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Sample records for abnormal event detection

  1. Saliency-based abnormal event detection in crowded scenes

    NASA Astrophysics Data System (ADS)

    Shi, Yanjiao; Liu, Yunxiang; Zhang, Qing; Yi, Yugen; Li, Wenju

    2016-11-01

    Abnormal event detection plays a critical role for intelligent video surveillance, and detection in crowded scenes is a challenging but more practical task. We present an abnormal event detection method for crowded video. Region-wise modeling is proposed to address the inconsistent detected motion of the same object due to different depths of field. Comparing to traditional block-wise modeling, the region-wise method not only can reduce heavily the number of models to be built but also can enrich the samples for training the normal events model. In order to reduce the computational burden and make the region-based anomaly detection feasible, a saliency detection technique is adopted in this paper. By identifying the salient parts of the image sequences, the irrelevant blocks are ignored, which removes the disturbance and improves the detection performance further. Experiments on the benchmark dataset and comparisons with the state-of-the-art algorithms validate the advantages of the proposed method.

  2. Abnormal events detection in crowded scenes by trajectory cluster

    NASA Astrophysics Data System (ADS)

    Zhou, Shifu; Zhang, Zhijiang; Zeng, Dan; Shen, Wei

    2015-02-01

    Abnormal events detection in crowded scenes has been a challenge due to volatility of the definitions for both normality and abnormality, the small number of pixels on the target, appearance ambiguity resulting from the dense packing, and severe inter-object occlusions. A novel framework was proposed for the detection of unusual events in crowded scenes using trajectories produced by moving pedestrians based on an intuition that the motion patterns of usual behaviors are similar to these of group activity, whereas unusual behaviors are not. First, spectral clustering is used to group trajectories with similar spatial patterns. Different trajectory clusters represent different activities. Then, unusual trajectories can be detected using these patterns. Furthermore, behavior of a mobile pedestrian can be defined by comparing its direction with these patterns, such as moving in the opposite direction of the group or traversing the group. Experimental results indicated that the proposed algorithm could be used to reliably locate the abnormal events in crowded scenes.

  3. Detection of Abnormal Events via Optical Flow Feature Analysis

    PubMed Central

    Wang, Tian; Snoussi, Hichem

    2015-01-01

    In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm. PMID:25811227

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

    PubMed

    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.

  5. Online Least Squares One-Class Support Vector Machines-Based Abnormal Visual Event Detection

    PubMed Central

    Wang, Tian; Chen, Jie; Zhou, Yi; Snoussi, Hichem

    2013-01-01

    The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samples to provide a basic normal model, then updates the model through remaining data. In the sparse online scheme, the model complexity is controlled by the coherence criterion. The online LS-OC-SVM is adopted to handle the abnormal event detection problem. Each frame of the video is characterized by the covariance matrix descriptor encoding the moving information, then is classified into a normal or an abnormal frame. Experiments are conducted, on a two-dimensional synthetic distribution dataset and a benchmark video surveillance dataset, to demonstrate the promising results of the proposed online LS-OC-SVM method. PMID:24351629

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

    PubMed

    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.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26196165

  8. Architecture design of the multi-functional wavelet-based ECG microprocessor for realtime detection of abnormal cardiac events.

    PubMed

    Cheng, Li-Fang; Chen, Tung-Chien; Chen, Liang-Gee

    2012-01-01

    Most of the abnormal cardiac events such as myocardial ischemia, acute myocardial infarction (AMI) and fatal arrhythmia can be diagnosed through continuous electrocardiogram (ECG) analysis. According to recent clinical research, early detection and alarming of such cardiac events can reduce the time delay to the hospital, and the clinical outcomes of these individuals can be greatly improved. Therefore, it would be helpful if there is a long-term ECG monitoring system with the ability to identify abnormal cardiac events and provide realtime warning for the users. The combination of the wireless body area sensor network (BASN) and the on-sensor ECG processor is a possible solution for this application. In this paper, we aim to design and implement a digital signal processor that is suitable for continuous ECG monitoring and alarming based on the continuous wavelet transform (CWT) through the proposed architectures--using both programmable RISC processor and application specific integrated circuits (ASIC) for performance optimization. According to the implementation results, the power consumption of the proposed processor integrated with an ASIC for CWT computation is only 79.4 mW. Compared with the single-RISC processor, about 91.6% of the power reduction is achieved.

  9. Varenicline and Abnormal Sleep Related Events

    PubMed Central

    Savage, Ruth L.; Zekarias, Alem; Caduff-Janosa, Pia

    2015-01-01

    Study Objectives: To assess adverse drug reaction reports of “abnormal sleep related events” associated with varenicline, a partial agonist to the α4β2 subtype of nicotinic acetylcholine receptors on neurones, indicated for smoking cessation. Design: Twenty-seven reports of “abnormal sleep related events” often associated with abnormal dreams, nightmares, or somnambulism, which are known to be associated with varenicline use, were identified in the World Health Organisation (WHO) Global Individual Case Safety Reports Database. Original anonymous reports were obtained from the four national pharmacovigilance centers that submitted these reports and assessed for reaction description and causality. Measurements and Results: These 27 reports include 10 of aggressive activity occurring during sleep and seven of other sleep related harmful or potentially harmful activities, such as apparently deliberate self-harm, moving a child or a car, or lighting a stove or a cigarette. Assessment of these 17 reports of aggression or other actual or potential harm showed that nine patients recovered or were recovering on varenicline withdrawal and there were no consistent alternative explanations. Thirteen patients experienced single events, and two had multiple events. Frequency was not stated for the remaining two patients. Conclusions: The descriptions of the reports of aggression during sleep with violent dreaming are similar to those of rapid eye movement sleep behavior disorder and also nonrapid eye movement (NREM) sleep parasomnias in some adults. Patients who experience somnambulism or dreams of a violent nature while taking varenicline should be advised to consult their health providers. Consideration should be given to clarifying the term sleep disorders in varenicline product information and including sleep related harmful and potentially harmful events. Citation: Savage RL, Zekarias A, Caduff-Janosa P. Varenicline and abnormal sleep related events. SLEEP 2015

  10. Abnormality detection in noisy biosignals.

    PubMed

    Kaya, Emine Merve; Elhilali, Mounya

    2013-01-01

    Although great strides have been achieved in computer-aided diagnosis (CAD) research, a major remaining problem is the ability to perform well under the presence of significant noise. In this work, we propose a mechanism to find instances of potential interest in time series for further analysis. Adaptive Kalman filters are employed in parallel among different feature axes. Lung sounds recorded in noisy conditions are used as an example application, with spectro-temporal feature extraction to capture the complex variabilities in sound. We demonstrate that both disease indicators and distortion events can be detected, reducing long time series signals into a sparse set of relevant events.

  11. Can transcutaneous recordings detect gastric electrical abnormalities?

    PubMed Central

    Familoni, B O; Bowes, K L; Kingma, Y J; Cote, K R

    1991-01-01

    The ability of transcutaneous recordings of gastric electrical activity to detect gastric electrical abnormalities was determined by simultaneous measurements of gastric electrical activity with surgically implanted serosal electrodes and cutaneous electrodes in six patients undergoing abdominal operations. Transient abnormalities in gastric electrical activity were seen in five of the six patients during the postoperative period. Recognition of normal gastric electrical activity by visual analysis was possible 67% of the time and with computer analysis 95% of the time. Ninety four per cent of abnormalities in frequency were detected by visual analysis and 93.7% by computer analysis. Abnormalities involving a loss of coupling, however, were not recognised by transcutaneous recordings. Transcutaneous recordings of gastric electrical activity assessed by computer analysis can usually recognise normal gastric electrical activity and tachygastria. Current techniques, however, are unable to detect abnormalities in electrical coupling. PMID:1864531

  12. Detection of anomalous events

    DOEpatents

    Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

    2016-06-07

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). 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 anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

  13. Detection of solar events

    DOEpatents

    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.

  14. First-Trimester Detection of Surface Abnormalities

    PubMed Central

    Rousian, Melek; Koning, Anton H. J.; Bonsel, Gouke J.; Eggink, Alex J.; Cornette, Jérôme M. J.; Schoonderwaldt, Ernst M.; Husen-Ebbinge, Margreet; Teunissen, Katinka K.; van der Spek, Peter J.; Steegers, Eric A. P.; Exalto, Niek

    2014-01-01

    The aim was to determine the diagnostic performance of 3-dimensional virtual reality ultrasound (3D_VR_US) and conventional 2- and 3-dimensional ultrasound (2D/3D_US) for first-trimester detection of structural abnormalities. Forty-eight first trimester cases (gold standard available, 22 normal, 26 abnormal) were evaluated offline using both techniques by 5 experienced, blinded sonographers. In each case, we analyzed whether each organ category was correctly indicated as normal or abnormal and whether the specific diagnosis was correctly made. Sensitivity in terms of normal or abnormal was comparable for both techniques (P = .24). The general sensitivity for specific diagnoses was 62.6% using 3D_VR_US and 52.2% using 2D/3D_US (P = .075). The 3D_VR_US more often correctly diagnosed skeleton/limb malformations (36.7% vs 10%; P = .013). Mean evaluation time in 3D_VR_US was 4:24 minutes and in 2D/3D_US 2:53 minutes (P < .001). General diagnostic performance of 3D_VR_US and 2D/3D_US apparently is comparable. Malformations of skeleton and limbs are more often detected using 3D_VR_US. Evaluation time is longer in 3D_VR_US. PMID:24440996

  15. Abnormal Activity Detection Using Pyroelectric Infrared Sensors.

    PubMed

    Luo, Xiaomu; Tan, Huoyuan; Guan, Qiuju; Liu, Tong; Zhuo, Hankz Hankui; Shen, Baihua

    2016-06-03

    Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them. The natural clustering of normal activities is discovered through a self-tuning spectral clustering algorithm with unsupervised model selection on the eigenvectors of a modified similarity matrix. Hidden Markov Models (HMMs) are employed to model each cluster of normal activities and form feature vectors. One-Class Support Vector Machines (OSVMs) are used to profile the normal activities and detect abnormal activities. To validate the efficacy of our method, we conducted experiments in real indoor environments. The encouraging results show that our method is able to detect abnormal activities given only the normal training samples, which aims to avoid the laborious and inconsistent data labeling process.

  16. Abnormal Activity Detection Using Pyroelectric Infrared Sensors

    PubMed Central

    Luo, Xiaomu; Tan, Huoyuan; Guan, Qiuju; Liu, Tong; Zhuo, Hankz Hankui; Shen, Baihua

    2016-01-01

    Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them. The natural clustering of normal activities is discovered through a self-tuning spectral clustering algorithm with unsupervised model selection on the eigenvectors of a modified similarity matrix. Hidden Markov Models (HMMs) are employed to model each cluster of normal activities and form feature vectors. One-Class Support Vector Machines (OSVMs) are used to profile the normal activities and detect abnormal activities. To validate the efficacy of our method, we conducted experiments in real indoor environments. The encouraging results show that our method is able to detect abnormal activities given only the normal training samples, which aims to avoid the laborious and inconsistent data labeling process. PMID:27271632

  17. Skeleton-Based Abnormal Gait Detection.

    PubMed

    Nguyen, Trong-Nguyen; Huynh, Huu-Hung; Meunier, Jean

    2016-10-26

    Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%.

  18. Skeleton-Based Abnormal Gait Detection

    PubMed Central

    Nguyen, Trong-Nguyen; Huynh, Huu-Hung; Meunier, Jean

    2016-01-01

    Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%. PMID:27792181

  19. Unsupervised abnormality detection using saliency and Retinex based color enhancement.

    PubMed

    Deeba, Farah; Mohammed, Shahed K; Bui, Francis M; Wahid, Khan A

    2016-08-01

    An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm. In the first stage, an adaptive color enhancement method based on Retinex theory is applied on the endoscopic images. In the second stage, an efficient salient region detection algorithm is applied to detect the clinically significant regions. The proposed algorithm is applied on a dataset containing images with diverse pathologies. The algorithm can successfully detect a significant percentage of the abnormal regions. From our experiment, it was evident that color enhancement method improves the performance of abnormality detection. The proposed algorithm can achieve a sensitivity of 97.33% and specificity of 79%, higher than state-of-the-art performance.

  20. Abnormal early cleavage events predict early embryo demise: sperm oxidative stress and early abnormal cleavage.

    PubMed

    Burruel, Victoria; Klooster, Katie; Barker, Christopher M; Pera, Renee Reijo; Meyers, Stuart

    2014-10-13

    Human embryos resulting from abnormal early cleavage can result in aneuploidy and failure to develop normally to the blastocyst stage. The nature of paternal influence on early embryo development has not been directly demonstrated although many studies have suggested effects from spermatozoal chromatin packaging, DNA damage, centriolar and mitotic spindle integrity, and plasma membrane integrity. The goal of this study was to determine whether early developmental events were affected by oxidative damage to the fertilizing sperm. Survival analysis was used to compare patterns of blastocyst formation based on P2 duration. Kaplan-Meier survival curves demonstrate that relatively few embryos with short (<1 hr) P2 times reached blastocysts, and the two curves diverged beginning on day 4, with nearly all of the embryos with longer P2 times reaching blastocysts by day 6 (p < .01). We determined that duration of the 2nd to 3rd mitoses were sensitive periods in the presence of spermatozoal oxidative stress. Embryos that displayed either too long or too short cytokineses demonstrated an increased failure to reach blastocyst stage and therefore survive for further development. Although paternal-derived gene expression occurs later in development, this study suggests a specific role in early mitosis that is highly influenced by paternal factors.

  1. Hepatic perfusion abnormalities during CT angiography: Detection and interpretation

    SciTech Connect

    Freeny, P.C.; Marks, W.M.

    1986-06-01

    Twenty-seven perfusion abnormalities were detected in 17 of 50 patients who underwent computed tomographic angiography (CTA) of the liver. All but one of the perfusion abnormalities occurred in patients with primary or metastatic liver tumors. Perfusion abnormalities were lobar in nine cases, segmental in 11, and subsegmental in seven; 14 were hypoperfusion and 13 were hyperperfusion abnormalities. The causes for the abnormalities included nonperfusion of a replaced hepatic artery (n = 11), cirrhosis and nodular regeneration (n = 3), altered hepatic hemodynamics (e.g., siphoning, laminar flow) caused by tumor (n = 7), contrast media washout from a nonperfused vessel (n = 1), compression of adjacent hepatic parenchyma (n = 1), and unknown (n = 4). Differentiation of perfusion abnormalities from tumor usually can be made by comparing the morphology of the known tumor with the suspected perfusion abnormality, changes of each on delayed CTA scans, and review of initial angiograms and other imaging studies.

  2. Improvement of Abnormality Detection System for Bathers Using Ultrasonic Sensors

    NASA Astrophysics Data System (ADS)

    Dobashi, Hiroki; Tajima, Takuya; Abe, Takehiko; Nambo, Hidetaka; Kimura, Haruhiko

    This paper proposes a new method for improving an existing abnormality detection system for person who soaks in a bathtub. As the number of aged people increases year by year in Japan, bathing accident of the aged is growing at a rapid rate, especially in-bathtub drowning accident. Therefore, prompt detection of bather's abnormality such as dizziness and fainting is important to prevent in-bathtub drowning. In order to detect bather's abnormality promptly, an abnormality detection system using seven ultrasonic sensors has been proposed. The system uses the following two methods: posture detection and behavior detection, to detect bather's different state from normal before an accident occurs, and improves a delay of detection considered to be a serious problem heretofore. There was however plenty of room for improvement. In order to improve detection rate of the system, we propose a new detection method in this paper. The method uses two ultrasonic sensors to beam bather's head and neck, and detects the head height and swing speed of the head. Experimental results are superior to the accuracy of the existing system, which enables us to detect bather's abnormality more accurately.

  3. Acoustic Event Detection and Classification

    NASA Astrophysics Data System (ADS)

    Temko, Andrey; Nadeu, Climent; Macho, Dušan; Malkin, Robert; Zieger, Christian; Omologo, Maurizio

    The human activity that takes place in meeting rooms or classrooms is reflected in a rich variety of acoustic events (AE), produced either by the human body or by objects handled by humans, so the determination of both the identity of sounds and their position in time may help to detect and describe that human activity. Indeed, speech is usually the most informative sound, but other kinds of AEs may also carry useful information, for example, clapping or laughing inside a speech, a strong yawn in the middle of a lecture, a chair moving or a door slam when the meeting has just started. Additionally, detection and classification of sounds other than speech may be useful to enhance the robustness of speech technologies like automatic speech recognition.

  4. Detection of abnormalities in a human gait using smart shoes

    NASA Astrophysics Data System (ADS)

    Kong, Kyoungchul; Bae, Joonbum; Tomizuka, Masayoshi

    2008-03-01

    Health monitoring systems require a means for detecting and quantifying abnormalities from measured signals. In this paper, a new method for detecting abnormalities in a human gait is proposed for an improved gait monitoring system for patients with walking problems. In the previous work, we introduced a fuzzy logic algorithm for detecting phases in a human gait based on four foot pressure sensors for each of the right and left foot. The fuzzy logic algorithm detects the gait phases smoothly and continuously, and retains all information obtained from sensors. In this paper, a higher level algorithm for detecting abnormalities in the gait phases obtained from the fuzzy logic is discussed. In the proposed algorithm, two major abnormalities are detected 1) when the sensors measure improper foot pressure patterns, and 2) when the human does not follow a natural sequence of gait phases. For mathematical realization of the algorithm, the gait phases are dealt with by a vector analysis method. The proposed detection algorithm is verified by experiments on abnormal gaits as well as normal gaits. The experiment makes use of the Smart Shoes that embeds four bladders filled with air, the pressure changes in which are detected by pressure transducers.

  5. Development of Abnormality Detection System for Bathers using Ultrasonic Sensors

    NASA Astrophysics Data System (ADS)

    Ohnishi, Yosuke; Abe, Takehiko; Nambo, Hidetaka; Kimura, Haruhiko; Ogoshi, Yasuhiro

    This paper proposes an abnormality detection system for bather sitting in bathtub. Increasing number of in-bathtub drowning accidents in Japan draws attention. Behind this large number of bathing accidents, Japan's unique social and cultural background come surface. For majority of people in Japan, bathing serves purpose in deep warming up of body, relax and enjoyable time. Therefore it is the custom for the Japanese to soak in bathtub. However overexposure to hot water may cause dizziness or fainting, which is possible to cause in-bathtub drowning. For drowning prevention, the system detects bather's abnormal state using an ultrasonic sensor array. The array, which has many ultrasonic sensors, is installed on the ceiling of bathroom above bathtub. The abnormality detection system uses the following two methods: posture detection and behavior detection. The function of posture detection is to estimate the risk of drowning by monitoring bather's posture. Meanwhile, the function of behavior detection is to estimate the risk of drowning by monitoring bather's behavior. By using these methods, the system detects bathers' different state from normal. As a result of experiment with a subject in the bathtub, the system was possible to detect abnormal state using subject's posture and behavior. Therefore the system is useful for monitoring bather to prevent drowning in bathtub.

  6. Detectability of Discrete Event Systems with Dynamic Event Observation

    PubMed Central

    Shu, Shaolong; Lin, Feng

    2009-01-01

    Our previous work considers detectability of discrete event systems which is to determine the current state and subsequent states of a system based on event observation. We assume that event observation is static, that is, if an event is observable, then all its occurrences are observable. However, in practical systems such as sensor networks, event observation often needs to be dynamic, that is, the occurrences of same events may or may not be observable, depending on the state of the system. In this paper, we generalize static event observation into dynamic event observation and consider the detectability problem under dynamic event observation. We define four types of detectabilities. To check detectabilities, we construct the observer with exponential complexity. To reduce computational complexity, we can also construct a detector with polynomial complexity to check strong detectabilities. Dynamic event observation can be implemented in two possible ways: a passive observation and an active observation. For the active observation, we discuss how to find minimal event observation policies that preserve four types of detectabilities respectively. PMID:20161618

  7. Detecting Abnormal Machine Characteristics in Cloud Infrastructures

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Das, Kamalika; Matthews, Bryan L.

    2011-01-01

    In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

  8. Using State Estimation Residuals to Detect Abnormal SCADA Data

    SciTech Connect

    Ma, Jian; Chen, Yousu; Huang, Zhenyu; Wong, Pak C.

    2010-04-30

    Detection of abnormal supervisory control and data acquisition (SCADA) data is critically important for safe and secure operation of modern power systems. In this paper, a methodology of abnormal SCADA data detection based on state estimation residuals is presented. Preceded with a brief overview of outlier detection methods and bad SCADA data detection for state estimation, the framework of the proposed methodology is described. Instead of using original SCADA measurements as the bad data sources, the residuals calculated based on the results of the state estimator are used as the input for the outlier detection algorithm. The BACON algorithm is applied to the outlier detection task. The IEEE 118-bus system is used as a test base to evaluate the effectiveness of the proposed methodology. The accuracy of the BACON method is compared with that of the 3-σ method for the simulated SCADA measurements and residuals.

  9. Proportionate Responses to Life Events Influence Clinicians' Judgments of Psychological Abnormality

    ERIC Educational Resources Information Center

    Kim, Nancy S.; Paulus, Daniel J.; Gonzalez, Jeffrey S.; Khalife, Danielle

    2012-01-01

    Psychological abnormality is a fundamental concept in the "Diagnostic and Statistical Manual of Mental Disorders" ("DSM-IV-TR"; American Psychiatric Association, 2000) and in all clinical evaluations. How do practicing clinical psychologists use the context of life events to judge the abnormality of a person's current behaviors? The appropriate…

  10. Guide to good practices for notifications and investigation of abnormal events

    SciTech Connect

    1998-12-01

    This Guide to Good Practices is written to enhance understanding of, and provide direction for, Notifications, Chapter VII, and Investigation of Abnormal Events, Chapter VI, of Department of Energy (DOE) Order 5480.19, Conduct of Operations Requirements for DOE Facilities. The practices in this guide should be considered when planning or reviewing programs for notifications and investigation of abnormal events. Contractors are advised to adopt procedures that meet the intent of DOE Order 5480.19. Notifications and Investigation of Abnormal Events are elements of an effective Conduct of Operations program. The complexity and array of activities performed in DOE facilities dictate the necessity for a coordinated notifications program and a consistent method for investigating abnormal events to promote safe and efficient operations.

  11. Guide to good practices for notifications and investigation of abnormal events

    SciTech Connect

    Not Available

    1993-06-01

    This Guide to Good Practices is written to enhance understanding of, and provide direction for, Notifications, Chapter VII, and Investigation of Abnormal Events, Chapter VI, of Department of Energy (DOE) Order 5480.19, ``Conduct of Operations Requirements for DOE Facilities.`` The practices in this guide should be considered when planning or reviewing programs for notifications and investigation of abnormal events. Contractors are advised to adopt procedures that meet the intent of DOE Order 5480.19. ``Notifications`` and ``Investigation of Abnormal Events`` are elements of an effective Conduct of Operations program. The complexity and array of activities performed in DOE facilities dictate the necessity for a coordinated notifications program and a consistent method for investigating abnormal events to promote safe and efficient operations.

  12. Event oriented dictionary learning for complex event detection.

    PubMed

    Yan, Yan; Yang, Yi; Meng, Deyu; Liu, Gaowen; Tong, Wei; Hauptmann, Alexander G; Sebe, Nicu

    2015-06-01

    Complex event detection is a retrieval task with the goal of finding videos of a particular event in a large-scale unconstrained Internet video archive, given example videos and text descriptions. Nowadays, different multimodal fusion schemes of low-level and high-level features are extensively investigated and evaluated for the complex event detection task. However, how to effectively select the high-level semantic meaningful concepts from a large pool to assist complex event detection is rarely studied in the literature. In this paper, we propose a novel strategy to automatically select semantic meaningful concepts for the event detection task based on both the events-kit text descriptions and the concepts high-level feature descriptions. Moreover, we introduce a novel event oriented dictionary representation based on the selected semantic concepts. Toward this goal, we leverage training images (frames) of selected concepts from the semantic indexing dataset with a pool of 346 concepts, into a novel supervised multitask lp -norm dictionary learning framework. Extensive experimental results on TRECVID multimedia event detection dataset demonstrate the efficacy of our proposed method.

  13. Methods and systems for detecting abnormal digital traffic

    DOEpatents

    Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

    2011-03-22

    Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

  14. Chromosomal abnormalities in fetuses with ultrasonographically detected neural tube defects.

    PubMed

    Kanit, Hakan; Özkan, Azra Arici; Öner, Soner Recai; Ispahi, Ciğdem; Endrikat, Jan Siegfried; Ertan, Kubilay

    2011-10-01

    We analyzed the karyotype of fetuses with ultrasonographically detected neural tube defects (NTDs). In our study, we included a total of 194 fetuses with NTDs. We analyzed the type of NTD, the karyotype, maternal age, fetal gestational age at diagnosis, and fetal sex. Of the 194 fetuses with NTDs, 87 were anencephalic and 107 had other, nonanencephalic, NTDs. A total of 12 fetuses were shown to have chromosomal abnormalities. Three of 87 anencephalic fetuses (3.45%) had chromosomal abnormalities. The sex ratio for anencephalic fetuses was 65.5% : 34.5% for female and male fetuses. Nine of 107 fetuses with other NTDs (8.41%) had chromosomal abnormalities. Seven fetuses had isolated NTDs and a further seven fetuses had additional ultrasonographic anomalies. Two of the latter had abnormal karyotypes. The sex ratio of all other NTD cases was 67.3% : 32.7% for female and male fetuses. The high number of chromosomal abnormalities justifies prenatal karyotyping in all fetuses with ultrasonographically diagnosed NTDs.

  15. Proportionate responses to life events influence clinicians' judgments of psychological abnormality.

    PubMed

    Kim, Nancy S; Paulus, Daniel J; Gonzalez, Jeffrey S; Khalife, Danielle

    2012-09-01

    Psychological abnormality is a fundamental concept in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000) and in all clinical evaluations. How do practicing clinical psychologists use the context of life events to judge the abnormality of a person's current behaviors? The appropriate role of life-event context in assessment has long been the subject of intense debate and scrutiny among clinical theorists, yet relatively little is known about clinicians' own judgments in practice. The authors propose a proportionate-response hypothesis, such that judgments of abnormality are influenced by whether the behaviors are a disproportionate response to past events, rendering them difficult to understand or explain. Licensed, practicing clinical psychologists (N = 77) were presented with vignettes describing hypothetical people's behaviors (disordered, mildly distressed, or unaffected) that had been preceded by either traumatic or mildly distressing events. Experts' judgments of abnormality were strongly and systematically influenced by the degree of mismatch between the past event and current behaviors in strength and valence, such that the greater the mismatch, the more abnormal the person seemed. A separate, additional group of clinical psychologists (N = 20) further confirmed that the greater the degree of mismatch, the greater the perceived difficulty in understanding the patient. These findings held true across clinicians of different theoretical orientations and in disorders for which these patterns of judgments ran contrary to formal recommendations in the DSM-IV-TR (American Psychiatric Association, 2000). The rationality of these effects and implications for clinical decision science are discussed.

  16. Detecting rare, abnormally large grains by x-ray diffraction

    DOE PAGES

    Boyce, Brad L.; Furnish, Timothy Allen; Padilla, H. A.; ...

    2015-07-16

    Bimodal grain structures are common in many alloys, arising from a number of different causes including incomplete recrystallization and abnormal grain growth. These bimodal grain structures have important technological implications, such as the well-known Goss texture which is now a cornerstone for electrical steels. Yet our ability to detect bimodal grain distributions is largely confined to brute force cross-sectional metallography. The present study presents a new method for rapid detection of unusually large grains embedded in a sea of much finer grains. Traditional X-ray diffraction-based grain size measurement techniques such as Scherrer, Williamson–Hall, or Warren–Averbach rely on peak breadth andmore » shape to extract information regarding the average crystallite size. However, these line broadening techniques are not well suited to identify a very small fraction of abnormally large grains. The present method utilizes statistically anomalous intensity spikes in the Bragg peak to identify regions where abnormally large grains are contributing to diffraction. This needle-in-a-haystack technique is demonstrated on a nanocrystalline Ni–Fe alloy which has undergone fatigue-induced abnormal grain growth. In this demonstration, the technique readily identifies a few large grains that occupy <0.00001 % of the interrogation volume. Finally, while the technique is demonstrated in the current study on nanocrystalline metal, it would likely apply to any bimodal polycrystal including ultrafine grained and fine microcrystalline materials with sufficiently distinct bimodal grain statistics.« less

  17. Detecting rare, abnormally large grains by x-ray diffraction

    SciTech Connect

    Boyce, Brad L.; Furnish, Timothy Allen; Padilla, H. A.; Van Campen, Douglas; Mehta, Apurva

    2015-07-16

    Bimodal grain structures are common in many alloys, arising from a number of different causes including incomplete recrystallization and abnormal grain growth. These bimodal grain structures have important technological implications, such as the well-known Goss texture which is now a cornerstone for electrical steels. Yet our ability to detect bimodal grain distributions is largely confined to brute force cross-sectional metallography. The present study presents a new method for rapid detection of unusually large grains embedded in a sea of much finer grains. Traditional X-ray diffraction-based grain size measurement techniques such as Scherrer, Williamson–Hall, or Warren–Averbach rely on peak breadth and shape to extract information regarding the average crystallite size. However, these line broadening techniques are not well suited to identify a very small fraction of abnormally large grains. The present method utilizes statistically anomalous intensity spikes in the Bragg peak to identify regions where abnormally large grains are contributing to diffraction. This needle-in-a-haystack technique is demonstrated on a nanocrystalline Ni–Fe alloy which has undergone fatigue-induced abnormal grain growth. In this demonstration, the technique readily identifies a few large grains that occupy <0.00001 % of the interrogation volume. Finally, while the technique is demonstrated in the current study on nanocrystalline metal, it would likely apply to any bimodal polycrystal including ultrafine grained and fine microcrystalline materials with sufficiently distinct bimodal grain statistics.

  18. Detection of Wind Turbine Power Performance Abnormalities Using Eigenvalue Analysis

    DTIC Science & Technology

    2014-12-23

    Detection of Wind Turbine Power Performance Abnormalities Using Eigenvalue Analysis Georgios Alexandros Skrimpas1, Christian Walsted Sweeney2, Kun S...University of Denmark, Lyngby, 2800, Denmark nm@elektro.dtu.dk jh@elektro.dtu.dk ABSTRACT Condition monitoring of wind turbines is a field of continu...ous research and development as new turbine configurations enter into the market and new failure modes appear. Systems utilising well established

  19. Improving the performance of cardiac abnormality detection from PCG signal

    NASA Astrophysics Data System (ADS)

    Sujit, N. R.; Kumar, C. Santhosh; Rajesh, C. B.

    2016-03-01

    The Phonocardiogram (PCG) signal contains important information about the condition of heart. Using PCG signal analysis prior recognition of coronary illness can be done. In this work, we developed a biomedical system for the detection of abnormality in heart and methods to enhance the performance of the system using SMOTE and AdaBoost technique have been presented. Time and frequency domain features extracted from the PCG signal is input to the system. The back-end classifier to the system developed is Decision Tree using CART (Classification and Regression Tree), with an overall classification accuracy of 78.33% and sensitivity (alarm accuracy) of 40%. Here sensitivity implies the precision obtained from classifying the abnormal heart sound, which is an essential parameter for a system. We further improve the performance of baseline system using SMOTE and AdaBoost algorithm. The proposed approach outperforms the baseline system by an absolute improvement in overall accuracy of 5% and sensitivity of 44.92%.

  20. Generalized Detectability for Discrete Event Systems

    PubMed Central

    Shu, Shaolong; Lin, Feng

    2011-01-01

    In our previous work, we investigated detectability of discrete event systems, which is defined as the ability to determine the current and subsequent states of a system based on observation. For different applications, we defined four types of detectabilities: (weak) detectability, strong detectability, (weak) periodic detectability, and strong periodic detectability. In this paper, we extend our results in three aspects. (1) We extend detectability from deterministic systems to nondeterministic systems. Such a generalization is necessary because there are many systems that need to be modeled as nondeterministic discrete event systems. (2) We develop polynomial algorithms to check strong detectability. The previous algorithms are based on observer whose construction is of exponential complexity, while the new algorithms are based on a new automaton called detector. (3) We extend detectability to D-detectability. While detectability requires determining the exact state of a system, D-detectability relaxes this requirement by asking only to distinguish certain pairs of states. With these extensions, the theory on detectability of discrete event systems becomes more applicable in solving many practical problems. PMID:21691432

  1. Detecting unitary events without discretization of time.

    PubMed

    Grün, S; Diesmann, M; Grammont, F; Riehle, A; Aertsen, A

    1999-12-15

    In earlier studies we developed the 'Unitary Events' analysis (Grün S. Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance and Interpretation. Reihe Physik, Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.) to detect the presence of conspicuous spike coincidences in multiple single unit recordings and to evaluate their statistical significance. The method enabled us to study the relation between spike synchronization and behavioral events (Riehle A, Grün S, Diesmann M, Aertsen A. Spike synchronization and rate modulation differentially involved in motor cortical function. Science 1997;278:1950-1953.). There is recent experimental evidence that the timing accuracy of coincident spiking events, which might be relevant for higher brain function, may be in the range of 1-5 ms. To detect coincidences on that time scale, we sectioned the observation interval into short disjunct time slices ('bins'). Unitary Events analysis of this discretized process demonstrated that coincident events can indeed be reliably detected. However, the method looses sensitivity for higher temporal jitter of the events constituting the coincidences (Grün S. Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance and Interpretation. Reihe Physik, Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.). Here we present a new approach, the 'multiple shift' method (MS), which overcomes the need for binning and treats the data in their (original) high time resolution (typically 1 ms, or better). Technically, coincidences are detected by shifting the spike trains against each other over the range of allowed coincidence width and integrating the number of exact coincidences (on the time resolution of the data) over all shifts. We found that the new method enhances the sensitivity for coincidences with temporal jitter. Both methods are outlined and compared on the basis of their analytical description and their application on

  2. Detecting Extreme Events in Gridded Climate Data

    SciTech Connect

    Ramachandra, Bharathkumar; Gadiraju, Krishna; Vatsavai, Raju; Kaiser, Dale Patrick; Karnowski, Thomas Paul

    2016-01-01

    Detecting and tracking extreme events in gridded climatological data is a challenging problem on several fronts: algorithms, scalability, and I/O. Successful detection of these events will give climate scientists an alternate view of the behavior of different climatological variables, leading to enhanced scientific understanding of the impacts of events such as heat and cold waves, and on a larger scale, the El Nin o Southern Oscillation. Recent advances in computing power and research in data sciences enabled us to look at this problem with a different perspective from what was previously possible. In this paper we present our computationally efficient algorithms for anomalous cluster detection on climate change big data. We provide results on detection and tracking of surface temperature and geopotential height anomalies, a trend analysis, and a study of relationships between the variables. We also identify the limitations of our approaches, future directions for research and alternate approaches.

  3. Detection of goal events in soccer videos

    NASA Astrophysics Data System (ADS)

    Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

    2004-12-01

    In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

  4. Detection of goal events in soccer videos

    NASA Astrophysics Data System (ADS)

    Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

    2005-01-01

    In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

  5. Automated Detection of Events of Scientific Interest

    NASA Technical Reports Server (NTRS)

    James, Mark

    2007-01-01

    A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

  6. Applying data mining techniques to detect abnormal flight characteristics

    NASA Astrophysics Data System (ADS)

    Aslaner, H. E.; Unal, Cagri; Iyigun, Cem

    2016-05-01

    This paper targets to highlight flight safety issues by applying data mining techniques to recorded flight data and proactively detecting abnormalities in certain flight phases. For this purpose, a result oriented method is offered which facilitates the process of post flight data analysis. In the first part of the study, a common time period of flight is defined and critical flight parameters are selected to be analyzed. Then the similarities of the flight parameters in time series basis are calculated for each flight by using Dynamic Time Warping (DTW) method. In the second part, hierarchical clustering technique is applied to the aggregate data matrix which is comprised of all the flights to be studied in terms of similarities among chosen parameters. Consequently, proximity levels among flight phases are determined. In the final part, an algorithm is constructed to distinguish outliers from clusters and classify them as suspicious flights.

  7. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

    Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

  8. Abnormal/Emergency Situations. Impact of Unmanned Aircraft Systems Emergency and Abnormal Events on the National Airspace System

    NASA Technical Reports Server (NTRS)

    2006-01-01

    Access 5 analyzed the differences between UAS and manned aircraft operations under five categories of abnormal or emergency situations: Link Failure, Lost Communications, Onboard System Failures, Control Station Failures and Abnormal Weather. These analyses were made from the vantage point of the impact that these operations have on the US air traffic control system, with recommendations for new policies and procedures included where appropriate.

  9. Detection and recognition of indoor smoking events

    NASA Astrophysics Data System (ADS)

    Bien, Tse-Lun; Lin, Chang Hong

    2013-03-01

    Smoking in public indoor spaces has become prohibited in many countries since it not only affects the health of the people around you, but also increases the risk of fire outbreaks. This paper proposes a novel scheme to automatically detect and recognize smoking events by using exsiting surveillance cameras. The main idea of our proposed method is to detect human smoking events by recognizing their actions. In this scheme, the human pose estimation is introduced to analyze human actions from their poses. The human pose estimation method segments head and both hands from human body parts by using a skin color detection method. However, the skin color methods may fail in insufficient light conditions. Therefore, the lighting compensation is applied to help the skin color detection method become more accurate. Due to the human body parts may be covered by shadows, which may cause the human pose estimation to fail, the Kalman filter is applied to track the missed body parts. After that, we evaluate the probability features of hands approaching the head. The support vector machine (SVM) is applied to learn and recognize the smoking events by the probability features. To analysis the performance of proposed method, the datasets established in the survillance camera view under indoor enviroment are tested. The experimental results show the effectiveness of our proposed method with accuracy rate of 83.33%.

  10. Novel instrumentation of multispectral imaging technology for detecting tissue abnormity

    NASA Astrophysics Data System (ADS)

    Yi, Dingrong; Kong, Linghua

    2012-10-01

    Multispectral imaging is becoming a powerful tool in a wide range of biological and clinical studies by adding spectral, spatial and temporal dimensions to visualize tissue abnormity and the underlying biological processes. A conventional spectral imaging system includes two physically separated major components: a band-passing selection device (such as liquid crystal tunable filter and diffraction grating) and a scientific-grade monochromatic camera, and is expensive and bulky. Recently micro-arrayed narrow-band optical mosaic filter was invented and successfully fabricated to reduce the size and cost of multispectral imaging devices in order to meet the clinical requirement for medical diagnostic imaging applications. However the challenging issue of how to integrate and place the micro filter mosaic chip to the targeting focal plane, i.e., the imaging sensor, of an off-shelf CMOS/CCD camera is not reported anywhere. This paper presents the methods and results of integrating such a miniaturized filter with off-shelf CMOS imaging sensors to produce handheld real-time multispectral imaging devices for the application of early stage pressure ulcer (ESPU) detection. Unlike conventional multispectral imaging devices which are bulky and expensive, the resulting handheld real-time multispectral ESPU detector can produce multiple images at different center wavelengths with a single shot, therefore eliminates the image registration procedure required by traditional multispectral imaging technologies.

