing feature we first use temporal neighbors to form a local space. An abnormal event is found if any abnormal feature...... is found that satisfies: the distance between its local space and the normal space is large. We evaluate our method on two public benchmark datasets: UCSD and Subway Entrance datasets. The comparison to the state-of-the-art methods validate our method's effectiveness....

  1. Subsurface Event Detection and Classification Using Wireless Signal Networks

    Directory of Open Access Journals (Sweden)

    Muhannad T. Suleiman

    2012-11-01

    Full Text Available Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs. The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  2. Learning Multimodal Deep Representations for Crowd Anomaly Event Detection

    Directory of Open Access Journals (Sweden)

    Shaonian Huang

    2018-01-01

    Full Text Available Anomaly event detection in crowd scenes is extremely important; however, the majority of existing studies merely use hand-crafted features to detect anomalies. In this study, a novel unsupervised deep learning framework is proposed to detect anomaly events in crowded scenes. Specifically, low-level visual features, energy features, and motion map features are simultaneously extracted based on spatiotemporal energy measurements. Three convolutional restricted Boltzmann machines are trained to model the mid-level feature representation of normal patterns. Then a multimodal fusion scheme is utilized to learn the deep representation of crowd patterns. Based on the learned deep representation, a one-class support vector machine model is used to detect anomaly events. The proposed method is evaluated using two available public datasets and compared with state-of-the-art methods. The experimental results show its competitive performance for anomaly event detection in video surveillance.

  3. Encoding Concept Prototypes for Video Event Detection and Summarization

    NARCIS (Netherlands)

    Mazloom, M.; Habibian, A.; Liu, D.; Snoek, C.G.M.; Chang, S.F.

    2015-01-01

    This paper proposes a new semantic video representation for few and zero example event detection and unsupervised video event summarization. Different from existing works, which obtain a semantic representation by training concepts over images or entire video clips, we propose an algorithm that

  4. Improved quantification accuracy for duplex real-time PCR detection of genetically modified soybean and maize in heat processed foods

    Directory of Open Access Journals (Sweden)

    CHENG Fang

    2013-04-01

    Full Text Available Real-time PCR technique has been widely used in quantitative GMO detection in recent years.The accuracy of GMOs quantification based on the real-time PCR methods is still a difficult problem,especially for the quantification of high processed samples.To develop the suitable and accurate real-time PCR system for high processed GM samples,we made ameliorations to several real-time PCR parameters,including re-designed shorter target DNA fragment,similar lengths of amplified endogenous and exogenous gene targets,similar GC contents and melting temperatures of PCR primers and TaqMan probes.Also,one Heat-Treatment Processing Model (HTPM was established using soybean flour samples containing GM soybean GTS 40-3-2 to validate the effectiveness of the improved real-time PCR system.Tested results showed that the quantitative bias of GM content in heat processed samples were lowered using the new PCR system.The improved duplex real-time PCR was further validated using processed foods derived from GM soybean,and more accurate GM content values in these foods was also achieved.These results demonstrated that the improved duplex real-time PCR would be quite suitable in quantitative detection of high processed food products.

  5. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhangbing Zhou

    2015-12-01

    Full Text Available With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s. When sensory data are collected at sink node(s, the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.

  6. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks.

    Science.gov (United States)

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-12-15

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.

  7. Integrating pedestrian simulation, tracking and event detection for crowd analysis

    OpenAIRE

    Butenuth, Matthias; Burkert, Florian; Kneidl, Angelika; Borrmann, Andre; Schmidt, Florian; Hinz, Stefan; Sirmacek, Beril; Hartmann, Dirk

    2011-01-01

    In this paper, an overall framework for crowd analysis is presented. Detection and tracking of pedestrians as well as detection of dense crowds is performed on image sequences to improve simulation models of pedestrian flows. Additionally, graph-based event detection is performed by using Hidden Markov Models on pedestrian trajectories utilizing knowledge from simulations. Experimental results show the benefit of our integrated framework using simulation and real-world data for crowd anal...

  8. Detection capability of the Italian network for teleseismic events

    Directory of Open Access Journals (Sweden)

    A. Marchetti

    1994-06-01

    Full Text Available The future GSE experiment is based on a global seismic monitoring system, that should be designed for monitoring compliance with a nuclear test ban treaty. Every country participating in the test will transmit data to the International Data Center. Because of the high quality of data required, we decided to conduct this study in order to determine the set of stations to be used in the experiment. The Italian telemetered seismological network can detect all events of at least magnitude 2.5 whose epicenters are inside the network itself. For external events the situation is different: the capabilíty of detection is conditioned not only by the noise condition of the station, but also by the relative position of epicenter and station. The ING bulletin (January 1991-June 1992 was the data set for the present work. Comparing these data with the National Earthquake Information Center (NEIC bulletin, we established which stations are most reliable in detecting teleseismic events and, moreover, how distance and back-azimuth can influence event detection. Furthermore, we investigated the reliability of the automatic acquisition system in relation to teleseismic event detection.

  9. Artificial intelligence based event detection in wireless sensor networks

    OpenAIRE

    Bahrepour, M.

    2013-01-01

    Wireless sensor networks (WSNs) are composed of large number of small, inexpensive devices, called sensor nodes, which are equipped with sensing, processing, and communication capabilities. While traditional applications of wireless sensor networks focused on periodic monitoring, the focus of more recent applications is on fast and reliable identification of out-of-ordinary situations and events. This new functionality of wireless sensor networks is known as event detection. Due to the fact t...

  10. Bi-Level Semantic Representation Analysis for Multimedia Event Detection.

    Science.gov (United States)

    Chang, Xiaojun; Ma, Zhigang; Yang, Yi; Zeng, Zhiqiang; Hauptmann, Alexander G

    2017-05-01

    Multimedia event detection has been one of the major endeavors in video event analysis. A variety of approaches have been proposed recently to tackle this problem. Among others, using semantic representation has been accredited for its promising performance and desirable ability for human-understandable reasoning. To generate semantic representation, we usually utilize several external image/video archives and apply the concept detectors trained on them to the event videos. Due to the intrinsic difference of these archives, the resulted representation is presumable to have different predicting capabilities for a certain event. Notwithstanding, not much work is available for assessing the efficacy of semantic representation from the source-level. On the other hand, it is plausible to perceive that some concepts are noisy for detecting a specific event. Motivated by these two shortcomings, we propose a bi-level semantic representation analyzing method. Regarding source-level, our method learns weights of semantic representation attained from different multimedia archives. Meanwhile, it restrains the negative influence of noisy or irrelevant concepts in the overall concept-level. In addition, we particularly focus on efficient multimedia event detection with few positive examples, which is highly appreciated in the real-world scenario. We perform extensive experiments on the challenging TRECVID MED 2013 and 2014 datasets with encouraging results that validate the efficacy of our proposed approach.

  11. Method for early detection of cooling-loss events

    Science.gov (United States)

    Bermudez, Sergio A.; Hamann, Hendrik; Marianno, Fernando J.

    2015-06-30

    A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

  12. Human Rights Event Detection from Heterogeneous Social Media Graphs.

    Science.gov (United States)

    Chen, Feng; Neill, Daniel B

    2015-03-01

    Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions.

  13. Context-aware event detection smartphone application for first responders

    Science.gov (United States)

    Boddhu, Sanjay K.; Dave, Rakesh P.; McCartney, Matt; West, James A.; Williams, Robert L.

    2013-05-01

    The rise of social networking platforms like Twitter, Facebook, etc…, have provided seamless sharing of information (as chat, video and other media) among its user community on a global scale. Further, the proliferation of the smartphones and their connectivity networks has powered the ordinary individuals to share and acquire information regarding the events happening in his/her immediate vicinity in a real-time fashion. This human-centric sensed data being generated in "human-as-sensor" approach is tremendously valuable as it delivered mostly with apt annotations and ground truth that would be missing in traditional machine-centric sensors, besides high redundancy factor (same data thru multiple users). Further, when appropriately employed this real-time data can support in detecting localized events like fire, accidents, shooting, etc…, as they unfold and pin-point individuals being affected by those events. This spatiotemporal information, when made available for first responders in the event vicinity (or approaching it) can greatly assist them to make effective decisions to protect property and life in a timely fashion. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications, that can provide a augmented reality view of the appropriate detected events in a given geographical location (localized) and also provide an event search capability over a large geographic extent. In its current state, the application thru its backend connectivity utilizes a data (Text & Image) processing framework, which deals with data challenges like; identifying and aggregating important events, analyzing and correlating the events temporally and spatially and building a search enabled event database. Further, the smartphone application with its backend data processing workflow has been successfully field tested with live user generated feeds.

  14. TNO at TRECVID 2013: Multimedia Event Detection and Instance Search

    NARCIS (Netherlands)

    Bouma, H.; Azzopardi, G.; Spitters, M.M.; Wit, J.J. de; Versloot, C.A.; Zon, R.W.L. van der; Eendebak, P.T.; Baan, J.; Hove, R.J.M. ten; Eekeren, A.W.M. van; Haar, F.B. ter; Hollander, R.J.M. den; Huis, R.J. van; Boer, M.H.T. de; Antwerpen, G. van; Broekhuijsen, B.J.; Daniele, L.M.; Brandt, P.; Schavemaker, J.G.M.; Kraaij, W.; Schutte, K.

    2013-01-01

    We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level

  15. Distributed Event Detection in Wireless Sensor Networks for Disaster Management

    NARCIS (Netherlands)

    Bahrepour, M.; Meratnia, Nirvana; Poel, Mannes; Taghikhaki, Zahra; Havinga, Paul J.M.

    2010-01-01

    Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and become one of the enabling technologies for disaster early-warning systems. Event detection functionality of WSNs can be of great help and importance for

  16. On Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Suresh, Mahima Agumbe

    2013-05-01

    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures have been proven costly and imprecise, particularly when dealing with large-scale distribution systems. In this article, to the best of our knowledge, for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. We propose the idea of using sensors that move along the edges of the network and detect events (i.e., attacks). To localize the events, sensors detect proximity to beacons, which are devices with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensors and beacons deployed) in a predetermined zone of interest, while ensuring a degree of coverage by sensors and a required accuracy in locating events using beacons. We propose algorithms for solving the aforementioned problem and demonstrate their effectiveness with results obtained from a realistic flow network simulator.

  17. System events: readily accessible features for surgical phase detection.

    Science.gov (United States)

    Malpani, Anand; Lea, Colin; Chen, Chi Chiung Grace; Hager, Gregory D

    2016-06-01

    Surgical phase recognition using sensor data is challenging due to high variation in patient anatomy and surgeon-specific operating styles. Segmenting surgical procedures into constituent phases is of significant utility for resident training, education, self-review, and context-aware operating room technologies. Phase annotation is a highly labor-intensive task and would benefit greatly from automated solutions. We propose a novel approach using system events-for example, activation of cautery tools-that are easily captured in most surgical procedures. Our method involves extracting event-based features over 90-s intervals and assigning a phase label to each interval. We explore three classification techniques: support vector machines, random forests, and temporal convolution neural networks. Each of these models independently predicts a label for each time interval. We also examine segmental inference using an approach based on the semi-Markov conditional random field, which jointly performs phase segmentation and classification. Our method is evaluated on a data set of 24 robot-assisted hysterectomy procedures. Our framework is able to detect surgical phases with an accuracy of 74 % using event-based features over a set of five different phases-ligation, dissection, colpotomy, cuff closure, and background. Precision and recall values for the cuff closure (Precision: 83 %, Recall: 98 %) and dissection (Precision: 75 %, Recall: 88 %) classes were higher than other classes. The normalized Levenshtein distance between predicted and ground truth phase sequence was 25 %. Our findings demonstrate that system events features are useful for automatically detecting surgical phase. Events contain phase information that cannot be obtained from motion data and that would require advanced computer vision algorithms to extract from a video. Many of these events are not specific to robotic surgery and can easily be recorded in non-robotic surgical modalities. In future

  18. Detecting rare gene transfer events in bacterial populations

    Directory of Open Access Journals (Sweden)

    Kaare Magne Nielsen

    2014-01-01

    Full Text Available Horizontal gene transfer (HGT enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research.

  19. Detection and interpretation of seismoacoustic events at German infrasound stations

    Science.gov (United States)

    Pilger, Christoph; Koch, Karl; Ceranna, Lars

    2016-04-01

    Three infrasound arrays with collocated or nearby installed seismometers are operated by the Federal Institute for Geosciences and Natural Resources (BGR) as the German National Data Center (NDC) for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Infrasound generated by seismoacoustic events is routinely detected at these infrasound arrays, but air-to-ground coupled acoustic waves occasionally show up in seismometer recordings as well. Different natural and artificial sources like meteoroids as well as industrial and mining activity generate infrasonic signatures that are simultaneously detected at microbarometers and seismometers. Furthermore, many near-surface sources like earthquakes and explosions generate both seismic and infrasonic waves that can be detected successively with both technologies. The combined interpretation of seismic and acoustic signatures provides additional information about the origin time and location of remote infrasound events or about the characterization of seismic events distinguishing man-made and natural origins. Furthermore, seismoacoustic studies help to improve the modelling of infrasound propagation and ducting in the atmosphere and allow quantifying the portion of energy coupled into ground and into air by seismoacoustic sources. An overview of different seismoacoustic sources and their detection by German infrasound stations as well as some conclusions on the benefit of a combined seismoacoustic analysis are presented within this study.

  20. Gait event detection during stair walking using a rate gyroscope.

    Science.gov (United States)

    Formento, Paola Catalfamo; Acevedo, Ruben; Ghoussayni, Salim; Ewins, David

    2014-03-19

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. These applications often require detection of the initial contact (IC) of the foot with the floor and/or final contact or foot off (FO) from the floor during outdoor walking. Previous investigations have reported the use of a single gyroscope placed on the shank for detection of IC and FO on level ground and incline walking. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects ascending and descending a set of stairs. Performance was compared with a reference pressure measurement system. The absolute mean difference between the gyroscope and the reference was less than 45 ms for IC and better than 135 ms for FO for both activities. Detection success was over 93%. These results provide preliminary evidence supporting the use of a gyroscope for gait event detection when walking up and down stairs.

  1. PMU Data Event Detection: A User Guide for Power Engineers

    Energy Technology Data Exchange (ETDEWEB)

    Allen, A.; Singh, M.; Muljadi, E.; Santoso, S.

    2014-10-01

    This user guide is intended to accompany a software package containing a Matrix Laboratory (MATLAB) script and related functions for processing phasor measurement unit (PMU) data. This package and guide have been developed by the National Renewable Energy Laboratory and the University of Texas at Austin. The objective of this data processing exercise is to discover events in the vast quantities of data collected by PMUs. This document attempts to cover some of the theory behind processing the data to isolate events as well as the functioning of the MATLAB scripts. The report describes (1) the algorithms and mathematical background that the accompanying MATLAB codes use to detect events in PMU data and (2) the inputs required from the user and the outputs generated by the scripts.

  2. Sound Event Detection for Music Signals Using Gaussian Processes

    Directory of Open Access Journals (Sweden)

    Pablo A. Alvarado-Durán

    2013-11-01

    Full Text Available In this paper we present a new methodology for detecting sound events in music signals using Gaussian Processes. Our method firstly takes a time-frequency representation, i.e. the spectrogram, of the input audio signal. Secondly the spectrogram dimension is reduced translating the linear Hertz frequency scale into the logarithmic Mel frequency scale using a triangular filter bank. Finally every short-time spectrum, i.e. every Mel spectrogram column, is classified as “Event” or “Not Event” by a Gaussian Processes Classifier. We compare our method with other event detection techniques widely used. To do so, we use MATLAB® to program each technique and test them using two datasets of music with different levels of complexity. Results show that the new methodology outperforms the standard approaches, getting an improvement by about 1.66 % on the dataset one and 0.45 % on the dataset two in terms of F-measure.

  3. Detecting modification of biomedical events using a deep parsing approach.

    Science.gov (United States)

    Mackinlay, Andrew; Martinez, David; Baldwin, Timothy

    2012-04-30

    This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. analysis of IkappaBalpha phosphorylation, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. inhibition of IkappaBalpha phosphorylation, where phosphorylation did not occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser. To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the RASP parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm. Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features. Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.

  4. Detecting modification of biomedical events using a deep parsing approach

    Directory of Open Access Journals (Sweden)

    MacKinlay Andrew

    2012-04-01

    Full Text Available Abstract Background This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. analysis of IkappaBalpha phosphorylation, where it is not specified whether phosphorylation did or did not occur or negated (e.g. inhibition of IkappaBalpha phosphorylation, where phosphorylation did not occur. The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser. Method To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the RASP parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm. Results Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features. Conclusions Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.

  5. Malware in the Future? Forecasting Analyst Detection of Cyber Events

    OpenAIRE

    Bakdash, Jonathan Z.; Hutchinson, Steve; Zaroukian, Erin G.; Marusich, Laura R.; Thirumuruganathan, Saravanan; Sample, Charmaine; Hoffman, Blaine; Das, Gautam

    2017-01-01

    Cyber attacks endanger physical, economic, social, and political security. We use a Bayesian state space model to forecast the number of future cyber attacks. Cyber attacks were defined as malware detected by cyber analysts over seven years using cyber events (i.e., reports of malware attacks supported by evidence) at a large Computer Security Service Provider (CSSP). This CSSP protects a variety of computers and networks, which are critical infrastructure, for the U.S. Department of Defense ...

  6. Microseismic Events Detection on Xishancun Landslide, Sichuan Province, China

    Science.gov (United States)

    Sheng, M.; Chu, R.; Wei, Z.

    2016-12-01

    On landslide, the slope movement and the fracturing of the rock mass often lead to microearthquakes, which are recorded as weak signals on seismographs. The distribution characteristics of temporal and spatial regional unstability as well as the impact of external factors on the unstable regions can be understand and analyzed by monitoring those microseismic events. Microseismic method can provide some information inside the landslide, which can be used as supplementary of geodetic methods for monitoring the movement of landslide surface. Compared to drilling on landslide, microseismic method is more economical and safe. Xishancun Landslide is located about 60km northwest of Wenchuan earthquake centroid, it keep deforming after the earthquake, which greatly increases the probability of disasters. In the autumn of 2015, 30 seismometers were deployed on the landslide for 3 months with intervals of 200 500 meters. First, we used regional earthquakes for time correction of seismometers to eliminate the influence of inaccuracy GPS clocks and the subsurface structure of stations. Due to low velocity of the loose medium, the travel time difference of microseismic events on the landslide up to 5s. According to travel time and waveform characteristics, we found many microseismic events and converted them into envelopes as templates, then we used a sliding-window cross-correlation technique based on waveform envelope to detect the other microseismic events. Consequently, 100 microseismic events were detected with the waveforms recorded on all seismometers. Based on the location, we found most of them located on the front of the landslide while the others located on the back end. The bottom and top of the landslide accumulated considerable energy and deformed largely, radiated waves could be recorded by all stations. What's more, the bottom with more events seemed very active. In addition, there were many smaller events happened in middle part of the landslide where released

  7. Towards Optimal Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Agumbe Suresh, Mahima

    2012-01-03

    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil & gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures, have been proven costly and imprecise, especially when dealing with large scale distribution systems. In this paper, to the best of our knowledge for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. Sensor nodes move along the edges of the network and detect events (i.e., attacks) and proximity to beacon nodes with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate their effectiveness with results obtained from a high fidelity simulator.

  8. Statistical language analysis for automatic exfiltration event detection.

    Energy Technology Data Exchange (ETDEWEB)

    Robinson, David Gerald

    2010-04-01

    This paper discusses the recent development a statistical approach for the automatic identification of anomalous network activity that is characteristic of exfiltration events. This approach is based on the language processing method eferred to as latent dirichlet allocation (LDA). Cyber security experts currently depend heavily on a rule-based framework for initial detection of suspect network events. The application of the rule set typically results in an extensive list of uspect network events that are then further explored manually for suspicious activity. The ability to identify anomalous network events is heavily dependent on the experience of the security personnel wading through the network log. Limitations f this approach are clear: rule-based systems only apply to exfiltration behavior that has previously been observed, and experienced cyber security personnel are rare commodities. Since the new methodology is not a discrete rule-based pproach, it is more difficult for an insider to disguise the exfiltration events. A further benefit is that the methodology provides a risk-based approach that can be implemented in a continuous, dynamic or evolutionary fashion. This permits uspect network activity to be identified early with a quantifiable risk associated with decision making when responding to suspicious activity.

  9. Event Detection Using "Variable Module Graphs" for Home Care Applications

    Directory of Open Access Journals (Sweden)

    Sethi Amit

    2007-01-01

    Full Text Available Technology has reached new heights making sound and video capture devices ubiquitous and affordable. We propose a paradigm to exploit this technology for home care applications especially for surveillance and complex event detection. Complex vision tasks such as event detection in a surveillance video can be divided into subtasks such as human detection, tracking, recognition, and trajectory analysis. The video can be thought of as being composed of various features. These features can be roughly arranged in a hierarchy from low-level features to high-level features. Low-level features include edges and blobs, and high-level features include objects and events. Loosely, the low-level feature extraction is based on signal/image processing techniques, while the high-level feature extraction is based on machine learning techniques. Traditionally, vision systems extract features in a feed-forward manner on the hierarchy, that is, certain modules extract low-level features and other modules make use of these low-level features to extract high-level features. Along with others in the research community, we have worked on this design approach. In this paper, we elaborate on recently introduced V/M graph. We present our work on using this paradigm for developing applications for home care applications. Primary objective is surveillance of location for subject tracking as well as detecting irregular or anomalous behavior. This is done automatically with minimal human involvement, where the system has been trained to raise an alarm when anomalous behavior is detected.

  10. Detection of Epileptic Seizure Event and Onset Using EEG

    Science.gov (United States)

    Ahammad, Nabeel; Fathima, Thasneem; Joseph, Paul

    2014-01-01

    This study proposes a method of automatic detection of epileptic seizure event and onset using wavelet based features and certain statistical features without wavelet decomposition. Normal and epileptic EEG signals were classified using linear classifier. For seizure event detection, Bonn University EEG database has been used. Three types of EEG signals (EEG signal recorded from healthy volunteer with eye open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. Important features such as energy, entropy, standard deviation, maximum, minimum, and mean at different subbands were computed and classification was done using linear classifier. The performance of classifier was determined in terms of specificity, sensitivity, and accuracy. The overall accuracy was 84.2%. In the case of seizure onset detection, the database used is CHB-MIT scalp EEG database. Along with wavelet based features, interquartile range (IQR) and mean absolute deviation (MAD) without wavelet decomposition were extracted. Latency was used to study the performance of seizure onset detection. Classifier gave a sensitivity of 98.5% with an average latency of 1.76 seconds. PMID:24616892

  11. Detection of Epileptic Seizure Event and Onset Using EEG

    Directory of Open Access Journals (Sweden)

    Nabeel Ahammad

    2014-01-01

    Full Text Available This study proposes a method of automatic detection of epileptic seizure event and onset using wavelet based features and certain statistical features without wavelet decomposition. Normal and epileptic EEG signals were classified using linear classifier. For seizure event detection, Bonn University EEG database has been used. Three types of EEG signals (EEG signal recorded from healthy volunteer with eye open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures were classified. Important features such as energy, entropy, standard deviation, maximum, minimum, and mean at different subbands were computed and classification was done using linear classifier. The performance of classifier was determined in terms of specificity, sensitivity, and accuracy. The overall accuracy was 84.2%. In the case of seizure onset detection, the database used is CHB-MIT scalp EEG database. Along with wavelet based features, interquartile range (IQR and mean absolute deviation (MAD without wavelet decomposition were extracted. Latency was used to study the performance of seizure onset detection. Classifier gave a sensitivity of 98.5% with an average latency of 1.76 seconds.

  12. Unsupervised behaviour-specific dictionary learning for abnormal event detection

    DEFF Research Database (Denmark)

    Ren, Huamin; Liu, Weifeng; Olsen, Søren Ingvor

    2015-01-01

    . Despite progress in this area, the relationship of atoms within the dictionary is commonly neglected, thereafter anomalies which are detected based on reconstruction error could brings high false alarm - noise or infrequent normal visual features could be wrongly detected as anomalies, especially when...... the training data is only a small proportion of the surveillance data. Therefore, we propose behavior-specific dictionaries (BSD) through unsupervised learning, pursuing atoms from the same type of behavior to represent one behavior dictionary. To further improve the dictionary by introducing information from...... potential infrequent normal patterns, we refine the dictionary by searching ‘missed atoms’ that have compact coefficients. Experimental results show that our BSD algorithm outperforms state-of-the-art dictionaries in abnormal event detection on the public UCSD dataset. Moreover, BSD has less false alarms...

  13. Machine learning for the automatic detection of anomalous events

    Science.gov (United States)

    Fisher, Wendy D.

    In this dissertation, we describe our research contributions for a novel approach to the application of machine learning for the automatic detection of anomalous events. We work in two different domains to ensure a robust data-driven workflow that could be generalized for monitoring other systems. Specifically, in our first domain, we begin with the identification of internal erosion events in earth dams and levees (EDLs) using geophysical data collected from sensors located on the surface of the levee. As EDLs across the globe reach the end of their design lives, effectively monitoring their structural integrity is of critical importance. The second domain of interest is related to mobile telecommunications, where we investigate a system for automatically detecting non-commercial base station routers (BSRs) operating in protected frequency space. The presence of non-commercial BSRs can disrupt the connectivity of end users, cause service issues for the commercial providers, and introduce significant security concerns. We provide our motivation, experimentation, and results from investigating a generalized novel data-driven workflow using several machine learning techniques. In Chapter 2, we present results from our performance study that uses popular unsupervised clustering algorithms to gain insights to our real-world problems, and evaluate our results using internal and external validation techniques. Using EDL passive seismic data from an experimental laboratory earth embankment, results consistently show a clear separation of events from non-events in four of the five clustering algorithms applied. Chapter 3 uses a multivariate Gaussian machine learning model to identify anomalies in our experimental data sets. For the EDL work, we used experimental data from two different laboratory earth embankments. Additionally, we explore five wavelet transform methods for signal denoising. The best performance is achieved with the Haar wavelets. We achieve up to 97

  14. Endmember detection in marine environment with oil spill event

    Science.gov (United States)

    Andreou, Charoula; Karathanassi, Vassilia

    2011-11-01

    Oil spill events are a crucial environmental issue. Detection of oil spills is important for both oil exploration and environmental protection. In this paper, investigation of hyperspectral remote sensing is performed for the detection of oil spills and the discrimination of different oil types. Spectral signatures of different oil types are very useful, since they may serve as endmembers in unmixing and classification models. Towards this direction, an oil spectral library, resulting from spectral measurements of artificial oil spills as well as of look-alikes in marine environment was compiled. Samples of four different oil types were used; two crude oils, one marine residual fuel oil, and one light petroleum product. Lookalikes comprise sea water, river discharges, shallow water and water with algae. Spectral measurements were acquired with spectro-radiometer GER1500. Moreover, oil and look-alikes spectral signatures have been examined whether they can be served as endmembers. This was accomplished by testifying their linear independence. After that, synthetic hyperspectral images based on the relevant oil spectral library were created. Several simplex-based endmember algorithms such as sequential maximum angle convex cone (SMACC), vertex component analysis (VCA), n-finder algorithm (N-FINDR), and automatic target generation process (ATGP) were applied on the synthetic images in order to evaluate their effectiveness for detecting oil spill events occurred from different oil types. Results showed that different types of oil spills with various thicknesses can be extracted as endmembers.

  15. Measuring target detection performance in paradigms with high event rates.

    Science.gov (United States)

    Bendixen, Alexandra; Andersen, Søren K

    2013-05-01

    Combining behavioral and neurophysiological measurements inevitably implies mutual constraints, such as when the neurophysiological measurement requires fast-paced stimulus presentation and hence the attribution of a behavioral response to a particular preceding stimulus becomes ambiguous. We develop and test a method for validly assessing behavioral detection performance in spite of this ambiguity. We examine four approaches taken in the literature to treat such situations. We analytically derive a new variant of computing the classical parameters of signal detection theory, hit and false alarm rates, adapted to fast-paced paradigms. Each of the previous approaches shows specific shortcomings (susceptibility towards response window choice, biased estimates of behavioral detection performance). Superior performance of our new approach is demonstrated for both simulated and empirical behavioral data. Further evidence is provided by reliable correspondence between behavioral performance and the N2b component as an electrophysiological indicator of target detection. The appropriateness of our approach is substantiated by both theoretical and empirical arguments. We demonstrate an easy-to-implement solution for measuring target detection performance independent of the rate of event presentation. Thus overcoming the measurement bias of previous approaches, our method will help to clarify the behavioral relevance of different measures of cortical activation. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  16. The waveform correlation event detection system global prototype software design

    Energy Technology Data Exchange (ETDEWEB)

    Beiriger, J.I.; Moore, S.G.; Trujillo, J.R.; Young, C.J.

    1997-12-01

    The WCEDS prototype software system was developed to investigate the usefulness of waveform correlation methods for CTBT monitoring. The WCEDS prototype performs global seismic event detection and has been used in numerous experiments. This report documents the software system design, presenting an overview of the system operation, describing the system functions, tracing the information flow through the system, discussing the software structures, and describing the subsystem services and interactions. The effectiveness of the software design in meeting project objectives is considered, as well as opportunities for code refuse and lessons learned from the development process. The report concludes with recommendations for modifications and additions envisioned for regional waveform-correlation-based detector.

  17. Use of sonification in the detection of anomalous events

    Science.gov (United States)

    Ballora, Mark; Cole, Robert J.; Kruesi, Heidi; Greene, Herbert; Monahan, Ganesh; Hall, David L.

    2012-06-01

    In this paper, we describe the construction of a soundtrack that fuses stock market data with information taken from tweets. This soundtrack, or auditory display, presents the numerical and text data in such a way that anomalous events may be readily detected, even by untrained listeners. The soundtrack generation is flexible, allowing an individual listener to create a unique audio mix from the available information sources. Properly constructed, the display exploits the auditory system's sensitivities to periodicities, to dynamic changes, and to patterns. This type of display could be valuable in environments that demand high levels of situational awareness based on multiple sources of incoming information.

  18. Understanding pharmacist decision making for adverse drug event (ADE) detection.

    Science.gov (United States)

    Phansalkar, Shobha; Hoffman, Jennifer M; Hurdle, John F; Patel, Vimla L

    2009-04-01

    Manual chart review is an effective but expensive method for adverse drug event (ADE) detection. Building an expert system capable of mimicking the human expert's decision pathway, to deduce the occurrence of an ADE, can improve efficiency and lower cost. As a first step to build such an expert system, this study explores pharmacist's decision-making processes for ADE detection. Think-aloud procedures were used to elicit verbalizations as pharmacists read through ADE case scenarios. Two types of information were extracted, firstly pharmacists' decision-making strategies regarding ADEs and secondly information regarding pharmacists' unmet information needs for ADE detection. Verbal protocols were recorded and analysed qualitatively to extract ADE information signals. Inter-reviewer agreement for classification of ADE information signals was calculated using Cohen's kappa. We extracted a total of 110 information signals, of which 73% consisted of information that was interpreted by the pharmacists from the case scenario and only about half (53%, n = 32) of the information signals were considered relevant for the detection of the ADEs. Excellent reliability was demonstrated between the reviewers for classifying signals. Fifty information signals regarding unmet information needs were extracted and grouped into themes based on the type of missing information. Pharmacists used a forward reasoning approach to make implicit deductions and validate hypotheses about possible ADEs. Verbal protocols also indicated that pharmacists' unmet information needs occurred frequently. Developing alerting systems that meet pharmacists' needs adequately will enhance their ability to reduce preventable ADEs, thus improving patient safety.

  19. Temporal Characteristics in Detecting Imminent Collision Events on Linear Trajectories

    Directory of Open Access Journals (Sweden)

    Rui Ni

    2011-05-01

    Full Text Available Previous research (Andersen & Kim, 2001 has shown that a linear trajectory collision event is specified by objects that expand and maintain a constant bearing (the object projected location in the visual field. In this research, we investigated the temporal characteristics in detecting such imminent collision events. Two experiments were conducted in which participants were presented with displays simulating a single approaching object in the scene while observers were either stationary or moving at one of the 3 speeds (24, 36, or 48 km/h. An object traveled for 9 seconds before colliding with or passing by the observer and the relative speed between object and observer remained constant. Participants were asked to report whether the object was on a collision path or not. In the first experiment, 3 seconds or 4 seconds of displays were presented that ended at the same 2-second time to contact (TTC position. In the second experiment, 3 seconds of displays were presented that ended at different TTC positions. Results show that observers were more accurate in collision detection in stationary condition than in motion. More importantly, results suggest that observers used information on bearing change rate to distinguish noncollision objects from collision objects.

  20. Detection of adverse drug events using an electronic trigger tool.

    Science.gov (United States)

    Lim, Dennison; Melucci, Joe; Rizer, Milisa K; Prier, Beth E; Weber, Robert J

    2016-09-01

    Implementation and refinement of an integrated electronic "trigger tool" for detecting adverse drug events (ADEs) is described. A three-month prospective study was conducted at a large medical center to test and improve the positive predictive value (PPV) of an electronic health record-based tool for detecting ADEs associated with use of four "trigger drugs": the reversal agents flumazenil, naloxone, phytonadione, and protamine. On administration of a trigger drug to an adult patient, an electronic message was transmitted to two pharmacists, who reviewed cases in near real time (typically, on the same day) to detect actual or potential ADEs. In phase 1 of the study, any use of a trigger drug resulted in an alert message; in subsequent phases, the alerting criteria were narrowed on the basis of clinical criteria and laboratory data with the goal of refining the trigger tool's PPV. A total of 87 drug administrations were reviewed during the three-month study period, with 27 ADEs detected. PPV values in phases 1, 2, and 3 were 0.33, 0.21, and 0.36, respectively. The relatively low overall PPV of the trigger tool was largely attributable to false-positive trigger messages associated with phytonadione use (such messages were reduced from 35 in phase 1 to 7 in phase 3). Evaluation and refinement of an electronic trigger tool based on detecting the use of the reversal agents flumazenil, naloxone, phytonadione, and protamine found an overall PPV of 0.31 during a three-month study period. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

  1. Detecting Rare Events in the Time-Domain

    Energy Technology Data Exchange (ETDEWEB)

    Rest, A; Garg, A

    2008-10-31

    One of the biggest challenges in current and future time-domain surveys is to extract the objects of interest from the immense data stream. There are two aspects to achieving this goal: detecting variable sources and classifying them. Difference imaging provides an elegant technique for identifying new transients or changes in source brightness. Much progress has been made in recent years toward refining the process. We discuss a selection of pitfalls that can afflict an automated difference imagine pipeline and describe some solutions. After identifying true astrophysical variables, we are faced with the challenge of classifying them. For rare events, such as supernovae and microlensing, this challenge is magnified because we must balance having selection criteria that select for the largest number of objects of interest against a high contamination rate. We discuss considerations and techniques for developing classification schemes.

  2. Barometric pressure and triaxial accelerometry-based falls event detection.

    Science.gov (United States)

    Bianchi, Federico; Redmond, Stephen J; Narayanan, Michael R; Cerutti, Sergio; Lovell, Nigel H

    2010-12-01

    Falls and fall related injuries are a significant cause of morbidity, disability, and health care utilization, particularly among the age group of 65 years and over. The ability to detect falls events in an unsupervised manner would lead to improved prognoses for falls victims. Several wearable accelerometry and gyroscope-based falls detection devices have been described in the literature; however, they all suffer from unacceptable false positive rates. This paper investigates the augmentation of such systems with a barometric pressure sensor, as a surrogate measure of altitude, to assist in discriminating real fall events from normal activities of daily living. The acceleration and air pressure data are recorded using a wearable device attached to the subject's waist and analyzed offline. The study incorporates several protocols including simulated falls onto a mattress and simulated activities of daily living, in a cohort of 20 young healthy volunteers (12 male and 8 female; age: 23.7 ±3.0 years). A heuristically trained decision tree classifier is used to label suspected falls. The proposed system demonstrated considerable improvements in comparison to an existing accelerometry-based technique; showing an accuracy, sensitivity and specificity of 96.9%, 97.5%, and 96.5%, respectively, in the indoor environment, with no false positives generated during extended testing during activities of daily living. This is compared to 85.3%, 75%, and 91.5% for the same measures, respectively, when using accelerometry alone. The increased specificity of this system may enhance the usage of falls detectors among the elderly population.

  3. Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance

    Directory of Open Access Journals (Sweden)

    Benabbas Yassine

    2011-01-01

    Full Text Available Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearance ambiguity, and occlusion. In this work, we propose to deal with this problem by modeling the global motion information obtained from optical flow vectors. The obtained direction and magnitude models learn the dominant motion orientations and magnitudes at each spatial location of the scene and are used to detect the major motion patterns. The applied region-based segmentation algorithm groups local blocks that share the same motion direction and speed and allows a subregion of the scene to appear in different patterns. The second part of the approach consists in the detection of events related to groups of people which are merge, split, walk, run, local dispersion, and evacuation by analyzing the instantaneous optical flow vectors and comparing the learned models. The approach is validated and experimented on standard datasets of the computer vision community. The qualitative and quantitative results are discussed.

  4. Communication of ALS Patients by Detecting Event-Related Potential

    Science.gov (United States)

    Kanou, Naoyuki; Sakuma, Kenji; Nakashima, Kenji

    Amyotrophic Lateral Sclerosis(ALS) patients are unable to successfully communicate their desires, although their mental capacity is the same as non-affected persons. Therefore, the authors put emphasis on Event-Related Potential(ERP) which elicits the highest outcome for the target visual and hearing stimuli. P300 is one component of ERP. It is positive potential that is elicited when the subject focuses attention on stimuli that appears infrequently. In this paper, the authors focused on P200 and N200 components, in addition to P300, for their great improvement in the rate of correct judgment in the target word-specific experiment. Hence the authors propose the algorithm that specifies target words by detecting these three components. Ten healthy subjects and ALS patient underwent the experiment in which a target word out of five words, was specified by this algorithm. The rates of correct judgment in nine of ten healthy subjects were more than 90.0%. The highest rate was 99.7%. The highest rate of ALS patient was 100.0%. Through these results, the authors found the possibility that ALS patients could communicate with surrounding persons by detecting ERP(P200, N200 and P300) as their desire.

  5. Identification of new events in Apollo 16 lunar seismic data by Hidden Markov Model-based event detection and classification

    Science.gov (United States)

    Knapmeyer-Endrun, Brigitte; Hammer, Conny

    2015-10-01

    Detection and identification of interesting events in single-station seismic data with little prior knowledge and under tight time constraints is a typical scenario in planetary seismology. The Apollo lunar seismic data, with the only confirmed events recorded on any extraterrestrial body yet, provide a valuable test case. Here we present the application of a stochastic event detector and classifier to the data of station Apollo 16. Based on a single-waveform example for each event class and some hours of background noise, the system is trained to recognize deep moonquakes, impacts, and shallow moonquakes and performs reliably over 3 years of data. The algorithm's demonstrated ability to detect rare events and flag previously undefined signal classes as new event types is of particular interest in the analysis of the first seismic recordings from a completely new environment. We are able to classify more than 50% of previously unclassified lunar events, and additionally find over 200 new events not listed in the current lunar event catalog. These events include deep moonquakes as well as impacts and could be used to update studies on temporal variations in event rate or deep moonquakes stacks used in phase picking for localization. No unambiguous new shallow moonquake was detected, but application to data of the other Apollo stations has the potential for additional new discoveries 40 years after the data were recorded. Besides, the classification system could be useful for future seismometer missions to other planets, e.g., the InSight mission to Mars.

  6. Balloon-Borne Infrasound Detection of Energetic Bolide Events

    Science.gov (United States)

    Young, Eliot F.; Ballard, Courtney; Klein, Viliam; Bowman, Daniel; Boslough, Mark

    2016-10-01

    Infrasound is usually defined as sound waves below 20 Hz, the nominal limit of human hearing. Infrasound waves propagate over vast distances through the Earth's atmosphere: the CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organization) has 48 installed infrasound-sensing stations around the world to detect nuclear detonations and other disturbances. In February 2013, several CTBTO infrasound stations detected infrasound signals from a large bolide that exploded over Chelyabinsk, Russia. Some stations recorded signals that had circumnavigated the Earth, over a day after the original event. The goal of this project is to improve upon the sensitivity of the CTBTO network by putting microphones on small, long-duration super-pressure balloons, with the overarching goal of studying the small end of the NEO population by using the Earth's atmosphere as a witness plate.A balloon-borne infrasound sensor is expected to have two advantages over ground-based stations: a lack of wind noise and a concentration of infrasound energy in the "stratospheric duct" between roughly 5 - 50 km altitude. To test these advantages, we have built a small balloon payload with five calibrated microphones. We plan to fly this payload on a NASA high-altitude balloon from Ft Sumner, NM in August 2016. We have arranged for three large explosions to take place in Socorro, NM while the balloon is aloft to assess the sensitivity of balloon-borne vs. ground-based infrasound sensors. We will report on the results from this test flight and the prospects for detecting/characterizing small bolides in the stratosphere.

  7. An Effective Method for Small Event Detection: Match and Locate (ML) and Its Applications

    Science.gov (United States)

    Zhang, M.; Wen, L.

    2014-12-01

    Detection of low magnitude event is critical and challenging in seismology. Traditional methods of event detection, which rely on phase identification, are usually hindered by low signal to noise ratio (SNR) in small event recordings. We develop a new method, named the match and locate (ML) method, for small event detection. The ML method employs some template events and detects small events through stacking cross-correlograms between waveforms of the template events and potential small event signals in the continuous waveforms over multiple stations and components. Unlike the traditional match filter method which assumes that the template event and slave event are co-located, the ML method scans over potential small event locations around the template, by making relative travel time corrections based on the relative locations of the template event and the potential small event before stacking. It makes event detection more efficient and at the same time relocates the detected event in high-precision. As an example of application and comparison with the matched filter method, we apply the ML and matched filter methods to detect the foreshocks before the 2011 Mw 9.0 Tohoku earthquake. The ML method detects four times more events than the templates and 10% more than the matched filter under the same detection threshold. Up to 42% of the events detected by the ML method are not co-located at the template locations with the largest event separation of 9.4 km. As another example of application, we apply the ML method to search for potential nuclear tests conducted by North Korea in the continuous seismic data recorded in Northeast China, using North Korea's 2009 and 2013 tests as templates. We report detection of a low-yield nuclear test conducted by North Korea in 2010.

  8. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Directory of Open Access Journals (Sweden)

    Vernon Lawhern

    Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

  9. Application of Polymerase Chain Reaction for High Sensitivity Detection of Roundup Ready™ Soybean Seeds and Grains in Varietal Mixtures

    Directory of Open Access Journals (Sweden)

    Ashok Pandey

    2011-01-01

    Full Text Available Strong increase in the production of genetically modified organisms (GMOs observed over the years has led to a consolidation of transgenic seed industries worldwide. The dichotomy between the evaluated risk and the perceived risk of transgenic use has defined their level of acceptability among different global societies. GMOs have been widely applied to agricultural commodities, among them the Roundup Ready™ (RR™ soybean line GTS 40-3-2 has become the most prevalent transgenic crop in the world. This variety was developed to confer plant tolerance against glyphosate-based agricultural herbicide Roundup Ready™. Issues related to detection and traceability of GMOs have gained worldwide interest due to their increasing global diffusion and the related socioeconomic and health implications. Also, due to the widespread use of GMOs in food production, labelling regulations have been established in some countries to protect the right of consumers and producers. Besides regulatory demand, consumer concern issues have resulted in the development of several methods of detecting and quantifying foods derived from genetically engineered crops and their raw materials. Polymerase chain reaction (PCR has been proven to be the method of choice to detect the presence or absence of the introduced genes of GMOs at DNA level. The present paper aims to verify whether the PCR technique can detect RR™ soybean seeds among conventional ones to further certification as non-GM soybean seeds and grains. This analysis could be accomplished through the development of new methodology called 'intentional contamination' of soybean conventional seeds or grains with the respective RR™ soybeans. The results show that the PCR method can be applied with high sensitivity in order to certify conventional soybean seeds and grains.

  10. Event-based home safety problem detection under the CPS home safety architecture

    OpenAIRE

    Yang, Zhengguo; Lim, Azman Osman; Tan, Yasuo

    2013-01-01

    This paper presents a CPS(Cyber-physical System) home safety architecture for home safety problem detection and reaction and shows some example cases. In order for home safety problem detection, there are three levels of events defined: elementary event, semantic event and entire event, which representing the meaning from parameter to single safety problem, and then the whole safety status of a house. For the relationship between these events and raw data, a Finite State Machine (FSM) based m...

  11. Semantic Concept Discovery for Large Scale Zero Shot Event Detection

    Science.gov (United States)

    2015-07-25

    for the event Rock climbing . From top to below are retrieved videos by selected concepts vocabu- lary, bi-concepts vocabulary, OR-composite concept...significantly improves on some events, such as Birthday party (E006), Flash mob gathering (E008) and Rock climbing (E027). For these events, the de- tection...concepts of the pro- posed method, we find that their classifiers are very discrimi- native and reliable. For instance, for the event Rock climbing we

  12. Automated Detection of Financial Events in News Text

    NARCIS (Netherlands)

    F.P. Hogenboom (Frederik)

    2014-01-01

    markdownabstractToday’s financial markets are inextricably linked with financial events like acquisitions, profit announcements, or product launches. Information extracted from news messages that report on such events could hence be beneficial for financial decision making. The ubiquity of news,

  13. Event Detection Challenges, Methods, and Applications in Natural and Artificial Systems

    Science.gov (United States)

    2009-03-01

    Sauvageon, Agogino, Mehr, and Tumer [2006], for instance, use a fourth degree polynomial within an event detection algorithm to sense high...AM, Mehr AF, and Tumer IY. 2006. “Comparison of Event Detection Methods for Centralized Sensor Networks.” IEEE Sensors Applications Symposium 2006...div898/handbook/index.htm>. • Sauvageon J, Agogino AM, Mehr AF, and Tumer IY. 2006. “Comparison of Event Detection Methods for Centralized Sensor

  14. Setting objective thresholds for rare event detection in flow cytometry

    OpenAIRE

    Richards, Adam J.; Staats, Janet; Enzor, Jennifer; McKinnon, Katherine; Frelinger, Jacob; Denny, Thomas N.; Weinhold, Kent J.; Chan, Cliburn

    2014-01-01

    The accurate identification of rare antigen-specific cytokine positive cells from peripheral blood mononuclear cells (PBMC) after antigenic stimulation in an intracellular staining (ICS) flow cytometry assay is challenging, as cytokine positive events may be fairly diffusely distributed and lack an obvious separation from the negative population. Traditionally, the approach by flow operators has been to manually set a positivity threshold to partition events into cytokine-positive and cytokin...

  15. Energy-Efficient Fault-Tolerant Dynamic Event Region Detection in Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Enemark, Hans-Jacob; Zhang, Yue; Dragoni, Nicola

    2015-01-01

    Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy, while need more energy consumption due to communication. Focusing on energy efficiency, this paper makes an improvement...

  16. Signal detection to identify serious adverse events (neuropsychiatric events in travelers taking mefloquine for chemoprophylaxis of malaria

    Directory of Open Access Journals (Sweden)

    Naing C

    2012-08-01

    Full Text Available Cho Naing,1,3 Kyan Aung,1 Syed Imran Ahmed,2 Joon Wah Mak31School of Medical Sciences, 2School of Pharmacy and Health Sciences, 3School of Postgraduate Studies and Research, International Medical University, Kuala Lumpur, MalaysiaBackground: For all medications, there is a trade-off between benefits and potential for harm. It is important for patient safety to detect drug-event combinations and analyze by appropriate statistical methods. Mefloquine is used as chemoprophylaxis for travelers going to regions with known chloroquine-resistant Plasmodium falciparum malaria. As such, there is a concern about serious adverse events associated with mefloquine chemoprophylaxis. The objective of the present study was to assess whether any signal would be detected for the serious adverse events of mefloquine, based on data in clinicoepidemiological studies.Materials and methods: We extracted data on adverse events related to mefloquine chemoprophylaxis from the two published datasets. Disproportionality reporting of adverse events such as neuropsychiatric events and other adverse events was presented in the 2 × 2 contingency table. Reporting odds ratio and corresponding 95% confidence interval [CI] data-mining algorithm was applied for the signal detection. The safety signals are considered significant when the ROR estimates and the lower limits of the corresponding 95% CI are ≥2.Results: Two datasets addressing adverse events of mefloquine chemoprophylaxis (one from a published article and one from a Cochrane systematic review were included for analyses. Reporting odds ratio 1.58, 95% CI: 1.49–1.68 based on published data in the selected article, and 1.195, 95% CI: 0.94–1.44 based on data in the selected Cochrane review. Overall, in both datasets, the reporting odds ratio values of lower 95% CI were less than 2.Conclusion: Based on available data, findings suggested that signals for serious adverse events pertinent to neuropsychiatric event were

  17. Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

    Science.gov (United States)

    Oliker, Nurit; Ostfeld, Avi

    2015-09-01

    Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. A Study on Double Event Detection for PHENIX at RHIC

    Science.gov (United States)

    Vazquez-Carson, Sebastian; Phenix Collaboration

    2016-09-01

    Many measurements made in Heavy Ion experiments such as PHENIX at RHIC focus on geometrical properties because phenomena such as collective flow give insight into quark-gluon plasma and the strong nuclear force. As part of this investigation, PHENIX has taken data in 2016 for deuteron on gold collisions at several energies. An acceptable luminosity is achieved by injecting up to 120 separate bunches each with billions of ions into the storage ring, from which two, separate beams are made to collide. This method has a drawback as there is a chance for multiple pairs of nuclei to collide in a single bunch crossing. Data taken in a double event cannot be separated into two independent events and has no clear interpretation. This effect's magnitude is estimated and incorporated in published results as a systematic uncertainty and studies on this topic have already been conducted within PHENIX. I develop several additional algorithms to flag multiple interaction events by examining the time dependence of data from the two Beam-Beam Counters - detectors surrounding the beam pipe on opposite ends of the interaction region. The algorithms are tested with data, in which events with double interactions are artificially produced using low luminosity data. I am working at the University of Colorado at Boulder on behalf of the PHENIX collaboration.

  19. Progress in air shower radio measurements : detection of distant events

    NARCIS (Netherlands)

    Bähren, L.; Buitink, S.J.; Falcke, H.D.E.; Horneffer, K.H.A.; Kuijpers, J.M.E.; Lafebre, S.J.; Nigl, A.; Petrovic, J.; Singh, K.

    2006-01-01

    Data taken during half a year of operation of 10 LOPES antennas (LOPES-10), triggered by EAS observed with KASCADE-Grande have been analysed. We report about the analysis of correlations of radio signals measured by LOPES-10 with extensive air shower events reconstructed by KASCADE-Grande, including

  20. Event detection with zero example : Select the right and suppress the wrong concepts

    NARCIS (Netherlands)

    Lu, Y.J.; Zhang, H.; Boer, M.H.T. de; Ngo, C.W.

    2016-01-01

    Complex video event detection without visual examples is a very challenging issue in multimedia retrieval. We present a state-of-the-art framework for event search without any need of exemplar videos and textual metadata in search corpus. To perform event search given only query words, the core of

  1. Event detection using population-based health care databases in randomized clinical trials

    DEFF Research Database (Denmark)

    Thuesen, Leif; Jensen, Lisette Okkels; Tilsted, Hans Henrik

    2013-01-01

    To describe a new research tool, designed to reflect routine clinical practice and relying on population-based health care databases to detect clinical events in randomized clinical trials.......To describe a new research tool, designed to reflect routine clinical practice and relying on population-based health care databases to detect clinical events in randomized clinical trials....

  2. Setting objective thresholds for rare event detection in flow cytometry.

    Science.gov (United States)

    Richards, Adam J; Staats, Janet; Enzor, Jennifer; McKinnon, Katherine; Frelinger, Jacob; Denny, Thomas N; Weinhold, Kent J; Chan, Cliburn

    2014-07-01

    The accurate identification of rare antigen-specific cytokine positive cells from peripheral blood mononuclear cells (PBMC) after antigenic stimulation in an intracellular staining (ICS) flow cytometry assay is challenging, as cytokine positive events may be fairly diffusely distributed and lack an obvious separation from the negative population. Traditionally, the approach by flow operators has been to manually set a positivity threshold to partition events into cytokine-positive and cytokine-negative. This approach suffers from subjectivity and inconsistency across different flow operators. The use of statistical clustering methods does not remove the need to find an objective threshold between between positive and negative events since consistent identification of rare event subsets is highly challenging for automated algorithms, especially when there is distributional overlap between the positive and negative events ("smear"). We present a new approach, based on the Fβ measure, that is similar to manual thresholding in providing a hard cutoff, but has the advantage of being determined objectively. The performance of this algorithm is compared with results obtained by expert visual gating. Several ICS data sets from the External Quality Assurance Program Oversight Laboratory (EQAPOL) proficiency program were used to make the comparisons. We first show that visually determined thresholds are difficult to reproduce and pose a problem when comparing results across operators or laboratories, as well as problems that occur with the use of commonly employed clustering algorithms. In contrast, a single parameterization for the Fβ method performs consistently across different centers, samples, and instruments because it optimizes the precision/recall tradeoff by using both negative and positive controls. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Signal Detection of Imipenem Compared to Other Drugs from Korea Adverse Event Reporting System Database

    OpenAIRE

    Park, Kyounghoon; Soukavong, Mick; Kim, Jungmee; Kwon, Kyoung-Eun; Jin, Xue-Mei; Lee, Joongyub; Yang, Bo Ram; Park, Byung-Joo

    2017-01-01

    Purpose To detect signals of adverse drug events after imipenem treatment using the Korea Institute of Drug Safety & Risk Management-Korea adverse event reporting system database (KIDS-KD). Materials and Methods We performed data mining using KIDS-KD, which was constructed using spontaneously reported adverse event (AE) reports between December 1988 and June 2014. We detected signals calculated the proportional reporting ratio, reporting odds ratio, and information component of imipenem. We d...

  4. Stable hyper-pooling and query expansion for event detection

    OpenAIRE

    Douze, Matthijs; Revaud, Jerome; Schmid, Cordelia; Jegou, Herve

    2013-01-01

    International audience; This paper makes two complementary contributions to event retrieval in large collections of videos. First, we propose hyper-pooling strategies that encode the frame descriptors into a representation of the video sequence in a stable manner. Our best choices compare favorably with regular pooling techniques based on k-means quantization. Second, we introduce a technique to improve the ranking. It can be interpreted either as a query expansion method or as a similarity a...

  5. Biomedical event trigger detection by dependency-based word embedding.

    Science.gov (United States)

    Wang, Jian; Zhang, Jianhai; An, Yuan; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia; Sun, Yuanyuan

    2016-08-10

    In biomedical research, events revealing complex relations between entities play an important role. Biomedical event trigger identification has become a research hotspot since its important role in biomedical event extraction. Traditional machine learning methods, such as support vector machines (SVM) and maxent classifiers, which aim to manually design powerful features fed to the classifiers, depend on the understanding of the specific task and cannot generalize to the new domain or new examples. In this paper, we propose an approach which utilizes neural network model based on dependency-based word embedding to automatically learn significant features from raw input for trigger classification. First, we employ Word2vecf, the modified version of Word2vec, to learn word embedding with rich semantic and functional information based on dependency relation tree. Then neural network architecture is used to learn more significant feature representation based on raw dependency-based word embedding. Meanwhile, we dynamically adjust the embedding while training for adapting to the trigger classification task. Finally, softmax classifier labels the examples by specific trigger class using the features learned by the model. The experimental results show that our approach achieves a micro-averaging F1 score of 78.27 and a macro-averaging F1 score of 76.94 % in significant trigger classes, and performs better than baseline methods. In addition, we can achieve the semantic distributed representation of every trigger word.

  6. Supervised machine learning on a network scale: application to seismic event classification and detection

    Science.gov (United States)

    Reynen, Andrew; Audet, Pascal

    2017-09-01

    A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

  7. Contamination event detection using multiple types of conventional water quality sensors in source water.

    Science.gov (United States)

    Liu, Shuming; Che, Han; Smith, Kate; Chen, Lei

    2014-08-01

    Early warning systems are often used to detect deliberate and accidental contamination events in a water system. Conventional methods normally detect a contamination event by comparing the predicted and observed water quality values from one sensor. This paper proposes a new method for event detection by exploring the correlative relationships between multiple types of conventional water quality sensors. The performance of the proposed method was evaluated using data from contaminant injection experiments in a laboratory. Results from these experiments demonstrated the correlative responses of multiple types of sensors. It was observed that the proposed method could detect a contamination event 9 minutes after the introduction of lead nitrate solution with a concentration of 0.01 mg L(-1). The proposed method employs three parameters. Their impact on the detection performance was also analyzed. The initial analysis showed that the correlative response is contaminant-specific, which implies that it can be utilized not only for contamination detection, but also for contaminant identification.

  8. Falls event detection using triaxial accelerometry and barometric pressure measurement.

    Science.gov (United States)

    Bianchi, Federico; Redmond, Stephen J; Narayanan, Michael R; Cerutti, Sergio; Celler, Branko G; Lovell, Nigel H

    2009-01-01

    A falls detection system, employing a Bluetooth-based wearable device, containing a triaxial accelerometer and a barometric pressure sensor, is described. The aim of this study is to evaluate the use of barometric pressure measurement, as a surrogate measure of altitude, to augment previously reported accelerometry-based falls detection algorithms. The accelerometry and barometric pressure signals obtained from the waist-mounted device are analyzed by a signal processing and classification algorithm to discriminate falls from activities of daily living. This falls detection algorithm has been compared to two existing algorithms which utilize accelerometry signals alone. A set of laboratory-based simulated falls, along with other tasks associated with activities of daily living (16 tests) were performed by 15 healthy volunteers (9 male and 6 female; age: 23.7 +/- 2.9 years; height: 1.74 +/- 0.11 m). The algorithm incorporating pressure information detected falls with the highest sensitivity (97.8%) and the highest specificity (96.7%).

  9. Spatial-temporal event detection in climate parameter imagery.

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, Sean Andrew; Gutierrez, Karen A.

    2011-10-01

    Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

  10. Detection and fine-grained classification of cyberbullying events

    OpenAIRE

    Van Hee, Cynthia; Lefever, Els; Verhoeven, Ben; Mennes, Julie; Desmet, Bart; De Pauw, Guy; Daelemans, Walter; Hoste, Veronique

    2015-01-01

    In the current era of online interactions, both positive and negative experiences are abundant on the Web. As in real life, negative experiences can have a serious impact on youngsters. Recent studies have reported cybervictimization rates among teenagers that vary between 20% and 40%. In this paper, we focus on cyberbullying as a particular form of cybervictimization and explore its automatic detection and fine-grained classification. Data containing cyberbullying was collected from the soci...

  11. Detecting impacts of extreme events with ecological in situ monitoring networks

    Directory of Open Access Journals (Sweden)

    M. D. Mahecha

    2017-09-01

    Full Text Available Extreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR, identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log–log space. For instance, networks with  ≈  100 randomly placed sites in Europe yield a  ≥  90 % chance of detecting the eight largest (typically very large extreme events; but only a  ≥  50 % chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON reliably detect the largest extremes, but that the extreme event detection rates are not higher than would

  12. Detecting impacts of extreme events with ecological in situ monitoring networks

    Science.gov (United States)

    Mahecha, Miguel D.; Gans, Fabian; Sippel, Sebastian; Donges, Jonathan F.; Kaminski, Thomas; Metzger, Stefan; Migliavacca, Mirco; Papale, Dario; Rammig, Anja; Zscheischler, Jakob

    2017-09-01

    Extreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR), identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log-log space. For instance, networks with ≈ 100 randomly placed sites in Europe yield a ≥ 90 % chance of detecting the eight largest (typically very large) extreme events; but only a ≥ 50 % chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON) reliably detect the largest extremes, but that the extreme event detection rates are not higher than would be achieved by randomly designed networks. Spatio

  13. Full-waveform detection of non-impulsive seismic events based on time-reversal methods

    Science.gov (United States)

    Solano, Ericka Alinne; Hjörleifsdóttir, Vala; Liu, Qinya

    2017-12-01

    We present a full-waveform detection method for non-impulsive seismic events, based on time-reversal principles. We use the strain Green's tensor as a matched filter, correlating it with continuous observed seismograms, to detect non-impulsive seismic events. We show that this is mathematically equivalent to an adjoint method for detecting earthquakes. We define the detection function, a scalar valued function, which depends on the stacked correlations for a group of stations. Event detections are given by the times at which the amplitude of the detection function exceeds a given value relative to the noise level. The method can make use of the whole seismic waveform or any combination of time-windows with different filters. It is expected to have an advantage compared to traditional detection methods for events that do not produce energetic and impulsive P waves, for example glacial events, landslides, volcanic events and transform-fault earthquakes for events which velocity structure along the path is relatively well known. Furthermore, the method has advantages over empirical Greens functions template matching methods, as it does not depend on records from previously detected events, and therefore is not limited to events occurring in similar regions and with similar focal mechanisms as these events. The method is not specific to any particular way of calculating the synthetic seismograms, and therefore complicated structural models can be used. This is particularly beneficial for intermediate size events that are registered on regional networks, for which the effect of lateral structure on the waveforms can be significant. To demonstrate the feasibility of the method, we apply it to two different areas located along the mid-oceanic ridge system west of Mexico where non-impulsive events have been reported. The first study area is between Clipperton and Siqueiros transform faults (9°N), during the time of two earthquake swarms, occurring in March 2012 and May

  14. High-resolution seismic event detection using local similarity for Large-N arrays.

    Science.gov (United States)

    Li, Zefeng; Peng, Zhigang; Hollis, Dan; Zhu, Lijun; McClellan, James

    2018-01-26

    We develop a novel method for seismic event detection that can be applied to large-N arrays. The method is based on a new detection function named local similarity, which quantifies the signal consistency between the examined station and its nearest neighbors. Using the 5200-station Long Beach nodal array, we demonstrate that stacked local similarity functions can be used to detect seismic events with amplitudes near or below noise levels. We apply the method to one-week continuous data around the 03/11/2011 Mw 9.1 Tohoku-Oki earthquake, to detect local and distant events. In the 5-10 Hz range, we detect various events of natural and anthropogenic origins, but without a clear increase in local seismicity during and following the surface waves of the Tohoku-Oki mainshock. In the 1-Hz low-pass-filtered range, we detect numerous events, likely representing aftershocks from the Tohoku-Oki mainshock region. This high-resolution detection technique can be applied to both ultra-dense and regular array recordings for monitoring ultra-weak micro-seismicity and detecting unusual seismic events in noisy environments.