  11. Multiple model estimator based detection of abnormal cell overheating in a Li-ion battery string with minimum number of temperature sensors

    NASA Astrophysics Data System (ADS)

    Lystianingrum, Vita; Hredzak, Branislav; Agelidis, Vassilios G.

    2015-01-01

    This paper proposes modeling of abnormal cell overheating caused by internal short circuit in a cell of a Li-ion battery string by augmenting the cell state space model with unknown input disturbance. Furthermore, with minimum number of temperature sensors, in order to identify which of the cells in the string is experiencing the abnormal overheating, a multiple model estimator (MME) is used. Simulation results demonstrate that the proposed MME can detect the abnormally overheating cell as well as quickly detect that an abnormal overheating event occurred in the battery string.

  12. Detection and diagnosis of abnormal transients in nuclear power plants

    SciTech Connect

    Lee, J.C.; Rank, P.J.; Hawkes, E.; Wehe, D.K. . Dept. of Nuclear Engineering); Reifman, J. )

    1991-01-01

    This document describes a simulation-based algorithm that combines fuzzy logic with macroscopic conservation equations to diagnose multiple-failure events subject to uncertainties in transient data. Clusters of single-failure data points of similar characteristics are obtained through a pattern recognition algorithm and the cluster centers are combined in the space of macroscopic inventory derivatives to generate multiple-failure cluster centers. A fuzzy membership function is used to represent the likelihood of a data point belonging to a cluster, and failure estimates are obtained through solution of a fuzzy matrix equation. The algorithm has been successful in detecting simulated malfunctions in the pressurizer of a pressurized water reactor. 11 refs., 9 figs., 1 tab.

  13. Phase-Space Detection of Cyber Events

    SciTech Connect

    Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J; Hively, Lee M

    2015-01-01

    Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The data analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.

  14. WCEDS: A waveform correlation event detection system

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Trujillo, J.R.; Withers, M.M.; Aster, R.C.; Astiz, L.; Shearer, P.M.

    1995-08-01

    We have developed a working prototype of a grid-based global event detection system based on waveform correlation. The algorithm comes from a long-period detector but we have recast it in a full matrix formulation which can reduce the number of multiplications needed by better than two orders of magnitude for realistic monitoring scenarios. The reduction is made possible by eliminating redundant multiplications in the original formulation. All unique correlations for a given origin time are stored in a correlation matrix (C) which is formed by a full matrix product of a Master Image matrix (M) and a data matrix (D). The detector value at each grid point is calculated by following a different summation path through the correlation matrix. Master Images can be derived either empirically or synthetically. Our testing has used synthetic Master Images because their influence on the detector is easier to understand. We tested the system using the matrix formulation with continuous data from the IRIS (Incorporate Research Institutes for Seismology) broadband global network to monitor a 2 degree evenly spaced surface grid with a time discretization of 1 sps; we successfully detected the largest event in a two hour segment from October 1993. The output at the correct gridpoint was at least 33% larger than at adjacent grid points, and the output at the correct gridpoint at the correct origin time was more than 500% larger than the output at the same gridpoint immediately before or after. Analysis of the C matrix for the origin time of the event demonstrates that there are many significant ``false`` correlations of observed phases with incorrect predicted phases. These false correlations dull the sensitivity of the detector and so must be dealt with if our system is to attain detection thresholds consistent with a Comprehensive Test Ban Treaty (CTBT).

  15. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    DOE PAGES

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; ...

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events thatmore » generated the phase picks.« less

  16. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    SciTech Connect

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events that generated the phase picks.

  17. Meteorological aspects of an abnormal cooling event over Iran in April 2009

    NASA Astrophysics Data System (ADS)

    Soltani, M.; Babu, C. A.; Mofidi, A.

    2014-04-01

    During the period from 12 to 15 April, 2009 nearly the entire Iran, apart from the southern border, experienced an advective cooling event. While winter freezing concerns are typical, the nature of this freezing event was unusual with respect to its date of occurrence and accompanying synoptic meteorological situation. To analyze the freezing event, the relevant meteorological data at multiple levels of the atmosphere were examined from the NCEP/NCAR reanalysis dataset. The results showed that a polar vortex was responsible for the freezing event over the country extending southward extraordinarily in such a way that its ridge influenced most parts of Iran. This was recognized as an abnormal extension of a polar vortex in the recent years. The sea-level pressure fields indicated that a ridge of large-scale anticyclone centered over Black Sea extended southward and prevailed over most parts of Iran. This resulted in the formation of a severe cold air advection from high latitudes (Polar region) over Iran. During the study period, moisture pumping was observed from the Arabian Sea and Persian Gulf. The winds at 1000 hPa level blew with a magnitude of 10 m s-1 toward south in the region of convergence (between -2 × 10-6 s-1 and -12 × 10-6 s-1). The vertical profiles of temperature and humidity also indicated that the ICE structural icing occurred at multiple levels of the atmosphere, i.e, from 800 hPa through 400 hPa levels. In addition to the carburetor (or induction), icing occurred between 900 and 700 hPa levels in the selected radiosonde stations during the study period. In addition, the HYSPLIT backward trajectory model outputs were in quite good agreement with the observed synoptic features.

  18. Diagnostic evaluation of RNA sequencing for the detection of genetic abnormalities associated with Ph-like acute lymphoblastic leukemia (ALL).

    PubMed

    Yap, Kai Lee; Furtado, Larissa V; Kiyotani, Kazuma; Curran, Emily; Stock, Wendy; McNeer, Jennifer L; Kadri, Sabah; Segal, Jeremy P; Nakamura, Yusuke; Le Beau, Michelle M; Gurbuxani, Sandeep; Raca, Gordana

    2017-04-01

    Philadelphia (Ph)-like acute lymphoblastic leukemia (ALL) is a molecular subtype of high-risk B-cell ALL characterized by formation of abnormal gene fusions involving tyrosine kinase (TK) and cytokine receptor genes and activation of TK signaling. Because of the diversity of associated genetic changes, the detection of Ph-like ALL cases currently requires multiple cytogenetic and molecular assays; thus, our goal was to develop a consolidated workflow for detecting genetic abnormalities in Ph-like ALL. We found that total and targeted RNA sequencing (RNAseq)-based approach allowed the detection of abnormal fusion transcripts (EBF1-PDGFRB, P2RY8-CRLF2, RCSD1-ABL1, and RCSD1-ABL2). The bioinformatics algorithm accurately detected the fusion transcripts without prior input about possible events. Additionally, we showed that RNAseq analysis enabled evaluation for disease-associated sequence variants in expressed transcripts. While total RNAseq can be a second tier approach allowing discovery of novel genetic alterations, the targeted RNAseq workflow offers a clinically applicable method for the detection of fusion transcripts.

  19. Using State Estimation Residuals to Detect Abnormal SCADA Data

    SciTech Connect

    Ma, Jian; Chen, Yousu; Huang, Zhenyu; Wong, Pak C.

    2010-06-14

    Detection of manipulated supervisory control and data acquisition (SCADA) data is critically important for the safe and secure operation of modern power systems. In this paper, a methodology of detecting manipulated SCADA data based on state estimation residuals is presented. A framework of the proposed methodology is described. Instead of using original SCADA measurements as the bad data sources, the residuals calculated based on the results of the state estimator are used as the input for the outlier detection process. The BACON algorithm is applied to detect outliers in the state estimation residuals. The IEEE 118-bus system is used as a test case to evaluate the effectiveness of the proposed methodology. The accuracy of the BACON method is compared with that of the 3-σ method for the simulated SCADA measurements and residuals.

  20. Abnormal spatiotemporal processing of emotional facial expressions in childhood autism: dipole source analysis of event-related potentials.

    PubMed

    Wong, Teresa K W; Fung, Peter C W; Chua, Siew E; McAlonan, Grainne M

    2008-07-01

    Previous studies of face processing in autism suggest abnormalities in anatomical development, functioning and connectivity/coordination of distributed brain systems involved in social cognition, but the spatial sequence and time course of rapid (sub-second) neural responses to emotional facial expressions have not been examined in detail. Source analysis of high-density event-related potentials (ERPs) is an optimal means to examine both the precise temporal profile and spatial location of early electrical brain activity in response to emotionally salient stimuli. Therefore, we recorded 128-channel ERPs from high-functioning males with autism (aged 6-10 years), and age-, sex- and IQ-matched typically developing controls during explicit and implicit processing of emotion from pictures showing happy, angry, fearful, sad and neutral facial expressions. Children with autism showed normal patterns of behavioural and ERP (P1, N170 and P2) responses. However, dipole source analysis revealed that ERP responses relating to face detection (visual cortex) and configural processing of faces (fusiform gyrus), as well as mental state decoding (medial prefrontal lobe), were significantly weaker and/or slower in autism compared with controls during both explicit and implicit emotion-processing tasks. Slower- and larger-amplitude ERP source activity in the parietal somatosensory cortices possibly reflected more effortful compensatory analytical strategies used by the autism group to process facial gender and emotion. Such aberrant neurophysiological processing of facial emotion observed in children with autism within the first 300 ms of stimulus presentation suggests abnormal cortical specialization within social brain networks, which would likely disrupt the development of normal social-cognitive skills.

  1. Parental decisions of prenatally detected sex chromosome abnormality.

    PubMed Central

    Kim, Yon-Ju; Park, So-Yeon; Han, Jung-Heol; Kim, Moon-Young; Yang, Jae-Hyug; Choi, Kyu-Hong; Kim, Young-Mi; Kim, Jin-Mee; Ryu, Hyun-Mee

    2002-01-01

    Because of the widespread use of amniocentesis, the prenatal recognition of sex chromosome abnormality (SCA) has become increasingly common. Recent literature provided an insight into the understanding of the natural history and prognosis for individuals with SCA. Our study was designed to review the parental decision on pregnancy with SCA. Over the last 10 yr, we diagnosed 38 cases (0.50%) with SCA out of 7,498 prenatal cases. We reviewed the records and the results of the pregnancies. We included the cases (n=25) of apparently normal anatomic fetus to analyze the factors influencing parental decision. We excluded 13 cases with obvious anomaly or presumably bad outcome. Fifteen (60%) couples continued their pregnancies and ten (40%) terminated theirs. Nine couples (64%) out of fourteen mosaicism cases continued their pregnancies. All five pregnancies assisted by reproductive technique continued their pregnancies. More pregnancies were continued when counseling was done by an MD geneticist rather than by an obstetrician. A significant trend was observed with a higher rate of pregnancy continuation in recent years. The genetic counseling is important to give appropriate information to the parents. Establishing guidelines and protocols will help both obstetricians and parents to make a decision. PMID:11850589

  2. Detecting seismic events using Benford's Law

    NASA Astrophysics Data System (ADS)

    Diaz, Jordi; Gallart, Josep; Ruiz, Mario

    2015-04-01

    The Benford's Law (BL) states that the distribution of first significant digits is not uniform but follows a logarithmic frequency distribution. Even if a remarkable wide range of natural and socioeconomical data sets, from stock market values to quantum phase transitions, fit this peculiar law, the conformity to it has deserved few scientific applications, being used mainly as a test to pinpoint anomalous or fraudulent data. We developed a procedure to detect the arrival of seismic waves based on the degree of conformity of the amplitude values in the raw seismic trace to the BL. The signal is divided in time windows of appropriate length and the fitting of the first digits distribution to BL is checked in each time window using a conformity estimator. We document that both teleseismic and local earthquakes can be clearly identified in this procedure and we compare its performance with respect to the classical STA/LTA approach. Moreover, we show that the conformity of the seismic record to the BL does not depend on the amplitude of the incoming series, as the occurrence of events with very different amplitudes result in quite similar degree of BL fitting. On the other hand, we show that natural or man-made quasi-monochromatic seismic signals, surface wave trains or engine-generated vibrations can be identified through their very low BL estimator values, when appropriate interval lengths are used. Therefore, we conclude that the degree of conformity of a seismic signal with the BL is primarily dependent on the frequency content of that signal.

  3. Method of detecting genetic deletions identified with chromosomal abnormalities

    DOEpatents

    Gray, Joe W; Pinkel, Daniel; Tkachuk, Douglas

    2013-11-26

    Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyzes. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acids probes are typically of a complexity greater tha 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particlularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar ut genetically different diseases, and for many prognostic and diagnostic applications.

  4. Method of detecting genetic translocations identified with chromosomal abnormalities

    DOEpatents

    Gray, Joe W.; Pinkel, Daniel; Tkachuk, Douglas

    2001-01-01

    Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyses. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acid probes are typically of a complexity greater than 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar but genetically different diseases, and for many prognostic and diagnostic applications.

  5. Noninvasive detection of fetal subchromosomal abnormalities by semiconductor sequencing of maternal plasma DNA

    PubMed Central

    Yin, Ai-hua; Peng, Chun-fang; Zhao, Xin; Caughey, Bennett A.; Yang, Jie-xia; Liu, Jian; Huang, Wei-wei; Liu, Chang; Luo, Dong-hong; Liu, Hai-liang; Chen, Yang-yi; Wu, Jing; Hou, Rui; Zhang, Mindy; Ai, Michael; Zheng, Lianghong; Xue, Rachel Q.; Mai, Ming-qin; Guo, Fang-fang; Qi, Yi-ming; Wang, Dong-mei; Krawczyk, Michal; Zhang, Daniel; Wang, Yu-nan; Huang, Quan-fei; Karin, Michael; Zhang, Kang

    2015-01-01

    Noninvasive prenatal testing (NIPT) using sequencing of fetal cell-free DNA from maternal plasma has enabled accurate prenatal diagnosis of aneuploidy and become increasingly accepted in clinical practice. We investigated whether NIPT using semiconductor sequencing platform (SSP) could reliably detect subchromosomal deletions/duplications in women carrying high-risk fetuses. We first showed that increasing concentration of abnormal DNA and sequencing depth improved detection. Subsequently, we analyzed plasma from 1,456 pregnant women to develop a method for estimating fetal DNA concentration based on the size distribution of DNA fragments. Finally, we collected plasma from 1,476 pregnant women with fetal structural abnormalities detected on ultrasound who also underwent an invasive diagnostic procedure. We used SSP of maternal plasma DNA to detect subchromosomal abnormalities and validated our results with array comparative genomic hybridization (aCGH). With 3.5 million reads, SSP detected 56 of 78 (71.8%) subchromosomal abnormalities detected by aCGH. With increased sequencing depth up to 10 million reads and restriction of the size of abnormalities to more than 1 Mb, sensitivity improved to 69 of 73 (94.5%). Of 55 false-positive samples, 35 were caused by deletions/duplications present in maternal DNA, indicating the necessity of a validation test to exclude maternal karyotype abnormalities. This study shows that detection of fetal subchromosomal abnormalities is a viable extension of NIPT based on SSP. Although we focused on the application of cell-free DNA sequencing for NIPT, we believe that this method has broader applications for genetic diagnosis, such as analysis of circulating tumor DNA for detection of cancer. PMID:26554006

  6. Noninvasive detection of fetal subchromosomal abnormalities by semiconductor sequencing of maternal plasma DNA.

    PubMed

    Yin, Ai-hua; Peng, Chun-fang; Zhao, Xin; Caughey, Bennett A; Yang, Jie-xia; Liu, Jian; Huang, Wei-wei; Liu, Chang; Luo, Dong-hong; Liu, Hai-liang; Chen, Yang-yi; Wu, Jing; Hou, Rui; Zhang, Mindy; Ai, Michael; Zheng, Lianghong; Xue, Rachel Q; Mai, Ming-qin; Guo, Fang-fang; Qi, Yi-ming; Wang, Dong-mei; Krawczyk, Michal; Zhang, Daniel; Wang, Yu-nan; Huang, Quan-fei; Karin, Michael; Zhang, Kang

    2015-11-24

    Noninvasive prenatal testing (NIPT) using sequencing of fetal cell-free DNA from maternal plasma has enabled accurate prenatal diagnosis of aneuploidy and become increasingly accepted in clinical practice. We investigated whether NIPT using semiconductor sequencing platform (SSP) could reliably detect subchromosomal deletions/duplications in women carrying high-risk fetuses. We first showed that increasing concentration of abnormal DNA and sequencing depth improved detection. Subsequently, we analyzed plasma from 1,456 pregnant women to develop a method for estimating fetal DNA concentration based on the size distribution of DNA fragments. Finally, we collected plasma from 1,476 pregnant women with fetal structural abnormalities detected on ultrasound who also underwent an invasive diagnostic procedure. We used SSP of maternal plasma DNA to detect subchromosomal abnormalities and validated our results with array comparative genomic hybridization (aCGH). With 3.5 million reads, SSP detected 56 of 78 (71.8%) subchromosomal abnormalities detected by aCGH. With increased sequencing depth up to 10 million reads and restriction of the size of abnormalities to more than 1 Mb, sensitivity improved to 69 of 73 (94.5%). Of 55 false-positive samples, 35 were caused by deletions/duplications present in maternal DNA, indicating the necessity of a validation test to exclude maternal karyotype abnormalities. This study shows that detection of fetal subchromosomal abnormalities is a viable extension of NIPT based on SSP. Although we focused on the application of cell-free DNA sequencing for NIPT, we believe that this method has broader applications for genetic diagnosis, such as analysis of circulating tumor DNA for detection of cancer.

  7. A Unified Framework for Event Summarization and Rare Event Detection from Multiple Views.

    PubMed

    Kwon, Junseok; Lee, Kyoung Mu

    2015-09-01

    A novel approach for event summarization and rare event detection is proposed. Unlike conventional methods that deal with event summarization and rare event detection independently, our method solves them in a single framework by transforming them into a graph editing problem. In our approach, a video is represented by a graph, each node of which indicates an event obtained by segmenting the video spatially and temporally. The edges between nodes describe the relationship between events. Based on the degree of relations, edges have different weights. After learning the graph structure, our method finds subgraphs that represent event summarization and rare events in the video by editing the graph, that is, merging its subgraphs or pruning its edges. The graph is edited to minimize a predefined energy model with the Markov Chain Monte Carlo (MCMC) method. The energy model consists of several parameters that represent the causality, frequency, and significance of events. We design a specific energy model that uses these parameters to satisfy each objective of event summarization and rare event detection. The proposed method is extended to obtain event summarization and rare event detection results across multiple videos captured from multiple views. For this purpose, the proposed method independently learns and edits each graph of individual videos for event summarization or rare event detection. Then, the method matches the extracted multiple graphs to each other, and constructs a single composite graph that represents event summarization or rare events from multiple views. Experimental results show that the proposed approach accurately summarizes multiple videos in a fully unsupervised manner. Moreover, the experiments demonstrate that the approach is advantageous in detecting rare transition of events.

  8. GABAergic influences on ORX receptor-dependent abnormal motor behaviors and neurodegenerative events in fish.

    PubMed

    Facciolo, Rosa Maria; Crudo, Michele; Giusi, Giuseppina; Canonaco, Marcello

    2010-02-15

    At date the major neuroreceptors i.e. gamma-aminobutyric acid(A) (GABA(A)R) and orexin (ORXR) systems are beginning to be linked to homeostasis, neuroendocrine and emotional states. In this study, intraperitoneal treatment of the marine teleost Thalassoma pavo with the highly selective GABA(A)R agonist (muscimol, MUS; 0.1 microg/g body weight) and/or its antagonist bicuculline (BIC; 1 microg/g body weight) have corroborated a GABA(A)ergic role on motor behaviors. In particular, MUS induced moderate (p<0.05) and great (p<0.01) increases of swimming towards food sources and resting states after 24 (1 dose) and 96 (4 doses) h treatment sessions, respectively, when compared to controls. Conversely, BIC caused a very strong (p<0.001) reduction of the former behavior and in some cases convulsive swimming. From the correlation of BIC-dependent behavioral changes to neuronal morphological and ORXR transcriptional variations, it appeared that the disinhibitory action of GABA(A)R was very likely responsible for very strong and strong ORXR mRNA reductions in cerebellum valvula and torus longitudinalis, respectively. Moreover these effects were linked to evident ultra-structural changes such as shrunken cell membranes and loss of cytoplasmic architecture. In contrast, MUS supplied a very low, if any, argyrophilic reaction in hypothalamic and mesencephalic regions plus a scarce level of ultra-structural damages. Interestingly, combined administrations of MUS+BIC were not related to consistent damages, aside mild neuronal alterations in motor-related areas such as optic tectum. Overall it is tempting to suggest, for the first time, a neuroprotective role of GABA(A)R inhibitory actions against the overexcitatory ORXR-dependent neurodegeneration and consequently abnormal swimming events in fish.

  9. Optical and electrical observations of an abnormal triggered lightning event with two upward propagations

    NASA Astrophysics Data System (ADS)

    Zheng, Dong; Zhang, Yijun; Lu, Weitao; Zhang, Yang; Dong, Wansheng; Chen, Shaodong; Dan, Jianru

    2012-08-01

    This study investigates an abnormal artificially triggered lightning event that produced two positive upward propagations: one during the initial stage (i.e., the upward leader (UL)) and the other after a negative downward aborted leader (DAL). The triggered lightning was induced in a weak thunderstorm over the experiment site and did not produce a return stroke. All of the intra-cloud lightning around the experiment site produced positive changes in the electric field. The initial stage was a weak discharge process. A downward dart leader propagated along the channel produced by the first UL, ending at a height of approximately 453 m and forming a DAL. Under the influence of the DAL, the electric field at a point located 78 m from the rod experienced a steady reduction of about 6.8 kV m-1 over 5.24 ms prior to the initiation of a new upward channel (i.e., the second upward propagation (UP)). The second UP, which started approximately 4.1 ms after the termination of the DAL and propagated along the original channel, was triggered by the DAL and sustained for approximately 2.95 ms. Two distinct current pulses were superimposed on the current of the second UP. The first pulse, which was related to the sudden initiation of the second UP, was characterized by a more rapid increase and decrease and a larger peak value than the second pulse, which was related to the development of the second UP into the area affected by the DAL. The second UP contained both a similar-to-leader process and a following neutralization process. This study introduces a new type of triggering leader, in which a new upward discharge is triggered in an established channel by an aborted leader propagating along the same channel with opposite polarity and propagation direction.

  10. GABAergic influences on ORX receptor-dependent abnormal motor behaviors and neurodegenerative events in fish

    SciTech Connect

    Facciolo, Rosa Maria; Crudo, Michele; Giusi, Giuseppina; Canonaco, Marcello

    2010-02-15

    At date the major neuroreceptors i.e. gamma-aminobutyric acid{sub A} (GABA{sub A}R) and orexin (ORXR) systems are beginning to be linked to homeostasis, neuroendocrine and emotional states. In this study, intraperitoneal treatment of the marine teleost Thalassoma pavo with the highly selective GABA{sub A}R agonist (muscimol, MUS; 0,1 mug/g body weight) and/or its antagonist bicuculline (BIC; 1 mug/g body weight) have corroborated a GABA{sub A}ergic role on motor behaviors. In particular, MUS induced moderate (p < 0.05) and great (p < 0.01) increases of swimming towards food sources and resting states after 24 (1 dose) and 96 (4 doses) h treatment sessions, respectively, when compared to controls. Conversely, BIC caused a very strong (p < 0.001) reduction of the former behavior and in some cases convulsive swimming. From the correlation of BIC-dependent behavioral changes to neuronal morphological and ORXR transcriptional variations, it appeared that the disinhibitory action of GABA{sub A}R was very likely responsible for very strong and strong ORXR mRNA reductions in cerebellum valvula and torus longitudinalis, respectively. Moreover these effects were linked to evident ultra-structural changes such as shrunken cell membranes and loss of cytoplasmic architecture. In contrast, MUS supplied a very low, if any, argyrophilic reaction in hypothalamic and mesencephalic regions plus a scarce level of ultra-structural damages. Interestingly, combined administrations of MUS + BIC were not related to consistent damages, aside mild neuronal alterations in motor-related areas such as optic tectum. Overall it is tempting to suggest, for the first time, a neuroprotective role of GABA{sub A}R inhibitory actions against the overexcitatory ORXR-dependent neurodegeneration and consequently abnormal swimming events in fish.

  11. Volume-based features for detection of bladder wall abnormal regions via MR cystography.

    PubMed

    Duan, Chaijie; Yuan, Kehong; Liu, Fanghua; Xiao, Ping; Lv, Guoqing; Liang, Zhengrong

    2011-09-01

    This paper proposes a framework for detecting the suspected abnormal region of the bladder wall via magnetic resonance (MR) cystography. Volume-based features are used. First, the bladder wall is divided into several layers, based on which a path from each voxel on the inner border to the outer border is found. By using the path length to measure the wall thickness and a bent rate (BR) term to measure the geometry property of the voxels on the inner border, the seed voxels representing the abnormalities on the inner border are determined. Then, by tracing the path from each seed, a weighted BR term is constructed to determine the suspected voxels, which are on the path and inside the bladder wall. All the suspected voxels are grouped together for the abnormal region. This work is significantly different from most of the previous computer-aided bladder tumor detection reports on two aspects. First of all, the T (1)-weighted MR images are used which give better image contrast and texture information for the bladder wall, comparing with the computed tomography images. Second, while most previous reports detected the abnormalities and indicated them on the reconstructed 3-D bladder model by surface rendering, we further determine the possible region of the abnormality inside the bladder wall. This study aims at a noninvasive procedure for bladder tumor detection and abnormal region delineation, which has the potential for further clinical analysis such as the invasion depth of the tumor and virtual cystoscopy diagnosis. Five datasets including two patients and three volunteers were used to test the presented method, all the tumors were detected by the method, and the overlap rates of the regions delineated by the computer against the experts were measured. The results demonstrated the potential of the method for detecting bladder wall abnormal regions via MR cystography.

  12. Robust event detection scheme for complex scenes in video surveillance

    NASA Astrophysics Data System (ADS)

    Chen, Erkang; Xu, Yi; Yang, Xiaokang; Zhang, Wenjun

    2011-07-01

    Event detection for video surveillance is a difficult task due to many challenges: cluttered background, illumination variations, scale variations, occlusions among people, etc. We propose an effective and efficient event detection scheme in such complex situations. Moving shadows due to illumination are tackled with a segmentation method with shadow detection, and scale variations are taken care of using the CamShift guided particle filter tracking algorithm. For event modeling, hidden Markov models are employed. The proposed scheme also reduces the overall computational cost by combing two human detection algorithms and using tracking information to aid human detection. Experimental results on TRECVid event detection evaluation demonstrate the efficacy of the proposed scheme. It is robust, especially to moving shadows and scale variations. Employing the scheme, we achieved the best run results for two events in the TRECVid benchmarking evaluation.

  13. Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

    NASA Astrophysics Data System (ADS)

    Al Azzawi, Dia

    Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

  14. Optimizing Detection Rate and Characterization of Subtle Paroxysmal Neonatal Abnormal Facial Movements with Multi-Camera Video-Electroencephalogram Recordings.

    PubMed

    Pisani, Francesco; Pavlidis, Elena; Cattani, Luca; Ferrari, Gianluigi; Raheli, Riccardo; Spagnoli, Carlotta

    2016-06-01

    Objectives We retrospectively analyze the diagnostic accuracy for paroxysmal abnormal facial movements, comparing one camera versus multi-camera approach. Background Polygraphic video-electroencephalogram (vEEG) recording is the current gold standard for brain monitoring in high-risk newborns, especially when neonatal seizures are suspected. One camera synchronized with the EEG is commonly used. Methods Since mid-June 2012, we have started using multiple cameras, one of which point toward newborns' faces. We evaluated vEEGs recorded in newborns in the study period between mid-June 2012 and the end of September 2014 and compared, for each recording, the diagnostic accuracies obtained with one-camera and multi-camera approaches. Results We recorded 147 vEEGs from 87 newborns and found 73 episodes of paroxysmal facial abnormal movements in 18 vEEGs of 11 newborns with the multi-camera approach. By using the single-camera approach, only 28.8% of these events were identified (21/73). Ten positive vEEGs with multicamera with 52 paroxysmal facial abnormal movements (52/73, 71.2%) would have been considered as negative with the single-camera approach. Conclusions The use of one additional facial camera can significantly increase the diagnostic accuracy of vEEGs in the detection of paroxysmal abnormal facial movements in the newborns.

  15. Incidental vesicoureteral reflux in neonates with antenatally detected hydronephrosis and other renal abnormalities.

    PubMed

    Zerin, J M; Ritchey, M L; Chang, A C

    1993-04-01

    Postnatal imaging findings were reviewed in 130 neonates and young infants referred for imaging evaluation of antenatally detected renal abnormalities. All children underwent voiding cystourethrography and upper urinary tract imaging with sonography and/or renal scintigraphy. Vesicoureteral reflux was present in 49 patients (38%) and was bilateral in 24. All grades of reflux were observed. Reflux occurred in 41 of 98 neonates (42%) in whom postnatal imaging revealed persistent upper tract abnormalities (eg, hydronephrosis, cysts, renal agenesis) and in eight of 32 (25%) with normal findings at postnatal sonography and/or renal scintigraphy. Reflux was the single most common urologic diagnosis and was the only postnatal abnormality in 12 patients (9%). The authors conclude that neonates with antenatally detected hydronephrosis should be routinely screened for reflux with voiding cystography. Detection and aggressive management of reflux in the asymptomatic neonate in whom renal growth and function are unimpaired theoretically offer the best opportunity for preventing renal injury later in childhood.

  16. Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.

    PubMed

    Zhang, Yudong; Ji, Genlin; Yang, Jiquan; Wang, Shuihua; Dong, Zhengchao; Phillips, Preetha; Sun, Ping

    2016-04-29

    It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal detection, and reported its preliminary results in this study. The kernel support vector machine (KSVM) was used as the classifier, and quantum-behaved particle swarm optimization (QPSO) was introduced to optimize the weights of the SVM. The results based on a 5 × 5-fold cross validation showed the performance of the proposed WE + QPSO-KSVM was superior to ``DWT + PCA + BP-NN'', ``DWT + PCA + RBF-NN'', ``DWT + PCA + PSO-KSVM'', ``WE + BPNN'', ``WE +$ KSVM'', and ``DWT $+$ PCA $+$ GA-KSVM'' w.r.t. sensitivity, specificity, and accuracy. The work provides a novel means to detect abnormal brains with excellent performance.

  17. Detection of chromosomal abnormalities and the 22q11 microdeletion in fetuses with congenital heart defects.

    PubMed

    Lv, Wei; Wang, Shuyu

    2014-11-01

    Chromosomal abnormalities and the 22q11 microdeletion are implicated in congenital heart defects (CHDs). This study was designed to detect these abnormalities in fetuses and determine the effect of genetic factors on CHD etiology. Between January 2010 and December 2011, 113 fetuses with CHD treated at the Beijing Obstetrics and Gynecology Hospital were investigated, using chromosome karyotyping of either amniotic fluid cell or umbilical cord blood cell samples. Fetuses with a normal result were then investigated for the 22q11 microdeletion by fluorescence in situ hybridization. Of the 113 patients, 12 (10.6%) exhibited chromosomal abnormalities, while 6 (5.3%) of the remaining 101 cases presented with a 22q11 microdeletion. The incidence of chromosomal abnormalities was significantly higher in the group of fetuses presenting with extracardiac malformations in addition to CHD (P<0.001), although the detection of the 22q11 microdeletion was not significantly different between the two groups (P=0.583). In addition, all fetuses with the 22q11 microdeletion occurred de novo. In conclusion, genetic factors are important in the etiology of CHD. Where fetuses present with cardiac defects, additional chromosomal analysis is required to detect extracardiac abnormalities. Fetuses with heart defects should also be considered for 22q11 microdeletion detection to evaluate fetal prognosis, particularly prior to surgery.

  18. Detecting plastic events in emulsions simulations

    NASA Astrophysics Data System (ADS)

    Lulli, Matteo; Matteo Lulli, Massimo Bernaschi, Mauro Sbragaglia Team

    2016-11-01

    Emulsions are complex systems which are formed by a number of non-coalescing droplets dispersed in a solvent leading to non-trivial effects in the overall flowing dynamics. Such systems possess a yield stress below which an elastic response to an external forcing occurs, while above the yield stress the system flows as a non-Newtonian fluid, i.e. the stress is not proportional to the shear. In the solid-like regime the network of the droplets interfaces stores the energy coming from the work exerted by an external forcing, which can be used to move the droplets in a non-reversible way, i.e. causing plastic events. The Kinetic-Elasto-Plastic (KEP) theory is an effective theory describing some features of the flowing regime relating the rate of plastic events to a scalar field called fluidity f =γ˙/σ , i.e. the inverse of an effective viscosity. Boundary conditions have a non-trivial role not captured by the KEP description. In this contribution we will compare numerical results against experiments concerning the Poiseuille flow of emulsions in microchannels with complex boundary geometries. Using an efficient computational tool we can show non-trivial results on plastic events for different realizations of the rough boundaries. The research leading to these results has received funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007- 2013)/ERC Grant Agreement no. [279004].

  19. Test and analysis on the abnormal noise of the ultrasonic detection device

    NASA Astrophysics Data System (ADS)

    Li, Guangya; Yang, Mingliang; Wang, Mingquan; Tan, Qiulin; Duan, Nengquan

    2014-03-01

    For the phenomenon that the abnormal noise appear suddenly when the ultrasonic detection device works at the rate of 800mm/min, a vibration testing for this detection device is designed and investigated in this paper. Deep analysis are carried out based on the experimental modal analysis method of point excitation with multiple point three vectors in response and spectrum analysis method. The analysis results demonstrate the main reasons of the abnormal noise, which is due to the resonance between the motor and the ultrasonic station.

  20. Abnormal contextual modulation of visual contour detection in patients with schizophrenia.

    PubMed

    Schallmo, Michael-Paul; Sponheim, Scott R; Olman, Cheryl A

    2013-01-01

    Schizophrenia patients demonstrate perceptual deficits consistent with broad dysfunction in visual context processing. These include poor integration of segments forming visual contours, and reduced visual contrast effects (e.g. weaker orientation-dependent surround suppression, ODSS). Background image context can influence contour perception, as stimuli near the contour affect detection accuracy. Because of ODSS, this contextual modulation depends on the relative orientation between the contour and flanking elements, with parallel flankers impairing contour perception. However in schizophrenia, the impact of abnormal ODSS during contour perception is not clear. It is also unknown whether deficient contour perception marks genetic liability for schizophrenia, or is strictly associated with clinical expression of this disorder. We examined contour detection in 25 adults with schizophrenia, 13 unaffected first-degree biological relatives of schizophrenia patients, and 28 healthy controls. Subjects performed a psychophysics experiment designed to quantify the effect of flanker orientation during contour detection. Overall, patients with schizophrenia showed poorer contour detection performance than relatives or controls. Parallel flankers suppressed and orthogonal flankers enhanced contour detection performance for all groups, but parallel suppression was relatively weaker for schizophrenia patients than healthy controls. Relatives of patients showed equivalent performance with controls. Computational modeling suggested that abnormal contextual modulation in schizophrenia may be explained by suppression that is more broadly tuned for orientation. Abnormal flanker suppression in schizophrenia is consistent with weaker ODSS and/or broader orientation tuning. This work provides the first evidence that such perceptual abnormalities may not be associated with a genetic liability for schizophrenia.

  1. Subsurface Event Detection and Classification Using Wireless Signal Networks

    PubMed Central

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

    2012-01-01

    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. PMID:23202191

  2. Global Seismic Event Detection Using Surface Waves: 15 Possible Antarctic Glacial Sliding Events

    NASA Astrophysics Data System (ADS)

    Chen, X.; Shearer, P. M.; Walker, K. T.; Fricker, H. A.

    2008-12-01

    To identify overlooked or anomalous seismic events not listed in standard catalogs, we have developed an algorithm to detect and locate global seismic events using intermediate-period (35-70s) surface waves. We apply our method to continuous vertical-component seismograms from the global seismic networks as archived in the IRIS UV FARM database from 1997 to 2007. We first bandpass filter the seismograms, apply automatic gain control, and compute envelope functions. We then examine 1654 target event locations defined at 5 degree intervals and stack the seismogram envelopes along the predicted Rayleigh-wave travel times. The resulting function has spatial and temporal peaks that indicate possible seismic events. We visually check these peaks using a graphical user interface to eliminate artifacts and assign an overall reliability grade (A, B or C) to the new events. We detect 78% of events in the Global Centroid Moment Tensor (CMT) catalog. However, we also find 840 new events not listed in the PDE, ISC and REB catalogs. Many of these new events were previously identified by Ekstrom (2006) using a different Rayleigh-wave detection scheme. Most of these new events are located along oceanic ridges and transform faults. Some new events can be associated with volcanic eruptions such as the 2000 Miyakejima sequence near Japan and others with apparent glacial sliding events in Greenland (Ekstrom et al., 2003). We focus our attention on 15 events detected from near the Antarctic coastline and relocate them using a cross-correlation approach. The events occur in 3 groups which are well-separated from areas of cataloged earthquake activity. We speculate that these are iceberg calving and/or glacial sliding events, and hope to test this by inverting for their source mechanisms and examining remote sensing data from their source regions.

  3. Myocardial perfusion abnormality in the area of ventricular septum-free wall junction and cardiovascular events in nonobstructive hypertrophic cardiomyopathy.

    PubMed

    Kaimoto, Satoshi; Kawasaki, Tatsuya; Kuribayashi, Toshiro; Yamano, Michiyo; Miki, Shigeyuki; Kamitani, Tadaaki; Matsubara, Hiroaki

    2012-10-01

    Myocardial perfusion abnormality in the left ventricle is known to be prognostic in patients with hypertrophic cardiomyopathy (HCM). Magnetic resonance imaging and necropsy studies on HCM hearts revealed myocardial lesions predominating in the area of ventricular septum-free wall junction. We assessed perfusion abnormality in this area and correlated it with the prognosis of HCM patients. We performed exercise Tc-99m tetrofosmin myocardial scintigraphy in 55 patients with nonobstructive HCM. Perfusion abnormalities were semiquantified using a 5-point scoring system in small areas of anterior junctions of basal, mid, and apical short axis views in addition to a conventional 17-segment model. All patients were prospectively followed for sudden death, cardiovascular death and hospitalization for heart failure or stroke associated with atrial fibrillation. Cardiovascular events occurred in 10 patients during an average follow-up period of 5.7 years. Stress and rest scores from anterior junction, and conventional summed stress score were significantly higher in patients with cardiovascular events than without (all P < 0.05). Anterior junction stress score of >2 produced a sensitivity of 50% and a specificity of 98% for cardiovascular events and was an independent predictor (hazard ratio 8.33; 95% confidence interval, 1.61-43.5; P = 0.01), with rest scores producing similar values, which were higher than summed stress score of >8 (5.68; 1.23-26.3; P = 0.03). The absence of myocardial perfusion abnormality in the narrow area of anterior junction differentiated HCM patients with low-risk.