  15. Learning Latent Super-Events to Detect Multiple Activities in Videos

    OpenAIRE

    Piergiovanni, AJ; Ryoo, Michael S.

    2017-01-01

    In this paper, we introduce the concept of learning latent \\emph{super-events} from activity videos, and present how it benefits activity detection in continuous videos. We define a super-event as a set of multiple events occurring together in videos with a particular temporal organization; it is the opposite concept of sub-events. Real-world videos contain multiple activities and are rarely segmented (e.g., surveillance videos), and learning latent super-events allows the model to capture ho...

  16. High-resolution bolometers for rare events detection

    Energy Technology Data Exchange (ETDEWEB)

    Vanzini, M. E-mail: marco.vanzini@mi.infn.it; Alessandrello, A.; Brofferio, C.; Bucci, C.; Coccia, E.; Cremonesi, O.; Fafone, V.; Fiorini, E.; Giuliani, A.; Nucciotti, A.; Pavan, M.; Peruzzi, A.; Pessina, G.; Pirro, S.; Pobes, C.; Parmeggiano, S.; Perego, M.; Previtali, E.; Rotilio, A.; Zanotti, L

    2001-04-01

    Since many years the Milano-Gran Sasso collaboration is developing large mass calorimeters for Double Beta Decay and Dark Matter searches, employing TeO{sub 2} crystals as absorber elements. Recently, we have focused our attention on the improvement of the detector resolution: an efficient dumping suspension and the implementation of a new cold electronics device, have strongly suppressed the main sources of noise. The increase in S/N ratio has been of almost an order of magnitude and the resolution achieved is competitive with that of Ge diodes for {gamma}-rays detection, while a FWHM of 3.2{+-}0.3 keV has been obtained for 5.4 MeV alpha particles, the best result with any kind of detector.

  17. High-resolution bolometers for rare events detection

    Science.gov (United States)

    Vanzini, M.; Alessandrello, A.; Brofferio, C.; Bucci, C.; Coccia, E.; Cremonesi, O.; Fafone, V.; Fiorini, E.; Giuliani, A.; Nucciotti, A.; Pavan, M.; Peruzzi, A.; Pessina, G.; Pirro, S.; Pobes, C.; Parmeggiano, S.; Perego, M.; Previtali, E.; Rotilio, A.; Zanotti, L.

    2001-04-01

    Since many years the Milano-Gran Sasso collaboration is developing large mass calorimeters for Double Beta Decay and Dark Matter searches, employing TeO 2 crystals as absorber elements. Recently, we have focused our attention on the improvement of the detector resolution: an efficient dumping suspension and the implementation of a new cold electronics device, have strongly suppressed the main sources of noise. The increase in S/ N ratio has been of almost an order of magnitude and the resolution achieved is competitive with that of Ge diodes for γ-rays detection, while a FWHM of 3.2±0.3 keV has been obtained for 5.4 MeV alpha particles, the best result with any kind of detector.

  18. A New Mining Method to Detect Real Time Substance Use Events from Wearable Biosensor Data Stream.

    Science.gov (United States)

    Wang, Jin; Fang, Hua; Carreiro, Stephanie; Wang, Honggang; Boyer, Edward

    2017-01-01

    Detecting real time substance use is a critical step for optimizing behavioral interventions to prevent drug abuse. Traditional methods based on self-reporting or urine screening are inefficient or intrusive for drug use detection, and inappropriate for timely interventions. For example, self-report suffers from distortion or recall bias; while urine screening often detects drug use that occurred only within the previous 72 hours. Methods for real-time substance use detection are severely underdeveloped, partly due to the novelty of wearable biosensor technique and the lack of substantive clinical data for evaluation. We propose a new real-time drug use event detection method using data obtained from wearable biosensors. Specifically, this method is built upon the slide window technique to process the data stream, and a distance-based outlier detection method to identify substance use events. This novel method is designed to examine how to detect and set up the thresholds of parameters in real-time drug use event detection for wearable biosensor data streams. Our numerical analyses empirically identified the thresholds of parameters used to detect the cocaine use and showed that this proposed method could be adapted to detect other substance use events.

  19. Systematic detection of seismic events at Mount St. Helens with an ultra-dense array

    Science.gov (United States)

    Meng, X.; Hartog, J. R.; Schmandt, B.; Hotovec-Ellis, A. J.; Hansen, S. M.; Vidale, J. E.; Vanderplas, J.

    2016-12-01

    During the summer of 2014, an ultra-dense array of 900 geophones was deployed around the crater of Mount St. Helens and continuously operated for 15 days. This dataset provides us an unprecedented opportunity to systematically detect seismic events around an active volcano and study their underlying mechanisms. We use a waveform-based matched filter technique to detect seismic events from this dataset. Due to the large volume of continuous data ( 1 TB), we performed the detection on the GPU cluster Stampede (https://www.tacc.utexas.edu/systems/stampede). We build a suite of template events from three catalogs: 1) the standard Pacific Northwest Seismic Network (PNSN) catalog (45 events); 2) the catalog from Hansen&Schmandt (2015) obtained with a reverse-time imaging method (212 events); and 3) the catalog identified with a matched filter technique using the PNSN permanent stations (190 events). By searching for template matches in the ultra-dense array, we find 2237 events. We then calibrate precise relative magnitudes for template and detected events, using a principal component fit to measure waveform amplitude ratios. The magnitude of completeness and b-value of the detected catalog is -0.5 and 1.1, respectively. Our detected catalog shows several intensive swarms, which are likely driven by fluid pressure transients in conduits or slip transients on faults underneath the volcano. We are currently relocating the detected catalog with HypoDD and measuring the seismic velocity changes at Mount St. Helens using the coda wave interferometry of detected repeating earthquakes. The accurate temporal-spatial migration pattern of seismicity and seismic property changes should shed light on the physical processes beneath Mount St. Helens.

  20. Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model ?

    OpenAIRE

    Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse

    2017-01-01

    Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algori...

  1. Building a Test Collection for Significant-Event Detection in Arabic Tweets

    OpenAIRE

    Almerekhi, Hind Ali

    2016-01-01

    With the increasing popularity of microblogging services like Twitter, researchers discov- ered a rich medium for tackling real-life problems like event detection. However, event detection in Twitter is often obstructed by the lack of public evaluation mechanisms such as test collections (set of tweets, labels, and queries to measure the eectiveness of an information retrieval system). The problem is more evident when non-English lan- guages, e.g., Arabic, are concerned. With t...

  2. An integrated logit model for contamination event detection in water distribution systems.

    Science.gov (United States)

    Housh, Mashor; Ostfeld, Avi

    2015-05-15

    The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Event-specific qualitative and quantitative detection of five genetically modified rice events using a single standard reference molecule.

    Science.gov (United States)

    Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Shin, Min-Ki; Moon, Gui-Im; Hong, Jin-Hwan; Kim, Hae-Yeong

    2017-07-01

    One novel standard reference plasmid, namely pUC-RICE5, was constructed as a positive control and calibrator for event-specific qualitative and quantitative detection of genetically modified (GM) rice (Bt63, Kemingdao1, Kefeng6, Kefeng8, and LLRice62). pUC-RICE5 contained fragments of a rice-specific endogenous reference gene (sucrose phosphate synthase) as well as the five GM rice events. An existing qualitative PCR assay approach was modified using pUC-RICE5 to create a quantitative method with limits of detection correlating to approximately 1-10 copies of rice haploid genomes. In this quantitative PCR assay, the square regression coefficients ranged from 0.993 to 1.000. The standard deviation and relative standard deviation values for repeatability ranged from 0.02 to 0.22 and 0.10% to 0.67%, respectively. The Ministry of Food and Drug Safety (Korea) validated the method and the results suggest it could be used routinely to identify five GM rice events. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Real-time detection and classification of anomalous events in streaming data

    Science.gov (United States)

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

    2016-04-19

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

  5. A robust neural network-based approach for microseismic event detection

    KAUST Repository

    Akram, Jubran

    2017-08-17

    We present an artificial neural network based approach for robust event detection from low S/N waveforms. We use a feed-forward network with a single hidden layer that is tuned on a training dataset and later applied on the entire example dataset for event detection. The input features used include the average of absolute amplitudes, variance, energy-ratio and polarization rectilinearity. These features are calculated in a moving-window of same length for the entire waveform. The output is set as a user-specified relative probability curve, which provides a robust way of distinguishing between weak and strong events. An optimal network is selected by studying the weight-based saliency and effect of number of neurons on the predicted results. Using synthetic data examples, we demonstrate that this approach is effective in detecting weaker events and reduces the number of false positives.

  6. An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

    Science.gov (United States)

    Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

    2015-01-01

    This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

  7. Validity of the clinical and administrative databases in detecting post-operative adverse events.

    Science.gov (United States)

    Rodrigo-Rincon, Isabel; Martin-Vizcaino, Marta P; Tirapu-Leon, Belen; Zabalza-Lopez, Pedro; Abad-Vicente, Francisco J; Merino-Peralta, Asuncion

    2015-08-01

    Patient safety has become a major public health concern and a priority for multiple institutions. Assessment of the adverse events is a key element for measuring the quality of healthcare organizations. The aim of this study was to measure the validity of the clinical and administrative database (CADB) as a source of information for the detection of post-operative adverse events. The study design was cross-sectional. The study was carried out at the Hospital de Navarra (north of Spain). The sample consisted of 1602 episodes of surgical hospitalization from nine surgical departments. Two sources of information were used: data extracted from the complete clinical record (CR), the gold standard, vs. the CADB. Rate of adverse events, sensitivity, positive predictive value and κ index were analysed for 28 types of post-operative adverse event. Each index was considered acceptable if it had a value >0.6. The rate of adverse events using the CADB was 12.5 vs. 24% using CR within 30 days of surgery (P = 0.0001) and 13.9% using CR during a hospital stay (P > 0.05). The overall sensitivity of the CADB in the detection of adverse events was 0.18, and the positive predictive value was 0.34. Two adverse events (accounted for 6% of the total events detected) had moderate validity and the rest poor validity. Forty-two per cent of the adverse events took place after patient discharge. Although the use of CADB is appealing, the present study suggests that it is of very limited value in the detection of adverse events post-operatively. © The Author 2015. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

  8. Using machine learning to detect events in eye-tracking data.

    Science.gov (United States)

    Zemblys, Raimondas; Niehorster, Diederick C; Komogortsev, Oleg; Holmqvist, Kenneth

    2017-02-23

    Event detection is a challenging stage in eye movement data analysis. A major drawback of current event detection methods is that parameters have to be adjusted based on eye movement data quality. Here we show that a fully automated classification of raw gaze samples as belonging to fixations, saccades, or other oculomotor events can be achieved using a machine-learning approach. Any already manually or algorithmically detected events can be used to train a classifier to produce similar classification of other data without the need for a user to set parameters. In this study, we explore the application of random forest machine-learning technique for the detection of fixations, saccades, and post-saccadic oscillations (PSOs). In an effort to show practical utility of the proposed method to the applications that employ eye movement classification algorithms, we provide an example where the method is employed in an eye movement-driven biometric application. We conclude that machine-learning techniques lead to superior detection compared to current state-of-the-art event detection algorithms and can reach the performance of manual coding.

  9. Visual Sensor Based Abnormal Event Detection with Moving Shadow Removal in Home Healthcare Applications

    OpenAIRE

    Young-Sook Lee; Wan-Young Chung

    2012-01-01

    Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects...

  10. Detection of vulnerable relays and sensitive controllers under cascading events based on performance indices

    DEFF Research Database (Denmark)

    Liu, Zhou; Chen, Zhe; Hu, Yanting

    2014-01-01

    ) based detection strategy is proposed to identify the vulnerable relays and sensitive controllers under the overloading situation during cascading events. Based on the impedance margin sensitivity, diverse performance indices are proposed to help improving this detection. A study case of voltage...... instability induced cascaded blackout built in real time digital simulator (RTDS) will be used to demonstrate the proposed strategy. The simulation results indicate this strategy can effectively detect the vulnerable relays and sensitive controllers under overloading situations....

  11. RNAEditor: easy detection of RNA editing events and the introduction of editing islands.

    Science.gov (United States)

    John, David; Weirick, Tyler; Dimmeler, Stefanie; Uchida, Shizuka

    2017-11-01

    RNA editing of adenosine residues to inosine ('A-to-I editing') is the most common RNA modification event detectible with RNA sequencing (RNA-seq). While not directly detectable, inosine is read by next-generation sequencers as guanine. Therefore, mapping RNA-seq reads to their corresponding reference genome can detect potential editing events by identifying 'A-to-G' conversions. However, one must exercise caution when searching for editing sites, as A-to-G conversions also arise from sequencing errors as well as mutations. To address these complexities, several algorithms and software products have been developed to accurately identify editing events. Here, we survey currently available methods to analyze RNA editing events and introduce a new easy-to-use bioinformatics tool 'RNAEditor' for the detection of RNA editing events. During the development of RNAEditor, we noticed editing often happened in clusters, which we named 'editing islands'. We developed a clustering algorithm to find editing islands and included it in RNAEditor. RNAEditor is freely available at http://rnaeditor.uni-frankfurt.de. We anticipate that RNAEditor will provide biologists with an easy-to-use tool for studying RNA editing events and the newly defined editing islands. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. Contamination Event Detection with Multivariate Time-Series Data in Agricultural Water Monitoring

    Directory of Open Access Journals (Sweden)

    Yingchi Mao

    2017-12-01

    Full Text Available Time series data of multiple water quality parameters are obtained from the water sensor networks deployed in the agricultural water supply network. The accurate and efficient detection and warning of contamination events to prevent pollution from spreading is one of the most important issues when pollution occurs. In order to comprehensively reduce the event detection deviation, a spatial–temporal-based event detection approach with multivariate time-series data for water quality monitoring (M-STED was proposed. The M-STED approach includes three parts. The first part is that M-STED adopts a Rule K algorithm to select backbone nodes as the nodes in the CDS, and forward the sensed data of multiple water parameters. The second part is to determine the state of each backbone node with back propagation neural network models and the sequential Bayesian analysis in the current timestamp. The third part is to establish a spatial model with Bayesian networks to estimate the state of the backbones in the next timestamp and trace the “outlier” node to its neighborhoods to detect a contamination event. The experimental results indicate that the average detection rate is more than 80% with M-STED and the false detection rate is lower than 9%, respectively. The M-STED approach can improve the rate of detection by about 40% and reduce the false alarm rate by about 45%, compared with the event detection with a single water parameter algorithm, S-STED. Moreover, the proposed M-STED can exhibit better performance in terms of detection delay and scalability.

  13. Assessing the probability of detection of horizontal gene transfer events in bacterial populations

    Directory of Open Access Journals (Sweden)

    Jeffrey P. Townsend

    2012-02-01

    Full Text Available Experimental approaches to identify horizontal gene transfer (HGT events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modelling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genetic material, such as antibiotic resistance genes or transgenes present in GMOs. Due to the long time scales involved and the exponential growth of bacteria with differing fitness, quantitative analyses incorporating bacterial generation time and levels of selection, such as the one presented here, will be a necessary component of any future experimental design and analysis of HGT as it occurs in natural settings.

  14. Autonomous Gait Event Detection with Portable Single-Camera Gait Kinematics Analysis System

    Directory of Open Access Journals (Sweden)

    Cheng Yang

    2016-01-01

    Full Text Available Laboratory-based nonwearable motion analysis systems have significantly advanced with robust objective measurement of the limb motion, resulting in quantified, standardized, and reliable outcome measures compared with traditional, semisubjective, observational gait analysis. However, the requirement for large laboratory space and operational expertise makes these systems impractical for gait analysis at local clinics and homes. In this paper, we focus on autonomous gait event detection with our bespoke, relatively inexpensive, and portable, single-camera gait kinematics analysis system. Our proposed system includes video acquisition with camera calibration, Kalman filter + Structural-Similarity-based marker tracking, autonomous knee angle calculation, video-frame-identification-based autonomous gait event detection, and result visualization. The only operational effort required is the marker-template selection for tracking initialization, aided by an easy-to-use graphic user interface. The knee angle validation on 10 stroke patients and 5 healthy volunteers against a gold standard optical motion analysis system indicates very good agreement. The autonomous gait event detection shows high detection rates for all gait events. Experimental results demonstrate that the proposed system can automatically measure the knee angle and detect gait events with good accuracy and thus offer an alternative, cost-effective, and convenient solution for clinical gait kinematics analysis.

  15. A novel method to precisely detect apnea and hypopnea events by airflow and oximetry signals.

    Science.gov (United States)

    Huang, Wu; Guo, Bing; Shen, Yan; Tang, Xiangdong

    2017-09-01

    Sleep apnea hypopnea syndrome (SAHS) affects people's quality of life. The apnea hypopnea index (AHI) is the key indicator for diagnosing SAHS. The determination of the AHI is based on accurate detection of apnea and hypopnea events. This paper provides a novel method to detect apnea and hypopnea events based on the respiratory nasal airflow signal and the oximetry signal. The method uses sliding window and short time slice methods to eliminate systematic and sporadic noise of the airflow signal for improving the detection precision. Using this algorithm, the sleep data of 30 subjects from the Huaxi Sleep Center of Sichuan University (HSCSU) and the Teaching Hospital of Chengdu University of Traditional Chinese Medicine (THCUTCM) were auto-analyzed for detecting the apnea and hypopnea events. The total predicted apnea and hypopnea events were 8470. By manual investigation, the sensitivity and positive predictive value (PPV) of detecting apnea and hypopnea events were 97.6% and 95.7%, respectively. The sleep data of 28 subjects form HSCSU were auto-diagnosed SAHS according to the AHI. The sensitivity and PPV were 92.3% and 92.3%, respectively. This is an effective and precise method to diagnose SAHS. It can fit the home care SAHS screener. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. On Event/Time Triggered and Distributed Analysis of a WSN System for Event Detection, Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Sofia Maria Dima

    2016-01-01

    Full Text Available Event detection in realistic WSN environments is a critical research domain, while the environmental monitoring comprises one of its most pronounced applications. Although efforts related to the environmental applications have been presented in the current literature, there is a significant lack of investigation on the performance of such systems, when applied in wireless environments. Aiming at addressing this shortage, in this paper an advanced multimodal approach is followed based on fuzzy logic. The proposed fuzzy inference system (FIS is implemented on TelosB motes and evaluates the probability of fire detection while aiming towards power conservation. Additionally to a straightforward centralized approach, a distributed implementation of the above FIS is also proposed, aiming towards network congestion reduction while optimally distributing the energy consumption among network nodes so as to maximize network lifetime. Moreover this work proposes an event based execution of the aforementioned FIS aiming to further reduce the computational as well as the communication cost, compared to a periodical time triggered FIS execution. As a final contribution, performance metrics acquired from all the proposed FIS implementation techniques are thoroughly compared and analyzed with respect to critical network conditions aiming to offer realistic evaluation and thus objective conclusions’ extraction.

  17. Infrasound Analysis: Reduction of Missed Events and Detection of Simultaneous Signals.

    Science.gov (United States)

    Averbuch, G.; Assink, J. D.; Smets, P. S. M.; Evers, L. G.

    2016-12-01

    Automatic detection of infrasound signals, e.g. using microbarometer arrays of the International Monitoring System (IMS) from the Comprehensive Nuclear-Test-Ban Treaty (CTBT), requires low rates of both false alarms and missed events. In this presentation, we focus on the detection of simultaneous, low signal-to-noise ratio (SNR) infrasound signals. Simultaneous signals may mask each other and may cause low SNR values. We introduce a new method based on the Fisher detector and the Hough transform which allows reducing the number of missed events by 1) detecting low SNR signals and 2) detecting simultaneous signals. The new method is applied on multiple years of infrasound data from I18DK (Greenland) and shows an increase of 20% in the number of detections.

  18. Multiplexed polarization OTDR system with high DOP and ability of multi-event detection.

    Science.gov (United States)

    Wang, Xuefeng; Wang, Chaodong; Tang, Ming; Fu, Songnian; Shum, Perry

    2017-05-01

    A novel polarization optical time domain reflectometry (POTDR) with high degree of polarization is proposed for multi-event detection. By employing multiple 2×2 optical fiber couplers and fiber mirrors, an arbitrary number and customized length of sensing fiber can be multiplexed into the system without modification of the other components, e.g., the light source, photodetector, signal processing device, etc. More importantly, the signal-to-noise ratio of this system is significantly improved, and the temporal depolarization effect can be almost completely suppressed. Additionally, the system response time is considerably reduced by dispensing with data averaging, so that intrusion events such as touching and moving fiber can be detected instantaneously and precisely located. Experiments have been conducted that proved the capability of multi-event simultaneous detection and vibration frequency measurement. This system promises application potential in multi-zone perimeter security and physical field measurement.

  19. Visual sensor based abnormal event detection with moving shadow removal in home healthcare applications.

    Science.gov (United States)

    Lee, Young-Sook; Chung, Wan-Young

    2012-01-01

    Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects more accurately and discriminate between abnormal and normal activities. To improve the accuracy of object detection and tracking, our proposed shadow removal algorithm is employed. Abnormal event detection based on visual sensor by using shape features variation and 3-D trajectory is presented to overcome the low fall detection rate. The experimental results showed that the success rate of detecting abnormal events was 97% with a false positive rate of 2%. Our proposed algorithm can allow distinguishing diverse fall activities such as forward falls, backward falls, and falling asides from normal activities.

  20. Visual Sensor Based Abnormal Event Detection with Moving Shadow Removal in Home Healthcare Applications

    Directory of Open Access Journals (Sweden)

    Young-Sook Lee

    2012-01-01

    Full Text Available Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects more accurately and discriminate between abnormal and normal activities. To improve the accuracy of object detection and tracking, our proposed shadow removal algorithm is employed. Abnormal event detection based on visual sensor by using shape features variation and 3-D trajectory is presented to overcome the low fall detection rate. The experimental results showed that the success rate of detecting abnormal events was 97% with a false positive rate of 2%. Our proposed algorithm can allow distinguishing diverse fall activities such as forward falls, backward falls, and falling asides from normal activities.

  1. Discrete Event Simulation Model of the Polaris 2.1 Gamma Ray Imaging Radiation Detection Device

    Science.gov (United States)

    2016-06-01

    Polaris given that the Polaris continues to make improvements not just in GPS and WIFI capabilities but in capture rates for different radiation ...release; distribution is unlimited DISCRETE EVENT SIMULATION MODEL OF THE POLARIS 2.1 GAMMA RAY IMAGING RADIATION DETECTION DEVICE by Andres T...OF THE POLARIS 2.1 GAMMA RAY IMAGING RADIATION DETECTION DEVICE 5. FUNDING NUMBERS 6. AUTHOR(S) Andres T. Juarez III 7. PERFORMING ORGANIZATION

  2. Events

    Directory of Open Access Journals (Sweden)

    Igor V. Karyakin

    2016-02-01

    Full Text Available The 9th ARRCN Symposium 2015 was held during 21st–25th October 2015 at the Novotel Hotel, Chumphon, Thailand, one of the most favored travel destinations in Asia. The 10th ARRCN Symposium 2017 will be held during October 2017 in the Davao, Philippines. International Symposium on the Montagu's Harrier (Circus pygargus «The Montagu's Harrier in Europe. Status. Threats. Protection», organized by the environmental organization «Landesbund für Vogelschutz in Bayern e.V.» (LBV was held on November 20-22, 2015 in Germany. The location of this event was the city of Wurzburg in Bavaria.

  3. Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection

    Science.gov (United States)

    Liu, Changyu; Li, Huiling

    2014-01-01

    We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches. PMID:25147840

  4. The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection

    NARCIS (Netherlands)

    Mettes, P.; Koelma, D.C.; Snoek, C.G.M.

    2016-01-01

    This paper strives for video event detection using a representation learned from deep convolutional neural networks. Different from the leading approaches, who all learn from the 1,000 classes defined in the ImageNet Large Scale Visual Recognition Challenge, we investigate how to leverage the

  5. Real-Time Event Detection for Monitoring Natural and Source Waterways - Sacramento, CA

    Science.gov (United States)

    The use of event detection systems in finished drinking water systems is increasing in order to monitor water quality in both operational and security contexts. Recent incidents involving harmful algal blooms and chemical spills into watersheds have increased interest in monitori...

  6. Use of wireless sensor networks for distributed event detection in disaster management applications

    NARCIS (Netherlands)

    Bahrepour, M.; Meratnia, Nirvana; Poel, Mannes; Taghikhaki, Zahra; Havinga, Paul J.M.

    Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and have become one of the enabling technologies for early-warning disaster systems. Event detection functionality of WSNs can be of great help and importance

  7. Detecting erosion events in earth dam and levee passive seismic data with clustering

    NARCIS (Netherlands)

    Belcher, W.; Camp, T.; Krzhizhanovskaya, V.V.

    2015-01-01

    Geophysical sensor technologies can be used to understand the structural integrity of Earth Dams and Levees (EDLs). We are part of an interdisciplinary team researching techniques for the advancement of EDL health monitoring and the automatic detection of internal erosion events. We present results

  8. Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model.

    Science.gov (United States)

    Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse

    2017-03-24

    Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algorithms, accumulating to a total of 558 steps. The reference for the gait events was obtained using marker and force plate data. All algorithms had excellent precision and no false positives were observed. Timing delays of the presented algorithms were similar to current state-of-the-art algorithms for the detection of IC and TO, whereas smaller delays were achieved for the detection of FF. Our results indicate that, based on their high precision and low delays, these algorithms can be used for the control of an NR/NP, with the exception of the HO event. Kinematic data is used in most NR/NP control schemes and is thus available at no additional cost, resulting in a minimal computational burden. The presented methods can also be applied for screening pathological gait or gait analysis in general in/outside of the laboratory.

  9. Detection and identification of multiple genetically modified events using DNA insert fingerprinting.

    Science.gov (United States)

    Raymond, Philippe; Gendron, Louis; Khalf, Moustafa; Paul, Sylvianne; Dibley, Kim L; Bhat, Somanath; Xie, Vicki R D; Partis, Lina; Moreau, Marie-Eve; Dollard, Cheryl; Coté, Marie-José; Laberge, Serge; Emslie, Kerry R

    2010-03-01

    Current screening and event-specific polymerase chain reaction (PCR) assays for the detection and identification of genetically modified organisms (GMOs) in samples of unknown composition or for the detection of non-regulated GMOs have limitations, and alternative approaches are required. A transgenic DNA fingerprinting methodology using restriction enzyme digestion, adaptor ligation, and nested PCR was developed where individual GMOs are distinguished by the characteristic fingerprint pattern of the fragments generated. The inter-laboratory reproducibility of the amplified fragment sizes using different capillary electrophoresis platforms was compared, and reproducible patterns were obtained with an average difference in fragment size of 2.4 bp. DNA insert fingerprints for 12 different maize events, including two maize hybrids and one soy event, were generated that reflected the composition of the transgenic DNA constructs. Once produced, the fingerprint profiles were added to a database which can be readily exchanged and shared between laboratories. This approach should facilitate the process of GMO identification and characterization.

  10. A novel seizure detection algorithm informed by hidden Markov model event states

    Science.gov (United States)

    Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian

    2016-06-01

    Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h-1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.

  11. Event detection and exception handling strategies in the ASDEX Upgrade discharge control system

    Energy Technology Data Exchange (ETDEWEB)

    Treutterer, W., E-mail: Wolfgang.Treutterer@ipp.mpg.de; Neu, G.; Rapson, C.; Raupp, G.; Zasche, D.; Zehetbauer, T.

    2013-10-15

    Highlights: •Event detection and exception handling is integrated in control system architecture. •Pulse control with local exception handling and pulse supervision with central exception handling are strictly separated. •Local exception handling limits the effect of an exception to a minimal part of the controlled system. •Central Exception Handling solves problems requiring coordinated action of multiple control components. -- Abstract: Thermonuclear plasmas are governed by nonlinear characteristics: plasma operation can be classified into scenarios with pronounced features like L and H-mode, ELMs or MHD activity. Transitions between them may be treated as events. Similarly, technical systems are also subject to events such as failure of measurement sensors, actuator saturation or violation of machine and plant operation limits. Such situations often are handled with a mixture of pulse abortion and iteratively improved pulse schedule reference programming. In case of protection-relevant events, however, the complexity of even a medium-sized device as ASDEX Upgrade requires a sophisticated and coordinated shutdown procedure rather than a simple stop of the pulse. The detection of events and their intelligent handling by the control system has been shown to be valuable also in terms of saving experiment time and cost. This paper outlines how ASDEX Upgrade's discharge control system (DCS) detects events and handles exceptions in two stages: locally and centrally. The goal of local exception handling is to limit the effect of an unexpected or asynchronous event to a minimal part of the controlled system. Thus, local exception handling facilitates robustness to failures but keeps the decision structures lean. A central state machine deals with exceptions requiring coordinated action of multiple control components. DCS implements the state machine by means of pulse schedule segments containing pre-programmed waveforms to define discharge goal and control

  12. Detection of genetically modified maize and soybean in feed samples.

    Science.gov (United States)

    Meriç, S; Cakır, O; Turgut-Kara, N; Arı, S

    2014-02-25

    Despite the controversy about genetically modified (GM) plants, they are still incrementally cultivated. In recent years, many food and feed products produced by genetic engineering technology have appeared on store shelves. Controlling the production and legal presentation of GM crops are very important for the environment and human health, especially in terms of long-term consumption. In this study, 11 kinds of feed obtained from different regions of Turkey were used for genetic analysis based on foreign gene determination. All samples were screened by conventional polymerase chain reaction (PCR) technique for widely used genetic elements; cauliflower mosaic virus 35S promoter (CaMV35S promoter), and nopaline synthase terminator (T-NOS) sequences for GM plants. After determination of GM plant-containing samples, nested PCR and conventional PCR analysis were performed to find out whether the samples contained Bt176 or GTS-40-3-2 for maize and soy, respectively. As a result of PCR-based GM plant analysis, all samples were found to be transgenic. Both 35S- and NOS-containing feed samples or potentially Bt176-containing samples, in other words, were analyzed with Bt176 insect resistant cryIAb gene-specific primers via nested PCR. Eventually, none of them were found Bt176-positive. On the other hand, when we applied conventional PCR to the same samples with the herbicide resistance CTP4-EPSPS construct-specific primers for transgenic soy variety GTS-40-3-2, we found that all samples were positive for GTS-40-3-2.

  13. Enhancing adverse drug event detection in electronic health records using molecular structure similarity: application to pancreatitis.

    Directory of Open Access Journals (Sweden)

    Santiago Vilar

    Full Text Available Adverse drug events (ADEs detection and assessment is at the center of pharmacovigilance. Data mining of systems, such as FDA's Adverse Event Reporting System (AERS and more recently, Electronic Health Records (EHRs, can aid in the automatic detection and analysis of ADEs. Although different data mining approaches have been shown to be valuable, it is still crucial to improve the quality of the generated signals.To leverage structural similarity by developing molecular fingerprint-based models (MFBMs to strengthen ADE signals generated from EHR data.A reference standard of drugs known to be causally associated with the adverse event pancreatitis was used to create a MFBM. Electronic Health Records (EHRs from the New York Presbyterian Hospital were mined to generate structured data. Disproportionality Analysis (DPA was applied to the data, and 278 possible signals related to the ADE pancreatitis were detected. Candidate drugs associated with these signals were then assessed using the MFBM to find the most promising candidates based on structural similarity.The use of MFBM as a means to strengthen or prioritize signals generated from the EHR significantly improved the detection accuracy of ADEs related to pancreatitis. MFBM also highlights the etiology of the ADE by identifying structurally similar drugs, which could follow a similar mechanism of action.The method proposed in this paper provides evidence of being a promising adjunct to existing automated ADE detection and analysis approaches.

  14. A novel adaptive, real-time algorithm to detect gait events from wearable sensors.

    Science.gov (United States)

    Chia Bejarano, Noelia; Ambrosini, Emilia; Pedrocchi, Alessandra; Ferrigno, Giancarlo; Monticone, Marco; Ferrante, Simona

    2015-05-01

    A real-time, adaptive algorithm based on two inertial and magnetic sensors placed on the shanks was developed for gait-event detection. For each leg, the algorithm detected the Initial Contact (IC), as the minimum of the flexion/extension angle, and the End Contact (EC) and the Mid-Swing (MS), as minimum and maximum of the angular velocity, respectively. The algorithm consisted of calibration, real-time detection, and step-by-step update. Data collected from 22 healthy subjects (21 to 85 years) walking at three self-selected speeds were used to validate the algorithm against the GaitRite system. Comparable levels of accuracy and significantly lower detection delays were achieved with respect to other published methods. The algorithm robustness was tested on ten healthy subjects performing sudden speed changes and on ten stroke subjects (43 to 89 years). For healthy subjects, F1-scores of 1 and mean detection delays lower than 14 ms were obtained. For stroke subjects, F1-scores of 0.998 and 0.944 were obtained for IC and EC, respectively, with mean detection delays always below 31 ms. The algorithm accurately detected gait events in real time from a heterogeneous dataset of gait patterns and paves the way for the design of closed-loop controllers for customized gait trainings and/or assistive devices.

  15. Personalized Behavior Pattern Recognition and Unusual Event Detection for Mobile Users

    Directory of Open Access Journals (Sweden)

    Junho Ahn

    2013-01-01

    Full Text Available Mobile phones have become widely used for obtaining help in emergencies, such as accidents, crimes, or health emergencies. The smartphone is an essential device that can record emergency situations, which can be used for clues or evidence, or as an alert system in such situations. In this paper, we focus on mobile-based identification of potentially unusual, or abnormal events, occurring in a mobile user's daily behavior patterns. For purposes of this research, we have classified events as “unusual” for a mobile user when an event is an infrequently occurring one from the user's normal behavior patterns–all of which are collected and recorded on a user's mobile phone. We build a general unusual event classification model to be automated on the smartphone for use by any mobile phone users. To classify both normal and unusual events, we analyzed the activity, location, and audio sensor data collected from 20 mobile phone users to identify these users' personalized normal daily behavior patterns and any unusual events occurring in their daily activity. We used binary fusion classification algorithms on the subjects' recorded experimental data and ultimately identified the most accurately performing fusion algorithm for unusual event detection.

  16. Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

    Science.gov (United States)

    Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

    2013-11-01

    The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

  17. Visual and Real-Time Event-Specific Loop-Mediated Isothermal Amplification Based Detection Assays for Bt Cotton Events MON531 and MON15985.

    Science.gov (United States)

    Randhawa, Gurinder Jit; Chhabra, Rashmi; Bhoge, Rajesh K; Singh, Monika

    2015-01-01

    Bt cotton events MON531 and MON15985 are authorized for commercial cultivation in more than 18 countries. In India, four Bt cotton events have been commercialized; more than 95% of total area under genetically modified (GM) cotton cultivation comprises events MON531 and MON15985. The present study reports on the development of efficient event-specific visual and real-time loop-mediated isothermal amplification (LAMP) assays for detection and identification of cotton events MON531 and MON15985. Efficiency of LAMP assays was compared with conventional and real-time PCR assays. Real-time LAMP assay was found time-efficient and most sensitive, detecting up to two target copies within 35 min. The developed real-time LAMP assays, when combined with efficient DNA extraction kit/protocol, may facilitate onsite GM detection to check authenticity of Bt cotton seeds.

  18. Signal Detection of Adverse Drug Reaction of Amoxicillin Using the Korea Adverse Event Reporting System Database.

    Science.gov (United States)

    Soukavong, Mick; Kim, Jungmee; Park, Kyounghoon; Yang, Bo Ram; Lee, Joongyub; Jin, Xue Mei; Park, Byung Joo

    2016-09-01

    We conducted pharmacovigilance data mining for a β-lactam antibiotics, amoxicillin, and compare the adverse events (AEs) with the drug labels of 9 countries including Korea, USA, UK, Japan, Germany, Swiss, Italy, France, and Laos. We used the Korea Adverse Event Reporting System (KAERS) database, a nationwide database of AE reports, between December 1988 and June 2014. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-AE pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was defined as a signal. The KAERS database contained a total of 807,582 AE reports, among which 1,722 reports were attributed to amoxicillin. Among the 192,510 antibiotics-AE pairs, the number of amoxicillin-AE pairs was 2,913. Among 241 AEs, 52 adverse events were detected as amoxicillin signals. Comparing the drug labels of 9 countries, 12 adverse events including ineffective medicine, bronchitis, rhinitis, sinusitis, dry mouth, gastroesophageal reflux, hypercholesterolemia, gastric carcinoma, abnormal crying, induration, pulmonary carcinoma, and influenza-like symptoms were not listed on any of the labels of nine countries. In conclusion, we detected 12 new signals of amoxicillin which were not listed on the labels of 9 countries. Therefore, it should be followed by signal evaluation including causal association, clinical significance, and preventability.

  19. Methods for the Detection of Adenosine-to-Inosine Editing Events in Cellular RNA.

    Science.gov (United States)

    Oakes, Eimile; Vadlamani, Pranathi; Hundley, Heather A

    2017-01-01

    Modification of RNA is essential for properly expressing the repertoire of RNA transcripts necessary for both cell type and developmental specific functions. RNA modifications serve to dynamically re-wire and fine-tune the genetic information carried by an invariable genome. One important type of RNA modification is RNA editing and the most common and well-studied type of RNA editing is the hydrolytic deamination of adenosine to inosine. Inosine is a biological mimic of guanosine; therefore, when RNA is reverse transcribed, inosine is recognized as guanosine by the reverse transcriptase and a cytidine is incorporated into the complementary DNA (cDNA) strand. During PCR amplification, guanosines pair with the newly incorporated cytidines. As a result, the adenosine-to-inosine (A-to-I) editing events are recognized as adenosine to guanosine changes when comparing the sequences of the genomic DNA to the cDNA. This chapter describes the methods for extracting endogenous RNA for subsequent analyses of A-to-I RNA editing using reverse transcriptase-based approaches. We discuss techniques for the detection of A-to-I RNA editing events in messenger RNA (mRNA), including analyzing editing levels at specific adenosines within the total pool of mRNA versus analyzing editing patterns that occur in individual transcripts and a method for detecting editing events across the entire transcriptome. The detection of RNA editing events and editing levels can be used to better understand normal biological processes and disease states.

  20. Semi-parametric Robust Event Detection for Massive Time-Domain Databases

    CERN Document Server

    Blocker, Alexander W

    2013-01-01

    The detection and analysis of events within massive collections of time-series has become an extremely important task for time-domain astronomy. In particular, many scientific investigations (e.g. the analysis of microlensing and other transients) begin with the detection of isolated events in irregularly-sampled series with both non-linear trends and non-Gaussian noise. We outline a semi-parametric, robust, parallel method for identifying variability and isolated events at multiple scales in the presence of the above complications. This approach harnesses the power of Bayesian modeling while maintaining much of the speed and scalability of more ad-hoc machine learning approaches. We also contrast this work with event detection methods from other fields, highlighting the unique challenges posed by astronomical surveys. Finally, we present results from the application of this method to 87.2 million EROS-2 sources, where we have obtained a greater than 100-fold reduction in candidates for certain types of pheno...

  1. Detection, tracking and event localization of jet stream features in 4-D atmospheric data

    Directory of Open Access Journals (Sweden)

    S. Limbach

    2012-04-01

    Full Text Available We introduce a novel algorithm for the efficient detection and tracking of features in spatiotemporal atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. The algorithm works on data given on a four-dimensional structured grid. Feature selection and clustering are based on adjustable local and global criteria, feature tracking is predominantly based on spatial overlaps of the feature's full volumes. The resulting 3-D features and the identified correspondences between features of consecutive time steps are represented as the nodes and edges of a directed acyclic graph, the event graph. Merging and splitting events appear in the event graph as nodes with multiple incoming or outgoing edges, respectively. The precise localization of the splitting events is based on a search for all grid points inside the initial 3-D feature that have a similar distance to two successive 3-D features of the next time step. The merging event is localized analogously, operating backward in time. As a first application of our method we present a climatology of upper-tropospheric jet streams and their events, based on four-dimensional wind speed data from European Centre for Medium-Range Weather Forecasts (ECMWF analyses. We compare our results with a climatology from a previous study, investigate the statistical distribution of the merging and splitting events, and illustrate the meteorological significance of the jet splitting events with a case study. A brief outlook is given on additional potential applications of the 4-D data segmentation technique.

  2. Microfluidic Arrayed Lab-On-A-Chip for Electrochemical Capacitive Detection of DNA Hybridization Events.

    Science.gov (United States)

    Ben-Yoav, Hadar; Dykstra, Peter H; Bentley, William E; Ghodssi, Reza

    2017-01-01

    A microfluidic electrochemical lab-on-a-chip (LOC) device for DNA hybridization detection has been developed. The device comprises a 3 × 3 array of microelectrodes integrated with a dual layer microfluidic valved manipulation system that provides controlled and automated capabilities for high throughput analysis of microliter volume samples. The surface of the microelectrodes is functionalized with single-stranded DNA (ssDNA) probes which enable specific detection of complementary ssDNA targets. These targets are detected by a capacitive technique which measures dielectric variation at the microelectrode-electrolyte interface due to DNA hybridization events. A quantitative analysis of the hybridization events is carried out based on a sensing modeling that includes detailed analysis of energy storage and dissipation components. By calculating these components during hybridization events the device is able to demonstrate specific and dose response sensing characteristics. The developed microfluidic LOC for DNA hybridization detection offers a technology for real-time and label-free assessment of genetic markers outside of laboratory settings, such as at the point-of-care or in-field environmental monitoring.

  3. Support Vector Machine Model for Automatic Detection and Classification of Seismic Events

    Science.gov (United States)

    Barros, Vesna; Barros, Lucas

    2016-04-01

    The automated processing of multiple seismic signals to detect, localize and classify seismic events is a central tool in both natural hazards monitoring and nuclear treaty verification. However, false detections and missed detections caused by station noise and incorrect classification of arrivals are still an issue and the events are often unclassified or poorly classified. Thus, machine learning techniques can be used in automatic processing for classifying the huge database of seismic recordings and provide more confidence in the final output. Applied in the context of the International Monitoring System (IMS) - a global sensor network developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) - we propose a fully automatic method for seismic event detection and classification based on a supervised pattern recognition technique called the Support Vector Machine (SVM). According to Kortström et al., 2015, the advantages of using SVM are handleability of large number of features and effectiveness in high dimensional spaces. Our objective is to detect seismic events from one IMS seismic station located in an area of high seismicity and mining activity and classify them as earthquakes or quarry blasts. It is expected to create a flexible and easily adjustable SVM method that can be applied in different regions and datasets. Taken a step further, accurate results for seismic stations could lead to a modification of the model and its parameters to make it applicable to other waveform technologies used to monitor nuclear explosions such as infrasound and hydroacoustic waveforms. As an authorized user, we have direct access to all IMS data and bulletins through a secure signatory account. A set of significant seismic waveforms containing different types of events (e.g. earthquake, quarry blasts) and noise is being analysed to train the model and learn the typical pattern of the signal from these events. Moreover, comparing the performance of the support

  4. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO

    Directory of Open Access Journals (Sweden)

    Lixin Yan

    2016-07-01

    Full Text Available The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1 the Markov blanket (MB algorithm is employed to extract the main factors associated with hazardous traffic events; (2 a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G have significant influences on hazardous traffic events. The sequential minimal optimization (SMO algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles.

  5. AGILE Detection of a Candidate Gamma-Ray Precursor to the ICECUBE-160731 Neutrino Event

    Science.gov (United States)

    Lucarelli, F.; Pittori, C.; Verrecchia, F.; Donnarumma, I.; Tavani, M.; Bulgarelli, A.; Giuliani, A.; Antonelli, L. A.; Caraveo, P.; Cattaneo, P. W.; Colafrancesco, S.; Longo, F.; Mereghetti, S.; Morselli, A.; Pacciani, L.; Piano, G.; Pellizzoni, A.; Pilia, M.; Rappoldi, A.; Trois, A.; Vercellone, S.

    2017-09-01

    On 2016 July 31 the ICECUBE collaboration reported the detection of a high-energy starting event induced by an astrophysical neutrino. Here, we report on a search for a gamma-ray counterpart to the ICECUBE-160731 event, made with the AGILE satellite. No detection was found spanning the time interval of ±1 ks around the neutrino event time T 0 using the AGILE “burst search” system. Looking for a possible gamma-ray precursor in the results of the AGILE-GRID automatic Quick Look procedure over predefined 48-hr time bins, we found an excess above 100 MeV between 1 and 2 days before T 0, which is positionally consistent with the ICECUBE error circle, that has a post-trial significance of about 4σ . A refined data analysis of this excess confirms, a posteriori, the automatic detection. The new AGILE transient source, named AGL J1418+0008, thus stands as a possible ICECUBE-160731 gamma-ray precursor. No other space missions nor ground observatories have reported any detection of transient emission consistent with the ICECUBE event. We show that Fermi-LAT had a low exposure for the ICECUBE region during the AGILE gamma-ray transient. Based on an extensive search for cataloged sources within the error regions of ICECUBE-160731 and AGL J1418+0008, we find a possible common counterpart showing some of the key features associated with the high-energy peaked BL Lac (HBL) class of blazars. Further investigations on the nature of this source using dedicated SWIFT ToO data are presented.

  6. Composite Event Specification and Detection for Supporting Active Capability in an OODBMS: Semantics Architecture and Implementation.

    Science.gov (United States)

    1995-03-01

    terms of the ’AND’ operator and since this definition itself is questionable these operator semantics are also unclear. " The automaton for the ’AND...Proceedings 17th International Cono frencc on Very Large Data Bases, Barcelona ( Catalonia , Spain), Sept. 1.991. 65 [FM87] C. L. Forgy and J... Catalonia , Spain), Sep. 1991. [GJS92a] N. H. Gehani, H. V. Jagadish, and 0. Shmueli. COMPOSE A System For Composite Event Specification and Detection

  7. Accelerometer Detects Pump Thrombosis and Thromboembolic Events in an In vitro HVAD Circuit.

    Science.gov (United States)

    Schalit, Itai; Espinoza, Andreas; Pettersen, Fred-Johan; Thiara, Amrit P S; Karlsen, Hilde; Sørensen, Gro; Fosse, Erik; Fiane, Arnt E; Halvorsen, Per S

    2017-10-27

    Pump thrombosis and stroke are serious complications of left ventricular assist device (LVAD) support. The aim of this study was to test the ability of an accelerometer to detect pump thrombosis and thromboembolic events (TEs) using real-time analysis of pump vibrations. An accelerometer sensor was attached to a HeartWare HVAD and tested in three in vitro experiments using different pumps for each experiment. Each experiment included thrombi injections sized 0.2-1.0 mL and control interventions: pump speed change, afterload increase, preload decrease, and saline bolus injections. A spectrogram was calculated from the accelerometer signal, and the third harmonic amplitude was used to test the sensitivity and specificity of the method. The third harmonic amplitude was compared with the pump energy consumption. The acceleration signals were of high quality. A significant change was identified in the accelerometer third harmonic during the thromboembolic interventions. The third harmonic detected thromboembolic events with higher sensitivity/specificity than LVAD energy consumption: 92%/94% vs. 72%/58%, respectively. A total of 60% of thromboembolic events led to a prolonged third harmonic amplitude change, which is indicative of thrombus mass residue on the impeller. We concluded that there is strong evidence to support the feasibility of real-time continuous LVAD monitoring for thromboembolic events and pump thrombosis using an accelerometer. Further in vivo studies are needed to confirm these promising findings.

  8. A Macro-Observation Scheme for Abnormal Event Detection in Daily-Life Video Sequences

    Directory of Open Access Journals (Sweden)

    Chiu Wei-Yao

    2010-01-01

    Full Text Available Abstract We propose a macro-observation scheme for abnormal event detection in daily life. The proposed macro-observation representation records the time-space energy of motions of all moving objects in a scene without segmenting individual object parts. The energy history of each pixel in the scene is instantly updated with exponential weights without explicitly specifying the duration of each activity. Since possible activities in daily life are numerous and distinct from each other and not all abnormal events can be foreseen, images from a video sequence that spans sufficient repetition of normal day-to-day activities are first randomly sampled. A constrained clustering model is proposed to partition the sampled images into groups. The new observed event that has distinct distance from any of the cluster centroids is then classified as an anomaly. The proposed method has been evaluated in daily work of a laboratory and BEHAVE benchmark dataset. The experimental results reveal that it can well detect abnormal events such as burglary and fighting as long as they last for a sufficient duration of time. The proposed method can be used as a support system for the scene that requires full time monitoring personnel.

  9. Automated Feature and Event Detection with SDO AIA and HMI Data

    Science.gov (United States)

    Davey, Alisdair; Martens, P. C. H.; Attrill, G. D. R.; Engell, A.; Farid, S.; Grigis, P. C.; Kasper, J.; Korreck, K.; Saar, S. H.; Su, Y.; Testa, P.; Wills-Davey, M.; Savcheva, A.; Bernasconi, P. N.; Raouafi, N.-E.; Delouille, V. A.; Hochedez, J. F..; Cirtain, J. W.; Deforest, C. E.; Angryk, R. A.; de Moortel, I.; Wiegelmann, T.; Georgouli, M. K.; McAteer, R. T. J.; Hurlburt, N.; Timmons, R.

    The Solar Dynamics Observatory (SDO) represents a new frontier in quantity and quality of solar data. At about 1.5 TB/day, the data will not be easily digestible by solar physicists using the same methods that have been employed for images from previous missions. In order for solar scientists to use the SDO data effectively they need meta-data that will allow them to identify and retrieve data sets that address their particular science questions. We are building a comprehensive computer vision pipeline for SDO, abstracting complete metadata on many of the features and events detectable on the Sun without human intervention. Our project unites more than a dozen individual, existing codes into a systematic tool that can be used by the entire solar community. The feature finding codes will run as part of the SDO Event Detection System (EDS) at the Joint Science Operations Center (JSOC; joint between Stanford and LMSAL). The metadata produced will be stored in the Heliophysics Event Knowledgebase (HEK), which will be accessible on-line for the rest of the world directly or via the Virtual Solar Observatory (VSO) . Solar scientists will be able to use the HEK to select event and feature data to download for science studies.

  10. Signal Detection of Imipenem Compared to Other Drugs from Korea Adverse Event Reporting System Database.

    Science.gov (United States)

    Park, Kyounghoon; Soukavong, Mick; Kim, Jungmee; Kwon, Kyoung Eun; Jin, Xue Mei; Lee, Joongyub; Yang, Bo Ram; Park, Byung Joo

    2017-05-01

    To detect signals of adverse drug events after imipenem treatment using the Korea Institute of Drug Safety & Risk Management-Korea adverse event reporting system database (KIDS-KD). We performed data mining using KIDS-KD, which was constructed using spontaneously reported adverse event (AE) reports between December 1988 and June 2014. We detected signals calculated the proportional reporting ratio, reporting odds ratio, and information component of imipenem. We defined a signal as any AE that satisfied all three indices. The signals were compared with drug labels of nine countries. There were 807582 spontaneous AEs reports in the KIDS-KD. Among those, the number of antibiotics related AEs was 192510; 3382 reports were associated with imipenem. The most common imipenem-associated AE was the drug eruption; 353 times. We calculated the signal by comparing with all other antibiotics and drugs; 58 and 53 signals satisfied the three methods. We compared the drug labelling information of nine countries, including the USA, the UK, Japan, Italy, Switzerland, Germany, France, Canada, and South Korea, and discovered that the following signals were currently not included in drug labels: hypokalemia, cardiac arrest, cardiac failure, Parkinson's syndrome, myocardial infarction, and prostate enlargement. Hypokalemia was an additional signal compared with all other antibiotics, and the other signals were not different compared with all other antibiotics and all other drugs. We detected new signals that were not listed on the drug labels of nine countries. However, further pharmacoepidemiologic research is needed to evaluate the causality of these signals.

  11. Adverse event detection (AED) system for continuously monitoring and evaluating structural health status

    Science.gov (United States)

    Yun, Jinsik; Ha, Dong Sam; Inman, Daniel J.; Owen, Robert B.

    2011-03-01

    Structural damage for spacecraft is mainly due to impacts such as collision of meteorites or space debris. We present a structural health monitoring (SHM) system for space applications, named Adverse Event Detection (AED), which integrates an acoustic sensor, an impedance-based SHM system, and a Lamb wave SHM system. With these three health-monitoring methods in place, we can determine the presence, location, and severity of damage. An acoustic sensor continuously monitors acoustic events, while the impedance-based and Lamb wave SHM systems are in sleep mode. If an acoustic sensor detects an impact, it activates the impedance-based SHM. The impedance-based system determines if the impact incurred damage. When damage is detected, it activates the Lamb wave SHM system to determine the severity and location of the damage. Further, since an acoustic sensor dissipates much less power than the two SHM systems and the two systems are activated only when there is an acoustic event, our system reduces overall power dissipation significantly. Our prototype system demonstrates the feasibility of the proposed concept.

  12. Presentation of the results of a Bayesian automatic event detection and localization program to human analysts

    Science.gov (United States)

    Kushida, N.; Kebede, F.; Feitio, P.; Le Bras, R.

    2016-12-01

    The Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) has been developing and testing NET-VISA (Arora et al., 2013), a Bayesian automatic event detection and localization program, and evaluating its performance in a realistic operational mode. In our preliminary testing at the CTBTO, NET-VISA shows better performance than its currently operating automatic localization program. However, given CTBTO's role and its international context, a new technology should be introduced cautiously when it replaces a key piece of the automatic processing. We integrated the results of NET-VISA into the Analyst Review Station, extensively used by the analysts so that they can check the accuracy and robustness of the Bayesian approach. We expect the workload of the analysts to be reduced because of the better performance of NET-VISA in finding missed events and getting a more complete set of stations than the current system which has been operating for nearly twenty years. The results of a series of tests indicate that the expectations born from the automatic tests, which show an overall overlap improvement of 11%, meaning that the missed events rate is cut by 42%, hold for the integrated interactive module as well. New events are found by analysts, which qualify for the CTBTO Reviewed Event Bulletin, beyond the ones analyzed through the standard procedures. Arora, N., Russell, S., and Sudderth, E., NET-VISA: Network Processing Vertically Integrated Seismic Analysis, 2013, Bull. Seismol. Soc. Am., 103, 709-729.

  13. Event Detection Using “Variable Module Graphs” for Home Care Applications

    Directory of Open Access Journals (Sweden)

    Thomas S. Huang

    2007-01-01

    Full Text Available Technology has reached new heights making sound and video capture devices ubiquitous and affordable. We propose a paradigm to exploit this technology for home care applications especially for surveillance and complex event detection. Complex vision tasks such as event detection in a surveillance video can be divided into subtasks such as human detection, tracking, recognition, and trajectory analysis. The video can be thought of as being composed of various features. These features can be roughly arranged in a hierarchy from low-level features to high-level features. Low-level features include edges and blobs, and high-level features include objects and events. Loosely, the low-level feature extraction is based on signal/image processing techniques, while the high-level feature extraction is based on machine learning techniques. Traditionally, vision systems extract features in a feed-forward manner on the hierarchy, that is, certain modules extract low-level features and other modules make use of these low-level features to extract high-level features. Along with others in the research community, we have worked on this design approach. In this paper, we elaborate on recently introduced V/M graph. We present our work on using this paradigm for developing applications for home care applications. Primary objective is surveillance of location for subject tracking as well as detecting irregular or anomalous behavior. This is done automatically with minimal human involvement, where the system has been trained to raise an alarm when anomalous behavior is detected.

  14. Detecting paralinguistic events in audio stream using context in features and probabilistic decisions.

    Science.gov (United States)

    Gupta, Rahul; Audhkhasi, Kartik; Lee, Sungbok; Narayanan, Shrikanth

    2016-03-01

    Non-verbal communication involves encoding, transmission and decoding of non-lexical cues and is realized using vocal (e.g. prosody) or visual (e.g. gaze, body language) channels during conversation. These cues perform the function of maintaining conversational flow, expressing emotions, and marking personality and interpersonal attitude. In particular, non-verbal cues in speech such as paralanguage and non-verbal vocal events (e.g. laughters, sighs, cries) are used to nuance meaning and convey emotions, mood and attitude. For instance, laughters are associated with affective expressions while fillers (e.g. um, ah, um) are used to hold floor during a conversation. In this paper we present an automatic non-verbal vocal events detection system focusing on the detect of laughter and fillers. We extend our system presented during Interspeech 2013 Social Signals Sub-challenge (that was the winning entry in the challenge) for frame-wise event detection and test several schemes for incorporating local context during detection. Specifically, we incorporate context at two separate levels in our system: (i) the raw frame-wise features and, (ii) the output decisions. Furthermore, our system processes the output probabilities based on a few heuristic rules in order to reduce erroneous frame-based predictions. Our overall system achieves an Area Under the Receiver Operating Characteristics curve of 95.3% for detecting laughters and 90.4% for fillers on the test set drawn from the data specifications of the Interspeech 2013 Social Signals Sub-challenge. We perform further analysis to understand the interrelation between the features and obtained results. Specifically, we conduct a feature sensitivity analysis and correlate it with each feature's stand alone performance. The observations suggest that the trained system is more sensitive to a feature carrying higher discriminability with implications towards a better system design.

  15. Detecting paralinguistic events in audio stream using context in features and probabilistic decisions☆

    Science.gov (United States)

    Gupta, Rahul; Audhkhasi, Kartik; Lee, Sungbok; Narayanan, Shrikanth

    2017-01-01

    Non-verbal communication involves encoding, transmission and decoding of non-lexical cues and is realized using vocal (e.g. prosody) or visual (e.g. gaze, body language) channels during conversation. These cues perform the function of maintaining conversational flow, expressing emotions, and marking personality and interpersonal attitude. In particular, non-verbal cues in speech such as paralanguage and non-verbal vocal events (e.g. laughters, sighs, cries) are used to nuance meaning and convey emotions, mood and attitude. For instance, laughters are associated with affective expressions while fillers (e.g. um, ah, um) are used to hold floor during a conversation. In this paper we present an automatic non-verbal vocal events detection system focusing on the detect of laughter and fillers. We extend our system presented during Interspeech 2013 Social Signals Sub-challenge (that was the winning entry in the challenge) for frame-wise event detection and test several schemes for incorporating local context during detection. Specifically, we incorporate context at two separate levels in our system: (i) the raw frame-wise features and, (ii) the output decisions. Furthermore, our system processes the output probabilities based on a few heuristic rules in order to reduce erroneous frame-based predictions. Our overall system achieves an Area Under the Receiver Operating Characteristics curve of 95.3% for detecting laughters and 90.4% for fillers on the test set drawn from the data specifications of the Interspeech 2013 Social Signals Sub-challenge. We perform further analysis to understand the interrelation between the features and obtained results. Specifically, we conduct a feature sensitivity analysis and correlate it with each feature's stand alone performance. The observations suggest that the trained system is more sensitive to a feature carrying higher discriminability with implications towards a better system design. PMID:28713197

  16. Digital disease detection: A systematic review of event-based internet biosurveillance systems.

    Science.gov (United States)

    O'Shea, Jesse

    2017-05-01

    Internet access and usage has changed how people seek and report health information. Meanwhile,infectious diseases continue to threaten humanity. The analysis of Big Data, or vast digital data, presents an opportunity to improve disease surveillance and epidemic intelligence. Epidemic intelligence contains two components: indicator based and event-based. A relatively new surveillance type has emerged called event-based Internet biosurveillance systems. These systems use information on events impacting health from Internet sources, such as social media or news aggregates. These systems circumvent the limitations of traditional reporting systems by being inexpensive, transparent, and flexible. Yet, innovations and the functionality of these systems can change rapidly. To update the current state of knowledge on event-based Internet biosurveillance systems by identifying all systems, including current functionality, with hopes to aid decision makers with whether to incorporate new methods into comprehensive programmes of surveillance. A systematic review was performed through PubMed, Scopus, and Google Scholar databases, while also including grey literature and other publication types. 50 event-based Internet systems were identified, including an extraction of 15 attributes for each system, described in 99 articles. Each system uses different innovative technology and data sources to gather data, process, and disseminate data to detect infectious disease outbreaks. The review emphasises the importance of using both formal and informal sources for timely and accurate infectious disease outbreak surveillance, cataloguing all event-based Internet biosurveillance systems. By doing so, future researchers will be able to use this review as a library for referencing systems, with hopes of learning, building, and expanding Internet-based surveillance systems. Event-based Internet biosurveillance should act as an extension of traditional systems, to be utilised as an

  17. Final Scientific Report, Integrated Seismic Event Detection and Location by Advanced Array Processing

    Energy Technology Data Exchange (ETDEWEB)

    Kvaerna, T.; Gibbons. S.J.; Ringdal, F; Harris, D.B.