  4. Event Detection using Twitter: A Spatio-Temporal Approach

    PubMed Central

    Cheng, Tao; Wicks, Thomas

    2014-01-01

    Background Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor. Methods This paper suggests an alternative methodology for event detection using space-time scan statistics (STSS). This technique looks for clusters within the dataset across both space and time, regardless of tweet content. It is expected that clusters of tweets will emerge during spatio-temporally relevant events, as people will tweet more than expected in order to describe the event and spread information. The special event used as a case study is the 2013 London helicopter crash. Results and Conclusion A spatio-temporally significant cluster is found relating to the London helicopter crash. Although the cluster only remains significant for a relatively short time, it is rich in information, such as important key words and photographs. The method also detects other special events such as football matches, as well as train and flight delays from Twitter data. These findings demonstrate that STSS is an effective approach to analysing Twitter data for event detection. PMID:24893168

  5. Abnormal Image Detection in Endoscopy Videos Using a Filter Bank and Local Binary Patterns.

    PubMed

    Nawarathna, Ruwan; Oh, JungHwan; Muthukudage, Jayantha; Tavanapong, Wallapak; Wong, Johnny; de Groen, Piet C; Tang, Shou Jiang

    2014-11-20

    Finding mucosal abnormalities (e.g., erythema, blood, ulcer, erosion, and polyp) is one of the most essential tasks during endoscopy video review. Since these abnormalities typically appear in a small number of frames (around 5% of the total frame number), automated detection of frames with an abnormality can save physician's time significantly. In this paper, we propose a new multi-texture analysis method that effectively discerns images showing mucosal abnormalities from the ones without any abnormality since most abnormalities in endoscopy images have textures that are clearly distinguishable from normal textures using an advanced image texture analysis method. The method uses a "texton histogram" of an image block as features. The histogram captures the distribution of different "textons" representing various textures in an endoscopy image. The textons are representative response vectors of an application of a combination of Leung and Malik (LM) filter bank (i.e., a set of image filters) and a set of Local Binary Patterns on the image. Our experimental results indicate that the proposed method achieves 92% recall and 91.8% specificity on wireless capsule endoscopy (WCE) images and 91% recall and 90.8% specificity on colonoscopy images.

  6. Detection of Cardiac Function Abnormality from MRI Images Using Normalized Wall Thickness Temporal Patterns.

    PubMed

    Wael, Mai; Ibrahim, El-Sayed H; Fahmy, Ahmed S

    2016-01-01

    Purpose. To develop a method for identifying abnormal myocardial function based on studying the normalized wall motion pattern during the cardiac cycle. Methods. The temporal pattern of the normalized myocardial wall thickness is used as a feature vector to assess the cardiac wall motion abnormality. Principal component analysis is used to reduce the feature dimensionality and the maximum likelihood method is used to differentiate between normal and abnormal features. The proposed method was applied on a dataset of 27 cases from normal subjects and patients. Results. The developed method achieved 81.5%, 85%, and 88.5% accuracy for identifying abnormal contractility in the basal, midventricular, and apical slices, respectively. Conclusions. A novel feature vector, namely, the normalized wall thickness, has been introduced for detecting myocardial regional wall motion abnormality. The proposed method provides assessment of the regional myocardial contractility for each cardiac segment and slice; therefore, it could be a valuable tool for automatic and fast determination of regional wall motion abnormality from conventional cine MRI images.

  7. Efficient method for events detection in phonocardiographic signals

    NASA Astrophysics Data System (ADS)

    Martinez-Alajarin, Juan; Ruiz-Merino, Ramon

    2005-06-01

    The auscultation of the heart is still the first basic analysis tool used to evaluate the functional state of the heart, as well as the first indicator used to submit the patient to a cardiologist. In order to improve the diagnosis capabilities of auscultation, signal processing algorithms are currently being developed to assist the physician at primary care centers for adult and pediatric population. A basic task for the diagnosis from the phonocardiogram is to detect the events (main and additional sounds, murmurs and clicks) present in the cardiac cycle. This is usually made by applying a threshold and detecting the events that are bigger than the threshold. However, this method usually does not allow the detection of the main sounds when additional sounds and murmurs exist, or it may join several events into a unique one. In this paper we present a reliable method to detect the events present in the phonocardiogram, even in the presence of heart murmurs or additional sounds. The method detects relative maxima peaks in the amplitude envelope of the phonocardiogram, and computes a set of parameters associated with each event. Finally, a set of characteristics is extracted from each event to aid in the identification of the events. Besides, the morphology of the murmurs is also detected, which aids in the differentiation of different diseases that can occur in the same temporal localization. The algorithms have been applied to real normal heart sounds and murmurs, achieving satisfactory results.

  8. Malaria detection with the Sysmex XE-2100 hematology analyzer using pseudoeosinophilia and abnormal WBC scattergram.

    PubMed

    Huh, Hee Jin; Oh, Gwi Young; Huh, Jung Won; Chae, Seok Lae

    2008-09-01

    Recent investigation using the Sysmex XE-2100 hematology analyzer (Sysmex Corporation, Japan) has demonstrated erroneously high eosinophil counts and abnormal white blood cell (WBC) scattergrams in malaria cases. This study was conducted to assess the diagnostic efficiency of the Sysmex XE-2100 analyzer for malaria. One hundred forty-four patients initially diagnosed with Plasmodium vivax infection, 319 patients with febrile illness, and 24 patients who underwent malaria treatment were analyzed. Atypical features on Sysmex XE-2100 analyzer were categorized as pseudoeosinophilia (a gap of more than 5% in eosinophil counts between the Sysmex XE-2100 analyzer and microscopic examination) and abnormal WBC scattergram. Pseudoeosinophilia or abnormal WBC scattergram were detected in 100 of 144 malaria-positive samples (sensitivity 69.4%, specificity 100%). The samples with pseudoeosinophilia or abnormal WBC scattergrams showed significantly higher parasite counts than the samples without pseudoeosinophilia or an abnormal WBC scattergram (P<0.05). All 24 samples from patients for whom the malaria smear was repeated after malaria treatment was initiated showed a normalized eosinophil count and a normal WBC histogram. In conclusion, attention to differential count and WBC scattergrams provided by the Sysmex XE-2100 would be a valuable tool in malaria detection.

  9. Video Event Detection Framework on Large-Scale Video Data

    ERIC Educational Resources Information Center

    Park, Dong-Jun

    2011-01-01

    Detection of events and actions in video entails substantial processing of very large, even open-ended, video streams. Video data present a unique challenge for the information retrieval community because properly representing video events is challenging. We propose a novel approach to analyze temporal aspects of video data. We consider video data…

  10. Frequency and patterns of abnormality detected by iodine-123 amine emission CT after cerebral infarction

    SciTech Connect

    Brott, T.G.; Gelfand, M.J.; Williams, C.C.; Spilker, J.A.; Hertzberg, V.S.

    1986-03-01

    Single photon emission computed tomography (SPECT) was performed in 31 patients with cerebral infarction and 13 who had had transient ischemic attacks, using iodine-123-labeled N,N,N'-trimethyl-N'-(2-hydroxyl-3-methyl-5-iodobenzyl)-1,3-propanediamin e (I-123-HIPDM) as the radiopharmaceutical. SPECT scans were compared with computed tomographic (CT) scans. SPECT was as sensitive as CT in detecting cerebral infarction (94% vs. 84%). The abnormalities were larger on the SPECT scans than on the CT scans in 19 cases, equal in seven, and smaller in five (SPECT abnormalities greater than or equal to CT abnormalities in 86% of cases). Fifteen of 30 patients with hemispheric infarction had decreased perfusion (decreased uptake of I-123-HIPDM) to the cerebellar hemisphere contralateral to the cerebral hemisphere involved by the infarction (crossed cerebellar diaschisis). Nine of these 15 patients had major motor deficits, while only one of the 15 without crossed cerebellar diaschisis had a major motor deficit.

  11. ["PELVIC ABNORMALITIES" AT THE THE OSPEDALE MAGGIORE OF MILAN: HISTORY AND CURRENT EVENTS].

    PubMed

    Franchini, Antonia Francesca; Galimberti, Paolo Maria; Lorusso, Lorenzo; Falconi, Bruno; Reggiani, Flores; Vecchio, Laura; Porro, Alessandro

    2015-01-01

    The authors deal with the theme of the genesis and the increase of the obstetrical collection of pelvic abnormalities, i.e. the "dry" specimens stored at the Ospedale Maggiore (Major Hospital) of Milan (Italy), and of their scientific and educational values. Recently, following the restoration of the crypt of the Annunciation Church of the Ospedale Maggiore, a large space was converted, which could accommodate the pelvises collection permanently. A first step tofinally be able to introduce these extraordinary specimens not only to experts, but also to a wider audience.

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

    PubMed Central

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

    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 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. PMID:26694394

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

    PubMed

    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.

  14. Improving the Identification of Phenotypic Abnormalities and Sexual Dimorphism in Mice When Studying Rare Event Categorical Characteristics.

    PubMed

    Karp, Natasha A; Heller, Ruth; Yaacoby, Shay; White, Jacqueline K; Benjamini, Yoav

    2017-02-01

    Biological research frequently involves the study of phenotyping data. Many of these studies focus on rare event categorical data, and functional genomics studies typically study the presence or absence of an abnormal phenotype. With the growing interest in the role of sex, there is a need to assess the phenotype for sexual dimorphism. The identification of abnormal phenotypes for downstream research is challenged by the small sample size, the rare event nature, and the multiple testing problem, as many variables are monitored simultaneously. Here, we develop a statistical pipeline to assess statistical and biological significance while managing the multiple testing problem. We propose a two-step pipeline to initially assess for a treatment effect, in our case example genotype, and then test for an interaction with sex. We compare multiple statistical methods and use simulations to investigate the control of the type-one error rate and power. To maximize the power while addressing the multiple testing issue, we implement filters to remove data sets where the hypotheses to be tested cannot achieve significance. A motivating case study utilizing a large scale high-throughput mouse phenotyping data set from the Wellcome Trust Sanger Institute Mouse Genetics Project, where the treatment is a gene ablation, demonstrates the benefits of the new pipeline on the downstream biological calls.

  15. Improving the Identification of Phenotypic Abnormalities and Sexual Dimorphism in Mice When Studying Rare Event Categorical Characteristics

    PubMed Central

    Karp, Natasha A.; Heller, Ruth; Yaacoby, Shay; White, Jacqueline K.; Benjamini, Yoav

    2017-01-01

    Biological research frequently involves the study of phenotyping data. Many of these studies focus on rare event categorical data, and functional genomics studies typically study the presence or absence of an abnormal phenotype. With the growing interest in the role of sex, there is a need to assess the phenotype for sexual dimorphism. The identification of abnormal phenotypes for downstream research is challenged by the small sample size, the rare event nature, and the multiple testing problem, as many variables are monitored simultaneously. Here, we develop a statistical pipeline to assess statistical and biological significance while managing the multiple testing problem. We propose a two-step pipeline to initially assess for a treatment effect, in our case example genotype, and then test for an interaction with sex. We compare multiple statistical methods and use simulations to investigate the control of the type-one error rate and power. To maximize the power while addressing the multiple testing issue, we implement filters to remove data sets where the hypotheses to be tested cannot achieve significance. A motivating case study utilizing a large scale high-throughput mouse phenotyping data set from the Wellcome Trust Sanger Institute Mouse Genetics Project, where the treatment is a gene ablation, demonstrates the benefits of the new pipeline on the downstream biological calls. PMID:27932544

  16. Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.

    PubMed

    Tripathy, R K; Dandapat, S

    2016-06-01

    The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.

  17. Accuracy of pulmonary auscultation to detect abnormal respiratory mechanics: a cross-sectional diagnostic study.

    PubMed

    Xavier, Glaciele Nascimento; Duarte, Antonio Carlos Magalhães; Melo-Silva, César Augusto; dos Santos, Carlos Eduardo Ventura Gaio; Amado, Veronica Moreira

    2014-12-01

    Pulmonary auscultation is a method used in clinical practice for the evaluation and detection of abnormalities relating to the respiratory system. This method has limitations, as it depends on the experience and hearing acuity of the examiner to determine adventitious sounds. In this context, it's important to analyze whether there is a correlation between auscultation of lung sounds and the behavior of the respiratory mechanical properties of the respiratory system in patients with immediate postoperative cardiac surgery.

  18. Automated contralateral subtraction of dental panoramic radiographs for detecting abnormalities in paranasal sinus

    NASA Astrophysics Data System (ADS)

    Hara, Takeshi; Mori, Shintaro; Kaneda, Takashi; Hayashi, Tatsuro; Katsumata, Akitoshi; Fujita, Hiroshi

    2011-03-01

    Inflammation in the paranasal sinus is often observed in seasonal allergic rhinitis or with colds, but is also an indication for odontogenic tumors, carcinoma of the maxillary sinus or a maxillary cyst. The detection of those findings in dental panoramic radiographs is not difficult for radiologists, but general dentists may miss the findings since they focus on treatments of teeth. The purpose of this work is to develop a contralateral subtraction method for detecting the odontogenic sinusitis region on dental panoramic radiographs. We developed a contralateral subtraction technique in paranasal sinus region, consisting of 1) image filtering of the smoothing and sobel operation for noise reduction and edge extraction, 2) image registration of mirrored image by using mutual information, and 3) image display method of subtracted pixel data. We employed 56 cases (24 normal and 32 abnormal). The abnormal regions and the normal cases were verified by a board-certified radiologist using CT scans. Observer studies with and without subtraction images were performed for 9 readers. The true-positive rate at a 50% confidence level in 7 out of 9 readers was improved, but there was no statistical significance in the difference of area-under-curve (AUC) in each radiologist. In conclusion, the contralateral subtraction images of dental panoramic radiographs may improve the detection rate of abnormal regions in paranasal sinus.

  19. A Framework of Simple Event Detection in Surveillance Video

    NASA Astrophysics Data System (ADS)

    Xu, Weiguang; Zhang, Yafei; Lu, Jianjiang; Tian, Yulong; Wang, Jiabao

    Video surveillance is playing more and more important role in people's social life. Real-time alerting of threaten events and searching interesting content in stored large scale video footage needs human operator to pay full attention on monitor for long time. The labor intensive mode has limit the effectiveness and efficiency of the system. A framework of simple event detection is presented advance the automation of video surveillance. An improved inner key point matching approach is used to compensate motion of background in real-time; frame difference are used to detect foreground; HOG based classifiers are used to classify foreground object into people and car; mean-shift is used to tracking the recognized objects. Events are detected based on predefined rules. The maturity of the algorithms guarantee the robustness of the framework, and the improved approach and the easily checked rules enable the framework to work in real-time. Future works to be done are also discussed.

  20. Detecting abnormality in optic nerve head images using a feature extraction analysis.

    PubMed

    Zhu, Haogang; Poostchi, Ali; Vernon, Stephen A; Crabb, David P

    2014-07-01

    Imaging and evaluation of the optic nerve head (ONH) plays an essential part in the detection and clinical management of glaucoma. The morphological characteristics of ONHs vary greatly from person to person and this variability means it is difficult to quantify them in a standardized way. We developed and evaluated a feature extraction approach using shift-invariant wavelet packet and kernel principal component analysis to quantify the shape features in ONH images acquired by scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]). The methods were developed and tested on 1996 eyes from three different clinical centers. A shape abnormality score (SAS) was developed from extracted features using a Gaussian process to identify glaucomatous abnormality. SAS can be used as a diagnostic index to quantify the overall likelihood of ONH abnormality. Maps showing areas of likely abnormality within the ONH were also derived. Diagnostic performance of the technique, as estimated by ROC analysis, was significantly better than the classification tools currently used in the HRT software - the technique offers the additional advantage of working with all images and is fully automated.

  1. Data mining for signal detection of adverse event safety data.

    PubMed

    Chen, Hung-Chia; Tsong, Yi; Chen, James J

    2013-01-01

    The Adverse Event Reporting System (AERS) is the primary database designed to support the Food and Drug Administration (FDA) postmarketing safety surveillance program for all approved drugs and therapeutic biologic products. Most current disproportionality analysis focuses on the detection of potential adverse events (AE) involving a single drug and a single AE only. In this paper, we present a data mining biclustering technique based on the singular value decomposition to extract local regions of association for a safety study. The analysis consists of collection of biclusters, each representing an association between a set of drugs with the corresponding set of adverse events. Significance of each bicluster can be tested using disproportionality analysis. Individual drug-event combination can be further tested. A safety data set consisting of 193 drugs with 8453 adverse events is analyzed as an illustration.

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

    PubMed

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

    2016-03-28

    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.

  3. Method for early detection of cooling-loss events

    DOEpatents

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

    2015-12-22

    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.

  4. Method for early detection of cooling-loss events

    DOEpatents

    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.

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

    PubMed

    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.

  6. White Matter Abnormalities in Post-traumatic Stress Disorder Following a Specific Traumatic Event.

    PubMed

    Li, Lei; Lei, Du; Li, Lingjiang; Huang, Xiaoqi; Suo, Xueling; Xiao, Fenglai; Kuang, Weihong; Li, Jin; Bi, Feng; Lui, Su; Kemp, Graham J; Sweeney, John A; Gong, Qiyong

    2016-02-01

    Studies of posttraumatic stress disorder (PTSD) are complicated by wide variability in the intensity and duration of prior stressors in patient participants, secondary effects of chronic psychiatric illness, and a variable history of treatment with psychiatric medications. In magnetic resonance imaging (MRI) studies, patient samples have often been small, and they were not often compared to similarly stressed patients without PTSD in order to control for general stress effects. Findings from these studies have been inconsistent. The present study investigated whole-brain microstructural alterations of white matter in a large drug-naive population who survived a specific, severe traumatic event (a major 8.0-magnitude earthquake). Using diffusion tensor imaging (DTI), we explored group differences between 88 PTSD patients and 91 matched traumatized non-PTSD controls in fractional anisotropy (FA), as well as its component elements axial diffusivity (AD) and radial diffusivity (RD), and examined these findings in relation to findings from deterministic DTI tractography. Relations between white matter alterations and psychiatric symptom severity were examined. PTSD patients, relative to similarly stressed controls, showed an FA increase as well as AD and RD changes in the white matter beneath left dorsolateral prefrontal cortex and forceps major. The observation of increased FA in the PTSD group suggests that the pathophysiology of PTSD after a specific acute traumatic event is distinct from what has been reported in patients with several years duration of illness. Alterations in dorsolateral prefrontal cortex may be an important aspect of illness pathophysiology, possibly via the region's established role in fear extinction circuitry. Use-dependent myelination or other secondary compensatory changes in response to heightened demands for threat appraisal and emotion regulation may be involved.

  7. White Matter Abnormalities in Post-traumatic Stress Disorder Following a Specific Traumatic Event

    PubMed Central

    Li, Lei; Lei, Du; Li, Lingjiang; Huang, Xiaoqi; Suo, Xueling; Xiao, Fenglai; Kuang, Weihong; Li, Jin; Bi, Feng; Lui, Su; Kemp, Graham J.; Sweeney, John A.; Gong, Qiyong

    2016-01-01

    Studies of posttraumatic stress disorder (PTSD) are complicated by wide variability in the intensity and duration of prior stressors in patient participants, secondary effects of chronic psychiatric illness, and a variable history of treatment with psychiatric medications. In magnetic resonance imaging (MRI) studies, patient samples have often been small, and they were not often compared to similarly stressed patients without PTSD in order to control for general stress effects. Findings from these studies have been inconsistent. The present study investigated whole-brain microstructural alterations of white matter in a large drug-naive population who survived a specific, severe traumatic event (a major 8.0-magnitude earthquake). Using diffusion tensor imaging (DTI), we explored group differences between 88 PTSD patients and 91 matched traumatized non-PTSD controls in fractional anisotropy (FA), as well as its component elements axial diffusivity (AD) and radial diffusivity (RD), and examined these findings in relation to findings from deterministic DTI tractography. Relations between white matter alterations and psychiatric symptom severity were examined. PTSD patients, relative to similarly stressed controls, showed an FA increase as well as AD and RD changes in the white matter beneath left dorsolateral prefrontal cortex and forceps major. The observation of increased FA in the PTSD group suggests that the pathophysiology of PTSD after a specific acute traumatic event is distinct from what has been reported in patients with several years duration of illness. Alterations in dorsolateral prefrontal cortex may be an important aspect of illness pathophysiology, possibly via the region's established role in fear extinction circuitry. Use-dependent myelination or other secondary compensatory changes in response to heightened demands for threat appraisal and emotion regulation may be involved. PMID:26981581

  8. Abnormal mortality of octopus after a storm water event: Accumulated lead and lead isotopes as fingerprints.

    PubMed

    Raimundo, J; Ruano, F; Pereira, J; Mil-Homens, M; Brito, P; Vale, C; Caetano, M

    2017-03-01

    Octopus vulgaris is a sedentary organism that inhabits coastal waters being exposed to anthropogenic compounds. Lead concentration in coastal environments reflects many processes and activities namely weathering, industrial and domestic discharges, and atmospheric deposition. Since lead isotopic composition is little affected by kinetic processes occurring between source and sink, its signature has been used to identify different Pb sources. After a short-term heavy rainfall, hundreds of octopus appeared dead in two Portuguese coastal areas. Histopathology and Pb levels and its stable isotopes were determined in tissues, such as digestive gland, of stranded octopus and compared to alive specimens, sediments and runoff material from the same areas. Histology results showed severe damage in stranded octopus tissues suggesting that death was probably associated to multiple organ failure linked to hypertrophy and exudates input. In addition, Pb in stranded specimens reach concentrations up to one order of magnitude above the levels reported for alive octopus. Pb isotopic signatures in stranded organisms were closer to runoff material pointing to a similar origin of Pb. In summary, the results in this study showed that a short-term runoff event might change abruptly the salinity leading to the disruption of the osmoregulation function of octopus and consequently leading to its death. The analyses of stable isotopic Pb signature in octopus tissues corroborate these results and points to a change in the Pb source due to runoff after the storm water event. Pb stable isotopes in octopus proved to be an adequate tool to confirm the cause of death and linking it to the environment conditions.

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

    PubMed Central

    Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

    2010-01-01

    This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

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

    PubMed

    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.

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

    PubMed Central

    2016-01-01

    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. PMID:27510377

  13. Abnormal mitochondrial dynamics and synaptic degeneration as early events in Alzheimer's disease: implications to mitochondria-targeted antioxidant therapeutics.

    PubMed

    Reddy, P Hemachandra; Tripathi, Raghav; Troung, Quang; Tirumala, Karuna; Reddy, Tejaswini P; Anekonda, Vishwanath; Shirendeb, Ulziibat P; Calkins, Marcus J; Reddy, Arubala P; Mao, Peizhong; Manczak, Maria

    2012-05-01

    Synaptic pathology and mitochondrial oxidative damage are early events in Alzheimer's disease (AD) progression. Loss of synapses and synaptic damage are the best correlates of cognitive deficits found in AD patients. Recent research on amyloid beta (Aβ) and mitochondria in AD revealed that Aβ accumulates in synapses and synaptic mitochondria, leading to abnormal mitochondrial dynamics and synaptic degeneration in AD neurons. Further, recent studies using live-cell imaging and primary neurons from amyloid beta precursor protein (AβPP) transgenic mice revealed reduced mitochondrial mass, defective axonal transport of mitochondria and synaptic degeneration, indicating that Aβ is responsible for mitochondrial and synaptic deficiencies. Tremendous progress has been made in studying antioxidant approaches in mouse models of AD and clinical trials of AD patients. This article highlights the recent developments made in Aβ-induced abnormal mitochondrial dynamics, defective mitochondrial biogenesis, impaired axonal transport and synaptic deficiencies in AD. This article also focuses on mitochondrial approaches in treating AD, and also discusses latest research on mitochondria-targeted antioxidants in AD. This article is part of a Special Issue entitled: Antioxidants and Antioxidant Treatment in Disease.

  14. Human visual system-based smoking event detection

    NASA Astrophysics Data System (ADS)

    Odetallah, Amjad D.; Agaian, Sos S.

    2012-06-01

    Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

  15. Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells

    PubMed Central

    Schubert, Jennifer M.; Bird, Benjamin; Papamarkakis, Kostas; Miljković, Miloš; Bedrossian, Kristi; Laver, Nora; Diem, Max

    2010-01-01

    Aim Spectral Cytopathology (SCP) is a novel spectroscopic method for objective and unsupervised classification of individual exfoliated cells. The limitations of conventional cytopathology are well-recognized within the pathology community. In SCP, cellular differentiation is made by observing molecular changes in the nucleus and the cytoplasm, which may or may not produce morphological changes detectable by conventional cytopathology. This proof of concept study demonstrates SCP’s potential as an enhancing tool for cytopathologists by aiding in the accurate and reproducible diagnosis of cells in all states of disease. Method Infrared spectra are collected from cervical cells deposited onto reflectively coated glass slides. Each cell has a corresponding infrared spectrum that describes its unique biochemical composition. Spectral data are processed and analyzed by an unsupervised chemometric algorithm, Principal Component Analysis (PCA). Results In this blind study, cervical samples are classified by analyzing the spectra of morphologically normal looking squamous cells from normal samples and samples diagnosed by conventional cytopathology with low grade squamous intraepithelial lesions (LSIL). SCP discriminated cytopathological diagnoses amongst twelve different cervical samples with a high degree of specificity and sensitivity. SCP also correlated two samples with abnormal spectral changes: these samples had a normal cytopathological diagnosis but had a history of abnormal cervical cytology. The spectral changes observed in the morphologically normal looking cells are most likely due to an infection with human papillomavirus, HPV. HPV DNA testing was conducted on five additional samples, and SCP accurately differentiated these samples by their HPV status. Conclusions SCP tracks biochemical variations in cells that are consistent with the onset of disease. HPV has been implicated as the cause of these changes detected spectroscopically. SCP does not depend on

  16. Detection of abnormally high amygdalin content in food by an enzyme immunoassay.

    PubMed

    Cho, A-Yeon; Yi, Kye Sook; Rhim, Jung-Hyo; Kim, Kyu-Il; Park, Jae-Young; Keum, Eun-Hee; Chung, Junho; Oh, Sangsuk

    2006-04-30

    Amygdalin is a cyanogenic glycoside compound which is commonly found in the pits of many fruits and raw nuts. Although amygdalin itself is not toxic, it can release cyanide (CN) after hydrolysis when the pits and nuts are crushed, moistened and incubated, possibly within the gastrointestinal tract. CN reversibly inhibits cellular oxidizing enzymes and cyanide poisoning generates a range of clinical symptoms. As some pits and nuts may contain unusually high levels of amygdalin such that there is a sufficient amount to induce critical CN poisoning in humans, the detection of abnormal content of amygdalin in those pits and nuts can be a life-saving measure. Although there are various methods to detect amygdalin in food extracts, an enzyme immunoassay has not been developed for this purpose. In this study we immunized New Zealand White rabbits with an amygdalin-KLH (keyhole limpet hemocyanin) conjugate and succeeded in raising anti-sera reactive to amygdalin, proving that amygdalin can behave as a hapten in rabbits. Using this polyclonal antibody, we developed a competition enzyme immunoassay for determination of amygdalin concentration in aqueous solutions. This technique was able to effectively detect abnormally high amygdalin content in various seeds and nuts. In conclusion, we proved that enzyme immunoassay can be used to determine the amount of amygdalin in food extracts, which will allow automated analysis with high throughput.

  17. Aseismic events in Southern California: Detection with InSAR

    NASA Astrophysics Data System (ADS)

    Lohman, R. B.; McGuire, J. J.; Lundgren, P.

    2007-05-01

    Aseismic slow slip events are usually studied using data types that have a dense temporal sampling rate, such as continuous GPS or tremor analysis using seismic data. However, even the sparser temporal coverage of InSAR data can further our understanding of these events in three significant ways - First, in areas where aseismic transients have been detected on geodetic arrays, InSAR may be able to provide a spatially denser image of the extent and magnitude of deformation. Second, InSAR observations are complementary to GPS because of the differing sensitivities to horizontal and vertical motions. Thirdly, in areas with no ground-based geodetic instrumentation, InSAR can be used in survey mode to detect deformation signals that are not associated with any observed seismicity. The temporal constraints on such signals may not be tight enough to allow for dynamics models of how aseismic transients occur, but InSAR-only detections can improve our understanding of the spatial extent of these types of events and can also identify key areas for future instrumentation and observation. Here, I summarize some of the contributions of InSAR observations of slow slip events, including data spanning the 2005 Obsidian Buttes swam in the Salton Trough, CA, and InSAR time-series results for the Salton Trough using both traditional interferometry and the persistent scatterer method.

  18. A methodology for detecting routing events in discrete flow networks.

    SciTech Connect

    Garcia, H. E.; Yoo, T.; Nuclear Technology

    2004-01-01

    A theoretical framework for formulating and implementing model-based monitoring of discrete flow networks is discussed. Possible flows of items are described as the sequence of discrete-event (DE) traces. Each trace defines the DE sequence(s) that are triggered when an entity follows a given flow-path and visits tracking locations distributed within the monitored system. Given the set of possible discrete flows, a possible-behavior model - an interacting set of automata - is constructed, where each automaton models the discrete flow of items at each tracking location. Event labels or symbols contain all the information required to unambiguously distinguish each discrete flow. Within the possible behavior, there is a special sub-behavior whose occurrence is required to be detected. The special behavior may be specified by the occurrence of routing events, such as faults. These intermittent or non-persistent events may occur repeatedly. An observation mask is then defined, characterizing the actual observation configuration available for collecting item tracking data. The analysis task is then to determine whether this observation configuration is capable of detecting the identified special behavior. The assessment is accomplished by evaluating several observability notions, such as detectability and diagnosability. If the corresponding property is satisfied, associated formal observers are constructed to perform the monitoring task at hand. The synthesis of an optimal observation mask may also be conducted to suggest an appropriate observation configuration guaranteeing the detection of the special events and to construct associated monitoring agents. The proposed framework, modeling methodology, and supporting techniques for discrete flow networks monitoring are presented and illustrated with an example.

  19. Comparison of Event Detection Methods for Centralized Sensor Networks

    NASA Technical Reports Server (NTRS)

    Sauvageon, Julien; Agogiono, Alice M.; Farhang, Ali; Tumer, Irem Y.

    2006-01-01

    The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

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

    NASA Astrophysics Data System (ADS)

    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.

  1. Mathematical impairment associated with high-contrast abnormalities in change detection and magnocellular visual evoked response.

    PubMed

    Jastrzebski, Nicola R; Crewther, Sheila G; Crewther, David P

    2015-10-01

    The cause of developmental dyscalculia, a specific deficit in acquisition of arithmetic skills, particularly of enumeration, has never been investigated with respect to the patency of the visual magnocellular system. Here, the question of dysfunction of the afferent magnocellular cortical input and its dorsal stream projections was tested directly using nonlinear analysis of the visual evoked potential (VEP) and through the psychophysical ability to rapidly detect visual change. A group of young adults with self-reported deficiencies of arithmetical ability, showed marked impairment in magnitude estimation and enumeration performance-though not in lexical decision reaction times when compared with an arithmetically capable group controlled for age and handedness. Multifocal nonlinear VEPs were recorded at low (24 %) and high (96 %) contrast. First- and second-order VEP kernels were comparable between groups at low contrast, but not at high contrast. The mathematically impaired group showed an abnormal lack of contrast saturation in the shortest latency first-order peak (N60) and a delayed P100 positivity in the first slice of the second-order kernel. Both features have previously been argued to be physiological markers of magnocellular function. Mathematically impaired participants also performed worse on a gap paradigm change detection for digit task showing increased reaction times for high-contrast stimuli but not for low-contrast stimuli compared with controls. The VEP results give direct evidence of abnormality in the occipital processing of magnocellular information in those with mathematical impairment. The anomalous high visual contrast physiological and psychophysical performance suggests an abnormality in the inhibitory processes that normally result in saturation of contrast gain in the magnocellular system.

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

    SciTech Connect

    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.

  3. Regional heart motion abnormality detection via information measures and unscented Kalman filtering.

    PubMed

    Punithakumar, Kumaradevan; Ben Ayed, Ismail; Islam, Ali; Ross, Ian G; Li, Shuo

    2010-01-01

    This study investigates regional heart motion abnormality detection using various classifier features with Shannon's Differential Entropy (SDE). Rather than relying on elementary measurements or a fixed set of moments, the SDE measures global distribution information and, as such, has more discriminative power in classifying distributions. Based on functional images, which are subject to noise and segmentation inaccuracies, heart wall motion analysis is acknowledged as a difficult problem and, therefore, incorporation of prior knowledge is desirable to enhance the accuracy. Given noisy data and nonlinear dynamic model to describe the myocardial motion, unscented Kalman filter, a recursive nonlinear Bayesian filter, is devised in this study so as to estimate LV cavity points. Subsequently, a naive Bayes classifier algorithm is constructed from the SDEs of different features in order to automatically detect abnormal functional regions of the myocardium. Using 90 x 20 segmented LV cavities of short-axis magnetic resonance images obtained from 30 subjects, the experimental analysis carried over 480 myocardial segments demonstrates that the proposed method perform significantly better than other recent methods, and can lead to a promising diagnostic support tool to assist clinicians.

  4. Automated Detection of Vessel Abnormalities on Fluorescein Angiogram in Malarial Retinopathy.

    PubMed

    Zhao, Yitian; MacCormick, Ian J C; Parry, David G; Beare, Nicholas A V; Harding, Simon P; Zheng, Yalin

    2015-06-08

    The detection and assessment of intravascular filling defects is important, because they may represent a process central to cerebral malaria pathogenesis: neurovascular sequestration. We have developed and validated a framework that can automatically detect intravascular filling defects in fluorescein angiogram images. It first employs a state-of-the-art segmentation approach to extract the vessels from images and then divide them into individual segments by geometrical analysis. A feature vector based on the intensity and shape of saliency maps is generated to represent the level of abnormality of each vessel segment. An AdaBoost classifier with weighted cost coefficient is trained to classify the vessel segments into normal and abnormal categories. To demonstrate its effectiveness, we apply this framework to 6,358 vessel segments in images from 10 patients with malarial retinopathy. The test sensitivity, specificity, accuracy, and area under curve (AUC) are 74.7%, 73.5%, 74.1% and 74.2% respectively when compared to the reference standard of human expert manual annotations. This performance is comparable to the agreement that we find between human observers of intravascular filling defects. Our method will be a powerful new tool for studying malarial retinopathy.

  5. Automated Detection of Vessel Abnormalities on Fluorescein Angiogram in Malarial Retinopathy

    PubMed Central

    Zhao, Yitian; MacCormick, Ian J. C.; Parry, David G.; Beare, Nicholas A. V.; Harding, Simon P.; Zheng, Yalin

    2015-01-01

    The detection and assessment of intravascular filling defects is important, because they may represent a process central to cerebral malaria pathogenesis: neurovascular sequestration. We have developed and validated a framework that can automatically detect intravascular filling defects in fluorescein angiogram images. It first employs a state-of-the-art segmentation approach to extract the vessels from images and then divide them into individual segments by geometrical analysis. A feature vector based on the intensity and shape of saliency maps is generated to represent the level of abnormality of each vessel segment. An AdaBoost classifier with weighted cost coefficient is trained to classify the vessel segments into normal and abnormal categories. To demonstrate its effectiveness, we apply this framework to 6,358 vessel segments in images from 10 patients with malarial retinopathy. The test sensitivity, specificity, accuracy, and area under curve (AUC) are 74.7%, 73.5%, 74.1% and 74.2% respectively when compared to the reference standard of human expert manual annotations. This performance is comparable to the agreement that we find between human observers of intravascular filling defects. Our method will be a powerful new tool for studying malarial retinopathy. PMID:26053690

  6. The use of oral endoscopy for detection of cheek teeth abnormalities in 300 horses.

    PubMed

    Simhofer, Hubert; Griss, Robert; Zetner, Karl

    2008-12-01

    The main objective of this study was to evaluate an endoscopic examination protocol for routine dental examination in horses. The oral cavities of 300 standing, sedated horses were examined under field and hospital conditions with a rigid endoscope using a standardised technique that included examination of the occlusal, lingual (palatal) and buccal surfaces of all cheek teeth rows. The most common cheek teeth abnormalities detected were sharp enamel edges (present in 96.3% of horses), focal overgrowths (64.3%), fissure fractures (54.3%), diastemata (24.3%) and infundibular hypoplasia/caries (48.3%). Rigid endoscopy of the equine oral cavity was found to be a safe non-invasive diagnostic technique that appeared to be superior to clinical oral examination for detecting subtle cheek teeth changes.

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

    PubMed Central

    2012-01-01

    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. PMID:22595089

  8. Integrated Seismic Event Detection and Location by Advanced Array Processing

    SciTech Connect

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

    2007-02-09

    The principal objective of this two-year study is to develop and test a new advanced, automatic approach to seismic detection/location using array processing. We address a strategy to obtain significantly improved precision in the location of low-magnitude events compared with current fully-automatic approaches, combined with a low false alarm rate. We have developed and evaluated a prototype automatic system which uses as a basis regional array processing with fixed, carefully calibrated, site-specific parameters in conjuction with improved automatic phase onset time estimation. We have in parallel developed tools for Matched Field Processing for optimized detection and source-region identification of seismic signals. This narrow-band procedure aims to mitigate some of the causes of difficulty encountered using the standard array processing system, specifically complicated source-time histories of seismic events and shortcomings in the plane-wave approximation for seismic phase arrivals at regional arrays.

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

    PubMed

    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.

  10. Detection of abnormal item based on time intervals for recommender systems.

    PubMed

    Gao, Min; Yuan, Quan; Ling, Bin; Xiong, Qingyu

    2014-01-01

    With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from "shilling" attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ(2)). We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users.

  11. Statistical language analysis for automatic exfiltration event detection.

    SciTech Connect

    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.

  12. The effects of anatomical information and observer expertise on abnormality detection task

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Cavaro-Ménard, C.; Le Callet, P.; Cooper, L. H. K.; Hunault, G.; Tanguy, J.-Y.

    2011-03-01

    This paper presents a novel study investigating the influences of Magnetic Resonance (MR) image anatomical information and observer expertise on an abnormality detection task. MRI is exquisitely sensitive for detecting brain abnormalities, particularly in the evaluation of white matter diseases, e.g. multiple sclerosis (MS). For this reason, MS lesions are simulated as the target stimuli for detection in the present study. Two different image backgrounds are used in the following experiments: a) homogeneous region of white matter tissue, and b) one slice of a healthy brain MR image. One expert radiologist (more than 10 years' experience), three radiologists (less than 5 years' experience) and eight naïve observers (without any prior medical knowledge) have performed these experiments, during which they have been asked different questions dependent upon level of experience; the three radiologists and eight naïve observers were asked if they were aware of any hyper-signal, likely to represent an MS lesion, while the most experienced consultant was asked if a clinically significant sign was present. With the percentages of response "yes" displayed on the y-axis and the lesion intensity contrasts on the x-axis, psychometric function is generated from the observer' responses. Results of psychometric functions and calculated thresholds indicate that radiologists have better hyper-signal detection ability than naïve observers, which is intuitively shown by the lower simple visibility thresholds of radiologists. However, when radiologists perform a task with clinical implications, e.g. to detect a clinically significant sign, their detection thresholds are elevated. Moreover, the study indicates that for the radiologists, the simple visibility thresholds remain the same with and without the anatomical information, which reduces the threshold for the clinically significant sign detection task. Findings provide further insight into human visual system processing for this

  13. Application of Kalman Filtering Techniques for Microseismic Event Detection

    NASA Astrophysics Data System (ADS)

    Baziw, E.; Weir-Jones, I.

    - Microseismic monitoring systems are generally installed in areas of induced seismicity caused by human activity. Induced seismicity results from changes in the state of stress which may occur as a result of excavation within the rock mass in mining (i.e., rockbursts), and changes in hydrostatic pressures and rock temperatures (e.g., during fluid injection or extraction) in oil exploitation, dam construction or fluid disposal. Microseismic monitoring systems determine event locations and important source parameters such as attenuation, seismic moment, source radius, static stress drop, peak particle velocity and seismic energy. An essential part of the operation of a microseismic monitoring system is the reliable detection of microseismic events. In the absence of reliable, automated picking techniques, operators rely upon manual picking. This is time-consuming, costly and, in the presence of background noise, very prone to error. The techniques described in this paper not only permit the reliable identification of events in cluttered signal environments they have also enabled the authors to develop reliable automated event picking procedures. This opens the way to use microseismic monitoring as a cost-effective production/operations procedure. It has been the experience of the authors that in certain noisy environments, the seismic monitoring system may trigger on and subsequently acquire substantial quantities of erroneous data, due to the high energy content of the ambient noise. Digital filtering techniques need to be applied on the microseismic data so that the ambient noise is removed and event detection simplified. The monitoring of seismic acoustic emissions is a continuous, real-time process and it is desirable to implement digital filters which can also be designed in the time domain and in real-time such as the Kalman Filter. This paper presents a real-time Kalman Filter which removes the statistically describable background noise from the recorded

  14. Improving the performance of univariate control charts for abnormal detection and classification

    NASA Astrophysics Data System (ADS)

    Yiakopoulos, Christos; Koutsoudaki, Maria; Gryllias, Konstantinos; Antoniadis, Ioannis

    2017-03-01

    Bearing failures in rotating machinery can cause machine breakdown and economical loss, if no effective actions are taken on time. Therefore, it is of prime importance to detect accurately the presence of faults, especially at their early stage, to prevent sequent damage and reduce costly downtime. The machinery fault diagnosis follows a roadmap of data acquisition, feature extraction and diagnostic decision making, in which mechanical vibration fault feature extraction is the foundation and the key to obtain an accurate diagnostic result. A challenge in this area is the selection of the most sensitive features for various types of fault, especially when the characteristics of failures are difficult to be extracted. Thus, a plethora of complex data-driven fault diagnosis methods are fed by prominent features, which are extracted and reduced through traditional or modern algorithms. Since most of the available datasets are captured during normal operating conditions, the last decade a number of novelty detection methods, able to work when only normal data are available, have been developed. In this study, a hybrid method combining univariate control charts and a feature extraction scheme is introduced focusing towards an abnormal change detection and classification, under the assumption that measurements under normal operating conditions of the machinery are available. The feature extraction method integrates the morphological operators and the Morlet wavelets. The effectiveness of the proposed methodology is validated on two different experimental cases with bearing faults, demonstrating that the proposed approach can improve the fault detection and classification performance of conventional control charts.

  15. Integrating event detection system operation characteristics into sensor placement optimization.

    SciTech Connect

    Hart, William Eugene; McKenna, Sean Andrew; Phillips, Cynthia Ann; Murray, Regan Elizabeth; Hart, David Blaine

    2010-05-01

    We consider the problem of placing sensors in a municipal water network when we can choose both the location of sensors and the sensitivity and specificity of the contamination warning system. Sensor stations in a municipal water distribution network continuously send sensor output information to a centralized computing facility, and event detection systems at the control center determine when to signal an anomaly worthy of response. Although most sensor placement research has assumed perfect anomaly detection, signal analysis software has parameters that control the tradeoff between false alarms and false negatives. We describe a nonlinear sensor placement formulation, which we heuristically optimize with a linear approximation that can be solved as a mixed-integer linear program. We report the results of initial experiments on a real network and discuss tradeoffs between early detection of contamination incidents, and control of false alarms.

  16. Detection of abnormalities in febrile AIDS patients with In-111-labeled leukocyte and Ga-67 scintigraphy

    SciTech Connect

    Fineman, D.S.; Palestro, C.J.; Kim, C.K.; Needle, L.B.; Vallabhajosula, S.; Solomon, R.W.; Goldsmith, S.J.

    1989-03-01

    Thirty-six patients with acquired immunodeficiency syndrome (AIDS), who were febrile but without localizing signs, underwent indium-111 leukocyte scintigraphy 24 hours after injection of labeled white blood cells (WBCs) and were restudied 48 hours after injection of gallium-67 citrate. Fifty-six abnormalities were identified as possible sources of the fever; 27 were confirmed with biopsy. Of these 27, 15 were identified only on In-111 WBC scans (including colitis, sinusitis, and focal bacterial pneumonia); six, only on Ga-67 scans (predominantly Pneumocystis carinii pneumonia and lymphadenopathy); and six, on both studies (predominantly pulmonary lesions). In-111 WBC scanning revealed 21 of 27 abnormalities (78%) and gallium scanning, 12 of 27 (44%). If only one scintigraphic study has been performed, particularly with Ga-67, a significant number of lesions would not have been detected. The authors believe radionuclide evaluation of the febrile AIDS patient without localizing signs should begin with In-111 WBC scintigraphy. Gallium scanning may be used depending on results of In-111 WBC scans or if there is a high index of suspicion for P carinii pneumonia.

  17. Detection of red tide events in the Ariake Sound, Japan

    NASA Astrophysics Data System (ADS)

    Ishizaka, Joji

    2003-05-01

    High resolution SeaWiFS data was used to detect a red tide event occurred in the Ariake Sound, Japan, in winter of 2000 to 2001. The area is small embayment surrounding by tidal flat, and it is known as one of the most productive areas in coast of Japan. The red tide event damaged to seaweed (Nori) culture, and the relation to the reclamation at the Isahaya Bay in the Sound has been discussed. SeaWiFS chlorophyll data showed the red tide started early December 2000, from the Isahaya Bay, although direct relationship to the reclamation was not clear. The red tide persisted to the end of February. Monthly average of SeaWiFS data from May 1998 to December 2001 indicated that the chlorophyll increased twice a year, early summer and fall after the rain. The red tide event was part of the fall bloom which started later and continued longer than other years. Ocean color is useful to detect the red tide; however, it is required to improve the algorithms to accurately estimate chlorophyll in high turbid water and to discriminate toxic flagellates.

  18. High Probabilities of Planet Detection during Microlensing Events.

    NASA Astrophysics Data System (ADS)

    Peale, S. J.

    2000-10-01

    The averaged probability of detecting a planetary companion of a lensing star during a gravitational microlensing event toward the Galactic center when the planet-lens mass ratio is 0.001 is shown to have a maximum exceeding 20% for a distribution of source-lens impact parameters that is determined by the efficiency of event detection, and a maximum exceeding 10% for a uniform distribution of impact parameters. The probability varies as the square root of the planet-lens mass ratio. A planet is assumed detectable if the perturbation of the light curve exceeds 2/(S/N) for a significant number of data points, where S/N is the signal-to noise ratio for the photometry of the source. The probability peaks at a planetary semimajor axis a that is close to the mean Einstein ring radius of the lenses of about 2 AU along the line of sight, and remains significant for 0.6<= a<= 10 AU. The low value of the mean Einstein ring radius results from the dominance of M stars in the mass function of the lenses. The probability is averaged over the distribution of the projected position of the planet onto the lens plane, over the lens mass function, over the distribution of impact parameters, over the distribution of lens along the line of sight to the source star, over the I band luminosity function of the sources adjusted for the source distance, and over the source distribution along the line of sight. If two or more parameters of the lensing event are known, such as the I magnitude of the source and the impact parameter, the averages over these parameters can be omitted and the probability of detection determined for a particular event. The calculated probabilities behave as expected with variations in the line of sight, the mass function of the lenses, the extinction and distance to and magnitude of the source, and with a more demanding detection criterion. The relatively high values of the probabilities are robust to plausible variations in the assumptions. The high

  19. Early Lung Cancer Detection in Uranium Miners with Abnormal Sputum Cytology

    SciTech Connect

    Saccomanno, G.

    2000-06-30

    ''Early Lung Cancer Detection in Uranium Miners with Abnormal Sputum Cytology'' was funded by the Department of Energy to monitor the health effects of radon exposure and/or cigarette smoke on uranium workers from the Colorado Plateau. The resulting Saccomanno Uranium Workers Archive and data base has been used as a source of information to prove eligibility for compensation under the Radiation Exposure Compensation Act and as the source of primary data tissue for a subcontract and other collaborations with outside investigators. The latter includes a study of radon exposure and lung cancer risk in a non-smoking cohort of uranium miners (subcontract); a study of genetic markers for lung cancer susceptibility; and a study of {sup 210}Pb accumulation in the skull as a biomarker of radon exposure.

  20. Detecting abnormal vasculature from photoacoustic signals using wavelet-packet features

    NASA Astrophysics Data System (ADS)

    Zalev, Jason; Kolios, Michael C.

    2011-03-01

    Photoacoustic systems can produce high-resolution, high-contrast images of vascular structures. To reconstruct images at very high-resolution, signals must be collected from many transducer locations, which can be time consuming due to limitations in transducer array technology. A method is presented to quickly discriminate between normal and abnormal tissue based on the structural morphology of vasculature. To demonstrate that the approach may be useful for cancer detection, a special simulator that produces photoacoustic signals from 3D models of vascular tissue is developed. Results show that it is possible to differentiate tissue classes even when it is not possible to resolve individual blood vessels. Performance of the algorithm remains strong as the number of transducer locations decreases and in the presence of noise.

  1. An efficient sampling algorithm for uncertain abnormal data detection in biomedical image processing and disease prediction.

    PubMed

    Liu, Fei; Zhang, Xi; Jia, Yan

    2015-01-01

    In this paper, we propose a computer information processing algorithm that can be used for biomedical image processing and disease prediction. A biomedical image is considered a data object in a multi-dimensional space. Each dimension is a feature that can be used for disease diagnosis. We introduce a new concept of the top (k1,k2) outlier. It can be used to detect abnormal data objects in the multi-dimensional space. This technique focuses on uncertain space, where each data object has several possible instances with distinct probabilities. We design an efficient sampling algorithm for the top (k1,k2) outlier in uncertain space. Some improvement techniques are used for acceleration. Experiments show our methods' high accuracy and high efficiency.

  2. Towards perception awareness: Perceptual event detection for Brain computer interfaces.

    PubMed

    Nejati, Hossein; Tsourides, Kleovoulos; Pomponiu, Victor; Ehrenberg, Evan C; Ngai-Man Cheung; Sinha, Pawan

    2015-08-01

    Brain computer interface (BCI) technology is becoming increasingly popular in many domains such as entertainment, mental state analysis, and rehabilitation. For robust performance in these domains, detecting perceptual events would be a vital ability, enabling adaptation to and act on the basis of user's perception of the environment. Here we present a framework to automatically mine spatiotemporal characteristics of a given perceptual event. As this "signature" is derived directly from subject's neural behavior, it can serve as a representation of the subject's perception of the targeted scenario, which in turn allows a BCI system to gain a new level of context awareness: perception awareness. As a proof of concept, we show the application of the proposed framework on MEG signal recordings from a face perception study, and the resulting temporal and spatial characteristics of the derived neural signature, as well as it's compatibility with the neuroscientific literature on face perception.

  3. Array-Based Comparative Genomic Hybridization for the Genomewide Detection of Submicroscopic Chromosomal Abnormalities

    PubMed Central

    Vissers, Lisenka E. L. M. ; de Vries, Bert B. A. ; Osoegawa, Kazutoyo ; Janssen, Irene M. ; Feuth, Ton ; Choy, Chik On ; Straatman, Huub ; van der Vliet, Walter ; Huys, Erik H. L. P. G. ; van Rijk, Anke ; Smeets, Dominique ; van Ravenswaaij-Arts, Conny M. A. ; Knoers, Nine V. ; van der Burgt, Ineke ; de Jong, Pieter J. ; Brunner, Han G. ; van Kessel, Ad Geurts ; Schoenmakers, Eric F. P. M. ; Veltman, Joris A. 

    2003-01-01

    Microdeletions and microduplications, not visible by routine chromosome analysis, are a major cause of human malformation and mental retardation. Novel high-resolution, whole-genome technologies can improve the diagnostic detection rate of these small chromosomal abnormalities. Array-based comparative genomic hybridization allows such a high-resolution screening by hybridizing differentially labeled test and reference DNAs to arrays consisting of thousands of genomic clones. In this study, we tested the diagnostic capacity of this technology using ∼3,500 flourescent in situ hybridization–verified clones selected to cover the genome with an average of 1 clone per megabase (Mb). The sensitivity and specificity of the technology were tested in normal-versus-normal control experiments and through the screening of patients with known microdeletion syndromes. Subsequently, a series of 20 cytogenetically normal patients with mental retardation and dysmorphisms suggestive of a chromosomal abnormality were analyzed. In this series, three microdeletions and two microduplications were identified and validated. Two of these genomic changes were identified also in one of the parents, indicating that these are large-scale genomic polymorphisms. Deletions and duplications as small as 1 Mb could be reliably detected by our approach. The percentage of false-positive results was reduced to a minimum by use of a dye-swap-replicate analysis, all but eliminating the need for laborious validation experiments and facilitating implementation in a routine diagnostic setting. This high-resolution assay will facilitate the identification of novel genes involved in human mental retardation and/or malformation syndromes and will provide insight into the flexibility and plasticity of the human genome. PMID:14628292

  4. Ventilatory defect in coal workers with simple pneumoconiosis: early detection of functional abnormalities.

    PubMed

    Lin, L C; Yang, S C; Lu, K W

    2001-05-01

    Airway obstruction is a prominent feature in coal workers' pneumoconiosis (CWP). However, many patients with CWP have even demonstrated a normal forced vital capacity (FVC) and forced expiratory volume in 1s (FEV1). The purpose of this study was to evaluate the ventilatory defect by spirometry and search for parameters, other than FVC and FEV1, suitable for early detection of pulmonary impairment in CWP. A sample of 227 coal miners was selected from the medical clinics of two teaching hospitals. Maximal expiratory flow volume measurement and determination of functional residual capacity (FRC) and residual volume (RV) were carried out with an automated plethysmograph. The prevalence of airway obstruction (FEV1/FVC < 70%) in this sample of miners was 52.9% (120/227). There was a progression of functional impairment with the transition from category 0 to categories 2 and 3, no matter what the miners smoking habits. All of the 107 non-obstructed miners had a normal FVC and FEV1. However, the mean values for FEF25-75% (mean forced expiratory flow during the middle half of FVC) and Vmax50 (maximal expiratory flow rate at 50% FVC) were abnormally low, and RV was already elevated, in those non-obstructed subjects with category 1 simple pneumoconiosis. A borderline abnormally elevated FRC in the miners with radiological category 3 of CWP was also noted. We conclude that the Vmax50, FEF25-75%, and RV appeared to be the discriminative indices for detecting early ventilatory defect in non-obstructed patients with simple CWP. Further studies is still needed to clarify the cause of small airway dysfunction.

  5. Endmember detection in marine environment with oil spill event

    NASA Astrophysics Data System (ADS)

    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.

  6. Real-Time Plasma Process Condition Sensing and Abnormal Process Detection

    PubMed Central

    Yang, Ryan; Chen, Rongshun

    2010-01-01

    The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools. PMID:22219683

  7. Real-time plasma process condition sensing and abnormal process detection.

    PubMed

    Yang, Ryan; Chen, Rongshun

    2010-01-01

    The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools.

  8. An Automated Visual Event Detection System for Cabled Observatory Video

    NASA Astrophysics Data System (ADS)

    Edgington, D. R.; Cline, D. E.; Mariette, J.

    2007-12-01

    The permanent presence of underwater cameras on oceanic cabled observatories, such as the Victoria Experimental Network Under the Sea (VENUS) and Eye-In-The-Sea (EITS) on Monterey Accelerated Research System (MARS), will generate valuable data that can move forward the boundaries of understanding the underwater world. However, sightings of underwater animal activities are rare, resulting in the recording of many hours of video with relatively few events of interest. The burden of video management and analysis often requires reducing the amount of video recorded and later analyzed. Sometimes enough human resources do not exist to analyze the video; the strains on human attention needed to analyze video demand an automated way to assist in video analysis. Towards this end, an Automated Visual Event Detection System (AVED) is in development at the Monterey Bay Aquarium Research Institute (MBARI) to address the problem of analyzing cabled observatory video. Here we describe the overall design of the system to process video data and enable science users to analyze the results. We present our results analyzing video from the VENUS observatory and test data from EITS deployments. This automated system for detecting visual events includes a collection of custom and open source software that can be run three ways: through a Web Service, through a Condor managed pool of AVED enabled compute servers, or locally on a single computer. The collection of software also includes a graphical user interface to preview or edit detected results and to setup processing options. To optimize the compute-intensive AVED algorithms, a parallel program has been implemented for high-data rate applications like the EITS instrument on MARS.

  9. Data mining to generate adverse drug events detection rules.

    PubMed

    Chazard, Emmanuel; Ficheur, Grégoire; Bernonville, Stéphanie; Luyckx, Michel; Beuscart, Régis

    2011-11-01

    Adverse drug events (ADEs) are a public health issue. Their detection usually relies on voluntary reporting or medical chart reviews. The objective of this paper is to automatically detect cases of ADEs by data mining. 115,447 complete past hospital stays are extracted from six French, Danish, and Bulgarian hospitals using a common data model including diagnoses, drug administrations, laboratory results, and free-text records. Different kinds of outcomes are traced, and supervised rule induction methods (decision trees and association rules) are used to discover ADE detection rules, with respect to time constraints. The rules are then filtered, validated, and reorganized by a committee of experts. The rules are described in a rule repository, and several statistics are automatically computed in every medical department, such as the confidence, relative risk, and median delay of outcome appearance. 236 validated ADE-detection rules are discovered; they enable to detect 27 different kinds of outcomes. The rules use a various number of conditions related to laboratory results, diseases, drug administration, and demographics. Some rules involve innovative conditions, such as drug discontinuations.

  10. Use of sonification in the detection of anomalous events

    NASA Astrophysics Data System (ADS)

    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.

  11. Prenatal aneupioidy detection by fluorencence in situ hybridization (FISH) in 1,068 second trimester pregnancies with fetal ultrasound abnormalities

    SciTech Connect

    Ward, B.E.; Wright, M.; Lytle, C. |

    1994-09-01

    One indication for rapid prenatal aneuploidy detection in uncultured amniocytes by FISH is the identification of fetal abnormalities by ultrasound. We analyzed 1,068 consecutive specimens from second trimester pregnancies with fetal ultrasound abnormalities referred for FISH plus cytogenetics. These specimens are a subset (14.7%) of the most recent 7,240 clinical referrals for these combined analyses. Hybridization with specific probes for chromosomes 21, 18, 13, X and Y were used to detect common aneuploidies. As defined by previously described criteria, specimens were reported as informative disomic, informative trisomic, or uninformative within two days of receipt. The rate of informative results from acceptable specimens was 90.1%. The vast majority of uninformative results was due to maternal cell contamination which precluded analysis. Within the informative group there were no false positives, false negatives nor reports of incorrect gender. Of the 1,068 tested specimens with ultrasound abnormalities, 135 (12.5%) were cytogenetically diagnosed as aneuploid. Prior to the cytogenetic analysis, a total of 107 aneuploidies were correctly identified by FISH. The remaining 26 aneuploidies generated an uninformative FISH result. The overall FISH detection rate for aneuploidy (including informative and uninformative results) was 79%. Other unbalanced chromosome abnormalities were present in 2.1% of specimens and 0.7% had balanced chromosome abnormalities. The inclusive total cytogenetic abnormality rate was 15.4%, of which 85% were potentially detectable by our FISH protocol. This clinical experience demonstrates that aneuploidy detection by FISH on uncultured amniocytes can provide accurate and rapid identification of aneuploidies, especially when such abnormalities are suspected following the diagnosis of fetal anomalies by ultrasound examination.

  12. Automatic adverse drug events detection using letters to the editor.

    PubMed

    Yang, Chao; Srinivasan, Padmini; Polgreen, Philip M

    2012-01-01

    We present and test the intuition that letters to the editor in journals carry early signals of adverse drug events (ADEs). Surprisingly these letters have not yet been exploited for automatic ADE detection unlike for example, clinical records and PubMed. Part of the challenge is that it is not easy to access the full-text of letters (for the most part these do not appear in PubMed). Also letters are likely underrated in comparison with full articles. Besides demonstrating that this intuition holds we contribute techniques for post market drug surveillance. Specifically, we test an automatic approach for ADE detection from letters using off-the-shelf machine learning tools. We also involve natural language processing for feature definitions. Overall we achieve high accuracy in our experiments and our method also works well on a second new test set. Our results encourage us to further pursue this line of research.

  13. Detectability of GW150914-like events by gravitational microlensing

    NASA Astrophysics Data System (ADS)

    Eilbott, Daniel; Riley, Alexander; Cohn, Jonathan; Kesden, Michael H.; King, Lindsay J.

    2017-01-01

    The recent discovery of gravitational waves from stellar-mass binary black holes (BBHs) provided direct evidence of the existence of these systems. These BBHs would have gravitational microlensing signatures that are, due to their large masses and small separations, distinct from single-lens signals. We apply Bayesian statistics to examine the distinguishability of BBH microlensing events from single-lens events under ideal observing conditions, using modern photometric and astrometric capabilities. Given one year of ideal observations, a source star at the Galactic center, a GW150914-like BBH lens (total mass 65 M⊙, mass ratio 0.8) at half that distance, and an impact parameter of 0.4 Einstein radii, we find that BBH separations down to 0.00634 Einstein radii are detectable, which is < 0.00716 Einstein radii, the limit at which the BBH would merge within the age of the universe. We encourage analyses of LSST data to search for similar modulation in all long-duration events, providing a new channel for the discovery of short-period BBHs in our Galaxy.

  14. Look what else we found - clinically significant abnormalities detected during routine ROP screening

    PubMed Central

    Jayadev, Chaitra; Vinekar, Anand; Bauer, Noel; Mangalesh, Shwetha; Mahendradas, Padmamalini; Kemmanu, Vasudha; Mallipatna, Ashwin; Shetty, Bhujang

    2015-01-01

    Purpose: The purpose of this study was to report the spectrum of anterior and posterior segment diagnoses in Asian Indian premature infants detected serendipitously during routine retinopathy of prematurity (ROP) screening during a 1 year period. Methods: A retrospective review of all Retcam (Clarity MSI, USA) imaging sessions during the year 2011 performed on infants born either <2001 g at birth and/or <34.1 weeks of gestation recruited for ROP screening was performed. All infants had a minimum of seven images at each session, which included the dilated anterior segment, disc, and macula center and the four quadrants using the 130° lens. Results: Of the 8954 imaging sessions of 1450 new infants recruited in 2011, there were 111 (7.66%) with a diagnosis other than ROP. Anterior segment diagnoses seen in 31 (27.9%) cases included clinically significant cataract, lid abnormalities, anophthalmos, microphthalmos, and corneal diseases. Posterior segment diagnoses in 80 (72.1%) cases included retinal hemorrhages, cherry red spots, and neonatal uveitis of infective etiologies. Of the 111 cases, 15 (13.5%) underwent surgical procedures and 24 (21.6%) underwent medical procedures; importantly, two eyes with retinoblastoma were detected which were managed timely. Conclusions: This study emphasizes the importance of ocular digital imaging in premature infants. Visually significant, potentially life-threatening, and even treatable conditions were detected serendipitously during routine ROP screening that may be missed or detected late otherwise. This pilot data may be used to advocate for a possible universal infant eye screening program using digital imaging. PMID:26139795

  15. Increased SERS detection efficiency for characterizing rare events in flow.

    PubMed

    Jacobs, Kevin T; Schultz, Zachary D

    2015-08-18

    Improved surface-enhanced Raman scattering (SERS) measurements of a flowing aqueous sample are accomplished by combining line focus optics with sheath-flow SERS detection. The straightforward introduction of a cylindrical lens into the optical path of the Raman excitation laser increases the efficiency of SERS detection and the reproducibility of SERS signals at low concentrations. The width of the line focus is matched to the width of the sample capillary from which the analyte elutes under hydrodynamic focusing conditions, allowing for increased collection across the SERS substrate while maintaining the power density below the damage threshold at any specific point. We show that a 4× increase in power spread across the line increases the signal-to-noise ratio by a factor of 2 for a variety of analytes, such as rhodamine 6G, amino acids, and lipid vesicles, without any detectable photodamage. COMSOL simulations and Raman maps elucidate the hydrodynamic focusing properties of the flow cell, providing a clearer picture of the confinement effects at the surface where the sample exits the capillary. The lipid vesicle results suggest that the combination of hydrodynamic focusing and increased optical collection enables the reproducible detection of rare events, in this case individual lipid vesicles.

  16. Accurate means of detecting and characterizing abnormal patterns of ventricular activation by phase image analysis

    SciTech Connect

    Botvinick, E.H.; Frais, M.A.; Shosa, D.W.; O'Connell, J.W.; Pacheco-Alvarez, J.A.; Scheinman, M.; Hattner, R.S.; Morady, F.; Faulkner, D.B.

    1982-08-01

    The ability of scintigraphic phase image analysis to characterize patterns of abnormal ventricular activation was investigated. The pattern of phase distribution and sequential phase changes over both right and left ventricular regions of interest were evaluated in 16 patients with normal electrical activation and wall motion and compared with those in 8 patients with an artificial pacemaker and 4 patients with sinus rhythm with the Wolff-Parkinson-White syndrome and delta waves. Normally, the site of earliest phase angle was seen at the base of the interventricular septum, with sequential change affecting the body of the septum and the cardiac apex and then spreading laterally to involve the body of both ventricles. The site of earliest phase angle was located at the apex of the right ventricle in seven patients with a right ventricular endocardial pacemaker and on the lateral left ventricular wall in one patient with a left ventricular epicardial pacemaker. In each case the site corresponded exactly to the position of the pacing electrode as seen on posteroanterior and left lateral chest X-ray films, and sequential phase changes spread from the initial focus to affect both ventricles. In each of the patients with the Wolff-Parkinson-White syndrome, the site of earliest ventricular phase angle was located, and it corresponded exactly to the site of the bypass tract as determined by endocardial mapping. In this way, four bypass pathways, two posterior left paraseptal, one left lateral and one right lateral, were correctly localized scintigraphically. On the basis of the sequence of mechanical contraction, phase image analysis provides an accurate noninvasive method of detecting abnormal foci of ventricular activation.

  17. Basic Characteristics of a Macroscopic Measure for Detecting Abnormal Changes in a Multiagent System

    PubMed Central

    Kinoshita, Tetsuo

    2015-01-01

    Multiagent application systems must deal with various changes in both the system and the system environment at runtime. Generally, such changes have undesirable negative effects on the system. To manage and control the system, it is important to observe and detect negative effects using an appropriate observation function of the system’s behavior. This paper focuses on the design of this function and proposes a new macroscopic measure with which to observe behavioral characteristics of a runtime multiagent system. The proposed measure is designed as the variance of fluctuation of a macroscopic activity factor of the whole system, based on theoretical analysis of the macroscopic behavioral model of a multiagent system. Experiments are conducted to investigate basic characteristics of the proposed measure, using a test bed system. The results of experiments show that the proposed measure reacts quickly and increases drastically in response to abnormal changes in the system. Hence, the proposed measure is considered a measure that can be used to detect undesirable changes in a multiagent system. PMID:25897499

  18. Model observer design for detecting multiple abnormalities in anatomical background images

    NASA Astrophysics Data System (ADS)

    Wen, Gezheng; Markey, Mia K.; Park, Subok

    2016-03-01

    As psychophysical studies are resource-intensive to conduct, model observers are commonly used to assess and optimize medical imaging quality. Existing model observers were typically designed to detect at most one signal. However, in clinical practice, there may be multiple abnormalities in a single image set (e.g., multifocal and multicentric breast cancers (MMBC)), which can impact treatment planning. Prevalence of signals can be different across anatomical regions, and human observers do not know the number or location of signals a priori. As new imaging techniques have the potential to improve multiple-signal detection (e.g., digital breast tomosynthesis may be more effective for diagnosis of MMBC than planar mammography), image quality assessment approaches addressing such tasks are needed. In this study, we present a model-observer mechanism to detect multiple signals in the same image dataset. To handle the high dimensionality of images, a novel implementation of partial least squares (PLS) was developed to estimate different sets of efficient channels directly from the images. Without any prior knowledge of the background or the signals, the PLS channels capture interactions between signals and the background which provide discriminant image information. Corresponding linear decision templates are employed to generate both image-level and location-specific scores on the presence of signals. Our preliminary results show that the model observer using PLS channels, compared to our first attempts with Laguerre-Gauss channels, can achieve high performance with a reasonably small number of channels, and the optimal design of the model observer may vary as the tasks of clinical interest change.

  19. The Evaluation of a Pulmonary Display to Detect Adverse Respiratory Events Using High Resolution Human Simulator

    PubMed Central

    Wachter, S. Blake; Johnson, Ken; Albert, Robert; Syroid, Noah; Drews, Frank; Westenskow, Dwayne

    2006-01-01

    Objective Authors developed a picture-graphics display for pulmonary function to present typical respiratory data used in perioperative and intensive care environments. The display utilizes color, shape and emergent alerting to highlight abnormal pulmonary physiology. The display serves as an adjunct to traditional operating room displays and monitors. Design To evaluate the prototype, nineteen clinician volunteers each managed four adverse respiratory events and one normal event using a high-resolution patient simulator which included the new displays (intervention subjects) and traditional displays (control subjects). Between-group comparisons included (i) time to diagnosis and treatment for each adverse respiratory event; (ii) the number of unnecessary treatments during the normal scenario; and (iii) self-reported workload estimates while managing study events. Measurements Two expert anesthesiologists reviewed video-taped transcriptions of the volunteers to determine time to treat and time to diagnosis. Time values were then compared between groups using a Mann-Whitney-U Test. Estimated workload for both groups was assessed using the NASA-TLX and compared between groups using an ANOVA. P-values < 0.05 were considered significant. Results Clinician volunteers detected and treated obstructed endotracheal tubes and intrinsic PEEP problems faster with graphical rather than conventional displays (p < 0.05). During the normal scenario simulation, 3 clinicians using the graphical display, and 5 clinicians using the conventional display gave unnecessary treatments. Clinician-volunteers reported significantly lower subjective workloads using the graphical display for the obstructed endotracheal tube scenario (p < 0.001) and the intrinsic PEEP scenario (p < 0.03). Conclusion Authors conclude that the graphical pulmonary display may serve as a useful adjunct to traditional displays in identifying adverse respiratory events. PMID:16929038

  20. Detecting and characterising ramp events in wind power time series

    NASA Astrophysics Data System (ADS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-12-01

    In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain.

  1. Detecting Rare Events in the Time-Domain

    SciTech Connect

    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. Detecting Tidal Disruption Events (TDEs) with the Einstein Probe

    NASA Astrophysics Data System (ADS)

    Yuan, W.; Komossa, S.; Zhang, C.; Feng, H.; Zhang, S.; Osborne, J.; O'Brien, P.; Watson, M.; Fraser, G.

    2014-07-01

    Stars are tidally disrupted and accreted when they approach supermassive black holes (SMBHs) closely, producing a flare of electromagnetic radiation. The majority of the (approximately two dozen) tidal disruption events (TDEs) identified so far have been discovered by their luminous, transient X-ray emission. Once TDEs are detected in much larger numbers, in future dedicated transient surveys, a wealth of new applications will become possible. Including (1) TDE rate measurements in dependence of host galaxy types, (2) an assessment of the population of IMBHs, and (3) new probes of general relativity and accretion processes. Here, we present the proposed X-ray mission Einstein Probe}, which aims at detecting TDEs in large numbers. The mission consists of a wide-field micro-pore Lobster-eye imager (60deg x 60deg, or ˜1 ster), and is designed to carry out an all-sky transient survey at energies of 0.5-4 keV. It will also carry an X-ray telescope of the same micro-pore optics for follow-ups, with a smaller field-of-view. It will be capable of issuing public transient alerts rapidly.

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Apparatus and method for detecting full-capture radiation events

    DOEpatents

    Odell, Daniel M. C.

    1994-01-01

    An apparatus and method for sampling the output signal of a radiation detector and distinguishing full-capture radiation events from Compton scattering events. The output signal of a radiation detector is continuously sampled. The samples are converted to digital values and input to a discriminator where samples that are representative of events are identified. The discriminator transfers only event samples, that is, samples representing full-capture events and Compton events, to a signal processor where the samples are saved in a three-dimensional count matrix with time (from the time of onset of the pulse) on the first axis, sample pulse current amplitude on the second axis, and number of samples on the third axis. The stored data are analyzed to separate the Compton events from full-capture events, and the energy of the full-capture events is determined without having determined the energies of any of the individual radiation detector events.

  5. Detecting and mitigating abnormal events in large scale networks: budget constrained placement on smart grids

    SciTech Connect

    Santhi, Nandakishore; Pan, Feng

    2010-10-19

    Several scenarios exist in the modern interconnected world which call for an efficient network interdiction algorithm. Applications are varied, including various monitoring and load shedding applications on large smart energy grids, computer network security, preventing the spread of Internet worms and malware, policing international smuggling networks, and controlling the spread of diseases. In this paper we consider some natural network optimization questions related to the budget constrained interdiction problem over general graphs, specifically focusing on the sensor/switch placement problem for large-scale energy grids. Many of these questions turn out to be computationally hard to tackle. We present a particular form of the interdiction question which is practically relevant and which we show as computationally tractable. A polynomial-time algorithm will be presented for solving this problem.

  6. Balloon-Borne Infrasound Detection of Energetic Bolide Events

    NASA Astrophysics Data System (ADS)

    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. Rare-event detection and process control for a biomedical application

    NASA Astrophysics Data System (ADS)

    Kegelmeyer, Laura N.

    1990-05-01

    Medical researchers are seeking a method for detecting chromosomal abnormalities in unborn children without requiring invasive procedures such as anmiocentesis. Software has been developed to utilize a light microscope to detect fetal cells that occur with very low frequency in a sample of maternal blood. This rare event detection involves dividing a microscope slide containing a maternal blood sample into as many as 40,000 fields, automatically focusing on each field-of-view, and searching for fetal cells. Size and shape information is obtained by calculating a figure of merit through various binary operations and is used to discriminate fetal cells from noise and artifacts. Once the rare fetal cells are located, the slide is automatically rescanned to count the total number of cells on the slide. Binary operations and image processing hardware are used as much as possible to reduce the total amount of time to analyze one slide. Current runtime for scoring one full slide is about four hours, with motorized stage movement and focusing being the speed-limiting factors. Fetal cells occurring with a frequency of less than 1 in 200,000 maternal cells have been consistently found with this system.

  8. DASAF: An R Package for Deep Sequencing-Based Detection of Fetal Autosomal Abnormalities from Maternal Cell-Free DNA

    PubMed Central

    Tang, Xiaoyan; Qiu, Feng; Tao, Chunmei; Gao, Junhui; Ma, Mengmeng; Zhong, Tingyan; Cai, JianPing; Li, Yixue

    2016-01-01

    Background. With the development of massively parallel sequencing (MPS), noninvasive prenatal diagnosis using maternal cell-free DNA is fast becoming the preferred method of fetal chromosomal abnormality detection, due to its inherent high accuracy and low risk. Typically, MPS data is parsed to calculate a risk score, which is used to predict whether a fetal chromosome is normal or not. Although there are several highly sensitive and specific MPS data-parsing algorithms, there are currently no tools that implement these methods. Results. We developed an R package, detection of autosomal abnormalities for fetus (DASAF), that implements the three most popular trisomy detection methods—the standard Z-score (STDZ) method, the GC correction Z-score (GCCZ) method, and the internal reference Z-score (IRZ) method—together with one subchromosome abnormality identification method (SCAZ). Conclusions. With the cost of DNA sequencing declining and with advances in personalized medicine, the demand for noninvasive prenatal testing will undoubtedly increase, which will in turn trigger an increase in the tools available for subsequent analysis. DASAF is a user-friendly tool, implemented in R, that supports identification of whole-chromosome as well as subchromosome abnormalities, based on maternal cell-free DNA sequencing data after genome mapping. PMID:27437397

  9. Automatic detection of volcano-seismic events by modeling state and event duration in hidden Markov models

    NASA Astrophysics Data System (ADS)

    Bhatti, Sohail Masood; Khan, Muhammad Salman; Wuth, Jorge; Huenupan, Fernando; Curilem, Millaray; Franco, Luis; Yoma, Nestor Becerra

    2016-09-01

    In this paper we propose an automatic volcano event detection system based on Hidden Markov Model (HMM) with state and event duration models. Since different volcanic events have different durations, therefore the state and whole event durations learnt from the training data are enforced on the corresponding state and event duration models within the HMM. Seismic signals from the Llaima volcano are used to train the system. Two types of events are employed in this study, Long Period (LP) and Volcano-Tectonic (VT). Experiments show that the standard HMMs can detect the volcano events with high accuracy but generates false positives. The results presented in this paper show that the incorporation of duration modeling can lead to reductions in false positive rate in event detection as high as 31% with a true positive accuracy equal to 94%. Further evaluation of the false positives indicate that the false alarms generated by the system were mostly potential events based on the signal-to-noise ratio criteria recommended by a volcano expert.