    2007-01-30

    In the field of nuclear explosion monitoring, it has become a priority to detect, locate, and identify seismic events down to increasingly small magnitudes. The consideration of smaller seismic events has implications for a reliable monitoring regime. Firstly, the number of events to be considered increases greatly; an exponential increase in naturally occurring seismicity is compounded by large numbers of seismic signals generated by human activity. Secondly, the signals from smaller events become more difficult to detect above the background noise and estimates of parameters required for locating the events may be subject to greater errors. Thirdly, events are likely to be observed by a far smaller number of seismic stations, and the reliability of event detection and location using a very limited set of observations needs to be quantified. For many key seismic stations, detection lists may be dominated by signals from routine industrial explosions which should be ascribed, automatically and with a high level of confidence, to known sources. This means that expensive analyst time is not spent locating routine events from repeating seismic sources and that events from unknown sources, which could be of concern in an explosion monitoring context, are more easily identified and can be examined with due care. We have obtained extensive lists of confirmed seismic events from mining and other artificial sources which have provided an excellent opportunity to assess the quality of existing fully-automatic event bulletins and to guide the development of new techniques for online seismic processing. Comparing the times and locations of confirmed events from sources in Fennoscandia and NW Russia with the corresponding time and location estimates reported in existing automatic bulletins has revealed substantial mislocation errors which preclude a confident association of detected signals with known industrial sources. The causes of the errors are well understood and are

  18. Event Detection Intelligent Camera: Demonstration of flexible, real-time data taking and processing

    Energy Technology Data Exchange (ETDEWEB)

    Szabolics, Tamás, E-mail: szabolics.tamas@wigner.mta.hu; Cseh, Gábor; Kocsis, Gábor; Szepesi, Tamás; Zoletnik, Sándor

    2015-10-15

    Highlights: • We present EDICAM's operation principles description. • Firmware tests results. • Software test results. • Further developments. - Abstract: An innovative fast camera (EDICAM – Event Detection Intelligent CAMera) was developed by MTA Wigner RCP in the last few years. This new concept was designed for intelligent event driven processing to be able to detect predefined events and track objects in the plasma. The camera provides a moderate frame rate of 400 Hz at full frame resolution (1280 × 1024), and readout of smaller region of interests can be done in the 1–140 kHz range even during exposure of the full image. One of the most important advantages of this hardware is a 10 Gbit/s optical link which ensures very fast communication and data transfer between the PC and the camera, enabling two level of processing: primitive algorithms in the camera hardware and high-level processing in the PC. This camera hardware has successfully proven to be able to monitoring the plasma in several fusion devices for example at ASDEX Upgrade, KSTAR and COMPASS with the first version of firmware. A new firmware and software package is under development. It allows to detect predefined events in real time and therefore the camera is capable to change its own operation or to give warnings e.g. to the safety system of the experiment. The EDICAM system can handle a huge amount of data (up to TBs) with high data rate (950 MB/s) and will be used as the central element of the 10 camera overview video diagnostic system of Wendenstein 7-X (W7-X) stellarator. This paper presents key elements of the newly developed built-in intelligence stressing the revolutionary new features and the results of the test of the different software elements.

  19. Detection of short-term slow slip events along the Nankai Trough via groundwater observations

    Science.gov (United States)

    Kitagawa, Yuichi; Koizumi, Naoji

    2013-12-01

    order to develop new tools or techniques to detect short-term slow slip events (S-SSEs) along subduction zones, we attempted to detect S-SSEs by conducting groundwater pressure observations. At ANO station, which is a groundwater observation station operated by the Geological Survey of Japan, the National Institute of Advanced Industrial Science and Technology, for earthquake prediction research, groundwater pressures changed due to six S-SSEs that occurred near ANO from June 2011 to April in 2013. The fault models of these S-SSEs, which were estimated mainly by observing the crustal strains and tilts, explained the changes in the groundwater pressures. If the strain sensitivity of the observed groundwater pressure or level is larger than 1 mm/nstrain and the noise level is smaller than 50 mm/day, it is possible to detect S-SSEs that occur in southwest Japan by conducting groundwater pressure or level observations.

  20. Multiscale vision model for event detection and reconstruction in two-photon imaging data

    DEFF Research Database (Denmark)

    Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke

    2014-01-01

    on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities.......Reliable detection of calcium waves in multiphoton imaging data is challenging because of the low signal-to-noise ratio and because of the unpredictability of the time and location of these spontaneous events. This paper describes our approach to calcium wave detection and reconstruction based...

  1. High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

    Science.gov (United States)

    Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

    2010-11-13

    Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates.

  2. DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

    Science.gov (United States)

    2013-04-24

    newborn infants [5] as well as the monitoring of fatigue in prolonged driving simulations [6]. In many of these settings, the experiments may last...and duration could be used to monitor subject performance during the task, as these features have been linked to drowsiness and fatigue [3]. Deviations...Shyh Lin, Shao-Hang Hung, Chih-Feng Chao, et al. (2010) A Real-Time Wireless Brain-Computer Interface System for Drowsiness Detection. IEEE Transactions

  3. Event Detection Using Mobile Phone Mass GPS Data and Their Reliavility Verification by Dmsp/ols Night Light Image

    Science.gov (United States)

    Yuki, Akiyama; Satoshi, Ueyama; Ryosuke, Shibasaki; Adachi, Ryuichiro

    2016-06-01

    In this study, we developed a method to detect sudden population concentration on a certain day and area, that is, an "Event," all over Japan in 2012 using mass GPS data provided from mobile phone users. First, stay locations of all phone users were detected using existing methods. Second, areas and days where Events occurred were detected by aggregation of mass stay locations into 1-km-square grid polygons. Finally, the proposed method could detect Events with an especially large number of visitors in the year by removing the influences of Events that occurred continuously throughout the year. In addition, we demonstrated reasonable reliability of the proposed Event detection method by comparing the results of Event detection with light intensities obtained from the night light images from the DMSP/OLS night light images. Our method can detect not only positive events such as festivals but also negative events such as natural disasters and road accidents. These results are expected to support policy development of urban planning, disaster prevention, and transportation management.

  4. [Detection of adverse events in hospitalized adult patients by using the Global Trigger Tool method].

    Science.gov (United States)

    Guzmán-Ruiz, O; Ruiz-López, P; Gómez-Cámara, A; Ramírez-Martín, M

    2015-01-01

    To identify and characterize adverse events (AE) in an Internal Medicine Department of a district hospital using an extension of the Global Trigger Tool (GTT), analyzing the diagnostic validity of the tool. An observational, analytical, descriptive and retrospective study was conducted on 2013 clinical charts from an Internal Medicine Department in order to detect EA through the identification of 'triggers' (an event often related to an AE). The 'triggers' and AE were located by systematic review of clinical documentation. The AE were characterized after they were identified. A total of 149 AE were detected in 291 clinical charts during 2013, of which 75.3% were detected directly by the tool, while the rest were not associated with a trigger. The percentage of charts that had at least one AE was 35.4%. The most frequent AE found was pressure ulcer (12%), followed by delirium, constipation, nosocomial respiratory infection and altered level of consciousness by drugs. Almost half (47.6%) of the AE were related to drug use, and 32.2% of all AE were considered preventable. The tool demonstrated a sensitivity of 91.3% (95%CI: 88.9-93.2) and a specificity of 32.5% (95%CI: 29.9-35.1). It had a positive predictive value of 42.5% (95%CI: 40.1-45.1) and a negative predictive value of 87.1% (95%CI: 83.8-89.9). The tool used in this study is valid, useful and reproducible for the detection of AE. It also serves to determine rates of injury and to observe their progression over time. A high frequency of both AE and preventable events were observed in this study. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

  5. Clinical outcome of subchromosomal events detected by whole‐genome noninvasive prenatal testing

    Science.gov (United States)

    Helgeson, J.; Wardrop, J.; Boomer, T.; Almasri, E.; Paxton, W. B.; Saldivar, J. S.; Dharajiya, N.; Monroe, T. J.; Farkas, D. H.; Grosu, D. S.

    2015-01-01

    Abstract Objective A novel algorithm to identify fetal microdeletion events in maternal plasma has been developed and used in clinical laboratory‐based noninvasive prenatal testing. We used this approach to identify the subchromosomal events 5pdel, 22q11del, 15qdel, 1p36del, 4pdel, 11qdel, and 8qdel in routine testing. We describe the clinical outcomes of those samples identified with these subchromosomal events. Methods Blood samples from high‐risk pregnant women submitted for noninvasive prenatal testing were analyzed using low coverage whole genome massively parallel sequencing. Sequencing data were analyzed using a novel algorithm to detect trisomies and microdeletions. Results In testing 175 393 samples, 55 subchromosomal deletions were reported. The overall positive predictive value for each subchromosomal aberration ranged from 60% to 100% for cases with diagnostic and clinical follow‐up information. The total false positive rate was 0.0017% for confirmed false positives results; false negative rate and sensitivity were not conclusively determined. Conclusion Noninvasive testing can be expanded into the detection of subchromosomal copy number variations, while maintaining overall high test specificity. In the current setting, our results demonstrate high positive predictive values for testing of rare subchromosomal deletions. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd. PMID:26088833

  6. Graph clustering for weapon discharge event detection and tracking in infrared imagery using deep features

    Science.gov (United States)

    Bhattacharjee, Sreyasee Das; Talukder, Ashit

    2017-05-01

    This paper addresses the problem of detecting and tracking weapon discharge event in an Infrared Imagery collection. While most of the prior work in related domains exploits the vast amount of complementary in- formation available from both visible-band (EO) and Infrared (IR) image (or video sequences), we handle the problem of recognizing human pose and activity detection exclusively in thermal (IR) images or videos. The task is primarily two-fold: 1) locating the individual in the scene from IR imagery, and 2) identifying the correct pose of the human individual (i.e. presence or absence of weapon discharge activity or intent). An efficient graph-based shortlisting strategy for identifying candidate regions of interest in the IR image utilizes both image saliency and mutual similarities from the initial list of the top scored proposals of a given query frame, which ensures an improved performance for both detection and recognition simultaneously and reduced false alarms. The proposed search strategy offers an efficient feature extraction scheme that can capture the maximum amount of object structural information by defining a region- based deep shape descriptor representing each object of interest present in the scene. Therefore, our solution is capable of handling the fundamental incompleteness of the IR imageries for which the conventional deep features optimized on the natural color images in Imagenet are not quite suitable. Our preliminary experiments on the OSU weapon dataset demonstrates significant success in automated recognition of weapon discharge events from IR imagery.

  7. Detection of genetically modified maize events in Brazilian maize-derived food products

    Directory of Open Access Journals (Sweden)

    Maria Regina Branquinho

    2013-09-01

    Full Text Available The Brazilian government has approved many transgenic maize lines for commercialization and has established a threshold of 1% for food labeling, which underscores need for monitoring programs. Thirty four samples including flours and different types of nacho chips were analyzed by conventional and real-time PCR in 2011 and 2012. The events MON810, Bt11, and TC1507 were detected in most of the samples, and NK603 was present only in the samples analyzed in 2012. The authorized lines GA21, T25, and the unauthorized Bt176 were not detected. All positive samples in the qualitative tests collected in 2011 showed a transgenic content higher than 1%, and none of them was correctly labeled. Regarding the samples collected in 2012, all positive samples were quantified higher than the threshold, and 47.0% were not correctly labeled. The overall results indicated that the major genetically modified organisms detected were MON810, TC1507, Bt11, and NK603 events. Some industries that had failed to label their products in 2011 started labeling them in 2012, demonstrating compliance with the current legislation observing the consumer rights. Although these results are encouraging, it has been clearly demonstrated the need for continuous monitoring programs to ensure consumers that food products are labeled properly.

  8. Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

    Science.gov (United States)

    Albayrak, Arif; Teng, William

    2015-01-01

    As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

  9. Detection and Separation of Speech Event Using Audio and Video Information Fusion and Its Application to Robust Speech Interface

    Directory of Open Access Journals (Sweden)

    Futoshi Asano

    2004-09-01

    Full Text Available A method of detecting speech events in a multiple-sound-source condition using audio and video information is proposed. For detecting speech events, sound localization using a microphone array and human tracking by stereo vision is combined by a Bayesian network. From the inference results of the Bayesian network, information on the time and location of speech events can be known. The information on the detected speech events is then utilized in the robust speech interface. A maximum likelihood adaptive beamformer is employed as a preprocessor of the speech recognizer to separate the speech signal from environmental noise. The coefficients of the beamformer are kept updated based on the information of the speech events. The information on the speech events is also used by the speech recognizer for extracting the speech segment.

  10. Advanced Clinical Decision Support for Vaccine Adverse Event Detection and Reporting.

    Science.gov (United States)

    Baker, Meghan A; Kaelber, David C; Bar-Shain, David S; Moro, Pedro L; Zambarano, Bob; Mazza, Megan; Garcia, Crystal; Henry, Adam; Platt, Richard; Klompas, Michael

    2015-09-15

    Reporting of adverse events (AEs) following vaccination can help identify rare or unexpected complications of immunizations and aid in characterizing potential vaccine safety signals. We developed an open-source, generalizable clinical decision support system called Electronic Support for Public Health-Vaccine Adverse Event Reporting System (ESP-VAERS) to assist clinicians with AE detection and reporting. ESP-VAERS monitors patients' electronic health records for new diagnoses, changes in laboratory values, and new allergies following vaccinations. When suggestive events are found, ESP-VAERS sends the patient's clinician a secure electronic message with an invitation to affirm or refute the message, add comments, and submit an automated, prepopulated electronic report to VAERS. High-probability AEs are reported automatically if the clinician does not respond. We implemented ESP-VAERS in December 2012 throughout the MetroHealth System, an integrated healthcare system in Ohio. We queried the VAERS database to determine MetroHealth's baseline reporting rates from January 2009 to March 2012 and then assessed changes in reporting rates with ESP-VAERS. In the 8 months following implementation, 91 622 vaccinations were given. ESP-VAERS sent 1385 messages to responsible clinicians describing potential AEs. Clinicians opened 1304 (94.2%) messages, responded to 209 (15.1%), and confirmed 16 for transmission to VAERS. An additional 16 high-probability AEs were sent automatically. Reported events included seizure, pleural effusion, and lymphocytopenia. The odds of a VAERS report submission during the implementation period were 30.2 (95% confidence interval, 9.52-95.5) times greater than the odds during the comparable preimplementation period. An open-source, electronic health record-based clinical decision support system can increase AE detection and reporting rates in VAERS. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society

  11. Detection of transgenic events in maize using immunochromatographic strip test and conventional PCR

    Directory of Open Access Journals (Sweden)

    Narjara Fonseca Cantelmo

    2013-10-01

    Full Text Available With the growth in the transgenic market, fast and economically viable methodologies are necessary for undertaking transgene detection tests, both for identification of contamination in seeds and in grain. Seeds from commercial conventional GNZ 2004, and transgenic VT-Pro (MON89034, Roundup Ready (NK603 and Herculex (TC1507 maize cultivars were used. In order to simulate different levels of contamination, the transgenic seeds were mixed with conventional seeds at levels of 0.2%, 0.4%, 1.0% and 1.6% for VT-Pro, and 0.2%, 0.5%, 0.8% and 1.2% for Roundup Ready and Herculex. The lateral flow membrane strip test was performed in the whole seed, endosperm and embryo. For evaluation of the specificity of the technique in detection of the TC1507 event by means of the conventional PCR technique, seeds of the commercial maize hybrid GNZ 2004 were used as negative control, and the maize hybrid 2B655Hx as positive control. In order to simulate different levels of contamination, transgenic seeds were mixed with conventional seeds at the levels of 10%, 5%, 1%, 0.5% and 0.1%. Seeds from each sample were crushed, and then DNA extraction was performed by the CTAB 2% method. Using the immunochromatographic strip, it was possible to evaluate the expression of proteins related to the VT-Pro, Roundup Ready and Herculex events when whole seeds were used at the 0.2% level of contamination, whereas by the conventional PCR technique, it was possible to detect the TC1507 event in samples with 1% contamination.

  12. Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.

    Directory of Open Access Journals (Sweden)

    Andrew Cron

    Full Text Available Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less. Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing enrichment, and the ability to align cell subsets across multiple data samples for comparative analysis. In this manuscript, we develop hierarchical modeling extensions to the Dirichlet Process Gaussian Mixture Model (DPGMM approach we have previously described for cell subset identification, and show that the hierarchical DPGMM (HDPGMM naturally generates an aligned data model that captures both commonalities and variations across multiple samples. HDPGMM also increases the sensitivity to extremely low frequency events by sharing information across multiple samples analyzed simultaneously. We validate the accuracy and reproducibility of HDPGMM estimates of antigen-specific T cells on clinically relevant reference peripheral blood mononuclear cell (PBMC samples with known frequencies of antigen-specific T cells. These cell samples take advantage of retrovirally TCR-transduced T cells spiked into autologous PBMC samples to give a defined number of antigen-specific T cells detectable by HLA-peptide multimer binding. We provide open source software that can take advantage of both multiple processors and GPU-acceleration to perform the numerically-demanding computations. We show that hierarchical modeling is a useful probabilistic approach that can provide a

  13. Analysis of arrhythmic events is useful to detect lead failure earlier in patients followed by remote monitoring.

    Science.gov (United States)

    Nishii, Nobuhiro; Miyoshi, Akihito; Kubo, Motoki; Miyamoto, Masakazu; Morimoto, Yoshimasa; Kawada, Satoshi; Nakagawa, Koji; Watanabe, Atsuyuki; Nakamura, Kazufumi; Morita, Hiroshi; Ito, Hiroshi

    2017-12-01

    Remote monitoring (RM) has been advocated as the new standard of care for patients with cardiovascular implantable electronic devices (CIEDs). RM has allowed the early detection of adverse clinical events, such as arrhythmia, lead failure, and battery depletion. However, lead failure was often identified only by arrhythmic events, but not impedance abnormalities. To compare the usefulness of arrhythmic events with conventional impedance abnormalities for identifying lead failure in CIED patients followed by RM. CIED patients in 12 hospitals have been followed by the RM center in Okayama University Hospital. All transmitted data have been analyzed and summarized. From April 2009 to March 2016, 1,873 patients have been followed by the RM center. During the mean follow-up period of 775 days, 42 lead failure events (atrial lead 22, right ventricular pacemaker lead 5, implantable cardioverter defibrillator [ICD] lead 15) were detected. The proportion of lead failures detected only by arrhythmic events, which were not detected by conventional impedance abnormalities, was significantly higher than that detected by impedance abnormalities (arrhythmic event 76.2%, 95% CI: 60.5-87.9%; impedance abnormalities 23.8%, 95% CI: 12.1-39.5%). Twenty-seven events (64.7%) were detected without any alert. Of 15 patients with ICD lead failure, none has experienced inappropriate therapy. RM can detect lead failure earlier, before clinical adverse events. However, CIEDs often diagnose lead failure as just arrhythmic events without any warning. Thus, to detect lead failure earlier, careful human analysis of arrhythmic events is useful. © 2017 Wiley Periodicals, Inc.

  14. Improving Infrasound Signal Detection and Event Location in the Western US Using Atmospheric Modeling

    Science.gov (United States)

    Dannemann, F. K.; Park, J.; Marcillo, O. E.; Blom, P. S.; Stump, B. W.; Hayward, C.

    2016-12-01

    Data from five infrasound arrays in the western US jointly operated by University of Utah Seismograph Station and Southern Methodist University are used to test a database-centric processing pipeline, InfraPy, for automated event detection, association and location. Infrasonic array data from a one-year time period (January 1 2012 to December 31 2012) are used. This study focuses on the identification and location of 53 ground-truth verified events produced from near surface military explosions at the Utah Test and Training Range (UTTR). Signals are detected using an adaptive F-detector, which accounts for correlated and uncorrelated time-varying noise in order to reduce false detections due to the presence of coherent noise. Variations in detection azimuth and correlation are found to be consistent with seasonal changes in atmospheric winds. The Bayesian infrasonic source location (BISL) method is used to produce source location and time credibility contours based on posterior probability density functions. Updates to the previous BISL methodology include the application of celerity range and azimuth deviation distributions in order to accurately account for the spatial and temporal variability of infrasound propagation through the atmosphere. These priors are estimated by ray tracing through Ground-to-Space (G2S) atmospheric models as a function of season and time of day using historic atmospheric characterizations from 2007 to 2013. Out of the 53 events, 31 are successfully located using the InfraPy pipeline. Confidence contour areas for maximum a posteriori event locations produce error estimates which are reduced a maximum of 98% and an average of 25% from location estimates utilizing a simple time independent uniform atmosphere. We compare real-time ray tracing results with the statistical atmospheric priors used in this study to examine large time differences between known origin times and estimated origin times that might be due to the misidentification of

  15. Gait event detection on level ground and incline walking using a rate gyroscope.

    Science.gov (United States)

    Catalfamo, Paola; Ghoussayni, Salim; Ewins, David

    2010-01-01

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. Accurate determination of the Initial Contact of the foot with the floor (IC) and the final contact or Foot Off (FO) on different terrains is important. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects walking outdoors on level ground, and up and down an incline. Performance was compared with a reference pressure measurement system. The mean difference between the gyroscope and the reference was less than -25 ms for IC and less than 75 ms for FO for all terrains. Detection success was over 98%. These results provide preliminary evidence supporting the use of the gyroscope for gait event detection on inclines as well as level walking.

  16. The ADE scorecards: a tool for adverse drug event detection in electronic health records.

    Science.gov (United States)

    Chazard, Emmanuel; Băceanu, Adrian; Ferret, Laurie; Ficheur, Grégoire

    2011-01-01

    Although several methods exist for Adverse Drug events (ADE) detection due to past hospitalizations, a tool that could display those ADEs to the physicians does not exist yet. This article presents the ADE Scorecards, a Web tool that enables to screen past hospitalizations extracted from Electronic Health Records (EHR), using a set of ADE detection rules, presently rules discovered by data mining. The tool enables the physicians to (1) get contextualized statistics about the ADEs that happen in their medical department, (2) see the rules that are useful in their department, i.e. the rules that could have enabled to prevent those ADEs and (3) review in detail the ADE cases, through a comprehensive interface displaying the diagnoses, procedures, lab results, administered drugs and anonymized records. The article shows a demonstration of the tool through a use case.

  17. Optimized Swinging Door Algorithm for Wind Power Ramp Event Detection: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Mingjian; Zhang, Jie; Florita, Anthony R.; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

    2015-08-06

    Significant wind power ramp events (WPREs) are those that influence the integration of wind power, and they are a concern to the continued reliable operation of the power grid. As wind power penetration has increased in recent years, so has the importance of wind power ramps. In this paper, an optimized swinging door algorithm (SDA) is developed to improve ramp detection performance. Wind power time series data are segmented by the original SDA, and then all significant ramps are detected and merged through a dynamic programming algorithm. An application of the optimized SDA is provided to ascertain the optimal parameter of the original SDA. Measured wind power data from the Electric Reliability Council of Texas (ERCOT) are used to evaluate the proposed optimized SDA.

  18. Single Event Upset Detection and Hardening schemes for CNTFET SRAM – A Review

    Directory of Open Access Journals (Sweden)

    T.R.Rajalakshmi

    2015-12-01

    Full Text Available Carbon nanotubes (CNT provide a better alternative of silicon, when it comes to nano scales. Thanks to its high stability and high performance of carbon nanotube, CNT based FET (CNTFET devices which are gaining popularity of late. Single Event Upset (SEU in a device is caused due to radiation. Radiation can be through two ways, one due to charge particles present in the atmosphere and other due to alpha particles. In this article we review some of the detection and hardening schemes in CMOS SRAM and make related simulations on CNTFET SRAM. The aim of this paper is to present the challenges the CNTFET SRAM is facing when the radiation effects are introduced. A full experimentation of all the schemes of detection and correction schemes will be beyond the scope, so only certain experiments that can be well carried out with CNTFET SRAM memory is more focussed.

  19. Endpoint Visual Detection of Three Genetically Modified Rice Events by Loop-Mediated Isothermal Amplification

    Directory of Open Access Journals (Sweden)

    Qing Zhu

    2012-11-01

    Full Text Available Genetically modified (GM rice KMD1, TT51-1, and KF6 are three of the most well known transgenic Bt rice lines in China. A rapid and sensitive molecular assay for risk assessment of GM rice is needed. Polymerase chain reaction (PCR, currently the most common method for detecting genetically modified organisms, requires temperature cycling and relatively complex procedures. Here we developed a visual and rapid loop-mediated isothermal amplification (LAMP method to amplify three GM rice event-specific junction sequences. Target DNA was amplified and visualized by two indicators (SYBR green or hydroxy naphthol blue [HNB] within 60 min at an isothermal temperature of 63 °C. Different kinds of plants were selected to ensure the specificity of detection and the results of the non-target samples were negative, indicating that the primer sets for the three GM rice varieties had good levels of specificity. The sensitivity of LAMP, with detection limits at low concentration levels (0.01%–0.005% GM, was 10- to 100-fold greater than that of conventional PCR. Additionally, the LAMP assay coupled with an indicator (SYBR green or HNB facilitated analysis. These findings revealed that the rapid detection method was suitable as a simple field-based test to determine the status of GM crops.

  20. Event-related potential measures of gap detection threshold during natural sleep.

    Science.gov (United States)

    Muller-Gass, Alexandra; Campbell, Kenneth

    2014-08-01

    The minimum time interval between two stimuli that can be reliably detected is called the gap detection threshold. The present study examines whether an unconscious state, natural sleep affects the gap detection threshold. Event-related potentials were recorded in 10 young adults while awake and during all-night sleep to provide an objective estimate of this threshold. These subjects were presented with 2, 4, 8 or 16ms gaps occurring in 1.5 duration white noise. During wakefulness, a significant N1 was elicited for the 8 and 16ms gaps. N1 was difficult to observe during stage N2 sleep, even for the longest gap. A large P2 was however elicited and was significant for the 8 and 16ms gaps. Also, a later, very large N350 was elicited by the 16ms gap. An N1 and P2 was significant only for the 16ms gap during REM sleep. ERPs to gaps occurring in noise segments can therefore be successfully elicited during natural sleep. The gap detection threshold is similar in the waking and sleeping states. Crown Copyright © 2014. Published by Elsevier Ireland Ltd. All rights reserved.

  1. Automated off-line respiratory event detection for the study of postoperative apnea in infants.

    Science.gov (United States)

    Aoude, Ahmed A; Kearney, Robert E; Brown, Karen A; Galiana, Henrietta L; Robles-Rubio, Carlos A

    2011-06-01

    Previously, we presented automated methods for thoraco-abdominal asynchrony estimation and movement artifact detection in respiratory inductance plethysmography (RIP) signals. This paper combines and improves these methods to give a method for the automated, off-line detection of pause, movement artifact, and asynchrony. Simulation studies demonstrated that the new combined method is accurate and robust in the presence of noise. The new procedure was successfully applied to cardiorespiratory signals acquired postoperatively from infants in the recovery room. A comparison of the events detected with the automated method to those visually scored by an expert clinician demonstrated a higher agreement (κ = 0.52) than that amongst several human scorers (κ = 0.31) in a clinical study . The method provides the following advantages: first, it is fully automated; second, it is more efficient than visual scoring; third, the analysis is repeatable and standardized; fourth, it provides greater agreement with an expert scorer compared to the agreement between trained scorers; fifth, it is amenable to online detection; and lastly, it is applicable to uncalibrated RIP signals. Examples of applications include respiratory monitoring of postsurgical patients and sleep studies.

  2. A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    ZiQi Hao

    2015-01-01

    Full Text Available As limited energy is one of the tough challenges in wireless sensor networks (WSN, energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We use k-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.

  3. Abnormal event detection in crowded scenes using two sparse dictionaries with saliency

    Science.gov (United States)

    Yu, Yaping; Shen, Wei; Huang, He; Zhang, Zhijiang

    2017-05-01

    Abnormal event detection in crowded scenes is a challenging problem due to the high density of the crowds and the occlusions between individuals. We propose a method using two sparse dictionaries with saliency to detect abnormal events in crowded scenes. By combining a multiscale histogram of optical flow (MHOF) and a multiscale histogram of oriented gradient (MHOG) into a multiscale histogram of optical flow and gradient, we are able to represent the feature of a spatial-temporal cuboid without separating the individuals in the crowd. While MHOF captures the temporal information, MHOG encodes both spatial and temporal information. The combination of these two features is able to represent the cuboid's appearance and motion characteristics even when the density of the crowds becomes high. An abnormal dictionary is added to the traditional sparse model with only a normal dictionary included. In addition, the saliency of the testing sample is combined with two sparse reconstruction costs on the normal and abnormal dictionary to measure the normalness of the testing sample. The experiment results show the effectiveness of our method.

  4. Pinda: a web service for detection and analysis of intraspecies gene duplication events.

    Science.gov (United States)

    Kontopoulos, Dimitrios-Georgios; Glykos, Nicholas M

    2013-09-01

    We present Pinda, a Web service for the detection and analysis of possible duplications of a given protein or DNA sequence within a source species. Pinda fully automates the whole gene duplication detection procedure, from performing the initial similarity searches, to generating the multiple sequence alignments and the corresponding phylogenetic trees, to bootstrapping the trees and producing a Z-score-based list of duplication candidates for the input sequence. Pinda has been cross-validated using an extensive set of known and bibliographically characterized duplication events. The service facilitates the automatic and dependable identification of gene duplication events, using some of the most successful bioinformatics software to perform an extensive analysis protocol. Pinda will prove of use for the analysis of newly discovered genes and proteins, thus also assisting the study of recently sequenced genomes. The service's location is http://orion.mbg.duth.gr/Pinda. The source code is freely available via https://github.com/dgkontopoulos/Pinda/. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  5. Detecting regular sound changes in linguistics as events of concerted evolution.

    Science.gov (United States)

    Hruschka, Daniel J; Branford, Simon; Smith, Eric D; Wilkins, Jon; Meade, Andrew; Pagel, Mark; Bhattacharya, Tanmoy

    2015-01-05

    Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Detection of ULF geomagnetic signals associated with seismic events in Central Mexico using Discrete Wavelet Transform

    Directory of Open Access Journals (Sweden)

    O. Chavez

    2010-12-01

    Full Text Available The geomagnetic observatory of Juriquilla Mexico, located at longitude –100.45° and latitude 20.70°, and 1946 m a.s.l., has been operational since June 2004 compiling geomagnetic field measurements with a three component fluxgate magnetometer. In this paper, the results of the analysis of these measurements in relation to important seismic activity in the period of 2007 to 2009 are presented. For this purpose, we used superposed epochs of Discrete Wavelet Transform of filtered signals for the three components of the geomagnetic field during relative seismic calm, and it was compared with seismic events of magnitudes greater than Ms > 5.5, which have occurred in Mexico. The analysed epochs consisted of 18 h of observations for a dataset corresponding to 18 different earthquakes (EQs. The time series were processed for a period of 9 h prior to and 9 h after each seismic event. This data processing was compared with the same number of observations during a seismic calm. The proposed methodology proved to be an efficient tool to detect signals associated with seismic activity, especially when the seismic events occur in a distance (D from the observatory to the EQ, such that the ratio D/ρ < 1.8 where ρ is the earthquake radius preparation zone. The methodology presented herein shows important anomalies in the Ultra Low Frequency Range (ULF; 0.005–1 Hz, primarily for 0.25 to 0.5 Hz. Furthermore, the time variance (σ2 increases prior to, during and after the seismic event in relation to the coefficient D1 obtained, principally in the Bx (N-S and By (E-W geomagnetic components. Therefore, this paper proposes and develops a new methodology to extract the abnormal signals of the geomagnetic anomalies related to different stages of the EQs.

  7. Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

    Directory of Open Access Journals (Sweden)

    Rodrigo Tavares Silva

    2015-11-01

    Full Text Available AbstractBackground:The recording of arrhythmic events (AE in renal transplant candidates (RTCs undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used.Objective:We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR.Methods:A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE.Results:During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002, and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001 were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041.Conclusions:In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT.

  8. Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Rodrigo Tavares; Martinelli Filho, Martino, E-mail: martino@cardiol.br; Peixoto, Giselle de Lima; Lima, José Jayme Galvão de; Siqueira, Sérgio Freitas de; Costa, Roberto; Gowdak, Luís Henrique Wolff [Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil); Paula, Flávio Jota de [Unidade de Transplante Renal - Divisão de Urologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil); Kalil Filho, Roberto; Ramires, José Antônio Franchini [Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil)

    2015-11-15

    The recording of arrhythmic events (AE) in renal transplant candidates (RTCs) undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used. We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR). A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE. During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT) occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002), and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001) were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD) was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041). In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT.

  9. Trimpi occurrence and geomagnetic activity: Analysis of events detected at Comandante Ferraz Brazilian Antarctic Station (L=2.25)

    OpenAIRE

    Fernandez, JH; Piazza, LR; Kaufmann, P

    2003-01-01

    [1] We present an analysis of the occurrence of Trimpi events observed at Comandante Ferraz Brazilian Antarctic Station (EACF), at L = 2.25, as observed by the amplitude of very low frequency (VLF) signals transmitted from Hawaii (NPM 21.4 kHz) from April 1996 to August 1999. The event parameters ( total duration, amplitude variation, time incidence, and type ( negative or positive)) were analyzed for 4394 events detected in the first year ( solar minimum and relatively low Trimpi activity). ...

  10. Detection Probability of Trends in Rare Events: Theory and Application to Heavy Precipitation in the Alpine Region.

    Science.gov (United States)

    Frei, Christoph; Schär, Christoph

    2001-04-01

    A statistical framework is presented for the assessment of climatological trends in the frequency of rare and extreme weather events. The methodology applies to long-term records of event counts and is based on the stochastic concept of binomial distributed counts. It embraces logistic regression for trend estimation and testing, and includes a quantification of the potential/limitation to discriminate a trend from the stochastic fluctuations in a record. This potential is expressed in terms of a detection probability, which is calculated from Monte Carlo-simulated surrogate records, and determined as a function of the record length, the magnitude of the trend and the average return period (i.e., the rarity) of events.Calculations of the detection probability for daily events reveal a strong sensitivity upon the rarity of events:in a 100-yr record of seasonal counts, a frequency change by a factor of 1.5 can be detected with a probability of 0.6 for events with an average return period of 30 days; however, this value drops to 0.2 for events with a return period of 100 days. For moderately rare events the detection probability decreases rapidly with shorter record length, but it does not significantly increase with longer record length when very rare events are considered. The results demonstrate the difficulty to determine trends of very rare events, underpin the need for long period data for trend analyses, and point toward a careful interpretation of statistically nonsignificant trend results.The statistical method is applied to examine seasonal trends of heavy daily precipitation at 113 rain gauge stations in the Alpine region of Switzerland (1901-94). For intense events (return period: 30 days) a statistically significant frequency increase was found in winter and autumn for a high number of stations. For strong precipitation events (return period larger than 100 days), trends are mostly statistically nonsignificant, which does not necessarily imply the absence

  11. Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm.

    Science.gov (United States)

    Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

    2016-10-01

    Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.

  12. Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm

    Directory of Open Access Journals (Sweden)

    Hui Zhou

    2016-10-01

    Full Text Available Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO and heel strike (HS gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.

  13. Solar Power Ramp Events Detection Using an Optimized Swinging Door Algorithm: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Mingjian; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

    2015-08-07

    Solar power ramp events (SPREs) are those that significantly influence the integration of solar power on non-clear days and threaten the reliable and economic operation of power systems. Accurately extracting solar power ramps becomes more important with increasing levels of solar power penetrations in power systems. In this paper, we develop an optimized swinging door algorithm (OpSDA) to detection. First, the swinging door algorithm (SDA) is utilized to segregate measured solar power generation into consecutive segments in a piecewise linear fashion. Then we use a dynamic programming approach to combine adjacent segments into significant ramps when the decision thresholds are met. In addition, the expected SPREs occurring in clear-sky solar power conditions are removed. Measured solar power data from Tucson Electric Power is used to assess the performance of the proposed methodology. OpSDA is compared to two other ramp detection methods: the SDA and the L1-Ramp Detect with Sliding Window (L1-SW) method. The statistical results show the validity and effectiveness of the proposed method. OpSDA can significantly improve the performance of the SDA, and it can perform as well as or better than L1-SW with substantially less computation time.

  14. Ultra-Low Power Sensor System for Disaster Event Detection in Metro Tunnel Systems

    Directory of Open Access Journals (Sweden)

    Jonah VINCKE

    2017-05-01

    Full Text Available In this extended paper, the concept for an ultra-low power wireless sensor network (WSN for underground tunnel systems is presented highlighting the chosen sensors. Its objectives are the detection of emergency events either from natural disasters, such as flooding or fire, or from terrorist attacks using explosives. Earlier works have demonstrated that the power consumption for the communication can be reduced such that the data acquisition (i.e. sensor sub-system becomes the most significant energy consumer. By using ultra-low power components for the smoke detector, a hydrostatic pressure sensor for water ingress detection and a passive acoustic emission sensor for explosion detection, all considered threats are covered while the energy consumption can be kept very low in relation to the data acquisition. In addition to 1 the sensor system is integrated into a sensor board. The total average power consumption for operating the sensor sub-system is measured to be 35.9 µW for lower and 7.8 µW for upper nodes.

  15. Automatic Detection of Pitching and Throwing Events in Baseball With Inertial Measurement Sensors.

    Science.gov (United States)

    Murray, Nick B; Black, Georgia M; Whiteley, Rod J; Gahan, Peter; Cole, Michael H; Utting, Andy; Gabbett, Tim J

    2017-04-01

    Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit. Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts). The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%). These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology.

  16. Successful syllable detection in aphasia despite processing impairments as revealed by event-related potentials

    Directory of Open Access Journals (Sweden)

    Becker Frank

    2007-01-01

    Full Text Available Abstract Background The role of impaired sound and speech sound processing for auditory language comprehension deficits in aphasia is unclear. No electrophysiological studies of attended speech sound processing in aphasia have been performed for stimuli that are discriminable even for patients with severe auditory comprehension deficits. Methods Event-related brain potentials (ERPs were used to study speech sound processing in a syllable detection task in aphasia. In an oddball paradigm, the participants had to detect the infrequent target syllable /ta:/ amongst the frequent standard syllable /ba:/. 10 subjects with moderate and 10 subjects with severe auditory comprehension impairment were compared to 11 healthy controls. Results N1 amplitude was reduced indicating impaired primary stimulus analysis; N1 reduction was a predictor for auditory comprehension impairment. N2 attenuation suggests reduced attended stimulus classification and discrimination. However, all aphasic patients were able to discriminate the stimuli almost without errors, and processes related to the target identification (P3 were not significantly reduced. The aphasic subjects might have discriminated the stimuli by purely auditory differences, while the ERP results reveal a reduction of language-related processing which however did not prevent performing the task. Topographic differences between aphasic subgroups and controls indicate compensatory changes in activation. Conclusion Stimulus processing in early time windows (N1, N2 is altered in aphasics with adverse consequences for auditory comprehension of complex language material, while allowing performance of simpler tasks (syllable detection. Compensational patterns of speech sound processing may be activated in syllable detection, but may not be functional in more complex tasks. The degree to which compensational processes can be activated probably varies depending on factors as lesion site, time after injury, and

  17. First events from the CNGS neutrino beam detected in the OPERA experiment

    CERN Document Server

    Acquafredda, R.; Ambrosio, M.; Anokhina, A.; Aoki, S.; Ariga, A.; Arrabito, L.; Autiero, D.; Badertscher, A.; Bergnoli, A.; Bersani Greggio, F.; Besnier, M.; Beyer, M.; Bondil-Blin, S.; Borer, K.; Boucrot, J.; Boyarkin, V.; Bozza, C.; Brugnera, R.; Buontempo, S.; Caffari, Y.; Campagne, Jean-Eric; Carlus, B.; Carrara, E.; Cazes, A.; Chaussard, L.; Chernyavsky, M.; Chiarella, V.; Chon-Sen, N.; Chukanov, A.; Ciesielski, R.; Consiglio, L.; Cozzi, M.; Dal Corso, F.; D'Ambrosio, N.; Damet, J.; De Lellis, G.; Declais, Y.; Descombes, T.; De Serio, M.; Di Capua, F.; Di Ferdinando, D.; Di Giovanni, A.; Di Marco, N.; Di Troia, C.; Dmitrievski, S.; Dracos, M.; Duchesneau, D.; Dulach, B.; Dusini, S.; Ebert, J.; Enikeev, R.; Ereditato, A.; Esposito, L.S.; Fanin, C.; Favier, J.; Felici, G.; Ferber, T.; Fournier, L.; Franceschi, A.; Frekers, D.; Fukuda, T.; Fukushima, C.; Galkin, V.I.; Galkin, V.A.; Gallet, R.; Garfagnini, A.; Gaudiot, G.; Giacomelli, G.; Giarmana, O.; Giorgini, M.; Girard, L.; Girerd, C.; Goellnitz, C.; Goldberg, J.; Gornoushkin, Y.; Grella, G.; Grianti, F.; Guerin, C.; Guler, M.; Gustavino, C.; Hagner, C.; Hamane, T.; Hara, T.; Hauger, M.; Hess, M.; Hoshino, K.; Ieva, M.; Incurvati, M.; Jakovcic, K.; Janicsko Csathy, J.; Janutta, B.; Jollet, C.; Juget, F.; Kazuyama, M.; Kim, S.H.; Kimura, M.; Knuesel, J.; Kodama, K.; Kolev, D.; Komatsu, M.; Kose, U.; Krasnoperov, A.; Kreslo, I.; Krumstein, Z.; Laktineh, I.; de La Taille, C.; Le Flour, T.; Lieunard, S.; Ljubicic, A.; Longhin, A.; Malgin, A.; Manai, K.; Mandrioli, G.; Mantello, U.; Marotta, A.; Marteau, J.; Martin-Chassard, G.; Matveev, V.; Messina, M.; Meyer, L.; Micanovic, S.; Migliozzi, P.; Miyamoto, S.; Monacelli, Piero; Monteiro, I.; Morishima, K.; Moser, U.; Muciaccia, M.T.; Mugnier, P.; Naganawa, N.; Nakamura, M.; Nakano, T.; Napolitano, T.; Natsume, M.; Niwa, K.; Nonoyama, Y.; Nozdrin, A.; Ogawa, S.; Olchevski, A.; Orlandi, D.; Ossetski, D.; Paoloni, A.; Park, B.D.; Park, I.G.; Pastore, A.; Patrizii, L.; Pellegrino, L.; Pessard, H.; Pilipenko, V.; Pistillo, C.; Polukhina, N.; Pozzato, M.; Pretzl, K.; Publichenko, P.; Raux, L.; Repellin, J.P.; Roganova, T.; Romano, G.; Rosa, G.; Rubbia, A.; Ryasny, V.; Ryazhskaya, O.; Ryzhikov, D.; Sadovski, A.; Sanelli, C.; Sato, O.; Sato, Y.; Saveliev, V.; Savvinov, N.; Sazhina, G.; Schembri, A.; Schmidt Parzefall, W.; Schroeder, H.; Schutz, H.U.; Scotto Lavina, L.; Sewing, J.; Shibuya, H.; Simone, S.; Sioli, M.; Sirignano, C.; Sirri, G.; Song, J.S.; Spaeti, R.; Spinetti, M.; Stanco, L.; Starkov, N.; Stipcevic, M.; Strolin, Paolo Emilio; Sugonyaev, V.; Takahashi, S.; Tereschenko, V.; Terranova, F.; Tezuka, I.; Tioukov, V.; Tikhomirov, I.; Tolun, P.; Toshito, T.; Tsarev, V.; Tsenov, R.; Ugolino, U.; Ushida, N.; Van Beek, G.; Verguilov, V.; Vilain, P.; Votano, L.; Vuilleumier, J.L.; Waelchli, T.; Waldi, R.; Weber, M.; Wilquet, G.; Wonsak, B.; Wurth, R.; Wurtz, J.; Yakushev, V.; Yoon, C.S.; Zaitsev, Y.; Zamboni, I.; Zimmerman, R.

    2006-01-01

    The OPERA neutrino detector at the underground Gran Sasso Laboratory (LNGS) was designed to perform the first detection of neutrino oscillations in appearance mode, through the study of nu_mu to nu_tau oscillations. The apparatus consists of a lead/emulsion-film target complemented by electronic detectors. It is placed in the high-energy, long-baseline CERN to LNGS beam (CNGS) 730 km away from the neutrino source. In August 2006 a first run with CNGS neutrinos was successfully conducted. A first sample of neutrino events was collected, statistically consistent with the integrated beam intensity. After a brief description of the beam and of the various sub-detectors, we report on the achievement of this milestone, presenting the first data and some analysis results.

  18. The Event Detection and the Apparent Velocity Estimation Based on Computer Vision

    Science.gov (United States)

    Shimojo, M.

    2012-08-01

    The high spatial and time resolution data obtained by the telescopes aboard Hinode revealed the new interesting dynamics in solar atmosphere. In order to detect such events and estimate the velocity of dynamics automatically, we examined the estimation methods of the optical flow based on the OpenCV that is the computer vision library. We applied the methods to the prominence eruption observed by NoRH, and the polar X-ray jet observed by XRT. As a result, it is clear that the methods work well for solar images if the images are optimized for the methods. It indicates that the optical flow estimation methods in the OpenCV library are very useful to analyze the solar phenomena.

  19. Detection of events of public health importance under the international health regulations: a toolkit to improve reporting of unusual events by frontline healthcare workers.

    Science.gov (United States)

    MacDonald, Emily; Aavitsland, Preben; Bitar, Dounia; Borgen, Katrine

    2011-09-21

    The International Health Regulations (IHR (2005)) require countries to notify WHO of any event which may constitute a public health emergency of international concern. This notification relies on reports of events occurring at the local level reaching the national public health authorities. By June 2012 WHO member states are expected to have implemented the capacity to "detect events involving disease or death above expected levels for the particular time and place" on the local level and report essential information to the appropriate level of public health authority. Our objective was to develop tools to assist European countries improve the reporting of unusual events of public health significance from frontline healthcare workers to public health authorities. We investigated obstacles and incentives to event reporting through a systematic literature review and expert consultations with national public health officials from various European countries. Multi-day expert meetings and qualitative interviews were used to gather experiences and examples of public health event reporting. Feedback on specific components of the toolkit was collected from healthcare workers and public health officials throughout the design process. Evidence from 79 scientific publications, two multi-day expert meetings and seven qualitative interviews stressed the need to clarify concepts and expectations around event reporting in European countries between the frontline and public health authorities. An analytical framework based on three priority areas for improved event reporting (professional engagement, communication and infrastructure) was developed and guided the development of the various tools. We developed a toolkit adaptable to country-specific needs that includes a guidance document for IHR National Focal Points and nine tool templates targeted at clinicians and laboratory staff: five awareness campaign tools, three education and training tools, and an implementation plan. The

  20. KIWI: A technology for public health event monitoring and early warning signal detection.

    Science.gov (United States)

    Mukhi, Shamir N

    2016-01-01

    To introduce the Canadian Network for Public Health Intelligence's new Knowledge Integration using Web-based Intelligence (KIWI) technology, and to pefrom preliminary evaluation of the KIWI technology using a case study. The purpose of this new technology is to support surveillance activities by monitoring unstructured data sources for the early detection and awareness of potential public health threats. A prototype of the KIWI technology, adapted for zoonotic and emerging diseases, was piloted by end-users with expertise in the field of public health and zoonotic/emerging disease surveillance. The technology was assessed using variables such as geographic coverage, user participation, and others; categorized by high-level attributes from evaluation guidelines for internet based surveillance systems. Special attention was given to the evaluation of the system's automated sense-making algorithm, which used variables such as sensitivity, specificity, and predictive values. Event-based surveillance evaluation was not applied to its full capacity as such an evaluation is beyond the scope of this paper. KIWI was piloted with user participation = 85.0% and geographic coverage within monitored sources = 83.9% of countries. The pilots, which focused on zoonotic and emerging diseases, lasted a combined total of 65 days and resulted in the collection of 3243 individual information pieces (IIP) and 2 community reported events (CRE) for processing. Ten sources were monitored during the second phase of the pilot, which resulted in 545 anticipatory intelligence signals (AIS). KIWI's automated sense-making algorithm (SMA) had sensitivity = 63.9% (95% CI: 60.2-67.5%), specificity = 88.6% (95% CI: 87.3-89.8%), positive predictive value = 59.8% (95% CI: 56.1-63.4%), and negative predictive value = 90.3% (95% CI: 89.0-91.4%). Literature suggests the need for internet based monitoring and surveillance systems that are customizable, integrated into collaborative networks of public

  1. Head movement compensation and multi-modal event detection in eye-tracking data for unconstrained head movements.

    Science.gov (United States)

    Larsson, Linnéa; Schwaller, Andrea; Nyström, Marcus; Stridh, Martin

    2016-12-01

    The complexity of analyzing eye-tracking signals increases as eye-trackers become more mobile. The signals from a mobile eye-tracker are recorded in relation to the head coordinate system and when the head and body move, the recorded eye-tracking signal is influenced by these movements, which render the subsequent event detection difficult. The purpose of the present paper is to develop a method that performs robust event detection in signals recorded using a mobile eye-tracker. The proposed method performs compensation of head movements recorded using an inertial measurement unit and employs a multi-modal event detection algorithm. The event detection algorithm is based on the head compensated eye-tracking signal combined with information about detected objects extracted from the scene camera of the mobile eye-tracker. The method is evaluated when participants are seated 2.6m in front of a big screen, and is therefore only valid for distant targets. The proposed method for head compensation decreases the standard deviation during intervals of fixations from 8° to 3.3° for eye-tracking signals recorded during large head movements. The multi-modal event detection algorithm outperforms both an existing algorithm (I-VDT) and the built-in-algorithm of the mobile eye-tracker with an average balanced accuracy, calculated over all types of eye movements, of 0.90, compared to 0.85 and 0.75, respectively for the compared algorithms. The proposed event detector that combines head movement compensation and information regarding detected objects in the scene video enables for improved classification of events in mobile eye-tracking data. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Microseismic events enhancement and detection in sensor arrays using autocorrelation-based filtering

    Science.gov (United States)

    Liu, Entao; Zhu, Lijun; Govinda Raj, Anupama; McClellan, James H.; Al-Shuhail, Abdullatif; Kaka, SanLinn I.; Iqbal, Naveed

    2017-11-01

    Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time-delayed arrival from the event, we propose an autocorrelation-based stacking method that designs a denoising filter from all the traces, as well as a multi-channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centered at zero in the lag domain. The effect of white noise is concentrated near zero lag, so the filter design requires a predictable adjustment of the zero-lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with colored noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces.

  3. Fully Autonomous Multiplet Event Detection: Application to Local-Distance Monitoring of Blood Falls Seismicity

    Energy Technology Data Exchange (ETDEWEB)

    Carmichael, Joshua Daniel [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Carr, Christina [Univ. of Alaska, Fairbanks, AK (United States); Pettit, Erin C. [Univ. of Alaska, Fairbanks, AK (United States)

    2015-06-18

    We apply a fully autonomous icequake detection methodology to a single day of high-sample rate (200 Hz) seismic network data recorded from the terminus of Taylor Glacier, ANT that temporally coincided with a brine release episode near Blood Falls (May 13, 2014). We demonstrate a statistically validated procedure to assemble waveforms triggered by icequakes into populations of clusters linked by intra-event waveform similarity. Our processing methodology implements a noise-adaptive power detector coupled with a complete-linkage clustering algorithm and noise-adaptive correlation detector. This detector-chain reveals a population of 20 multiplet sequences that includes ~150 icequakes and produces zero false alarms on the concurrent, diurnally variable noise. Our results are very promising for identifying changes in background seismicity associated with the presence or absence of brine release episodes. We thereby suggest that our methodology could be applied to longer time periods to establish a brine-release monitoring program for Blood Falls that is based on icequake detections.

  4. Modeling Patterns of Activity and Detecting Abnormal Events with Low-Level Co-occurrences

    Science.gov (United States)

    Benezeth, Yannick; Jodoin, Pierre-Marc; Saligrama, Venkatesh

    We explore in this chapter a location-based approach for behavior modeling and abnormality detection. In contrast to conventional object-based approaches for which objects are identified, classified, and tracked to locate objects with suspicious behavior, we proceed directly with event characterization and behavior modeling using low-level features. Our approach consists of two-phases. In the first phase, co-occurrence of activity between temporal sequences of motion labels are used to build a statistical model for normal behavior. This model of co-occurrence statistics is embedded within a co-occurrence matrix which accounts for spatio-temporal co-occurrence of activity. In the second phase, the co-occurrence matrix is used as a potential function in a Markov-Random Field framework to describe, as the video streams in, the probability of observing new volumes of activity. The co-occurrence matrix is thus used for detecting moving objects whose behavior differs from the ones observed during the training phase. Interestingly, the Markov-Random Field distribution implicitly accounts for speed, direction, as well as the average size of the objects without any higher-level intervention. Furthermore, when the spatio-temporal volume is large enough, the co-occurrence distribution contains the average normal path followed by moving objects. Our method has been tested on various outdoor videos representing various challenges.

  5. Detecting Forest Disturbance Events from MODIS and Landsat Time Series for the Conterminous United States

    Science.gov (United States)

    Zhang, G.; Ganguly, S.; Saatchi, S. S.; Hagen, S. C.; Harris, N.; Yu, Y.; Nemani, R. R.

    2013-12-01

    Spatial and temporal patterns of forest disturbance and regrowth processes are key for understanding aboveground terrestrial vegetation biomass and carbon stocks at regional-to-continental scales. The NASA Carbon Monitoring System (CMS) program seeks key input datasets, especially information related to impacts due to natural/man-made disturbances in forested landscapes of Conterminous U.S. (CONUS), that would reduce uncertainties in current carbon stock estimation and emission models. This study provides a end-to-end forest disturbance detection framework based on pixel time series analysis from MODIS (Moderate Resolution Imaging Spectroradiometer) and Landsat surface spectral reflectance data. We applied the BFAST (Breaks for Additive Seasonal and Trend) algorithm to the Normalized Difference Vegetation Index (NDVI) data for the time period from 2000 to 2011. A harmonic seasonal model was implemented in BFAST to decompose the time series to seasonal and interannual trend components in order to detect abrupt changes in magnitude and direction of these components. To apply the BFAST for whole CONUS, we built a parallel computing setup for processing massive time-series data using the high performance computing facility of the NASA Earth Exchange (NEX). In the implementation process, we extracted the dominant deforestation events from the magnitude of abrupt changes in both seasonal and interannual components, and estimated dates for corresponding deforestation events. We estimated the recovery rate for deforested regions through regression models developed between NDVI values and time since disturbance for all pixels. A similar implementation of the BFAST algorithm was performed over selected Landsat scenes (all Landsat cloud free data was used to generate NDVI from atmospherically corrected spectral reflectances) to demonstrate the spatial coherence in retrieval layers between MODIS and Landsat. In future, the application of this largely parallel disturbance

  6. The power to detect recent fragmentation events using genetic differentiation methods.

    Directory of Open Access Journals (Sweden)

    Michael W Lloyd

    Full Text Available Habitat loss and fragmentation are imminent threats to biological diversity worldwide and thus are fundamental issues in conservation biology. Increased isolation alone has been implicated as a driver of negative impacts in populations associated with fragmented landscapes. Genetic monitoring and the use of measures of genetic divergence have been proposed as means to detect changes in landscape connectivity. Our goal was to evaluate the sensitivity of Wright's F st, Hedrick' G'st , Sherwin's MI, and Jost's D to recent fragmentation events across a range of population sizes and sampling regimes. We constructed an individual-based model, which used a factorial design to compare effects of varying population size, presence or absence of overlapping generations, and presence or absence of population sub-structuring. Increases in population size, overlapping generations, and population sub-structuring each reduced F st, G'st , MI, and D. The signal of fragmentation was detected within two generations for all metrics. However, the magnitude of the change in each was small in all cases, and when N e was >100 individuals it was extremely small. Multi-generational sampling and population estimates are required to differentiate the signal of background divergence from changes in Fst , G'st , MI, and D associated with fragmentation. Finally, the window during which rapid change in Fst , G'st , MI, and D between generations occurs can be small, and if missed would lead to inconclusive results. For these reasons, use of F st, G'st , MI, or D for detecting and monitoring changes in connectivity is likely to prove difficult in real-world scenarios. We advocate use of genetic monitoring only in conjunction with estimates of actual movement among patches such that one could compare current movement with the genetic signature of past movement to determine there has been a change.

  7. THE DETECTION OF A SN IIn IN OPTICAL FOLLOW-UP OBSERVATIONS OF ICECUBE NEUTRINO EVENTS

    Energy Technology Data Exchange (ETDEWEB)

    Aartsen, M. G.; Abraham, K.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Ahrens, M.; Altmann, D.; Anderson, T.; Archinger, M.; Arguelles, C.; Arlen, T. C.; Auffenberg, J.; Bai, X.; Barwick, S. W.; Baum, V.; Bay, R.; Beatty, J. J.; Becker Tjus, J.; Becker, K.-H. [Astrophysics Research Centre, School of Mathematics and Physics, Queen' s University Belfast, Belfast, BT7 1NN (United Kingdom); Collaboration: IceCube Collaboration; for the PTF Collaboration; for the Swift Collaboration; for the Pan-STARRS1 Science Consortium; and others

    2015-09-20

    The IceCube neutrino observatory pursues a follow-up program selecting interesting neutrino events in real-time and issuing alerts for electromagnetic follow-up observations. In 2012 March, the most significant neutrino alert during the first three years of operation was issued by IceCube. In the follow-up observations performed by the Palomar Transient Factory (PTF), a Type IIn supernova (SN IIn) PTF12csy was found 0.°2 away from the neutrino alert direction, with an error radius of 0.°54. It has a redshift of z = 0.0684, corresponding to a luminosity distance of about 300 Mpc and the Pan-STARRS1 survey shows that its explosion time was at least 158 days (in host galaxy rest frame) before the neutrino alert, so that a causal connection is unlikely. The a posteriori significance of the chance detection of both the neutrinos and the SN at any epoch is 2.2σ within IceCube's 2011/12 data acquisition season. Also, a complementary neutrino analysis reveals no long-term signal over the course of one year. Therefore, we consider the SN detection coincidental and the neutrinos uncorrelated to the SN. However, the SN is unusual and interesting by itself: it is luminous and energetic, bearing strong resemblance to the SN IIn 2010jl, and shows signs of interaction of the SN ejecta with a dense circumstellar medium. High-energy neutrino emission is expected in models of diffusive shock acceleration, but at a low, non-detectable level for this specific SN. In this paper, we describe the SN PTF12csy and present both the neutrino and electromagnetic data, as well as their analysis.

  8. The Power to Detect Recent Fragmentation Events Using Genetic Differentiation Methods

    Science.gov (United States)

    Lloyd, Michael W.; Campbell, Lesley; Neel, Maile C.

    2013-01-01

    Habitat loss and fragmentation are imminent threats to biological diversity worldwide and thus are fundamental issues in conservation biology. Increased isolation alone has been implicated as a driver of negative impacts in populations associated with fragmented landscapes. Genetic monitoring and the use of measures of genetic divergence have been proposed as means to detect changes in landscape connectivity. Our goal was to evaluate the sensitivity of Wright’s Fst, Hedrick’ G’st, Sherwin’s MI, and Jost’s D to recent fragmentation events across a range of population sizes and sampling regimes. We constructed an individual-based model, which used a factorial design to compare effects of varying population size, presence or absence of overlapping generations, and presence or absence of population sub-structuring. Increases in population size, overlapping generations, and population sub-structuring each reduced Fst, G’st, MI, and D. The signal of fragmentation was detected within two generations for all metrics. However, the magnitude of the change in each was small in all cases, and when Ne was >100 individuals it was extremely small. Multi-generational sampling and population estimates are required to differentiate the signal of background divergence from changes in Fst, G’st, MI, and D associated with fragmentation. Finally, the window during which rapid change in Fst, G’st, MI, and D between generations occurs can be small, and if missed would lead to inconclusive results. For these reasons, use of Fst, G’st, MI, or D for detecting and monitoring changes in connectivity is likely to prove difficult in real-world scenarios. We advocate use of genetic monitoring only in conjunction with estimates of actual movement among patches such that one could compare current movement with the genetic signature of past movement to determine there has been a change. PMID:23704965

  9. Markov Switching Model for Quick Detection of Event Related Desynchronization in EEG

    Directory of Open Access Journals (Sweden)

    Giuseppe Lisi

    2018-02-01

    Full Text Available Quick detection of motor intentions is critical in order to minimize the time required to activate a neuroprosthesis. We propose a Markov Switching Model (MSM to achieve quick detection of an event related desynchronization (ERD elicited by motor imagery (MI and recorded by electroencephalography (EEG. Conventional brain computer interfaces (BCI rely on sliding window classifiers in order to perform online continuous classification of the rest vs. MI classes. Based on this approach, the detection of abrupt changes in the sensorimotor power suffers from an intrinsic delay caused by the necessity of computing an estimate of variance across several tenths of a second. Here we propose to avoid explicitly computing the EEG signal variance, and estimate the ERD state directly from the voltage information, in order to reduce the detection latency. This is achieved by using a model suitable in situations characterized by abrupt changes of state, the MSM. In our implementation, the model takes the form of a Gaussian observation model whose variance is governed by two latent discrete states with Markovian dynamics. Its objective is to estimate the brain state (i.e., rest vs. ERD given the EEG voltage, spatially filtered by common spatial pattern (CSP, as observation. The two variances associated with the two latent states are calibrated using the variance of the CSP projection during rest and MI, respectively. The transition matrix of the latent states is optimized by the “quickest detection” strategy that minimizes a cost function of detection latency and false positive rate. Data collected by a dry EEG system from 50 healthy subjects, was used to assess performance and compare the MSM with several logistic regression classifiers of different sliding window lengths. As a result, the MSM achieves a significantly better tradeoff between latency, false positive and true positive rates. The proposed model could be used to achieve a more reactive and

  10. A signal detection method for temporal variation of adverse effect with vaccine adverse event reporting system data.

    Science.gov (United States)

    Cai, Yi; Du, Jingcheng; Huang, Jing; Ellenberg, Susan S; Hennessy, Sean; Tao, Cui; Chen, Yong

    2017-07-05

    To identify safety signals by manual review of individual report in large surveillance databases is time consuming; such an approach is very unlikely to reveal complex relationships between medications and adverse events. Since the late 1990s, efforts have been made to develop data mining tools to systematically and automatically search for safety signals in surveillance databases. Influenza vaccines present special challenges to safety surveillance because the vaccine changes every year in response to the influenza strains predicted to be prevalent that year. Therefore, it may be expected that reporting rates of adverse events following flu vaccines (number of reports for a specific vaccine-event combination/number of reports for all vaccine-event combinations) may vary substantially across reporting years. Current surveillance methods seldom consider these variations in signal detection, and reports from different years are typically collapsed together to conduct safety analyses. However, merging reports from different years ignores the potential heterogeneity of reporting rates across years and may miss important safety signals. Reports of adverse events between years 1990 to 2013 were extracted from the Vaccine Adverse Event Reporting System (VAERS) database and formatted into a three-dimensional data array with types of vaccine, groups of adverse events and reporting time as the three dimensions. We propose a random effects model to test the heterogeneity of reporting rates for a given vaccine-event combination across reporting years. The proposed method provides a rigorous statistical procedure to detect differences of reporting rates among years. We also introduce a new visualization tool to summarize the result of the proposed method when applied to multiple vaccine-adverse event combinations. We applied the proposed method to detect safety signals of FLU3, an influenza vaccine containing three flu strains, in the VAERS database. We showed that it had high

  11. Automatic seismic event detection using migration and stacking: a performance and parameter study in Hengill, southwest Iceland

    Science.gov (United States)

    Wagner, F.; Tryggvason, A.; Roberts, R.; Lund, B.; Gudmundsson, Ó.

    2017-06-01

    We investigate the performance of a seismic event detection algorithm using migration and stacking of seismic traces. The focus lies on determining optimal data dependent detection parameters for a data set from a temporary network in the volcanically active Hengill area, southwest Iceland. We test variations of the short-term average to long-term average and Kurtosis functions, calculated from filtered seismic traces, as input data. With optimal detection parameters, our algorithm identified 94 per cent (219 events) of the events detected by the South Iceland Lowlands (SIL) system, that is, the automatic system routinely used on Iceland, as well as a further 209 events, previously missed. The assessed number of incorrect (false) detections was 25 per cent for our algorithm, which was considerably better than that from SIL (40 per cent). Empirical tests show that well-functioning processing parameters can be effectively selected based on analysis of small, representative subsections of data. Our migration approach is more computationally expensive than some alternatives, but not prohibitively so, and it appears well suited to analysis of large swarms of low magnitude events with interevent times on the order of seconds. It is, therefore, an attractive, practical tool for monitoring of natural or anthropogenic seismicity related to, for example, volcanoes, drilling or fluid injection.

  12. FOREWORD: 3rd Symposium on Large TPCs for Low Energy Event Detection

    Science.gov (United States)

    Irastorza, Igor G.; Colas, Paul; Gorodetzky, Phillippe

    2007-05-01

    The Third International Symposium on large TPCs for low-energy rare-event detection was held at Carré des sciences, Poincaré auditorium, 25 rue de la Montagne Ste Geneviève in Paris on 11 12 December 2006. This prestigious location belonging to the Ministry of Research is hosted in the former Ecole Polytechnique. The meeting, held in Paris every two years, gathers a significant community of physicists involved in rare event detection. Its purpose is an extensive discussion of present and future projects using large TPCs for low energy, low background detection of rare events (low-energy neutrinos, dark matter, solar axions). The use of a new generation of Micro-Pattern Gaseous Detectors (MPGD) appears to be a promising way to reach this goal. The program this year was enriched by a new session devoted to the detection challenge of polarized gamma rays, relevant novel experimental techniques and the impact on particle physics, astrophysics and astronomy. A very particular feature of this conference is the large variety of talks ranging from purely theoretical to purely experimental subjects including novel technological aspects. This allows discussion and exchange of useful information and new ideas that are emerging to address particle physics experimental challenges. The scientific highlights at the Symposium came on many fronts: Status of low-energy neutrino physics and double-beta decay New ideas on double-beta decay experiments Gamma ray polarization measurement combining high-precision TPCs with MPGD read-out Dark Matter challenges in both axion and WIMP search with new emerging ideas for detection improvements Progress in gaseous and liquid TPCs for rare event detection Georges Charpak opened the meeting with a talk on gaseous detectors for applications in the bio-medical field. He also underlined the importance of new MPGD detectors for both physics and applications. There were about 100 registered participants at the symposium. The successful

  13. Wavelet based automated postural event detection and activity classification with single imu - biomed 2013.

    Science.gov (United States)

    Lockhart, Thurmon E; Soangra, Rahul; Zhang, Jian; Wu, Xuefan

    2013-01-01

    Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person’s activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient’s home. In order to provide a low-cost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment – TEMPO (Technology Enabled Medical Precision Observation). Using this IMU system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection

  14. Objective detection of long-term slow slip events along the Nankai Trough using GNSS data (1996-2016)

    Science.gov (United States)

    Kobayashi, Akio

    2017-12-01

    This paper presents a method for objective detection of long-term slow slip events with durations on the order of years, on the plate boundary along the Nankai Trough, relying on global navigation satellite system daily coordinate data. The Chugoku region of Japan was held fixed to remove common mode errors, and a displacement component was calculated relative to the direction of plate subduction. Correlations were then calculated between this displacement component and a 3-year ramp function with a 1-year slope. Nearly all periods of strong correlation coincide with periods of previously reported long-term slow slip events. A period of strong correlation around the Kii Channel in 2000-2002 is attributed to a previously undocumented long-term slow slip event beneath the Kii Channel and the eastern part of Shikoku Island with an equivalent moment magnitude of 6.6. This detection method reveals variation among long-term slow slip events along the Nankai Trough.

  15. An automated cross-correlation based event detection technique and its application to surface passive data set

    Science.gov (United States)

    Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

    2013-01-01

    In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

  16. Detection of microsleep events in a car driving simulation study using electrocardiographic features

    Directory of Open Access Journals (Sweden)

    Lenis Gustavo

    2016-09-01

    Full Text Available Microsleep events (MSE are short intrusions of sleep under the demand of sustained attention. They can impose a major threat to safety while driving a car and are considered one of the most significant causes of traffic accidents. Driver’s fatigue and MSE account for up to 20% of all car crashes in Europe and at least 100,000 accidents in the US every year. Unfortunately, there is not a standardized test developed to quantify the degree of vigilance of a driver. To account for this problem, different approaches based on biosignal analysis have been studied in the past. In this paper, we investigate an electrocardiographic-based detection of MSE using morphological and rhythmical features. 14 records from a car driving simulation study with a high incidence of MSE were analyzed and the behavior of the ECG features before and after an MSE in relation to reference baseline values (without drowsiness were investigated. The results show that MSE cannot be detected (or predicted using only the ECG. However, in the presence of MSE, the rhythmical and morphological features were observed to be significantly different than the ones calculated for the reference signal without sleepiness. In particular, when MSE were present, the heart rate diminished while the heart rate variability increased. Time distances between P wave and R peak, and R peak and T wave and their dispersion increased also. This demonstrates a noticeable change of the autonomous regulation of the heart. In future, the ECG parameter could be used as a surrogate measure of fatigue.

  17. On the feasibility of using satellite gravity observations for detecting large-scale solid mass transfer events

    Science.gov (United States)

    Peidou, Athina C.; Fotopoulos, Georgia; Pagiatakis, Spiros

    2017-10-01

    The main focus of this paper is to assess the feasibility of utilizing dedicated satellite gravity missions in order to detect large-scale solid mass transfer events (e.g. landslides). Specifically, a sensitivity analysis of Gravity Recovery and Climate Experiment (GRACE) gravity field solutions in conjunction with simulated case studies is employed to predict gravity changes due to past subaerial and submarine mass transfer events, namely the Agulhas slump in southeastern Africa and the Heart Mountain Landslide in northwestern Wyoming. The detectability of these events is evaluated by taking into account the expected noise level in the GRACE gravity field solutions and simulating their impact on the gravity field through forward modelling of the mass transfer. The spectral content of the estimated gravity changes induced by a simulated large-scale landslide event is estimated for the known spatial resolution of the GRACE observations using wavelet multiresolution analysis. The results indicate that both the Agulhas slump and the Heart Mountain Landslide could have been detected by GRACE, resulting in {\\vert }0.4{\\vert } and {\\vert }0.18{\\vert } mGal change on GRACE solutions, respectively. The suggested methodology is further extended to the case studies of the submarine landslide in Tohoku, Japan, and the Grand Banks landslide in Newfoundland, Canada. The detectability of these events using GRACE solutions is assessed through their impact on the gravity field.

  18. One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms.

    Science.gov (United States)

    Andersson, Richard; Larsson, Linnea; Holmqvist, Kenneth; Stridh, Martin; Nyström, Marcus

    2017-04-01

    Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484-2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

  19. First Satellite-detected Perturbations of Outgoing Longwave Radiation Associated with Blowing Snow Events over Antarctica

    Science.gov (United States)

    Yang, Yuekui; Palm, Stephen P.; Marshak, Alexander; Wu, Dong L.; Yu, Hongbin; Fu, Qiang

    2014-01-01

    We present the first satellite-detected perturbations of the outgoing longwave radiation (OLR) associated with blowing snow events over the Antarctic ice sheet using data from Cloud-Aerosol Lidar with Orthogonal Polarization and Clouds and the Earth's Radiant Energy System. Significant cloud-free OLR differences are observed between the clear and blowing snow sky, with the sign andmagnitude depending on season and time of the day. During nighttime, OLRs are usually larger when blowing snow is present; the average difference in OLRs between without and with blowing snow over the East Antarctic Ice Sheet is about 5.2 W/m2 for the winter months of 2009. During daytime, in contrast, the OLR perturbation is usually smaller or even has the opposite sign. The observed seasonal variations and day-night differences in the OLR perturbation are consistent with theoretical calculations of the influence of blowing snow on OLR. Detailed atmospheric profiles are needed to quantify the radiative effect of blowing snow from the satellite observations.

  20. Snake scales, partial exposure, and the Snake Detection Theory: A human event-related potentials study

    Science.gov (United States)

    Van Strien, Jan W.; Isbell, Lynne A.

    2017-01-01

    Studies of event-related potentials in humans have established larger early posterior negativity (EPN) in response to pictures depicting snakes than to pictures depicting other creatures. Ethological research has recently shown that macaques and wild vervet monkeys respond strongly to partially exposed snake models and scale patterns on the snake skin. Here, we examined whether snake skin patterns and partially exposed snakes elicit a larger EPN in humans. In Task 1, we employed pictures with close-ups of snake skins, lizard skins, and bird plumage. In task 2, we employed pictures of partially exposed snakes, lizards, and birds. Participants watched a random rapid serial visual presentation of these pictures. The EPN was scored as the mean activity (225–300 ms after picture onset) at occipital and parieto-occipital electrodes. Consistent with previous studies, and with the Snake Detection Theory, the EPN was significantly larger for snake skin pictures than for lizard skin and bird plumage pictures, and for lizard skin pictures than for bird plumage pictures. Likewise, the EPN was larger for partially exposed snakes than for partially exposed lizards and birds. The results suggest that the EPN snake effect is partly driven by snake skin scale patterns which are otherwise rare in nature. PMID:28387376

  1. Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France.

    Science.gov (United States)

    Abat, Cédric; Chaudet, Hervé; Colson, Philippe; Rolain, Jean-Marc; Raoult, Didier

    2015-08-01

    Infectious diseases are a major threat to humanity, and accurate surveillance is essential. We describe how to implement a laboratory data-based surveillance system in a clinical microbiology laboratory. Two historical Microsoft Excel databases were implemented. The data were then sorted and used to execute the following 2 surveillance systems in Excel: the Bacterial real-time Laboratory-based Surveillance System (BALYSES) for monitoring the number of patients infected with bacterial species isolated at least once in our laboratory during the study periodl and the Marseille Antibiotic Resistance Surveillance System (MARSS), which surveys the primary β-lactam resistance phenotypes for 15 selected bacterial species. The first historical database contained 174,853 identifications of bacteria, and the second contained 12,062 results of antibiotic susceptibility testing. From May 21, 2013, through June 4, 2014, BALYSES and MARSS enabled the detection of 52 abnormal events for 24 bacterial species, leading to 19 official reports. This system is currently being refined and improved.

  2. Fractal analysis of GPS time series for early detection of disastrous seismic events

    Science.gov (United States)

    Filatov, Denis M.; Lyubushin, Alexey A.

    2017-03-01

    A new method of fractal analysis of time series for estimating the chaoticity of behaviour of open stochastic dynamical systems is developed. The method is a modification of the conventional detrended fluctuation analysis (DFA) technique. We start from analysing both methods from the physical point of view and demonstrate the difference between them which results in a higher accuracy of the new method compared to the conventional DFA. Then, applying the developed method to estimate the measure of chaoticity of a real dynamical system - the Earth's crust, we reveal that the latter exhibits two distinct mechanisms of transition to a critical state: while the first mechanism has already been known due to numerous studies of other dynamical systems, the second one is new and has not previously been described. Using GPS time series, we demonstrate efficiency of the developed method in identification of critical states of the Earth's crust. Finally we employ the method to solve a practically important task: we show how the developed measure of chaoticity can be used for early detection of disastrous seismic events and provide a detailed discussion of the numerical results, which are shown to be consistent with outcomes of other researches on the topic.

  3. Vision-based Detection of Acoustic Timed Events: a Case Study on Clarinet Note Onsets

    Science.gov (United States)

    Bazzica, A.; van Gemert, J. C.; Liem, C. C. S.; Hanjalic, A.

    2017-05-01

    Acoustic events often have a visual counterpart. Knowledge of visual information can aid the understanding of complex auditory scenes, even when only a stereo mixdown is available in the audio domain, \\eg identifying which musicians are playing in large musical ensembles. In this paper, we consider a vision-based approach to note onset detection. As a case study we focus on challenging, real-world clarinetist videos and carry out preliminary experiments on a 3D convolutional neural network based on multiple streams and purposely avoiding temporal pooling. We release an audiovisual dataset with 4.5 hours of clarinetist videos together with cleaned annotations which include about 36,000 onsets and the coordinates for a number of salient points and regions of interest. By performing several training trials on our dataset, we learned that the problem is challenging. We found that the CNN model is highly sensitive to the optimization algorithm and hyper-parameters, and that treating the problem as binary classification may prevent the joint optimization of precision and recall. To encourage further research, we publicly share our dataset, annotations and all models and detail which issues we came across during our preliminary experiments.

  4. Security Event Counts Estimate in Automated Systems for Network Attacks Detection

    Directory of Open Access Journals (Sweden)

    D. O. Kovalev

    2011-03-01

    Full Text Available Information security monitoring systems specifics in large automated systems are being analyzed. Security events distribution for different time intervals was determined and further used to estimate the security events counts. Proposed events counts estimate method is based on a dynamically updated table of moments. This method allows to determine the acceptable number of security events at different time intervals as well as exceeding situations which are being the signal for abnormal network activity.

  5. In situ detection of water quality contamination events based on signal complexity analysis using online ultraviolet-visible spectral sensor.

    Science.gov (United States)

    Huang, Pingjie; Wang, Ke; Hou, Dibo; Zhang, Jian; Yu, Jie; Zhang, Guangxin

    2017-08-01

    The contaminant detection in water distribution systems is essential to protect public health from potentially harmful compounds resulting from accidental spills or intentional releases. As a noninvasive optical technique, ultraviolet-visible (UV-Vis) spectroscopy is investigated for detecting contamination events. However, current methods for event detection exhibit the shortcomings of noise susceptibility. In this paper, a new method that has less sensitivity to noise was proposed to detect water quality contamination events by analyzing the complexity of the UV-Vis spectrum series. The proposed method applied approximate entropy (ApEn) to measure spectrum signals' complexity, which made a distinction between normal and abnormal signals. The impact of noise was attenuated with the help of ApEn's insensitivity to signal disturbance. This method was tested on a real water distribution system data set with various concentration simulation events. Results from the experiment and analysis show that the proposed method has a good performance on noise tolerance and provides a better detection result compared with the autoregressive model and sequential probability ratio test.

  6. Automated Sensor Tuning for Seismic Event Detection at a Carbon Capture, Utilization, and Storage Site, Farnsworth Unit, Ochiltree County, Texas

    Science.gov (United States)

    Ziegler, A.; Balch, R. S.; Knox, H. A.; Van Wijk, J. W.; Draelos, T.; Peterson, M. G.

    2016-12-01

    We present results (e.g. seismic detections and STA/LTA detection parameters) from a continuous downhole seismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project. Specifically, we evaluate data from a passive vertical monitoring array consisting of 16 levels of 3-component 15Hz geophones installed in the field and continuously recording since January 2014. This detection database is directly compared to ancillary data (i.e. wellbore pressure) to determine if there is any relationship between seismic observables and CO2 injection and pressure maintenance in the field. Of particular interest is detection of relatively low-amplitude signals constituting long-period long-duration (LPLD) events that may be associated with slow shear-slip analogous to low frequency tectonic tremor. While this category of seismic event provides great insight into dynamic behavior of the pressurized subsurface, it is inherently difficult to detect. To automatically detect seismic events using effective data processing parameters, an automated sensor tuning (AST) algorithm developed by Sandia National Laboratories is being utilized. AST exploits ideas from neuro-dynamic programming (reinforcement learning) to automatically self-tune and determine optimal detection parameter settings. AST adapts in near real-time to changing conditions and automatically self-tune a signal detector to identify (detect) only signals from events of interest, leading to a reduction in the number of missed legitimate event detections and the number of false event detections. Funding for this project is provided by the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) through the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591. Additional support has been provided by site operator Chaparral Energy, L.L.C. and Schlumberger Carbon Services. Sandia National

  7. Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

    Science.gov (United States)

    Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

    2014-01-15

    Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs. © 2013.

  8. A secure distributed logistic regression protocol for the detection of rare adverse drug events.

    Science.gov (United States)

    El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

    2013-05-01

    There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for correlations among patients within sites through

  9. UKIRT Microlensing Surveys as a Pathfinder for WFIRST: The Detection of Five Highly Extinguished Low-∣b∣ Events

    Science.gov (United States)

    Shvartzvald, Y.; Bryden, G.; Gould, A.; Henderson, C. B.; Howell, S. B.; Beichman, C.

    2017-02-01

    Optical microlensing surveys are restricted from detecting events near the Galactic plane and center, where the event rate is thought to be the highest due to the high optical extinction of these fields. In the near-infrared (NIR), however, the lower extinction leads to a corresponding increase in event detections and is a primary driver for the wavelength coverage of the WFIRST microlensing survey. During the 2015 and 2016 bulge observing seasons, we conducted NIR microlensing surveys with UKIRT in conjunction with and in support of the Spitzer and Kepler microlensing campaigns. Here, we report on five highly extinguished ({A}H=0.81{--}1.97), low-Galactic latitude (-0.98≤slant b≤slant -0.36) microlensing events discovered from our 2016 survey. Four of them were monitored with an hourly cadence by optical surveys but were not reported as discoveries, likely due to the high extinction. Our UKIRT surveys and suggested future NIR surveys enable the first measurement of the microlensing event rate in the NIR. This wavelength regime overlaps with the bandpass of the filter in which the WFIRST microlensing survey will conduct its highest-cadence observations, making this event rate derivation critically important for optimizing its yield.

  10. A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits.

    Science.gov (United States)

    Gouwanda, Darwin; Gopalai, Alpha Agape

    2015-02-01

    Gait events detection allows clinicians and biomechanics researchers to determine timing of gait events, to estimate duration of stance phase and swing phase and to segment gait data. It also aids biomedical engineers to improve the design of orthoses and FES (functional electrical stimulation) systems. In recent years, researchers have resorted to using gyroscopes to determine heel-strike (HS) and toe-off (TO) events in gait cycles. However, these methods are subjected to significant delays when implemented in real-time gait monitoring devices, orthoses, and FES systems. Therefore, the work presented in this paper proposes a method that addresses these delays, to ensure real-time gait event detection. The proposed algorithm combines the use of heuristics and zero-crossing method to identify HS and TO. Experiments involving: (1) normal walking; (2) walking with knee brace; and (3) walking with ankle brace for overground walking and treadmill walking were designed to verify and validate the identified HS and TO. The performance of the proposed method was compared against the established gait detection algorithms. It was observed that the proposed method produced detection rate that was comparable to earlier reported methods and recorded reduced time delays, at an average of 100 ms. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

  11. Signal classification and event reconstruction for acoustic neutrino detection in sea water with KM3NeT

    Science.gov (United States)

    Kießling, Dominik

    2017-03-01

    The research infrastructure KM3NeT will comprise a multi cubic kilometer neutrino telescope that is currently being constructed in the Mediterranean Sea. Modules with optical and acoustic sensors are used in the detector. While the main purpose of the acoustic sensors is the position calibration of the detection units, they can be used as instruments for studies on acoustic neutrino detection, too. In this article, methods for signal classification and event reconstruction for acoustic neutrino detectors will be presented, which were developed using Monte Carlo simulations. For the signal classification the disk-like emission pattern of the acoustic neutrino signal is used. This approach improves the suppression of transient background by several orders of magnitude. Additionally, an event reconstruction is developed based on the signal classification. An overview of these algorithms will be presented and the efficiency of the classification will be discussed. The quality of the event reconstruction will also be presented.

  12. Signal classification and event reconstruction for acoustic neutrino detection in sea water with KM3NeT

    Directory of Open Access Journals (Sweden)

    Kießling Dominik

    2017-01-01

    Full Text Available The research infrastructure KM3NeT will comprise a multi cubic kilometer neutrino telescope that is currently being constructed in the Mediterranean Sea. Modules with optical and acoustic sensors are used in the detector. While the main purpose of the acoustic sensors is the position calibration of the detection units, they can be used as instruments for studies on acoustic neutrino detection, too. In this article, methods for signal classification and event reconstruction for acoustic neutrino detectors will be presented, which were developed using Monte Carlo simulations. For the signal classification the disk–like emission pattern of the acoustic neutrino signal is used. This approach improves the suppression of transient background by several orders of magnitude. Additionally, an event reconstruction is developed based on the signal classification. An overview of these algorithms will be presented and the efficiency of the classification will be discussed. The quality of the event reconstruction will also be presented.

  13. Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

    Science.gov (United States)

    Chen, Yen-Lin; Liang, Wen-Yew; Chiang, Chuan-Yen; Hsieh, Tung-Ju; Lee, Da-Cheng; Yuan, Shyan-Ming; Chang, Yang-Lang

    2011-01-01

    This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions. PMID:22163990

  14. Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

    Directory of Open Access Journals (Sweden)

    Yang-Lang Chang

    2011-07-01

    Full Text Available This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions.

  15. Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

    Science.gov (United States)

    Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

    2015-08-01

    In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

  16. Automatic detection of esophageal pressure events. Is there an alternative to rule-based criteria?

    DEFF Research Database (Denmark)

    Kruse-Andersen, S; Rütz, K; Kolberg, Jens Godsk

    1995-01-01

    curves generated by muscular contractions, rule-based criteria do not always select the pressure events most relevant for further analysis. We have therefore been searching for a new concept for automatic event recognition. The present study describes a new system, based on the method of neurocomputing...

  17. Detection of adverse events of transfusion in a teaching hospital in Ghana.

    Science.gov (United States)

    Owusu-Ofori, A K; Owusu-Ofori, S P; Bates, I

    2017-06-01

    Monitoring the whole chain of events from the blood donors to recipients, documenting any undesirable or untoward effects and introducing measures to prevent their recurrence if possible are components of haemovigilance systems. Only few sub-Saharan African countries have haemovigilance systems, and there are very little data on adverse events of transfusion. Adverse events monitoring is an integral part of a haemovigilance system. Our study aimed to establish the incidence and types of adverse events of transfusions in Ghana and to identify interventions to improve effectiveness. This prospective observational 1-year study enrolled 372 recipients of 432 transfusions in a Ghanaian teaching hospital. Vital signs were monitored at 15, 30 and 60 min intervals during the transfusion, then 8 h until 24 h post-transfusion. Three investigators independently classified any new signs and symptoms according to Serious Hazards of Transfusion definitions. The adverse events incidence was 21·3% (92/432), predominantly mild acute transfusion reactions (84%). A total of 20 transfusions (4·6%) were stopped before completion, 60% of them for mild febrile reactions, which could have been managed with transfusion in situ. This prospective study indicates a high incidence of adverse events of transfusion in Kumasi, Ghana. The significant numbers of discontinued transfusions suggest that guidelines on how to manage transfusion reactions would help preserve scarce blood stocks. Gradual implementation of a haemovigilance system, starting with monitoring adverse transfusion events, is a pragmatic approach in resource-limited settings. © 2017 British Blood Transfusion Society.

  18. [Comparison of the "Trigger" tool with the minimum basic data set for detecting adverse events in general surgery].

    Science.gov (United States)

    Pérez Zapata, A I; Gutiérrez Samaniego, M; Rodríguez Cuéllar, E; Gómez de la Cámara, A; Ruiz López, P

    Surgery is a high risk for the occurrence of adverse events (AE). The main objective of this study is to compare the effectiveness of the Trigger tool with the Hospital National Health System registration of Discharges, the minimum basic data set (MBDS), in detecting adverse events in patients admitted to General Surgery and undergoing surgery. Observational and descriptive retrospective study of patients admitted to general surgery of a tertiary hospital, and undergoing surgery in 2012. The identification of adverse events was made by reviewing the medical records, using an adaptation of "Global Trigger Tool" methodology, as well as the (MBDS) registered on the same patients. Once the AE were identified, they were classified according to damage and to the extent to which these could have been avoided. The area under the curve (ROC) were used to determine the discriminatory power of the tools. The Hanley and Mcneil test was used to compare both tools. AE prevalence was 36.8%. The TT detected 89.9% of all AE, while the MBDS detected 28.48%. The TT provides more information on the nature and characteristics of the AE. The area under the curve was 0.89 for the TT and 0.66 for the MBDS. These differences were statistically significant (P<.001). The Trigger tool detects three times more adverse events than the MBDS registry. The prevalence of adverse events in General Surgery is higher than that estimated in other studies. Copyright © 2017 SECA. Publicado por Elsevier España, S.L.U. All rights reserved.

  19. Detection of rain events in radiological early warning networks with spectro-dosimetric systems

    Science.gov (United States)

    Dąbrowski, R.; Dombrowski, H.; Kessler, P.; Röttger, A.; Neumaier, S.

    2017-10-01

    Short-term pronounced increases of the ambient dose equivalent rate, due to rainfall are a well-known phenomenon. Increases in the same order of magnitude or even below may also be caused by a nuclear or radiological event, i.e. by artificial radiation. Hence, it is important to be able to identify natural rain events in dosimetric early warning networks and to distinguish them from radiological events. Novel spectrometric systems based on scintillators may be used to differentiate between the two scenarios, because the measured gamma spectra provide significant nuclide-specific information. This paper describes three simple, automatic methods to check whether an dot H*(10) increase is caused by a rain event or by artificial radiation. These methods were applied to measurements of three spectrometric systems based on CeBr3, LaBr3 and SrI2 scintillation crystals, investigated and tested for their practicability at a free-field reference site of PTB.

  20. [Performance and optimisation of a trigger tool for the detection of adverse events in hospitalised adult patients].

    Science.gov (United States)

    Guzmán Ruiz, Óscar; Pérez Lázaro, Juan José; Ruiz López, Pedro

    To characterise the performance of the triggers used in the detection of adverse events (AE) of hospitalised adult patients and to define a simplified panel of triggers to facilitate the detection of AE. Cross-sectional study of charts of patients from a service of internal medicine to detect EA through systematic review of the charts and identification of triggers (clinical event often related to AE), determining if there was AE as the context in which it appeared the trigger. Once the EA was detected, we proceeded to the characterization of the triggers that detected it. Logistic regression was applied to select the triggers with greater AE detection capability. A total of 291 charts were reviewed, with a total of 562 triggers in 103 patients, of which 163 were involved in detecting an AE. The triggers that detected the most AE were "A.1. Pressure ulcer" (9.82%), "B.5. Laxative or enema" (8.59%), "A.8. Agitation" (8.59%), "A.9. Over-sedation" (7.98%), "A.7. Haemorrhage" (6.75%) and "B.4. Antipsychotic" (6.75%). A simplified model was obtained using logistic regression, and included the variable "Number of drugs" and the triggers "Over-sedation", "Urinary catheterisation", "Readmission in 30 days", "Laxative or enema" and "Abrupt medication stop". This model showed a probability of 81% to correctly classify charts with EA or without EA (p <0.001; 95% confidence interval: 0.763-0.871). A high number of triggers were associated with AE. The summary model is capable of detecting a large amount of AE, with a minimum of elements. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

  1. Research and development of a high-temperature helium-leak detection system (joint research). Part 1 survey on leakage events and current leak detection technology

    Energy Technology Data Exchange (ETDEWEB)

    Sakaba, Nariaki; Nakazawa, Toshio; Kawasaki, Kozo [Japan Atomic Energy Research Inst., Oarai, Ibaraki (Japan). Oarai Research Establishment; Urakami, Masao; Saisyu, Sadanori [Japan Atomic Power Co., Tokyo (Japan)

    2003-03-01

    In High Temperature Gas-cooled Reactors (HTGR), the detection of leakage of helium at an early stage is very important for the safety and stability of operations. Since helium is a colourless gas, it is generally difficult to identify the location and the amount of leakage when very little leakage has occurred. The purpose of this R and D is to develop a helium leak detection system for the high temperature environment appropriate to the HTGR. As the first step in the development, this paper describes the result of surveying leakage events at nuclear facilities inside and outside Japan and current gas leakage detection technology to adapt optical-fibre detection technology to HTGRs. (author)

  2. A Data-Driven Monitoring Technique for Enhanced Fall Events Detection

    KAUST Repository

    Zerrouki, Nabil

    2016-07-26

    Fall detection is a crucial issue in the health care of seniors. In this work, we propose an innovative method for detecting falls via a simple human body descriptors. The extracted features are discriminative enough to describe human postures and not too computationally complex to allow a fast processing. The fall detection is addressed as a statistical anomaly detection problem. The proposed approach combines modeling using principal component analysis modeling with the exponentially weighted moving average (EWMA) monitoring chart. The EWMA scheme is applied on the ignored principal components to detect the presence of falls. Using two different fall detection datasets, URFD and FDD, we have demonstrated the greater sensitivity and effectiveness of the developed method over the conventional PCA-based methods.

  3. Zero shot Event Detection using Multi modal Fusion of Weakly Supervised Concepts (Open Access)

    Science.gov (United States)

    2014-09-25

    speech activity detection (SAD) and a hidden Markov model (HMM) based multi-pass large vocabulary ASR to obtain speech content in the video, and encode...average the detection scores across the video to get the final video- level feature vector. 4.5. Automatic Speech Recognition (ASR) We use GMM-based...a speech activity detection (SAD) system that employs two GMMs, for speech and non- speech observations respectively. The SAD model incorporates video

  4. One Novel Multiple-Target Plasmid Reference Molecule Targeting Eight Genetically Modified Canola Events for Genetically Modified Canola Detection.

    Science.gov (United States)

    Li, Zhuqing; Li, Xiang; Wang, Canhua; Song, Guiwen; Pi, Liqun; Zheng, Lan; Zhang, Dabing; Yang, Litao

    2017-09-27

    Multiple-target plasmid DNA reference materials have been generated and utilized as good substitutes of matrix-based reference materials in the analysis of genetically modified organisms (GMOs). Herein, we report the construction of one multiple-target plasmid reference molecule, pCAN, which harbors eight GM canola event-specific sequences (RF1, RF2, MS1, MS8, Topas 19/2, Oxy235, RT73, and T45) and a partial sequence of the canola endogenous reference gene PEP. The applicability of this plasmid reference material in qualitative and quantitative PCR assays of the eight GM canola events was evaluated, including the analysis of specificity, limit of detection (LOD), limit of quantification (LOQ), and performance of pCAN in the analysis of various canola samples, etc. The LODs are 15 copies for RF2, MS1, and RT73 assays using pCAN as the calibrator and 10 genome copies for the other events. The LOQ in each event-specific real-time PCR assay is 20 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and PEP assays are between 91% and 97%, and the squared regression coefficients (R2) are all higher than 0.99. The quantification bias values varied from 0.47% to 20.68% with relative standard deviation (RSD) from 1.06% to 24.61% in the quantification of simulated samples. Furthermore, 10 practical canola samples sampled from imported shipments in the port of Shanghai, China, were analyzed employing pCAN as the calibrator, and the results were comparable with those assays using commercial certified materials as the calibrator. Concluding from these results, we believe that this newly developed pCAN plasmid is one good candidate for being a plasmid DNA reference material in the detection and quantification of the eight GM canola events in routine analysis.

  5. INTEGRAL Detection of the First Prompt Gamma-Ray Signal Coincident with the Gravitational-wave Event GW170817

    Science.gov (United States)

    Savchenko, V.; Ferrigno, C.; Kuulkers, E.; Bazzano, A.; Bozzo, E.; Brandt, S.; Chenevez, J.; Courvoisier, T. J.-L.; Diehl, R.; Domingo, A.; Hanlon, L.; Jourdain, E.; von Kienlin, A.; Laurent, P.; Lebrun, F.; Lutovinov, A.; Martin-Carrillo, A.; Mereghetti, S.; Natalucci, L.; Rodi, J.; Roques, J.-P.; Sunyaev, R.; Ubertini, P.

    2017-10-01

    We report the INTernational Gamma-ray Astrophysics Laboratory (INTEGRAL) detection of the short gamma-ray burst GRB 170817A (discovered by Fermi-GBM) with a signal-to-noise ratio of 4.6, and, for the first time, its association with the gravitational waves (GWs) from binary neutron star (BNS) merging event GW170817 detected by the LIGO and Virgo observatories. The significance of association between the gamma-ray burst observed by INTEGRAL and GW170817 is 3.2σ, while the association between the Fermi-GBM and INTEGRAL detections is 4.2σ. GRB 170817A was detected by the SPI-ACS instrument about 2 s after the end of the GW event. We measure a fluence of (1.4 ± 0.4 ± 0.6) × 10-7 erg cm-2 (75-2000 keV), where, respectively, the statistical error is given at the 1σ confidence level, and the systematic error corresponds to the uncertainty in the spectral model and instrument response. We also report on the pointed follow-up observations carried out by INTEGRAL, starting 19.5 hr after the event, and lasting for 5.4 days. We provide a stringent upper limit on any electromagnetic signal in a very broad energy range, from 3 keV to 8 MeV, constraining the soft gamma-ray afterglow flux to INTEGRAL, we constrained the gamma-ray line emission from radioactive decays that are expected to be the principal source of the energy behind a kilonova event following a BNS coalescence. Finally, we put a stringent upper limit on any delayed bursting activity, for example, from a newly formed magnetar.

  6. INTEGRAL Detection of the First Prompt Gamma-Ray Signal Coincident with the Gravitational-wave Event GW170817

    Energy Technology Data Exchange (ETDEWEB)

    Savchenko, V.; Ferrigno, C.; Bozzo, E.; Courvoisier, T. J.-L. [ISDC, Department of Astronomy, University of Geneva, Chemin d’Écogia, 16 CH-1290 Versoix (Switzerland); Kuulkers, E. [European Space Research and Technology Centre (ESA/ESTEC), Keplerlaan 1, 2201 AZ Noordwijk (Netherlands); Bazzano, A.; Natalucci, L.; Rodi, J. [INAF-Institute for Space Astrophysics and Planetology, Via Fosso del Cavaliere 100, I-00133-Rome (Italy); Brandt, S.; Chenevez, J. [DTU Space, National Space Institute Elektrovej, Building 327 DK-2800 Kongens Lyngby (Denmark); Diehl, R.; Von Kienlin, A. [Max-Planck-Institut für Extraterrestrische Physik, Garching (Germany); Domingo, A. [Centro de Astrobiología (CAB-CSIC/INTA, ESAC Campus), Camino bajo del Castillo S/N, E-28692 Villanueva de la Cañada, Madrid (Spain); Hanlon, L.; Martin-Carrillo, A. [Space Science Group, School of Physics, University College Dublin, Belfield, Dublin 4 (Ireland); Jourdain, E. [IRAP, Université de Toulouse, CNRS, UPS, CNES, 9 Av. Roche, F-31028 Toulouse (France); Laurent, P.; Lebrun, F. [APC, AstroParticule et Cosmologie, Université Paris Diderot, CNRS/IN2P3, CEA/Irfu, Observatoire de Paris Sorbonne Paris Cité, 10 rue Alice Domont et Léonie Duquet, F-75205 Paris Cedex 13 (France); Lutovinov, A. [Space Research Institute of Russian Academy of Sciences, Profsoyuznaya 84/32, 117997 Moscow (Russian Federation); Mereghetti, S. [INAF, IASF-Milano, via E.Bassini 15, I-20133 Milano (Italy); and others

    2017-10-20

    We report the INTernational Gamma-ray Astrophysics Laboratory ( INTEGRAL ) detection of the short gamma-ray burst GRB 170817A (discovered by Fermi -GBM) with a signal-to-noise ratio of 4.6, and, for the first time, its association with the gravitational waves (GWs) from binary neutron star (BNS) merging event GW170817 detected by the LIGO and Virgo observatories. The significance of association between the gamma-ray burst observed by INTEGRAL and GW170817 is 3.2σ, while the association between the Fermi -GBM and INTEGRAL detections is 4.2σ. GRB 170817A was detected by the SPI-ACS instrument about 2 s after the end of the GW event. We measure a fluence of (1.4 ± 0.4 ± 0.6) × 10{sup −7} erg cm{sup −2} (75–2000 keV), where, respectively, the statistical error is given at the 1σ confidence level, and the systematic error corresponds to the uncertainty in the spectral model and instrument response. We also report on the pointed follow-up observations carried out by INTEGRAL , starting 19.5 hr after the event, and lasting for 5.4 days. We provide a stringent upper limit on any electromagnetic signal in a very broad energy range, from 3 keV to 8 MeV, constraining the soft gamma-ray afterglow flux to <7.1 × 10{sup −11} erg cm{sup −2} s{sup −1} (80–300 keV). Exploiting the unique capabilities of INTEGRAL , we constrained the gamma-ray line emission from radioactive decays that are expected to be the principal source of the energy behind a kilonova event following a BNS coalescence. Finally, we put a stringent upper limit on any delayed bursting activity, for example, from a newly formed magnetar.

  7. PortVis: A Tool for Port-Based Detection of Security Events

    Energy Technology Data Exchange (ETDEWEB)

    McPherson, J; Ma, K; Krystosk, P; Bartoletti, T; Christensen, M

    2004-06-29

    Most visualizations of security-related network data require large amounts of finely detailed, high-dimensional data. However, in some cases, the data available can only be coarsely detailed because of security concerns or other limitations. How can interesting security events still be discovered in data that lacks important details, such as IP addresses, network security alarms, and labels? In this paper, we discuss a system we have designed that takes very coarsely detailed data-basic, summarized information of the activity on each TCP port during each given hour-and uses visualization to help uncover interesting security events.

  8. Assessment of a Compton-event suppression gamma-spectrometer for the detection of fission products at trace levels

    CERN Document Server

    Peerani, P; Hrnecek, E; Betti, M

    2002-01-01

    The improvement in detection limits for low and high activity samples measured with the Compton-suppression gamma-spectrometer installed at the Institute for Transuranium Elements (ITU) for environmental monitoring of radioactivity, as well as nuclear safeguards, is discussed. The advantage of using two parallel acquisition lines for simultaneous measurement with and without Compton-event suppression is outlined with respect to cascade and non-cascade gamma-emitters. The background reduction by Compton-event suppression made it possible to detect small peaks, which otherwise would not have been found in a conventional spectrum. In Compton-event suppression mode, the detection limit for sup 1 sup 3 sup 7 Cs was improved by a factor of about 3, for sup 2 sup 4 sup 1 Am we found a factor of 1.2 both in high and low active samples. The measurements of environmental reference samples showed good agreement with certified values in both acquisition modes. The application of this instrument for the determination of f...

  9. Online surveillance of media health event reporting in Nepal: digital disease detection from a One Health perspective.

    Science.gov (United States)

    Schwind, Jessica S; Norman, Stephanie A; Karmacharya, Dibesh; Wolking, David J; Dixit, Sameer M; Rajbhandari, Rajesh M; Mekaru, Sumiko R; Brownstein, John S

    2017-09-21

    Traditional media and the internet are crucial sources of health information. Media can significantly shape public opinion, knowledge and understanding of emerging and endemic health threats. As digital communication rapidly progresses, local access and dissemination of health information contribute significantly to global disease detection and reporting. Health event reports in Nepal (October 2013-December 2014) were used to characterize Nepal's media environment from a One Health perspective using HealthMap - a global online disease surveillance and mapping tool. Event variables (location, media source type, disease or risk factor of interest, and affected species) were extracted from HealthMap. A total of 179 health reports were captured from various sources including newspapers, inter-government agency bulletins, individual reports, and trade websites, yielding 108 (60%) unique articles. Human health events were reported most often (n = 85; 79%), followed by animal health events (n = 23; 21%), with no reports focused solely on environmental health. By expanding event coverage across all of the health sectors, media in developing countries could play a crucial role in national risk communication efforts and could enhance early warning systems for disasters and disease outbreaks.

  10. Snake scales, partial exposure, and the Snake Detection Theory: A human event-related potentials study

    NARCIS (Netherlands)

    J.W. van Strien (Jan); L.A. Isbell (Lynne A.)

    2017-01-01

    textabstractStudies of event-related potentials in humans have established larger early posterior negativity (EPN) in response to pictures depicting snakes than to pictures depicting other creatures. Ethological research has recently shown that macaques and wild vervet monkeys respond strongly to

  11. Going against the flow: a case for upstream dispersal and detection of uncommon dispersal events

    NARCIS (Netherlands)

    Wubs, E.R.J.; Fraaije, Rob G.A.; Groot, de G.A.; Erkens, R.H.J.; Garsen, Annemarie G.; Kleyheeg, Erik; Raven, Bart M.; Soons, Merel B.

    2016-01-01

    1.Dispersal and colonisation are key processes determining species survival, and their importance is increasing as a consequence of ongoing habitat fragmentation, land-use change and climate change. Identification of long-distance dispersal events, including upstream dispersal, and of the dispersal

  12. Going against the flow: a case for upstream dispersal and detection of uncommon dispersal events

    NARCIS (Netherlands)

    Wubs, E. R. Jasper; Fraaije, Rob G. A.; de Groot, G. Arjen; Erkens, Roy H. J.; Garssen, Annemarie G.; Kleyheeg, Erik; Raven, Bart M.; Soons, Merel B.

    2016-01-01

    * Dispersal and colonisation are key processes determining species survival, and their importance is increasing as a consequence of ongoing habitat fragmentation, land-use change and climate change. Identification of long-distance dispersal events, including upstream dispersal, and of the dispersal

  13. Dune Detective, Using Ecological Studies to Reconstruct Events Which Shaped a Barrier Island.

    Science.gov (United States)

    Godfrey, Paul J.; Hon, Will

    This publication is designed for use as part of a curriculum series developed by the Regional Marine Science Project. Students in grades 11 and 12 are exposed to research methods through a series of field exercises guiding investigators in reconstructing the events which have shaped the natural communities of a barrier beach. Background…

  14. Monkeying around with the Gorillas in Our Midst: Familiarity with an Inattentional-Blindness Task Does Not Improve the Detection of Unexpected Events

    Directory of Open Access Journals (Sweden)

    Daniel J Simons

    2010-04-01

    Full Text Available When people know to look for an unexpected event (eg, a gorilla in a basketball game, they tend to notice that event. But does knowledge that an unexpected event might occur improve the detection of other unexpected events in a similar scene? Subjects watched a new video in which, in addition to the gorilla, two other unexpected events occurred: a curtain changed color, and one player left the scene. Subjects who knew about videos like this one consistently spotted the gorilla in the new video, but they were slightly less likely to notice the other events. Foreknowledge that unexpected events might occur does not enhance the ability to detect other such events.

  15. Novel Observational Technique of Gravitational Wave (GW) Events: Detecting and Locating Electromagnetic Counterparts to GW Sources using Dust Scattering Halos

    Science.gov (United States)

    Nederlander, Richard; Paerels, Frits

    2018-01-01

    We discuss a novel observational technique for detecting and locating the electromagnetic counterpart to its GW source, providing astronomers with a several-hour reprieve after a GW event’s occurrence. The technique relies on identifying a dust scattering halo caused by GW-produced X-rays scattering off Galactic dust clouds. The travel time delay of these scattered photons makes them detectable for up to several hours after the prompt event, and the location of the gravitational wave source will be at the geometric center of the halo. The center can be determined with precision sufficient enough to allow the host galaxy to be discerned. This novel technique will be especially relevant for binary black-hole mergers because their counterparts have, as of now, been difficult to detect.

  16. Mining the IPTV Channel Change Event Stream to Discover Insight and Detect Ads

    Directory of Open Access Journals (Sweden)

    Matej Kren

    2016-01-01

    Full Text Available IPTV has been widely deployed throughout the world, bringing significant advantages to users in terms of the channel offering, video on demand, and interactive applications. One aspect that has been often neglected is the ability of precise and unobtrusive telemetry. TV set-top boxes that are deployed in modern IPTV systems can be thought of as capable sensor nodes that collect vast amounts of data, representing both the user activity and the quality of service delivered by the system itself. In this paper we focus on the user-generated events and analyze how the data stream of channel change events received from the entire IPTV network can be mined to obtain insight about the content. We demonstrate that it is possible to predict the occurrence of TV ads with high probability and show that the approach could be extended to model the user behavior and classify the viewership in multiple dimensions.

  17. Signature Based Detection of User Events for Post-mortem Forensic Analysis

    Science.gov (United States)

    James, Joshua Isaac; Gladyshev, Pavel; Zhu, Yuandong

    This paper introduces a novel approach to user event reconstruction by showing the practicality of generating and implementing signature-based analysis methods to reconstruct high-level user actions from a collection of low-level traces found during a post-mortem forensic analysis of a system. Traditional forensic analysis and the inferences an investigator normally makes when given digital evidence, are examined. It is then demonstrated that this natural process of inferring high-level events from low-level traces may be encoded using signature-matching techniques. Simple signatures using the defined method are created and applied for three popular Windows-based programs as a proof of concept.

  18. Embedding surveillance into clinical care to detect serious adverse events in pregnancy.

    OpenAIRE

    Seale, Anna C; Barsosio, Hellen C.; Koech, Angela C.; Berkley, James A

    2015-01-01

    Severe maternal complications in pregnancy in sub-Saharan Africa contribute to high maternal mortality and morbidity. Incidence data on severe maternal complications, life-threatening conditions, maternal deaths and birth outcomes are essential for clinical audit and to inform trial design of the types and frequency of expected severe adverse events (SAEs). However, such data are very limited, especially in sub-Saharan Africa. We set up standardized, systematic clinical surveillance embedded ...

  19. Late Fusion and Calibration for Multimedia Event Detection Using Few Examples (Author’s Manuscript)

    Science.gov (United States)

    2014-07-14

    Hidden Markov Model Fisher Vector descriptors [21]. SVM with Gaussian kernel was used to train two event classifiers, one for each set of action concepts...requires input from various analysis channels (image and motion analysis, audio concepts, speech content, character recognition , etc.) that we will refer...adaptation using the first-pass recognition output. We also performed supervised and un- supervised language model adaptation. The lattice-based approach

  20. Enriched encoding: reward motivation organizes cortical networks for hippocampal detection of unexpected events.

    Science.gov (United States)

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical-hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions-a potentially unique contribution of the hippocampus to reward learning. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Detecting Signals of Disproportionate Reporting from Singapore's Spontaneous Adverse Event Reporting System: An Application of the Sequential Probability Ratio Test.

    Science.gov (United States)

    Chan, Cheng Leng; Rudrappa, Sowmya; Ang, Pei San; Li, Shu Chuen; Evans, Stephen J W

    2017-08-01

    The ability to detect safety concerns from spontaneous adverse drug reaction reports in a timely and efficient manner remains important in public health. This paper explores the behaviour of the Sequential Probability Ratio Test (SPRT) and ability to detect signals of disproportionate reporting (SDRs) in the Singapore context. We used SPRT with a combination of two hypothesised relative risks (hRRs) of 2 and 4.1 to detect signals of both common and rare adverse events in our small database. We compared SPRT with other methods in terms of number of signals detected and whether labelled adverse drug reactions were detected or the reaction terms were considered serious. The other methods used were reporting odds ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN) and Gamma Poisson Shrinker (GPS). The SPRT produced 2187 signals in common with all methods, 268 unique signals, and 70 signals in common with at least one other method, and did not produce signals in 178 cases where two other methods detected them, and there were 403 signals unique to one of the other methods. In terms of sensitivity, ROR performed better than other methods, but the SPRT method found more new signals. The performances of the methods were similar for negative predictive value and specificity. Using a combination of hRRs for SPRT could be a useful screening tool for regulatory agencies, and more detailed investigation of the medical utility of the system is merited.

  2. The Diurnal Variation of the Wimp Detection Event Rates in Directional Experiments

    CERN Document Server

    Vergados, J D

    2009-01-01

    The recent WMAP data have confirmed that exotic dark matter together with the vacuum energy (cosmological constant) dominate in the flat Universe. Modern particle theories naturally provide viable cold dark matter candidates with masses in the GeV-TeV region. Supersymmetry provides the lightest supersymmetric particle (LSP), theories in extra dimensions supply the lightest Kaluza-Klein particle (LKP) etc. The nature of dark matter can only be unraveled only by its direct detection in the laboratory. All such candidates will be called WIMPs (Weakly Interacting Massive Particles). In any case the direct dark matter search, which amounts to detecting the recoiling nucleus, following its collision with WIMP, is central to particle physics and cosmology. In this work we briefly review the theoretical elements relevant to the direct dark matter detection experiments, paying particular attention to directional experiments. i.e experiments in which, not only the energy but the direction of the recoiling nucleus is ob...

  3. Control Surface Fault Diagnosis with Specified Detection Probability - Real Event Experiences

    DEFF Research Database (Denmark)

    Hansen, Søren; Blanke, Mogens

    2013-01-01

    desired levels of false alarms and detection probabilities. Self-tuning residual generators are employed for diagnosis and are combined with statistical change detection to form a setup for robust fault diagnosis. On-line estimation of test statistics is used to obtain a detection threshold and a desired......Diagnosis of actuator faults is crucial for aircraft since loss of actuation can have catastrophic consequences. For autonomous aircraft the steps necessary to achieve fault tolerance is limited when only basic and non-redundant sensor and actuators suites are present. Through diagnosis...... that exploits analytical redundancies it is, nevertheless, possible to cheaply enhance the level of safety. This paper presents a method for diagnosing control surface faults by using basic sensors and hardware available on an autonomous aircraft. The capability of fault diagnosis is demonstrated obtaining...

  4. homeSound: Real-Time Audio Event Detection Based on High Performance Computing for Behaviour and Surveillance Remote Monitoring

    Science.gov (United States)

    Alsina-Pagès, Rosa Ma; Navarro, Joan; Alías, Francesc; Hervás, Marcos

    2017-01-01

    The consistent growth in human life expectancy during the recent years has driven governments and private organizations to increase the efforts in caring for the eldest segment of the population. These institutions have built hospitals and retirement homes that have been rapidly overfilled, making their associated maintenance and operating costs prohibitive. The latest advances in technology and communications envisage new ways to monitor those people with special needs at their own home, increasing their quality of life in a cost-affordable way. The purpose of this paper is to present an Ambient Assisted Living (AAL) platform able to analyze, identify, and detect specific acoustic events happening in daily life environments, which enables the medic staff to remotely track the status of every patient in real-time. Additionally, this tele-care proposal is validated through a proof-of-concept experiment that takes benefit of the capabilities of the NVIDIA Graphical Processing Unit running on a Jetson TK1 board to locally detect acoustic events. Conducted experiments demonstrate the feasibility of this approach by reaching an overall accuracy of 82% when identifying a set of 14 indoor environment events related to the domestic surveillance and patients’ behaviour monitoring field. Obtained results encourage practitioners to keep working in this direction, and enable health care providers to remotely track the status of their patients in real-time with non-invasive methods. PMID:28406459

  5. homeSound: Real-Time Audio Event Detection Based on High Performance Computing for Behaviour and Surveillance Remote Monitoring.

    Science.gov (United States)

    Alsina-Pagès, Rosa Ma; Navarro, Joan; Alías, Francesc; Hervás, Marcos

    2017-04-13

    The consistent growth in human life expectancy during the recent years has driven governments and private organizations to increase the efforts in caring for the eldest segment of the population. These institutions have built hospitals and retirement homes that have been rapidly overfilled, making their associated maintenance and operating costs prohibitive. The latest advances in technology and communications envisage new ways to monitor those people with special needs at their own home, increasing their quality of life in a cost-affordable way. The purpose of this paper is to present an Ambient Assisted Living (AAL) platform able to analyze, identify, and detect specific acoustic events happening in daily life environments, which enables the medic staff to remotely track the status of every patient in real-time. Additionally, this tele-care proposal is validated through a proof-of-concept experiment that takes benefit of the capabilities of the NVIDIA Graphical Processing Unit running on a Jetson TK1 board to locally detect acoustic events. Conducted experiments demonstrate the feasibility of this approach by reaching an overall accuracy of 82% when identifying a set of 14 indoor environment events related to the domestic surveillance and patients' behaviour monitoring field. Obtained results encourage practitioners to keep working in this direction, and enable health care providers to remotely track the status of their patients in real-time with non-invasive methods.

  6. Short Personality and Life Event scale for detection of suicide attempters.

    Science.gov (United States)

    Artieda-Urrutia, Paula; Delgado-Gómez, David; Ruiz-Hernández, Diego; García-Vega, Juan Manuel; Berenguer, Nuria; Oquendo, Maria A; Blasco-Fontecilla, Hilario

    2015-01-01

    To develop a brief and reliable psychometric scale to identify individuals at risk for suicidal behaviour. Case-control study. 182 individuals (61 suicide attempters, 57 psychiatric controls, and 64 psychiatrically healthy controls) aged 18 or older, admitted to the Emergency Department at Puerta de Hierro University Hospital in Madrid, Spain. All participants completed a form including their socio-demographic and clinical characteristics, and the Personality and Life Events scale (27 items). To assess Axis I diagnoses, all psychiatric patients (including suicide attempters) were administered the Mini International Neuropsychiatric Interview. Descriptive statistics were computed for the socio-demographic factors. Additionally, χ(2) independence tests were applied to evaluate differences in socio-demographic and clinical variables, and the Personality and Life Events scale between groups. A stepwise linear regression with backward variable selection was conducted to build the Short Personality Life Event (S-PLE) scale. In order to evaluate the accuracy, a ROC analysis was conducted. The internal reliability was assessed using Cronbach's α, and the external reliability was evaluated using a test-retest procedure. The S-PLE scale, composed of just 6 items, showed good performance in discriminating between medical controls, psychiatric controls and suicide attempters in an independent sample. For instance, the S-PLE scale discriminated between past suicide and past non-suicide attempters with sensitivity of 80% and specificity of 75%. The area under the ROC curve was 88%. A factor analysis extracted only one factor, revealing a single dimension of the S-PLE scale. Furthermore, the S-PLE scale provides values of internal and external reliability between poor (test-retest: 0.55) and acceptable (Cronbach's α: 0.65) ranges. Administration time is about one minute. The S-PLE scale is a useful and accurate instrument for estimating the risk of suicidal behaviour in

  7. Electrical detection of specific versus non-specific binding events in breast cancer cells

    Science.gov (United States)

    King, Benjamin C.; Clark, Michael; Burkhead, Thomas; Sethu, Palaniappan; Rai, Shesh; Kloecker, Goetz; Panchapakesan, Balaji

    2012-10-01

    Detection of circulating tumor cells (CTCs) from patient blood samples offers a desirable alternative to invasive tissue biopsies for screening of malignant carcinomas. A rigorous CTC detection method must identify CTCs from millions of other formed elements in blood and distinguish them from healthy tissue cells also present in the blood. CTCs are known to overexpress surface receptors, many of which aid them in invading other tissue, and these provide an avenue for their detection. We have developed carbon nanotube (CNT) thin film devices to specifically detect these receptors in intact cells. The CNT sidewalls are functionalized with antibodies specific to Epithelial Cell Adhesion Molecule (EpCAM), a marker overexpressed by breast and other carcinomas. Specific binding of EpCAM to anti-EpCAM antibodies causes a change in the local charge environment of the CNT surface which produces a characteristic electrical signal. Two cell lines were tested in the device: MCF7, a mammary adenocarcinoma line which overexpresses EpCAM, and MCF10A, a non-tumorigenic mammary epithelial line which does not. Introduction of MCF7s caused significant changes in the electrical conductance of the devices due to specific binding and associated charge environment change near the CNT sidewalls. Introduction of MCF10A displays a different profile due to purely nonspecific interactions. The profile of specific vs. nonspecific interaction signatures using carbon based devices will guide development of this diagnostic tool towards clinical sample volumes with wide variety of markers.

  8. Detection of microsleep events in a car driving simulation study using electrocardiographic features

    OpenAIRE

    Lenis Gustavo; Reichensperger Patrick; Sommer David; Heinze Christian; Golz Martin; Dössel Olaf

    2016-01-01

    Microsleep events (MSE) are short intrusions of sleep under the demand of sustained attention. They can impose a major threat to safety while driving a car and are considered one of the most significant causes of traffic accidents. Driver’s fatigue and MSE account for up to 20% of all car crashes in Europe and at least 100,000 accidents in the US every year. Unfortunately, there is not a standardized test developed to quantify the degree of vigilance of a driver. To account for this problem, ...

  9. Detection of centimeter-sized meteoroid impact events in Saturn's F ring

    Science.gov (United States)

    Showalter, M. R.

    1998-01-01

    Voyager images reveal that three prominent clumps in Saturn's F ring were short-lived, appearing rapidly and then spreading and decaying in brightness over periods of approximately 2 weeks. These features arise from hypervelocity impacts by approximately 10-centimeter meteoroids into F ring bodies. Future ring observations of these impact events could constrain the centimeter-sized component of the meteoroid population, which is otherwise unmeasurable but plays an important role in the evolution of rings and surfaces in the outer solar system. The F ring's numerous other clumps are much longer lived and appear to be unrelated to impacts.

  10. myBlackBox: Blackbox Mobile Cloud Systems for Personalized Unusual Event Detection

    Directory of Open Access Journals (Sweden)

    Junho Ahn

    2016-05-01

    Full Text Available We demonstrate the feasibility of constructing a novel and practical real-world mobile cloud system, called myBlackBox, that efficiently fuses multimodal smartphone sensor data to identify and log unusual personal events in mobile users’ daily lives. The system incorporates a hybrid architectural design that combines unsupervised classification of audio, accelerometer and location data with supervised joint fusion classification to achieve high accuracy, customization, convenience and scalability. We show the feasibility of myBlackBox by implementing and evaluating this end-to-end system that combines Android smartphones with cloud servers, deployed for 15 users over a one-month period.