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

    PubMed Central

    Lawhern, Vernon; Hairston, W. David; Robbins, Kay

    2013-01-01

    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. PMID:23638169

  11. Detection of Local/Regional Events in Kuwait Using Next-Generation Detection Algorithms

    SciTech Connect

    Gok, M. Rengin; Al-Jerri, Farra; Dodge, Douglas; Al-Enezi, Abdullah; Hauk, Terri; Mellors, R.

    2014-12-10

    Seismic networks around the world use conventional triggering algorithms to detect seismic signals in order to locate local/regional seismic events. Kuwait National Seismological Network (KNSN) of Kuwait Institute of Scientific Research (KISR) is operating seven broad-band and short-period three-component stations in Kuwait. The network is equipped with Nanometrics digitizers and uses Antelope and Guralp acquisition software for processing and archiving the data. In this study, we selected 10 days of archived hourly-segmented continuous data of five stations (Figure 1) and 250 days of continuous recording at MIB. For the temporary deployment our selection criteria was based on KNSN catalog intensity for the period of time we test the method. An autonomous event detection and clustering framework is employed to test a more complete catalog of this short period of time. The goal is to illustrate the effectiveness of the technique and pursue the framework for longer period of time.

  12. Adverse drug events and medication errors: detection and classification methods.

    PubMed

    Morimoto, T; Gandhi, T K; Seger, A C; Hsieh, T C; Bates, D W

    2004-08-01

    Investigating the incidence, type, and preventability of adverse drug events (ADEs) and medication errors is crucial to improving the quality of health care delivery. ADEs, potential ADEs, and medication errors can be collected by extraction from practice data, solicitation of incidents from health professionals, and patient surveys. Practice data include charts, laboratory, prescription data, and administrative databases, and can be reviewed manually or screened by computer systems to identify signals. Research nurses, pharmacists, or research assistants review these signals, and those that are likely to represent an ADE or medication error are presented to reviewers who independently categorize them into ADEs, potential ADEs, medication errors, or exclusions. These incidents are also classified according to preventability, ameliorability, disability, severity, stage, and responsible person. These classifications, as well as the initial selection of incidents, have been evaluated for agreement between reviewers and the level of agreement found ranged from satisfactory to excellent (kappa = 0.32-0.98). The method of ADE and medication error detection and classification described is feasible and has good reliability. It can be used in various clinical settings to measure and improve medication safety.

  13. Using REDItools to Detect RNA Editing Events in NGS Datasets.

    PubMed

    Picardi, Ernesto; D'Erchia, Anna Maria; Montalvo, Antonio; Pesole, Graziano

    2015-03-09

    RNA editing is a post-transcriptional/co-transcriptional molecular phenomenon whereby a genetic message is modified from the corresponding DNA template by means of substitutions, insertions, and/or deletions. It occurs in a variety of organisms and different cellular locations through evolutionally and biochemically unrelated proteins. RNA editing has a plethora of biological effects including the modulation of alternative splicing and fine-tuning of gene expression. RNA editing events by base substitutions can be detected on a genomic scale by NGS technologies through the REDItools package, an ad hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq data or RNA-Seq data alone. REDItools implement effective filters to minimize biases due to sequencing errors, mapping errors, and SNPs. The package is freely available at Google Code repository (http://code.google.com/p/reditools/) and released under the MIT license. In the present unit we show three basic protocols corresponding to three main REDItools scripts.

  14. Visual traffic surveillance framework: classification to event detection

    NASA Astrophysics Data System (ADS)

    Ambardekar, Amol; Nicolescu, Mircea; Bebis, George; Nicolescu, Monica

    2013-10-01

    Visual traffic surveillance using computer vision techniques can be noninvasive, automated, and cost effective. Traffic surveillance systems with the ability to detect, count, and classify vehicles can be employed in gathering traffic statistics and achieving better traffic control in intelligent transportation systems. However, vehicle classification poses a difficult problem as vehicles have high intraclass variation and relatively low interclass variation. Five different object recognition techniques are investigated: principal component analysis (PCA)+difference from vehicle space, PCA+difference in vehicle space, PCA+support vector machine, linear discriminant analysis, and constellation-based modeling applied to the problem of vehicle classification. Three of the techniques that performed well were incorporated into a unified traffic surveillance system for online classification of vehicles, which uses tracking results to improve the classification accuracy. To evaluate the accuracy of the system, 31 min of traffic video containing multilane traffic intersection was processed. It was possible to achieve classification accuracy as high as 90.49% while classifying correctly tracked vehicles into four classes: cars, SUVs/vans, pickup trucks, and buses/semis. While processing a video, our system also recorded important traffic parameters such as the appearance, speed, trajectory of a vehicle, etc. This information was later used in a search assistant tool to find interesting traffic events.

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

    PubMed Central

    Naing, Cho; Aung, Kyan; Ahmed, Syed Imran; Mak, Joon Wah

    2012-01-01

    Background 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 not detected for mefloquine. Further studies are needed to substantiate this. PMID:22936859

  16. Large Time Projection Chambers for Rare Event Detection

    SciTech Connect

    Heffner, M

    2009-11-03

    The Time Projection Chamber (TPC) concept [add ref to TPC section] has been applied to many projects outside of particle physics and the accelerator based experiments where it was initially developed. TPCs in non-accelerator particle physics experiments are principally focused on rare event detection (e.g. neutrino and darkmater experiments) and the physics of these experiments can place dramatically different constraints on the TPC design (only extensions to the traditional TPCs are discussed here). The drift gas, or liquid, is usually the target or matter under observation and due to very low signal rates a TPC with the largest active mass is desired. The large mass complicates particle tracking of short and sometimes very low energy particles. Other special design issues include, efficient light collection, background rejection, internal triggering and optimal energy resolution. Backgrounds from gamma-rays and neutrons are significant design issues in the construction of these TPCs. They are generally placed deep underground to shield from cosmogenic particles and surrounded with shielding to reduce radiation from the local surroundings. The construction materials have to be carefully screened for radiopurity as they are in close contact with the active mass and can be a signification source of background events. The TPC excels in reducing this internal background because the mass inside the fieldcage forms one monolithic volume from which fiducial cuts can be made ex post facto to isolate quiet drift mass, and can be circulated and purified to a very high level. Self shielding in these large mass systems can be significant and the effect improves with density. The liquid phase TPC can obtain a high density at low pressure which results in very good self-shielding and compact installation with a lightweight containment. The down sides are the need for cryogenics, slower charge drift, tracks shorter than the typical electron diffusion, lower energy resolution (e

  17. Transient Evoked Potential in a Critical Event Detection Task.

    DTIC Science & Technology

    1984-02-01

    Vigilance and Discrimination: A Reassessment," Science, 164:326-328, 1969. 38. Fabiani , Monica and others. "Individual Differences in the von Restorff...implies that events which elicit a P300 are more likely to be remembered than events which do not 2-23 .... . . ... invoke a P300 (15:507-510). Fabiani

  18. HPV is detectable in virtually all abnormal cervical cytology samples after reinvestigation of HPV negatives with multiple alternative PCR tests.

    PubMed

    Evans, Mark Francis; Adamson, Christine Stewart-Crawford; Schned, Laura Meredith; St John, Timothy Louis; Leiman, Gladwyn; Ashikaga, Takamaru; Cooper, Kumarasen

    2010-09-01

    The demonstration of human papillomavirus (HPV) in 99.7% of cervical carcinoma surgical specimens from around the world required investigations by multiple alternative polymerase chain reaction (PCR) assays. A similar approach may therefore be necessary to best characterize HPV prevalence and genotype distribution among cervical cytology samples. In an earlier study, 752 of 799 (94.1%) abnormal and 82 of 300 (27.3%) normal cytology specimens tested HPV positive after PCR using GP5+/6+primers. This study has reinvestigated the "HPV negative" abnormal samples (20 atypical squamous cells of undetermined significance, 5 low-grade squamous intraepithelial lesion, 14 atypical squamous cells, cannot exclude HSIL, 6 high-grade squamous intraepithelial lesion) and an age-matched cohort of "HPV negative" normal (negative for an intraepithelial lesion or malignancy) samples by PCR using PGMY09/11, FAP59/64, and LCR-E7 primers. PGMY09/11-GP5+/6+ nested PCR was performed on samples that were HPV negative by PGMY09/11 PCR. After the first 3 assays, HPV was detected in 41 of 45 (91.1%) abnormal and in 10 of 47 (21.3%) normal samples (P<0.0001). Eighteen HPV genotypes were detected and in some samples the genotype that was identified differed between the tests. The nondetection of common HPV genotypes (eg, HPVs 6, 11, 16, and 18) was notable. High-grade histopathology was found for 2 patients with HPV52-positive cytopathology. Combined with our earlier study, HPV (40 different genotypes) is shown in 99.5% of abnormal samples (99.8% inclusive of the nested PCR data). These findings show that HPV genotype and prevalence estimates are dependent on the method(s) of detection and indicate that suboptimal analytical sensitivity for one or more of the less common high-risk HPV genotypes could lead to impaired clinical sensitivity. HPV may be causal in almost every instance of abnormal cervical cytology; however, passenger HPV that is incidental to an abnormality may also have been

  19. Identification of FISH biomarkers to detect chromosome abnormalities associated with prostate adenocarcinoma in tumour and field effect environment

    PubMed Central

    2014-01-01

    Background To reduce sampling error associated with cancer detection in prostate needle biopsies, we explored the possibility of using fluorescence in situ hybridisation (FISH) to detect chromosomal abnormalities in the histologically benign prostate tissue from patients with adenocarcinoma of prostate. Methods Tumour specimens from 33 radical prostatectomy (RP) cases, histologically benign tissue from 17 of the 33 RP cases, and 26 benign prostatic hyperplasia (BPH) control cases were evaluated with Locus Specific Identifier (LSI) probes MYC (8q24), LPL (8p21.22), and PTEN (10q23), as well as with centromere enumerator probes CEP8, CEP10, and CEP7. A distribution of FISH signals in the tumour and histologically benign adjacent tissue was compared to that in BPH specimens using receiver operating characteristic curve analysis. Results The combination of MYC gain, CEP8 Abnormal, PTEN loss or chromosome 7 aneusomy was positive in the tumour area of all of the 33 specimens from patients with adenocarcinomas, and in 88% of adjacent histologically benign regions (15 out of 17) but in only 15% (4 out of 26) of the benign prostatic hyperplasia control specimens. Conclusions A panel of FISH markers may allow detection of genomic abnormalities that associate with adenocarcinoma in the field adjacent to and surrounding the tumour, and thus could potentially indicate the presence of cancer in the specimen even if the cancer focus itself was missed by biopsy and histology review. PMID:24568597

  20. Sonic Hedgehog: A Good Gene Gone Bad? Detection and Treatment of Genetic Abnormalities.

    ERIC Educational Resources Information Center

    Yaich, Lauren E.

    2001-01-01

    Presents a case of a baby born with the genetic condition holoprosencephaly in which students explore the "Sonic hedgehog" gene, signal transduction, and the ethics of body and tissue donation. Presents a two-part assignment that features students writing an informed consent document that explains the science behind this congenital abnormality,…

  1. Intelligent Detection of Abnormal Neonatal Cerebral Haemodynamics in a Neonatal Intensive Care Environment

    DTIC Science & Technology

    2001-10-25

    necessity, with staff demonstrating willingness and interest in their use [2]. Abnormal cerebral haemodynamics is a condition that causes brain death and...vol. 11, 1985, pp:441-449. [4] J.B. McMenamin and J.J. Volpe, “Doppler ultrasonography in the determination of neonatal brain death ”, Ann. Neurol

  2. Detection Method of Three Events to Window and Key Using Light Sensor for Crime Prevention

    NASA Astrophysics Data System (ADS)

    Yamawaki, Akira; Katakami, Takayuki; Kitazono, Yuhki; Serikawa, Seiichi

    The three events to the window and the key occurring when a thief attempts to intrude into the house are detected by the different sensors conventionally. This paper proposes a method detecting the three events by using the simple light-sensor consisting of an infrared LED and a photodiode. In the experiments, the light sensor shows the different tendencies that can detect each event. This fact indicates that our proposal can realize a sensor module more efficiently instead of using different sensors.

  3. Migration Based Event Detection and Automatic P- and S-Phase Picking in Hengill, Southwest Iceland

    NASA Astrophysics Data System (ADS)

    Wagner, F.; Tryggvason, A.; Gudmundsson, O.; Roberts, R.; Bodvarsson, R.; Fehler, M.

    2015-12-01

    Automatic detection of seismic events is a complicated process. Common procedures depend on the detection of seismic phases (e.g. P and S) in single trace analyses and their correct association with locatable point sources. The event detection threshold is thus directly related to the single trace detection threshold. Highly sensitive phase detectors detect low signal-to-noise ratio (S/N) phases but also produce a low percentage of locatable events. Short inter-event times of only a few seconds, which is not uncommon during seismic or volcanic crises, is a complication to any event association algorithm. We present an event detection algorithm based on seismic migration of trace attributes into an a-priori three-dimensional (3D) velocity model. We evaluate its capacity as automatic detector compared to conventional methods. Detecting events using seismic migration removes the need for phase association. The event detector runs on a stack of time shifted traces, which increases S/N and thus allows for a low detection threshold. Detected events come with an origin time and a location estimate, enabling a focused trace analysis, including P- and S-phase recognition, to discard false detections and build a basis for accurate automatic phase picking. We apply the migration based detection algorithm to data from a semi-permanent seismic network at Hengill, an active volcanic region with several geothermal production sites in southwest Iceland. The network includes 26 stations with inter-station distances down to 5 km. Results show a high success rate compared to the manually picked catalogue (up to 90% detected). New detections, that were missed by the standard detection routine, show a generally good ratio of true to false alarms, i.e. most of the new events are locatable.

  4. A role for maternal serum screening in detecting chromosomal abnormalities in fetuses with isolated choroid plexus cysts: a prospective multicentre study.

    PubMed

    Brown, T; Kliewer, M A; Hertzberg, B S; Ruiz, C; Stamper, T H; Rosnes, J; Lucas, A; Wright, L N; Chescheir, N C; Farmer, L; Jordan, S; Kay, H H

    1999-05-01

    A prospective multicentre study was performed to identify patients with fetal choroid plexus cysts and examine the association between choroid plexus cysts and chromosome abnormalities in the context of variables such as maternal age, serum triple-screen results, race, other prenatally-identified fetal anomalies and cyst characteristics. A total of 18 437 scans were performed in 5 centres and 257 fetuses were identified with choroid plexus cysts. Outcome was available on 250 patients, and of these, chromosomal abnormalities were detected in a total of 13 (5.2 per cent) fetuses. 26 patients in the group had additional ultrasound abnormalities, and 8 of these had fetal chromosome abnormalities. Among the 224 patients with isolated choroid plexus cysts, 5 (2.2 per cent) were found to have chromosomal abnormalities. All cases with identified chromosomal abnormalities were associated with an additional risk factor, such as other ultrasound findings, advanced maternal age or abnormal maternal serum triple-screen results.

  5. Solar activity cycle and the incidence of foetal chromosome abnormalities detected at prenatal diagnosis

    NASA Astrophysics Data System (ADS)

    Halpern, Gabrielle J.; Stoupel, Eliahu G.; Barkai, Gad; Chaki, Rina; Legum, Cyril; Fejgin, Moshe D.; Shohat, Mordechai

    1995-06-01

    We studied 2001 foetuses during the period of minimal solar activity of solar cycle 21 and 2265 foetuses during the period of maximal solar activity of solar cycle 22, in all women aged 37 years and over who underwent free prenatal diagnosis in four hospitals in the greater Tel Aviv area. There were no significant differences in the total incidence of chromosomal abnormalities or of trisomy between the two periods (2.15% and 1.8% versus 2.34% and 2.12%, respectively). However, the trend of excessive incidence of chromosomal abnormalities in the period of maximal solar activity suggests that a prospective study in a large population would be required to rule out any possible effect of extreme solar activity.

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

    PubMed

    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.

  7. Brain abnormalities in bipolar disorder detected by quantitative T1ρ mapping.

    PubMed

    Johnson, C P; Follmer, R L; Oguz, I; Warren, L A; Christensen, G E; Fiedorowicz, J G; Magnotta, V A; Wemmie, J A

    2015-02-01

    Abnormal metabolism has been reported in bipolar disorder, however, these studies have been limited to specific regions of the brain. To investigate whole-brain changes potentially associated with these processes, we applied a magnetic resonance imaging technique novel to psychiatric research, quantitative mapping of T1 relaxation in the rotating frame (T1ρ). This method is sensitive to proton chemical exchange, which is affected by pH, metabolite concentrations and cellular density with high spatial resolution relative to alternative techniques such as magnetic resonance spectroscopy and positron emission tomography. Study participants included 15 patients with bipolar I disorder in the euthymic state and 25 normal controls balanced for age and gender. T1ρ maps were generated and compared between the bipolar and control groups using voxel-wise and regional analyses. T1ρ values were found to be elevated in the cerebral white matter and cerebellum in the bipolar group. However, volumes of these areas were normal as measured by high-resolution T1- and T2-weighted magnetic resonance imaging. Interestingly, the cerebellar T1ρ abnormalities were normalized in participants receiving lithium treatment. These findings are consistent with metabolic or microstructural abnormalities in bipolar disorder and draw attention to roles of the cerebral white matter and cerebellum. This study highlights the potential utility of high-resolution T1ρ mapping in psychiatric research.

  8. Clinical utility of a multigated modified anterior projection in the detection of left ventricular inferior and apical wall motion abnormalities

    SciTech Connect

    Polak, J.F.; Bianco, J.A.; Kemper, A.J.; Tow, D.E.

    1982-04-01

    Recent evidence indicates that the left anterior oblique projection (LAO) multigated radionuclide ventriculogram (RVG) underestimates presence and extent of apical and inferior left ventricular (LV) wall motion abnormalities. We investigated, prospectively, the sensitivity and specificity of a modified anterior projection (MAP), which incorporates cephalad tilting. Thirty-three consecutive patients undergoing cardiac catheterization suspected to have coronary artery disease were studied with RVG, using both the MAP and LAO views. LAO views were analyzed using the ejection fraction image (REFI), and the regional ejection fraction (REF) of the inferoapical region. The MAP studies were analyzed using stroke volume image (SVI) to evaluate apical and inferior LV regions. Results were as follows: (Formula: see text), Both intraobserver and interobserver variabilities were comparable to those of conventional angiographic studies used in detection of apical and inferior asynergy. It is concluded that the multigated MAP offers additional information about abnormalities of the LV inferior and apical regions.

  9. Extent of resection of peritumoral diffusion tensor imaging-detected abnormality as a predictor of survival in adult glioblastoma patients.

    PubMed

    Yan, Jiun-Lin; van der Hoorn, Anouk; Larkin, Timothy J; Boonzaier, Natalie R; Matys, Tomasz; Price, Stephen J

    2017-01-01

    OBJECTIVE Diffusion tensor imaging (DTI) has been shown to detect tumor invasion in glioblastoma patients and has been applied in surgical planning. However, the clinical value of the extent of resection based on DTI is unclear. Therefore, the correlation between the extent of resection of DTI abnormalities and patients' outcome was retrospectively reviewed. METHODS A review was conducted of 31 patients with newly diagnosed supratentorial glioblastoma who underwent standard 5-aminolevulinic acid-aided surgery with the aim of maximal resection of the enhancing tumor component. All patients underwent presurgical MRI, including volumetric postcontrast T1-weighted imaging, DTI, and FLAIR. Postsurgical anatomical MR images were obtained within 72 hours of resection. The diffusion tensor was split into an isotropic (p) and anisotropic (q) component. The extent of resection was measured for the abnormal area on the p, q, FLAIR, and postcontrast T1-weighted images. Data were analyzed in relation to patients' outcome using univariate and multivariate Cox regression models controlling for possible confounding factors including age, O(6)-methylguanine-DNA-methyltrans-ferase methylation status, and isocitrate dehydrogenase-1 mutation. RESULTS Complete resection of the enhanced tumor shown on the postcontrast T1-weighted images was achieved in 24 of 31 patients (77%). The mean extent of resection of the abnormal p, q, and FLAIR areas was 57%, 83%, and 59%, respectively. Increased resection of the abnormal p and q areas correlated positively with progression-free survival (p = 0.009 and p = 0.006, respectively). Additionally, a larger, residual, abnormal q volume predicted significantly shorter time to progression (p = 0.008). More extensive resection of the abnormal q and contrast-enhanced area improved overall survival (p = 0.041 and 0.050, respectively). CONCLUSIONS Longer progression-free survival and overall survival were seen in glioblastoma patients in whom more DTI

  10. Cadmium-induced immune abnormality is a key pathogenic event in human and rat models of preeclampsia.

    PubMed

    Zhang, Qiong; Huang, Yinping; Zhang, Keke; Huang, Yanjun; Yan, Yan; Wang, Fan; Wu, Jie; Wang, Xiao; Xu, Zhangye; Chen, Yongtao; Cheng, Xue; Li, Yong; Jiao, Jinyu; Ye, Duyun

    2016-11-01

    With increased industrial development, cadmium is an increasingly important environmental pollutant. Studies have identified various adverse effects of cadmium on human beings. However, the relationships between cadmium pollution and the pathogenesis of preeclampsia remain elusive. The objective of this study is to explore the effects of cadmium on immune system among preeclamptic patients and rats. The results showed that the cadmium levels in the peripheral blood of preeclamptic patients were significantly higher than those observed in normal pregnancy. Based on it, a novel rat model of preeclampsia was established by the intraperitoneal administration of cadmium chloride (CdCl2) (0.125 mg of Cd/kg body weight) on gestational days 9-14. Key features of preeclampsia, including hypertension, proteinuria, placental abnormalities and small foetal size, appeared in pregnant rats after the administration of low-dose of CdCl2. Cadmium increased immunoglobulin production, mainly angiotensin II type 1-receptor-agonistic autoantibodies (AT1-AA), by increasing the expression of activation-induced cytosine deaminase (AID) in B cells. AID is critical for the maturation of antibody and autoantibody responses. In addition, angiotensin II type 1-receptor-agonistic autoantibody, which emerged recently as a potential pathogenic contributor to PE, was responsible for the deposition of complement component 5 (C5) in kidneys of pregnant rats via angiotensin II type 1 receptor (AT1R) activation. C5a is a fragment of C5 that is released during C5 activation. Selectively interfering with C5a signalling by a complement C5a receptor-specific antagonist significantly attenuated hypertension and proteinuria in Cd-injected pregnant rats. Our results suggest that cadmium induces immune abnormalities that may be a key pathogenic contributor to preeclampsia and provide new insights into treatment strategies of preeclampsia.

  11. A model of human event detection in multiple process monitoring situations

    NASA Technical Reports Server (NTRS)

    Greenstein, J. S.; Rouse, W. B.

    1978-01-01

    It is proposed that human decision making in many multi-task situations might be modeled in terms of the manner in which the human detects events related to his tasks and the manner in which he allocates his attention among his tasks once he feels events have occurred. A model of human event detection performance in such a situation is presented. An assumption of the model is that, in attempting to detect events, the human generates the probability that events have occurred. Discriminant analysis is used to model the human's generation of these probabilities. An experimental study of human event detection performance in a multiple process monitoring situation is described and the application of the event detection model to this situation is addressed. The experimental study employed a situation in which subjects simulataneously monitored several dynamic processes for the occurrence of events and made yes/no decisions on the presence of events in each process. Input to the event detection model of the information displayed to the experimental subjects allows comparison of the model's performance with the performance of the subjects.

  12. Method and apparatus for detecting and determining event characteristics with reduced data collection

    NASA Technical Reports Server (NTRS)

    Totman, Peter D. (Inventor); Everton, Randy L. (Inventor); Egget, Mark R. (Inventor); Macon, David J. (Inventor)

    2007-01-01

    A method and apparatus for detecting and determining event characteristics such as, for example, the material failure of a component, in a manner which significantly reduces the amount of data collected. A sensor array, including a plurality of individual sensor elements, is coupled to a programmable logic device (PLD) configured to operate in a passive state and an active state. A triggering event is established such that the PLD records information only upon detection of the occurrence of the triggering event which causes a change in state within one or more of the plurality of sensor elements. Upon the occurrence of the triggering event, the change in state of the one or more sensor elements causes the PLD to record in memory which sensor element detected the event and at what time the event was detected. The PLD may be coupled with a computer for subsequent downloading and analysis of the acquired data.

  13. Detection of severe weather events using new remote sensing methods

    NASA Astrophysics Data System (ADS)

    Choy, S.; Wang, C.; Zhang, K.; Kuleshov, Y.

    2012-04-01

    The potential of using ground- and space-based Global Positioning System (GPS) observations for studying severe weather events is presented using the March 2010 Melbourne storm as a case study. This event generated record rainfall and flash flooding across the state of Victoria, Australia. The Victorian GPSnet is the only state-wide and densest ground-based GPS infrastructure in Australia. This provides a unique opportunity to study the spatial and temporal variations in precipitable water vapour (PWV) as the storm passed over the network. The results show strong spatial and temporal correlation between variations of the ground-based GPS-PWV estimates and the thunderstorm passage. This finding demonstrates that the ground-based GPS techniques can supplement conventional meteorological observations in studying, monitoring, and potentially predicting severe weather events. The advantage of using ground-based GPS technique is that it is capable of providing continuous observation of the storm passage with high temporal resolution; while the spatial resolution of the distribution of water vapour is dependent on the geographical location and density of the GPS stations. The results from the space-based GPS radio occultation (RO) technique, on the other hand, are not as robust. Although GPS RO can capture the dynamics of the atmosphere with high vertical resolution, its limited geographical coverage in a local region and its temporal resolution over a short period of time raise an important question about its potential for monitoring severe weather events, particularly local thunderstorms which have a relatively short life-span. GPS RO technique will be more suitable for long-term climatology studies over a large area. It is anticipated that the findings from this study will encourage further research into using GPS meteorology technique for monitoring and forecasting severe weather events in the Australian region.

  14. Detection of structural and numerical chomosomal abnormalities by ACM-FISH analysis in sperm of oligozoospermic infertility patients

    SciTech Connect

    Schmid, T E; Brinkworth, M H; Hill, F; Sloter, E; Kamischke, A; Marchetti, F; Nieschlag, E; Wyrobek, A J

    2003-11-10

    Modern reproductive technologies are enabling the treatment of infertile men with severe disturbances of spermatogenesis. The possibility of elevated frequencies of genetically and chromosomally defective sperm has become an issue of concern with the increased usage of intracytoplasmic sperm injection (ICSI), which can enable men with severely impaired sperm production to father children. Several papers have been published about aneuploidy in oligozoospermic patients, but relatively little is known about chromosome structural aberrations in the sperm of these patients. We examined sperm from infertile, oligozoospermic individuals for structural and numerical chromosomal abnormalities using a multicolor ACM FISH assay that utilizes DNA probes specific for three regions of chromosome 1 to detect human sperm that carry numerical chromosomal abnormalities plus two categories of structural aberrations: duplications and deletions of 1pter and 1cen, and chromosomal breaks within the 1cen-1q12 region. There was a significant increase in the average frequencies of sperm with duplications and deletions in the infertility patients compared with the healthy concurrent controls. There was also a significantly elevated level of breaks within the 1cen-1q12 region. There was no evidence for an increase in chromosome-1 disomy, or in diploidy. Our data reveal that oligozoospermia is associated with chromosomal structural abnormalities suggesting that, oligozoospermic men carry a higher burden of transmissible, chromosome damage. The findings raise the possibility of elevated levels of transmissible chromosomal defects following ICSI treatment.

  15. Congenital Abnormalities

    MedlinePlus

    ... Listen Español Text Size Email Print Share Congenital Abnormalities Page Content Article Body About 3% to 4% ... of congenital abnormalities earlier. 5 Categories of Congenital Abnormalities Chromosome Abnormalities Chromosomes are structures that carry genetic ...

  16. A Dynamically Configurable Log-based Distributed Security Event Detection Methodology using Simple Event Correlator

    DTIC Science & Technology

    2010-06-01

    from SANS Whitepaper - "... Detecting Attacks on Web Applications from Log Files" #look for image tags type=Single continue=TakeNext ptype=RegExp...shellcmd /home/user/sec -2.5.3/ common/syslogclient "... Synthetic : " "$2|$1|xss detected in image tag: $3" #send the raw log type=Single ptype=RegExp...Expressions taken from SANS Whitepaper - "... Detecting Attacks on Web Applications from Log Files" #look for image tags type=Single continue=TakeNext

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

    PubMed

    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.

  18. 76 FR 22925 - Assumption Buster Workshop: Abnormal Behavior Detection Finds Malicious Actors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-25

    ... card. Fraud detection algorithms (based on user behavior models) and procedures immediately set off... unusual behavior on the part of authorized users. The fraud detection algorithms use the financial... sets of values to be analyzed with well understood algorithms. For example, credit card purchases...

  19. Functional brain abnormalities in psychiatric disorders: neural mechanisms to detect and resolve cognitive conflict and interference.

    PubMed

    Melcher, Tobias; Falkai, Peter; Gruber, Oliver

    2008-11-01

    In the present article, we review functional neuroimaging studies on interference processing and performance monitoring in three groups of psychiatric disorders, (1) mood disorders, (2) schizophrenia, and (3) obsessive-compulsive disorder (OCD). Ad (1) Behavioral performance measures suggest an impaired interference resolution capability in symptomatic bipolar disorder patients. A series of neuroimaging analyses found alterations in the ACC-DLPFC system in mood disorder (unipolar depressed and bipolar) patients, putatively reflective of an abnormal interplay of monitoring and executive neurocognitive functions. Other studies of euthymic bipolar patients showed relatively decreased interference-related activation in rostroventral PFC which conceivably underlies defective inhibitory control. Ad (2) Behavioral Stroop studies revealed a specific performance pattern of schizophrenia patients (normal RT interference but increased error interference and RT facilitation) suggestive of a deficit in ignoring irrelevant (word) information. Moreover, reduced/absent behavioral post-error and post-conflict adaptation effects suggest alterations in performance monitoring and/or adjustment capability in these patients. Neuroimaging findings converge to suggest a disorder-related abnormal neurophysiology in ACC which consistently showed conflict- and error-related hypoactivation that, however, appeared to be modulated by different factors. Moreover, studies suggest a specific deficit in context processing in schizophrenia, evidently related to activation reduction in DLPFC. Ad (3) Behavioral findings provide evidence for impaired interference resolution in OCD. Neuroimaging results consistently showed conflict- and error-related ACC hyperactivation which--conforming OCD pathogenesis models--can be conclusively interpreted as reflecting overactive performance monitoring. Taken together, interference resolution and performance monitoring appeared to be fruitful concepts in the

  20. Power System Extreme Event Detection: The VulnerabilityFrontier

    SciTech Connect

    Lesieutre, Bernard C.; Pinar, Ali; Roy, Sandip

    2007-10-17

    In this work we apply graph theoretic tools to provide aclose bound on a frontier relating the number of line outages in a gridto the power disrupted by the outages. This frontier describes theboundary of a space relating the possible severity of a disturbance interms of power disruption, from zero to some maximum on the boundary, tothe number line outages involved in the event. We present the usefulnessof this analysis with a complete analysis of a 30 bus system, and presentresults for larger systems.

  1. Data-mining-based detection of adverse drug events.

    PubMed

    Chazard, Emmanuel; Preda, Cristian; Merlin, Béatrice; Ficheur, Grégoire; Beuscart, Régis

    2009-01-01

    Every year adverse drug events (ADEs) are known to be responsible for 98,000 deaths in the USA. Classical methods rely on report statements, expert knowledge, and staff operated record review. One of our objectives, in the PSIP project framework, is to use data mining (e.g., decision trees) to electronically identify situations leading to risk of ADEs. 10,500 hospitalization records from Denmark and France were used. 500 rules were automatically obtained, which are currently being validated by experts. A decision support system to prevent ADEs is then to be developed. The article examines a decision tree and the rules in the field of vitamin K antagonists.

  2. Nonthreshold-based event detection for 3d environment monitoring in sensor networks

    SciTech Connect

    Li, M.; Liu, Y.H.; Chen, L.

    2008-12-15

    Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.

  3. Robust algorithmic detection of the developed cardiac pathologies and emerging or transient abnormalities from short periods of RR data

    NASA Astrophysics Data System (ADS)

    Gavrishchaka, Valeriy V.; Senyukova, Olga

    2011-06-01

    Numerous research efforts and clinical testing have confirmed validity of heart rate variability (HRV) analysis as one of the cardiac diagnostics modalities. The majority of HRV analysis tools currently used in practice are based on linear indicators. Methods from nonlinear dynamics (NLD) provide more natural modeling framework for adaptive biological systems with multiple feedback loops. Compared to linear indicators, many NLD-based measures are much less sensitive to data artifacts and non-stationarity. However, majority of NLD measures require long time series for stable calculation. Similar restrictions also apply for linear indicators. Such requirements could drastically limit practical usability of HRV analysis in many applications, including express diagnostics, early indication of subtle directional changes during personalization of medical treatment, and robust detection of emerging or transient abnormalities. Recently we have illustrated that these challenges could be overcome by using classification framework based on boosting-like ensemble learning techniques that are capable of discovering robust meta-indicators from existing HRV measures and other incomplete empirical knowledge. In this paper we demonstrate universality of such meta-indicators and discuss operational details of their practical usage. Using such pathology examples as congestive heart failure (CHF) and arrhythmias, we show that classifiers trained on short RR segments (down to several minutes) could achieve reasonable classification accuracy (˜80-85% and higher). These indicators calculated from longer RR segments could be applicable for accurate diagnostics with classification accuracy approaching 100%. In addition, it is feasible to discover single "normal-abnormal" meta-classifier capable of detecting multiple abnormalities.

  4. Neuro-evolutionary event detection technique for downhole microseismic surveys

    NASA Astrophysics Data System (ADS)

    Maity, Debotyam; Salehi, Iraj

    2016-01-01

    Recent years have seen a significant increase in borehole microseismic data acquisition programs associated with unconventional reservoir developments such as hydraulic fracturing programs for shale oil and gas. The data so acquired is used for hydraulic fracture monitoring and diagnostics and therefore, the quality of the data in terms of resolution and accuracy has a significant impact on its value to the industry. Borehole microseismic data acquired in such environments typically suffer from propagation effects due to the presence of thin interbedded shale layers as well as noise and interference effects. Moreover, acquisition geometry has significant impact on detectability across portions of the sensor array. Our work focuses on developing robust first arrival detection and pick selection workflow for both P and S waves specifically designed for such environments. We introduce a novel workflow for refinement of picks with immunity towards significant noise artifacts and applicability over data with very low signal-to-noise ratio provided some accurate picks have already been made. This workflow utilizes multi-step hybrid detection and classification routine which makes use of a neural network based autopicker for initial picking and an evolutionary algorithm for pick refinement. We highlight the results from an actual field case study including multiple examples demonstrating immunity towards noise and compare the effectiveness of the workflow with two contemporary autopicking routines without the application of the shared detection/refinement procedure. Finally, we use a windowed waveform cross-correlation based uncertainty estimation method for potential quality control purposes. While the workflow was developed to work with the neural network based autopicker, it can be used with any other traditional autopicker and provides significant improvements in pick detection across seismic gathers.

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

    SciTech Connect

    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.

  6. Multi-Detection Events, Probability Density Functions, and Reduced Location Area

    SciTech Connect

    Eslinger, Paul W.; Schrom, Brian T.

    2016-03-01

    Abstract Several efforts have been made in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) community to assess the benefits of combining detections of radionuclides to improve the location estimates available from atmospheric transport modeling (ATM) backtrack calculations. We present a Bayesian estimation approach rather than a simple dilution field of regard approach to allow xenon detections and non-detections to be combined mathematically. This system represents one possible probabilistic approach to radionuclide event formation. Application of this method to a recent interesting radionuclide event shows a substantial reduction in the location uncertainty of that event.

  7. Detection of intermittent events in atmospheric time series

    NASA Astrophysics Data System (ADS)

    Paradisi, P.; Cesari, R.; Palatella, L.; Contini, D.; Donateo, A.

    2009-04-01

    The modeling approach in atmospheric sciences is based on the assumption that local fluxes of mass, momentum, heat, etc... can be described as linear functions of the local gradient of some intensive property (concentration, flow strain, temperature,...). This is essentially associated with Gaussian statistics and short range (exponential) correlations. However, the atmosphere is a complex dynamical system displaying a wide range of spatial and temporal scales. A global description of the atmospheric dynamics should include a great number of degrees of freedom, strongly interacting on several temporal and spatial scales, thus generating long range (power-law) correlations and non-Gaussian distribution of fluctuations (Lévy flights, Lévy walks, Continuous Time Random Walks) [1]. This is typically associated with anomalous diffusion and scaling, non-trivial memory features and correlation decays and, especially, with the emergence of flux-gradient relationships that are non-linear and/or non-local in time and/or space. Actually, the local flux-gradient relationship is greatly preferred due to a more clear physical meaning, allowing to perform direct comparisons with experimental data, and, especially, to smaller computational costs in numerical models. In particular, the linearity of this relationship allows to define a transport coefficient (e.g., turbulent diffusivity) and the modeling effort is usually focused on this coefficient. However, the validity of the local (and linear) flux-gradient model is strongly dependent on the range of spatial and temporal scales represented by the model and, consequently, by the sub-grid processes included in the flux-gradient relationship. In this work, in order to check the validity of local and linear flux-gradient relationships, an approach based on the concept of renewal critical events [2] is introduced. In fact, in renewal theory [2], the dynamical origin of anomalous behaviour and non-local flux-gradient relation is

  8. Simple Movement and Detection in Discrete Event Simulation

    DTIC Science & Technology

    2005-12-01

    with a description of uniform linear motion in the following section. We will then con- sider the simplest kind of sensing, the “ cookie -cutter.” A... cookie -cutter sensor sees everything that is within its range R, and must be notified at the precise time a target enters it range. In a time-step...simulation, cookie -cutter detection is very easy. Simply compute the distance between the sensor and the target at each time step. If the target is

  9. Detection of liver cancer and abnormal liver tissue by Raman spectroscopy and fluorescence

    NASA Astrophysics Data System (ADS)

    Li, Xiaozhou; Ding, Jianhua; Zhang, Xiujun; Lin, Junxiu; Wang, Deli

    2005-01-01

    In this paper, laser induced human serum Raman spectra of liver cancer are measured. The spectra differences in serum from normal people and liver disease patients are analyzed. For the typical spectrum of normal serum, there are three sharp Raman peaks and relative intensity of Raman peaks excited by 514.5nm is higher than that excited by 488.0nm. For the Raman spectrum of liver cancer serum there are no peaks or very weak Raman peaks at the same positions. Results from more than two hundred case measurements show that clinical diagnostic accuracy is 92.86%. And then, the liver fibrosis and liver cirrhosis are studied applying the technology of LIF. To liver cirrhosis, the shape of Raman peak is similar to normal and fluorescence spectrum is similar to that of liver cancer from statistic data. The experiment indicates that there is notable fluorescence difference between the abnormal and normal liver tissue and have blue shift in fluorescence peak. Except for human serum, we use rats serum for researching either. Compared with results of path al examination, we analyze the spectra of normal cases, hepatic fibrosis and hepatocirrhosis respectively in an attempt to find some difference between them. Red shift of fluorescence peak is observed with disease evolution using 514.5nm excitation of an Ar-ion laser. However, no distinct changes happen with 488.0nm excitation. These results have important reference values to explore the method of laser spectrum diagnosis.

  10. [Methods for early detection of predisposition to abnormal increases in body weight of children and adolescents].

    PubMed

    Ivashchenko, S N

    2014-01-01

    This article presents the results of a special method designed for the early identification of children's and adolescents' propensity for abnormal weight gain. The basis of this technique is the principle of monitoring the actual values of body mass index for each child or young person at the age of dynamic changes in the index of the normal range. The weekly body weight of each child or adolescent who participates in the study is measured and the results are included in a special registry. Measurement of the body weight of the children and adolescents occurs in the morning at the same hour on an empty stomach after use of the toilet and performance of necessary hygiene. Afterwards, the obtained values of their body mass indices are compared with those considered normal for age, according to official data. In cases when the resulting body mass index of a child or young person exceeds the range of normal-for-age values, an in-depth medical examination of the child or adolescent is conducted together with the nature of their food intake and mode of physical activity, which may then be corrected.

  11. Detecting and Locating Seismic Events Without Phase Picks or Velocity Models

    NASA Astrophysics Data System (ADS)

    Arrowsmith, S.; Young, C. J.; Ballard, S.; Slinkard, M.

    2015-12-01

    The standard paradigm for seismic event monitoring is to scan waveforms from a network of stations and identify the arrival time of various seismic phases. A signal association algorithm then groups the picks to form events, which are subsequently located by minimizing residuals between measured travel times and travel times predicted by an Earth model. Many of these steps are prone to significant errors which can lead to erroneous arrival associations and event locations. Here, we revisit a concept for event detection that does not require phase picks or travel time curves and fuses detection, association and location into a single algorithm. Our pickless event detector exploits existing catalog and waveform data to build an empirical stack of the full regional seismic wavefield, which is subsequently used to detect and locate events at a network level using correlation techniques. Because the technique uses more of the information content of the original waveforms, the concept is particularly powerful for detecting weak events that would be missed by conventional methods. We apply our detector to seismic data from the University of Utah Seismograph Stations network and compare our results with the earthquake catalog published by the University of Utah. We demonstrate that the pickless detector can detect and locate significant numbers of events previously missed by standard data processing techniques.

  12. A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

    PubMed Central

    Zhang, Shukui; Chen, Hao; Zhu, Qiaoming

    2014-01-01

    The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690

  13. Rates of mutant and inherited structural cytogenetic abnormalities detected at amniocentesis: results on about 63,000 fetuses.

    PubMed

    Hook, E B; Cross, P K

    1987-01-01

    We report data on diagnoses made on amniotic fluid specimens from 1977 to 1984 as reported to the New York State Chromosome Registry. The rate of all de novo (presumed mutant) abnormalities was about 2 per 1,000 in about 61,000 fetuses in which results are unlikely to be biased by the reason for amniocentesis (except for maternal age). This includes about 0.5 per 1,000 de novo markers, about 0.5 per 1,000 other de novo unbalanced, and about 1.0 per 1,000 de novo balanced rearrangements. In about 55,000 fetuses in which rates of inherited abnormalities could be evaluated without apparent bias, the rate of all inherited rearrangement was about 2.9 per 1,000. This includes about 0.3 per 1,000 inherited markers, about 0.2 per 1,000 other inherited unbalanced rearrangements, and about 2.4 per 1,000 inherited balanced abnormalities. Only mutant markers showed a clear association with maternal age (37.6 +/- 2.7 in 24 cases v. 35.8 +/- 3.6 in controls). Inherited markers did not exhibit this trend (35.8 +/- 2.0 in 12 cases v. 36.4 +/- 2.8 in controls). Paternal age does not appear to account for the association. Among abnormalities of known origin, the ratio of mutant to inherited cases is for markers 64:36, for other unbalanced rearrangements 73:27, and for all balanced abnormalities 29:71. In a subgroup of about 55,000 fetuses, of 263 total abnormalities there were 8 instances of apparent true somatic mosaics (5 mutant and 3 of unknown origin but almost certainly mutant). There were also 20 instances of markers in which presumptive somatic loss had resulted in mosaicism (10 mutant, 6 of unknown origin and 4 inherited) and 13 other instances of mosaicism associated with apparent somatic loss (9 mutant, 3 of unknown origin, and 1 inherited). The sex ratio (Y to non-Y karyotypes) for all abnormalities detected was 228:210 (1.09), not different from controls. Only deletions (5:14) and 'other' unbalanced rearrangements (5:13) exhibited a suggestive deviation from this trend

  14. Detection of Abnormal Muscle Activations during Walking Following Spinal Cord Injury (SCI)

    ERIC Educational Resources Information Center

    Wang, Ping; Low, K. H.; McGregor, Alison H.; Tow, Adela

    2013-01-01

    In order to identify optimal rehabilitation strategies for spinal cord injury (SCI) participants, assessment of impaired walking is required to detect, monitor and quantify movement disorders. In the proposed assessment, ten healthy and seven SCI participants were recruited to perform an over-ground walking test at slow walking speeds. SCI…

  15. Molecular detection of chromosomal abnormalities in germ and somatic cells of aged male mice

    SciTech Connect

    Lowe, X.; Baulch, J.; Quintana, L.; Ramsey, M.; Breneman, J.; Tucker, J.; Wyrobek, A.; Collins, B.; Allen, J.; Holland, N.

    1994-12-31

    Three cytogenetic methods were applied to eight B6C3F1 male mice aged 22.5 - 30.5mo to determine if advanced age was associated with an elevated risk of producing chromosomally defective germinal and somatic cells; sperm aneuploidy analysis by multi-color fluorescence in situ hybridization for three chromosomes, spermatid micronucleus analysis with anti-kinetochore antibodies, and translocation analysis of somatic metaphases by {open_quotes}painting{close_quotes} for two chromosomes. Eight mice aged 2.4mo served as controls. Sperm aneuploidy was measured by multi-color fluorescence in situ co-hybridization with DNA probes specific for chromosomes X, Y and 8, scoring 10,000 cells per animal. The aged group showed significant 1.5 - 2.0 fold increases in the hyperhaploidy phenotypes X-X-8, Y-Y-8, 8-8-Y, and 8-8-X with the greater effects appearing in animals aged >29mo. The aged group also showed significantly increased frequencies of micronucleated spermatids (2.0 vs 0.4 per 1000; all were kinetochore negative). Analysis of metaphase chromosomes from blood by {open_quotes}painting{close_quotes} of chromosomes 2 and 8 yielded 4 translocation per 858 cell-equivalents in the aged group which was a non-significant elevation over 0/202 in controls. Although interpretation must be cautious due to the small number of animals analyzed, these findings suggest that advanced paternal age may be a risk factor for chromosomal abnormalities of reproductive and somatic importance.

  16. Detection of Upper Airway Status and Respiratory Events by a Current Generation Positive Airway Pressure Device

    PubMed Central

    Li, Qing Yun; Berry, Richard B.; Goetting, Mark G.; Staley, Bethany; Soto-Calderon, Haideliza; Tsai, Sheila C.; Jasko, Jeffrey G.; Pack, Allan I.; Kuna, Samuel T.

    2015-01-01

    Study Objectives: To compare a positive airway pressure (PAP) device's detection of respiratory events and airway status during device-detected apneas with events scored on simultaneous polysomnography (PSG). Design: Prospective PSGs of patients with sleep apnea using a new-generation PAP device. Settings: Four clinical and academic sleep centers. Patients: Forty-five patients with obstructive sleep apnea (OSA) and complex sleep apnea (Comp SA) performed a PSG on PAP levels adjusted to induce respiratory events. Interventions: None. Measurements and Results: PAP device data identifying the type of respiratory event and whether the airway during a device-detected apnea was open or obstructed were compared to time-synced, manually scored respiratory events on simultaneous PSG recording. Intraclass correlation coefficients between device-detected and PSG scored events were 0.854 for apnea-hypopnea index (AHI), 0.783 for apnea index, 0.252 for hypopnea index, and 0.098 for respiratory event-related arousals index. At a device AHI (AHIFlow) of 10 events/h, area under the receiver operating characteristic curve was 0.98, with sensitivity 0.92 and specificity 0.84. AHIFlow tended to overestimate AHI on PSG at values less than 10 events/h. The device detected that the airway was obstructed in 87.4% of manually scored obstructive apneas. Of the device-detected apneas with clear airway, a minority (15.8%) were manually scored as obstructive apneas. Conclusions: A device-detected apnea-hypopnea index (AHIFlow) < 10 events/h on a positive airway pressure device is strong evidence of good treatment efficacy. Device-detected airway status agrees closely with the presumed airway status during polysomnography scored events, but should not be equated with a specific type of respiratory event. Citation: Li QY, Berry RB, Goetting MG, Staley B, Soto-Calderon H, Tsai SC, Jasko JG, Pack AI, Kuna ST. Detection of upper airway status and respiratory events by a current generation positive

  17. Event-related complexity analysis and its application in the detection of facial attractiveness.

    PubMed

    Deng, Zhidong; Zhang, Zimu

    2014-11-01

    In this study, an event-related complexity (ERC) analysis method is proposed and used to explore the neural correlates of facial attractiveness detection in the context of a cognitive experiment. The ERC method gives a quantitative index for measuring the diverse brain activation properties that represent the neural correlates of event-related responses. This analysis reveals distinct effects of facial attractiveness processing and also provides further information that could not have been achieved from event-related potential alone.

  18. An adaptive fault-tolerant event detection scheme for wireless sensor networks.

    PubMed

    Yim, Sung-Jib; Choi, Yoon-Hwa

    2010-01-01

    In this paper, we present an adaptive fault-tolerant event detection scheme for wireless sensor networks. Each sensor node detects an event locally in a distributed manner by using the sensor readings of its neighboring nodes. Confidence levels of sensor nodes are used to dynamically adjust the threshold for decision making, resulting in consistent performance even with increasing number of faulty nodes. In addition, the scheme employs a moving average filter to tolerate most transient faults in sensor readings, reducing the effective fault probability. Only three bits of data are exchanged to reduce the communication overhead in detecting events. Simulation results show that event detection accuracy and false alarm rate are kept very high and low, respectively, even in the case where 50% of the sensor nodes are faulty.

  19. Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

    PubMed Central

    Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

    2014-01-01

    Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

  20. MCD for detection of event-based landslides

    NASA Astrophysics Data System (ADS)

    Mondini, A. C.; Chang, K.; Guzzetti, F.

    2011-12-01

    Landslides play an important role in the landscape evolution of mountainous terrain. They also present a socioeconomic problem in terms of risk for people and properties. Landslide inventory maps are not available for many areas affected by slope instabilities, resulting in a lack of primary information for the comprehension of the phenomenon, evaluation of relative landslide statistics, and civil protection operations on large scales. Traditional methods for the preparation of landslide inventory maps are based on the geomorphological interpretation of stereoscopic aerial photography and field surveys. These methods are expensive and time consuming. The exploitation of new remote sensing data, in particular very high resolution (VHR) satellite images, and new dedicated methods present an alternative to the traditional methods and are at the forefront of modern landslide research. Recent studies have showed the possibility to produce accurate landslide maps, reducing the time and resources required for their compilation and systematic update. This paper presents the Multiple Change Detection (MCD) technique, a new method that has shown promising results in landslide mapping. Through supervised or unsupervised classifiers, MCD combines different algorithms of change detection metrics, such as change in Normalized Differential Vegetation Index, spectral angle, principal component analysis, and independent component analysis, and applies them to a multi-temporal set of VHR satellite images to distinguish new landslides from stable areas. MCD has been applied with success in different geographical areas and with different satellite images, suggesting it is a reliable and robust technique. The technique can distinguish old from new landslides and capture runout features. Results of these case studies will be presented in the conference. Also to be presented are new developments of MCD involving the introduction of a priori information on landslide susceptibility within

  1. Seismic network detection probability assessment using waveforms and accounting to event association logic

    NASA Astrophysics Data System (ADS)

    Pinsky, Vladimir; Shapira, Avi

    2017-01-01

    The geographical area where a seismic event of magnitude M ≥ M t is detected by a seismic station network, for a defined probability is derived from a station probability of detection estimated as a function of epicentral distance. The latter is determined from both the bulletin data and the waveforms recorded by the station during the occurrence of the event with and without band-pass filtering. For simulating the real detection process, the waveforms are processed using the conventional Carl Johnson detection and association algorithm. The attempt is presented to account for the association time criterion in addition to the conventional approach adopted by the known PMC method.

  2. Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

    PubMed

    Renjith, Arokia; Manjula, P; Mohan Kumar, P

    2015-01-01

    Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

  3. Atlas-Based Analysis of Neurodevelopment from Infancy to Adulthood Using Diffusion Tensor Imaging and Applications for Automated Abnormality Detection

    PubMed Central

    Faria, Andreia V.; Zhang, Jiangyang; Oishi, Kenichi; Li, Xin; Jiang, Hangyi; Akhter, Kazi; Hermoye, Laurent; Lee, Seung-Koo; Hoon, Alexander; Stachinko, Elaine; Miller, Michael I.; van Zijl, Peter C.M.; Mori, Susumu

    2010-01-01

    Quantification of normal brain maturation is a crucial step in understanding developmental abnormalities in brain anatomy and function. The aim of this study was to develop atlas-based tools for time-dependent quantitative image analysis, and to characterize the anatomical changes that occur from 2 years of age to adulthood. We used large deformation diffeomorphic metric mapping to register diffusion tensor images of normal participants into the common coordinates and used a pre-segmented atlas to segment the entire brain into 176 structures. Both voxel- and atlas-based analyses reported structure that showed distinctive changes in terms of its volume and diffusivity measures. In the white matter, fractional anisotropy (FA) linearly increased with age in logarithmic scale, while diffusivity indices, such as apparent diffusion coefficient (ADC), and axial and radial diffusivity, decreased at a different rate in several regions. The average, variability, and the time course of each measured parameter are incorporated into the atlas, which can be used for automated detection of developmental abnormalities. As a demonstration of future application studies, the brainstem anatomy of cerebral palsy patients was evaluated and the altered anatomy was delineated. PMID:20420929

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

    PubMed

    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.

  5. Comparison of the STA/LTA and power spectral density methods for microseismic event detection

    NASA Astrophysics Data System (ADS)

    Vaezi, Yoones; Van der Baan, Mirko

    2015-12-01

    Robust event detection and picking is a prerequisite for reliable (micro-) seismic interpretations. Detection of weak events is a common challenge among various available event detection algorithms. In this paper we compare the performance of two event detection methods, the short-term average/long-term average (STA/LTA) method, which is the most commonly used technique in industry, and a newly introduced method that is based on the power spectral density (PSD) measurements. We have applied both techniques to a 1-hr long segment of the vertical component of some raw continuous data recorded at a borehole geophone in a hydraulic fracturing experiment. The PSD technique outperforms the STA/LTA technique by detecting a higher number of weak events while keeping the number of false alarms at a reasonable level. The time-frequency representations obtained through the PSD method can also help define a more suitable bandpass filter which is usually required for the STA/LTA method. The method offers thus much promise for automated event detection in industrial, local, regional and global seismological data sets.

  6. Probabilistic approaches to fault detection in networked discrete event systems.

    PubMed

    Athanasopoulou, Eleftheria; Hadjicostis, Christoforos N

    2005-09-01

    In this paper, we consider distributed systems that can be modeled as finite state machines with known behavior under fault-free conditions, and we study the detection of a general class of faults that manifest themselves as permanent changes in the next-state transition functionality of the system. This scenario could arise in a variety of situations encountered in communication networks, including faults occurred due to design or implementation errors during the execution of communication protocols. In our approach, fault diagnosis is performed by an external observer/diagnoser that functions as a finite state machine and which has access to the input sequence applied to the system but has only limited access to the system state or output. In particular, we assume that the observer/diagnoser is only able to obtain partial information regarding the state of the given system at intermittent time intervals that are determined by certain synchronizing conditions between the system and the observer/diagnoser. By adopting a probabilistic framework, we analyze ways to optimally choose these synchronizing conditions and develop adaptive strategies that achieve a low probability of aliasing, i.e., a low probability that the external observer/diagnoser incorrectly declares the system as fault-free. An application of these ideas in the context of protocol testing/classification is provided as an example.

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

    PubMed

    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.

  8. Electroencephalogram (EEG) duration needed to detect abnormalities in angelman syndrome: is 1 hour of overnight recording sufficient?

    PubMed

    Robinson, Althea A; Goldman, Suzanne; Barnes, Gregory; Goodpaster, Luke; Malow, Beth A

    2015-01-01

    Approximately, 90% of patients with Angelman syndrome present with epileptic seizures. Obtaining an electroencephalogram (EEG) with sleep improves the chances of detecting ictal, interictal, and benign abnormal rhythms in Angelman syndrome. However, electroencephalograms, even when obtained during sleep, can be challenging in this population because of tactile sensitivities as well as anxiety related to a novel environment. We tested the hypothesis that 1 hour of sleep on an electroencephalogram would provide as much information as an entire night of electroencephalogram recording, yet more than a routine electroencephalogram conducted during the day. Overnight polysomnograms were collected in 14 children with Angelman syndrome seen at Vanderbilt University. All patients who obtained sleep within the first hour of the overnight electroencephalogram had interictal discharges recorded. Our results show that when sleep is obtained, a 1-hour electroencephalogram yields just as much information as recording an entire night.

  9. Detecting cardiac events - state-of-the-art.

    PubMed

    Collinson, Paul

    2015-11-01

    Cardiac biomarker measurement currently addresses two key questions in patient management: the differential diagnosis of chest pain and the differential diagnosis of the patient with breathlessness. There are currently three major themes in the strategies for the differential diagnosis of chest pain. The first is to undertake troponin measurement in patients selected to be at lower risk, hence to have a low prior probability of disease. The second is the introduction of high-sensitivity cardiac troponin (hs cTn) assays into routine clinical use with measurement at 0 and 3 h from admission. Two other approaches that utilize the diagnostic characteristics of these assays have also been suggested. The first is to use the limit of detection or limit of blank of the assay as the diagnostic discriminant. The second approach is to use the low imprecision of the assay within the reference interval and combine a discriminant value with an absolute rate of change (delta value). The third is the use of additional biomarkers to allow early discharge from the emergency department. The concept is to measure high-sensitivity cardiac troponin plus the extra marker on admission. The role of measurement of B-type natriuretic peptide or its N-terminal prohormone, N-terminal pro-B-type natriuretic peptide, has been accepted and incorporated into guidelines for chronic heart failure for some time. More recently, guidelines for acute heart failure can also recommend a single measurement of B-type natriuretic peptide or N-terminal pro-B-type natriuretic peptide in people presenting with new suspected acute heart failure.

  10. Comparison of nine tractography algorithms for detecting abnormal structural brain networks in Alzheimer’s disease

    PubMed Central

    Zhan, Liang; Zhou, Jiayu; Wang, Yalin; Jin, Yan; Jahanshad, Neda; Prasad, Gautam; Nir, Talia M.; Leonardo, Cassandra D.; Ye, Jieping; Thompson, Paul M.; for the Alzheimer’s Disease Neuroimaging Initiative

    2015-01-01

    Alzheimer’s disease (AD) involves a gradual breakdown of brain connectivity, and network analyses offer a promising new approach to track and understand disease progression. Even so, our ability to detect degenerative changes in brain networks depends on the methods used. Here we compared several tractography and feature extraction methods to see which ones gave best diagnostic classification for 202 people with AD, mild cognitive impairment or normal cognition, scanned with 41-gradient diffusion-weighted magnetic resonance imaging as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. We computed brain networks based on whole brain tractography with nine different methods – four of them tensor-based deterministic (FACT, RK2, SL, and TL), two orientation distribution function (ODF)-based deterministic (FACT, RK2), two ODF-based probabilistic approaches (Hough and PICo), and one “ball-and-stick” approach (Probtrackx). Brain networks derived from different tractography algorithms did not differ in terms of classification performance on ADNI, but performing principal components analysis on networks helped classification in some cases. Small differences may still be detectable in a truly vast cohort, but these experiments help assess the relative advantages of different tractography algorithms, and different post-processing choices, when used for classification. PMID:25926791

  11. Detecting reproductive system abnormalities of broiler breeder roosters at different ages.

    PubMed

    Lagares, M A; Ecco, R; Martins, Nrs; Lara, Ljc; Rocha, Jsr; Vilela, Dar; Barbosa, V M; Mantovani, P F; Braga, Jfv; Preis, I S; Gheller, V A; Cardeal, P C; Baião, N C

    2017-02-01

    The objective of this study was to detect the reasons of rooster's fertility decrease at 50 weeks of age. Therefore, the reproductive system of broiler breeder roosters was laparoscopic, macroscopic and histopathology evaluated, and a comparison of the anatomical aspect with the sperm analysis and birds' age was realized. Cobb roosters (n = 59) were distributed into two groups (30 and 50 weeks). Evaluations were performed with laparoscopy, macroscopy and histopathology, and seminal quality, blood serum testosterone concentration and weight were also determined. The old roosters presented smaller testicle size, higher intensity epididymal lithiasis and lower testicle sperm production, compared to the young roosters. The use of the endoscope could easily distinguish a normal-sized testicle than an atrophic one. Four old roosters with severe testicular atrophy did not show spermatogenesis, although three still had sperm in the ejaculate. This would falsely indicate a wrong diagnosis of normal fertility before the testicular atrophy took place. In conclusion, in addition to the weight increase with age, the testicular atrophy and impairment of sperm production seemed to be the main reason to the decrease in the rooster's fertility at 50 weeks of age. Therefore, the use of the laparoscopy as a way to detect the roosters with testicular atrophy before 50 weeks of age and their removal from them flock could be useful as a diagnostic tool to prevent the birds' fertility loss.

  12. Supervisory control design based on hybrid systems and fuzzy events detection. Application to an oxichlorination reactor.

    PubMed

    Altamiranda, Edmary; Torres, Horacio; Colina, Eliezer; Chacón, Edgar

    2002-10-01

    This paper presents a supervisory control scheme based on hybrid systems theory and fuzzy events detection. The fuzzy event detector is a linguistic model, which synthesizes complex relations between process variables and process events incorporating experts' knowledge about the process operation. This kind of detection allows the anticipation of appropriate control actions, which depend upon the selected membership functions used to characterize the process under scrutiny. The proposed supervisory control scheme was successfully implemented for an oxichlorination reactor in a vinyl monomer plant. This implementation has allowed improvement of reactor stability and reduction of raw material consumption.

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

    DOEpatents

    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.

  14. The results of the flight test of the small satellite "Compass-2" aimed at searching for abnormal phenomena in the ionosphere associated with earthquakes and other natural and man-caused events.

    NASA Astrophysics Data System (ADS)

    Dokukin, Vladimir

    preparation were detected in the dynamic spectrum of the record of the low-frequency wave analyzer obtained over Kamchatka at 21:35:49 on 27.02.2007, i.e., a day prior to the M=4.2 earthquake, which occurred in that area on 28.02.2007. The results of the experimental data analysis have shown that the scientific equipment "Compass - 2" can be used as a basis for the subsequent projects for monitoring of the ionosphere and searching for abnormal phenomena associated with earthquakes and other natural and man-caused events.

  15. Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: detecting, quantifying, and predicting.

    PubMed

    Tang, Xiaoying; Holland, Dominic; Dale, Anders M; Younes, Laurent; Miller, Michael I

    2014-08-01

    This article assesses the feasibility of using shape information to detect and quantify the subcortical and ventricular structural changes in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. We first demonstrate structural shape abnormalities in MCI and AD as compared with healthy controls (HC). Exploring the development to AD, we then divide the MCI participants into two subgroups based on longitudinal clinical information: (1) MCI patients who remained stable; (2) MCI patients who converted to AD over time. We focus on seven structures (amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricles) in 754 MR scans (210 HC, 369 MCI of which 151 converted to AD over time, and 175 AD). The hippocampus and amygdala were further subsegmented based on high field 0.8 mm isotropic 7.0T scans for finer exploration. For MCI and AD, prominent ventricular expansions were detected and we found that these patients had strongest hippocampal atrophy occurring at CA1 and strongest amygdala atrophy at the basolateral complex. Mild atrophy in basal ganglia structures was also detected in MCI and AD. Stronger atrophy in the amygdala and hippocampus, and greater expansion in ventricles was observed in MCI converters, relative to those MCI who remained stable. Furthermore, we performed principal component analysis on a linear shape space of each structure. A subsequent linear discriminant analysis on the principal component values of hippocampus, amygdala, and ventricle leads to correct classification of 88% HC subjects and 86% AD subjects.

  16. Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

    PubMed

    Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

    2016-12-08

    This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

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

    PubMed

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

    2016-01-01

    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.

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

    PubMed Central

    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

  19. Automated detection of abnormalities in paranasal sinus on dental panoramic radiographs by using contralateral subtraction technique based on mandible contour

    NASA Astrophysics Data System (ADS)

    Mori, Shintaro; Hara, Takeshi; Tagami, Motoki; Muramatsu, Chicako; Kaneda, Takashi; Katsumata, Akitoshi; Fujita, Hiroshi

    2013-02-01

    Inflammation in paranasal sinus sometimes becomes chronic to take long terms for the treatment. The finding is important for the early treatment, but general dentists may not recognize the findings because they focus on teeth treatments. The purpose of this study was to develop a computer-aided detection (CAD) system for the inflammation in paranasal sinus on dental panoramic radiographs (DPRs) by using the mandible contour and to demonstrate the potential usefulness of the CAD system by means of receiver operating characteristic analysis. The detection scheme consists of 3 steps: 1) Contour extraction of mandible, 2) Contralateral subtraction, and 3) Automated detection. The Canny operator and active contour model were applied to extract the edge at the first step. At the subtraction step, the right region of the extracted contour image was flipped to compare with the left region. Mutual information between two selected regions was obtained to estimate the shift parameters of image registration. The subtraction images were generated based on the shift parameter. Rectangle regions of left and right paranasal sinus on the subtraction image were determined based on the size of mandible. The abnormal side of the regions was determined by taking the difference between the averages of each region. Thirteen readers were responded to all cases without and with the automated results. The averaged AUC of all readers was increased from 0.69 to 0.73 with statistical significance (p=0.032) when the automated detection results were provided. In conclusion, the automated detection method based on contralateral subtraction technique improves readers' interpretation performance of inflammation in paranasal sinus on DPRs.

  20. Early snowmelt events: detection, distribution, and significance in a major sub-arctic watershed

    NASA Astrophysics Data System (ADS)

    Alese Semmens, Kathryn; Ramage, Joan; Bartsch, Annett; Liston, Glen E.

    2013-03-01

    High latitude drainage basins are experiencing higher average temperatures, earlier snowmelt onset in spring, and an increase in rain on snow (ROS) events in winter, trends that climate models project into the future. Snowmelt-dominated basins are most sensitive to winter temperature increases that influence the frequency of ROS events and the timing and duration of snowmelt, resulting in changes to spring runoff. Of specific interest in this study are early melt events that occur in late winter preceding melt onset in the spring. The study focuses on satellite determination and characterization of these early melt events using the Yukon River Basin (Canada/USA) as a test domain. The timing of these events was estimated using data from passive (Advanced Microwave Scanning Radiometer—EOS (AMSR-E)) and active (SeaWinds on Quick Scatterometer (QuikSCAT)) microwave remote sensors, employing detection algorithms for brightness temperature (AMSR-E) and radar backscatter (QuikSCAT). The satellite detected events were validated with ground station meteorological and hydrological data, and the spatial and temporal variability of the events across the entire river basin was characterized. Possible causative factors for the detected events, including ROS, fog, and positive air temperatures, were determined by comparing the timing of the events to parameters from SnowModel and National Centers for Environmental Prediction North American Regional Reanalysis (NARR) outputs, and weather station data. All melt events coincided with above freezing temperatures, while a limited number corresponded to ROS (determined from SnowModel and ground data) and a majority to fog occurrence (determined from NARR). The results underscore the significant influence that warm air intrusions have on melt in some areas and demonstrate the large temporal and spatial variability over years and regions. The study provides a method for melt detection and a baseline from which to assess future change.

  1. Detection of zones of abnormal strains in structures using Gaussian curvature analysis

    SciTech Connect

    Lisle, R.J.

    1994-12-01

    Whereas some folds, such as those produced by flexural slip, do not theoretically entail strain within the folded surfaces, any surface involving double curvature (such as domes and saddles) cannot form without some stretching or contraction of the bedding. Whether straining of the surfaces is required during folding depends on the three-dimensional fold shape and, in particular, on the Gaussian curvature at points on the folded surface. Using this as a basis, I present a method for detecting zones of anomalously high strain in oil-field structures from Gaussian curvature analysis (GCA) of natural structures. The new method of GCA is suitable for analyzing surfaces that have been mapped seismically. A Gaussian curvature map of the structure is a principal outcome of the analysis and can be used to predict the density of strain-related subseismic structures, such as small-scale fracturing. The Goose Egg dome, near Casper, Wyoming, is analyzed and provides an example of GCA. In this structure, a relationship is observed between fracture densities and Gaussian curvature.

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

    PubMed

    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.

  3. Event Detection and Visualization of Ocean Eddies based on SSH and Velocity Field

    NASA Astrophysics Data System (ADS)

    Matsuoka, Daisuke; Araki, Fumiaki; Inoue, Yumi; Sasaki, Hideharu

    2016-04-01

    Numerical studies of ocean eddies have been progressed using high-resolution ocean general circulation models. In order to understand ocean eddies from simulation results with large amount of information volume, it is necessary to visualize not only distribution of eddies of each time step, but also events or phenomena of eddies. However, previous methods cannot precisely detect eddies, especially, during the events such as eddies' amalgamation, bifurcation. In the present study, we propose a new approach of eddy's detection, tracking and event visualization based on sea surface height (SSH) and velocity field. The proposed method detects eddies region as well as streams and currents region, and classifies detected eddies into several types. By tracking the time-varying change of classified eddies, it is possible to detect not only eddies event such as amalgamation and bifurcation but also the interaction between eddy and ocean current. As a result of visualizing detected eddies and events, we succeeded in creating the movie which enables us to intuitively understand the region of interest.

  4. Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

    NASA Technical Reports Server (NTRS)

    Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.

    2006-01-01

    Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

  5. Neuroradiological advances detect abnormal neuroanatomy underlying neuropsychological impairments: the power of PET imaging.

    PubMed

    Hayempour, Benjamin Jacob; Alavi, Abass

    2013-09-01

    Medical imaging has made a major contribution to cerebral dysfunction due to inherited diseases, as well as injuries sustained with modern living, such as car accidents, falling down, and work-related injuries. These injuries, up until the introduction of sensitive techniques such as positron emission tomography (PET), were overlooked because of heavy reliance on structural imaging techniques such as MRI and CT. These techniques are extremely insensitive for dysfunction caused by such underlying disorders. We believe that the use of these highly powerful functional neuroimaging technologies, such as PET, has substantially improved our ability to assess these patients properly in the clinical setting, to determine their natural course, and to assess the efficacy of various interventional detections. As such the contribution from the evolution of PET technology has substantially improved our knowledge and ability over the past 3 decades to help patients who are the victims of serious deficiencies due to these injuries. In particular, in recent years the use of PET/CT and soon PET/MRI will provide the best option for a structure-function relationship in these patients. We are of the belief that the clinical effectiveness of PET in managing these patients can be translated to the use of this important approach in bringing justice to the victims of many patients who are otherwise uncompensated for disorders that they have suffered without any justification. Therefore, legally opposing views about the relevance of PET in the court system by some research groups may not be justifiable. This has proven to be the case in many court cases, where such imaging techniques have been employed either for criminal or financial compensation purposes in the past 2 decades.

  6. Optimizing Biosurveillance Systems that Use Threshold-based Event Detection Methods

    DTIC Science & Technology

    2009-06-01

    Optimizing Biosurveillance Systems that Use Threshold-based Event Detection Methods Ronald D. Fricker, Jr.∗ and David Banschbach† June 1, 2009...Abstract We describe a methodology for optimizing a threshold detection-based biosurveillance system. The goal is to maximize the system-wide probability of...Using this approach, pub- lic health officials can “tune” their biosurveillance systems to optimally detect various threats, thereby allowing

  7. A new paradigm of dielectric relaxation spectroscopy for non-invasive detection of breast abnormalities: a preliminary feasibility analysis

    NASA Astrophysics Data System (ADS)

    Dhurjaty, Sreeram; Qiu, Yuchen; Tan, Maxine; Qian, Wei; Zheng, Bin

    2016-03-01

    In order to improve efficacy of screening mammography, in recent years, we have been investigating the feasibility of applying a resonance-frequency based electrical impedance spectroscopy (REIS) technology to noninvasively detect breast abnormalities that may lead to the development of cancer in the near-term. Despite promising study-results, we found that REIS suffered from relatively poor reproducibility due to perturbations in electrode placement, contact pressure variation on the breast, as well as variation of the resonating inductor. To overcome this limitation, in this study, we propose and analyze a new paradigm of Dielectric Relaxation Spectroscopy (DRS) that measures polarization-lag of dielectric signals in breast-capacitance when excited by the pulses or sine waves. Unlike conventional DRS that operates using the signals at very high frequencies (GHz) to examine changes in polarization, our new method detects and characterizes the dielectric properties of tissue at low frequencies (<=10 MHz) due to the advent of inexpensive oscillators that are accurate to 1 pico-second (used in GPS receivers) as well as measurement of amplitudes of 1 ppm or better. From theoretical analysis, we have proved that the sensitivity of new DRS in detecting permittivity of water increased by >=80 times as compared to conventional DRS, which operates at frequencies around 4GHz. By analyzing and comparing the relationship between the new DRS and REIS, we found that this DRS has potential advantages in enhancing repeatability from various readings, including temperature-insensitive detection, and yielding higher resolution or sensitivity (up to 100 Femtofarads).

  8. Cooperative object tracking and composite event detection with wireless embedded smart cameras.

    PubMed

    Wang, Youlu; Velipasalar, Senem; Casares, Mauricio

    2010-10-01

    Embedded smart cameras have limited processing power, memory, energy, and bandwidth. Thus, many system- and algorithm-wise challenges remain to be addressed to have operational, battery-powered wireless smart-camera networks. We present a wireless embedded smart-camera system for cooperative object tracking and detection of composite events spanning multiple camera views. Each camera is a CITRIC mote consisting of a camera board and wireless mote. Lightweight and robust foreground detection and tracking algorithms are implemented on the camera boards. Cameras exchange small-sized data wirelessly in a peer-to-peer manner. Instead of transferring or saving every frame or trajectory, events of interest are detected. Simpler events are combined in a time sequence to define semantically higher-level events. Event complexity can be increased by increasing the number of primitives and/or number of camera views they span. Examples of consistently tracking objects across different cameras, updating location of occluded/lost objects from other cameras, and detecting composite events spanning two or three camera views, are presented. All the processing is performed on camera boards. Operating current plots of smart cameras, obtained when performing different tasks, are also presented. Power consumption is analyzed based upon these measurements.

  9. Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects

    PubMed Central

    Ziegler, G.; Ridgway, G.R.; Dahnke, R.; Gaser, C.

    2014-01-01

    Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18–94 years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease. PMID:24742919

  10. [Evaluation study of abnormal detectability with Thurstone and Scheffé (Nakaya) of paired comparison method using chest phantom].

    PubMed

    Mochizuki, Yasuo

    2014-01-01

    Monitors are increasingly being used as diagnostic imaging devices. In this study, using an all-purpose liquid-crystal display (LCD), the rate of detection of abnormalities was investigated using Thurstone's and Scheffé's (Nakaya) paired comparison methods. A chest phantom was prepared as a test sample with acryl and aluminum plates and intensities suggesting small adenocarcinomas. For the acquisition conditions for computed radiography, after setting the baseline at a dose at which the film density of the standard screen-film system at the same as those for the lung, costal bone, and mediastinum, 5 steps of 2-fold serial doses were then set: 1/4, 1/2, 1, 2, and 4. The test sample was observed by 10 students. On the Thurstone scale, detectability decreased with a decrease in the dose in the lung, costal bone, and mediastinum. When the significance of differences between the values at adjacent doses was investigated using the yardstick method, using Scheffé's method revealed a significant difference between the 4- and 2-fold doses and between the 1/2 and 1/4 doses in the pulmonary region. A significant difference was also noted between the baseline and 1/2 doses in the mediastinum. Changes in the order of the scale values may not occur in the intervals in which significant differences were noted using Scheffé's methods.

  11. Automated identification of abnormal metaphase chromosome cells for the detection of chronic myeloid leukemia using microscopic images

    NASA Astrophysics Data System (ADS)

    Wang, Xingwei; Zheng, Bin; Li, Shibo; Mulvihill, John J.; Chen, Xiaodong; Liu, Hong

    2010-07-01

    Karyotyping is an important process to classify chromosomes into standard classes and the results are routinely used by the clinicians to diagnose cancers and genetic diseases. However, visual karyotyping using microscopic images is time-consuming and tedious, which reduces the diagnostic efficiency and accuracy. Although many efforts have been made to develop computerized schemes for automated karyotyping, no schemes can get be performed without substantial human intervention. Instead of developing a method to classify all chromosome classes, we develop an automatic scheme to detect abnormal metaphase cells by identifying a specific class of chromosomes (class 22) and prescreen for suspicious chronic myeloid leukemia (CML). The scheme includes three steps: (1) iteratively segment randomly distributed individual chromosomes, (2) process segmented chromosomes and compute image features to identify the candidates, and (3) apply an adaptive matching template to identify chromosomes of class 22. An image data set of 451 metaphase cells extracted from bone marrow specimens of 30 positive and 30 negative cases for CML is selected to test the scheme's performance. The overall case-based classification accuracy is 93.3% (100% sensitivity and 86.7% specificity). The results demonstrate the feasibility of applying an automated scheme to detect or prescreen the suspicious cancer cases.