  11. Semi-automated camera trap image processing for the detection of ungulate fence crossing events.

    Science.gov (United States)

    Janzen, Michael; Visser, Kaitlyn; Visscher, Darcy; MacLeod, Ian; Vujnovic, Dragomir; Vujnovic, Ksenija

    2017-09-27

    Remote cameras are an increasingly important tool for ecological research. While remote camera traps collect field data with minimal human attention, the images they collect require post-processing and characterization before it can be ecologically and statistically analyzed, requiring the input of substantial time and money from researchers. The need for post-processing is due, in part, to a high incidence of non-target images. We developed a stand-alone semi-automated computer program to aid in image processing, categorization, and data reduction by employing background subtraction and histogram rules. Unlike previous work that uses video as input, our program uses still camera trap images. The program was developed for an ungulate fence crossing project and tested against an image dataset which had been previously processed by a human operator. Our program placed images into categories representing the confidence of a particular sequence of images containing a fence crossing event. This resulted in a reduction of 54.8% of images that required further human operator characterization while retaining 72.6% of the known fence crossing events. This program can provide researchers using remote camera data the ability to reduce the time and cost required for image post-processing and characterization. Further, we discuss how this procedure might be generalized to situations not specifically related to animal use of linear features.

  12. Combined passive detection and ultrafast active imaging of cavitation events induced by short pulses of high-intensity ultrasound

    Science.gov (United States)

    Gateau, Jérôme; Aubry, Jean-François; Pernot, Mathieu; Fink, Mathias; Tanter, Mickaël

    2011-01-01

    The activation of natural gas nuclei to induce larger bubbles is possible using short ultrasonic excitations of high amplitude, and is required for ultrasound cavitation therapies. However, little is known about the distribution of nuclei in tissues. Therefore, the acoustic pressure level necessary to generate bubbles in a targeted zone and their exact location are currently difficult to predict. In order to monitor the initiation of cavitation activity, a novel all-ultrasound technique sensitive to single nucleation events is presented here. It is based on combined passive detection and ultrafast active imaging over a large volume and with the same multi-element probe. Bubble nucleation was induced with a focused transducer (660kHz, f#=1) driven by a high power (up to 300 W) electric burst of one to two cycles. Detection was performed with a linear array (4–7MHz) aligned with the single-element focal point. In vitro experiments in gelatin gel and muscular tissue are presented. The synchronized passive detection enabled radio-frequency data to be recorded, comprising high-frequency coherent wave fronts as signatures of the acoustic emissions linked to the activation of the nuclei. Active change detection images were obtained by subtracting echoes collected in the unucleated medium. These indicated the appearance of stable cavitating regions. Thanks to the ultrafast frame rate, active detection occurred as soon as 330 μs after the high amplitude excitation and the dynamics of the induced regions were studied individually. PMID:21429844

  13. Event-related brain potentials reveal the time-course of language change detection in early bilinguals.

    Science.gov (United States)

    Kuipers, Jan-Rouke; Thierry, Guillaume

    2010-05-01

    Using event-related brain potentials, we investigated the temporal course of language change detection in proficient bilinguals as compared to matched controls. Welsh-English bilingual participants and English controls were presented with a variant of the oddball paradigm involving picture-word pairs. The language of the spoken word was manipulated such that English was the frequent stimulus (75%) and Welsh the infrequent stimulus (25%). We also manipulated semantic relatedness between pictures and words, such that only half of the pictures were followed by a word that corresponded with the identity of the picture. The P2 wave was significantly modulated by language in the bilingual group only, suggesting that this group detected a language change as early as 200 ms after word onset. Monolinguals also reliably detected the language change, but at a later stage of semantic integration (N400 range), since Welsh words were perceived as meaningless. The early detection of a language change in bilinguals triggered stimulus re-evaluation mechanisms reflected by a significant P600 modulation by Welsh words. Furthermore, compared to English unrelated words, English words matching the picture identity elicited significantly greater P2 amplitudes in the bilingual group only, suggesting that proficient bilinguals validate an incoming word against their expectation based on the context. Overall, highly proficient bilinguals appear to detect language changes very early on during speech perception and to consciously monitor language changes when they occur. 2010 Elsevier Inc. All rights reserved.

  14. Saharan dust events at the Jungfraujoch: detection by wavelength dependence of the single scattering albedo and first climatology analysis

    Directory of Open Access Journals (Sweden)

    M. Collaud Coen

    2004-01-01

    Full Text Available Scattering and absorption coefficients have been measured continuously at several wavelengths since March 2001 at the high altitude site Jungfraujoch (3580ma.s.l.. From these data, the wavelength dependences of the Ångström exponent and particularly of the single scattering albedo are determined. While the exponent of the single scattering albedo usually increases with wavelength, it decreases with wavelength during Saharan dust events (SDE due to the greater size of the mineral aerosol particles and their different chemical composition. This change in the sign of the single scattering exponent turns out to be a sensitive means for detecting Saharan dust events. The occurrence of SDE detected by this new method was confirmed by visual inspection of filter colors and by studying long-range back-trajectories. An examination of SDE over a 22-month period shows that SDE are more frequent during the March-June period as well as during October and November. The trajectory analysis indicated a mean traveling time of 96.5h, with the most important source countries situated in the northern and north-western part of the Saharan desert. Most of the SDE do not lead to a detectable increase of the 48-h total suspended particulate matter (TSP concentration at the Jungfraujoch. During Saharan dust events, the average contribution of this dust to hourly TSP at the Jungfraujoch is 16µg/m3, which corresponds to an annual mean of 0.8µg/m3 or 24% of TSP.

  15. Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water

    Science.gov (United States)

    Schmidt, F.; Liu, S.

    2016-12-01

    Source water quality plays an important role for the safety of drinking water and early detection of its contamination is vital to taking appropriate countermeasures. However, compared to drinking water, it is more difficult to detect contamination events because its environment is less controlled and numerous natural causes contribute to a high variability of the background values. In this project, Artificial Neural Networks (ANNs) and a Contamination Event Detection Process (CED Process) were used to identify events in river water. The ANN models the response of basic water quality sensors obtained in laboratory experiments in an off-line learning stage and continuously forecasts future values of the time line in an on-line forecasting step. During this second stage, the CED Process compares the forecast to the measured value and classifies it as regular background or event value, which modifies the ANN's continuous learning and influences its forecasts. In addition to this basic setup, external information is fed to the CED Process: A so-called Operator Input (OI) is provided to inform about unusual water quality levels that are unrelated to the presence of contamination, for example due to cooling water discharge from a nearby power plant. This study's primary goal is to evaluate how well the OI fits into the design of the combined forecasting ANN and CED Process and to understand its effects on the online forecasting stage. To test this, data from laboratory experiments conducted previously at the School of Environment, Tsinghua University, have been used to perform simulations highlighting features and drawbacks of this method. Applying the OI has been shown to have a positive influence on the ANN's ability to handle a sudden change in background values, which is unrelated to contamination. However, it might also mask the presence of an event, an issue that underlines the necessity to have several instances of the algorithm run in parallel. Other difficulties

  16. Near Real-Time Event Detection & Prediction Using Intelligent Software Agents

    Science.gov (United States)

    2006-03-01

    network structures until the late 1980’s. In 1986, Rumelhart, Hinton, and Williams announced the discovery of a new learning algorithm that eliminated...network model for detecting changes in the process mean. Computers ind. Engng 28, 51-61. [26] Coca, D., Billings , S.A. A direct approach to...Sicily (Italy). Chaos Solitons & Fractals 23: 1921-1929, 2005. [30] Curtis, Myron. Computer programs for obtaining kinetic data on human movement

  17. The Diurnal Variation of the Wimp Detection Event Rates in Directional Experiments

    OpenAIRE

    Vergados, J D; Moustakidis, Ch. C.

    2009-01-01

    The recent WMAP data have confirmed that exotic dark matter together with the vacuum energy (cosmological constant) dominate in the flat Universe. Modern particle theories naturally provide viable cold dark matter candidates with masses in the GeV-TeV region. Supersymmetry provides the lightest supersymmetric particle (LSP), theories in extra dimensions supply the lightest Kaluza-Klein particle (LKP) etc. The nature of dark matter can only be unraveled only by its direct detection in the labo...

  18. Mobile Sensor Networks: A Discrete Event Simulation of WMD Threat Detection in Urban Traffic Schemes

    Science.gov (United States)

    2007-03-01

    sample space. A “penalized edge weighter” allows the Dijkstra algorithm to excessively penalize roads with speed categorizations above a fixed value...debarkation, etc. Despite the low likelihood of detection at each stage, an attack would need to successfully navigate all wickets in order to execute...Various random search algorithms exist for open fields of movement and are widely studied and used in anti-submarine warfare and ocean surface search

  19. Target Word-Specific Experiment by Detecting Event-Related Potential for ALS Patients

    Science.gov (United States)

    Kanou, Naoyuki; Sakuma, Kenji; Nakashima, Kenji

    For communication of ALS patients, the authors put emphasis on ERP. This paper described that ALS patient could get high rate of correct judgment on the target word-specific experiment by detecting ERP. For practical use, it is very important that ALS patients can communicate with surrounding person smoothly. The authors discussed how to shorten the time to specify the target word, and discussed the prevention of misjudgment.

  20. Evaluating Monitoring Strategies to Detect Precipitation-Induced Microbial Contamination Events in Karstic Springs Used for Drinking Water

    Directory of Open Access Journals (Sweden)

    Michael D. Besmer

    2017-11-01

    Full Text Available Monitoring of microbial drinking water quality is a key component for ensuring safety and understanding risk, but conventional monitoring strategies are typically based on low sampling frequencies (e.g., quarterly or monthly. This is of concern because many drinking water sources, such as karstic springs are often subject to changes in bacterial concentrations on much shorter time scales (e.g., hours to days, for example after precipitation events. Microbial contamination events are crucial from a risk assessment perspective and should therefore be targeted by monitoring strategies to establish both the frequency of their occurrence and the magnitude of bacterial peak concentrations. In this study we used monitoring data from two specific karstic springs. We assessed the performance of conventional monitoring based on historical records and tested a number of alternative strategies based on a high-resolution data set of bacterial concentrations in spring water collected with online flow cytometry (FCM. We quantified the effect of increasing sampling frequency and found that for the specific case studied, at least bi-weekly sampling would be needed to detect precipitation events with a probability of >90%. We then proposed an optimized monitoring strategy with three targeted samples per event, triggered by precipitation measurements. This approach is more effective and efficient than simply increasing overall sampling frequency. It would enable the water utility to (1 analyze any relevant event and (2 limit median underestimation of peak concentrations to approximately 10%. We conclude with a generalized perspective on sampling optimization and argue that the assessment of short-term dynamics causing microbial peak loads initially requires increased sampling/analysis efforts, but can be optimized subsequently to account for limited resources. This offers water utilities and public health authorities systematic ways to evaluate and optimize their

  1. A new method for detecting interactions between the senses in event-related potentials

    DEFF Research Database (Denmark)

    Gondan, Matthias; Röder, B.

    2006-01-01

    not contain common activity: This activity would be subtracted twice from one ERP and would, therefore, contaminate the result. In the present study, ERPs to unimodal, bimodal, and trimodal auditory, visual, and tactile stimuli (T) were recorded. We demonstrate that (T + TAV) - (TA + TV) is equivalent to AV......Event-related potentials (ERPs) can be used in multisensory research to determine the point in time when different senses start to interact, for example, the auditory and the visual system. For this purpose, the ERP to bimodal stimuli (AV) is often compared to the sum of the ERPs to auditory (A......) and visual (V) stimuli: AV - (A + V). If the result is non-zero, this is interpreted as an indicator for multisensory interactions. Using this method, several studies have demonstrated auditory-visual interactions as early as 50 ms after stimulus onset. The subtraction requires that A, V, and AV do...

  2. Efficient Data Collection and Event Boundary Detection in Wireless Sensor Networks Using Tiny Models

    Science.gov (United States)

    King, Kraig; Nittel, Silvia

    Using wireless geosensor networks (WGSN), sensor nodes often monitor a phenomenon that is both continuous in time and space. However, sensor nodes take discrete samples, and an analytical framework inside or outside the WSN is used to analyze the phenomenon. In both cases, expensive communication is used to stream a large number of data samples to other nodes and to the base station. In this work, we explore a novel alternative that utilizes predictive process knowledge of the observed phenomena to minimize upstream communication. Often, observed phenomena adhere to a process with predictable behavior over time. We present a strategy for developing and running so-called 'tiny models' on individual sensor nodes that capture the predictable behavior of the phenomenon; nodes now only communicate when unexpected events are observed. Using multiple simulations, we demonstrate that a significant percentage of messages can be reduced during data collection.

  3. Can social media data lead to earlier detection of drug-related adverse events?

    Science.gov (United States)

    Duh, Mei Sheng; Cremieux, Pierre; Audenrode, Marc Van; Vekeman, Francis; Karner, Paul; Zhang, Haimin; Greenberg, Paul

    2016-12-01

    To compare the patient characteristics and the inter-temporal reporting patterns of adverse events (AEs) for atorvastatin (Lipitor® ) and sibutramine (Meridia® ) in social media (AskaPatient.com) versus the FDA Adverse Event Reporting System (FAERS). We identified clinically important AEs associated with atorvastatin (muscle pain) and sibutramine (cardiovascular AEs), compared their patterns in social media postings versus FAERS and used Granger causality tests to assess whether social media postings were useful in forecasting FAERS reports. We analyzed 998 and 270 social media postings between 2001 and 2014, 69 003 and 7383 FAERS reports between 1997 and 2014 for atorvastatin and sibutramine, respectively. Social media reporters were younger (atorvastatin: 53.9 vs. 64.0 years, p Social media reviews contained fewer serious AEs (atorvastatin, pain: 2.5% vs. 38.2%; sibutramine, cardiovascular issues: 7.9% vs. 63.0%; p social media sibutramine reviews mentioning cardiac issues helped predict those in FAERS 11 months later (p social media atorvastatin reviews did not help predict FAERS reports. Social media AE reporters were younger and focused on less-serious and fewer types of AEs than FAERS reporters. The potential for social media to provide earlier indications of AEs compared with FAERS is uncertain. Our findings highlight some of the promises and limitations of online social media versus conventional pharmacovigilance sources and the need for careful interpretation of the results. © 2016 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd. © 2016 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.

  4. Sequence Symmetry Analysis as a Signal Detection Tool for Potential Heart Failure Adverse Events in an Administrative Claims Database.

    Science.gov (United States)

    Wahab, Izyan A; Pratt, Nicole L; Ellett, Lisa Kalisch; Roughead, Elizabeth E

    2016-04-01

    The potential for routine sequence symmetry analysis (SSA) signal detection in health claims databases to detect new safety signals of medicines is unknown. Our objective was to assess the potential utility of SSA as a signal detection tool in health claims data for detecting medicines with potential heart failure (HF) adverse event signals. We applied the SSA method to all subsidized single-ingredient medicines in Australia. The source of data was the Australian Government Department of Veterans' Affairs (DVA) administrative claims database using data collected between 2002 and 2011. We used first ever HF hospitalization and frusemide initiation as indicators for HF. A signal was considered to be present if the lower limit of the 95 % confidence interval for the adjusted sequence ratio was greater than one. To identify potential new signals of HF, we excluded medicines where HF or edema was listed in the product information (PI) of that medicine or for any other medicine in the same class. We also excluded medicines that were used in HF treatment and medicines indicated for diseases that may contribute to the development of HF. We tested 691 medicines. HF signals were detected for 12 % (80/691) using the hospitalization event and 22 % (153/691) using frusemide initiation. Among medicines that did not have HF listed in the PI, SSA found 11 % (44/397) associated with HF hospitalization and 15 % (60/397) associated with frusemide initiation. Of the medicines tested in which no other medicine in the same class had HF or edema in the PI, and where the medicine was not indicated for a disease that is a risk factor for HF, potential new signals were generated for 2-3 % of these medicines tested (12 of 397 medicines using HF hospitalization and 9 of 397 medicines using frusemide initiation). SSA generated potential new signals of HF for some anti-glaucoma and anti-dyspepsia medicines. For some of the potential signals, the event is biologically plausible and some have pre

  5. Amperometric detection of single vesicle acetylcholine release events from an artificial cell.

    Science.gov (United States)

    Keighron, Jacqueline D; Wigström, Joakim; Kurczy, Michael E; Bergman, Jenny; Wang, Yuanmo; Cans, Ann-Sofie

    2015-01-21

    Acetylcholine is a highly abundant nonelectroactive neurotransmitter in the mammalian central nervous system. Neurochemical release occurs on the millisecond time scale, requiring a fast, sensitive sensor such as an enzymatic amperometric electrode. Typically, the enzyme used for enzymatic electrochemical sensors is applied in excess to maximize signal. Here, in addition to sensitivity, we have also sought to maximize temporal resolution, by designing a sensor that is sensitive enough to work at near monolayer enzyme coverage. Reducing the enzyme layer thickness increases sensor temporal resolution by decreasing the distance and reducing the diffusion time for the enzyme product to travel to the sensor surface for detection. In this instance, the sensor consists of electrodeposited gold nanoparticle modified carbon fiber microelectrodes (CFMEs). Enzymes often are sensitive to curvature upon surface adsorption; thus, it was important to deposit discrete nanoparticles to maintain enzyme activity while depositing as much gold as possible to maximize enzyme coverage. To further enhance sensitivity, the enzymes acetylcholinesterase (AChE) and choline oxidase (ChO) were immobilized onto the gold nanoparticles at the previously determined optimal ratio (1:10 AChE/ChO) for most efficient sequential enzymatic activity. This optimization approach has enabled the rapid detection to temporally resolve single vesicle acetylcholine release from an artificial cell. The sensor described is a significant advancement in that it allows for the recording of acetylcholine release on the order of the time scale for neurochemical release in secretory cells.

  6. [The possibility of a multiresolution wavelet analysis for detecting the P300 event related potential].

    Science.gov (United States)

    Aldea, Roxana; Lazăr, Anca Mihaela

    2012-01-01

    The main objective is to high-light the P300 potential on certain electroencephalographic signals. P300 occurs at a relatively well defined time in relation to a stimulus and it represents a signal with a specified band frequency. The electroencephalographic (EEG) was recorded with 4 wet electrodes by means of g.MOBIlab+ module, a g.tec acquisition system. The multiresolution wavelet transform was chosen to extract the P300 potential from the EEG signal because it provides information on both time and frequency domains. The multiresolution wavelet transform decomposes the signal in sub-bands and it helps to highlight the P300 potential. The spectrum of the P300 potential is around 3Hz. For the multiresolution wavelet decomposition this corresponds to coefficients of approximation of order 4 according to 0 to 60 Hz band of the original EEG signal. The representation of these coefficients emphasizes a better detection of P300 potential then in the original signal. It is shown to be a more appropriate method than the direct analysis of the signal because it works with lower dimensional signals. This method of detection of the P300 potential can be used successfully in the implementation of a Brain Computer Interface (BCI).

  7. Clinical Experiments of Communication by ALS Patient Utilizing Detecting Event-Related Potential

    Science.gov (United States)

    Kanou, Naoyuki; Sakuma, Kenji; Nakashima, Kenji

    Amyotrophic Lateral Sclerosis(ALS) patients are unable to successfully communicate their desires, although their mentality is normal, and so, the necessity of Communication Aids(CA) for ALS patients is realized. Therefore, the authors are focused on Event-Related Potential(ERP) which is elicited primarily for the target by visual and auditory stimuli. P200, N200 and P300 are components of ERP. These are potentials that are elicited when the subject focuses attention on stimuli that appears infrequently. ALS patient participated in two experiments. In the first experiment, a target word out of five words on a computer display was specified. The five words were linked to an each electric appliance, allowing the ALS patient to switch on a target appliance by ERP. In the second experiment, a target word in a 5×5 matrix was specified by measure of ERP. The rows and columns of the matrix were reversed randomly. The word on a crossing point of rows and columns including the target word, was specified as the target word. The rate of correct judgment in the first and second experiments were 100% in N200 and 96% in P200. For practical use of this system, it is very important to determine suitable communication algorithms for each patient by performing these experiments evaluating the results.

  8. a Topic Modeling Based Representation to Detect Tweet Locations. Example of the Event "je Suis Charlie"

    Science.gov (United States)

    Morchid, M.; Josselin, D.; Portilla, Y.; Dufour, R.; Altman, E.; Linarès, G.

    2015-09-01

    Social Networks became a major actor in information propagation. Using the Twitter popular platform, mobile users post or relay messages from different locations. The tweet content, meaning and location, show how an event-such as the bursty one "JeSuisCharlie", happened in France in January 2015, is comprehended in different countries. This research aims at clustering the tweets according to the co-occurrence of their terms, including the country, and forecasting the probable country of a non-located tweet, knowing its content. First, we present the process of collecting a large quantity of data from the Twitter website. We finally have a set of 2,189 located tweets about "Charlie", from the 7th to the 14th of January. We describe an original method adapted from the Author-Topic (AT) model based on the Latent Dirichlet Allocation (LDA) method. We define an homogeneous space containing both lexical content (words) and spatial information (country). During a training process on a part of the sample, we provide a set of clusters (topics) based on statistical relations between lexical and spatial terms. During a clustering task, we evaluate the method effectiveness on the rest of the sample that reaches up to 95% of good assignment. It shows that our model is pertinent to foresee tweet location after a learning process.

  9. [Event-related EEG potentials associated with error detection in psychiatric disorder: literature review].

    Science.gov (United States)

    Balogh, Lívia; Czobor, Pál

    2010-01-01

    Error-related bioelectric signals constitute a special subgroup of event-related potentials. Researchers have identified two evoked potential components to be closely related to error processing, namely error-related negativity (ERN) and error-positivity (Pe), and they linked these to specific cognitive functions. In our article first we give a brief description of these components, then based on the available literature, we review differences in error-related evoked potentials observed in patients across psychiatric disorders. The PubMed and Medline search engines were used in order to identify all relevant articles, published between 2000 and 2009. For the purpose of the current paper we reviewed publications summarizing results of clinical trials. Patients suffering from schizophrenia, anorexia nervosa or borderline personality disorder exhibited a decrease in the amplitude of error-negativity when compared with healthy controls, while in cases of depression and anxiety an increase in the amplitude has been observed. Some of the articles suggest specific personality variables, such as impulsivity, perfectionism, negative emotions or sensitivity to punishment to underlie these electrophysiological differences. Research in the field of error-related electric activity has come to the focus of psychiatry research only recently, thus the amount of available data is significantly limited. However, since this is a relatively new field of research, the results available at present are noteworthy and promising for future electrophysiological investigations in psychiatric disorders.

  10. Impact of health information technology on detection of potential adverse drug events at the ordering stage.

    Science.gov (United States)

    Roberts, Lance L; Ward, Marcia M; Brokel, Jane M; Wakefield, Douglas S; Crandall, Donald K; Conlon, Paul

    2010-11-01

    The impact of implementing commercially available health care information technologies at hospitals in a large health system on the identification of potential adverse drug events (ADEs) at the medication ordering stage was studied. All hospitals in the health system had implemented a clinical decision-support system (CDSS) consisting of a centralized clinical data repository, interfaces for reports, a results reviewer, and a package of ADE alert rules. Additional technology including computerized provider order entry (CPOE), an advanced CDSS, and evidence-based order sets was implemented in nine hospitals. ADE alerts at these hospitals were compared with alerts at nine hospitals without the advanced technology. A linear mixed-effects model was used in determining the mean response profile of six dependent variables over 28 total months for each experimental group. Overall, hospitals with CPOE and an advanced CDSS captured significantly more ADE alerts for pharmacist review; an average of 336 additional potential ADEs per month per hospital were reviewed. Pharmacists identified some 94% of the alerts as false positives. Alerts identified as potentially true positives were reviewed with physicians, and order changes were recommended. The number of true-positive alerts per 1000 admissions increased. The implementation of CPOE and advanced CDSS tools significantly increased the number of potential ADE alerts for pharmacist review and the number of true-positive ADE alerts identified per 1000 admissions.

  11. Dopaminergic mechanisms of target detection - P300 event related potential and striatal dopamine.

    Science.gov (United States)

    Pogarell, Oliver; Padberg, Frank; Karch, Susanne; Segmiller, Felix; Juckel, Georg; Mulert, Christoph; Hegerl, Ulrich; Tatsch, Klaus; Koch, Walter

    2011-12-30

    The P300 is a cortically generated event related potential (ERP) widely used in neurophysiological research since it is related to cognitive functions and central information processing. Intracerebral recordings and functional neuroimaging studies have demonstrated that this potential is generated by various brain regions including frontal, temporal and parietal cortices. Regarding the neurochemical background, clinical and genetic investigations suggest that dopaminergic neurons could be involved in the generation of the P300. However, there is no direct evidence in vivo that P300 amplitudes and latencies are related to dopaminergic parameters. The aim of this study was to further elucidate dopaminergic aspects of the P300 ERP by combining neurophysiological and nuclear medicine assessments in vivo. Patients with a major depressive episode underwent both P300 recordings and dynamic [¹²³I] IBZM SPECT for the evaluation of striatal dopamine D₂/D₃-receptor availability. There were statistically significant positive correlations of the striatal dopamine D₂/D₃-receptor status with P300 amplitudes and significant negative correlations with P300 latencies. Using this combined approach, the study presents direct evidence in vivo that the central dopaminergic system might play an important role in the generation of the P300 and that central dopaminergic activity could be involved in the modulation of P300 parameters. This association might be of relevance for the interpretation of P300 studies in psychiatric disorders. 2011 Elsevier Ireland Ltd. All rights reserved.

  12. Accuracy and precision of equine gait event detection during walking with limb and trunk mounted inertial sensors

    DEFF Research Database (Denmark)

    Olsen, Emil; Andersen, Pia Haubro; Pfau, Thilo

    2012-01-01

    . Accuracy (bias) and precision (SD of bias) was calculated to compare force plate and IMU timings for gait events. Data were collected from seven horses. One hundred and twenty three (123) front limb steps were analysed; hoof-on was detected with a bias (SD) of -7 (23) ms, hoof-off with 0.7 (37) ms...... Measurement Units (IMUs). Four IMUs were mounted on the distal limb and five IMUs were attached to the skin over the dorsal spinous processes at the withers, fourth lumbar vertebrae and sacrum as well as left and right tuber coxae. IMU data were synchronised to a force plate array and a motion capture system...... and front limb stance with -0.02 (37) ms. A total of 119 hind limb steps were analysed; hoof-on was found with a bias (SD) of -4 (25) ms, hoof-off with 6 (21) ms and hind limb stance with 0.2 (28) ms. IMUs mounted on the distal limbs and sacrum can detect gait events accurately and precisely....

  13. Secondary scintillation yield of xenon with sub-percent levels of CO2 additive for rare-event detection

    Science.gov (United States)

    Henriques, C. A. O.; Freitas, E. D. C.; Azevedo, C. D. R.; González-Díaz, D.; Mano, R. D. P.; Jorge, M. R.; Fernandes, L. M. P.; Monteiro, C. M. B.; Gómez-Cadenas, J. J.; Álvarez, V.; Benlloch-Rodríguez, J. M.; Borges, F. I. G. M.; Botas, A.; Cárcel, S.; Carríon, J. V.; Cebrían, S.; Conde, C. A. N.; Díaz, J.; Diesburg, M.; Esteve, R.; Felkai, R.; Ferrario, P.; Ferreira, A. L.; Goldschmidt, A.; Gutiérrez, R. M.; Hauptman, J.; Hernandez, A. I.; Hernando Morata, J. A.; Herrero, V.; Jones, B. J. P.; Labarga, L.; Laing, A.; Lebrun, P.; Liubarsky, I.; López-March, N.; Losada, M.; Martín-Albo, J.; Martínez-Lema, G.; Martínez, A.; McDonald, A. D.; Monrabal, F.; Mora, F. J.; Moutinho, L. M.; Muñoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Nygren, D. R.; Palmeiro, B.; Para, A.; Pérez, J.; Querol, M.; Renner, J.; Ripoll, L.; Rodríguez, J.; Rogers, L.; Santos, F. P.; dos Santos, J. M. F.; Simón, A.; Sofka, C.; Sorel, M.; Stiegler, T.; Toledo, J. F.; Torrent, J.; Tsamalaidze, Z.; Veloso, J. F. C. A.; Webb, R.; White, J. T.; Yahlali, N.; NEXT Collaboration

    2017-10-01

    Xe-CO2 mixtures are important alternatives to pure xenon in Time Projection Chambers (TPC) based on secondary scintillation (electroluminescence) signal amplification with applications in the important field of rare event detection such as directional dark matter, double electron capture and double beta decay detection. The addition of CO2 to pure xenon at the level of 0.05-0.1% can reduce significantly the scale of electron diffusion from 10 mm /√{m} to 2.5 mm /√{m}, with high impact on the discrimination efficiency of the events through pattern recognition of the topology of primary ionization trails. We have measured the electroluminescence (EL) yield of Xe-CO2 mixtures, with sub-percent CO2 concentrations. We demonstrate that the EL production is still high in these mixtures, 70% and 35% relative to that produced in pure xenon, for CO2 concentrations around 0.05% and 0.1%, respectively. The contribution of the statistical fluctuations in EL production to the energy resolution increases with increasing CO2 concentration, being smaller than the contribution of the Fano factor for concentrations below 0.1% CO2.

  14. Secondary scintillation yield of xenon with sub-percent levels of CO2 additive for rare-event detection

    Directory of Open Access Journals (Sweden)

    C.A.O. Henriques

    2017-10-01

    Full Text Available Xe–CO2 mixtures are important alternatives to pure xenon in Time Projection Chambers (TPC based on secondary scintillation (electroluminescence signal amplification with applications in the important field of rare event detection such as directional dark matter, double electron capture and double beta decay detection. The addition of CO2 to pure xenon at the level of 0.05–0.1% can reduce significantly the scale of electron diffusion from 10 mm/m to 2.5 mm/m, with high impact on the discrimination efficiency of the events through pattern recognition of the topology of primary ionization trails. We have measured the electroluminescence (EL yield of Xe–CO2 mixtures, with sub-percent CO2 concentrations. We demonstrate that the EL production is still high in these mixtures, 70% and 35% relative to that produced in pure xenon, for CO2 concentrations around 0.05% and 0.1%, respectively. The contribution of the statistical fluctuations in EL production to the energy resolution increases with increasing CO2 concentration, being smaller than the contribution of the Fano factor for concentrations below 0.1% CO2.

  15. Application of stochastic discrete event system framework for detection of induced low rate TCP attack.

    Science.gov (United States)

    Barbhuiya, F A; Agarwal, Mayank; Purwar, Sanketh; Biswas, Santosh; Nandi, Sukumar

    2015-09-01

    TCP is the most widely accepted transport layer protocol. The major emphasis during the development of TCP was its functionality and efficiency. However, not much consideration was given on studying the possibility of attackers exploiting the protocol, which has lead to several attacks on TCP. This paper deals with the induced low rate TCP attack. Since the attack is relatively new, only a few schemes have been proposed to mitigate it. However, the main issues with these schemes are scalability, change in TCP header, lack of formal frameworks, etc. In this paper, we have adapted the stochastic DES framework for detecting the attack, which addresses most of these issues. We have successfully deployed and tested the proposed DES based IDS on a test bed. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Ex-vivo detection of neural events using THz BioMEMS

    CERN Document Server

    Abbas, Abdennour; Croix, Dominique; Salzet, Michel; Bocquet, Bertrand

    2009-01-01

    Background: Electromagnetic frequencies up to a few terahertz (THz) can yield real-time and noninvasive measurements on biological matter. Unfortunately, strong absorption in aqueous solutions and low spatial resolution return difficult free-space investigations. A new approach based on integrated THz circuits was used. The authors designed and fabricated a BioMEMS (Biological MicroElectro-Mechanical System) compatible with microfluidic circulation and electromagnetic propagation. It is dedicated to the ex vivo detection of nitric oxide synthase (NOS) activity, which is involved in neurodegenerative phenomena. Material/Methods: The biological model was a leech's central nervous system. After its injury, the production of NO was observed and measured in the far-THz spectral domain. The nerve cord was put inside a BioMEMS realized in polydimethylsiloxane (PDMS) sealed on a glass wafer. Glass is a good material for supporting high-frequency integrated waveguides such as coplanar waveguides (CPWs). Measurements w...

  17. Detection of pollution transport events southeast of Mexico City using ground-based visible spectroscopy measurements of nitrogen dioxide

    Directory of Open Access Journals (Sweden)

    M. Grutter

    2009-07-01

    Full Text Available This work presents ground based differential optical absorption spectroscopy (DOAS measurements of nitrogen dioxide (NO2 during the MILAGRO field campaign in March 2006 at the Tenango del Aire research site located to the southeast of Mexico City. The DOAS NO2 column density measurements are used in conjunction with ceilometer, meteorological and surface nitric oxide (NO, nitrogen oxides (NOx and total reactive nitrogen (NOy measurements to analyze pollution transport events to the southeast of Mexico City during the MILARGO field campaign. The study divides the data set into three case study pollution transport events that occurred at the Tenango del Aire research site. The unique data set is then used to provide an in depth analysis of example days of each of the pollution transport events. An in depth analysis of 13 March 2006, a Case One day, shows the transport of several air pollution plumes during the morning through the Tenango del Aire research site when southerly winds are present and demonstrates how DOAS tropospheric NO2 vertical column densities (VCD, surface NO2 mixing ratios and ceilometer data are used to determine the vertical homogeneity of the pollution layer. The analysis of 18 March 2006, a Case Two day, shows that when northerly winds are present for the entire day, the air at the Tenango del Aire research site is relatively clean and no major pollution plumes are detected. Case 3 days are characterized by relatively clean air throughout the morning with large DOAS NO2 enhancements detected in the afternoon. The analysis of 28 March 2006 show the DOAS NO2 enhancements are likely due to lightning activity and demonstrate how suitable ground-based DOAS measruements are for monitoring anthropogenic and natural pollution sources that reside above the mixing layer.

  18. Reconstruction of the Magnetkoepfl rockfall event - Detecting rock fall release zones using terrestrial laser scanning, Hohe Tauern, Austria

    Science.gov (United States)

    Hartmeyer, I.; Keuschnig, M.; Delleske, R.; Schrott, L.

    2012-04-01

    Instability of rock faces in high mountain areas is an important risk factor for man and infrastructure, particularly within the context of climate change. Numerous rock fall events in the European Alps suggest an increasing occurrence of mass movements due to rising temperatures in recent years. Within the MOREXPERT project ('Monitoring Expert System for Hazardous Rock Walls') a new long-term monitoring site for mass movement and permafrost interaction has been initiated in the Austrian Alps. The study area is located at the Kitzsteinhorn (Hohe Tauern), a particularly interesting site for the investigation of glacier retreat and potential permafrost degradation and their respective consequences for the stability of alpine rock faces. To detect and quantify changes occurring at the terrain surface an extensive terrestrial laser scanning (TLS) monitoring campaign was started in 2011. TLS creates three-dimensional high-resolution images of the scanned area allowing precise quantification of changes in geometry and volume in steep rock faces over distances of up to several hundreds of meters. Within the TLS monitoring campaign at the Kitzsteinhorn a large number of differently dimensioned rock faces is examined (varying size, slope inclination etc.). Scanned areas include the Kitzsteinhorn northwest and south face, the Magnetkoepfl east face as well as a couple of small rock faces in the vicinity of the summit station. During the night from August 27th to August 28th 2011 a rock fall event was documented by employees of the cable car company. The release zone could not immediately be detected. The east face of the Magnetkoepfl covers approximately 70 meters in height and about 200 meters in width. It is made up of calcareous mica-schist and displays an abundance of well-developed joint sets with large joint apertures. Meteorological data from a weather station located at the same altitude (2.950m) and just 500m away from the release zone show that the rock fall event

  19. [Compliance with the surgical safety checklist and surgical events detected by the Global Trigger Tool].

    Science.gov (United States)

    Menéndez Fraga, M D; Cueva Álvarez, M A; Franco Castellanos, M R; Fernández Moral, V; Castro Del Río, M P; Arias Pérez, J I; Fernández León, A; Vázquez Valdés, F

    2016-06-01

    The implementing of the WHO Surgical Safety Checklist (SSC) has helped to improve patient safety. The aim of this study was to assess the level of compliance of the SSC, and incorporating the non-compliances as «triggers» in the Global Trigger Tool (GTT). Acute Geriatric Hospital (200 beds). Retrospective study, study period: 2011-2014. The SSC formulary and the methodology of the GTT were used for the analysis of electronic medical records and the compliance with the SSC. The NCCP MERP categories were used to assess the severity of the harm. Out of all the electronic medical records (EMR), a total of 227 (23.6%) discharged patients (1.7% of interventions in the four year study period) were analysed. All (100%) of the EMR included the SSC, with 94.4% of the items being completed, and 28.2% of SSC had all items completed in the 3 phases of the process. Surgical adverse events decreased from 16.3% in 2011 to 9.4% in 2014 (P=.2838, not significant), and compliance with all items of SSC was increased from 18.6% to 39.1% (P=.0246, significant). The GTT systematises and evaluates, at low cost, the triggers and incidents/ AEs found in the EMR in order to assess the compliance with the SSC and consider non-compliance of SSC as «triggers» for further analysis. This strategy has never been referred to in the GTT or in the SCC formulary. Copyright © 2016 SECA. Published by Elsevier Espana. All rights reserved.

  20. Detection of Fractal Behavior in Temporal Series of Synaptic Quantal Release Events: A Feasibility Study

    Directory of Open Access Journals (Sweden)

    Jacopo Lamanna

    2012-01-01

    Full Text Available Since the pioneering work of Fatt and Katz at the neuromuscular junction (NMJ, spontaneous synaptic release (minis, that is, the quantal discharge of neurotransmitter molecules which occurs in the absence of action potentials, has been unanimously considered a memoryless random Poisson process where each quantum is discharged with a very low release probability independently from other quanta. When this model was thoroughly tested, for both population and single-synapse recordings, some clear evidence in favor of a more complex scenario emerged. This included short- and long-range correlation in mini occurrences and divergence from mono-exponential inter-mini-interval distributions, both unexpected for a homogeneous Poisson process, that is, with a rate parameter that does not change over time. Since we are interested in accurately quantifying the fractal exponent α of the spontaneous neurotransmitter release process at central synaptic sites, this work was aimed at evaluating the sensitivity of the most established methods available, such as the periodogram, the Allan, factor and the detrended fluctuation analysis. For this analysis we matched spontaneous release series recorded at individual hippocampal synapses (single-synapse recordings to generate large collections of simulated quantal events by means of a custom algorithm combining Monte Carlo sampling methods with spectral methods for the generation of 1/f series. These tests were performed by varying separately: (i the fractal exponent α of the rate driving the release process; (ii the distribution of intervals between successive releases, mimicking those encountered in single-synapse experimental series; (iii the number of samples. The aims were to provide a methodological framework for approaching the fractal analysis of single-unit spontaneous release series recorded at central synapses.

  1. Detecting kinematic boundary surfaces in phase space and particle mass measurements in SUSY-like events

    CERN Document Server

    2016-01-01

    We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain $\\tilde q\\to \\tilde\\chi^0_2\\to \\tilde \\ell \\to \\tilde \\chi^0_1$, we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, $\\bar\\Sigma$, which is ...

  2. Detecting kinematic boundary surfaces in phase space: particle mass measurements in SUSY-like events

    Science.gov (United States)

    Debnath, Dipsikha; Gainer, James S.; Kilic, Can; Kim, Doojin; Matchev, Konstantin T.; Yang, Yuan-Pao

    2017-06-01

    We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain \\tilde{q}\\to {\\tilde{χ}}_2^0\\to \\tilde{ℓ}\\to {\\tilde{χ}}_1^0 , we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, \\overline{Σ} , which is the average RSD per unit area, calculated over the hypothesized boundary. We show that the location of the \\overline{Σ} maximum correlates very well with the true values of the new particle masses. Our approach represents the natural extension of the one-dimensional kinematic endpoint method to the relevant three dimensions of invariant mass phase space.

  3. Age Dating Merger Events in Early Type Galaxies via the Detection of AGB Light

    Science.gov (United States)

    Bothun, G.

    2005-01-01

    A thorough statistical analysis of the J-H vs. H-K color plane of all detected early type galaxies in the 2MASS catalog with velocities less than 5000 km/s has been performed. This all sky survey is not sensitive to one particular galactic environment and therefore a representative range of early type galaxy environments have been sampled. Virtually all N-body simulation so major mergers produces a central starburst due to rapid collection of gas. This central starburst is of sufficient amplitude to change the stellar population in the central regions of the galaxy. Intermediate age populations are given away by the presence of AGB stars which will drive the central colors redder in H-K relative to the J- H baseline. This color anomaly has a lifetime of 2-5 billion years depending on the amplitude of the initial starburst Employing this technique on the entire 2MASS sample (several hundred galaxies) reveals that the AGB signature occurs less than 1% of the time. This is a straightforward indication that virtually all nearby early type galaxies have not had a major merger occur within the last few billion years.

  4. Detecting kinematic boundary surfaces in phase space: particle mass measurements in SUSY-like events

    CERN Document Server

    Debnath, Dipsikha; Kilic, Can; Kim, Doojin; Matchev, Konstantin T.; Yang, Yuan-Pao

    2017-06-19

    We critically examine the classic endpoint method for particle mass determination, focusing on difficult corners of parameter space, where some of the measurements are not independent, while others are adversely affected by the experimental resolution. In such scenarios, mass differences can be measured relatively well, but the overall mass scale remains poorly constrained. Using the example of the standard SUSY decay chain $\\tilde q\\to \\tilde\\chi^0_2\\to \\tilde \\ell \\to \\tilde \\chi^0_1$, we demonstrate that sensitivity to the remaining mass scale parameter can be recovered by measuring the two-dimensional kinematical boundary in the relevant three-dimensional phase space of invariant masses squared. We develop an algorithm for detecting this boundary, which uses the geometric properties of the Voronoi tessellation of the data, and in particular, the relative standard deviation (RSD) of the volumes of the neighbors for each Voronoi cell in the tessellation. We propose a new observable, $\\bar\\Sigma$, which is t...

  5. Tidal modulation of slow slip events in the Nankai trough subduction zone detected by borehole strainmeters

    Science.gov (United States)

    Kikuchi, J.; Ide, S.; Matsumoto, N.

    2016-12-01

    Slow slip events (SSEs) often occur in the Nankai subduction zone, Japan, within a band-like zone extended from the center of Honshu to western Shikoku. SSEs are believed as shear slip on the plate interface, where the frictional property changes from velocity weakening to strengthening in the dip direction. Therefore the dynamics of SSEs may give some hints on the depth dependent friction and plate subduction. The tidal modulation of SSEs has been identified by statistical analysis using strain data of Plate Boundary Observatory, in the Cascadia subduction zone [Hawthorne & Rubin, 2010]. Here, we perform similar statistical analyses using strain data recorded at borehole stations maintained by National Institute of Advanced Industrial Science and Technology, in western Japan. The correlation between the oscillation in SSEs and tidal stress was confirmed statistically. In Nankai subduction zone, it is known that SSEs are accompanied with high activity of deep tectonic tremors [Hirose & Obara, 2006]. These tremors have been known to be sensitive to tidal stress [Nakata et al., 2008]. Therefore, the tidal modulation of SSEs is another representation of tidal modulation of tremors. To clarify the relation between SSEs and tremors, we investigate whether strain changes corresponding to SSEs can be explained only by tremors activity. For an SSE occurred in Aug. 2010 in Bungo channel, we assume that the seismic moment of the SSE is 1.6 × 1018 Nm (Mw 6.1) based on the inversion of GNSS data [Nishimura et al., 2013], and that this moment is released by 715 tremors that occur during this SSE [Idehara et al., 2014]. In this case, each tremor is assigned with seismic moment of 2.2 × 1015 Nm (Mw 4.2). Then the strain change at the observation station by these tremors is calculated using the Okada [1992] method, assuming a half space and focal mechanism consistent with the regional plate motion. The calculated strain is qualitatively similar with the observed strain

  6. Exploration of the association rules mining technique for the signal detection of adverse drug events in spontaneous reporting systems.

    Science.gov (United States)

    Wang, Chao; Guo, Xiao-Jing; Xu, Jin-Fang; Wu, Cheng; Sun, Ya-Lin; Ye, Xiao-Fei; Qian, Wei; Ma, Xiu-Qiang; Du, Wen-Min; He, Jia

    2012-01-01

    The detection of signals of adverse drug events (ADEs) has increased because of the use of data mining algorithms in spontaneous reporting systems (SRSs). However, different data mining algorithms have different traits and conditions for application. The objective of our study was to explore the application of association rule (AR) mining in ADE signal detection and to compare its performance with that of other algorithms. Monte Carlo simulation was applied to generate drug-ADE reports randomly according to the characteristics of SRS datasets. Thousand simulated datasets were mined by AR and other algorithms. On average, 108,337 reports were generated by the Monte Carlo simulation. Based on the predefined criterion that 10% of the drug-ADE combinations were true signals, with RR equaling to 10, 4.9, 1.5, and 1.2, AR detected, on average, 284 suspected associations with a minimum support of 3 and a minimum lift of 1.2. The area under the receiver operating characteristic (ROC) curve of the AR was 0.788, which was equivalent to that shown for other algorithms. Additionally, AR was applied to reports submitted to the Shanghai SRS in 2009. Five hundred seventy combinations were detected using AR from 24,297 SRS reports, and they were compared with recognized ADEs identified by clinical experts and various other sources. AR appears to be an effective method for ADE signal detection, both in simulated and real SRS datasets. The limitations of this method exposed in our study, i.e., a non-uniform thresholds setting and redundant rules, require further research.

  7. Automatic Event Detection in Search for Inter-Moss Loops in IRIS Si IV Slit-Jaw Images

    Science.gov (United States)

    Fayock, Brian; Winebarger, Amy R.; De Pontieu, Bart

    2015-01-01

    The high-resolution capabilities of the Interface Region Imaging Spectrometer (IRIS) mission have allowed the exploration of the finer details of the solar magnetic structure from the chromosphere to the lower corona that have previously been unresolved. Of particular interest to us are the relatively short-lived, low-lying magnetic loops that have foot points in neighboring moss regions. These inter-moss loops have also appeared in several AIA pass bands, which are generally associated with temperatures that are at least an order of magnitude higher than that of the Si IV emission seen in the 1400 angstrom pass band of IRIS. While the emission lines seen in these pass bands can be associated with a range of temperatures, the simultaneous appearance of these loops in IRIS 1400 and AIA 171, 193, and 211 suggest that they are not in ionization equilibrium. To study these structures in detail, we have developed a series of algorithms to automatically detect signal brightening or events on a pixel-by-pixel basis and group them together as structures for each of the above data sets. These algorithms have successfully picked out all activity fitting certain adjustable criteria. The resulting groups of events are then statistically analyzed to determine which characteristics can be used to distinguish the inter-moss loops from all other structures. While a few characteristic histograms reveal that manually selected inter-moss loops lie outside the norm, a combination of several characteristics will need to be used to determine the statistical likelihood that a group of events be categorized automatically as a loop of interest. The goal of this project is to be able to automatically pick out inter-moss loops from an entire data set and calculate the characteristics that have previously been determined manually, such as length, intensity, and lifetime. We will discuss the algorithms, preliminary results, and current progress of automatic characterization.

  8. NuLat: 3D Event Reconstruction of a ROL Detector for Neutrino Detection and Background Rejection

    Science.gov (United States)

    Yokley, Zachary; NuLat Collaboration

    2015-04-01

    NuLat is a proposed very-short baseline reactor antineutrino experiment that employs a unique detector design, a Ragahavan Optical Lattice (ROL), developed for the LENS solar neutrino experiment. The 3D lattice provides high spatial and temporal resolution and allows for energy deposition in each voxel to be determined independently of other voxels, as well as the time sequence associated with each voxel energy deposition. This unique feature arises from two independent means to spatially locate energy deposits: via timing and via optical channeling. NuLat, the first application of a ROL detector targeting physics results, will measure the reactor antineutrino flux at very short baselines via inverse beta decay (IBD). The ROL design of NuLat makes possible the reconstruction of positron energy with little contamination due to the annihilation gammas which smear the positron energy resolution in a traditional detector. IBD events are cleanly tagged via temporal and spatial coincidence of neutron capture in the vertex voxel or nearest neighbors. This talk will present work on IBD event reconstruction in NuLat and its likely impact on sterile neutrino detection via operation in higher background locations enabled by its superior rejection of backgrounds. This research has been funded in part by the National Science Foundation on Award Numbers 1001394 and 1001078.

  9. Adverse Events Associated with Hospitalization or Detected through the RAI-HC Assessment among Canadian Home Care Clients

    Science.gov (United States)

    Doran, Diane; Hirdes, John P.; Blais, Régis; Baker, G. Ross; Poss, Jeff W.; Li, Xiaoqiang; Dill, Donna; Gruneir, Andrea; Heckman, George; Lacroix, Hélène; Mitchell, Lori; O'Beirne, Maeve; Foebel, Andrea; White, Nancy; Qian, Gan; Nahm, Sang-Myong; Yim, Odilia; Droppo, Lisa; McIsaac, Corrine

    2013-01-01

    Background: The occurrence of adverse events (AEs) in care settings is a patient safety concern that has significant consequences across healthcare systems. Patient safety problems have been well documented in acute care settings; however, similar data for clients in home care (HC) settings in Canada are limited. The purpose of this Canadian study was to investigate AEs in HC, specifically those associated with hospitalization or detected through the Resident Assessment Instrument for Home Care (RAI-HC). Method: A retrospective cohort design was used. The cohort consisted of HC clients from the provinces of Nova Scotia, Ontario, British Columbia and the Winnipeg Regional Health Authority. Results: The overall incidence rate of AEs associated with hospitalization ranged from 6% to 9%. The incidence rate of AEs determined from the RAI-HC was 4%. Injurious falls, injuries from other than fall and medication-related events were the most frequent AEs associated with hospitalization, whereas new caregiver distress was the most frequent AE identified through the RAI-HC. Conclusion: The incidence of AEs from all sources of data ranged from 4% to 9%. More resources are needed to target strategies for addressing safety risks in HC in a broader context. Tools such as the RAI-HC and its Clinical Assessment Protocols, already available in Canada, could be very useful in the assessment and management of HC clients who are at safety risk. PMID:23968676

  10. Detection and discrimination of maintenance and de novo CpG methylation events using MethylBreak.

    Science.gov (United States)

    Hsu, William; Mercado, Augustus T; Hsiao, George; Yeh, Jui-Ming; Chen, Chung-Yung

    2017-05-15

    Understanding the principles governing the establishment and maintenance activities of DNA methyltransferases (DNMTs) can help in the development of predictive biomarkers associated with genetic disorders and diseases. A detection system was developed that distinguishes and quantifies methylation events using methylation-sensitive endonucleases and molecular beacon technology. MethylBreak (MB) is a 22-mer oligonucleotide with one hemimethylated and two unmethylated CpG sites, which are also recognition sites for Sau96I and SacII, and is attached to a fluorophore and a quencher. Maintenance methylation was quantified by fluorescence emission due to the digestion of SacII when the hemimethylated CpG site is methylated, which inhibits Sau96I cleavage. The signal difference between SacII digestion of both MB substrate and maintenance methylated MB corresponds to de novo methylation event. Our technology successfully discriminated and measured both methylation activities at different concentrations of MB and achieved a high correlation coefficient of R(2)=0.997. Additionally, MB was effectively applied to normal and cancer cell lines and in the analysis of enzymatic kinetics and RNA inhibition of recombinant human DNMT1. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Real-time automated 3D sensing, detection, and recognition of dynamic biological micro-organic events

    Science.gov (United States)

    Javidi, Bahram; Yeom, Seokwon; Moon, Inkyu; Daneshpanah, Mehdi

    2006-05-01

    In this paper, we present an overview of three-dimensional (3D) optical imaging techniques for real-time automated sensing, visualization, and recognition of dynamic biological microorganisms. Real time sensing and 3D reconstruction of the dynamic biological microscopic objects can be performed by single-exposure on-line (SEOL) digital holographic microscopy. A coherent 3D microscope-based interferometer is constructed to record digital holograms of dynamic micro biological events. Complex amplitude 3D images of the biological microorganisms are computationally reconstructed at different depths by digital signal processing. Bayesian segmentation algorithms are applied to identify regions of interest for further processing. A number of pattern recognition approaches are addressed to identify and recognize the microorganisms. One uses 3D morphology of the microorganisms by analyzing 3D geometrical shapes which is composed of magnitude and phase. Segmentation, feature extraction, graph matching, feature selection, and training and decision rules are used to recognize the biological microorganisms. In a different approach, 3D technique is used that are tolerant to the varying shapes of the non-rigid biological microorganisms. After segmentation, a number of sampling patches are arbitrarily extracted from the complex amplitudes of the reconstructed 3D biological microorganism. These patches are processed using a number of cost functions and statistical inference theory for the equality of means and equality of variances between the sampling segments. Also, we discuss the possibility of employing computational integral imaging for 3D sensing, visualization, and recognition of biological microorganisms illuminated under incoherent light. Experimental results with several biological microorganisms are presented to illustrate detection, segmentation, and identification of micro biological events.

  12. Glaucoma progression detection by retinal nerve fiber layer measurement using scanning laser polarimetry: event and trend analysis.

    Science.gov (United States)

    Moon, Byung Gil; Sung, Kyung Rim; Cho, Jung Woo; Kang, Sung Yong; Yun, Sung-Cheol; Na, Jung Hwa; Lee, Youngrok; Kook, Michael S

    2012-06-01

    To evaluate the use of scanning laser polarimetry (SLP, GDx VCC) to measure the retinal nerve fiber layer (RNFL) thickness in order to evaluate the progression of glaucoma. Test-retest measurement variability was determined in 47 glaucomatous eyes. One eye each from 152 glaucomatous patients with at least 4 years of follow-up was enrolled. Visual field (VF) loss progression was determined by both event analysis (EA, Humphrey guided progression analysis) and trend analysis (TA, linear regression analysis of the visual field index). SLP progression was defined as a reduction of RNFL exceeding the predetermined repeatability coefficient in three consecutive exams, as compared to the baseline measure (EA). The slope of RNFL thickness change over time was determined by linear regression analysis (TA). Twenty-two eyes (14.5%) progressed according to the VF EA, 16 (10.5%) by VF TA, 37 (24.3%) by SLP EA and 19 (12.5%) by SLP TA. Agreement between VF and SLP progression was poor in both EA and TA (VF EA vs. SLP EA, k = 0.110; VF TA vs. SLP TA, k = 0.129). The mean (±standard deviation) progression rate of RNFL thickness as measured by SLP TA did not significantly differ between VF EA progressors and non-progressors (-0.224 ± 0.148 µm/yr vs. -0.218 ± 0.151 µm/yr, p = 0.874). SLP TA and EA showed similar levels of sensitivity when VF progression was considered as the reference standard. RNFL thickness as measurement by SLP was shown to be capable of detecting glaucoma progression. Both EA and TA of SLP showed poor agreement with VF outcomes in detecting glaucoma progression.

  13. A multi-station matched filter and coherent network processing approach to the automatic detection and relative location of seismic events

    Science.gov (United States)

    Gibbons, Steven J.; Näsholm, Sven Peter; Kværna, Tormod

    2014-05-01

    Correlation detectors facilitate seismic monitoring in the near vicinity of previously observed events at far lower detection thresholds than are possible using the methods applied in most existing processing pipelines. The use of seismic arrays has been demonstrated to be highly beneficial in pressing down the detection threshold, due to superior noise suppression, and also in eliminating vast numbers of false alarms by performing array processing on the multi-channel output of the correlation detectors. This last property means that it is highly desirable to run continuous detectors for sites of repeating seismic events on a single-array basis for many arrays across a global network. Spurious detections for a given signal template on a single array can however still occur when an unrelated wavefront crosses the array from a very similar direction to that of the master event wavefront. We present an algorithm which scans automatically the output from multiple stations - both array and 3-component - for coherence between the individual station correlator outputs that is consistent with a disturbance in the vicinity of the master event. The procedure results in a categorical rejection of an event hypothesis in the absence of support from stations other than the one generating the trigger and provides a fully automatic relative event location estimate when patterns in the correlation detector outputs are found to be consistent with a common event. This coherence-based approach removes the need to make explicit measurements of the time-differences for single stations and this eliminates a potential source of error. The method is demonstrated for the North Korea nuclear test site and the relative event location estimates obtained for the 2006, 2009, and 2013 events are compared with previous estimates from different station configurations.

  14. Matched-filter detection of the missing pre-mainshock events and aftershocks in the 2015 Gorkha, Nepal earthquake sequence

    Science.gov (United States)

    Huang, Hui; Meng, Lingsen; Plasencia, Milton; Wang, Yali; Wang, Liangshu; Xu, Mingjie

    2017-09-01

    The 25 April 2015 Mw 7.8 Gorkha, Nepal earthquake occurred at the bottom edge of the locked portion of the Main Himalayan Thrust, where the Indian plate underthrusts the Himalayan wedge. The earthquake was followed by a number of large aftershocks, but not preceded by any foreshocks within 3 weeks according to the NEIC or ISC catalog. However, due to the limited station coverage of the local seismic network, a large portion of events may not be reported in routine catalogs. Here, we employ the matched filter technique to recover the undocumented earthquakes for the period beginning 80 days before through 30 days after the 2015 Gorkha earthquake. We detect twice as many aftershocks as those listed in the ISC catalog. We observe an along-strike aftershock expansion after the mainshock and before the largest Mw 7.3 aftershock that occurred on 12 May 2015. Repeating earthquakes are found to the ESE of the mainshock rupture area, suggesting that the expansion may be partially driven by afterslip. In addition, we observe a significant increase in seismicity rate 3-4 days prior to the mainshock, initiating 6 h after a M 5.2 earthquake, located 240 km to the NW of the mainshock. The increase of seismic activities occurs in a wide region around the Gorkha principal slip zone, indicating the effect of delayed dynamic triggering may contribute to the large-scale unloading process prior to the 2015 Gorkha mainshock.

  15. A measurement of the muon number in showers using inclined events detected at the Pierre Auger Observatory

    Directory of Open Access Journals (Sweden)

    Rodriguez G.

    2013-06-01

    Full Text Available The average muon content of measured showers with zenith angles between 62∘ and 80∘ detected at the Pierre Auger Observatory is obtained as a function of shower energy using a reconstruction method specifically designed for inclined showers and the hybrid character of the detector. The reconstruction of inclined showers relies on a comparison between the measured signals at ground and reference patterns at ground level from which an overall normalization factor is obtained. Since inclined showers are dominated by muons this factor gives the relative muon size. It can be calibrated using a subsample of showers simultaneously recorded with the fluorescence detector (FD and the surface detector (SD which provides an independent calorimetric measurement of the energy. The muon size obtained for each shower becomes a measurement of the relative number of muons with respect to the reference distributions. The precision of the measurement is assessed using simulated events which are reconstructed using exactly the same procedure. We compare the relative number of muons versus energy as obtained to simulations. Proton simulations with QGSJETII show a factor of 2.13 ± 0.04(stat ± 0.11(sys at 1019eV without significant variations in the energy range explored between 4 × 1018eV to 7 × 1019eV. We find that none of the current shower models, neither for proton nor for iron primaries, are able to predict as many muons as are observed.

  16. Detection of Healthcare-Related Extended-Spectrum Beta-Lactamase-Producing Escherichia coli Transmission Events Using Combined Genetic and Phenotypic Epidemiology.

    Directory of Open Access Journals (Sweden)

    Anne F Voor In 't Holt

    Full Text Available Since the year 2000 there has been a sharp increase in the prevalence of healthcare-related infections caused by extended-spectrum beta-lactamase (ESBL-producing Escherichia coli. However, the high community prevalence of ESBL-producing E. coli isolates means that many E. coli typing techniques may not be suitable for detecting E. coli transmission events. Therefore, we investigated if High-throughput MultiLocus Sequence Typing (HiMLST and/or Raman spectroscopy were suitable techniques for detecting recent E. coli transmission events.This study was conducted from January until December 2010 at Erasmus University Medical Center, Rotterdam, the Netherlands. Isolates were typed using HiMLST and Raman spectroscopy. A genetic cluster was defined as two or more patients carrying identical isolates. We used predefined definitions for epidemiological relatedness to assess healthcare-related transmission.We included 194 patients; strains of 112 patients were typed using HiMLST and strains of 194 patients were typed using Raman spectroscopy. Raman spectroscopy identified 16 clusters while HiMLST identified 10 clusters. However, no healthcare-related transmission events were detected. When combining data from both typing techniques, we identified eight clusters (n = 34 patients, as well as 78 patients with a non-cluster isolate. However, we could not detect any healthcare-related transmission in these 8 clusters.Although clusters were genetically detected using HiMLST and Raman spectroscopy, no definite epidemiological relationships could be demonstrated which makes the possibility of healthcare-related transmission events highly unlikely. Our results suggest that typing of ESBL-producing E. coli using HiMLST and/or Raman spectroscopy is not helpful in detecting E. coli healthcare-related transmission events.

  17. Estimating the distribution of a renewal process from times at which events from an independent process are detected.