  12. Adverse event detection in drug development: recommendations and obligations beyond phase 3.

    PubMed

    Berlin, Jesse A; Glasser, Susan C; Ellenberg, Susan S

    2008-08-01

    Premarketing studies of drugs, although large enough to demonstrate efficacy and detect common adverse events, cannot reliably detect an increased incidence of rare adverse events or events with significant latency. For most drugs, only about 500 to 3000 participants are studied, for relatively short durations, before a drug is marketed. Systems for assessment of postmarketing adverse events include spontaneous reports, computerized claims or medical record databases, and formal postmarketing studies. We briefly review the strengths and limitations of each. Postmarketing surveillance is essential for developing a full understanding of the balance between benefits and adverse effects. More work is needed in analysis of data from spontaneous reports of adverse effects and automated databases, design of ad hoc studies, and design of economically feasible large randomized studies.

  13. On-line Machine Learning and Event Detection in Petascale Data Streams

    NASA Astrophysics Data System (ADS)

    Thompson, David R.; Wagstaff, K. L.

    2012-01-01

    Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data

  14. Utility and limitations of multiplex ligation-dependent probe amplification technique in the detection of cytogenetic abnormalities in products of conception

    PubMed Central

    Saxena, D; Agarwal, M; Gupta, D; Agrawal, S; Das, V; Phadke, SR

    2016-01-01

    Background and Introduction: Chromosomal abnormality is found in about half of first-trimester abortions. Karyotype is the gold standard to detect chromosomal abnormalities. Multiplex ligation-dependent probe amplification (MLPA) offers advantage over karyotype in terms of lower failure rate, faster turnaround time, and much higher resolution than conventional karyotyping and found to be 98% concordant with conventional karyotype. Aim: We performed this study to look for the utility of MLPA in diagnosing chromosomal abnormalities in first-trimester abortions. Materials and Methods: MLPA using subtelomeric SALSA probe sets (P036 and P070) was used to detect cytogenetic abnormalities in products of conception in missed/spontaneous abortions. Results: A total of ninety abortus samples were analyzed by MLPA. Successful results were provided in (67) 74.4% of the cases while no conclusion could be drawn in 25.6% (23) of the cases. Fifty-five (82.1%) cases were cytogenetically normal and 17.9% (12) had some abnormality. Aneuploidy was detected in 8 (66.7%) cases, 3 (25%) had double-segment imbalance, and one (8.3%) had partial aneuploidy. Conclusion: We suggest that MLPA is a good substitute to traditional karyotype. PMID:27763481

  15. Detection of bubble nucleation event in superheated drop detector by the pressure sensor

    NASA Astrophysics Data System (ADS)

    Das, Mala; Biswas, Nilanjan

    2017-01-01

    Superheated drop detector consisting of drops of superheated liquid suspended in polymer or gel matrix is of great demand, mainly because of its insensitivity to ß-particles and ?-rays and also because of the low cost. The bubble nucleation event is detected by measuring the acoustic shock wave released during the nucleation process. 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 study the effect of the size of the drop on the pressure recovery time. Probability of detection of events has increased for larger size of the superheated drops and lesser volume of air in contact with the gel matrix. The exponential decay fitting to the pressure sensor signals shows the dead time for pressure recovery of such a drop detector to be a few microseconds.

  16. Automated detection of apnea/hypopnea events in healthy children polysomnograms: preliminary results.

    PubMed

    Held, Claudio M; Causa, Leonardo; Jaillet, Fabrice; Chamorro, Rodrigo; Garrido, Marcelo; Algarin, Cecilia; Peirano, Patricio

    2013-01-01

    A methodology to detect sleep apnea/hypopnea events in the respiratory signals of polysomnographic recordings is presented. It applies empirical mode decomposition (EMD), Hilbert-Huang transform (HHT), fuzzy logic and signal preprocessing techniques for feature extraction, expert criteria and context analysis. EMD, HHT and fuzzy logic are used for artifact detection and preliminary detection of respiration signal zones with significant variations in the amplitude of the signal; feature extraction, expert criteria and context analysis are used to characterize and validate the respiratory events. An annotated database of 30 all-night polysomnographic recordings, acquired from 30 healthy ten-year-old children, was divided in a training set of 15 recordings (485 sleep apnea/hypopnea events), a validation set of five recordings (109 sleep apnea/hypopnea events), and a testing set of ten recordings (281 sleep apnea/hypopnea events). The overall detection performance on the testing data set was 89.7% sensitivity and 16.3% false-positive rate. The next step is to include discrimination among apneas, hypopneas and respiratory pauses.

  17. Method for detecting binding events using micro-X-ray fluorescence spectrometry

    DOEpatents

    Warner, Benjamin P.; Havrilla, George J.; Mann, Grace

    2010-12-28

    Method for detecting binding events using micro-X-ray fluorescence spectrometry. Receptors are exposed to at least one potential binder and arrayed on a substrate support. Each member of the array is exposed to X-ray radiation. The magnitude of a detectable X-ray fluorescence signal for at least one element can be used to determine whether a binding event between a binder and a receptor has occurred, and can provide information related to the extent of binding between the binder and receptor.

  18. Detection of invisible and crucial events: from seismic fluctuations to the war against terrorism

    NASA Astrophysics Data System (ADS)

    Allegrini, Paolo; Fronzoni, Leone; Grigolini, Paolo; Latora, Vito; Mega, Mirko S.; Palatella, Luigi; Rapisarda, Andrea; Vinciguerra, Sergio

    2004-04-01

    We prove the efficiency of a new method for the detection of crucial events that might have useful applications to the war against terrorism. This has to do with the search for rare but significant events, a theme of research that has been made of extreme importance by the tragedy of September 11. This method is applied here to defining the statistics of seismic main-shocks, as done in cond-mat/0212529. The emphasis here is on the conceptual issues behind the results obtained in cond-mat/0212529 than on geophysics. This discussion suggests that the method has a wider range of validity. We support this general discussion with a dynamic model originally proposed in cond-mat/0107597 for purposes different from geophysical applications. However, it is a case where the crucial events to detect are under our control, thereby making it possible for us to check the accuracy of the method of detection of invisible and crucial events that we propose here for a general purpose, including the war against terrorism. For this model an analytical treatment has been recently found [cond-mat/0209038], supporting the claims that we make in this paper for the accuracy of the method of detection. For the reader's convenience, the results on the seismic fluctuations are suitably reviewed, and discussed in the light of the more general perspective of this paper. We also review the model for seismic fluctuations, proposed in the earlier work of cond-mat/0212529. This model shares with the model of cond-mat/0107597 the property that the crucial events are imbedded in a sea of secondary events, but it allows us to reveal with accuracy the statistics of the crucial events for different mathematical reasons.

  19. Using Atmospheric Circulation Patterns to Detect and Attribute Changes in the Risk of Extreme Climate Events

    NASA Astrophysics Data System (ADS)

    Diffenbaugh, N. S.; Horton, D. E.; Singh, D.; Swain, D. L.; Touma, D. E.; Mankin, J. S.

    2015-12-01

    Because of the high cost of extreme events and the growing evidence that global warming is likely to alter the statistical distribution of climate variables, detection and attribution of changes in the probability of extreme climate events has become a pressing topic for the scientific community, elected officials, and the public. While most of the emphasis has thus far focused on analyzing the climate variable of interest (most often temperature or precipitation, but also flooding and drought), there is an emerging emphasis on applying detection and attribution analysis techniques to the underlying physical causes of individual extreme events. This approach is promising in part because the underlying physical causes (such as atmospheric circulation patterns) can in some cases be more accurately represented in climate models than the more proximal climate variable (such as precipitation). In addition, and more scientifically critical, is the fact that the most extreme events result from a rare combination of interacting causes, often referred to as "ingredients". Rare events will therefore always have a strong influence of "natural" variability. Analyzing the underlying physical mechanisms can therefore help to test whether there have been changes in the probability of the constituent conditions of an individual event, or whether the co-occurrence of causal conditions cannot be distinguished from random chance. This presentation will review approaches to applying detection/attribution analysis to the underlying physical causes of extreme events (including both "thermodynamic" and "dynamic" causes), and provide a number of case studies, including the role of frequency of atmospheric circulation patterns in the probability of hot, cold, wet and dry events.

  20. Developing assessment system for wireless capsule endoscopy videos based on event detection

    NASA Astrophysics Data System (ADS)

    Chen, Ying-ju; Yasen, Wisam; Lee, Jeongkyu; Lee, Dongha; Kim, Yongho

    2009-02-01

    Along with the advancing of technology in wireless and miniature camera, Wireless Capsule Endoscopy (WCE), the combination of both, enables a physician to diagnose patient's digestive system without actually perform a surgical procedure. Although WCE is a technical breakthrough that allows physicians to visualize the entire small bowel noninvasively, the video viewing time takes 1 - 2 hours. This is very time consuming for the gastroenterologist. Not only it sets a limit on the wide application of this technology but also it incurs considerable amount of cost. Therefore, it is important to automate such process so that the medical clinicians only focus on interested events. As an extension from our previous work that characterizes the motility of digestive tract in WCE videos, we propose a new assessment system for energy based events detection (EG-EBD) to classify the events in WCE videos. For the system, we first extract general features of a WCE video that can characterize the intestinal contractions in digestive organs. Then, the event boundaries are identified by using High Frequency Content (HFC) function. The segments are classified into WCE event by special features. In this system, we focus on entering duodenum, entering cecum, and active bleeding. This assessment system can be easily extended to discover more WCE events, such as detailed organ segmentation and more diseases, by using new special features. In addition, the system provides a score for every WCE image for each event. Using the event scores, the system helps a specialist to speedup the diagnosis process.

  1. Alveolar abnormalities

    MedlinePlus

    ... page: //medlineplus.gov/ency/article/001093.htm Alveolar abnormalities To use the sharing features on this page, please enable JavaScript. Alveolar abnormalities are changes in the tiny air sacs in ...

  2. Nail abnormalities

    MedlinePlus

    Beau's lines; Fingernail abnormalities; Spoon nails; Onycholysis; Leukonychia; Koilonychia; Brittle nails ... 2012:chap 71. Zaiac MN, Walker A. Nail abnormalities associated with systemic pathologies. Clin Dermatol . 2013;31: ...

  3. Why conventional detection methods fail in identifying the existence of contamination events.

    PubMed

    Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

    2016-04-15

    Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading.

  4. Improving Magnitude Detection Thresholds Using Multi-Station Multi-Event, and Multi-Phase Methods

    DTIC Science & Technology

    2008-07-31

    applied to different tectonic settings and for what percentage of the seismicity. 111 million correlations were performed on Lg-waves for the events in...a significant detection spike. 30 24. Figure 24. Example of an aftershock (spike at 2400 samples) detected after a mainshock (spike at 1500...false alarms in 36 days for a SNR of 0.32. The significant result of this study is that a correlation detector has more than an order of magnitude

  5. Wenchuan Event Detection And Localization Using Waveform Correlation Coupled With Double Difference

    NASA Astrophysics Data System (ADS)

    Slinkard, M.; Heck, S.; Schaff, D. P.; Young, C. J.; Richards, P. G.

    2014-12-01

    The well-studied Wenchuan aftershock sequence triggered by the May 12, 2008, Ms 8.0, mainshock offers an ideal test case for evaluating the effectiveness of using waveform correlation coupled with double difference relocation to detect and locate events in a large aftershock sequence. We use Sandia's SeisCorr detector to process 3 months of data recorded by permanent IRIS and temporary ASCENT stations using templates from events listed in a global catalog to find similar events in the raw data stream. Then we take the detections and relocate them using the double difference method. We explore both the performance that can be expected with using just a small number of stations, and, the benefits of reprocessing a well-studied sequence such as this one using waveform correlation to find even more events. We benchmark our results against previously published results describing relocations of regional catalog data. Before starting this project, we had examples where with just a few stations at far-regional distances, waveform correlation combined with double difference did and impressive job of detection and location events with precision at the few hundred and even tens of meters level.

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

    PubMed Central

    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

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

    SciTech Connect

    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

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

    PubMed

    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.

  9. Detecting Continuity Violations in Infancy: A New Account and New Evidence from Covering and Tube Events

    ERIC Educational Resources Information Center

    Wang, S.h.; Baillargeon, R.; Paterson, S.

    2005-01-01

    Recent research on infants' responses to occlusion and containment events indicates that, although some violations of the continuity principle are detected at an early age e.g. Aguiar, A., & Baillargeon, R. (1999). 2.5-month-old infants' reasoning about when objects should and should not be occluded. Cognitive Psychology 39, 116-157; Hespos, S.…

  10. Adverse drug reactions – examples of detection of rare events using databases

    PubMed Central

    Chan, Esther W; Liu, Kirin Q L; Chui, Celine S L; Sing, Chor-Wing; Wong, Lisa Y L; Wong, Ian C K

    2015-01-01

    It is recognised that randomised controlled trials are not feasible for capturing rare adverse events. There is an increasing trend towards observational research methodologies using large population-based health databases. These databases offer more scope for adequate sample sizes, allowing for comprehensive patient characterisation and assessment of the associated factors. While direct causality cannot be established and confounders cannot be ignored, databases present an opportunity to explore and quantify rare events. The use of databases for the detection of rare adverse events in the following conditions, sudden death associated with attention deficit hyperactivity disorder (ADHD) treatment, retinal detachment associated with the use of fluoroquinolones and toxic epidermal necrolysis associated with drug exposure, are discussed as examples. In general, rare adverse events tend to have immediate and important clinical implications and may be life-threatening. An understanding of the causative factors is therefore important, in addition to the research methodologies and database platforms that enable the undertaking of the research. PMID:25060360

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  13. (13)N-Ammonia PET/CT Detection of Myocardial Perfusion Abnormalities in Beagle Dogs After Local Heart Irradiation.

    PubMed

    Song, Jianbo; Yan, Rui; Wu, Zhifang; Li, Jianguo; Yan, Min; Hao, Xinzhong; Liu, Jianzhong; Li, Sijin

    2017-04-01

    Our objective was to determine the potential value of (13)N-ammonia PET/CT myocardial perfusion imaging (MPI) for early detection of myocardial perfusion changes induced by radiation damage. Methods: Thirty-six Beagle dogs were randomly divided into a control group (n = 18) or an irradiation group (n = 18). The latter underwent local irradiation to the left ventricular anterior cardiac wall with a single dose of 20 Gy, whereas the former received sham irradiation. All dogs underwent (13)N-ammonia PET/CT MPI 1 wk before irradiation and at 3, 6, and 12 mo after sham or local irradiation. One week after undergoing (13)N-ammonia PET/CT MPI, the irradiation group underwent coronary angiography. Six randomly selected dogs from each group were sacrificed and used to detect pathologic cardiac injury at 3, 6, and 12 mo after irradiation. Results: Compared with the control group and baseline, the irradiation group showed significantly increased perfusion in the irradiated area of the heart at 3 mo after irradiation, perfusion reduction at 6 mo after irradiation, and a perfusion defect at 12 mo after irradiation. There was no significant difference in the left ventricular ejection fraction between the control and irradiation groups at baseline or at 3 mo after irradiation. The irradiation group showed a reduction of left ventricular ejection fraction compared with the control group at 6 mo (50.0% ± 8.1% vs. 59.3% ± 4.1%, P = 0.016) and 12 mo (47.2% ± 6.7% vs. 57.4% ± 3.3%, P = 0.002) after irradiation. No coronary stenosis was observed in the irradiation group. Regional wall motion abnormalities appeared in the irradiated area at 6 mo after irradiation, and its extent was enlarged at 12 mo after irradiation. Pathologic changes were observed; radiation-induced myocardial tissue damage and microvascular fibrosis in the irradiated area progressively increased over time. Conclusion:(13)N-ammonia PET/CT MPI can dynamically detect myocardial perfusion changes together with

  14. Detection and analysis of microseismic events using a Matched Filtering Algorithm (MFA)

    NASA Astrophysics Data System (ADS)

    Caffagni, Enrico; Eaton, David W.; Jones, Joshua P.; van der Baan, Mirko

    2016-07-01

    A new Matched Filtering Algorithm (MFA) is proposed for detecting and analysing microseismic events recorded by downhole monitoring of hydraulic fracturing. This method requires a set of well-located template (`parent') events, which are obtained using conventional microseismic processing and selected on the basis of high signal-to-noise (S/N) ratio and representative spatial distribution of the recorded microseismicity. Detection and extraction of `child' events are based on stacked, multichannel cross-correlation of the continuous waveform data, using the parent events as reference signals. The location of a child event relative to its parent is determined using an automated process, by rotation of the multicomponent waveforms into the ray-centred co-ordinates of the parent and maximizing the energy of the stacked amplitude envelope within a search volume around the parent's hypocentre. After correction for geometrical spreading and attenuation, the relative magnitude of the child event is obtained automatically using the ratio of stacked envelope peak with respect to its parent. Since only a small number of parent events require interactive analysis such as picking P- and S-wave arrivals, the MFA approach offers the potential for significant reduction in effort for downhole microseismic processing. Our algorithm also facilitates the analysis of single-phase child events, that is, microseismic events for which only one of the S- or P-wave arrivals is evident due to unfavourable S/N conditions. A real-data example using microseismic monitoring data from four stages of an open-hole slickwater hydraulic fracture treatment in western Canada demonstrates that a sparse set of parents (in this case, 4.6 per cent of the originally located events) yields a significant (more than fourfold increase) in the number of located events compared with the original catalogue. Moreover, analysis of the new MFA catalogue suggests that this approach leads to more robust interpretation

  15. Pre-trained D-CNN models for detecting complex events in unconstrained videos

    NASA Astrophysics Data System (ADS)

    Robinson, Joseph P.; Fu, Yun

    2016-05-01

    Rapid event detection faces an emergent need to process large videos collections; whether surveillance videos or unconstrained web videos, the ability to automatically recognize high-level, complex events is a challenging task. Motivated by pre-existing methods being complex, computationally demanding, and often non-replicable, we designed a simple system that is quick, effective and carries minimal overhead in terms of memory and storage. Our system is clearly described, modular in nature, replicable on any Desktop, and demonstrated with extensive experiments, backed by insightful analysis on different Convolutional Neural Networks (CNNs), as stand-alone and fused with others. With a large corpus of unconstrained, real-world video data, we examine the usefulness of different CNN models as features extractors for modeling high-level events, i.e., pre-trained CNNs that differ in architectures, training data, and number of outputs. For each CNN, we use 1-fps from all training exemplar to train one-vs-rest SVMs for each event. To represent videos, frame-level features were fused using a variety of techniques. The best being to max-pool between predetermined shot boundaries, then average-pool to form the final video-level descriptor. Through extensive analysis, several insights were found on using pre-trained CNNs as off-the-shelf feature extractors for the task of event detection. Fusing SVMs of different CNNs revealed some interesting facts, finding some combinations to be complimentary. It was concluded that no single CNN works best for all events, as some events are more object-driven while others are more scene-based. Our top performance resulted from learning event-dependent weights for different CNNs.

  16. Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection.

    PubMed

    Olson, Sarah H; Benedum, Corey M; Mekaru, Sumiko R; Preston, Nicholas D; Mazet, Jonna A K; Joly, Damien O; Brownstein, John S

    2015-08-01

    The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data.

  17. EO/IR satellite constellations for the early detection and tracking of collision events

    NASA Astrophysics Data System (ADS)

    Zatezalo, A.; El-Fallah, A.; Mahler, R.; Mehra, R. K.; Pham, K.

    2010-04-01

    The detection and tracking of collision events involving existing Low Earth Orbit (LEO) Resident Space Objects (RSOs) is becoming increasingly important with the higher LEO space objects traffic volume which is anticipated to increase even further in the near future. Changes in velocity that can lead to a collision are hard to detect early on time, and before the collision happens. Several collision events can happen at the same time and continuous monitoring of the LEO orbit is necessary in order to determine and implement collision avoidance strategies. We present a simulation of a constellation system consisting of multiple platforms carrying EO/IR sensors for the detection of such collisions. The presented simulation encompasses the full complexity of LEO trajectories changes which can collide with currently operating satellites. Efficient multitarget filter with information-theoretic multisensor management is implemented and evaluated on different constellations.

  18. Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection

    PubMed Central

    Olson, Sarah H.; Benedum, Corey M.; Mekaru, Sumiko R.; Preston, Nicholas D.; Mazet, Jonna A.K.; Joly, Damien O.

    2015-01-01

    The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data. PMID:26196106

  19. Total Coronary Atherosclerotic Plaque Burden Assessment by CT Angiography for Detecting Obstructive Coronary Artery Disease Associated with Myocardial Perfusion Abnormalities

    PubMed Central

    Kishi, Satoru; Magalhães, Tiago A.; Cerci, Rodrigo J.; Matheson, Matthew B.; Vavere, Andrea; Tanami, Yutaka; Kitslaar, Pieter H.; George, Richard T.; Brinker, Jeffrey; Miller, Julie M.; Clouse, Melvin E.; Lemos, Pedro A.; Niinuma, Hiroyuki; Reiber, Johan H.C.; Rochitte, Carlos E.; Rybicki, Frank J.; Di Carli, Marcelo F.; Cox, Christopher; Lima, Joao A.C.; Arbab-Zadeh, Armin

    2016-01-01

    Background Total atherosclerotic plaque burden assessment by CT angiography (CTA) is a promising tool for diagnosis and prognosis of coronary artery disease (CAD) but its validation is restricted to small clinical studies. We tested the feasibility of semi-automatically derived coronary atheroma burden assessment for identifying patients with hemodynamically significant CAD in a large cohort of patients with heterogenous characteristics. Methods This study focused on the CTA component of the CORE320 study population. A semi-automated contour detection algorithm quantified total coronary atheroma volume defined as the difference between vessel and lumen volume. Percent atheroma volume (PAV = [total atheroma volume/total vessel volume]×100) was the primary metric for assessment (n=374). The area under the receiver operating characteristic curve (AUC) determined the diagnostic accuracy for identifying patients with hemodynamically significant CAD defined as ≥50% stenosis by quantitative coronary angiography and associated myocardial perfusion abnormality by SPECT. Results Of 374 patients, 139 (37%) had hemodynamically significant CAD. The AUC for PAV was 0.78 (95% confidence interval [CI] 0.73–0.83) compared to 0.84 [0.79–0.88] by standard expert CTA interpretation (p=0.02). Accuracy for both CTA (0.91 [0.87, 0.96]) and PAV (0.86 [0.81–0.91]) increased after excluding patients with history of CAD (p<0.01 for both). Bland-Altman analysis revealed good agreement between two observers ( bias of 280.2 mm3 [161.8, 398.7]). Conclusions A semi-automatically derived index of total coronary atheroma volume yields good accuracy for identifying patients with hemodynamically significant CAD, though marginally inferior to CTA expert reading. These results convey promise for rapid, reliable evaluation of clinically relevant CAD. PMID:26817414

  20. Event Detection and Location of Earthquakes Using the Cascadia Initiative Dataset

    NASA Astrophysics Data System (ADS)

    Morton, E.; Bilek, S. L.; Rowe, C. A.

    2015-12-01

    The Cascadia subduction zone (CSZ) produces a range of slip behavior along the plate boundary megathrust, from great earthquakes to episodic slow slip and tremor (ETS). Unlike other subduction zones that produce great earthquakes and ETS, the CSZ is notable for the lack of small and moderate magnitude earthquakes recorded. The seismogenic zone extent is currently estimated to be primarily offshore, thus the lack of observed small, interplate earthquakes may be partially due to the use of only land seismometers. The Cascadia Initiative (CI) community seismic experiment seeks to address this issue by including ocean bottom seismometers (OBS) deployed directly over the locked seismogenic zone, in addition to land seismometers. We use these seismic data to explore whether small magnitude earthquakes are occurring on the plate interface, but have gone undetected by the land-based seismic networks. We select a subset of small magnitude (M0.1-3.7) earthquakes from existing earthquake catalogs, based on land seismic data, whose preliminary hypocentral locations suggest they may have occurred on the plate interface. We window the waveforms on CI OBS and land seismometers around the phase arrival times for these earthquakes to generate templates for subspace detection, which allows for additional flexibility over traditional matched filter detection methods. Here we present event detections from the first year of CI deployment and preliminary locations for the detected events. Initial results of scanning the first year of the CI deployment using one cluster of template events, located near a previously identified subducted seamount, include 473 detections on OBS station M08A (~61.6 km offshore) and 710 detections on OBS station J25A (~44.8 km northeast of M08A). Ongoing efforts include detection using additional OBS stations along the margin, as well as determining locations of clusters detected in the first year of deployment.

  1. Long-Duration Neutron Production in Solar Eruptive Events Detected with the MESSENGER Neutron Spectrometer

    NASA Astrophysics Data System (ADS)

    Feldman, W. C.; Lawrence, D. J.; Vestrand, W. T.; Peplowski, P. N.

    2014-12-01

    Nine long-duration neutron solar eruptive events (SEEs) between 31 December 2007 and 16 March 2013 appear to be excellent candidates for detection of fast neutrons from the Sun by the MESSENGER Neutron Spectrometer (NS). One event (on 4 June 2011) is the cleanest example, because it was not accompanied by energetic ions at MESSENGER having energies greater than 50±10 MeV/nuc. The purpose of this study is to assemble a set of conditions common to all events that can help identify the physical conditions at their origin. We classified the nine events into three categories: (1) those having tight magnetic connection to the Sun as well as to spacecraft at 1 AU that can separately measure the energetic proton, alpha particle, and electron flux spectra, (2) those with sufficiently close connection that the energetic flux spectra can be compared, (3) those that have only marginal connections, and (4) those that are also seen at Earth. Four events fall into category (1), three into category (2), two into category (3), and parts of four events overlapped neutron events also seen by the scintillation FIBer solar neutron telescope (FIB) detector placed on the International Space Station in 2009. Seven of the nine events that have either tight or marginal magnetic connection have alpha particle abundances less than 2%. For each event, we modeled expected fast neutron count rates from the 1 AU ion spectrum, a process that accounts for the transport of the neutrons through the spacecraft to the NS. The ratios of measured to predicted fast-neutron counts range between 2.0 and 12.1.

  2. Automatic microseismic event detection by band-limited phase-only correlation

    NASA Astrophysics Data System (ADS)

    Wu, Shaojiang; Wang, Yibo; Zhan, Yi; Chang, Xu

    2016-12-01

    Identification and detection of microseismic events is a significant issue in source locations and source mechanism analysis. The number of the records is notably large, especially in the case of some real-time monitoring, and while the majority of microseismic events are highly weak and sparse, automatic algorithms are indispensable. In this study, we introduce an effective method for the identification and detection of microseismic events by judging whether the P-wave phase exists in a local segment from a single three-component microseismic records. The new judging algorithm consists primarily of the following key steps: 1) transform the waveform time series into time-varying spectral representations using the S-transform; 2) calculate the similarity of the frequency content in the time-frequency domain using the phase-only correlation function; and 3) identify the P-phase by the combination analysis between any two components. The proposed algorithm is compared to a similar approach using the cross-correlation in the time domain between any two components and later tested with synthetic microseismic datasets and real field-recorded datasets. The results indicate that the proposed algorithm is able to distinguish similar and dissimilar waveforms, even for low signal noise ratio and emergent events, which is important for accurate and rapid selection of microseismic events from a large number of records. This method can be applied to other geophysical analyses based on the waveform data.

  3. Event-specific quantitative detection of nine genetically modified maizes using one novel standard reference molecule.

    PubMed

    Yang, Litao; Guo, Jinchao; Pan, Aihu; Zhang, Haibo; Zhang, Kewei; Wang, Zhengming; Zhang, Dabing

    2007-01-10

    With the development of genetically modified organism (GMO) detection techniques, the Polymerase Chain Reaction (PCR) technique has been the mainstay for GMO detection, and real-time PCR is the most effective and important method for GMO quantification. An event-specific detection strategy based on the unique and specific integration junction sequences between the host plant genome DNA and the integrated gene is being developed for its high specificity. This study establishes the event-specific detection methods for TC1507 and CBH351 maizes. In addition, the event-specific TaqMan real-time PCR detection methods for another seven GM maize events (Bt11, Bt176, GA21, MON810, MON863, NK603, and T25) were systematically optimized and developed. In these PCR assays, the fluorescent quencher, TAMRA, was dyed on the T-base of the probe at the internal position to improve the intensity of the fluorescent signal. To overcome the difficulties in obtaining the certified reference materials of these GM maizes, one novel standard reference molecule containing all nine specific integration junction sequences of these GM maizes and the maize endogenous reference gene, zSSIIb, was constructed and used for quantitative analysis. The limits of detection of these methods were 20 copies for these different GM maizes, the limits of quantitation were about 20 copies, and the dynamic ranges for quantification were from 0.05 to 100% in 100 ng of DNA template. Furthermore, nine groups of the mixed maize samples of these nine GM maize events were quantitatively analyzed to evaluate the accuracy and precision. The accuracy expressed as bias varied from 0.67 to 28.00% for the nine tested groups of GM maize samples, and the precision expressed as relative standard deviations was from 0.83 to 26.20%. All of these indicated that the established event-specific real-time PCR detection systems and the reference molecule in this study are suitable for the identification and quantification of these GM

  4. Detections of Planets in Binaries Through the Channel of Chang–Refsdal Gravitational Lensing Events

    NASA Astrophysics Data System (ADS)

    Han, Cheongho; Shin, In-Gu; Jung, Youn Kil

    2017-02-01

    Chang–Refsdal (C–R) lensing, which refers to the gravitational lensing of a point mass perturbed by a constant external shear, provides a good approximation in describing lensing behaviors of either a very wide or a very close binary lens. C–R lensing events, which are identified by short-term anomalies near the peak of high-magnification lensing light curves, are routinely detected from lensing surveys, but not much attention is paid to them. In this paper, we point out that C–R lensing events provide an important channel to detect planets in binaries, both in close and wide binary systems. Detecting planets through the C–R lensing event channel is possible because the planet-induced perturbation occurs in the same region of the C–R lensing-induced anomaly and thus the existence of the planet can be identified by the additional deviation in the central perturbation. By presenting the analysis of the actually observed C–R lensing event OGLE-2015-BLG-1319, we demonstrate that dense and high-precision coverage of a C–R lensing-induced perturbation can provide a strong constraint on the existence of a planet in a wide range of planet parameters. The sample of an increased number of microlensing planets in binary systems will provide important observational constraints in giving shape to the details of planet formation, which have been restricted to the case of single stars to date.

  5. A Heuristic Indication and Warning Staging Model for Detection and Assessment of Biological Events

    PubMed Central

    Wilson, James M.; Polyak, Marat G.; Blake, Jane W.; Collmann, Jeff

    2008-01-01

    Objective This paper presents a model designed to enable rapid detection and assessment of biological threats that may require swift intervention by the international public health community. Design We utilized Strauss’ grounded theory to develop an expanded model of social disruption due to biological events based on retrospective and prospective case studies. We then applied this model to the temporal domain and propose a heuristic staging model, the Wilson–Collmann Scale for assessing biological event evolution. Measurements We retrospectively and manually examined hard copy archival local media reports in the native vernacular for three biological events associated with substantial social disruption. The model was then tested prospectively through media harvesting based on keywords corresponding to the model parameters. Results Our heuristic staging model provides valuable information about the features of a biological event that can be used to determine the level of concern warranted, such as whether the pathogen in question is responding to established public health disease control measures, including the use of antimicrobials or vaccines; whether the public health and medical infrastructure of the country involved is adequate to mount the necessary response; whether the country’s officials are providing an appropriate level of information to international public health authorities; and whether the event poses a international threat. The approach is applicable for monitoring open-source (public-domain) media for indications and warnings of such events, and specifically for markers of the social disruption that commonly occur as these events unfold. These indications and warnings can then be used as the basis for staging the biological threat in the same manner that the United States National Weather Service currently uses storm warning models (such as the Saffir-Simpson Hurricane Scale) to detect and assess threatening weather conditions. Conclusion

  6. Detection, visualization and animation of abnormal anatomic structure with a deformable probabilistic brain atlas based on random vector field transformations.

    PubMed

    Thompson, P M; Toga, A W

    1997-09-01

    probability maps are animated in video format (on the accompanying CD-ROM). Applications of the deformable probabilistic atlas include the transfer of multi-subject 3-D functional, vascular and histologic maps onto a single anatomic template, the mapping of 3-D atlases onto the scans of new subjects, and the rapid detection, quantification and mapping of local shape changes in 3-D medical images in disease and during normal or abnormal growth and development.

  7. Exploring the Limits of Waveform Correlation Event Detection as Applied to Three Earthquake Aftershock Sequences

    NASA Astrophysics Data System (ADS)

    Young, C. J.; Carr, D.; Resor, M.; Duffey, S.

    2009-12-01

    Swarms of earthquakes and/or aftershock sequences can dramatically increase the level of seismicity in a region for a period of time lasting from days to months, depending on the swarm or sequence. Such occurrences can provide a large amount of useful information to seismologists. For those who monitor seismic events for possible nuclear explosions, however, these swarms/sequences are a nuisance. In an explosion monitoring system, each event must be treated as a possible nuclear test until it can be proven, to a high degree of confidence, not to be. Seismic events recorded by the same station with highly correlated waveforms almost certainly have a similar location and source type, so clusters of events within a swarm can quickly be identified as earthquakes. We have developed a number of tools that can be used to exploit the high degree of waveform similarity expected to be associated with swarms/sequences. Dendro Tool measures correlations between known events. The Waveform Correlation Detector is intended to act as a detector, finding events in raw data which correlate with known events. The Self Scanner is used to find all correlated segments within a raw data steam and does not require an event library. All three techniques together provide an opportunity to study the similarities of events in an aftershock sequence in different ways. To comprehensively characterize the benefits and limits of waveform correlation techniques, we studied 3 aftershock sequences, using our 3 tools, at multiple stations. We explored the effects of station distance and event magnitudes on correlation results. Lastly, we show the reduction in detection threshold and analyst workload offered by waveform correlation techniques compared to STA/LTA based detection. We analyzed 4 days of data from each aftershock sequence using all three methods. Most known events clustered in a similar manner across the toolsets. Up to 25% of catalogued events were found to be a member of a cluster. In

  8. Wave-induced burst precipitation events detected with a digital ionosonde

    SciTech Connect

    Jarvis, M.J.; Smith, A.J. ); Berkey, F.T. ); Carpenter, D.L. )

    1990-01-01

    Initial results are presented from two methods whereby burst precipitation events in the lower ionosphere, almost certainly induced by VLF wave-particle interactions in the magnetosphere, have been detected using a ground-based digital ionosonde. In the first method, HF echoes are received above the critical frequency of the surrounding plasma; particle energies and the location and extent of the plasma enhancement may be deduced. In the second method, a rapid decrease in the phase of ionospheric echoes is observed due to refractive index changes along the echo path; particle energies, the duration of the precipitation event and the precipitation energy flux can be estimated.

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

    DTIC Science & Technology

    1995-03-01

    For all outgoing edges i from ’n’ propagate parameters in node ’n’ to the nodei connected by edge i activate-operator-node( nodej ); Delete propagated...El E2 Figure 6: Detection of X in recent mode PROCEDURE activate-operator-node( nodej ) /* Recent Context */ CASE nodei is of type a primitive or...composite event has been signalled to nodej */ AND(E1, E2): if left event el is signalled if E2’s list is not empty Pass <e2, el> to the parent Replace el in

  10. Detecting adverse drug events in discharge summaries using variations on the simple Bayes model.

    PubMed

    Visweswaran, Shyam; Hanbury, Paul; Saul, Melissa; Cooper, Gregory F

    2003-01-01

    Detection and prevention of adverse events and, in particular, adverse drug events (ADEs), is an important problem in health care today. We describe the implementation and evaluation of four variations on the simple Bayes model for identifying ADE-related discharge summaries. Our results show that these probabilistic techniques achieve an ROC curve area of up to 0.77 in correctly determining which patient cases should be assigned an ADE-related ICD-9-CM code. These results suggest a potential for these techniques to contribute to the development of an automated system that helps identify ADEs, as a step toward further understanding and preventing them.

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

    PubMed Central

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-01-01

    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. PMID:27420073

  12. Detection of seismic events triggered by P-waves from the 2011 Tohoku-Oki earthquake

    NASA Astrophysics Data System (ADS)

    Miyazawa, Masatoshi

    2012-12-01

    Large-amplitude surface waves from the 2011 Tohoku-Oki earthquake triggered many seismic events across Japan, while the smaller amplitude P-wave triggering remains unclear. A spectral method was used to detect seismic events triggered by the first arriving P-waves over Japan. This method uses a reference event to correct for source and propagation effects, so that the local response near the station can be examined in detail. P-wave triggering was found in the regions where triggered non-volcanic tremor (NVT) has been observed, and some seismic and volcanic regions. The triggering strain due to P-waves is of the order of 10-8 to 10-7, which is 1 to 2 orders of magnitude smaller than the triggering strain necessary for the surface wave triggering. In the regions of NVT, the triggered event was not identified with slow events, but with other seismic events such as tectonic earthquakes. The sequence of triggering in the regions started with P-wave arrivals. The subsequent surface waves contributed to triggering of NVT, possibly together with slow slip, which resulted in the large amplitude of the NVT.

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

    PubMed

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-07-13

    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.

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

    PubMed

    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.

  15. An algorithm to detect low incidence arrhythmic events in electrocardiographic records from ambulatory patients.

    PubMed

    Hungenahally, S K; Willis, R J

    1994-11-01

    An algorithm was devised to detect low incidence arrhythmic events in electrocardiograms obtained during ambulatory monitoring. The algorithm incorporated baseline correction and R wave detection. The RR interval was used to identify tachycardia, bradycardia, and premature ventricular beats. Only a few beats before and after the arrhythmic event were stored. The software was evaluated on a prototype hardware system which consisted of an Intel 86/30 single board computer with a suitable analog pre-processor and an analog to digital converter. The algorithm was used to determine the incidence and type of arrhythmia in records from an ambulatory electrocardiogram (ECG) database and from a cardiac exercise laboratory. These results were compared to annotations on the records which were assumed to be correct. Standard criteria used previously to evaluate algorithms designed for arrhythmia detection were sensitivity, specificity, and diagnostic accuracy. Sensitivities ranging from 77 to 100%, specificities from 94 to 100%, and diagnostic accuracies from 92 to 100% were obtained on the different data sets. These results compare favourably with published results based on more elaborate algorithms. By circumventing the need to make a continuous record of the ECG, the algorithm could form the basis for a compact monitoring device for the detection of arrhythmic events which are so infrequent that standard 24-h Holter monitoring is insufficient.