    Science.gov (United States)

    Song, Ruiguang; Karon, John M; White, Edward; Goldbaum, Gary

    2006-09-01

    The analysis of length-biased data has been mostly limited to the interarrival interval of a renewal process covering a specific time point. Motivated by a surveillance problem, we consider a more general situation where this time point is random and related to a specific event, for example, status change or onset of a disease. We also consider the problem when additional information is available on whether the event intervals (interarrival intervals covering the random event) end within or after a random time period (which we call a window period) following the random event. Under the assumptions that the occurrence rate of the random event is low and the renewal process is independent of the random event, we provide formulae for the estimation of the distribution of interarrival times based on the observed event intervals. Procedures for testing the required assumptions are also furnished. We apply our results to human immunodeficiency virus (HIV) test data from public test sites in Seattle, Washington, where the random event is HIV infection and the window period is from the onset of HIV infection to the time at which a less sensitive HIV test becomes positive. Results show that the estimator of the intertest interval length distribution from event intervals ending within the window period is less biased than the estimator from all event intervals; the latter estimator is affected by right truncation. Finally, we discuss possible applications to estimating HIV incidence and analyzing length-biased samples with right or left truncated data.

  18. Development and Event-specific Detection of Transgenic Glyphosate-resistant Rice Expressing the G2-EPSPS Gene.

    Science.gov (United States)

    Dong, Yufeng; Jin, Xi; Tang, Qiaoling; Zhang, Xin; Yang, Jiangtao; Liu, Xiaojing; Cai, Junfeng; Zhang, Xiaobing; Wang, Xujing; Wang, Zhixing

    2017-01-01

    Glyphosate is a widely used herbicide, due to its broad spectrum, low cost, low toxicity, high efficiency, and non-selective characteristics. Rice farmers rarely use glyphosate as a herbicide, because the crop is sensitive to this chemical. The development of transgenic glyphosate-tolerant rice could greatly improve the economics of rice production. Here, we transformed the Pseudomonas fluorescens G2 5-enolpyruvyl shikimate-3-phosphate synthase (EPSPS) gene G2-EPSPS, which conferred tolerance to glyphosate herbicide into a widely used japonica rice cultivar, Zhonghua 11 (ZH11), to develop two highly glyphosate-tolerant transgenic rice lines, G2-6 and G2-7, with one exogenous gene integration. Seed germination tests and glyphosate-tolerance assays of plants grown in a greenhouse showed that the two transgenic lines could greatly improve glyphosate-tolerance compared with the wild-type; The glyphosate-tolerance field test indicated that both transgenic lines could grow at concentrations of 20,000 ppm glyphosate, which is more than 20-times the recommended concentration in the field. Isolation of the flanking sequence of transgenic rice G2-6 indicated that the 5'-terminal of T-DNA was inserted into chromosome 8 of the rice genome. An event-specific PCR test system was established and the limit of detection of the primers reached five copies. Overall, the G2-EPSPS gene significantly improved glyphosate-tolerance in transgenic rice; furthermore, it is a useful candidate gene for the future development of commercial transgenic rice.

  19. A comment on Farwell : brain fingerprinting: a comprehensive tutorial review of detection of concealed information with event-related brain potentials

    NARCIS (Netherlands)

    Meijer, E.H.; Ben-Shakhar, G.; Verschuere, B.; Donchin, E.

    2013-01-01

    In a recent issue of Cognitive Neurodynamics Farwell (Cogn Neurodyn 6:115-154, 2012) published a comprehensive tutorial review of the use of Event Related Brain Potentials (ERP) in the detection of concealed information. Farwell’s review covered much of his own work employing his ‘‘brain

  20. Vibrotactile Detection, Identification and Directional Perception of signal-Processed Sounds from Environmental Events: A Pilot Field Evaluation in Five Cases

    Directory of Open Access Journals (Sweden)

    Parivash Ranjbar

    2008-09-01

    Full Text Available Objectives: Conducting field tests of a vibrotactile aid for deaf/deafblind persons for detection, identification and directional perception of environmental sounds. Methods: Five deaf (3F/2M, 22–36 years individuals tested the aid separately in a home environment (kitchen and in a traffic environment. Their eyes were blindfolded and they wore a headband and holding a vibrator for sound identification. In the headband, three microphones were mounted and two vibrators for signalling direction of the sound source. The sounds originated from events typical for the home environment and traffic. The subjects were inexperienced (events unknown and experienced (events known. They identified the events in a home and traffic environment, but perceived sound source direction only in traffic. Results: The detection scores were higher than 98% both in the home and in the traffic environment. In the home environment, identification scores varied between 25%-58% when the subjects were inexperienced and between 33%-83% when they were experienced. In traffic, identification scores varied between 20%-40% when the subjects were inexperienced and between 22%-56% when they were experienced. The directional perception scores varied between 30%-60% when inexperienced and between 61%-83% when experienced. Discussion: The vibratory aid consistently improved all participants’ detection, identification and directional perception ability.

  1. Gait Event Detection in Real-World Environment for Long-Term Applications: Incorporating Domain Knowledge Into Time-Frequency Analysis.

    Science.gov (United States)

    Khandelwal, Siddhartha; Wickstrom, Nicholas

    2016-12-01

    Detecting gait events is the key to many gait analysis applications that would benefit from continuous monitoring or long-term analysis. Most gait event detection algorithms using wearable sensors that offer a potential for use in daily living have been developed from data collected in controlled indoor experiments. However, for real-word applications, it is essential that the analysis is carried out in humans' natural environment; that involves different gait speeds, changing walking terrains, varying surface inclinations and regular turns among other factors. Existing domain knowledge in the form of principles or underlying fundamental gait relationships can be utilized to drive and support the data analysis in order to develop robust algorithms that can tackle real-world challenges in gait analysis. This paper presents a novel approach that exhibits how domain knowledge about human gait can be incorporated into time-frequency analysis to detect gait events from long-term accelerometer signals. The accuracy and robustness of the proposed algorithm are validated by experiments done in indoor and outdoor environments with approximately 93 600 gait events in total. The proposed algorithm exhibits consistently high performance scores across all datasets in both, indoor and outdoor environments.

  2. Effectiveness of pacemaker tele-monitoring on quality of life, functional capacity, event detection and workload: The PONIENTE trial.

    Science.gov (United States)

    Lopez-Villegas, Antonio; Catalan-Matamoros, Daniel; Robles-Musso, Emilio; Peiro, Salvador

    2016-11-01

    The purpose of the present study was to assess the effectiveness of the remote monitoring (RM) of older adults with pacemakers on health-related quality of life, functional capacity, feasibility, reliability and safety. The PONIENTE study is a controlled, non-randomized, non-blinded clinical trial, with data collection carried out during the pre-implant stage and after 12 months. Between October of 2012 and November of 2013, 82 patients were assigned to either a remote monitoring group (n = 30) or a conventional hospital monitoring (HM) group (n = 52). The EuroQol-5D (EQ-5D) and the Duke Activity Status Index were used to measure health-related quality of life and functional capacity, respectively. Baseline characteristics and number of hospital visits were also analyzed. The baseline characteristics of the two study groups were similar for both the EQ-5D (RM 0.74, HM 0.67; P = 0.404) and the Duke Activity Status Index (RM 21.42, HM 19.95; P = 0.272). At the 12-month follow up, the EQ-5D utility score was improved for both groups (RM 0.91, HM 0.81; P = 0.154), unlike the EQ-5D Visual Analog Scale (P = 0.043). The Duke Activity Status Index score was similar to the baseline score. The number of in-hospital visits was 27% lower (3 vs 4; P < 0.001) in the remote group as compared with the hospital group. The PONIENTE trial suggests that the remote monitoring of pacemakers in older adults is an equivalent option to hospital monitoring, in terms of health-related quality of life and functional capacity. Furthermore, it allows for the early detection of clinical and pacemaker-related adverse events, and significantly reduces the number of in-hospital visits. Geriatr Gerontol Int 2016; 16: 1188-1195. © 2015 Japan Geriatrics Society.

  3. Pulse oximetry recorded from the Phone Oximeter for detection of obstructive sleep apnea events with and without oxygen desaturation in children.

    Science.gov (United States)

    Garde, Ainara; Dehkordi, Parastoo; Wensley, David; Ansermino, J Mark; Dumont, Guy A

    2015-01-01

    Obstructive sleep apnea (OSA) disrupts normal ventilation during sleep and can lead to serious health problems in children if left untreated. Polysomnography, the gold standard for OSA diagnosis, is resource intensive and requires a specialized laboratory. Thus, we proposed to use the Phone Oximeter™, a portable device integrating pulse oximetry with a smartphone, to detect OSA events. As a proportion of OSA events occur without oxygen desaturation (defined as SpO2 decreases ≥ 3%), we suggest combining SpO2 and pulse rate variability (PRV) analysis to identify all OSA events and provide a more detailed sleep analysis. We recruited 160 children and recorded pulse oximetry consisting of SpO2 and plethysmography (PPG) using the Phone Oximeter™, alongside standard polysomnography. A sleep technician visually scored all OSA events with and without oxygen desaturation from polysomnography. We divided pulse oximetry signals into 1-min signal segments and extracted several features from SpO2 and PPG analysis in the time and frequency domain. Segments with OSA, especially the ones with oxygen desaturation, presented greater SpO2 variability and modulation reflected in the spectral domain than segments without OSA. Segments with OSA also showed higher heart rate and sympathetic activity through the PRV analysis relative to segments without OSA. PRV analysis was more sensitive than SpO2 analysis for identification of OSA events without oxygen desaturation. Combining SpO2 and PRV analysis enhanced OSA event detection through a multiple logistic regression model. The area under the ROC curve increased from 81% to 87%. Thus, the Phone Oximeter™ might be useful to monitor sleep and identify OSA events with and without oxygen desaturation at home.

  4. Event-specific qualitative and quantitative PCR detection of the GMO carnation (Dianthus caryophyllus) variety Moonlite based upon the 5'-transgene integration sequence.

    Science.gov (United States)

    Li, P; Jia, J W; Jiang, L X; Zhu, H; Bai, L; Wang, J B; Tang, X M; Pan, A H

    2012-04-27

    To ensure the implementation of genetically modified organism (GMO)-labeling regulations, an event-specific detection method was developed based on the junction sequence of an exogenous integrant in the transgenic carnation variety Moonlite. The 5'-transgene integration sequence was isolated by thermal asymmetric interlaced PCR. Based upon the 5'-transgene integration sequence, the event-specific primers and TaqMan probe were designed to amplify the fragments, which spanned the exogenous DNA and carnation genomic DNA. Qualitative and quantitative PCR assays were developed employing the designed primers and probe. The detection limit of the qualitative PCR assay was 0.05% for Moonlite in 100 ng total carnation genomic DNA, corresponding to about 79 copies of the carnation haploid genome; the limit of detection and quantification of the quantitative PCR assay were estimated to be 38 and 190 copies of haploid carnation genomic DNA, respectively. Carnation samples with different contents of genetically modified components were quantified and the bias between the observed and true values of three samples were lower than the acceptance criterion (GMO detection method. These results indicated that these event-specific methods would be useful for the identification and quantification of the GMO carnation Moonlite.

  5. The Effect of Real-time Clinical Monitoring and a "Closed Loop" Medication System on Adverse Drug Event Detection

    National Research Council Canada - National Science Library

    Mendelowitz, Paul C

    2008-01-01

    ...; as well as beside bar code scanning of patient, staff and medications. The implementation of this comprehensive redesign has allowed us to conduct research to determine whether decision support will foster a reduction in adverse drug events...

  6. The association of colonoscopy quality indicators with the detection of screen-relevant lesions, adverse events, and postcolonoscopy cancers in an asymptomatic Canadian colorectal cancer screening population.

    Science.gov (United States)

    Hilsden, Robert J; Dube, Catherine; Heitman, Steven J; Bridges, Ronald; McGregor, S Elizabeth; Rostom, Alaa

    2015-11-01

    Although several quality indicators of colonoscopy have been defined, quality assurance activities should be directed at the measurement of quality indicators that are predictive of key screening colonoscopy outcomes. The goal of this study was to examine the association among established quality indicators and the detection of screen-relevant lesions (SRLs), adverse events, and postcolonoscopy cancers. Historical cohort study. Canadian colorectal cancer screening center. A total of 18,456 asymptomatic men and women ages 40 to 74, at either average risk or increased risk for colorectal cancer because of a family history, who underwent a screening colonoscopy from 2008 to 2010. Using univariate and multivariate analyses, we explored the association among procedural quality indicators and 3 colonoscopy outcomes: detection of SRLs, adverse events, and postcolonoscopy cancers. The crude rates of SRLs, adverse events, and postcolonoscopy cancers were 240, 6.44, and .54 per 1000 colonoscopies, respectively. Several indicators, including endoscopist withdrawal time (OR, 1.3; 95% CI, 1.2-1.4) and cecal intubation rate (OR, 13.9; 95% CI, 1.9-96.9), were associated with the detection of SRLs. No quality indicator was associated with the risk of adverse events. Endoscopist average withdrawal time over 6 minutes (OR, .12; 95% CI, .002-.85) and SRL detection rate over 20% (OR, .17; 95% CI, .03-.74) were associated with a reduced risk of postcolonoscopy cancers. Single-center study. Quality assurance programs should prioritize the measurement of endoscopist average withdrawal time and adenoma (SRL) detection rate. Copyright © 2015 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

  7. Detection of zero anisotropy at 5.2 AU during the November 1998 solar particle event: Ulysses Anisotropy Telescopes observations

    Directory of Open Access Journals (Sweden)

    S. Dalla

    Full Text Available For the first time during the mission, the Anisotropy Telescopes instrument on board the Ulysses spacecraft measured constant zero anisotropy of protons in the 1.3-2.2 MeV energy range, for a period lasting more than three days. This measurement was made during the energetic particle event taking place at Ulysses between 25 November and 15 December 1998, an event characterised by constant high proton fluxes within a region delimited by two interplanetary forward shocks, at a distance of 5.2 AU from the Sun and heliographic latitude of 17°S. We present the ATs results for this event and discuss their possible interpretation and their relevance to the issue of intercalibration of the two telescopes.

    Key words: Interplanetary physics (energetic particles - Solar physics, astrophysics and astronomy (energetic particles - Space plasma physics (instruments and techniques

  8. Detection and Interpretation of Low-Level and High-Level Surprising and Important Events in Large-Scale Data Streams

    Science.gov (United States)

    2016-06-28

    neuro-inspired visual processing is demonstrated to perform so well during such large-scale, real- world testing. Many more details are available in...Distribution Unlimited UU UU UU UU 28-06-2016 17-Sep-2012 16-Mar-2016 Final Report: Detection and Interpretation of Low-Level and High-Level Surprising and... Interpretation of Low-Level and High-Level Surprising and Important Events in Large- Scale Data Streams Report Title This project explored how to

  9. Detecting potential safety issues in large clinical or observational trials by Bayesian screening when event counts arise from poisson distributions.

    Science.gov (United States)

    Gould, A Lawrence

    2013-01-01

    Patients in large clinical trials and in studies employing large observational databases report many different adverse events, most of which will not have been anticipated at the outset. Conventional hypothesis testing of between group differences for each adverse event can be problematic: Lack of significance does not mean lack of risk, the tests usually are not adjusted for multiplicity, and the data determine which hypotheses are tested. This article describes a Bayesian screening approach that does not test hypotheses, is self-adjusting for multiplicity, provides a direct assessment of the likelihood of no material drug-event association, and quantifies the strength of the observed association. The criteria for assessing drug-event associations can be determined by clinical or regulatory considerations. In contrast to conventional approaches, the diagnostic properties of this new approach can be evaluated analytically. Application of the method to findings from a vaccine trial yields results similar to those found by methods using a false discovery rate argument or a hierarchical Bayes approach. [Supplemental materials are available for this article. Go to the publisher's online edition of Journal of Biopharmaceutical Statistics for the following free supplemental resource: Appendix R: Code for calculations.].

  10. A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI

    Directory of Open Access Journals (Sweden)

    Christoph Reichert

    2017-10-01

    Full Text Available In brain-computer interface (BCI applications the detection of neural processing as revealed by event-related potentials (ERPs is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG.

  11. A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI.

    Science.gov (United States)

    Reichert, Christoph; Dürschmid, Stefan; Heinze, Hans-Jochen; Hinrichs, Hermann

    2017-01-01

    In brain-computer interface (BCI) applications the detection of neural processing as revealed by event-related potentials (ERPs) is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG) provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG) could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs) compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA) compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG.

  12. Final report for LDRD project 11-0029 : high-interest event detection in large-scale multi-modal data sets : proof of concept.

    Energy Technology Data Exchange (ETDEWEB)

    Rohrer, Brandon Robinson

    2011-09-01

    Events of interest to data analysts are sometimes difficult to characterize in detail. Rather, they consist of anomalies, events that are unpredicted, unusual, or otherwise incongruent. The purpose of this LDRD was to test the hypothesis that a biologically-inspired anomaly detection algorithm could be used to detect contextual, multi-modal anomalies. There currently is no other solution to this problem, but the existence of a solution would have a great national security impact. The technical focus of this research was the application of a brain-emulating cognition and control architecture (BECCA) to the problem of anomaly detection. One aspect of BECCA in particular was discovered to be critical to improved anomaly detection capabilities: it's feature creator. During the course of this project the feature creator was developed and tested against multiple data types. Development direction was drawn from psychological and neurophysiological measurements. Major technical achievements include the creation of hierarchical feature sets created from both audio and imagery data.

  13. Copy number ratios determined by two digital polymerase chain reaction systems in genetically modified grains

    Science.gov (United States)

    Pérez Urquiza, M.; Acatzi Silva, A. I.

    2014-02-01

    Three certified reference materials produced from powdered seeds to measure the copy number ratio sequences of p35S/hmgA in maize containing MON 810 event, p35S/Le1 in soybeans containing GTS 40-3-2 event and DREB1A/acc1 in wheat were produced according to the ISO Guides 34 and 35. In this paper, we report digital polymerase chain reaction (dPCR) protocols, performance parameters and results of copy number ratio content of genetically modified organisms (GMOs) in these materials using two new dPCR systems to detect and quantify molecular deoxyribonucleic acid: the BioMark® (Fluidigm) and the OpenArray® (Life Technologies) systems. These technologies were implemented at the National Institute of Metrology in Mexico (CENAM) and in the Reference Center for GMO Detection from the Ministry of Agriculture (CNRDOGM), respectively. The main advantage of this technique against the more-used quantitative polymerase chain reaction (qPCR) is that it generates an absolute number of target molecules in the sample, without reference to standards or an endogenous control, which is very useful when not much information is available for new developments or there are no standard reference materials in the market as in the wheat case presented, or when it was not possible to test the purity of seeds as in the maize case presented here. Both systems reported enhanced productivity, increased reliability and reduced instrument footprint. In this paper, the performance parameters and uncertainty of measurement obtained with both systems are presented and compared.

  14. Design of a system for detecting and reporting security incidents and adverse events in thyroid and parathyroid surgery

    Directory of Open Access Journals (Sweden)

    José Luis PARDAL-REFOYO

    2016-03-01

    Full Text Available Introduction: Patient safety is defined as the reduction of risk of unnecessary harm associated with healthcare. Up to 9.3% of patients admitted into a hospital present some adverse event related to the assistance. This can cause damage to the patient, more instrumentation, increased morbidity, increased hospital stay and increased cost. To identify, record and analyze adverse events is necessary to have an incident reporting system. Objective: Developing a local system for reporting security incidents and adverse events in surgery of the thyroid gland. Method: A working group was formed with representatives from all units related to the process of thyroidectomy, checkpoints were established, checklists for each control point were designed, a strategic analysis of the group's activity was performed, a literature review was done in order to identify the major incident reporting systems, the items that the incident report form must have were identified and the form was designed. Results: The incident report form collects data on the patient, the communicator and the incident (type, cause, consequence, severity, frequency, risk matrix. It has a first paragraph with narrative sections and a second with drop-down lists. The form is accessible only to the working group for voluntary use. Conclusions: The purpose of the reporting system is learning and prevention.

  15. [Analysis of exogenous gene and protein digestion and absorption of SD rats (Rattus norvegicus) fed roundup ready soybean meal].

    Science.gov (United States)

    Yuan, Jianqin; Chang, Hong; Zhao, Jianghe; Shi, Zongyong; Wang, Jundong

    2016-05-25

    Metabolism and deposition of exogenous gene and protein from transgenic glyphosate herbicide-tolerant soybean meal in SD rats were studied in the experiment. The transgenic soybean GTS40-3-2 meal and its non-transgenic counterpart (parent A5403) were fed to the generation and the second generation Sprague-Dawley (SD) rats (Rattus norvegicus). The study added the genetically modified (GM) soybean meal and its non-transgenic control soybean meal (parent A5403) in a ratio of 20% respectively to the feeds. By using qualitative, quantitative PCR and ELISA methods to detect transgenic soybean residues of metabolism ingredients in rats, the safety and influence of GM soybean were evaluated. The results showed that the intestinal fecal and cecum contents of rats were detected with residues of GM ingredients, intestinal flora and organs were not found related genes and protein. These results indicated that transgenic glyphosate herbicide-tolerant soybean GTS40-3-2 meal was as safe as its non-GM soybean meal in long-term feeding study.

  16. Lessons derived from two high-frequency sea level events in the Atlantic: implications for coastal risk analysis and tsunami detection

    Directory of Open Access Journals (Sweden)

    Begoña Pérez-Gómez

    2016-11-01

    Full Text Available The upgrade and enhancement of sea level networks worldwide for integration in sea level hazard warning systems have significantly increased the possibilities for measuring and analyzing high frequency sea level oscillations, with typical periods ranging from a few minutes to a few hours. Many tide gauges now afford 1 min or more frequent sampling and have shown such events to be a common occurrence. Their origins and spatial distribution are diverse and must be well understood in order to correctly design and interpret, for example, the automatic detection algorithms used by tsunami warning centers. Two events recorded recently in European Atlantic waters are analyzed here: possible wave-induced seiches that occurred along the North coast of Spain during the storms of January and February of 2014, and oscillations detected after an earthquake in the mid-Atlantic the 13th of February of 2015. The former caused significant flooding in towns and villages and a huge increase in wave-induced coastal damage that was reported in the media for weeks. The second was a smaller signal present in several tide gauges along the Atlantic coast that, that coincided with the occurrence of this earthquake, leading to a debate on the potential detection of a very small tsunami and how it might yield significant information for tsunami wave modelers and for the development of tsunami detection software. These kinds of events inform us about the limitations of automatic algorithms for tsunami warning and help to improve the information provided to tsunami warning centers, whilst also emphasizing the importance of other forcings in generating extreme sea levels and their associated potential for causing damage to infrastructure.

  17. Novel ST-MUSIC-based spectral analysis for detection of ULF geomagnetic signals anomalies associated with seismic events in Mexico

    Directory of Open Access Journals (Sweden)

    Omar Chavez

    2016-05-01

    Full Text Available Recently, the analysis of ultra-low-frequency (ULF geomagnetic signals in order to detect seismic anomalies has been reported in several works. Yet, they, although having promising results, present problems for their detection since these anomalies are generally too much weak and embedded in high noise levels. In this work, a short-time multiple signal classification (ST-MUSIC, which is a technique with high-frequency resolution and noise immunity, is proposed for the detection of seismic anomalies in the ULF geomagnetic signals. Besides, the energy (E of geomagnetic signals processed by ST-MUSIC is also presented as a complementary parameter to measure the fluctuations between seismic activity and seismic calm period. The usefulness and effectiveness of the proposal are demonstrated through the analysis of a synthetic signal and five real signals with earthquakes. The analysed ULF geomagnetic signals have been obtained using a tri-axial fluxgate magnetometer at the Juriquilla station, which is localized in Queretaro, Mexico (geographic coordinates: longitude 100.45° E and latitude 20.70° N. The results obtained show the detection of seismic perturbations before, during, and after the main shock, making the proposal a suitable tool for detecting seismic precursors.

  18. The clinical relevance of embolic events detected by transesophageal echocardiography during cemented total hip arthroplasty: a randomized clinical trial.

    Science.gov (United States)

    Koessler, M J; Fabiani, R; Hamer, H; Pitto, R P

    2001-01-01

    The first aim of this prospective clinical study was to characterize the relationship between embolic events observed during cemented total hip arthroplasty using transesophageal echocardiography (TEE), and changes in cardiopulmonary function. The second aim was to assess the efficiency of a modified cementing technique that was developed to reduce the risk of embolism. The modification consists in a vacuum drainage placed in the proximal femur to reduce the increase of intramedullary pressure during insertion of the prosthesis. One hundred twenty patients were randomized into two groups. Group 1 received a total hip arthroplasty cemented conventionally, whereas Group 2 was cemented with the modified technique. Continuous TEE, hemodynamic monitoring, and blood gas analysis were done during the perioperative period. Severe embolic events were imaged during the insertion of the femoral component and the reduction of the hip joint. Embolism occurred in 93.3% of patients operated on with the conventional cementing technique, compared with 13.3% of patients operated on with the modified technique (P syndrome in any study patient. The results of the study indicate that embolic events observed using TEE can cause increased pulmonary shunt values during hip arthroplasty, especially in patients with systemic disease (ASA physical status III). The modified surgical technique effectively reduced the incidence of embolization during cemented hip arthroplasty. Use of conventional cementing techniques is associated with echocardiographic evidence of embolism in 93% of patients and with a significant increase in pulmonary shunting. The incidence of embolism and change in shunting are reduced with a modified cementing technique that limits increases in intramedullary pressure.

  19. Error Detection and Response Adjustment in Youth With Mild Spastic Cerebral Palsy : An Event-Related Brain Potential Study

    NARCIS (Netherlands)

    Hakkarainen, Elina; Pirila, Silja; Kaartinen, Jukka; van der Meere, Jaap J.

    This study evaluated the brain activation state during error making in youth with mild spastic cerebral palsy and a peer control group while carrying out a stimulus recognition task. The key question was whether patients were detecting their own errors and subsequently improving their performance in

  20. Integrated dielectrophoretic and surface plasmonic platform for million-fold improvement in the detection of fluorescent events.

    Science.gov (United States)

    Velmanickam, Logeeshan; Fondakowski, Michael; Lima, Ivan T; Nawarathna, Dharmakeerthi

    2017-07-01

    We present an integrated dielectrophoretic (DEP) and surface plasmonic technique to quantify ∼1 pM of fluorescent molecules in low conductivity buffers. We have established a DEP force on target molecules to bring those molecules and place them on the nanometallic structures (hotspots) for quantification through surface plasmonic effects. Our results show that the DEP is capable of placing the fluorescent molecules on the hotspots, which are depicted as a significant reduction in the fluorescence lifetime of those molecules. To efficiently integrate the DEP and plasmonic effects, we have designed and utilized pearl-shaped interdigitated electrodes (PIDEs) in experiments. These electrodes generate 2-3 times higher DEP force than traditional interdigitated electrodes. Therefore, high-throughput assays can be developed. The nanometallic structures were strategically fabricated in the periphery of PIDEs for smooth integration of DEP and plasmonic detection. With the introduction of DEP, about 106-fold improvement was achieved over existing plasmonic-based detection. Therefore, this simple addition to the existing surface plasmonic-based detection will enable the disease related protein detection.

  1. INTEGRAL Detection of the First Prompt Gamma-Ray Signal Coincident with the Gravitational-wave Event GW170817

    DEFF Research Database (Denmark)

    Savchenko, V.; Ferrigno, C.; Kuulkers, E.

    2017-01-01

    We report the INTernational Gamma-ray Astrophysics Laboratory (INTEGRAL) detection of the short gamma-ray burst GRB 170817A (discovered by Fermi-GBM) with a signal-to-noise ratio of 4.6, and, for the first time, its association with the gravitational waves (GWs) from binary neutron star (BNS...

  2. Does QRS Voltage Correction by Body Mass Index Improve the Accuracy of Electrocardiography in Detecting Left Ventricular Hypertrophy and Predicting Cardiovascular Events in a General Population?

    Science.gov (United States)

    Cuspidi, Cesare; Facchetti, Rita; Bombelli, Michele; Sala, Carla; Tadic, Marijana; Grassi, Guido; Mancia, Giuseppe

    2016-05-01

    The authors assessed the value of body mass index (BMI) correction of two electrocardiographic criteria in improving detection of left ventricular hypertrophy (LVH) and prediction of cardiovascular and all-cause mortality in the Italian study Pressioni Arteriose Monitorate E Loro Associazioni (PAMELA) population. At entry, 1549 patients underwent diagnostic tests, 24-hour ambulatory blood pressure (BP) monitoring, standard electrocardiography, and echocardiography. The BMI-corrected Cornell voltage and Sokolow-Lyon voltage criteria provided better results for detection of echocardiographic LVH as compared with unadjusted electrocardiographic parameters. Cornell voltage index, but not Sokolow-Lyon index, was associated with an increased risk of cardiovascular events (and all-cause mortality). The adjusted risk of cardiovascular events related to one-standard deviation increment of BMI-corrected Cornell voltage was similar to that conferred by the uncorrected criterion in the total population, but outperformed in obese participants. These findings show that correction for BMI may improve the diagnostic accuracy of Cornell voltage index in detecting LVH and prediction of cardiovascular mortality in obese individuals. © 2015 Wiley Periodicals, Inc.

  3. Detection of paroxysmal atrial fibrillation by 30-day event monitoring in cryptogenic ischemic stroke: the Stroke and Monitoring for PAF in Real Time (SMART) Registry.

    Science.gov (United States)

    Flint, Alexander C; Banki, Nader M; Ren, Xiushui; Rao, Vivek A; Go, Alan S

    2012-10-01

    Patients with cryptogenic ischemic stroke may have undetected paroxysmal atrial fibrillation (PAF). We established the Stroke and Monitoring for PAF in Real Time (SMART) Registry to determine the yield of 30-day outpatient PAF monitoring in cryptogenic ischemic stroke. The SMART Registry was a 3-year, prospective multicenter registry of 239 patients with cryptogenic ischemic stroke undergoing 30-day outpatient autotriggered PAF detection in Kaiser Permanente Northern California. In intention-to-monitor analysis, PAF was detected in 29 of 239 patients (12.1%; 95% CI, 8.6%-16.9%). After retrospective chart review was performed, a new diagnosis of PAF was confirmed in 26 of 236 patients (11.0%; 95% CI, 7.6%-15.7%). The majority of detected PAF events were asymptomatic; only 6 of 98 recorded PAF events (6.1%) were patient-triggered or associated with symptoms. -Approximately 1 in every 9 patients with cryptogenic ischemic stroke was found to have new PAF within 30 days. Routine monitoring in this population should be strongly considered.

  4. Evaluation of feature extraction techniques on event-related potentials for detection of attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Castro-Cabrera, P; Gomez-Garcia, J; Restrepo, F; Moscoso, O; Castellanos-Dominguez, G

    2010-01-01

    Event-related potentials (ERPs) are one of the most informative and dynamic methods of monitoring cognitive processes, which are widely used in clinical research to deal a variety of psychiatric and neurological disorders as attention-deficit/hyperactivity disorder (ADHD). This work proposes an extraction and selection methodology for discriminating between normal and pathological patients with ADHD by using ERPs. Three different sets of features (morphological, wavelets, and nonlinear based) are analyzed, looking for the best classification accuracy. The results show that the wavelet features provided a good discriminative capability, but it improved by combining all the set of features and applying a feature selection algorithm, reaching a maximum accuracy rate of 91.3%.

  5. [Is stress cardiovascular magnetic resonance really useful to detect ischemia and predict events in patients with different cardiovascular risk profile?

    Science.gov (United States)

    Esteban-Fernández, Alberto; Coma-Canella, Isabel; Bastarrika, Gorka; Barba-Cosials, Joaquín; Azcárate-Agüero, Pedro M

    The aim of this study was to evaluate the diagnostic and prognostic usefulness of stress cardiovascular magnetic resonance (stress CMR) in patients with different cardiovascular risk profile and to assess if the degree of hypoperfusion is important to guide clinical decisions. We included patients submitted to adenosine stress CMR to rule out myocardial ischemia. We evaluated its diagnostic accuracy with likelihood ratio (LR) and its prognostic value with survival curves and a Cox regression model. 295 patients were studied. The positive LR was 3.40 and the negative one 0.47. The maximal usefulness of the test was found in patients without previous ischemic cardiomyopathy (positive LR 4.85), patients with atypical chest pain (positive LR 8.56), patients with low or intermediate cardiovascular risk (positive LR 3.87) and those with moderate or severe hypoperfusion (positive LR 8.63). Sixty cardiovascular major events were registered. The best survival prognosis was found in patients with a negative result (p=0.001) or mild hypoperfusion (p=0.038). In the multivariate analysis, a moderate or severe hypoperfusion increased cardiovascular event probability (HR=2.2; IC 95% 1.26-3.92), with no differences between a mild positive and a negative result (HR=0.93; IC 95% 0.38-2.28). Stress CMR was specially useful in patients with low or intermediate cardiovascular risk, patients with atypical chest pain, patients without previous ischemic cardiomyopathy and those with moderate or severe hypoperfusion. Hypoperfusion degree was the main issue factor to guide clinical decisions. Copyright © 2016 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

  6. Simulation and prototyping of 2 m long resistive plate chambers for detection of fast neutrons and multi-neutron event identification

    Energy Technology Data Exchange (ETDEWEB)

    Elekes, Z., E-mail: z.elekes@hzdr.de [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Aumann, T. [GSI Helmholtzzentrumfür Schwerionenforschung, Darmstadt (Germany); Technische Universität Darmstadt, Darmstadt (Germany); Bemmerer, D. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Boretzky, K. [GSI Helmholtzzentrumfür Schwerionenforschung, Darmstadt (Germany); Caesar, C. [GSI Helmholtzzentrumfür Schwerionenforschung, Darmstadt (Germany); Technische Universität Darmstadt, Darmstadt (Germany); Cowan, T.C. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Technische Universität Dresden, Dresden (Germany); Hehner, J.; Heil, M. [GSI Helmholtzzentrumfür Schwerionenforschung, Darmstadt (Germany); Kempe, M. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Rossi, D. [GSI Helmholtzzentrumfür Schwerionenforschung, Darmstadt (Germany); Röder, M. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Technische Universität Dresden, Dresden (Germany); Simon, H. [GSI Helmholtzzentrumfür Schwerionenforschung, Darmstadt (Germany); Sobiella, M.; Stach, D. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Reinhardt, T. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Technische Universität Dresden, Dresden (Germany); Wagner, A.; Yakorev, D. [Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Zilges, A. [Universität zu Köln, Köln (Germany); Zuber, K. [Technische Universität Dresden, Dresden (Germany)

    2013-02-11

    Resistive plate chamber (RPC) prototypes of 2 m length were simulated and built. The experimental tests using a 31 MeV electron beam, discussed in details, showed an efficiency higher than 90% and an excellent time resolution of around σ=100ps. Furthermore, comprehensive simulations were performed by GEANT4 toolkit in order to study the possible use of these RPCs for fast neutron (200 MeV–1 GeV) detection and multi-neutron event identification. The validation of simulation parameters was carried out via a comparison to experimental data. A possible setup for invariant mass spectroscopy of multi-neutron emission is presented and the characteristics are discussed. The results show that the setup has a high detection efficiency. Its capability of determining the momentum of the outgoing neutrons and reconstructing the relative energy between the fragments from nuclear reactions is demonstrated for different scenarios.

  7. A multilevel analytical approach for detection and visualization of intracellular NO production and nitrosation events using diaminofluoresceins.

    Science.gov (United States)

    Cortese-Krott, Miriam M; Rodriguez-Mateos, Ana; Kuhnle, Gunter G C; Brown, Geoff; Feelisch, Martin; Kelm, Malte

    2012-12-01

    Diaminofluoresceins are widely used probes for detection and intracellular localization of NO formation in cultured/isolated cells and intact tissues. The fluorinated derivative 4-amino-5-methylamino-2',7'-difluorofluorescein (DAF-FM) has gained increasing popularity in recent years because of its improved NO sensitivity, pH stability, and resistance to photobleaching compared to the first-generation compound, DAF-2. Detection of NO production by either reagent relies on conversion of the parent compound into a fluorescent triazole, DAF-FM-T and DAF-2-T, respectively. Although this reaction is specific for NO and/or reactive nitrosating species, it is also affected by the presence of oxidants/antioxidants. Moreover, the reaction with other molecules can lead to the formation of fluorescent products other than the expected triazole. Thus additional controls and structural confirmation of the reaction products are essential. Using human red blood cells as an exemplary cellular system we here describe robust protocols for the analysis of intracellular DAF-FM-T formation using an array of fluorescence-based methods (laser-scanning fluorescence microscopy, flow cytometry, and fluorimetry) and analytical separation techniques (reversed-phase HPLC and LC-MS/MS). When used in combination, these assays afford unequivocal identification of the fluorescent signal as being derived from NO and are applicable to most other cellular systems without or with only minor modifications. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. An event-specific method for the detection and quantification of ML01, a genetically modified Saccharomyces cerevisiae wine strain, using quantitative PCR.

    Science.gov (United States)

    Vaudano, Enrico; Costantini, Antonella; Garcia-Moruno, Emilia

    2016-10-03

    The availability of genetically modified (GM) yeasts for winemaking and, in particular, transgenic strains based on the integration of genetic constructs deriving from other organisms into the genome of Saccharomyces cerevisiae, has been a reality for several years. Despite this, their use is only authorized in a few countries and limited to two strains: ML01, able to convert malic acid into lactic acid during alcoholic fermentation, and ECMo01 suitable for reducing the risk of carbamate production. In this work we propose a quali-quantitative culture-independent method for the detection of GM yeast ML01 in commercial preparations of ADY (Active Dry Yeast) consisting of efficient extraction of DNA and qPCR (quantitative PCR) analysis based on event-specific assay targeting MLC (malolactic cassette), and a taxon-specific S. cerevisiae assay detecting the MRP2 gene. The ADY DNA extraction methodology has been shown to provide good purity DNA suitable for subsequent qPCR. The MLC and MRP2 qPCR assay showed characteristics of specificity, dynamic range, limit of quantification (LOQ) limit of detection (LOD), precision and trueness, which were fully compliant with international reference guidelines. The method has been shown to reliably detect 0.005% (mass/mass) of GM ML01 S. cerevisiae in commercial preparations of ADY. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Present self, past self and close-other: Event-related potential study of face and name detection.

    Science.gov (United States)

    Kotlewska, Ilona; Nowicka, Anna

    2015-09-01

    A growing body of evidence suggests that information regarding the past self and other people is processed similarly. However, there is not much evidence supporting this notion at the neural level. In this event-related potential (ERP) study we examined processing of one's own marital and family name (i.e., present and past self-name, respectively) and images of present and past self-face in comparison to names and faces of others (the close-other, famous and unknown person). Amplitudes of P300 (a late ERP component associated with attention, emotion, and autobiographical memory) to self-face and self-name, either present or past, was enhanced in comparison to famous and unknown faces and names. No differences, however, were observed between the past and present self-names as well as between past and present self-faces. Moreover, P300 amplitude to the past self-face was enhanced in the right hemisphere in comparison to the close-other's face, whereas P300 amplitudes to the past self-name and the close-other's name did not differ. Thus, our results indicated that information related to non-physical aspects of the past self were processed similarly to the close-other. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Detecting Drug Interactions From Adverse-Event Reports: Interaction Between Paroxetine and Pravastatin Increases Blood Glucose Levels

    Science.gov (United States)

    Tatonetti, NP; Denny, JC; Murphy, SN; Fernald, GH; Krishnan, G; Castro, V; Yue, P; Tsau, PS; Kohane, I; Roden, DM; Altman, RB

    2011-01-01

    The lipid-lowering agent pravastatin and the antidepressant paroxetine are among the most widely prescribed drugs in the world. Unexpected interactions between them could have important public health implications. We mined the US Food and Drug Administration’s (FDA’s) Adverse Event Reporting System (AERS) for side-effect profiles involving glucose homeostasis and found a surprisingly strong signal for comedication with pravastatin and paroxetine. We retrospectively evaluated changes in blood glucose in 104 patients with diabetes and 135 without diabetes who had received comedication with these two drugs, using data in electronic medical record (EMR) systems of three geographically distinct sites. We assessed the mean random blood glucose levels before and after treatment with the drugs. We found that pravastatin and paroxetine, when administered together, had a synergistic effect on blood glucose. The average increase was 19 mg/dl (1.0 mmol/l) overall, and in those with diabetes it was 48 mg/dl (2.7 mmol/l). In contrast, neither drug administered singly was associated with such changes in glucose levels. An increase in glucose levels is not a general effect of combined therapy with selective serotonin reuptake inhibitors (SSRIs) and statins. PMID:21613990

  11. Data-mining for detecting signals of adverse drug reactions of fluoxetine using the Korea Adverse Event Reporting System (KAERS) database.

    Science.gov (United States)

    Kim, Seonji; Park, Kyounghoon; Kim, Mi-Sook; Yang, Bo Ram; Choi, Hyun Jin; Park, Byung-Joo

    2017-10-01

    Selective serotonin reuptake inhibitors (SSRIs) have become one of the most broadly used medications in psychiatry. Fluoxetine is the first representative antidepressant SSRI drug approved by the Food and Drug Administration (FDA) in 1987. Safety information on fluoxetine use alone was less reported than its combined use with other drugs. There were no published papers on adverse drug reactions (ADRs) of fluoxetine analyzing spontaneous adverse events reports. We detected signals of the adverse drug reactions of fluoxetine by data mining using the Korea Adverse Events Reporting System (KAERS) database. We defined signals in this study by the reporting odds ratios (ROR), proportional reporting ratios (PRR), and information components (IC) indices. The KAERS database included 860,224 AE reports, among which 866 reports contained fluoxetine. We compared the labels of fluoxetine among the United States, UK, Germany, France, China, and Korea. Some of the signals, including emotional lability, myositis, spinal stenosis, paradoxical drug reaction, drug dependence, extrapyramidal disorder, adrenal insufficiency, and intracranial hemorrhage, were not labeled in the six countries. In conclusion, we identified new signals that were not known at the time of market approval. However, certain factors should be required for signal evaluation, such as clinical significance, preventability, and causality of the detected signals. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. EVALUATION OF THE RELIABILITY OF DETECTION OF ADVERSE EVENTS АS A DYNAMIC PROCESS IN THE MULTY-TECNOLOGY PLATFORM «SOFTWARE PACKAGE ELECTRONICS MANAGERY SECURITY GUYRD»

    Directory of Open Access Journals (Sweden)

    L. N. Elisov

    2015-01-01

    Full Text Available The paper conciders one of the operational procedures implemented in the multy-functional technological. This package provides an automated system for providing airport aviation security. The procedure performs dynamic evaluation of reliability of negative events detection.

  13. Evaluation of epidemic intelligence systems integrated in the early alerting and reporting project for the detection of A/H5N1 influenza events.

    Science.gov (United States)

    Barboza, Philippe; Vaillant, Laetitia; Mawudeku, Abla; Nelson, Noele P; Hartley, David M; Madoff, Lawrence C; Linge, Jens P; Collier, Nigel; Brownstein, John S; Yangarber, Roman; Astagneau, Pascal

    2013-01-01

    The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI) Early Alerting and Reporting (EAR) project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7-13.8). This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users.

  14. Evaluation of epidemic intelligence systems integrated in the early alerting and reporting project for the detection of A/H5N1 influenza events.

    Directory of Open Access Journals (Sweden)

    Philippe Barboza

    Full Text Available The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI Early Alerting and Reporting (EAR project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7-13.8. This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users.

  15. A study of N250 event-related brain potential during face and non-face detection tasks.

    Science.gov (United States)

    Nasr, Shahin; Esteky, Hossein

    2009-05-08

    Face perception relies on activation of a complex set of different neural modules. In this study, we assessed the stimulus selectivity of the occipitotemporal N250 ERP component and the possible link between its neural substrates and modules underlying preceding (N170/VPP) and following (P400) category selective ERPs. We recorded N250 during face and leaf detection tasks while we varied stimulus visibility from trial to trial by using a backward masking paradigm. Our results revealed that N250, but not the other tested potentials, was exclusively sensitive to the visibility of faces even when the non-face stimuli served as the task target. We also found a correlation between evoked N170 and N250, in response to face stimuli and to a lesser extent in response to other non-face objects, irrespective of the subjects' task. Besides N250, P400 also showed a strong correlation with N170, but here, the amount of correlation was not affected by stimulus category. Interestingly, despite N250 and N400 correlation with N170, we did not find any correlation between N250 and P400, suggesting that modules underlying these ERP components belong to two different face-processing pathways. We suggest that N250 is initiated by N170 and indexes processes exclusively responsible for encoding faces.

  16. The use of single bipolar scalp derivation for the detection of ictal events during long-term EEG monitoring.

    Science.gov (United States)

    Bennis, Frank C; Geertsema, Evelien E; Velis, Demetrios N; Reus, Elise Em; Visser, Gerhard H

    2017-09-01

    Epilepsy is difficult to diagnose using routine EEG recordings of short duration in patients who have low seizure frequency. Long-term EEG may be useful but is impractical in an out-of-hospital setting. We investigated whether single-channel scalp EEG placed behind the earlobe is suitable for seizure identification during prolonged EEG monitoring. Scalp EEG samples were selected from subjects over 15 years of age, and comprised two segments of either background followed by seizure or background followed by background. Bipolar EEG derivations in three directions (F8-T8, C4-T8 and T8-P8) were evaluated for the presence of a seizure by two experienced reviewers. For each EEG segment containing a seizure, one pair of electrodes was oriented towards the suspected region of seizure onset, while two pairs of electrodes were oriented elsewhere. The EEG data contained five frontally localized seizures, five parietal, five temporal, two occipital, and four primary or secondary generalized seizures. The sensitivity and specificity for recognition of seizures was 86% and 95% for Reviewer 1, and 79% and 99% for Reviewer 2, respectively. When identifying a seizure with the lead orientation towards the region of seizure onset, both reviewers identified 20 out of 21 seizures (95%). When the lead was not oriented towards the region of seizure onset, the reviewers identified 34 and 30 out of 42 ictal records correctly, respectively. These results suggest that it is possible to identify epileptic seizures by bipolar EEG derivation using only two scalp electrodes. Lead orientation towards the suspected region of seizure onset is important for optimal detection sensitivity.

  17. Detection of prospective memory deficits in mild cognitive impairment of suspected Alzheimer's disease etiology using a novel event-based prospective memory task.

    LENUS (Irish Health Repository)

    Blanco-Campal, Alberto

    2009-01-01

    We investigated the relative discriminatory efficacy of an event-based prospective memory (PM) task, in which specificity of the instructions and perceptual salience of the PM cue were manipulated, compared with two widely used retrospective memory (RM) tests (Rivermead Paragraph Recall Test and CERAD-Word List Test), when detecting mild cognitive impairment of suspected Alzheimer\\'s disease etiology (MCI-AD) (N = 19) from normal controls (NC) (N = 21). Statistical analyses showed high discriminatory capacity of the PM task for detecting MCI-AD. The Non-Specific-Non-Salient condition proved particularly useful in detecting MCI-AD, possibly reflecting the difficulty of the task, requiring more strategic attentional resources to monitor for the PM cue. With a cutoff score of <4\\/10, the Non-Specific-Non-Salient condition achieved a sensitivity = 84%, and a specificity = 95%, superior to the most discriminative RM test used (CERAD-Total Learning: sensitivity = 83%; specificity = 76%). Results suggest that PM is an early sign of memory failure in MCI-AD and may be a more pronounced deficit than retrospective failure, probably reflecting the greater self-initiated retrieval demands involved in the PM task used. Limitations include the relatively small sample size, and the use of a convenience sample (i.e. memory clinic attenders and healthy active volunteers), reducing the generalizability of the results, which should be regarded as preliminary. (JINS, 2009, 15, 154-159.).

  18. Evidence from auditory and visual event-related potential (ERP) studies of deviance detection (MMN and vMMN) linking predictive coding theories and perceptual object representations.

    Science.gov (United States)

    Winkler, István; Czigler, István

    2012-02-01

    Predictive coding theories posit that the perceptual system is structured as a hierarchically organized set of generative models with increasingly general models at higher levels. The difference between model predictions and the actual input (prediction error) drives model selection and adaptation processes minimizing the prediction error. Event-related brain potentials elicited by sensory deviance are thought to reflect the processing of prediction error at an intermediate level in the hierarchy. We review evidence from auditory and visual studies of deviance detection suggesting that the memory representations inferred from these studies meet the criteria set for perceptual object representations. Based on this evidence we then argue that these perceptual object representations are closely related to the generative models assumed by predictive coding theories. Copyright © 2011 Elsevier B.V. All rights reserved.

  19. Calibration of a solid state nuclear track detector (SSNTD) with high detection threshold to search for rare events in cosmic rays

    CERN Document Server

    Dey, S; Maulik, A; Sibaji, R; Saha, Swapan K; Syam, D; Pakarinen, J; Voulot, D; Wenander, F

    2011-01-01

    We have investigated a commercially available polymer for its suitability as a solid state nuclear track detector (SSNTD). We identified that polymer to be polyethylene terephthalate (PET) and found that it has a higher detection threshold compared to many other widely used SSNTDs which makes this detector particularly suitable for rare event search in cosmic rays as it eliminates the dominant low Z background. Systematic studies were carried out to determine its charge response which is essential before any new material can be used as an SSNTD. In this paper we describe the charge response of PET to 129Xe, 78Kr and 49Ti ions from the REX-ISOLDE facility at CERN, present the calibration curve for PET and characterize it as a nuclear track detector.

  20. Noninvasive detection of increased carotid artery temperature in patients with coronary artery disease predicts major cardiovascular events at one year: Results from a prospective multicenter study.

    Science.gov (United States)

    Toutouzas, Konstantinos; Benetos, Georgios; Koutagiar, Iosif; Barampoutis, Nikolaos; Mitropoulou, Fotini; Davlouros, Periklis; Sfikakis, Petros P; Alexopoulos, Dimitrios; Stefanadis, Christodoulos; Siores, Elias; Tousoulis, Dimitris

    2017-07-01

    Limited prospective data have been reported regarding the impact of carotid inflammation on cardiovascular events in patients with coronary artery disease (CAD). Microwave radiometry (MWR) is a noninvasive, simple method that has been used for evaluation of carotid artery temperature which, when increased, predicts 'inflamed' plaques with vulnerable characteristics. We prospectively tested the hypothesis that increased carotid artery temperature predicts future cerebro- and cardiovascular events in patients with CAD. Consecutive patients from 3 centers, with documented CAD by coronary angiography, were studied. In both carotid arteries, common carotid intima-media thickness and plaque thickness were evaluated by ultrasound. Temperature difference (ΔT), measured by MWR, was considered as the maximal temperature along the carotid artery minus the minimum; ΔT ≥0.90 °C was assigned as high. Major cardiovascular events (MACE, death, stroke, myocardial infarction or revascularization) were recorded during the following year. In total, 250 patients were studied; of them 40 patients (16%) had high ΔT values in both carotid arteries. MACEs occurred in 30% of patients having bilateral high ΔT versus 3.8% in the remaining patients (p<0.001). Bilateral high ΔT was independently associated with increased one-year MACE rate (HR = 6.32, 95% CI 2.42-16.53, p<0.001, by multivariate cox regression hazard model). The addition of ΔT information on a baseline model based on cardiovascular risk factors and extent of CAD significantly increased the prognostic value of the model (c-statistic increase 0.744 to 0.845, p dif  = 0.05) CONCLUSIONS: Carotid inflammation, detected by MWR, has an incremental prognostic value in patients with documented CAD. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Impaired target detection in schizophrenia and the ventral attentional network: Findings from a joint event-related potential–functional MRI analysis

    Directory of Open Access Journals (Sweden)

    Jonathan K. Wynn

    2015-01-01

    Full Text Available Schizophrenia patients have abnormal neural responses to salient, infrequent events. We integrated event-related potentials (ERP and fMRI to examine the contributions of the ventral (salience and dorsal (sustained attention networks to this dysfunctional neural activation. Twenty-one schizophrenia patients and 22 healthy controls were assessed in separate sessions with ERP and fMRI during a visual oddball task. Visual P100, N100, and P300 ERP waveforms and fMRI activation were assessed. A joint independent components analysis (jICA on the ERP and fMRI data were conducted. Patients exhibited reduced P300, but not P100 or N100, amplitudes to targets and reduced fMRI neural activation in both dorsal and ventral attentional networks compared with controls. However, the jICA revealed that the P300 was linked specifically to activation in the ventral (salience network, including anterior cingulate, anterior insula, and temporal parietal junction, with patients exhibiting significantly lower activation. The P100 and N100 were linked to activation in the dorsal (sustained network, with no group differences in level of activation. This joint analysis approach revealed the nature of target detection deficits that were not discernable by either imaging methodology alone, highlighting the utility of a multimodal fMRI and ERP approach to understand attentional network deficits in schizophrenia.

  2. Drug Adverse Event Detection in Health Plan Data Using the Gamma Poisson Shrinker and Comparison to the Tree-based Scan Statistic

    Directory of Open Access Journals (Sweden)

    David Smith

    2013-03-01

    Full Text Available Background: Drug adverse event (AE signal detection using the Gamma Poisson Shrinker (GPS is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan. Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds.

  3. On the Agreement between Manual and Automated Methods for Single-Trial Detection and Estimation of Features from Event-Related Potentials.

    Science.gov (United States)

    Biurrun Manresa, José A; Arguissain, Federico G; Medina Redondo, David E; Mørch, Carsten D; Andersen, Ole K

    2015-01-01

    The agreement between humans and algorithms on whether an event-related potential (ERP) is present or not and the level of variation in the estimated values of its relevant features are largely unknown. Thus, the aim of this study was to determine the categorical and quantitative agreement between manual and automated methods for single-trial detection and estimation of ERP features. To this end, ERPs were elicited in sixteen healthy volunteers using electrical stimulation at graded intensities below and above the nociceptive withdrawal reflex threshold. Presence/absence of an ERP peak (categorical outcome) and its amplitude and latency (quantitative outcome) in each single-trial were evaluated independently by two human observers and two automated algorithms taken from existing literature. Categorical agreement was assessed using percentage positive and negative agreement and Cohen's κ, whereas quantitative agreement was evaluated using Bland-Altman analysis and the coefficient of variation. Typical values for the categorical agreement between manual and automated methods were derived, as well as reference values for the average and maximum differences that can be expected if one method is used instead of the others. Results showed that the human observers presented the highest categorical and quantitative agreement, and there were significantly large differences between detection and estimation of quantitative features among methods. In conclusion, substantial care should be taken in the selection of the detection/estimation approach, since factors like stimulation intensity and expected number of trials with/without response can play a significant role in the outcome of a study.

  4. Detection of Saharan dust and biomass burning events using near-real-time intensive aerosol optical properties in the north-western Mediterranean

    Science.gov (United States)

    Ealo, Marina; Alastuey, Andrés; Ripoll, Anna; Pérez, Noemí; Cruz Minguillón, María; Querol, Xavier; Pandolfi, Marco

    2016-10-01

    The study of Saharan dust events (SDEs) and biomass burning (BB) emissions are both topics of great scientific interest since they are frequent and important polluting scenarios affecting air quality and climate. The main aim of this work is evaluating the feasibility of using near-real-time in situ aerosol optical measurements for the detection of these atmospheric events in the western Mediterranean Basin (WMB). With this aim, intensive aerosol optical properties (SAE: scattering Ångström exponent, AAE: absorption Ångström exponent, SSAAE: single scattering albedo Ångström exponent and g: asymmetry parameter) were derived from multi-wavelength aerosol light scattering, hemispheric backscattering and absorption measurements performed at regional (Montseny; MSY, 720 m a.s.l.) and continental (Montsec; MSA, 1570 m a.s.l.) background sites in the WMB. A sensitivity study aiming at calibrating the measured intensive optical properties for SDEs and BB detection is presented and discussed. The detection of SDEs by means of the SSAAE parameter and Ångström matrix (made up by SAE and AAE) depended on the altitude of the measurement station and on SDE intensity. At MSA (mountain-top site) SSAAE detected around 85 % of SDEs compared with 50 % at the MSY station, where pollution episodes dominated by fine anthropogenic particles frequently masked the effect of mineral dust on optical properties during less intense SDEs. Furthermore, an interesting feature of SSAAE was its capability to detect the presence of mineral dust after the end of SDEs. Thus, resuspension processes driven by summer regional atmospheric circulations and dry conditions after SDEs favoured the accumulation of mineral dust at regional level having important consequences for air quality. On average, SAE, AAE and g ranged between -0.7 and 1, 1.3 and 2.5 and 0.5 and 0.75 respectively during SDEs. Based on the aethalometer model, BB contribution to equivalent black carbon (BC) accounted for 36 and 40

  5. Detection of Saharan dust and biomass burning events using near-real-time intensive aerosol optical properties in the north-western Mediterranean

    Directory of Open Access Journals (Sweden)

    M. Ealo

    2016-10-01

    Full Text Available The study of Saharan dust events (SDEs and biomass burning (BB emissions are both topics of great scientific interest since they are frequent and important polluting scenarios affecting air quality and climate. The main aim of this work is evaluating the feasibility of using near-real-time in situ aerosol optical measurements for the detection of these atmospheric events in the western Mediterranean Basin (WMB. With this aim, intensive aerosol optical properties (SAE: scattering Ångström exponent, AAE: absorption Ångström exponent, SSAAE: single scattering albedo Ångström exponent and g: asymmetry parameter were derived from multi-wavelength aerosol light scattering, hemispheric backscattering and absorption measurements performed at regional (Montseny; MSY, 720 m a.s.l. and continental (Montsec; MSA, 1570 m a.s.l. background sites in the WMB. A sensitivity study aiming at calibrating the measured intensive optical properties for SDEs and BB detection is presented and discussed. The detection of SDEs by means of the SSAAE parameter and Ångström matrix (made up by SAE and AAE depended on the altitude of the measurement station and on SDE intensity. At MSA (mountain-top site SSAAE detected around 85 % of SDEs compared with 50 % at the MSY station, where pollution episodes dominated by fine anthropogenic particles frequently masked the effect of mineral dust on optical properties during less intense SDEs. Furthermore, an interesting feature of SSAAE was its capability to detect the presence of mineral dust after the end of SDEs. Thus, resuspension processes driven by summer regional atmospheric circulations and dry conditions after SDEs favoured the accumulation of mineral dust at regional level having important consequences for air quality. On average, SAE, AAE and g ranged between −0.7 and 1, 1.3 and 2.5 and 0.5 and 0.75 respectively during SDEs. Based on the aethalometer model, BB contribution to equivalent black carbon (BC

  6. On the feasibility of detecting the ionospheric effects of solar energetic particle events at Mars using spacecraft‐spacecraft radio links

    National Research Council Canada - National Science Library

    Withers, Paul

    2016-01-01

    ...) events on the ionosphere of Mars are substantial, but observations have not yet provided quantitative information on the magnitude or vertical distribution of the plasma produced below 100 km by SEP events...

  7. Determination of Acoustic Cavitation Probabilities and Thresholds Using a Single Focusing Transducer to Induce and Detect Acoustic Cavitation Events: I. Method and Terminology.

    Science.gov (United States)

    Haller, Julian; Wilkens, Volker; Shaw, Adam

    2018-02-01

    A method to determine acoustic cavitation probabilities in tissue-mimicking materials (TMMs) is described that uses a high-intensity focused ultrasound (HIFU) transducer for both inducing and detecting the acoustic cavitation events. The method was evaluated by studying acoustic cavitation probabilities in agar-based TMMs with and without scatterers and for different sonication modes like continuous wave, single pulses (microseconds to milliseconds) and repeated burst signals. Acoustic cavitation thresholds (defined here as the peak rarefactional in situ pressure at which the acoustic cavitation probability reaches 50%) at a frequency of 1.06 MHz were observed between 1.1 MPa (for 1 s of continuous wave sonication) and 4.6 MPa (for 1 s of a repeated burst signal with 25-cycle burst length and 10-ms burst period) in a 3% (by weight) agar phantom without scatterers. The method and its evaluation are described, and general terminology useful for standardizing the description of insonation conditions and comparing results is provided. In the accompanying second part, the presented method is used to systematically study the acoustic cavitation thresholds in the same material for a range of sonication modes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  8. Slow slip events in the Kii Peninsula and Shikoku, Japan detected by strain changes at the integrated observatories of Geological Survey of Japan, AIST

    Science.gov (United States)

    Itaba, S.; Ohtani, R.; Kitagawa, Y.; Matsumoto, N.; Koizumi, N.

    2009-12-01

    In 2006, Geological Survey of Japan (GSJ), National Institute of Advanced Industrial Science and Technology (AIST) started constructing integrated observatories in and around Shikoku and Kii Peninsula, Japan for research on the Tonankai and Nankai earthquakes. Two observatories were constructed at Kii Peninsula in June 2007, and ten were completed in January 2009. Each observatory has three wells where water temperature, water level (pressure) and ground motion are observed. At one of the three wells, crustal strain is also observed by a multi-component borehole strain meter. According to Automatic Tremor Monitoring System (ATMOS) of Hiroshima University, 11 tremor activities have occurred in the Kii Peninsula since June 2007. We detected strain changes related to these tremor activities. The changes can be explained by short-term slow slip events (SSEs) occurring at several segments of the plate boundary, whose locations are consistent with the tremor activities (e.g. Itaba et al., 2009a). We analyzed these SSEs with the forward method in consideration of locations of the tremors. On the other hand, the observation suggested the existence of SSEs before or without the tremors (e.g. Fukuda and Sagiya, 2008; Itaba et al., 2009b). Therefore, it is important to detect SSEs just by strain changes. We tried to decide the fault planes for SSEs only using the strain data of the observatories of AIST. Since it is difficult to detect strain changes related to SSEs at two or more observatories of AIST, we decided the fault plain by a grid-search method. As a result, the fault plains for SSEs were consistent with the locations of the tremors. References Fukuda, M. and T. Sagiya, Slow strain changes recorded at Shingu borehole station in the southeastern Kii peninsula, The 7th General Assembly of Asian Seismological Commission and The 2008 Fall meeting of Seismological Society of Japan, Tsukuba, 2008. Itaba, S., N. Koizumi, N. Matsumoto and R. Ohtani, Continuous Observation of

  9. Gap detection measured with electrically evoked auditory event-related potentials and speech-perception abilities in children with auditory neuropathy spectrum disorder.

    Science.gov (United States)

    He, Shuman; Grose, John H; Teagle, Holly F B; Woodard, Jennifer; Park, Lisa R; Hatch, Debora R; Buchman, Craig A

    2013-01-01

    This study aimed (1) to investigate the feasibility of recording the electrically evoked auditory event-related potential (eERP), including the onset P1-N1-P2 complex and the electrically evoked auditory change complex (EACC) in response to temporal gaps, in children with auditory neuropathy spectrum disorder (ANSD); and (2) to evaluate the relationship between these measures and speech-perception abilities in these subjects. Fifteen ANSD children who are Cochlear Nucleus device users participated in this study. For each subject, the speech-processor microphone was bypassed and the eERPs were elicited by direct stimulation of one mid-array electrode (electrode 12). The stimulus was a train of biphasic current pulses 800 msec in duration. Two basic stimulation conditions were used to elicit the eERP. In the no-gap condition, the entire pulse train was delivered uninterrupted to electrode 12, and the onset P1-N1-P2 complex was measured relative to the stimulus onset. In the gapped condition, the stimulus consisted of two pulse train bursts, each being 400 msec in duration, presented sequentially on the same electrode and separated by one of five gaps (i.e., 5, 10, 20, 50, and 100 msec). Open-set speech-perception ability of these subjects with ANSD was assessed using the phonetically balanced kindergarten (PBK) word lists presented at 60 dB SPL, using monitored live voice in a sound booth. The eERPs were recorded from all subjects with ANSD who participated in this study. There were no significant differences in test-retest reliability, root mean square amplitude or P1 latency for the onset P1-N1-P2 complex between subjects with good (>70% correct on PBK words) and poorer speech-perception performance. In general, the EACC showed less mature morphological characteristics than the onset P1-N1-P2 response recorded from the same subject. There was a robust correlation between the PBK word scores and the EACC thresholds for gap detection. Subjects with poorer speech

  10. Histopathological events and detection of Metarhizium anisopliae using specific primers in infected immature stages of the fruit fly Anastrepha fraterculus (Wiedemann, 1830 (Diptera: Tephritidae

    Directory of Open Access Journals (Sweden)

    IJ. Bechara

    Full Text Available The fungus Metarhizium anisopliae is used on a large scale in Brazil as a microbial control agent against the sugar cane spittlebugs, Mahanarva posticata and M. fimbriolata (Hemiptera., Cercopidae. We applied strain E9 of M. anisopliae in a bioassay on soil, with field doses of conidia to determine if it can cause infection, disease and mortality in immature stages of Anastrepha fraterculus, the South American fruit fly. All the events were studied histologically and at the molecular level during the disease cycle, using a novel histological technique, light green staining, associated with light microscopy, and by PCR, using a specific DNA primer developed for M. anisopliae capable to identify Brazilian strains like E9. The entire infection cycle, which starts by conidial adhesion to the cuticle of the host, followed by germination with or without the formation of an appressorium, penetration through the cuticle and colonisation, with development of a dimorphic phase, hyphal bodies in the hemocoel, and death of the host, lasted 96 hours under the bioassay conditions, similar to what occurs under field conditions. During the disease cycle, the propagules of the entomopathogenic fungus were detected by identifying DNA with the specific primer ITSMet: 5' TCTGAATTTTTTATAAGTAT 3' with ITS4 (5' TCCTCCGCTTATTGATATGC 3' as a reverse primer. This simple methodology permits in situ studies of the infective process, contributing to our understanding of the host-pathogen relationship and allowing monitoring of the efficacy and survival of this entomopathogenic fungus in large-scale applications in the field. It also facilitates monitoring the environmental impact of M. anisopliae on non-target insects.

  11. BOLD response to deviant face detection informed by P300 event-related potential parameters: a simultaneous ERP-fMRI study.

    Science.gov (United States)

    Campanella, Salvatore; Bourguignon, Mathieu; Peigneux, Philippe; Metens, Thierry; Nouali, Mustapha; Goldman, Serge; Verbanck, Paul; De Tiège, Xavier

    2013-05-01

    Faces are multi-dimensional stimuli conveying parallel information about identity and emotion. Although event-related potential (ERP) studies have disclosed a P300 component in oddball responses to both deviant identity and emotional target faces, it is hypothesized that partially different neural processes should subtend emotion vs. identity within the core network of face processing. In the present study, we used simultaneous ERP-fMRI recordings and ERP-informed analysis of functional magnetic resonance imaging (fMRI) data to evidence the specific neural networks underlying P300 generation in response to different deviant emotional vs. identity faces. 18 participants were scanned during a visual oddball task in which they had to detect 3 types of deviant faces representing a change in emotion-fear or happiness-or in identity, within a series of frequent neutral ones. Amplitude and latency parameters of the P300 component, recorded for each type of deviant faces, were used to constrain fMRI analyses. Analysis of fMRI data informed by single-trial parameters of the P300 component disclosed specific activation patterns for fearful, happy and identity deviant faces. For fearful faces, P300 amplitudes were associated with BOLD changes in the left fusiform gyrus whereas latencies were linked to left superior orbito-frontal and right fusiform activations. P300 amplitude modulations for happy deviant faces involved the left posterior cingulate gyrus and right parahippocampal regions whereas P300 latencies related to the right insula and left caudate regions. Finally, identity deviant faces were associated with widespread activities involving cortical and subcortical regions when P300 amplitudes were considered, and P300 latencies were associated with activity in right hippocampal/parahippocampal regions. Our results suggest the existence of differential cerebral functional processes involved in the responses to deviant face stimuli, depending on the quality of the

  12. Search for correlations between the arrival directions of IceCube neutrino events and ultrahigh-energy cosmic rays detected by the Pierre Auger Observatory and the Telescope Array

    NARCIS (Netherlands)

    Collaboration, The IceCube; Aartsen, M. G.; Abraham, K.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Ahrens, M.; Altmann, D.; Anderson, T.; Ansseau, I.; Archinger, M.; Arguelles, C.; Arlen, T. C.; Auffenberg, J.; Bai, X.; Barwick, S. W.; Baum, V.; Bay, R.; Beatty, J. J.; Tjus, J. Becker; Becker, K. -H.; Beiser, E.; Berghaus, P.; Berley, D.; Bernardini, E.; Bernhard, A.; Besson, D. Z.; Binder, G.; Bindig, D.; Bissok, M.; Blaufuss, E.; Blumenthal, J.; Boersma, D. J.; Bohm, C.; Börner, M.; Bos, F.; Bose, D.; Böser, S.; Botner, O.; Braun, J.; Brayeur, L.; Bretz, H. -P.; Buzinsky, N.; Casey, J.; Casier, M.; Cheung, E.; Chirkin, D.; Christov, A.; Clark, K.; Classen, L.; Coenders, S.; Cowen, D. F.; Silva, A. H. Cruz; Daughhetee, J.; Davis, J. C.; Day, M.; André, J. P. A. M. de; Clercq, C. De; Rosendo, E. del Pino; Dembinski, H.; Ridder, S. De; Desiati, P.; Vries, K. D. de; Wasseige, G. de; With, M. de; DeYoung, T.; Díaz-Vélez, J. C.; Lorenzo, V. di; Dumm, J. P.; Dunkman, M.; Eberhardt, B.; Ehrhardt, T.; Eichmann, B.; Euler, S.; Evenson, P. A.; Fahey, S.; Fazely, A. R.; Feintzeig, J.; Felde, J.; Filimonov, K.; Finley, C.; Fischer-Wasels, T.; Flis, S.; Fösig, C. -C.; Fuchs, T.; Gaisser, T. K.; Gaior, R.; Gallagher, J.; Gerhardt, L.; Ghorbani, K.; Gier, D.; Gladstone, L.; Glagla, M.; Glüsenkamp, T.; Goldschmidt, A.; Golup, G.; Gonzalez, J. G.; Góra, D.; Grant, D.; Griffith, Z.; Groß, A.; Ha, C.; Haack, C.; Ismail, A. Haj; Hallgren, A.; Halzen, F.; Hansen, E.; Hansmann, B.; Hanson, K.; Hebecker, D.; Heereman, D.; Helbing, K.; Hellauer, R.; Hickford, S.; Hignight, J.; Hill, G. C.; Hoffman, K. D.; Hoffmann, R.; Holzapfel, K.; Homeier, A.; Hoshina, K.; Huang, F.; Huber, M.; Huelsnitz, W.; Hulth, P. O.; Hultqvist, K.; In, S.; Ishihara, A.; Jacobi, E.; Japaridze, G. S.; Jeong, M.; Jero, K.; Jurkovic, M.; Kappes, A.; Karg, T.; Karle, A.; Kauer, M.; Keivani, A.; Kelley, J. L.; Kemp, J.; Kheirandish, A.; Kiryluk, J.; Kläs, J.; Klein, S. R.; Kohnen, G.; Koirala, R.; Kolanoski, H.; Konietz, R.; Köpke, L.; Kopper, C.; Kopper, S.; Koskinen, D. J.; Kowalski, M.; Krings, K.; Kroll, G.; Kroll, M.; Krückl, G.; Kunnen, J.; Kurahashi, N.; Kuwabara, T.; Labare, M.; Lanfranchi, J. L.; Larson, M. J.; Lesiak-Bzdak, M.; Leuermann, M.; Leuner, J.; Lu, L.; Lünemann, J.; Madsen, J.; Maggi, G.; Mahn, K. B. M.; Mandelartz, M.; Maruyama, R.; Mase, K.; Matis, H. S.; Maunu, R.; McNally, F.; Meagher, K.; Medici, M.; Meli, A.; Menne, T.; Merino, G.; Meures, T.; Miarecki, S.; Middell, E.; Mohrmann, L.; Montaruli, T.; Morse, R.; Nahnhauer, R.; Naumann, U.; Neer, G.; Niederhausen, H.; Nowicki, S. C.; Nygren, D. R.; Pollmann, A. Obertacke; Olivas, A.; Omairat, A.; O'Murchadha, A.; Palczewski, T.; Pandya, H.; Pankova, D. V.; Paul, L.; Pepper, J. A.; Heros, C. Pérez de los; Pfendner, C.; Pieloth, D.; Pinat, E.; Posselt, J.; Price, P. B.; Przybylski, G. T.; Quinnan, M.; Raab, C.; Rädel, L.; Rameez, M.; Rawlins, K.; Reimann, R.; Relich, M.; Resconi, E.; Rhode, W.; Richman, M.; Richter, S.; Riedel, B.; Robertson, S.; Rongen, M.; Rott, C.; Ruhe, T.; Ryckbosch, D.; Sabbatini, L.; Sander, H. -G.; Sandrock, A.; Sandroos, J.; Sarkar, S.; Schatto, K.; Schimp, M.; Schmidt, T.; Schoenen, S.; Schöneberg, S.; Schönwald, A.; Schulte, L.; Schumacher, L.; Seckel, D.; Seunarine, S.; Soldin, D.; Song, M.; Spiczak, G. M.; Spiering, C.; Stahlberg, M.; Stamatikos, M.; Stanev, T.; Stasik, A.; Steuer, A.; Stezelberger, T.; Stokstad, R. G.; Stößl, A.; Ström, R.; Strotjohann, N. L.; Sullivan, G. W.; Sutherland, M.; Taavola, H.; Taboada, I.; Tatar, J.; Ter-Antonyan, S.; Terliuk, A.; Tešić, G.; Tilav, S.; Toale, P. A.; Tobin, M. N.; Toscano, S.; Tosi, D.; Tselengidou, M.; Turcati, A.; Unger, E.; Usner, M.; Vallecorsa, S.; Vandenbroucke, J.; Eijndhoven, N. van; Vanheule, S.; Santen, J. van; Veenkamp, J.; Vehring, M.; Voge, M.; Vraeghe, M.; Walck, C.; Wallace, A.; Wallraff, M.; Wandkowsky, N.; Weaver, Ch; Wendt, C.; Westerhoff, S.; Whelan, B. J.; Wiebe, K.; Wiebusch, C. H.; Wille, L.; Williams, D. R.; Wissing, H.; Wolf, M.; Wood, T. R.; Woschnagg, K.; Xu, D. L.; Xu, X. W.; Xu, Y.; Yanez, J. P.; Yodh, G.; Yoshida, S.; Collaboration, M. Zoll The Pierre Auger; Aab, A.; Abreu, P.; Aglietta, M.; Ahn, E. J.; Samarai, I. Al; Albuquerque, I. F. M.; Allekotte, I.; Allison, P.; Almela, A.; Castillo, J. Alvarez; Alvarez-Muñiz, J.; Batista, R. Alves; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andrada, B.; Andringa, S.; Aramo, C.; Arqueros, F.; Arsene, N.; Asorey, H.; Assis, P.; Aublin, J.; Avila, G.; Awal, N.; Badescu, A. M.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellido, J. A.; Berat, C.; Bertaina, M. E.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blaess, S. G.; Blanco, A.; Blanco, M.; Blazek, J.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Borodai, N.; Botti, A. M.; Brack, J.; Brancus, I.; Bretz, T.; Bridgeman, A.; Briechle, F. L.; Buchholz, P.; Bueno, A.; Buitink, S.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Candusso, M.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Chavez, A. G.; Chiavassa, A.; Chinellato, J. A.; Diaz, J. C. Chirinos; Chudoba, J.; Clay, R. W.; Colalillo, R.; Coleman, A.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cooper, M. J.; Cordier, A.; Coutu, S.; Covault, C. E.; Dallier, R.; D'Amico, S.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; Almeida, R. M. de; Jong, S. J. de; Mauro, G. De; Neto, J. R. T. de Mello; Mitri, I. De; Oliveira, J. de; Souza, V. de; Debatin, J.; Peral, L. del; Deligny, O.; Dhital, N.; Giulio, C. Di; Matteo, A. Di; Castro, M. L. Díaz; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dorofeev, A.; Anjos, R. C. dos; Dova, M. T.; Dundovic, A.; Ebr, J.; Engel, R.; Erdmann, M.; Erfani, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fratu, O.; Freire, M. M.; Fujii, T.; Fuster, A.; Gallo, F.; García, B.; Garcia-Gamez, D.; Garcia-Pinto, D.; Gate, F.; Gemmeke, H.; Gherghel-Lascu, A.; Ghia, P. L.; Giaccari, U.; Giammarchi, M.; Giller, M.; Głas, D.; Glaser, C.; Glass, H.; Golup, G.; Berisso, M. Gómez; Vitale, P. F. Gómez; González, N.; Gookin, B.; Gordon, J.; Gorgi, A.; Gorham, P.; Gouffon, P.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guarino, F.; Guedes, G. P.; Hampel, M. R.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Hasankiadeh, Q.; Haungs, A.; Hebbeker, T.; Heck, D.; Heimann, P.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holt, E.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huege, T.; Insolia, A.; Isar, P. G.; Jandt, I.; Jansen, S.; Jarne, C.; Johnsen, J. A.; Josebachuili, M.; Kääpä, A.; Kambeitz, O.; Kampert, K. H.; Kasper, P.; Katkov, I.; Keilhauer, B.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Krause, R.; Krohm, N.; Kuempel, D.; Mezek, G. Kukec; Kunka, N.; Awad, A. Kuotb; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Lebrun, D.; Lebrun, P.; Oliveira, M. A. Leigui de; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; Lopes, L.; López, R.; Casado, A. López; Lucero, A.; Malacari, M.; Mallamaci, M.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, V.; Mariş, I. C.; Marsella, G.; Martello, D.; Martinez, H.; Bravo, O. Martínez; Meza, J. J. Masías; Mathes, H. J.; Mathys, S.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina, C.; Medina-Tanco, G.; Mello, V. B. B.; Melo, D.; Menshikov, A.; Messina, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Montanet, F.; Morello, C.; Mostafá, M.; Moura, C. A.; Müller, G.; Muller, M. A.; Müller, S.; Naranjo, I.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nguyen, P. H.; Niculescu-Oglinzanu, M.; Niechciol, M.; Niemietz, L.; Niggemann, T.; Nitz, D.; Nosek, D.; Novotny, V.; Nožka, H.; Núñez, L. A.; Ochilo, L.; Oikonomou, F.; Olinto, A.; Pacheco, N.; Selmi-Dei, D. Pakk; Palatka, M.; Pallotta, J.; Papenbreer, P.; Parente, G.; Parra, A.; Paul, T.; Pech, M.; Pękala, J.; Pelayo, R.; Peña-Rodriguez, J.; Pepe, I. M.; Perrone, L.; Petermann, E.; Peters, C.; Petrera, S.; Phuntsok, J.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Porowski, C.; Prado, R. R.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Quinn, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Reinert, D.; Revenu, B.; Ridky, J.; Risse, M.; Ristori, P.; Rizi, V.; Carvalho, W. Rodrigues de; Rojo, J. Rodriguez; Rodríguez-Frías, M. D.; Rogozin, D.; Rosado, J.; Roth, M.; Roulet, E.; Rovero, A. C.; Saffi, S. J.; Saftoiu, A.; Salazar, H.; Saleh, A.; Greus, F. Salesa; Salina, G.; Gomez, J. D. Sanabria; Sánchez, F.; Sanchez-Lucas, P.; Santos, E. M.; Santos, E.; Sarazin, F.; Sarkar, B.; Sarmento, R.; Sarmiento-Cano, C.; Sato, R.; Scarso, C.; Schauer, M.; Scherini, V.; Schieler, H.; Schmidt, D.; Scholten, O.; Schoorlemmer, H.; Schovánek, P.; Schröder, F. G.; Schulz, A.; Schulz, J.; Schumacher, J.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sigl, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sonntag, S.; Sorokin, J.; Squartini, R.; Stanca, D.; Stanič, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Strafella, F.; Stutz, A.; Suarez, F.; Durán, M. Suarez; Suomijärvi, T.; Supanitsky, A. D.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Taborda, O. A.; Tapia, A.; Tepe, A.; Theodoro, V. M.; Timmermans, C.; Peixoto, C. J. Todero; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Elipe, G. Torralba; Machado, D. Torres; Travnicek, P.; Trini, M.; Ulrich, R.; Unger, M.; Urban, M.; Galicia, J. F. Valdés; Valiño, I.; Valore, L.; Aar, G. van; Bodegom, P. van; Berg, A. M. van den; Vliet, A. van; Varela, E.; Cárdenas, B. Vargas; Varner, G.; Vasquez, R.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Vorobiov, S.; Wahlberg, H.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Wiencke, L.; Wilczyński, H.; Winchen, T.; Wittkowski, D.; Wundheiler, B.; Wykes, S.; Yang, L.; Yapici, T.; Yushkov, A.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zepeda, A.; Zimmermann, B.; Ziolkowski, M.; Zong, Z.; Collaboration, F. Zuccarello The Telescope Array; Abbasi, R. U.; Abe, M.; Abu-Zayyad, T.; Allen, M.; Azuma, R.; Barcikowski, E.; Belz, J. W.; Bergman, D. R.; Blake, S. A.; Cady, R.; Chae, M. J.; Cheon, B. G.; Chiba, J.; Chikawa, M.; Cho, W. R.; Fujii, T.; Fukushima, M.; Goto, T.; Hanlon, W.; Hayashi, Y.; Hayashida, N.; Hibino, K.; Honda, K.; Ikeda, D.; Inoue, N.; Ishii, T.; Ishimori, R.; Ito, H.; Ivanov, D.; Jui, C. C. H.; Kadota, K.; Kakimoto, F.; Kalashev, O.; Kasahara, K.; Kawai, H.; Kawakami, S.; Kawana, S.; Kawata, K.; Kido, E.; Kim, H. B.; Kim, J. H.; Kim, J. H.; Kitamura, S.; Kitamura, Y.; Kuzmin, V.; Kwon, Y. J.; Lan, J.; Lim, S. I.; Lundquist, J. P.; Machida, K.; Martens, K.; Matsuda, T.; Matsuyama, T.; Matthews, J. N.; Minamino, M.; Mukai, Y.; Myers, I.; Nagasawa, K.; Nagataki, S.; Nakamura, T.; Nonaka, T.; Nozato, A.; Ogio, S.; Ogura, J.; Ohnishi, M.; Ohoka, H.; Oki, K.; Okuda, T.; Ono, M.; Oshima, A.; Ozawa, S.; Park, I. H.; Pshirkov, M. S.; Rodriguez, D. C.; Rubtsov, G.; Ryu, D.; Sagawa, H.; Sakurai, N.; Scott, L. M.; Shah, P. D.; Shibata, F.; Shibata, T.; Shimodaira, H.; Shin, B. K.; Shin, H. S.; Smith, J. D.; Sokolsky, P.; Springer, R. W.; Stokes, B. T.; Stratton, S. R.; Stroman, T. A.; Suzawa, T.; Takamura, M.; Takeda, M.; Takeishi, R.; Taketa, A.; Takita, M.; Tameda, Y.; Tanaka, H.; Tanaka, K.; Tanaka, M.; Thomas, S. B.; Thomson, G. B.; Tinyakov, P.; Tkachev, I.; Tokuno, H.; Tomida, T.; Troitsky, S.; Tsunesada, Y.; Tsutsumi, K.; Uchihori, Y.; Udo, S.; Urban, F.; Vasiloff, G.; Wong, T.; Yamane, R.; Yamaoka, H.; Yamazaki, K.; Yang, J.; Yashiro, K.; Yoneda, Y.; Yoshida, S.; Yoshii, H.; Zollinger, R.; Zundel, Z.

    2015-01-01

    This paper presents the results of different searches for correlations between very high-energy neutrino candidates detected by IceCube and the highest-energy cosmic rays measured by the Pierre Auger Observatory and the Telescope Array. We first consider samples of cascade neutrino events and of

  13. Event Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2001-01-01

    are dynamic and we present a modeling approach that can be used to model such dynamics. We characterize events as both information objects and change agents (Bækgaard 1997). When viewed as information objects events are phenomena that can be observed and described. For example, borrow events in a library can......The purpose of this chapter is to discuss conceptual event modeling within a context of information modeling. Traditionally, information modeling has been concerned with the modeling of a universe of discourse in terms of information structures. However, most interesting universes of discourse...... be characterized by their occurrence times and the participating books and borrowers. When we characterize events as information objects we focus on concepts like information structures. When viewed as change agents events are phenomena that trigger change. For example, when borrow event occurs books are moved...

  14. SENTINEL EVENTS

    Directory of Open Access Journals (Sweden)

    Andrej Robida

    2004-09-01

    Full Text Available Background. The Objective of the article is a two year statistics on sentinel events in hospitals. Results of a survey on sentinel events and the attitude of hospital leaders and staff are also included. Some recommendations regarding patient safety and the handling of sentinel events are given.Methods. In March 2002 the Ministry of Health introduce a voluntary reporting system on sentinel events in Slovenian hospitals. Sentinel events were analyzed according to the place the event, its content, and root causes. To show results of the first year, a conference for hospital directors and medical directors was organized. A survey was conducted among the participants with the purpose of gathering information about their view on sentinel events. One hundred questionnaires were distributed.Results. Sentinel events. There were 14 reports of sentinel events in the first year and 7 in the second. In 4 cases reports were received only after written reminders were sent to the responsible persons, in one case no reports were obtained. There were 14 deaths, 5 of these were in-hospital suicides, 6 were due to an adverse event, 3 were unexplained. Events not leading to death were a suicide attempt, a wrong side surgery, a paraplegia after spinal anaesthesia, a fall with a femoral neck fracture, a damage of the spleen in the event of pleural space drainage, inadvertent embolization with absolute alcohol into a femoral artery and a physical attack on a physician by a patient. Analysis of root causes of sentinel events showed that in most cases processes were inadequate.Survey. One quarter of those surveyed did not know about the sentinel events reporting system. 16% were having actual problems when reporting events and 47% beleived that there was an attempt to blame individuals. Obstacles in reporting events openly were fear of consequences, moral shame, fear of public disclosure of names of participants in the event and exposure in mass media. The majority of

  15. Event by event method for quantum interference simulation

    NARCIS (Netherlands)

    Mutia Delina, M

    2014-01-01

    Event by event method is a simulation approach which is not based on the knowledge of the Schrödinger equation. This approach uses the classical wave theory and particle concept: we use particles, not waves. The data is obtained by counting the events that were detected by the detector, just as in

  16. Event Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2001-01-01

    The purpose of this chapter is to discuss conceptual event modeling within a context of information modeling. Traditionally, information modeling has been concerned with the modeling of a universe of discourse in terms of information structures. However, most interesting universes of discourse...... are dynamic and we present a modeling approach that can be used to model such dynamics.We characterize events as both information objects and change agents (Bækgaard 1997). When viewed as information objects events are phenomena that can be observed and described. For example, borrow events in a library can...

  17. A Quantitative PCR-Electrochemical Genosensor Test for the Screening of Biotech Crops

    Directory of Open Access Journals (Sweden)

    Suely Moura-Melo

    2017-04-01

    Full Text Available The design of screening methods for the detection of genetically modified organisms (GMOs in food would improve the efficiency in their control. We report here a PCR amplification method combined with a sequence-specific electrochemical genosensor for the quantification of a DNA sequence characteristic of the 35S promoter derived from the cauliflower mosaic virus (CaMV. Specifically, we employ a genosensor constructed by chemisorption of a thiolated capture probe and p-aminothiophenol gold surfaces to entrap on the sensing layer the unpurified PCR amplicons, together with a signaling probe labeled with fluorescein. The proposed test allows for the determination of a transgene copy number in both hemizygous (maize MON810 trait and homozygous (soybean GTS40-3-2 transformed plants, and exhibits a limit of quantification of at least 0.25% for both kinds of GMO lines.

  18. A Quantitative PCR-Electrochemical Genosensor Test for the Screening of Biotech Crops

    Science.gov (United States)

    Moura-Melo, Suely; Miranda-Castro, Rebeca; de-los-Santos-Álvarez, Noemí; Miranda-Ordieres, Arturo J.; dos Santos Junior, José Ribeiro; da Silva Fonseca, Rosana A.; Lobo-Castañón, María Jesús

    2017-01-01

    The design of screening methods for the detection of genetically modified organisms (GMOs) in food would improve the efficiency in their control. We report here a PCR amplification method combined with a sequence-specific electrochemical genosensor for the quantification of a DNA sequence characteristic of the 35S promoter derived from the cauliflower mosaic virus (CaMV). Specifically, we employ a genosensor constructed by chemisorption of a thiolated capture probe and p-aminothiophenol gold surfaces to entrap on the sensing layer the unpurified PCR amplicons, together with a signaling probe labeled with fluorescein. The proposed test allows for the determination of a transgene copy number in both hemizygous (maize MON810 trait) and homozygous (soybean GTS40-3-2) transformed plants, and exhibits a limit of quantification of at least 0.25% for both kinds of GMO lines. PMID:28420193

  19. Development, optimization, and single laboratory validation of an event-specific real-time PCR method for the detection and quantification of Golden Rice 2 using a novel taxon-specific assay.

    Science.gov (United States)

    Jacchia, Sara; Nardini, Elena; Savini, Christian; Petrillo, Mauro; Angers-Loustau, Alexandre; Shim, Jung-Hyun; Trijatmiko, Kurniawan; Kreysa, Joachim; Mazzara, Marco

    2015-02-18

    In this study, we developed, optimized, and in-house validated a real-time PCR method for the event-specific detection and quantification of Golden Rice 2, a genetically modified rice with provitamin A in the grain. We optimized and evaluated the performance of the taxon (targeting rice Phospholipase D α2 gene)- and event (targeting the 3' insert-to-plant DNA junction)-specific assays that compose the method as independent modules, using haploid genome equivalents as unit of measurement. We verified the specificity of the two real-time PCR assays and determined their dynamic range, limit of quantification, limit of detection, and robustness. We also confirmed that the taxon-specific DNA sequence is present in single copy in the rice genome and verified its stability of amplification across 132 rice varieties. A relative quantification experiment evidenced the correct performance of the two assays when used in combination.

  20. Monitoring of all-cause mortality in Belgium (Be-MOMO): a new and automated system for the early detection and quantification of the mortality impact of public health events.

    Science.gov (United States)

    Cox, Bianca; Wuillaume, Françoise; Van Oyen, Herman; Maes, Sophie

    2010-08-01

    Be-MOMO is the monitoring of all-cause death registry data in Belgium. The new methods are described and the detection and quantification of outbreaks is presented for the period April 2006-March 2007. Sensitivity, specificity and timeliness are illustrated by means of a temporal comparison with known health events. Relevant events are identified from important mortality risks: climate, air pollution and influenza. Baselines and thresholds for deaths by gender, age group, day and week are estimated by the method of Farrington et al. (J R Stat Soc Ser A, 159:547-563, 1996). By adding seasonal terms to the basic model, a complete 5-year reference period can be used, while a reduction of noise allows the application to daily counts. Ignoring two false positives, all flags could be classified into five distinct outbreaks, coinciding with four heat periods and an influenza epidemic. Negative deviations from expected mortality in autumn and winter might reflect a displacement of mortality by the heat waves. Still, significant positive excess was found during five influenza weeks. Correcting for the delay in registration of deaths, outbreaks could be detected as soon as 1-2 weeks after the event. The sensitivity of Be-MOMO to different health threats suggests its potential usefulness in early warning: mortality thresholds and baselines might serve as rapid tools for detecting and quantifying outbreaks, crucial for public health decision-making and evaluation of measures.

  1. Automatic, ECG-based detection of autonomic arousals and their association with cortical arousals, leg movements, and respiratory events in sleep

    DEFF Research Database (Denmark)

    Olsen, Mads; Schneider, Logan Douglas; Cheung, Joseph

    2018-01-01

    The current definition of sleep arousals neglects to address the diversity of arousals and their systemic cohesion. Autonomic arousals (AA) are autonomic activations often associated with cortical arousals (CA), but they may also occur in isolation in relation to a respiratory event, a leg moveme...

  2. Climate instability and tipping points in the Late Devonian: Detection of the Hangenberg Event in an open oceanic island arc in the Central Asian Orogenic Belt

    Czech Academy of Sciences Publication Activity Database

    Carmichael, A.; Waters, J. A.; Batchelor, C. J.; Coleman, D. M.; Suttner, T. J.; Kido, E.; Moore, L. M.; Chadimová, Leona

    2016-01-01

    Roč. 32, 1 April (2016), s. 213-231 ISSN 1342-937X Institutional support: RVO:67985831 Keywords : Central Asian Orogenic Belt * chemostratigraphy * Devonian-Carboniferous * Hangenberg Event * West Junggar Subject RIV: DB - Geology ; Mineralogy Impact factor: 6.959, year: 2016

  3. Atypical antipsychotic drugs and diabetes mellitus in the US Food and Drug Administration Adverse Event database: a systematic Bayesian signal detection analysis.

    Science.gov (United States)

    Baker, Ross A; Pikalov, Andrei; Tran, Quynh-Van; Kremenets, Tatyana; Arani, Ramin B; Doraiswamy, P Murali

    2009-01-01

    Prior literature suggests that the risk of diabetes-related adverse events (DRAEs) differs between atypical antipsychotics. The present study evaluated the potential association between atypical antipsychotics or haloperidol and diabetes using data from the FDA AERS database. Analysis of AERS data was conducted for clozapine, risperidone, olanzapine, quetiapine, ziprasidone, aripiprazole or haloperidol with 24 DRAEs from the Medical Dictionary for Regulatory Activities using a Multi-item Gamma Poisson Shrinker (MGPS) data-mining algorithm. Using MGPS, adjusted reporting ratios (Empiric Bayes Geometric Mean or EBGM) and 90% confidence intervals (CIs; EB05-EB95) were calculated to estimate the degree of drug-event association relative to all drugs and events. Logistic regression odds ratios and 90% CIs (LR05-LR95) were calculated for diabetes mellitus events. All six atypicals had an EB05 >/= 2 for at least one DRAE. The most common event was diabetes mellitus (2,784 cases). Adjusted reporting ratios (CIs) for diabetes mellitus were: olanzapine 9.6 (9.2-10.0; 1306 cases); risperidone 3.8 (3.5-4.1; 447 cases); quetiapine 3.5 (3.2-3.9; 283 cases); clozapine 3.1 (2.9-3.3; 464 cases); ziprasidone 2.4 (2.0-2.9; 74 cases); aripiprazole 2.4 (1.9-2.9; 71 cases); haloperidol 2.0 (1.7-2.3; 139 cases). Logistic regression odds ratios agreed with adjusted reporting ratios. In the AERS database, lower associations with DRAEs were seen for haloperidol, aripiprazole and ziprasidone, and higher associations were seen for olanzapine, risperidone, clozapine and quetiapine. Our findings support differential risk of diabetes across atypical antipsychotics, reinforcing the need for metabolic monitoring of patients taking antipsychotics.

  4. Surface Management System Departure Event Data Analysis

    Science.gov (United States)

    Monroe, Gilena A.

    2010-01-01

    This paper presents a data analysis of the Surface Management System (SMS) performance of departure events, including push-back and runway departure events.The paper focuses on the detection performance, or the ability to detect departure events, as well as the prediction performance of SMS. The results detail a modest overall detection performance of push-back events and a significantly high overall detection performance of runway departure events. The overall detection performance of SMS for push-back events is approximately 55%.The overall detection performance of SMS for runway departure events nears 100%. This paper also presents the overall SMS prediction performance for runway departure events as well as the timeliness of the Aircraft Situation Display for Industry data source for SMS predictions.

  5. Plasma-enabled graded nanotube biosensing arrays on a Si nanodevice platform: catalyst-free integration and in situ detection of nucleation events.

    Science.gov (United States)

    Kumar, Shailesh; Mehdipour, Hamid; Ostrikov, Kostya Ken

    2013-01-04

    Low-temperature plasmas in direct contact with arbitrary, written linear features on a Si wafer enable catalyst-free integration of carbon nanotubes into a Si-based nanodevice platform and in situ resolution of individual nucleation events. The graded nanotube arrays show reliable, reproducible, and competitive performance in electron field emission and biosensing nanodevices. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Topography's event

    DEFF Research Database (Denmark)

    Munck Petersen, Rikke

    measure is not there alone since you measure it in something both visual, physical and shaped by views and ideas of society; something thought and abstract. Such knowledge point out the need for being able to measure other factors that visual and physical. Metrical and proportional view of the world seems...... - to stimulate and elaborate the event of conception and topological thinking....

  7. Topography's event

    DEFF Research Database (Denmark)

    Munck Petersen, Rikke

    The aim of the paper is first to discuss how horizon and scale can be understood, secondly how they differ and what they might have in common? If topography can be seen as a way of working with these relations experiences, creations and latencies? Thirdly if diagrams and diagrammatology can bring...... - to stimulate and elaborate the event of conception and topological thinking....

  8. The vaccine data link in Nha Trang, Vietnam: a progress report on the implementation of a database to detect adverse events related to vaccinations.

    Science.gov (United States)

    Ali, Mohammad; Canh, Do Gia; Clemens, John D; Park, Jin-Kyung; von Seidlein, Lorenz; Thiem, Vu Dinh; Tho, Le Huu; Trach, Dang Duc

    2003-04-02

    Real, perceived and unknown adverse events secondary to vaccinations are a source of concern for care providers of children. In the USA large linked databases have provided helpful information regarding the safety of vaccines. Very little prospectively collected data on vaccine safety is available from resource poor countries, but safety concerns may be even more relevant in such settings. Vaccine manufacturers do not have to pass the same rigorous safety standards as vaccine manufacturers in rich countries. Vaccines, which protect against cholera, Japanese encephalitis, rabies or typhoid fever are predominantly used in resource poor, tropical countries and frequently do not undergo vigorous post marketing surveillance. New vaccines specifically suited for resource poor countries are sometimes marketed without the scrutiny of vigilant, independent regulatory authorities. We describe here the design and implementation of a large linked database for a semi-rural province in central Vietnam. The design overcomes several problems inherent in data bases of medical events and vaccinations in developing countries. Assigning a permanent identification (ID) number to each resident avoids the ambiguities of ID numbers based on the address. The distribution and use of medical identification cards with a permanent ID number assists in the unambiguous identification of vaccinees and patients. Medical records of all admissions are coded according to International Classification of Diseases (ICD-10) and transcribed into a computer system. Because these processes are novel the data collected by the study will be validated. Project staff will check records on vaccinations and hospital admissions through household visits at regular intervals. Data describing vaccinations and medical events are linked to the data collected by the project staff in a computer system. Based on the validation of the data we hope to optimize this model. Once we find the model working it is planned export

  9. Measurement of the cosmic ray spectrum above 4 x 10(18) eV using inclined events detected with the Pierre Auger Observatory

    NARCIS (Netherlands)

    Aab, A.; Abreu, P.; Aglietta, M.; Ahn, E. J.; Al Samarai, I.; Albuquerque, I. F. M.; Allekotte, I.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muniz, J.; Batista, R. Alves; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Aramo, C.; Aranda, V. M.; Arqueros, F.; Arsene, N.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Awal, N.; Badescu, A. M.; Barber, K. B.; Baeuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellido, J. A.; Berat, C.; Bertaina, M. E.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blaess, S. G.; Blanco, A.; Blanco, M.; Bleve, C.; Bluemer, H.; Bohacova, M.; Boncioli, D.; Bonifazi, C.; Borodai, N.; Brack, J.; Brancus, I.; Bridgeman, A.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buitink, S.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Candusso, M.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Chavez, A. G.; Chiavassa, A.; Chinellato, J. A.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Coleman, A.; Collica, L.; Coluccia, M. R.; Conceicao, R.; Contreras, F.; Cooper, M. J.; Cordier, A.; Coutu, S.; Covault, C. E.; Cronin, J.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Jong, S. J.; De Mauro, G.; de Mello Neto, J. R. T.; De Mitri, I.; de Oliveira, J.; de Souza, V.; del Pera, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Di Matteo, A.; Diaz, J. C.; Diaz Castro, M. L.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dorofeev, A.; Dorosti Hasankiadeh, Q.; Dova, M. T.; Ebr, J.; Engel, R.; Erdmann, M.; Erfani, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fernandes, M.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipcic, A.; Fox, B. D.; Fratu, O.; Freire, M. M.; Fuchs, B.; Fujii, T.; Garcia, B.; Garcia-Pinto, D.; Gate, F.; Gemmeke, H.; Gherghel-Lascu, A.; Ghia, P. L.; Giaccari, U.; Giammarchi, M.; Giller, M.; Glas, D.; Glaser, C.; Glass, H.; Golup, G.; Gomez Berisso, M.; Gomez Vitale, P. F.; Gonzalez, N.; Gookin, B.; Gordon, J.; Gorgi, A.; Gorham, P.; Gouffon, P.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guarino, F.; Guedes, G. P.; Hampel, M. R.; Hansen, P.; Harari, D.; Harrison, T. A.; Hartmann, S.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Heimann, P.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holt, E.; Homola, P.; Hoerandel, J. R.; Horvath, P.; Hrabovsky, M.; Huber, D.; Huege, T.; Insolia, A.; Isar, P. G.; Jandt, I.; Jansen, S.; Jarne, C.; Johnsen, J. A.; Josebachuili, M.; Kaapa, A.; Kambeitz, O.; Kampert, K. H.; Kasper, P.; Katkov, I.; Kegl, B.; Keilhauer, B.; Keivani, A.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Krause, R.; Krohm, N.; Kroemer, O.; Kuempe, D.; Kunka, N.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; Lopes, L.; Lopez, R.; Lopez Casado, A.; Louedec, K.; Lu, L.; Lucero, A.; Malacari, M.; Maldera, S.; Mallamaci, M.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, V.; Maris, I. C.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martinez Bravo, O.; Martraire, D.; Masias Meza, J. J.; Mathes, H. J.; Mathys, S.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maure, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina, C.; Medina-Tanco, G.; Meissner, R.; Mello, V. B. B.; Melo, D.; Menshikov, A.; Messina, S.; Meyhandan, R.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Montanet, F.; Morello, C.; Mostafa, M.; Moura, C. A.; Muller, M. A.; Mueller, G.; Mueller, S.; Mussa, R.; Navarra, G.; Navas, S.; Necesa, P.; Nellen, L.; Nelles, A.; Neuser, J.; Newton, D.; Nguyen, P. H.; Niculescu-Oglinzanu, M.; Niechcio, M.; Niemietz, L.; Niggemann, T.; Nitz, D.; Nosek, D.; Novotny, V.; Nozka, L.; Ochilo, L.; Oikonomou, F.; Olinto, A.; Olmos-Gilbaja, V. M.; Pacheco, N.; Selmi-Dei, D. Pakk; Palatka, M.; Pallotta, J.; Papenbreer, P.; Parente, G.; Parra, A.; Paul, T.; Pech, M.; Pekala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Petermann, E.; Peters, C.; Petrera, S.; Petrov, Y.; Phuntsok, J.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Porcelli, A.; Porowski, C.; Prado, R. R.; Privitera, P.; Prouza, M.; Purrello, V.; Quel, E. J.; Querchfeld, S.; Quinn, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rizi, V.; Rodrigues de Carvalho, W.; Fernandez, G. Rodriguez; Rodriguez Rojo, J.; Rodriguez-Frias, M. D.; Rogozin, D.; Rosado, J.; Roth, M.; Rouletl, E.; Rovero, A. C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Saleh, A.; Salesa Greus, F.; Salina, G.; Sanchez, F.; Sanchez-Lucas, P.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sarmento, R.; Sato, R.; Scarso, C.; Schauer, M.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, D.; Scholten, O.; Schoorlemmer, H.; Schovanek, P.; Schroeder, F. G.; Schulz, A.; Schulz, J.; Schumacher, J.; Sciutto, S. J.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Smialkowski, A.; Smida, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Squartini, R.; Srivastava, Y. N.; Stanca, D.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Stutz, A.; Suarez, F.; Suomijarvi, T.; Supanitsky, A. D.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Taborda, O. A.; Tapia, A.; Tepe, A.; Theodoro, V. M.; Timmermans, C.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tome, B.; Tonachini, A.; Elipe, G. Torralba; Torres Machado, D.; Travnicek, P.; Ulrich, R.; Unger, M.; Urban, M.; Valdes Galicia, J. F.; Valino, I.; Valore, L.; van Aar, G.; van Bodegom, P.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cardenas, B.; Varner, G.; Vasquez, R.; Vazquez, J. R.; Vazquez, R. A.; Veberic, D.; Verzi, V.; Vicha, J.; Videla, M.; Villasenor, L.; Vlcek, B.; Vorobiov, S.; Wahlberg, H.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Widom, A.; Wiencke, L.; Wilczynski, H.; Winchen, T.; Wittkowski, D.; Wundheiler, B.; Wykes, S.; Yang, L.; Yapici, T.; Yushkov, A.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zepeda, A.; Zhu, Y.; Zimmermann, B.; Ziolkowski, M.; Zuccarello, F.

    A measurement of the cosmic-ray spectrum for energies exceeding 4x10(18) eV is presented, which is based on the analysis of showers with zenith angles greater than 60 degrees detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux

  10. A comparison of accuracy and precision of 5 gait-event detection algorithms from motion capture in horses during over ground walk

    DEFF Research Database (Denmark)

    Olsen, Emil; Boye, Jenny Katrine; Pfau, Thilo

    2012-01-01

    Motion capture is frequently used over ground in equine locomotion science to study kinematics. Determination of gait events (hoof-on/off and stance) without force plates is essential to cut the data into strides. The lack of comparative evidence emphasise the need to compare existing algorithms...... surrounded by a 12-camera infrared motion capture system. The algorithms were based on horizontal or vertical velocity displacement and velocity of the hoof relative to the centre of mass movement or fetlock angle and velocity or displacement of the hoof. Horizontal hoof velocity relative to the centre...

  11. Probabilistic historical biogeography: new models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing

    Directory of Open Access Journals (Sweden)

    Nicholas Joseph Matzke

    2013-12-01

    Full Text Available Historical biogeography has been characterized by a large diversity of methods and unresolved debates about which processes, such as dispersal or vicariance, are most important for explaining distributions. A new R package, BioGeoBEARS, implements many models in a common likelihood framework, so that standard statistical model selection procedures can be applied to let the data choose the best model. Available models include a likelihood version of DIVA (“DIVALIKE”, LAGRANGE’s DEC model, and BAYAREA, as well as “+J” versions of these models which include founder-event speciation, an important process left out of most inference methods. I use BioGeoBEARS on a large sample of island and non-island clades (including two fossil clades to show that founder-event speciation is a crucial process in almost every clade, and that most published datasets reject the non-J models currently in widespread use. BioGeoBEARS is open-source and freely available for installation at the Comprehensive R Archive Network at http://CRAN.R-project.org/package=BioGeoBEARS. A step-by-step tutorial is available at http://phylo.wikidot.com/biogeobears.

  12. Event-by-event simulation of quantum phenomena

    NARCIS (Netherlands)

    De Raedt, Hans; Michielsen, Kristel

    A discrete-event simulation approach is reviewed that does not require the knowledge of the solution of the wave equation of the whole system, yet reproduces the statistical distributions of wave theory by generating detection events one-by-one. The simulation approach is illustrated by applications

  13. Single-Step qPCR and dPCR Detection of Diverse CRISPR-Cas9 Gene Editing Events In Vivo

    Directory of Open Access Journals (Sweden)

    Micol Falabella

    2017-10-01

    Full Text Available Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR-CRISPR-associated protein 9 (Cas9-based technology is currently the most flexible means to create targeted mutations by recombination or indel mutations by nonhomologous end joining. During mouse transgenesis, recombinant and indel alleles are often pursued simultaneously. Multiple alleles can be formed in each animal to create significant genetic complexity that complicates the CRISPR-Cas9 approach and analysis. Currently, there are no rapid methods to measure the extent of on-site editing with broad mutation sensitivity. In this study, we demonstrate the allelic diversity arising from targeted CRISPR editing in founder mice. Using this DNA sample collection, we validated specific quantitative and digital PCR methods (qPCR and dPCR, respectively for measuring the frequency of on-target editing in founder mice. We found that locked nucleic acid (LNA probes combined with an internal reference probe (Drop-Off Assay provide accurate measurements of editing rates. The Drop-Off LNA Assay also detected on-target CRISPR-Cas9 gene editing in blastocysts with a sensitivity comparable to PCR-clone sequencing. Lastly, we demonstrate that the allele-specific LNA probes used in qPCR competitor assays can accurately detect recombinant mutations in founder mice. In summary, we show that LNA-based qPCR and dPCR assays provide a rapid method for quantifying the extent of on-target genome editing in vivo, testing RNA guides, and detecting recombinant mutations.

  14. Single-Step qPCR and dPCR Detection of Diverse CRISPR-Cas9 Gene Editing Events in Vivo

    Science.gov (United States)

    Falabella, Micol; Sun, Linqing; Barr, Justin; Pena, Andressa Z.; Kershaw, Erin E.; Gingras, Sebastien; Goncharova, Elena A.; Kaufman, Brett A.

    2017-01-01

    Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-based technology is currently the most flexible means to create targeted mutations by recombination or indel mutations by nonhomologous end joining. During mouse transgenesis, recombinant and indel alleles are often pursued simultaneously. Multiple alleles can be formed in each animal to create significant genetic complexity that complicates the CRISPR-Cas9 approach and analysis. Currently, there are no rapid methods to measure the extent of on-site editing with broad mutation sensitivity. In this study, we demonstrate the allelic diversity arising from targeted CRISPR editing in founder mice. Using this DNA sample collection, we validated specific quantitative and digital PCR methods (qPCR and dPCR, respectively) for measuring the frequency of on-target editing in founder mice. We found that locked nucleic acid (LNA) probes combined with an internal reference probe (Drop-Off Assay) provide accurate measurements of editing rates. The Drop-Off LNA Assay also detected on-target CRISPR-Cas9 gene editing in blastocysts with a sensitivity comparable to PCR-clone sequencing. Lastly, we demonstrate that the allele-specific LNA probes used in qPCR competitor assays can accurately detect recombinant mutations in founder mice. In summary, we show that LNA-based qPCR and dPCR assays provide a rapid method for quantifying the extent of on-target genome editing in vivo, testing RNA guides, and detecting recombinant mutations. PMID:28860183

  15. Musical Stairs: A motivational therapy tool for children with disabilities featuring automated detection of stair-climbing gait events via inertial sensors.

    Science.gov (United States)

    Khan, Ajmal; Biddiss, Elaine

    2017-02-01

    Stair-climbing is a key component of rehabilitation therapies for children with physical disabilities. This paper reports on the design of a system, Musical Stairs, to provide auditory feedback during stair-climbing therapies. Musical Stairs is composed of two foot-mounted inertial sensors, a step detection algorithm, and an auditory feedback response. In Phase 1, we establish its clinical feasibility via a Wizard-of-Oz AB/BA cross-over design with 17 children, aged 4-6 years, having diverse diagnoses and gait abilities. Self-, therapist- and blinded-observer reports indicated increased motivation with auditory feedback. Phase 2 describes the construction of a database comprised of synchronized video and inertial data associated with 1568 steps up and down stairs completed by 26 children aged 4-6 years with diverse diagnoses and gait. Lastly, in Phase 3, data from 18 children in the database were used to train a rule-based step detection algorithm based on local minima in the acceleration profile and the foot's swing angle. A step detection rate of 96% [SD=3%] and false positive rate of 6% [SD=5%] were achieved with an independent test set (n=8). Recommendations for future development and evaluation are discussed. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

  16. Degradation and detection of transgenic Bacillus thuringiensis DNA and proteins in flour of three genetically modified rice events submitted to a set of thermal processes.

    Science.gov (United States)

    Wang, Xiaofu; Chen, Xiaoyun; Xu, Junfeng; Dai, Chen; Shen, Wenbiao

    2015-10-01

    This study aimed to investigate the degradation of three transgenic Bacillus thuringiensis (Bt) genes (Cry1Ab, Cry1Ac, and Cry1Ab/Ac) and the corresponding encoded Bt proteins in KMD1, KF6, and TT51-1 rice powder, respectively, following autoclaving, cooking, baking, or microwaving. Exogenous Bt genes were more stable than the endogenous sucrose phosphate synthase (SPS) gene, and short DNA fragments were detected more frequently than long DNA fragments in both the Bt and SPS genes. Autoclaving, cooking (boiling in water, 30 min), and baking (200 °C, 30 min) induced the most severe Bt protein degradation effects, and Cry1Ab protein was more stable than Cry1Ac and Cry1Ab/Ac protein, which was further confirmed by baking samples at 180 °C for different periods of time. Microwaving induced mild degradation of the Bt and SPS genes, and Bt proteins, whereas baking (180 °C, 15 min), cooking and autoclaving led to further degradation, and baking (200 °C, 30 min) induced the most severe degradation. The findings of the study indicated that degradation of the Bt genes and proteins somewhat correlated with the treatment intensity. Polymerase chain reaction, enzyme-linked immunosorbent assay, and lateral flow tests were used to detect the corresponding transgenic components. Strategies for detecting transgenic ingredients in highly processed foods are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Seismic event classification system

    Science.gov (United States)

    Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

    1994-01-01

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

  18. Measurement of the cosmic ray spectrum above $4{\\times}10^{18}$ eV using inclined events detected with the Pierre Auger Observatory

    OpenAIRE

    The Pierre Auger Collaboration; Aab, Alexander; Abreu, Pedro; Aglietta, Marco; Ahn, Eun-Joo; Samarai, Imen Al; Albuquerque, Ivone; Allekotte, Ingomar; Allison, Patrick; Almela, Alejandro; Castillo, Jesus Alvarez; Alvarez-Muñiz, Jaime; Batista, Rafael Alves; Ambrosio, Michelangelo; Aminaei, Amin

    2015-01-01

    A measurement of the cosmic-ray spectrum for energies exceeding $4{\\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\\gamma}$ with index $\\gamma=2.70 \\pm 0.02 \\,\\text{(stat)}...

  19. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  20. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  1. Semantic Event Correlation Using Ontologies

    Science.gov (United States)

    Moser, Thomas; Roth, Heinz; Rozsnyai, Szabolcs; Mordinyi, Richard; Biffl, Stefan

    Complex event processing (CEP) is a software architecture paradigm that aims at low latency, high throughput, and quick adaptability of applications for supporting and improving event-driven business processes. Events sensed in real time are the basic information units on which CEP applications operate and react in self-contained decision cycles based on defined processing logic and rules. Event correlation is necessary to relate events gathered from various sources for detecting patterns and situations of interest in the business context. Unfortunately, event correlation has been limited to syntactically identical attribute values instead of addressing semantically equivalent attribute meanings. Semantic equivalence is particularly relevant if events come from organizations that use different terminologies for common concepts.

  2. Detection of cases of progressive multifocal leukoencephalopathy associated with new biologicals and targeted cancer therapies from the FDA's adverse event reporting system.

    Science.gov (United States)

    Raisch, Dennis W; Rafi, John A; Chen, Cheng; Bennett, Charles L

    2016-08-01

    To identify and summarize FDA's Adverse Event Reporting System (FAERS) cases of progressive multifocal leukoencephalopathy (PML) associated with biological and targeted cancer therapies (BTCT) that were approved between 2009 and 2015. FAERS was searched using each BTCT name as primary or secondary suspect drug and the adverse reaction of PML. Among BTCTs with >2 case reports of PML, proportional reporting ratios (PRR) and 95% confidence intervals (CI) were calculated. Among 49 new BTCTs, 82 cases of PML were found for 16 drugs. Significant PRR signals were found among 7 (14.6%) BTCTs including: brentuximab (24.5, CI:14.8-40.6), ofatumumab (16.3, CI:9.6-27.4), alemtuzumab (9.9, CI:6.0-16.4), obinutuzumab (7.4, CI:2.4-22.8), ibrutinib (5.6 CI:3.0-10.5), belimumab (4.5 CI:2.3-9.0), and idelalisib (4.1, CI:1.3-12.6). Among the 82 cases with significant signals, confirmation of the diagnosis of PML using objective criteria was found in 56% of the cases. A limitation of FAERS data is that missing data are common. When using BTCTs, clinicians and patients consider the risk of PML versus the therapeutic benefit, particularly when used in combination with other drugs which may cause PML, such as rituximab. It is important to recognize that PML may occur in some conditions, such as chronic lymphocytic leukemia, regardless of drug therapy.

  3. Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery

    Directory of Open Access Journals (Sweden)

    Lixia Gong

    2016-10-01

    Full Text Available Compared with optical sensors, Synthetic Aperture Radar (SAR can provide important damage information due to its ability to map areas affected by earthquakes independently from weather conditions and solar illumination. In 2013, a new TerraSAR-X mode named staring spotlight (ST, whose azimuth resolution was improved to 0.24 m, was introduced for various applications. This data source made it possible to extract detailed information from individual buildings. In this paper, we present a new concept for individual building damage assessment using a post-event sub-meter very high resolution (VHR SAR image and a building footprint map. With the building footprint map, the original footprints of buildings can be located in the SAR image. Based on the building imaging analysis of a building in the SAR image, the features in the building footprint can be extracted to identify standing and collapsed buildings. Three machine learning classifiers, including random forest (RF, support vector machine (SVM and K-nearest neighbor (K-NN, are used in the experiments. The results show that the proposed method can obtain good overall accuracy, which is above 80% with the three classifiers. The efficiency of the proposed method is demonstrated based on samples of buildings using descending and ascending sub-meter VHR ST images, which were all acquired from the same area in old Beichuan County, China.

  4. Intercorporate Security Event Correlation

    Directory of Open Access Journals (Sweden)

    D. O. Kovalev

    2010-03-01

    Full Text Available Security controls are prone to false positives and false negatives which can lead to unwanted reputation losses for the bank. The reputational database within the security operations center (SOC and intercorporate correlation of security events are offered as a solution to increase attack detection fidelity. The theses introduce the definition and structure of the reputation, architectures of reputational exchange and the place of intercorporate correlation in overall SOC correlation analysis.

  5. Event Index - a LHCb Event Search System

    CERN Document Server

    INSPIRE-00392208; Kazeev, Nikita; Redkin, Artem

    2015-12-23

    LHC experiments generate up to $10^{12}$ events per year. This paper describes Event Index - an event search system. Event Index's primary function is quickly selecting subsets of events from a combination of conditions, such as the estimated decay channel or stripping lines output. Event Index is essentially Apache Lucene optimized for read-only indexes distributed over independent shards on independent nodes.

  6. A Combined Atmospheric Rivers and Geopotential Height Analysis for the Detection of High Streamflow Event Probability Occurrence in UK and Germany

    Science.gov (United States)

    Rosario Conticello, Federico; Cioffi, Francesco; Lall, Upmanu; Merz, Bruno

    2017-04-01

    The role of atmospheric rivers (ARs) in inducing High Streamflow Events (HSEs) in Europe has been confirmed by numerous studies. Here, we assume as HSEs the streamflows exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. Among the indicators of ARs are: the Integrated Water Vapor (IWV) and Integrated Water Vapor Transport (IVT). For both indicators the literature suggests thresholds in order to identify ARs. Furthermore, local thresholds of such indices are used to assess the occurrence of HSEs in a given region. Recent research on ARs still leaves room for open issues: 1) The literature is not unanimous in defining which of the two indicators is better. 2) The selection of the thresholds is based on subjective assessments. 3) The predictability of HSEs at the local scale associated with these indices seems to be weak and to exist only in the winter months. In order to address these issues, we propose an original methodology: (i) to choose between the two indicators which one is the most suitable for HSEs predictions; (ii) to select IWT and/or IVT (IVT/IWV) local thresholds in a more objective way; (iii) to implement an algorithm able to determine whether a IVT/IWV configuration is inducing HSEs, regardless of the season. In pursuing this goal, besides IWV and IVT fields, we introduce as further predictor the geopotential height at 850 hPa (GPH850) field, that implicitly contains information about the pattern of temperature, direction and intensity of the winds. In fact, the introduction of the GPH850 would help to improve the assessment of the occurrence of HSEs throughout the year. It is also plausible to hypothesize, that IVT/IWV local thresholds could vary in dependence of the GPH850 configuration. In this study, we propose a model to statistically relate these predictors, IVT/IWV and GPH850, to the simultaneous occurrence of HSEs in one or more streamflow gauges in UK and Germany. Historical data from 57 streamflow gauges

  7. Detection of canonical A-to-G editing events at 3' UTRs and microRNA target sites in human lungs using next-generation sequencing.

    Science.gov (United States)

    Soundararajan, Ramani; Stearns, Timothy M; Griswold, Anthony L; Mehta, Arpit; Czachor, Alexander; Fukumoto, Jutaro; Lockey, Richard F; King, Benjamin L; Kolliputi, Narasaiah

    2015-11-03

    RNA editing is a post-transcriptional modification of RNA. The majority of these changes result from adenosine deaminase acting on RNA (ADARs) catalyzing the conversion of adenosine residues to inosine in double-stranded RNAs (dsRNAs). Massively parallel sequencing has enabled the identification of RNA editing sites in human transcriptomes. In this study, we sequenced DNA and RNA from human lungs and identified RNA editing sites with high confidence via a computational pipeline utilizing stringent analysis thresholds. We identified a total of 3,447 editing sites that overlapped in three human lung samples, and with 50% of these sites having canonical A-to-G base changes. Approximately 27% of the edited sites overlapped with Alu repeats, and showed A-to-G clustering (>3 clusters in 100 bp). The majority of edited sites mapped to either 3' untranslated regions (UTRs) or introns close to splice sites; whereas, only few sites were in exons resulting in non-synonymous amino acid changes. Interestingly, we identified 652 A-to-G editing events in the 3' UTR of 205 target genes that mapped to 932 potential miRNA target binding sites. Several of these miRNA edited sites were validated in silico. Additionally, we validated several A-to-G edited sites by Sanger sequencing. Altogether, our study suggests a role for RNA editing in miRNA-mediated gene regulation and splicing in human lungs. In this study, we have generated a RNA editome of human lung tissue that can be compared with other RNA editomes across different lung tissues to delineate a role for RNA editing in normal and diseased states.

  8. Event trigger identification for biomedical events extraction using domain knowledge.

    Science.gov (United States)

    Zhou, Deyu; Zhong, Dayou; He, Yulan

    2014-06-01

    In molecular biology, molecular events describe observable alterations of biomolecules, such as binding of proteins or RNA production. These events might be responsible for drug reactions or development of certain diseases. As such, biomedical event extraction, the process of automatically detecting description of molecular interactions in research articles, attracted substantial research interest recently. Event trigger identification, detecting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. Taking the event types as classes, event trigger identification can be viewed as a classification task. For each word in a sentence, a trained classifier predicts whether the word corresponds to an event type and which event type based on the context features. Therefore, a well-designed feature set with a good level of discrimination and generalization is crucial for the performance of event trigger identification. In this article, we propose a novel framework for event trigger identification. In particular, we learn biomedical domain knowledge from a large text corpus built from Medline and embed it into word features using neural language modeling. The embedded features are then combined with the syntactic and semantic context features using the multiple kernel learning method. The combined feature set is used for training the event trigger classifier. Experimental results on the golden standard corpus show that >2.5% improvement on F-score is achieved by the proposed framework when compared with the state-of-the-art approach, demonstrating the effectiveness of the proposed framework. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. On the usability of frequency distributions and source attribution of Cs-137 detections encountered in the IMS radio-nuclide network for radionuclide event screening and climate change monitoring

    Science.gov (United States)

    Becker, A.; Wotawa, G.; Zähringer, M.

    2009-04-01

    Under the provisions of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), airborne radioactivity is measured by means of high purity Germanium gamma ray detectors deployed in a global monitoring network. Almost 60 of the scheduled 80 stations have been put in provisional operations by the end of 2008. Each station daily sends the 24 hour samples' spectroscopic data to the Vienna based Provisional Technical Secretariat (PTS) of the CTBT Organization (CTBTO) for review for treaty-relevant nuclides. Cs-137 is one of these relevant isotopes. Its typical minimum detectable concentration is in the order of a few Bq/m3. However, this isotope is also known to occur in atmospheric trace concentrations, due to known non CTBT relevant processes and sources related to, for example, the re-suspension of cesium from historic nuclear tests and/or the Chernobyl reactor disaster, temporarily enhanced by bio-mass burning (Wotawa et al. 2006). Properly attributed cesium detections can be used as a proxy to detect Aeolian dust events (Igarashi et al, 2001) that potentially carry cesium from all aforementioned sources but are also known to play an important role for the radiative forcing in the atmosphere (shadow effect), at the surface (albedo) and the carbon dioxide cycle when interacting with oceanic phytoplankton (Mikami and Shi, 2005). In this context this paper provides a systematic attribution of recent Cs-137 detections in the PTS monitoring network in order to Characterize those stations which are regularly affected by Cs-137 Provide input for procedures that distinguish CTBT relevant detection from other sources (event screening) Explore on the capability of certain stations to use their Cs-137 detections as a proxy to detect aeolian dust events and to flag the belonging filters to be relevant for further investigations in this field (-> EGU-2009 Session CL16/AS4.6/GM10.1: Aeolian dust: initiator, player, and recorder of environmental change). References Igarashi, Y., M

  10. Barren-ground caribou (Rangifer tarandus groenlandicus) behaviour after recent fire events; integrating caribou telemetry data with Landsat fire detection techniques.

    Science.gov (United States)

    Rickbeil, Gregory J M; Hermosilla, Txomin; Coops, Nicholas C; White, Joanne C; Wulder, Michael A

    2017-03-01

    Fire regimes are changing throughout the North American boreal forest in complex ways. Fire is also a major factor governing access to high-quality forage such as terricholous lichens for barren-ground caribou (Rangifer tarandus groenlandicus). Additionally, fire alters forest structure which can affect barren-ground caribou's ability to navigate in a landscape. Here, we characterize how the size and severity of fires are changing across five barren-ground caribou herd ranges in the Northwest Territories and Nunavut, Canada. Additionally, we demonstrate how time since fire, fire severity, and season result in complex changes in caribou behavioural metrics estimated using telemetry data. Fire disturbances were identified using novel gap-free Landsat surface reflectance composites from 1985 to 2011 across all herd ranges. Burn severity was estimated using the differenced normalized burn ratio. Annual area burned and burn severity were assessed through time for each herd and related to two behavioural metrics: velocity and relative turning angle. Neither annual area burned nor burn severity displayed any temporal trend within the study period. However, certain herds, such as the Ahiak/Beverly, have more exposure to fire than other herds (i.e. Cape Bathurst had a maximum forested area burned of less than 4 km 2 ). Time since fire and burn severity both significantly affected velocity and relative turning angles. During fall, winter, and spring, fire virtually eliminated foraging-focused behaviour for all 26 years of analysis while more severe fires resulted in a marked increase in movement-focused behaviour compared to unburnt patches. Between seasons, caribou used burned areas as early as 1-year postfire, demonstrating complex, nonlinear reactions to time since fire, fire severity, and season. In all cases, increases in movement-focused behaviour were detected postfire. We conclude that changes in caribou behaviour immediately postfire are primarily driven by

  11. Is your error my concern? An event-related potential study on own and observed error detection in cooperation and competition

    Directory of Open Access Journals (Sweden)

    Ellen R.A. De Bruijn

    2012-02-01

    Full Text Available For successful goal-directed behavior it is essential for humans to continuously monitor one’s actions and detect errors as fast as possible. EEG studies have identified an error-related ERP component known as the error-related negativity or ERN. Theories on error monitoring propose a direct relation to reward processing. Whenever an error is made, the outcome of an action turns out to be worse than expected, resulting in a loss of reward and hence eliciting the ERN. However, as own errors are always associated with a loss of reward, disentangling whether the ERN is error- or reward-dependent has proven to be an extremely difficult endeavor. Recently, an ERN has also been demonstrated following the observation of other’s errors. An important difference with own errors is that other people’s errors can be associated with loss or gain depending on the cooperative or competitive context in which they are made. We conducted an ERP study to disentangle whether performance monitoring is error- or reward-dependent. Twelve pairs (N=24 of participants performed and observed a speeded-choice reaction task in two contexts. Own errors were always associated with a loss of reward. Observed errors in the cooperative context also yielded a loss of reward, but observed errors in the competitive context resulted in a gain. The results showed that the ERN was present following all types of errors independent of who made the error and the outcome of the action. Consequently, the current study demonstrates that performance monitoring as reflected by the ERN is error-specific and not directly dependent on reward.

  12. Integrated Disease Investigations and Surveillance planning: a systems approach to strengthening national surveillance and detection of events of public health importance in support of the International Health Regulations

    Directory of Open Access Journals (Sweden)

    Kennedy Sarah

    2010-12-01

    Full Text Available Abstract The international community continues to define common strategic themes of actions to improve global partnership and international collaborations in order to protect our populations. The International Health Regulations (IHR[2005] offer one of these strategic themes whereby World Health Organization (WHO Member States and global partners engaged in biosecurity, biosurveillance and public health can define commonalities and leverage their respective missions and resources to optimize interventions. The U.S. Defense Threat Reduction Agency’s Cooperative Biologica Engagement Program (CBEP works with partner countries across clinical, veterinary, epidemiological, and laboratory communities to enhance national disease surveillance, detection, diagnostic, and reporting capabilities. CBEP, like many other capacity building programs, has wrestled with ways to improve partner country buy-in and ownership and to develop sustainable solutions that impact integrated disease surveillance outcomes. Designing successful implementation strategies represents a complex and challenging exercise and requires robust and transparent collaboration at the country level. To address this challenge, the Laboratory Systems Development Branch of the U.S. Centers for Disease Control and Prevention (CDC and CBEP have partnered to create a set of tools that brings together key leadership of the surveillance system into a deliberate system design process. This process takes into account strengths and limitations of the existing system, how the components inter-connect and relate to one another, and how they can be systematically refined within the local context. The planning tools encourage cross-disciplinary thinking, critical evaluation and analysis of existing capabilities, and discussions across organizational and departmental lines toward a shared course of action and purpose. The underlying concepts and methodology of these tools are presented here.

  13. Event related potentials reveal early phonological and orthographic processing of single letters in letter-detection and letter-rhyme paradigms

    Directory of Open Access Journals (Sweden)

    Sewon Adrian Bann

    2016-04-01

    Full Text Available Introduction: When and where phonological processing occurs in the brain is still under some debate. Most paired-rhyme and phonological priming studies used word stimuli, which involve complex neural networks for word recognition and semantics. This study investigates early (300ms orthographic and phonological processing of letters.Methods: Eighteen participants aged 20-35 engaged in three two-forced choice experiments, one letter-detection (LetterID and two letter-rhyme (Paired-Rhyme and Letter-Rhyme tasks. From the EEG recordings, ERP differences within and across task stimuli were found. We also calculated the global field power (GFP for each participant. Accuracies and reaction times were also measured from their button presses for each task. Results: Behavioural: Reaction times were 18ms faster to letter than pseudoletter stimuli, and 27ms faster to rhyme than nonrhyme stimuli. ERP/GFP: In the LetterID task, grand-mean EPs showed typical P1, N1, P2, and P3 waveform morphologies to letter and pseudoletter stimuli, with GFPs to pseudoletters being greater than letters from 160-600ms. Across both rhyme tasks, there were greater negativities for nonrhyme than for rhyme stimuli at 145ms and 426ms. The P2 effect for rhyme stimuli was smaller than letter stimuli when compared across tasks.Conclusion: Differences in early processing of letters versus pseudoletters between 130-190ms suggest that letters are processed earlier and perhaps faster in the brain than pseudoletters. The P2 effect between letter and rhyme stimuli likely reflect sublexical phonological processing. Together, findings from our study fill in evidence for the temporal dynamics of orthographic and phonological processing of single letters.

  14. Integrated Disease Investigations and Surveillance planning: a systems approach to strengthening national surveillance and detection of events of public health importance in support of the International Health Regulations.

    Science.gov (United States)

    Taboy, Celine H; Chapman, Will; Albetkova, Adilya; Kennedy, Sarah; Rayfield, Mark A

    2010-12-03

    The international community continues to define common strategic themes of actions to improve global partnership and international collaborations in order to protect our populations. The International Health Regulations (IHR[2005]) offer one of these strategic themes whereby World Health Organization (WHO) Member States and global partners engaged in biosecurity, biosurveillance and public health can define commonalities and leverage their respective missions and resources to optimize interventions. The U.S. Defense Threat Reduction Agency's Cooperative Biological Engagement Program (CBEP) works with partner countries across clinical, veterinary, epidemiological, and laboratory communities to enhance national disease surveillance, detection, diagnostic, and reporting capabilities. CBEP, like many other capacity building programs, has wrestled with ways to improve partner country buy-in and ownership and to develop sustainable solutions that impact integrated disease surveillance outcomes. Designing successful implementation strategies represents a complex and challenging exercise and requires robust and transparent collaboration at the country level. To address this challenge, the Laboratory Systems Development Branch of the U.S. Centers for Disease Control and Prevention (CDC) and CBEP have partnered to create a set of tools that brings together key leadership of the surveillance system into a deliberate system design process. This process takes into account strengths and limitations of the existing system, how the components inter-connect and relate to one another, and how they can be systematically refined within the local context. The planning tools encourage cross-disciplinary thinking, critical evaluation and analysis of existing capabilities, and discussions across organizational and departmental lines toward a shared course of action and purpose. The underlying concepts and methodology of these tools are presented here.

  15. Events diary

    Science.gov (United States)

    2000-01-01

    as Imperial College, the Royal Albert Hall, the Royal College of Art, the Natural History and Science Museums and the Royal Geographical Society. Under the heading `Shaping the future together' BA2000 will explore science, engineering and technology in their wider cultural context. Further information about this event on 6 - 12 September may be obtained from Sandra Koura, BA2000 Festival Manager, British Association for the Advancement of Science, 23 Savile Row, London W1X 2NB (tel: 0171 973 3075, e-mail: sandra.koura@britassoc.org.uk ). Details of the creating SPARKS events may be obtained from creating.sparks@britassoc.org.uk or from the website www.britassoc.org.uk . Other events 3 - 7 July, Porto Alegre, Brazil VII Interamerican conference on physics education: The preparation of physicists and physics teachers in contemporary society. Info: IACPE7@if.ufrgs.br or cabbat1.cnea.gov.ar/iacpe/iacpei.htm 27 August - 1 September, Barcelona, Spain GIREP conference: Physics teacher education beyond 2000. Info: www.blues.uab.es/phyteb/index.html

  16. Relativistic tidal disruption events

    Directory of Open Access Journals (Sweden)

    Levan A.

    2012-12-01

    Full Text Available In March 2011 Swift detected an extremely luminous and long-lived outburst from the nucleus of an otherwise quiescent, low luminosity (LMC-like galaxy. Named Swift J1644+57, its combination of high-energy luminosity (1048 ergs s−1 at peak, rapid X-ray variability (factors of >100 on timescales of 100 seconds and luminous, rising radio emission suggested that we were witnessing the birth of a moderately relativistic jet (Γ ∼ 2 − 5, created when a star is tidally disrupted by the supermassive black hole in the centre of the galaxy. A second event, Swift J2058+0516, detected two months later, with broadly similar properties lends further weight to this interpretation. Taken together this suggests that a fraction of tidal disruption events do indeed create relativistic outflows, demonstrates their detectability, and also implies that low mass galaxies can host massive black holes. Here, I briefly outline the observational properties of these relativistic tidal flares observed last year, and their evolution over the first year since their discovery.

  17. Adverse event detection, monitoring, and evaluation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR project delivers a single-sensor structural health-monitoring (SHM) system that uses the impedance method to monitor structural integrity, wave propagation...

  18. ISOMER: Informative Segment Observations for Multimedia Event Recounting

    NARCIS (Netherlands)

    Sun, C.; Burns, B.; Nevatia, R.; Snoek, C.; Bolles, B.; Myers, G.; Wang, W.; Yeh, E.

    2014-01-01

    This paper describes a system for multimedia event detection and recounting. The goal is to detect a high level event class in unconstrained web videos and generate event oriented summarization for display to users. For this purpose, we detect informative segments and collect observations for them,

  19. Predicting civil unrest by categorizing Dutch Twitter events

    NARCIS (Netherlands)

    van Noord, R.; Kunneman, F.A.; Bosch, A.P.J. van den

    2016-01-01

    We propose a system that assigns topical labels to automatically detected events in the Twitter stream. The automatic detection and labeling of events in social media streams is a 'big data' problem. The early detection of future social events, specifically those associated with civil unrest, has a

  20. Predicting civil unrest by categorizing Dutch Twitter Events

    NARCIS (Netherlands)

    van Noord, Rik; Kunneman, F.; van den Bosch, Antal

    2016-01-01

    We propose a system that assigns topical labels to automatically detected events in the Twitter stream. The automatic detection and labeling of events in social media streams is a ’big data’ problem. The early detection of future social events, specifically those associated with civil unrest, has a

  1. Event dependent sampling of recurrent events

    DEFF Research Database (Denmark)

    Kvist, Tine Kajsa; Andersen, Per Kragh; Angst, Jules

    2010-01-01

    The effect of event-dependent sampling of processes consisting of recurrent events is investigated when analyzing whether the risk of recurrence increases with event count. We study the situation where processes are selected for study if an event occurs in a certain selection interval. Motivation...

  2. Future Events

    Directory of Open Access Journals (Sweden)

    Adli Tıp Uzmanları Derneği ATUD

    2010-04-01

    ://www.amc.edu/Academic/CME/ Upcoming_ Events.html QCLG-meeting 2011 26 November 2011, 29 November 2011 Brussels, Belgium URL: http://www.enfsi.eu/page.php?uid=2 ENFSI Joint Meeting 01 December 2011, 02 December 2011 The Hague (NFI, The Netherlands URL: http://www.enfsi.eu/page.php?uid=2 Bloodstain Pattern Recognition - Basic course 05 December 2011, 09 December 2011 The Hague, The Netherlands URL: http://www.enfsi.eu/page.php?uid= Expert Witness Intensive Training Course - 2 Day December 8th to 9th 2011 United Kingdom /London URL: http://www.healthcareconferencesuk.co.uk/ expert_witness 6th USA Pacific Medical & Legal Conference December 13th to 20th 2011 New York /USA URL: http://www.conferences21 .com/index.php? menu=home 12th Annual Multispecialty Conference on Medical Negligence & Risk Management in Medicine, Surgery, Emergency Medicine, Radiology & Family Medicine January 5th to 8th 2012 Costa Rica / URL http://www.bumc.bu.edu/cme/educational-opportunities/live-meetings/oblawl2/ 16th Annual Europe Pacific Medical & Legal Conference January 8th to 15th 2012 Italy /Cortina D’Ampezzo URL: http://www.conferences21.com/index.php? menu = home 3rd International Workshop on Medical Image Analysis and Description for Diagnosis Systems(MIAD 2012 1- 4 February 2012 Vilamoura, Algarve, Portugal URL: http://www.biostec.org/MIAD.asp 3rd International Conference on Current Trends in Forensic Sciences, Forensic Medicine & Toxicology February 3rd to 5th 2012 India /Jaipur URL: http://www.iamleconf.in/home 3rd International Conference on Legal Medicine, Medical Negligence & Litigation in Medical Practice February 3rd to 5th 2012 India /Jaipur URL http://www.iamleconf.in/ 12th Annual Pan Europe Pacific Medical & Legal Conference February 5th to 12th 2012 France /Paris URL: http://www.conferences21.com/index.php? menu=home American College of Legal Medicine 2012 Annual Conference February 23rd to 26th 2012 Louisiana /New Orleans USA URL: http://www.aclm.org/

  3. Event Index - an LHCb Event Search System

    CERN Document Server

    Ustyuzhanin, Andrey

    2015-01-01

    During LHC Run 1, the LHCb experiment recorded around 1011 collision events. This paper describes Event Index | an event search system. Its primary function is to quickly select subsets of events from a combination of conditions, such as the estimated decay channel or number of hits in a subdetector. Event Index is essentially Apache Lucene [1] optimized for read-only indexes distributed over independent shards on independent nodes.

  4. Vaccine Adverse Events

    Science.gov (United States)

    ... Biologics Evaluation & Research Vaccine Adverse Events Vaccine Adverse Events Share Tweet Linkedin Pin it More sharing options ... the primary immunization series in infants Report Adverse Event Report a Vaccine Adverse Event Contact FDA (800) ...

  5. Gastrointestinal events with clopidogrel

    DEFF Research Database (Denmark)

    Grove, Erik Lerkevang; Würtz, Morten; Schwarz, Peter

    2013-01-01

    Clopidogrel prevents cardiovascular events, but has been linked with adverse gastrointestinal (GI) complications, particularly bleeding events.......Clopidogrel prevents cardiovascular events, but has been linked with adverse gastrointestinal (GI) complications, particularly bleeding events....

  6. Creating Special Events

    Science.gov (United States)

    deLisle, Lee

    2009-01-01

    "Creating Special Events" is organized as a systematic approach to festivals and events for students who seek a career in event management. This book looks at the evolution and history of festivals and events and proceeds to the nuts and bolts of event management. The book presents event management as the means of planning, organizing, directing,…

  7. Pharmacy study of natural health product adverse reactions (SONAR): a cross-sectional study using active surveillance in community pharmacies to detect adverse events associated with natural health products and assess causality.

    Science.gov (United States)

    Necyk, Candace; Tsuyuki, Ross T; Boon, Heather; Foster, Brian C; Legatt, Don; Cembrowski, George; Murty, Mano; Barnes, Joanne; Charrois, Theresa L; Arnason, John T; Ware, Mark A; Rosychuk, Rhonda J; Vohra, Sunita

    2014-03-28

    To investigate the rates and causality of adverse event(s) (AE) associated with natural health product (NHP) use, prescription drug use and concurrent NHP-drug use through active surveillance in community pharmacies. Cross-sectional study of screened patients. 10 community pharmacies across Alberta and British Columbia, Canada from 14 January to 30 July 2011. The participating pharmacy staff screened consecutive patients, or agents of patients, who were dropping or picking up prescription medications. Patients were screened to determine the proportions of them using prescription drugs and/or NHPs, as well as their respective AE rates. All AEs reported by the screened patients who took a NHP, consented to, and were available for, a detailed telephone interview (14%) were adjudicated fully to assess for causality. Over a total of 105 pharmacy weeks and 1118 patients screened, 410 patients reported taking prescription drugs only (36.7%; 95% CI 33.9% to 39.5%), 37 reported taking NHPs only (3.3%; 95% CI 2.4% to 4.5%) and 657 reported taking prescription drugs and NHPs concurrently (58.8%; 95% CI 55.9% to 61.6%). In total, 54 patients reported an AE, representing 1.2% (95% CI 0.51% to 2.9%), 2.7% (95% CI 0.4% to 16.9%) and 7.3% (95% CI 5.6% to 9.6%) of each population, respectively. Compared with patients who reported using prescription drugs, the patients who reported using prescription drugs and NHPs concurrently were 6.4 times more likely to experience an AE (OR; 95% CI 2.52 to 16.17; ppharmacies take NHPs and prescription drugs concurrently, and of those, 7.4% (95% CI 6.3% to 8.8%) report an AE. A substantial proportion of community pharmacy patients use prescription drugs and NHPs concurrently; these patients are at a greater risk of experiencing an AE. Active surveillance provides a means of detecting such AEs and collecting high-quality data on which causality assessment can be based.

  8. National Special Security Events

    National Research Council Canada - National Science Library

    Reese, Shawn

    2007-01-01

    ...) as National Special Security Events (NSSE) Beginning in September 1998 through February 2007, there have been 27 events designated as NSSEs Some of these events have included presidential inaugurations, presidential nominating conventions...

  9. Signaling communication events in a computer network

    Science.gov (United States)

    Bender, Carl A.; DiNicola, Paul D.; Gildea, Kevin J.; Govindaraju, Rama K.; Kim, Chulho; Mirza, Jamshed H.; Shah, Gautam H.; Nieplocha, Jaroslaw

    2000-01-01

    A method, apparatus and program product for detecting a communication event in a distributed parallel data processing system in which a message is sent from an origin to a target. A low-level application programming interface (LAPI) is provided which has an operation for associating a counter with a communication event to be detected. The LAPI increments the counter upon the occurrence of the communication event. The number in the counter is monitored, and when the number increases, the event is detected. A completion counter in the origin is associated with the completion of a message being sent from the origin to the target. When the message is completed, LAPI increments the completion counter such that monitoring the completion counter detects the completion of the message. The completion counter may be used to insure that a first message has been sent from the origin to the target and completed before a second message is sent.

  10. Infants Segment Continuous Events Using Transitional Probabilities

    Science.gov (United States)

    Stahl, Aimee E.; Romberg, Alexa R.; Roseberry, Sarah; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

    2014-01-01

    Throughout their 1st year, infants adeptly detect statistical structure in their environment. However, little is known about whether statistical learning is a primary mechanism for event segmentation. This study directly tests whether statistical learning alone is sufficient to segment continuous events. Twenty-eight 7- to 9-month-old infants…

  11. Predictive Validity of the Beers and Screening Tool of Older Persons' Potentially Inappropriate Prescriptions (STOPP) Criteria to Detect Adverse Drug Events, Hospitalizations, and Emergency Department Visits in the United States.

    Science.gov (United States)

    Brown, Joshua D; Hutchison, Lisa C; Li, Chenghui; Painter, Jacob T; Martin, Bradley C

    2016-01-01

    To compare the predictive validity of the 2003 Beers, 2012 American Geriatrics Society (AGS) Beers, and Screening Tool of Older Persons' potentially inappropriate Prescriptions (STOPP) criteria. Retrospective cohort. Managed care administrative claims data from 2006 to 2009. Commercially insured persons aged 65 and older in the United States (N=174,275). Association between adverse drug events (ADEs), emergency department (ED) visits, and hospitalization outcomes and inappropriate medication use using time-varying Cox proportional hazard models. Measures of model discrimination (c-index) and hazard ratios (HRs) were calculated to compare unadjusted and adjusted models for associations. The prevalence of inappropriate prescribing was 34.1% for the 2012 AGS Beers criteria, 32.2% for the 2003 Beers criteria, and 27.6% for the STOPP criteria. Each set of criteria modestly discriminated ADEs in unadjusted analyses (STOPP criteria: hazard ratio (HR)=2.89, 95% confidence interval (CI)=2.68-3.12, C-index=0.607; 2012 AGS Beers criteria: HR=2.51, 95% CI=2.33-2.70, C-index=0.603; 2003 Beers criteria: HR=2.65, 95% CI=2.46-2.85, C-index=0.605). Similar results were observed for ED visits and hospitalizations. The c-indices increased to between 0.65 and 0.70 in adjusted analyses. The kappa for agreement between criteria was 0.80 for the 2003 and 2012 AGS Beers criteria, 0.58 for the 2012 AGS Beers and STOPP criteria, and 0.59 for the 2003 Beers and STOPP criteria. For the three outcomes, the 2012 AGS Beers criteria had the highest sensitivity (61.2-71.2%) and the lowest specificity (41.2-70.7%), and the STOPP criteria had the lowest sensitivity (53.8-64.7%) but the highest specificity (47.8-78.1%). All three criteria were modestly prognostic for ADEs, EDs, and hospitalizations, with the STOPP criteria slightly outperforming both Beers criteria. With low sensitivity, low specificity, and low agreement between the criteria, they can be used in a complementary fashion to enhance

  12. Episodes, events, and models

    Directory of Open Access Journals (Sweden)

    Sangeet eKhemlani

    2015-10-01

    Full Text Available We describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event segmentation is automatic, and that event segmentation yields mental simulations of events. But it posits two novel principles as well: first, discrete episodic markers track perceptual and conceptual changes, and can be retrieved to construct event models. Second, the process of retrieving and reconstructing those episodic markers is constrained and prioritized. We describe a computational implementation of the theory, as well as a robotic extension of the theory that demonstrates the processes of online event segmentation and event model construction. The theory is the first unified computational account of event segmentation and temporal inference. We conclude by demonstrating now neuroimaging data can constrain and inspire the construction of process-level theories of human reasoning.

  13. Automatic Distribution Network Reconfiguration: An Event-Driven Approach

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Fei; Jiang, Huaiguang; Tan, Jin

    2016-11-14

    This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observable and detectable.

  14. Co-design Events

    DEFF Research Database (Denmark)

    Brandt, Eva; Eriksen, Mette Agger

    2010-01-01

    One powerful co-design event is worth a thousand hours of individual work! Driving Innovation as a series of co-design events helps mobilize and involve all stakeholders to explore present everyday practices and to sketch new possible futures. But what makes a co-design event powerful? And why...... are series of events better than a sequence of deliverables and milestones in keeping innovation on track?...

  15. Event Modelling in CMS

    CERN Document Server

    Gunnellini, Paolo

    2017-01-01

    Latest tests of double parton scattering, underlying event tunes, minimum bias, and diffraction made by comparing CMS Run I and Run II data to the state-of-the-art theoretical predictions interfaced with up-to-date parton shower codes are presented. Studies to derive and to test the new CMS event tune obtained through jet kinematics in top quark pair events and global event variables are described.

  16. Conferences and Events

    International Development Research Centre (IDRC) Digital Library (Canada)

    André Lavoie

    2016-06-14

    Jun 14, 2016 ... Events include business meetings; corporate, branch or divisional management meetings; employee ... are responsible for demonstrating the highest standard of ethical conduct as outlined in the IDRC ... All other events such as social events, the Government of Canada Workplace Charitable. Campaign ...

  17. Traumatic events and children

    Science.gov (United States)

    ... for in your child and how to take care of your child after a traumatic event. Get professional help if your child is not recovering. Kinds of Traumatic Events Your child could experience a one-time traumatic event or a repeated trauma that happens over and over again. Examples of ...

  18. Event studies in Turkey

    Directory of Open Access Journals (Sweden)

    Ulkem Basdas

    2014-09-01

    Full Text Available The primary goal of this paper is to review the event studies conducted for Turkey to in order to identify the common components in their designs. This paper contributes to the existing literature by reviewing all event studies for Turkey for the first time, but more importantly; this review leads to the upcoming event studies on Turkey by highlighting main components of a proper design. Based on the review of 75 studies, it is observed that event studies generally choose BIST-100 (formerly, ISE-100 market index and market adjusted returns with the parametric tests. In general, the studies prefer to rely on one type of model to calculate abnormal returns without discussing the selection of the underlying model. Especially for the event studies focusing on the impact of political events or macroeconomic announcements in Turkey, there is a risk of clustering due to the application of same event date for all observations.

  19. Negated bio-events: analysis and identification

    Science.gov (United States)

    2013-01-01

    Background Negation occurs frequently in scientific literature, especially in biomedical literature. It has previously been reported that around 13% of sentences found in biomedical research articles contain negation. Historically, the main motivation for identifying negated events has been to ensure their exclusion from lists of extracted interactions. However, recently, there has been a growing interest in negative results, which has resulted in negation detection being identified as a key challenge in biomedical relation extraction. In this article, we focus on the problem of identifying negated bio-events, given gold standard event annotations. Results We have conducted a detailed analysis of three open access bio-event corpora containing negation information (i.e., GENIA Event, BioInfer and BioNLP’09 ST), and have identified the main types of negated bio-events. We have analysed the key aspects of a machine learning solution to the problem of detecting negated events, including selection of negation cues, feature engineering and the choice of learning algorithm. Combining the best solutions for each aspect of the problem, we propose a novel framework for the identification of negated bio-events. We have evaluated our system on each of the three open access corpora mentioned above. The performance of the system significantly surpasses the best results previously reported on the BioNLP’09 ST corpus, and achieves even better results on the GENIA Event and BioInfer corpora, both of which contain more varied and complex events. Conclusions Recently, in the field of biomedical text mining, the development and enhancement of event-based systems has received significant interest. The ability to identify negated events is a key performance element for these systems. We have conducted the first detailed study on the analysis and identification of negated bio-events. Our proposed framework can be integrated with state-of-the-art event extraction systems. The

  20. Automatic detection of laughter

    NARCIS (Netherlands)

    Truong, K.P.; Leeuwen, D.A. van

    2005-01-01

    In the context of detecting ‘paralinguistic events’ with the aim to make classification of the speaker’s emotional state possible, a detector was developed for one of the most obvious ‘paralinguistic events’, namely laughter. Gaussian Mixture Models were trained with Perceptual Linear Prediction

  1. Soundscapes, events, resistance

    Directory of Open Access Journals (Sweden)

    Andrea Mubi Brighenti

    2008-12-01

    Full Text Available Put it bluntly, a soundscape is the sonic counterpart, or component, of landscape. From such minimal assumption, some interesting consequences follow: just as landscape is far from being a simple stage-set upon which events take place, soundscape, too, is itself evental, i.e., it consists of events. Not only because its nature, far from being acoustics is always ‘psychoacoustics’, as Murray Schafer (1977/1994 first argued. Processes of environmental perception are of course there.

  2. Features, Events, and Processes: Disruptive Events

    Energy Technology Data Exchange (ETDEWEB)

    J. King

    2004-03-31

    The primary purpose of this analysis is to evaluate seismic- and igneous-related features, events, and processes (FEPs). These FEPs represent areas of natural system processes that have the potential to produce disruptive events (DE) that could impact repository performance and are related to the geologic processes of tectonism, structural deformation, seismicity, and igneous activity. Collectively, they are referred to as the DE FEPs. This evaluation determines which of the DE FEPs are excluded from modeling used to support the total system performance assessment for license application (TSPA-LA). The evaluation is based on the data and results presented in supporting analysis reports, model reports, technical information, or corroborative documents that are cited in the individual FEP discussions in Section 6.2 of this analysis report.

  3. Reliable Event Detectors for Constrained Resources Wireless Sensor Node Hardware

    Directory of Open Access Journals (Sweden)

    López Trinidad MarcoAntonio

    2009-01-01

    Full Text Available Abstract A novel event detector algorithm, which points out in-door acoustic human activities, for constrained wireless sensor node hardware is proposed in the present paper. In our approach, event detections are computed from the signal energy statistics change rate at two instants separated by an samples interval. The experimentation is run in two phases: (i the detector characterisation and tuning seek detector configurations that enable event detections from three acoustic human activities: closing a door, dropping a plastic bottle, and clapping;(ii event detector validation tests measure the reliability to signal events from general acoustic activities, people talking particularly. The test results, which included emulated node hardware, actual sensor node, and a one-hop WSN, demonstrate the detector implementations signaled successfully events. And for the WSN, we found that event detections decay in a nonlinear fashion as the distance , between the acoustic signal source and the sensor, is increased.

  4. Features, Events, and Processes: Disruptive Events

    Energy Technology Data Exchange (ETDEWEB)

    P. Sanchez

    2004-11-08

    The purpose of this analysis report is to evaluate and document the inclusion or exclusion of the disruptive events features, events, and processes (FEPs) with respect to modeling used to support the total system performance assessment for license application (TSPA-LA). A screening decision, either ''Included'' or ''Excluded,'' is given for each FEP, along with the technical basis for screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.114 (d), (e), and (f) [DIRS 156605]. The FEPs addressed in this report deal with both seismic and igneous disruptive events, such as fault displacements through the repository and an igneous intrusion into the repository. For included FEPs, this analysis summarizes the implementation of the FEP in TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from TSPA-LA (i.e., why the FEP is excluded). Previous versions of this report were developed to support the total system performance assessments (TSPA) for various prior repository designs. This revision addresses the repository design for the license application (LA).

  5. Committed Sport Event Volunteers

    Science.gov (United States)

    Han, Keunsu; Quarterman, Jerome; Strigas, Ethan; Ha, Jaehyun; Lee, Seungbum

    2013-01-01

    The purpose of this study was to investigate the relationships among selected demographic characteristics (income, education and age), motivation and commitment of volunteers at a sporting event. Three-hundred and five questionnaires were collected from volunteers in a marathon event and analyzed using structural equation modeling (SEM). Based on…

  6. The ATLAS Event Builder

    CERN Document Server

    Vandelli, W; Battaglia, A; Beck, H P; Blair, R; Bogaerts, A; Bosman, M; Ciobotaru, M; Cranfield, R; Crone, G; Dawson, J; Dobinson, Robert W; Dobson, M; Dos Anjos, A; Drake, G; Ermoline, Y; Ferrari, R; Ferrer, M L; Francis, D; Gadomski, S; Gameiro, S; Gorini, B; Green, B; Haberichter, W; Haberli, C; Hauser, R; Hinkelbein, C; Hughes-Jones, R; Joos, M; Kieft, G; Klous, S; Korcyl, K; Kordas, K; Kugel, A; Leahu, L; Lehmann, G; Martin, B; Mapelli, L; Meessen, C; Meirosu, C; Misiejuk, A; Mornacchi, G; Müller, M; Nagasaka, Y; Negri, A; Pasqualucci, E; Pauly, T; Petersen, J; Pope, B; Schlereth, J L; Spiwoks, R; Stancu, S; Strong, J; Sushkov, S; Szymocha, T; Tremblet, L; Ünel, G; Vermeulen, J; Werner, P; Wheeler-Ellis, S; Wickens, F; Wiedenmann, W; Yu, M; Yasu, Y; Zhang, J; Zobernig, H; 2007 IEEE Nuclear Science Symposium and Medical Imaging Conference

    2008-01-01

    Event data from proton-proton collisions at the LHC will be selected by the ATLAS experiment in a three-level trigger system, which, at its first two trigger levels (LVL1+LVL2), reduces the initial bunch crossing rate of 40~MHz to $sim$3~kHz. At this rate, the Event Builder collects the data from the readout system PCs (ROSs) and provides fully assembled events to the Event Filter (EF). The EF is the third trigger level and its aim is to achieve a further rate reduction to $sim$200~Hz on the permanent storage. The Event Builder is based on a farm of O(100) PCs, interconnected via a Gigabit Ethernet to O(150) ROSs. These PCs run Linux and multi-threaded software applications implemented in C++. All the ROSs, and substantial fractions of the Event Builder and Event Filter PCs have been installed and commissioned. We report on performance tests on this initial system, which is capable of going beyond the required data rates and bandwidths for Event Building for the ATLAS experiment.

  7. The Agency of Event

    DEFF Research Database (Denmark)

    Nicholas, Paul; Tamke, Martin; Riiber, Jacob

    2014-01-01

    This paper explores the notion of agency within event-based models. We present an event-based modeling approach that links interdependent generative, analytic and decision making sub-models within a system of exchange. Two case study projects demonstrate the underlying modeling concepts and metho...

  8. Practices Surrounding Event Photos

    NARCIS (Netherlands)

    Vyas, Dhaval; Nijholt, Antinus; van der Veer, Gerrit C.; Kotzé, P.; Marsden, G.; Lindgaard, G.; Wesson, J.; Winckler, M.

    Sharing photos through mobile devices has a great potential for creating shared experiences of social events between co-located as well as remote participants. In order to design novel event sharing tools, we need to develop indepth understanding of current practices surrounding these so called

  9. Conferences and Events

    International Development Research Centre (IDRC) Digital Library (Canada)

    André Lavoie

    2016-01-18

    Jan 18, 2016 ... Evening meal events for Governors, held in connection with Board meetings, must not cost more per person than 2.625 times the applicable meal allowance. The Chair of the Board must authorize any exception to the provision of this paragraph. Overnight stays related to events (other than conferences and ...

  10. Extracting semantically enriched events from biomedical literature

    Directory of Open Access Journals (Sweden)

    Miwa Makoto

    2012-05-01

    Full Text Available Abstract Background Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Results Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP’09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP’09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. Conclusions We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned

  11. Automated Testing with Targeted Event Sequence Generation

    DEFF Research Database (Denmark)

    Jensen, Casper Svenning; Prasad, Mukul R.; Møller, Anders

    2013-01-01

    Automated software testing aims to detect errors by producing test inputs that cover as much of the application source code as possible. Applications for mobile devices are typically event-driven, which raises the challenge of automatically producing event sequences that result in high coverage....... Some existing approaches use random or model-based testing that largely treats the application as a black box. Other approaches use symbolic execution, either starting from the entry points of the applications or on specific event sequences. A common limitation of the existing approaches...... is that they often fail to reach the parts of the application code that require more complex event sequences. We propose a two-phase technique for automatically finding event sequences that reach a given target line in the application code. The first phase performs concolic execution to build summaries...

  12. Reliable Event Detectors for Constrained Resources Wireless Sensor Node Hardware

    OpenAIRE

    López Trinidad MarcoAntonio; Valle Maurizio

    2009-01-01

    Abstract A novel event detector algorithm, which points out in-door acoustic human activities, for constrained wireless sensor node hardware is proposed in the present paper. In our approach, event detections are computed from the signal energy statistics change rate at two instants separated by an samples interval. The experimentation is run in two phases: (i) the detector characterisation and tuning seek detector configurations that enable event detections from three acoustic human activi...

  13. Basic non-linear effects in silicon radiation detector in detection of highly ionizing particles: registration of ultra rare events of superheavy nuclei in the long-term experiments

    CERN Document Server

    Tsyganov, Y S

    2015-01-01

    Sources of non-linear response of PIPS detector, when detecting highly ionizing particles like recoils (EVR), fission fragments and heavy ions, including formation of large pulse-height defect (PHD) are considered. An analytical formula to calculate the recombination component of EVR PHD is proposed on the base of surface recombination model with some empirical correction. PC-based simulation code for generating the spectrum of the measured recoil signal amplitudes of the heavy implanted nuclei is presented. The simulated spectra are compared with the experimental ones for the different facilities: the Dubna Gas Filled Recoil Separator (DGFRS), SHIP and RIKEN gas-filled separator. After the short reviewing of the detection system of the DGFRS, is considered the real-time matrix algorithm application aimed to the radical background suppression in the complete-fusion heavy-ion induced nuclear reactions. Typical examples of application in the long term experiments aimed to the synthesis of superheavy elements Z=...

  14. RAS Initiative - Events

    Science.gov (United States)

    The NCI RAS Initiative has organized multiple events with outside experts to discuss how the latest scientific and technological breakthroughs can be applied to discover vulnerabilities in RAS-driven cancers.

  15. News and Events

    Science.gov (United States)

    The latest news from the Office of Cancer Nanotechnology Research and the Alliance, as well as upcoming and past events attended by the Office of Cancer Nanotechnology Research staff, and relevant upcoming scientific meetings.

  16. "Universe" event at AIMS

    Science.gov (United States)

    2008-06-01

    Report of event of 11 May 2008 held at the African Institute of Mathematical Sciences (Muizenberg, Cape), with speakers Michael Griffin (Administrator of NASA), Stephen Hawking (Cambridge), David Gross (Kavli Institute, Santa Barbara) and George Smoot (Berkeley).

  17. Analysis of extreme events

    CSIR Research Space (South Africa)

    Khuluse, S

    2009-04-01

    Full Text Available ) determination of the distribution of the damage and (iii) preparation of products that enable prediction of future risk events. The methodology provided by extreme value theory can also be a powerful tool in risk analysis...

  18. Event visualization in ATLAS

    Science.gov (United States)

    Bianchi, R. M.; Boudreau, J.; Konstantinidis, N.; Martyniuk, A. C.; Moyse, E.; Thomas, J.; Waugh, B. M.; Yallup, D. P.; ATLAS Collaboration

    2017-10-01

    At the beginning, HEP experiments made use of photographical images both to record and store experimental data and to illustrate their findings. Then the experiments evolved and needed to find ways to visualize their data. With the availability of computer graphics, software packages to display event data and the detector geometry started to be developed. Here, an overview of the usage of event display tools in HEP is presented. Then the case of the ATLAS experiment is considered in more detail and two widely used event display packages are presented, Atlantis and VP1, focusing on the software technologies they employ, as well as their strengths, differences and their usage in the experiment: from physics analysis to detector development, and from online monitoring to outreach and communication. Towards the end, the other ATLAS visualization tools will be briefly presented as well. Future development plans and improvements in the ATLAS event display packages will also be discussed.

  19. Event visualization in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00211497; The ATLAS collaboration; Boudreau, Joseph; Konstantinidis, Nikolaos; Martyniuk, Alex; Moyse, Edward; Thomas, Juergen; Waugh, Ben; Yallup, David

    2017-01-01

    At the beginning, HEP experiments made use of photographical images both to record and store experimental data and to illustrate their findings. Then the experiments evolved and needed to find ways to visualize their data. With the availability of computer graphics, software packages to display event data and the detector geometry started to be developed. Here, an overview of the usage of event display tools in HEP is presented. Then the case of the ATLAS experiment is considered in more detail and two widely used event display packages are presented, Atlantis and VP1, focusing on the software technologies they employ, as well as their strengths, differences and their usage in the experiment: from physics analysis to detector development, and from online monitoring to outreach and communication. Towards the end, the other ATLAS visualization tools will be briefly presented as well. Future development plans and improvements in the ATLAS event display packages will also be discussed.

  20. CCG - News & Events

    Science.gov (United States)

    NCI's Center for Cancer Genomics (CCG) has been widely recognized for its research efforts to facilitiate advances in cancer genomic research and improve patient outcomes. Find the latest news about and events featuring CCG.

  1. Discrete Event Simulation

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 18; Issue 1. Discrete Event Simulation. Matthew Jacob ... Keywords. Simulation; modelling; computer programming. Author Affiliations. Matthew Jacob1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012.

  2. Studying overt word reading and speech production with event-related fMRI: a method for detecting, assessing, and correcting articulation-induced signal changes and for measuring onset time and duration of articulation.

    Science.gov (United States)

    Huang, Jie; Francis, Andrea P; Carr, Thomas H

    2008-01-01

    A quantitative method is introduced for detecting and correcting artifactual signal changes in BOLD time series data arising from the magnetic field warping caused by motion of the articulatory apparatus when speaking aloud, with extensions to detection of subvocal articulatory activity during silent reading. Whole-head images allow the large, spike-like signal changes from the moving tongue and other components of the articulatory apparatus to be detected and localized in time, providing a measure of the time of vocalization onset, the vocalization duration, and also an estimate of the magnitude and shape of the signal change resulting from motion. Data from brain voxels are then examined during the vocalization period, and statistical outliers corresponding to contamination from articulatory motion are removed and replaced by linear interpolation from adjacent, uncontaminated data points. This quantitative approach to cleansing brain time series data of articulatory-motion-induced artifact is combined with a pre-scanning training regimen that reduces gross head movement during reading aloud to the levels observed during reading silently, which can be corrected with available image registration techniques. The combination of quantitative analysis of articulatory motion artifacts and pre-scanning training makes possible a much wider range of tasks involving overt speech than are currently being used in fMRI studies of language and cognition, as well as characterization of subvocal movements of the articulatory apparatus that are relevant to theories of reading skill, verbal rehearsal in working memory, and problem solving.

  3. Gargamelle: neutral current event

    CERN Multimedia

    1973-01-01

    This event shows real tracks of particles from the 1200 litre Gargamelle bubble chamber that ran on the PS from 1970 to 1976 and on the SPS from 1976 to 1979. In this image a neutrino passes close to a nucleon and reemerges as a neutrino. Such events are called neutral curent, as they are mediated by the Z0 boson which has no electric charge.

  4. QCD (&) event generators

    Energy Technology Data Exchange (ETDEWEB)

    Skands, Peter Z.; /Fermilab

    2005-07-01

    Recent developments in QCD phenomenology have spurred on several improved approaches to Monte Carlo event generation, relative to the post-LEP state of the art. In this brief review, the emphasis is placed on approaches for (1) consistently merging fixed-order matrix element calculations with parton shower descriptions of QCD radiation, (2) improving the parton shower algorithms themselves, and (3) improving the description of the underlying event in hadron collisions.

  5. First Indico Virtual Event

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    The first Indico virtual event will take place on February 4th 15:00 and will focus on two main topics The release of Indico v1.2 The migration of the OO Indico backend database (ZODB) to a more standard DBMS It will be fully virtual using the CERN Vidyo service and will foster discussions between developers and administrators of Indico servers worldwide. Connections to the virtual room will be open, but attendees are encouraged to register to the event, in order to be informed of any changes in the organisation if any. If you would like to add a topic of discussion or propose yourself a contribution, please let us know at indico-team@cern.ch. Connection to Vidyo Vidyo connection details are available here CERN Vidyo service documentation can be found here First-time users are encouraged to try the service before connecting to the real event

  6. Discrete-Event Simulation

    Directory of Open Access Journals (Sweden)

    Prateek Sharma

    2015-04-01

    Full Text Available Abstract Simulation can be regarded as the emulation of the behavior of a real-world system over an interval of time. The process of simulation relies upon the generation of the history of a system and then analyzing that history to predict the outcome and improve the working of real systems. Simulations can be of various kinds but the topic of interest here is one of the most important kind of simulation which is Discrete-Event Simulation which models the system as a discrete sequence of events in time. So this paper aims at introducing about Discrete-Event Simulation and analyzing how it is beneficial to the real world systems.

  7. Keyframe labeling technique for surveillance event classification

    Science.gov (United States)

    Şaykol, Ediz; Baştan, Muhammet; Güdükbay, Uğur; Ulusoy, Özgür

    2010-11-01

    The huge amount of video data generated by surveillance systems necessitates the use of automatic tools for their efficient analysis, indexing, and retrieval. Automated access to the semantic content of surveillance videos to detect anomalous events is among the basic tasks; however, due to the high variability of the audio-visual features and large size of the video input, it still remains a challenging task, though a considerable amount of research dealing with automated access to video surveillance has appeared in the literature. We propose a keyframe labeling technique, especially for indoor environments, which assigns labels to keyframes extracted by a keyframe detection algorithm, and hence transforms the input video to an event-sequence representation. This representation is used to detect unusual behaviors, such as crossover, deposit, and pickup, with the help of three separate mechanisms based on finite state automata. The keyframes are detected based on a grid-based motion representation of the moving regions, called the motion appearance mask. It has been shown through performance experiments that the keyframe labeling algorithm significantly reduces the storage requirements and yields reasonable event detection and classification performance.

  8. Conferences and Events

    International Development Research Centre (IDRC) Digital Library (Canada)

    André Lavoie

    2017-06-28

    Jun 28, 2017 ... Training events that relate to ensuring that employees are qualified to perform their assigned duties – for instance, acquiring or maintaining professional accreditations of recognized professional bodies as required by the employees to practice their profession; and membership to such professional bodies;.

  9. Events and Effects

    DEFF Research Database (Denmark)

    Rytter, Mikkel

    2010-01-01

    Analyzing the period of ‘intensive transnationalism’ among Pakistani migrants in Denmark precipitated by the 2005 earthquake in Kashmir, this article explores the relationship between events and effects on a global scale. One significant initiative after the disaster was the founding of an ad hoc...

  10. The ATLAS event filter

    CERN Document Server

    Beck, H P; Boissat, C; Davis, R; Duval, P Y; Etienne, F; Fede, E; Francis, D; Green, P; Hemmer, F; Jones, R; MacKinnon, J; Mapelli, Livio P; Meessen, C; Mommsen, R K; Mornacchi, Giuseppe; Nacasch, R; Negri, A; Pinfold, James L; Polesello, G; Qian, Z; Rafflin, C; Scannicchio, D A; Stanescu, C; Touchard, F; Vercesi, V

    1999-01-01

    An overview of the studies for the ATLAS Event Filter is given. The architecture and the high level design of the DAQ-1 prototype is presented. The current status if the prototypes is briefly given. Finally, future plans and milestones are given. (11 refs).

  11. Print Centre Event 2

    OpenAIRE

    Hadbavny, Michelle

    2012-01-01

    During Institutions by Artists, Fillip was pleased to present a series of free, parallel events in the lobby of SFU Woodward’s that investigated the material culture produced by the institutional practices of artists. The Print Centre featured talks, launches, and screenings by conference presenters and attendees. Presented in collaboration with a temporary book store hosted by Motto Books (Berlin).

  12. Print Centre Event 3

    OpenAIRE

    Hadbavny, Michelle

    2012-01-01

    During Institutions by Artists, Fillip was pleased to present a series of free, parallel events in the lobby of SFU Woodward’s that investigated the material culture produced by the institutional practices of artists. The Print Centre featured talks, launches, and screenings by conference presenters and attendees. Presented in collaboration with a temporary book store hosted by Motto Books (Berlin).

  13. Language As Social Event.

    Science.gov (United States)

    Harste, Jerome C.

    A taxonomy developed for the study of the growth and development of written language from the perspective of social event was tested with a group of 68 children, aged three to six years. The subjects were presented with a wide variety of environmental print messages (road signs, toys, fast food signs, and household products) and were questioned…

  14. Business Event Notification Service (BENS)

    Data.gov (United States)

    Department of Veterans Affairs — BENS provides a notification of pre-defined business events to applications, portals, and automated business processes. Such events are defined in the Event Catalog,...

  15. Whole-Genome Analysis of Gene Conversion Events

    Science.gov (United States)

    Hsu, Chih-Hao; Zhang, Yu; Hardison, Ross; Miller, Webb

    Gene conversion events are often overlooked in analyses of genome evolution. In a conversion event, an interval of DNA sequence (not necessarily containing a gene) overwrites a highly similar sequence. The event creates relationships among genomic intervals that can confound attempts to identify orthologs and to transfer functional annotation between genomes. Here we examine 1,112,202 paralogous pairs of human genomic intervals, and detect conversion events in about 13.5% of them. Properties of the putative gene conversions are analyzed, such as the lengths of the paralogous pairs and the spacing between their sources and targets. Our approach is illustrated using conversion events in the beta-globin gene cluster.

  16. Event-Based Activity Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2004-01-01

    We present and discuss a modeling approach that supports event-based modeling of information and activity in information systems. Interacting human actors and IT-actors may carry out such activity. We use events to create meaningful relations between information structures and the related...... activities inside and outside an IT-system. We use event-activity diagrams to model activity. Such diagrams support the modeling of activity flow, object flow, shared events, triggering events, and interrupting events....

  17. ATLAS EventIndex General Dataflow and Monitoring Infrastructure

    CERN Document Server

    Barberis, Dario; The ATLAS collaboration

    2016-01-01

    The ATLAS EventIndex has been running in production since mid-2015, reliably collecting information worldwide about all produced events and storing them in a central Hadoop infrastructure at CERN. A subset of this information is copied to an Oracle relational database for fast datasets discovery, event-picking, crosschecks with other ATLAS systems and checks for event duplication. The system design and its optimization is serving event picking from requests of a few events up to scales of tens of thousand of events, and in addition, data consistency checks are performed for large production campaigns. Detecting duplicate events with a scope of physics collections has recently arisen as an important use case. This paper describes the general architecture of the project and the data flow and operation issues, which are addressed by recent developments to improve the throughput of the overall system. In this direction, the data collection system is reducing the usage of the messaging infrastructure to overcome t...

  18. ATLAS EventIndex general dataflow and monitoring infrastructure

    CERN Document Server

    AUTHOR|(SzGeCERN)638886; The ATLAS collaboration; Barberis, Dario; Favareto, Andrea; Garcia Montoro, Carlos; Gonzalez de la Hoz, Santiago; Hrivnac, Julius; Prokoshin, Fedor; Salt, Jose; Sanchez, Javier; Toebbicke, Rainer; Yuan, Ruijun

    2017-01-01

    The ATLAS EventIndex has been running in production since mid-2015, reliably collecting information worldwide about all produced events and storing them in a central Hadoop infrastructure at CERN. A subset of this information is copied to an Oracle relational database for fast dataset discovery, event-picking, crosschecks with other ATLAS systems and checks for event duplication. The system design and its optimization is serving event picking from requests of a few events up to scales of tens of thousand of events, and in addition, data consistency checks are performed for large production campaigns. Detecting duplicate events with a scope of physics collections has recently arisen as an important use case. This paper describes the general architecture of the project and the data flow and operation issues, which are addressed by recent developments to improve the throughput of the overall system. In this direction, the data collection system is reducing the usage of the messaging infrastructure to overcome th...

  19. Agriculture: Natural Events and Disasters

    Science.gov (United States)

    Natural Events and DiasastersInformation on Natural Events and Disasters. Every year natural disasters, such as hurricanes, floods, fires, earthquakes, and tornadoes, challenge agricultural production.

  20. Multiple Orderings of Events in Disease Progression.

    Science.gov (United States)

    Young, Alexandra L; Oxtoby, Neil P; Huang, Jonathan; Marinescu, Razvan V; Daga, Pankaj; Cash, David M; Fox, Nick C; Ourselin, Sebastien; Schott, Jonathan M; Alexander, Daniel C

    2015-01-01

    The event-based model constructs a discrete picture of disease progression from cross-sectional data sets, with each event corresponding to a new biomarker becoming abnormal. However, it relies on the assumption that all subjects follow a single event sequence. This is a major simplification for sporadic disease data sets, which are highly heterogeneous, include distinct subgroups, and contain significant proportions of outliers. In this work we relax this assumption by considering two extensions to the event-based model: a generalised Mallows model, which allows subjects to deviate from the main event sequence, and a Dirichlet process mixture of generalised Mallows models, which models clusters of subjects that follow different event sequences, each of which has a corresponding variance. We develop a Gibbs sampling technique to infer the parameters of the two models from multi-modal biomarker data sets. We apply our technique to data from the Alzheimer's Disease Neuroimaging Initiative to determine the sequence in which brain regions become abnormal in sporadic Alzheimer's disease, as well as the heterogeneity of that sequence in the cohort. We find that the generalised Mallows model estimates a larger variation in the event sequence across subjects than the original event-based model. Fitting a Dirichlet process model detects three subgroups of the population with different event sequences. The Gibbs sampler additionally provides an estimate of the uncertainty in each of the model parameters, for example an individual's latent disease stage and cluster assignment. The distributions and mixtures of sequences that this new family of models introduces offer better characterisation of disease progression of heterogeneous populations, new insight into disease mechanisms, and have the potential for enhanced disease stratification and differential diagnosis.

  1. The Method of Event Determination Registered on the Event Source

    OpenAIRE

    Aleksandr Vasilevich Kuznetcov

    2016-01-01

    In this article the method of event determination registered into audit trails on the event source based on solution of linear programming task is described. This method allows optimizing the event management process within an information security management system by quantity of incidents. This method considers restrictions related to performance of the event source.

  2. The Method of Event Determination Registered on the Event Source

    Directory of Open Access Journals (Sweden)

    Aleksandr Vasilevich Kuznetcov

    2016-03-01

    Full Text Available In this article the method of event determination registered into audit trails on the event source based on solution of linear programming task is described. This method allows optimizing the event management process within an information security management system by quantity of incidents. This method considers restrictions related to performance of the event source.

  3. Potential role of telemedical service centers in managing remote monitoring data transmitted daily by cardiac implantable electronic devices: results of the early detection of cardiovascular events in device patients with heart failure (detecT-Pilot) study.

    Science.gov (United States)

    Müller, Axel; Goette, Andreas; Perings, Christian; Nägele, Herbert; Konorza, Thomas; Spitzer, Wilhelm; Schulz, Sabine-Susan; von Bary, Christian; Hoffmann, Matthias; Albani, Marco; Sack, Stefan; Niederlöhner, Annegret; Lewalter, Thorsten

    2013-06-01

    Implantable cardioverter-defibrillators (ICDs) alone or combined with cardiac resynchronization therapy (CRT-Ds) featuring automatic home monitoring (HM) function can be monitored remotely on a daily basis. Different ways of implementing HM into clinical routines are possible, with efficient patient management being the main objective. In this study, a concept using a telemedical service center (TmSC) to manage HM data was developed and investigated regarding patients' satisfaction, physicians' satisfaction, and alert filtering. Fifty-five ICD or CRT-D patients with symptomatic heart failure were enrolled. The TmSC received HM data, identified "actionable parameters" (APs) by following protocol-defined procedures, conducted structured patient interviews, and forwarded selected APs to the respective follow-up clinic. Satisfaction of patients and physicians with the TmSC was evaluated at the end of the study by purpose-designed questionnaires. During a mean follow-up of 402±200 days, 3,831 APs were identified and analyzed at the TmSC (5.28 per patient-month). Most APs were triggered by a pilot detection algorithm for worsening heart failure (2.80 per patient-month), followed by atrial tachyarrhythmia episodes (1.10 per patient-month) and ventricular pacing issues (0.87 per patient-month). The TmSC forwarded 682 APs (18% of all APs) to 10 study sites. Approximately 65% of physicians and patients deemed the TmSC improved patient care. The TmSC-based management concept was well accepted and appreciated by the majority of physicians and patients. It may be helpful in gaining symptomatic information on top of automatic HM data and in supporting smaller clinics in the follow-up of their device patients.

  4. Event Relation Recognition by Multi Part of Speech Association Distribution Characteristics

    Directory of Open Access Journals (Sweden)

    Han Chao

    2017-01-01

    Full Text Available Event relation recognition, as one of natural language processing technologies, faces information stream of texts detecting event relation. By analyzing the influence of the words of different parts of speech on the relevance of events. And use the form of lexical chain to extract and store the relevant vocabulary between events, this paper propose an event relation recognization method based on lexical chain to detect latent semantic relation between events: whether events hold logical relation or not. Cornpared with the method based on dependency cue inference, the proposed method achieves 7. 68% improvement.

  5. ATLAS EventIndex General Dataflow and Monitoring Infrastructure

    CERN Document Server

    Fernandez Casani, Alvaro; The ATLAS collaboration

    2016-01-01

    The ATLAS EventIndex has been running in production since mid-2015, reliably collecting information worldwide about all produced events and storing them in a central Hadoop infrastructure at CERN. A subset of this information is copied to an Oracle relational database for fast access. The system design and its optimization is serving event picking from requests of a few events up to scales of tens of thousand of events, and in addition, data consistency checks are performed for large production campaigns. Detecting duplicate events with a scope of physics collections has recently arisen as an important use case. This paper describes the general architecture of the project and the data flow and operation issues, which are addressed by recent developments to improve the throughput of the overall system. In this direction, the data collection system is reducing the usage of the messaging infrastructure to overcome the performance shortcomings detected during production peaks; an object storage approach is instea...

  6. Corrigendum: The loudest event statistic: general formulation, properties and applications

    Science.gov (United States)

    Biswas, Rahul; Brady, Patrick R.; Creighton, Jolien D. E.; Fairhurst, Stephen; Mendell, Gregory; Privitera, Stephen

    2013-04-01

    The loudest event statistic, a method by which the rate at which events occur can be deduced from the significance of the most significant event (or loudest event), has been employed in several papers describing the search for gravitational waves produced by coalescing compact binaries in data from the LIGO and Virgo observatories. The paper ‘The loudest event statistic: general formulation, properties and applications’ (Biswas et al 2009 Class. Quantum Grav. 26 175009) presents a general formulation of the loudest event statistic and addresses topics on the estimation of rate intervals, on combining multiple experiments, and on marginalizing over uncertainties in parameters. A conceptual error in section 5 of Biswas et al (2009) led to invalid results regarding the marginalization over uncertainties in the averaged detection efficiency; specifically its equations (23) and (24) are incorrect, as are its equations (25) and (27). This corrigendum presents a correct treatment of the marginalization of uncertainties in the estimated detection efficiency.

  7. Chelyabinsk event: injuries

    Science.gov (United States)

    Kartashova, A.; Popova, O.; Jenniskens, P.; Glazachev, D.

    2017-09-01

    In the morning of 2013 February 15 (at 3:20 UT), a relatively large ( 20m) meteoroid entered the Earth atmosphere in the Chelyabinsk Region of Russia and caused an airburst strong enough to