  16. CTBT infrasound network performance to detect the 2013 Russian fireball event

    NASA Astrophysics Data System (ADS)

    Pilger, Christoph; Ceranna, Lars; Ross, J. Ole; Le Pichon, Alexis; Mialle, Pierrick; Garcés, Milton A.

    2015-04-01

    The explosive fragmentation of the 2013 Chelyabinsk meteorite generated a large airburst with an equivalent yield of 500 kT TNT. It is the most energetic event recorded by the infrasound component of the Comprehensive Nuclear-Test-Ban Treaty-International Monitoring System (CTBT-IMS), globally detected by 20 out of 42 operational stations. This study performs a station-by-station estimation of the IMS detection capability to explain infrasound detections and nondetections from short to long distances, using the Chelyabinsk meteorite as global reference event. Investigated parameters influencing the detection capability are the directivity of the line source signal, the ducting of acoustic energy, and the individual noise conditions at each station. Findings include a clear detection preference for stations perpendicular to the meteorite trajectory, even over large distances. Only a weak influence of stratospheric ducting is observed for this low-frequency case. Furthermore, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.

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

    NASA Astrophysics Data System (ADS)

    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

  18. Use of a clinical event monitor to prevent and detect medication errors.

    PubMed Central

    Payne, T. H.; Savarino, J.; Marshall, R.; Hoey, C. T.

    2000-01-01

    Errors in health care facilities are common and often unrecognized. We have used our clinical event monitor to prevent and detect medication errors by scrutinizing electronic messages sent to it when any medication order is written in our facility. A growing collection of medication safety rules covering dose limit errors, laboratory monitoring, and other topics may be applied to each medication order message to provide an additional layer of protection beyond existing order checks, reminders, and alerts available within our computer-based record system. During a typical day the event monitor receives 4802 messages, of which 4719 pertain to medication orders. We have found the clinical event monitor to be a valuable tool for clinicians and quality management groups charged with improving medication safety. PMID:11079962

  19. Valvular Abnormalities Detected by Echocardiography in 5-Year Survivors of Childhood Cancer: A Long-Term Follow-Up Study

    SciTech Connect

    Pal, Helena J. van der; Caron, Huib N.; Kremer, Leontien C.; Dalen, Elvira C. van

    2015-01-01

    Purpose: To determine the prevalence of valvular abnormalities after radiation therapy involving the heart region and/or treatment with anthracyclines and to identify associated risk factors in a large cohort of 5-year childhood cancer survivors (CCS). Methods and Materials: The study cohort consisted of all 626 eligible 5-year CCS diagnosed with childhood cancer in the Emma Children's Hospital/Academic Medical Center between 1966 and 1996 and treated with radiation therapy involving the heart region and/or anthracyclines. We determined the presence of valvular abnormalities according to echocardiograms. Physical radiation dose was converted into the equivalent dose in 2-Gy fractions (EQD{sub 2}). Using multivariable logistic regression analyses, we examined the associations between cancer treatment and valvular abnormalities. Results: We identified 225 mainly mild echocardiographic valvular abnormalities in 169 of 545 CCS (31%) with a cardiac assessment (median follow-up time, 14.9 years [range, 5.1-36.8 years]; median attained age 22.0 years [range, 7.0-49.7 years]). Twenty-four CCS (4.4%) had 31 moderate or higher-graded abnormalities. Most common abnormalities were tricuspid valve disorders (n=119; 21.8%) and mitral valve disorders (n=73; 13.4%). The risk of valvular abnormalities was associated with increasing radiation dose (using EQD{sub 2}) involving the heart region (odds ratio 1.33 per 10 Gy) and the presence of congenital heart disease (odds ratio 3.43). We found no statistically significant evidence that anthracyclines increase the risk. Conclusions: Almost one-third of CCS treated with potentially cardiotoxic therapy had 1 or more asymptomatic, mostly mild valvular abnormalities after a median follow-up of nearly 15 years. The most important risk factors are higher EQD{sub 2} to the heart region and congenital heart disease. Studies with longer follow-up are necessary to investigate the clinical course of asymptomatic valvular abnormalities in

  20. Assessment and validation of a simple automated method for the detection of gait events and intervals.

    PubMed

    Ghoussayni, Salim; Stevens, Christopher; Durham, Sally; Ewins, David

    2004-12-01

    A simple and rapid automatic method for detection of gait events at the foot could speed up and possibly increase the repeatability of gait analysis and evaluations of treatments for pathological gaits. The aim of this study was to compare and validate a kinematic-based algorithm used in the detection of four gait events, heel contact, heel rise, toe contact and toe off. Force platform data is often used to obtain start and end of contact phases, but not usually heel rise and toe contact events. For this purpose synchronised kinematic, kinetic and video data were captured from 12 healthy adult subjects walking both barefoot and shod at slow and normal self-selected speeds. The data were used to determine the gait events using three methods: force, visual inspection and algorithm methods. Ninety percent of all timings given by the algorithm were within one frame (16.7 ms) when compared to visual inspection. There were no statistically significant differences between the visual and algorithm timings. For both heel and toe contact the differences between the three methods were within 1.5 frames, whereas for heel rise and toe off the differences between the force on one side and the visual and algorithm on the other were higher and more varied (up to 175 ms). In addition, the algorithm method provided the duration of three intervals, heel contact to toe contact, toe contact to heel rise and heel rise to toe off, which are not readily available from force platform data. The ability to automatically and reliably detect the timings of these four gait events and three intervals using kinematic data alone is an asset to clinical gait analysis.

  1. Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

    2013-05-01

    It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

  2. Real-time gait event detection for lower limb amputees using a single wearable sensor.

    PubMed

    Maqbool, H F; Husman, M A B; Awad, M I; Abouhossein, A; Mehryar, P; Iqbal, N; Dehghani-Sanij, A A

    2016-08-01

    This paper presents a rule-based real-time gait event/phase detection system (R-GEDS) using a shank mounted inertial measurement unit (IMU) for lower limb amputees during the level ground walking. Development of the algorithm is based on the shank angular velocity in the sagittal plane and linear acceleration signal in the shank longitudinal direction. System performance was evaluated with four control subjects (CS) and one transfemoral amputee (TFA) and the results were validated with four FlexiForce footswitches (FSW). The results showed a data latency for initial contact (IC) and toe off (TO) within a range of ± 40 ms for both CS and TFA. A delay of about 3.7 ± 62 ms for a foot-flat start (FFS) and an early detection of -9.4 ± 66 ms for heel-off (HO) was found for CS. Prosthetic side showed an early detection of -105 ± 95 ms for FFS whereas intact side showed a delay of 141 ±73 ms for HO. The difference in the kinematics of the TFA and CS is one of the potential reasons for high variations in the time difference. Overall, detection accuracy was 99.78% for all the events in both groups. Based on the validated results, the proposed system can be used to accurately detect the temporal gait events in real-time that leads to the detection of gait phase system and therefore, can be utilized in gait analysis applications and the control of lower limb prostheses.

  3. Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use

    PubMed Central

    Moghaddam, Athena K.; Yuen, Hiu Kim; Archambault, Philippe S.; Routhier, François; Michaud, François; Boissy, Patrick

    2014-01-01

    Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. Unfortunately, PW incidents and accidents are not uncommon and their consequences can be serious. The objective of this paper is to develop technological tools that can be used to characterize a wheelchair user’s driving behavior under various settings. In the experiments conducted, PWs are outfitted with a datalogging platform that records, in real-time, the 3-D acceleration of the PW. Data collection was conducted over 35 different activities, designed to capture a spectrum of PW driving events performed at different speeds (collisions with fixed or moving objects, rolling on incline plane, and rolling across multiple types obstacles). The data was processed using time-series analysis and data mining techniques, to automatically detect and identify the different events. We compared the classification accuracy using four different types of time-series features: 1) time-delay embeddings; 2) time-domain characterization; 3) frequency-domain features; and 4) wavelet transforms. In the analysis, we compared the classification accuracy obtained when distinguishing between safe and unsafe events during each of the 35 different activities. For the purposes of this study, unsafe events were defined as activities containing collisions against objects at different speed, and the remainder were defined as safe events. We were able to accurately detect 98% of unsafe events, with a low (12%) false positive rate, using only five examples of each activity. This proof-of-concept study shows that the proposed approach has the potential of capturing, based on limited input from embedded sensors, contextual information on PW use, and of automatically characterizing a user’s PW driving behavior. PMID:27170879

  4. Residual Events during Use of CPAP: Prevalence, Predictors, and Detection Accuracy

    PubMed Central

    Reiter, Joel; Zleik, Bashar; Bazalakova, Mihaela; Mehta, Pankaj; Thomas, Robert Joseph

    2016-01-01

    Study Objectives: To assess the frequency, severity, and determinants of residual respiratory events during continuous positive airway therapy (CPAP) for obstructive sleep apnea (OSA) as determined by device output. Methods: Subjects were consecutive OSA patients at an American Academy of Sleep Medicine accredited multidisciplinary sleep center. Inclusion criteria included CPAP use for a minimum of 3 months, and a minimum nightly use of 4 hours. Compliance metrics and waveform data from 217 subjects were analyzed retrospectively. Events were scored manually when there was a clear reduction of amplitude (≥ 30%) or flow-limitation with 2–3 larger recovery breaths. Automatically detected versus manually scored events were subjected to statistical analyses included Bland-Altman plots, correlation coefficients, and logistic regression exploring predictors of residual events. Results: The mean patient age was 54.7 ± 14.2 years; 63% were males. All patients had a primary diagnosis of obstructive sleep apnea, 26% defined as complex sleep apnea. Residual flow measurement based apnea-hypopnea index (AHIFLOW) > 5, 10, and 15/h was seen in 32.3%, 9.7%, and 1.8% vs. 60.8%, 23%, and 7.8% of subjects based on automated vs. manual scoring of waveform data. Automatically detected versus manually scored average AHIFLOW was 4.4 ± 3.8 vs. 7.3 ± 5.1 per hour. In a logistic regression analysis, the only predictors for a manual AHIFLOW > 5/h were the absolute central apnea index (CAI), (odds ratio [OR]: 1.5, p: 0.01, CI: 1.1–2.0), or using a CAI threshold of 5/h of sleep (OR: 5.0, p: < 0.001, CI: 2.2–13.8). For AHIFLOW > 10/h, the OR was 1.14, p: 0.03 (CI: 1.1–1.3) per every CAI unit of 1/hour. Conclusions: Residual respiratory events are common during CPAP treatment, may be missed by automated device detection and predicted by a high central apnea index on the baseline diagnostic study. Direct visualization of flow data is generally available and improves detection

  5. Using Structured Telephone Follow-up Assessments to Improve Suicide-related Adverse Event Detection

    PubMed Central

    Arias, Sarah A.; Zhang, Zi; Hillerns, Carla; Sullivan, Ashley F.; Boudreaux, Edwin D.; Miller, Ivan; Camargo, Carlos A.

    2014-01-01

    Adverse event (AE) detection and reporting practices were compared during the first phase of the Emergency Department Safety Assessment and Follow-up Evaluation (ED-SAFE), a suicide intervention study. Data were collected using a combination of chart reviews and structured telephone follow-up assessments post-enrollment. Beyond chart reviews, structured telephone follow-up assessments identified 45% of the total AEs in our study. Notably, detection of suicide attempts significantly varied by approach with 53 (18%) detected by chart review, 173 (59%) by structured telephone follow-up assessments, and 69 (23%) marked as duplicates. Findings provide support for utilizing multiple methods for more robust AE detection in suicide research. PMID:24588679

  6. A Method for Automated Detection of Usability Problems from Client User Interface Events

    PubMed Central

    Saadawi, Gilan M.; Legowski, Elizabeth; Medvedeva, Olga; Chavan, Girish; Crowley, Rebecca S.

    2005-01-01

    Think-aloud usability analysis provides extremely useful data but is very time-consuming and expensive to perform because of the extensive manual video analysis that is required. We describe a simple method for automated detection of usability problems from client user interface events for a developing medical intelligent tutoring system. The method incorporates (1) an agent-based method for communication that funnels all interface events and system responses to a centralized database, (2) a simple schema for representing interface events and higher order subgoals, and (3) an algorithm that reproduces the criteria used for manual coding of usability problems. A correction factor was empirically determining to account for the slower task performance of users when thinking aloud. We tested the validity of the method by simultaneously identifying usability problems using TAU and manually computing them from stored interface event data using the proposed algorithm. All usability problems that did not rely on verbal utterances were detectable with the proposed method. PMID:16779121

  7. Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence.

    PubMed

    Ohyama, Junji; Watanabe, Katsumi

    2016-01-01

    We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images.

  8. Nanoporous niobium oxide for label-free detection of DNA hybridization events.

    PubMed

    Choi, Jinsub; Lim, Jae Hoon; Rho, Sangchul; Jahng, Deokjin; Lee, Jaeyoung; Kim, Kyung Ja

    2008-01-15

    We found that DNA probes can be immobilized on anodically prepared porous niobium oxide without a chemical modification of both the DNA probes and the substrate. By using the porous niobium oxide with a positive surface charge, DNA hybridization events are detected on the basis of the blue-shift of a maximum absorption peak in UV-vis-NIR spectroscopy. The blue-shift is ascribed to the change of surface charge upon single- or double-stranded DNA. The method does not require a label and shows high sensitivity with the detection limit of the concentration of 1nM.

  9. A multivariate based event detection method and performance comparison with two baseline methods.

    PubMed

    Liu, Shuming; Smith, Kate; Che, Han

    2015-09-01

    Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate.

  10. The grain size distribution and the detection of abnormal grain growth of austenite in an eutectoid steel containing niobium

    SciTech Connect

    Bruno, J.C. . Dept. de Engenharia Mecanica e de Materiais); Rios, P.R. . Dept. de Ciencia dos Materiais e Metalurgia)

    1995-02-15

    The abnormal grain growth of austenite was studied in a commercial steel of composition (wt%): 0.70 C, 1.36 Mn, 0.72 Si, 0.015 P, 0.027 S and 0.03 Nb. Specimens were thermocycled at various conditions and then grain size distribution determined. The grain size distribution shape did not change during normal grain growth but this distribution widened and flattened during the abnormal grain growth. The initial smaller mean size of carbonitrides and/or the highest homogeneity of niobium carbonitride size distribution of the samples submitted to thermal cycles, in comparison with the normalized samples, increased the abnormal grain growth temperature from 1,373 K to 1,473 K.

  11. Meiotic abnormalities

    SciTech Connect

    1993-12-31

    Chapter 19, describes meiotic abnormalities. These include nondisjunction of autosomes and sex chromosomes, genetic and environmental causes of nondisjunction, misdivision of the centromere, chromosomally abnormal human sperm, male infertility, parental age, and origin of diploid gametes. 57 refs., 2 figs., 1 tab.

  12. Event Detection for Hydrothermal Plumes: A case study at Grotto Vent

    NASA Astrophysics Data System (ADS)

    Bemis, K. G.; Ozer, S.; Xu, G.; Rona, P. A.; Silver, D.

    2012-12-01

    Evidence is mounting that geologic events such as volcanic eruptions (and intrusions) and earthquakes (near and far) influence the flow rates and temperatures of hydrothermal systems. Connecting such suppositions to observations of hydrothermal output is challenging, but new ongoing time series have the potential to capture such events. This study explores using activity detection, a technique modified from computer vision, to identify pre-defined events within an extended time series recorded by COVIS (Cabled Observatory Vent Imaging Sonar) and applies it to a time series, with gaps, from Sept 2010 to the present; available measurements include plume orientation, plume rise rate, and diffuse flow area at the NEPTUNE Canada Observatory at Grotto Vent, Main Endeavour Field, Juan de Fuca Ridge. Activity detection is the process of finding a pattern (activity) in a data set containing many different types of patterns. Among many approaches proposed to model and detect activities, we have chosen a graph-based technique, Petri Nets, as they do not require training data to model the activity. They use the domain expert's knowledge to build the activity as a combination of feature states and their transitions (actions). Starting from a conceptual model of how hydrothermal plumes respond to daily tides, we have developed a Petri Net based detection algorithm that identifies deviations from the specified response. Initially we assumed that the orientation of the plume would change smoothly and symmetrically in a consistent daily pattern. However, results indicate that the rate of directional changes varies. The present Petri Net detects unusually large and rapid changes in direction or amount of bending; however inspection of Figure 1 suggests that many of the events detected may be artifacts resulting from gaps in the data or from the large temporal spacing. Still, considerable complexity overlies the "normal" tidal response pattern (the data has a dominant frequency of

  13. Detection and Type-Distribution of Human Papillomavirus in Vulva and Vaginal Abnormal Cytology Lesions and Cancer Tissues from Thai Women.

    PubMed

    Ngamkham, Jarunya; Boonmark, Krittika; Phansri, Thainsang

    2016-01-01

    Vulva and Vaginal cancers are rare among all gynecological cancers worldwide, including Thailand, and typically affect women in later life. Persistent high risk human papillomavirus (HR-HPV) infection is one of several important causes of cancer development. In this study, we focused on HPV investigation and specific type distribution from Thai women with abnormality lesions and cancers of the vulva and Vaginal. A total of ninety paraffin-embedded samples of vulva and Vaginal abnormalities and cancer cells with histologically confirmed were collected from Thai women, who were diagnosed in 2003-2012 at the National Cancer Institute, Thailand. HPV DNA was detected and genotyped using polymerase chain reaction and enzyme immunoassay with GP5+/ bio 6+ consensus specific primers and digoxigenin-labeled specific oligoprobes, respectively. The human β-globin gene was used as an internal control. Overall results represented that HPV frequency was 16/34 (47.1%) and 8/20 (40.0%) samples of vulva with cancer and abnormal cytology lesions, respectively, while, 3/5 (60%) and 16/33 (51.61%) samples of Vaginal cancer and abnormal cytology lesions, respectively, were HPV DNA positive. Single HPV type and multiple HPV type infection could be observed in both type of cancers and abnormal lesion samples in the different histological categorizes. HPV16 was the most frequent type in all cancers and abnormal cytology lesions, whereas HPV 18 was less frequent and could be detected as co-infection with other high risk HPV types. In addition, low risk types such as HPV 6, 11 and 70 could be detected in Vulva cancer and abnormal cytology lesion samples, whereas, all Vaginal cancer samples exhibited only high risk HPV types; HPV 16 and 31. In conclusion, from our results in this study we suggest that women with persistent high risk HPV type infection are at risk of developing vulva and Vaginal cancers and HPV 16 was observed at the highest frequent both of these, similar to the cervical

  14. SU-E-J-122: Detecting Treatment-Induced Metabolic Abnormalities in Craniopharyngioma Patients Undergoing Surgery and Proton Therapy

    SciTech Connect

    Hua, C; Shulkin, B; Li, Y; LI, X; Merchant, T; Indelicato, D; Boop, F

    2014-06-01

    Purpose: To identify treatment-induced defects in the brain of children with craniopharyngioma receiving surgery and proton therapy using fluorodeoxyglucose positron emission tomography (FDG PET). Methods: Forty seven patients were enrolled on a clinical trial for craniopharyngioma with serial imaging and functional evaluations. Proton therapy was delivered using the double-scattered beams with a prescribed dose of 54 Cobalt Gray Equivalent. FDG tracer uptake in each of 63 anatomical regions was computed after warping PET images to a 3D reference template in Talairach coordinates. Regional uptake was deemed significantly low or high if exceeding two standard deviations of normal population from the mean. For establishing the normal ranges, 132 children aged 1–20 years with noncentral nervous system related diseases and normal-appearing cerebral PET scans were analyzed. Age- and gender-dependent regional uptake models were developed by linear regression and confidence intervals were calculated. Results: Most common PET abnormality before proton therapy was significantly low uptake in the frontal lobe, the occipital lobe (particularly in cuneus), the medial and ventral temporal lobe, cingulate gyrus, caudate nuclei, and thalamus. They were related to injury from surgical corridors, tumor mass effect, insertion of a ventricular catheter, and the placement of an Ommaya reservoir. Surprisingly a significantly high uptake was observed in temporal gyri and the parietal lobe. In 13 patients who already completed 18-month PET scans, metabolic abnormalities improved in 11 patients from baseline. One patient had persistent abnormalities. Only one revealed new uptake abnormalities in thalamus, brainstem, cerebellum, and insula. Conclusion: Postoperative FDG PET of craniopharyngioma patients revealed metabolic abnormalities in specific regions of the brain. Proton therapy did not appear to exacerbate these surgery- and tumor-induced defects. In patients with persistent and

  15. Real-time gait event detection for normal subjects from lower trunk accelerations.

    PubMed

    González, Rafael C; López, Antonio M; Rodriguez-Uría, Javier; Alvarez, Diego; Alvarez, Juan C

    2010-03-01

    In this paper we report on a novel algorithm for the real-time detection and timing of initial (IC) and final contact (FC) gait events. We process the vertical and antero-posterior accelerations registered at the lower trunk (L3 vertebra). The algorithm is based on a set of heuristic rules extracted from a set of 1719 steps. An independent experiment was conducted to compare the results of our algorithms with those obtained from a Digimax force platform. The results show small deviations from times of occurrence of events recorded from the platform (13+/-35 ms for IC and 9+/-54 ms for FC). Results for the FC timing are especially relevant in this field, as no previous work has addressed its temporal location through the processing of lower trunk accelerations. The delay in the real-time detection of the IC is 117+/-39 ms and 34+/-72 ms for the FC, improving previously reported results for real-time detection of events from lower trunk accelerations.

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

    NASA Astrophysics Data System (ADS)

    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.

  17. Early detection of cell activation events by means of attenuated total reflection Fourier transform infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Titus, Jitto; Filfili, Chadi; Hilliard, Julia K.; Ward, John A.; Unil Perera, A. G.

    2014-06-01

    Activation of Jurkat T-cells in culture following treatment with anti-CD3 (Cluster of Differentiation 3) antibody is detectable by interrogating the treated T-cells using the Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy technique. Cell activation was detected within 75 min after the cells encountered specific immunoglobulin molecules. Spectral markers noted following ligation of the CD3 receptor with anti CD3 antibody provides proof-of-concept that ATR-FTIR spectroscopy is a sensitive measure of molecular events subsequent to cells interacting with anti-CD3 Immunoglobulin G. The resultant ligation of the CD3 receptor results in the initiation of well defined, specific signaling pathways that parallel the measurable molecular events detected using ATR-FTIR. Paired t-test with post-hoc Bonferroni corrections for multiple comparisons has resulted in the identification of statistically significant spectral markers (p < 0.02) at 1367 and 1358 cm-1. Together, these data demonstrate that early treatment-specific cellular events can be measured by ATR-FTIR and that this technique can be used to identify specific agents via the responses of the cell biosensor at different time points postexposure.

  18. Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System.

    PubMed

    Wang, Yu-Long; Shi, Peng; Lim, Cheng-Chew; Liu, Yuan

    2016-12-01

    This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.

  19. Method for the depth corrected detection of ionizing events from a co-planar grids sensor

    DOEpatents

    De Geronimo, Gianluigi; Bolotnikov, Aleksey E.; Carini, Gabriella

    2009-05-12

    A method for the detection of ionizing events utilizing a co-planar grids sensor comprising a semiconductor substrate, cathode electrode, collecting grid and non-collecting grid. The semiconductor substrate is sensitive to ionizing radiation. A voltage less than 0 Volts is applied to the cathode electrode. A voltage greater than the voltage applied to the cathode is applied to the non-collecting grid. A voltage greater than the voltage applied to the non-collecting grid is applied to the collecting grid. The collecting grid and the non-collecting grid are summed and subtracted creating a sum and difference respectively. The difference and sum are divided creating a ratio. A gain coefficient factor for each depth (distance between the ionizing event and the collecting grid) is determined, whereby the difference between the collecting electrode and the non-collecting electrode multiplied by the corresponding gain coefficient is the depth corrected energy of an ionizing event. Therefore, the energy of each ionizing event is the difference between the collecting grid and the non-collecting grid multiplied by the corresponding gain coefficient. The depth of the ionizing event can also be determined from the ratio.

  20. Data mining in the US Vaccine Adverse Event Reporting System (VAERS): early detection of intussusception and other events after rotavirus vaccination.

    PubMed

    Niu, M T; Erwin, D E; Braun, M M

    2001-09-14

    The Vaccine Adverse Event Reporting System (VAERS) is the US passive surveillance system monitoring vaccine safety. A major limitation of VAERS is the lack of denominator data (number of doses of administered vaccine), an element necessary for calculating reporting rates. Empirical Bayesian data mining, a data analysis method, utilizes the number of events reported for each vaccine and statistically screens the database for higher than expected vaccine-event combinations signaling a potential vaccine-associated event. This is the first study of data mining in VAERS designed to test the utility of this method to detect retrospectively a known side effect of vaccination-intussusception following rotavirus (RV) vaccine. From October 1998 to December 1999, 112 cases of intussusception were reported. The data mining method was able to detect a signal for RV-intussusception in February 1999 when only four cases were reported. These results demonstrate the utility of data mining to detect significant vaccine-associated events at early date. Data mining appears to be an efficient and effective computer-based program that may enhance early detection of adverse events in passive surveillance systems.

  1. Syndromic Surveillance Based on Emergency Visits: A Reactive Tool for Unusual Events Detection

    PubMed Central

    Vilain, Pascal; Bourdé, Arnaud; Cassou, Pierre-Jean Marianne dit; Jacques-Antoine, Yves; Morbidelli, Philippe; Filleul, Laurent

    2013-01-01

    Objective To show with examples that syndromic surveillance system can be a reactive tool for public health surveillance. Introduction The late health events such as the heat wave of 2003 showed the need to make public health surveillance evolve in France. Thus, the French Institute for Public Health Surveillance has developed syndromic surveillance systems based on several information sources such as emergency departments (1). In Reunion Island, the chikungunya outbreak of 2005–2006, then the influenza pandemic of 2009 contributed to the implementation and the development of this surveillance system (2–3). In the past years, this tool allowed to follow and measure the impact of seasonal epidemics. Nevertheless, its usefulness for the detection of minor unusual events had yet to be demonstrated. Methods In Reunion Island, the syndromic surveillance system is based on the activity of six emergency departments. Two types of indicators are constructed from collected data: - Qualitative indicators for the alert (every visit whose diagnostic relates to a notifiable disease or potential epidemic disease);- Quantitative indicators for the epidemic/cluster detection (number of visits based on syndromic grouping). Daily and weekly analyses are carried out. A decision algorithm allows to validate the signal and to organize an epidemiological investigation if necessary. Results Each year, about 150 000 visits are registered in the six emergency departments that is 415 consultations per day on average. Several unusual health events on small-scale were detected early. In August 2011, the surveillance system allowed to detect the first autochthonous cases of measles, a few days before this notifiable disease was reported to health authorities (Figure 1). In January 2012, the data of emergency departments allowed to validate the signal of viral meningitis as well as to detect a cluster in the West of the island and to follow its trend. In June 2012, a family foodborne illness

  2. Advanced Geospatial Hydrodynamic Signals Analysis for Tsunami Event Detection and Warning

    NASA Astrophysics Data System (ADS)

    Arbab-Zavar, Banafshe; Sabeur, Zoheir

    2013-04-01

    Current early tsunami warning can be issued upon the detection of a seismic event which may occur at a given location offshore. This also provides an opportunity to predict the tsunami wave propagation and run-ups at potentially affected coastal zones by selecting the best matching seismic event from a database of pre-computed tsunami scenarios. Nevertheless, it remains difficult and challenging to obtain the rupture parameters of the tsunamigenic earthquakes in real time and simulate the tsunami propagation with high accuracy. In this study, we propose a supporting approach, in which the hydrodynamic signal is systematically analysed for traces of a tsunamigenic signal. The combination of relatively low amplitudes of a tsunami signal at deep waters and the frequent occurrence of background signals and noise contributes to a generally low signal to noise ratio for the tsunami signal; which in turn makes the detection of this signal difficult. In order to improve the accuracy and confidence of detection, a re-identification framework in which a tsunamigenic signal is detected via the scan of a network of hydrodynamic stations with water level sensing is performed. The aim is to attempt the re-identification of the same signatures as the tsunami wave spatially propagates through the hydrodynamic stations sensing network. The re-identification of the tsunamigenic signal is technically possible since the tsunami signal at the open ocean itself conserves its birthmarks relating it to the source event. As well as supporting the initial detection and improving the confidence of detection, a re-identified signal is indicative of the spatial range of the signal, and thereby it can be used to facilitate the identification of certain background signals such as wind waves which do not have as large a spatial reach as tsunamis. In this paper, the proposed methodology for the automatic detection of tsunamigenic signals has been achieved using open data from NOAA with a recorded

  3. BioSense: implementation of a National Early Event Detection and Situational Awareness System.

    PubMed

    Bradley, Colleen A; Rolka, H; Walker, D; Loonsk, J

    2005-08-26

    BioSense is a CDC initiative to support enhanced early detection, quantification, and localization of possible biologic terrorism attacks and other events of public health concern on a national level. The goals of the BioSense initiative are to advance early detection by providing the standards, infrastructure, and data acquisition for near real-time reporting, analytic evaluation and implementation, and early event detection support for state and local public health officials. BioSense collects and analyzes Department of Defense and Department of Veterans Affairs ambulatory clinical diagnoses and procedures and Laboratory Corporation of America laboratory-test orders. The application summarizes and presents analytical results and data visualizations by source, day, and syndrome for each ZIP code, state, and metropolitan area through maps, graphs, and tables. An initial proof of a concept evaluation project was conducted before the system was made available to state and local users in April 2004. User recruitment involved identifying and training BioSense administrators and users from state and local health departments. User support has been an essential component of the implementation and enhancement process. CDC initiated the BioIntelligence Center (BIC) in June 2004 to conduct internal monitoring of BioSense national data daily. BIC staff have supported state and local system monitoring, conducted data anomaly inquiries, and communicated with state and local public health officials. Substantial investments will be made in providing regional, state, and local data for early event detection and situational awareness, test beds for data and algorithm evaluation, detection algorithm development, and data management technologies, while maintaining the focus on state and local public health needs.

  4. Group localisation and unsupervised detection and classification of basic crowd behaviour events for surveillance applications

    NASA Astrophysics Data System (ADS)

    Roubtsova, Nadejda S.; de With, Peter H. N.

    2013-02-01

    Technology for monitoring crowd behaviour is in demand for surveillance and security applications. The trend in research is to tackle detection of complex crowd behaviour events (panic, ght, evacuation etc.) directly using machine learning techniques. In this paper, we present a contrary, bottom-up approach seeking basic group information: (1) instantaneous location and (2) the merge, split and lateral slide-by events - the three basic motion patterns comprising any crowd behaviour. The focus on such generic group information makes our algorithm suitable as a building block in a variety of surveillance systems, possibly integrated with static content analysis solutions. Our feature extraction framework has optical ow in its core. The framework is universal being motion-based, rather than object-detection-based and generates a large variety of motion-blob- characterising features useful for an array of classi cation problems. Motion-based characterisation is performed on a group as an atomic whole and not by means of superposition of individual human motions. Within that feature space, our classi cation system makes decisions based on heuristic rules and thresholds, without machine learning. Our system performs well on group localisation, consistently generating contours around both moving and halted groups. The visual output of our periodical group localisation is equivalent to tracking and the group contour accuracy ranges from adequate to exceptionally good. The system successfully detects and classi es within our merge/split/slide-by event space in surveillance-type video sequences, di ering in resolution, scale, quality and motion content. Quantitatively, its performance is characterised by a good recall: 83% on detection and 71% on combined detection and classi cation.

  5. Seismic Event Identification Using Scanning Detection: A Comparison of Denoising and Classification Methods

    NASA Astrophysics Data System (ADS)

    Rowe, C. A.; MacCarthy, J. K.; Giudicepietro, F.

    2005-12-01

    Automatic detection and classification methods are increasingly important in observatory operations, as the volume and rate of incoming data exceed the capacity of human analysis staff to process the data in near-real-time. We explore the success of scanning detection for similar event identification in a variety of seismic waveform catalogs. Several waveform pre-processing methods are applied to previously recorded events which are scanned through triggered and continuous waveform catalogs to determine the success and false alarm rate for detections of repeating signals. Pre-processing approaches include adaptive, cross-coherency filtering, adaptive, auto-associative neural network filtering, discrete wavelet package decomposition and linear predictive coding as well as suites of standard bandpass filters. Classification / detection methods for the various pre-processed signals are applied to investigate the robustness of the individual and combined approaches. The classifiers as applied to the processed waveforms include dendrogram-based clustering and neural network classifiers. We will present findings for the various combinations of methods as applied to tectonic earthquakes, mine blasts and volcanic seismicity.

  6. Application of data cubes for improving detection of water cycle extreme events

    NASA Astrophysics Data System (ADS)

    Teng, W. L.; Albayrak, A.

    2015-12-01

    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 for 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 (WCE) events, a specific case of anomaly detection, requiring time series data. We investigate the use of the sequential probability ratio test (SPRT) for anomaly detection and support vector machines (SVM) for anomaly classification. We show an example of detection of WCE events, using the Global Land Data Assimilation Systems (GLDAS) data set.

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Fault detection and isolation in manufacturing systems with an identified discrete event model

    NASA Astrophysics Data System (ADS)

    Roth, Matthias; Schneider, Stefan; Lesage, Jean-Jacques; Litz, Lothar

    2012-10-01

    In this article a generic method for fault detection and isolation (FDI) in manufacturing systems considered as discrete event systems (DES) is presented. The method uses an identified model of the closed-loop of plant and controller built on the basis of observed fault-free system behaviour. An identification algorithm known from literature is used to determine the fault detection model in form of a non-deterministic automaton. New results of how to parameterise this algorithm are reported. To assess the fault detection capability of an identified automaton, probabilistic measures are proposed. For fault isolation, the concept of residuals adapted for DES is used by defining appropriate set operations representing generic fault symptoms. The method is applied to a case study system.

  9. Bio-inspired WSN architecture: event detection and loacalization in a fault tolerant WSN

    NASA Astrophysics Data System (ADS)

    Alayev, Yosef; Damarla, Thyagaraju

    2009-05-01

    One can think of human body as a sensory network. In particular, skin has several neurons that provide the sense of touch with different sensitivities, and neurons for communicating the sensory signals to the brain. Even though skin might occasionally experience some lacerations, it performs remarkably well (fault tolerant) with the failure of some sensors. One of the challenges in collaborative wireless sensor networks (WSN) is fault tolerant detection and localization of targets. In this paper we present a biologically inspired architecture model for WSN. Diagnosis of sensors in WSN model presented here is derived from the concept of the immune system. We present an architecture for WSN for detection and localization of multiple targets inspired by human nervous system. We show that the advantages of such bio-inspired networks are reduced data for communication, self-diagnosis to detect faulty sensors in real-time and the ability to localize events. We present the results of our algorithms on simulation data.

  10. The temporal reliability of sound modulates visual detection: an event-related potential study.

    PubMed

    Li, Qi; Wu, Yan; Yang, Jingjing; Wu, Jinglong; Touge, Tetsuo

    2015-01-01

    Utilizing the high temporal resolution of event-related potentials (ERPs), we examined the effects of temporal reliability of sounds on visual detection. Significantly faster reaction times to visual target stimuli were observed when reliable temporal information was provided by a task-irrelevant auditory stimulus. Three main ERP components related to the effects of auditory temporal reliability were found: the first at 180-240 ms over a wide central area, the second at 300-400 ms over an anterior area, and the third at 300-380 ms over bilateral temporal areas. Our results support the hypothesis that temporal reliability affects visual detection and indicate that auditory facilitation of visual detection is partly due to spread of attention and thus results from implicit temporal linking of auditory and visual information at a relatively late processing stage.

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

    PubMed

    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.

  12. An evaluation of generalized likelihood Ratio Outlier Detection to identification of seismic events in Western China

    SciTech Connect

    Taylor, S.R.; Hartse, H.E.

    1996-09-24

    The Generalized Likelihood Ratio Outlier Detection Technique for seismic event identification is evaluated using synthetic test data and frequency-dependent P{sub g}/L{sub g} measurements from western China. For most seismic stations that are to be part of the proposed International Monitoring System for the Comprehensive Test Ban Treaty, there will be few or no nuclear explosions in the magnitude range of interest (e.g. M{sub b} < 4) on which to base an event-identification system using traditional classification techniques. Outlier detection is a reasonable alternative approach to the seismic discrimination problem when no calibration explosions are available. Distance-corrected P{sub g}/L{sub g} data in seven different frequency bands ranging from 0.5 to 8 Hz from the Chinese Digital Seismic Station WMQ are used to evaluate the technique. The data are collected from 157 known earthquakes, 215 unknown events (presumed earthquakes and possibly some industrial explosions), and 18 known nuclear explosions (1 from the Chinese Lop Nor test site and 17 from the East Kazakh test site). A feature selection technique is used to find the best combination of discriminants to use for outlier detection. Good discrimination performance is found by combining a low-frequency (0.5 to 1 Hz) P{sub g}/L{sub g} ratio with high-frequency ratios (e.g. 2 to 4 and 4 to 8 Hz). Although the low-frequency ratio does not discriminate between earthquakes and nuclear explosions well by itself, it can be effectively combined with the high-frequency discriminants. Based on the tests with real and synthetic data, the outlier detection technique appears to be an effective approach to seismic monitoring in uncalibrated regions.

  13. Exupery volcano fast response system - The event detection and waveform classification system

    NASA Astrophysics Data System (ADS)

    Hammer, Conny; Ohrnberger, Matthias

    2010-05-01

    Volcanic eruptions are often preceded by seismic activity which can be used to quantify the volcanic activity since the number and the size of certain types of seismic events usually increase before periods of volcanic crisis. The implementation of an automatic detection and classification system for seismic signals of volcanic origin allows not only for the processing of large amounts of data in short time, but also provides consistent and time-invariant results. Here, we have developed a system based upon a combination of different methods. To enable a first robust event detection in the continuous data stream different modules are implemented in the real time system Earthworm which is widely distributed in active volcano monitoring observatories worldwide. Among those software modules are classical trigger algorithm like STA/LTA and cross-correlation master event matching which is also used to detect different classes of signals. Furthermore an additional module is implemented in the real time system to compute continuous activity parameters which are also used to quantify the volcanic activity. Most automatic classification systems need a sufficiently large pre-classified data set for training the system. However in case of a volcanic crisis we are often confronted with a lack of training data due to insufficient prior observations because prior data acquisition might be carried out with different equipment at a low number of sites and due to the imminent crisis there might be no time for the time-consuming and tedious process of preparing a training data set. For this reason we have developed a novel seismic event spotting technique in order to be less dependent on the existence of previously acquired data bases of event classes. One main goal is therefore to provide observatory staff with a robust event classification based on a minimum number of reference waveforms. By using a "learning-while-recording" approach we are allowing for the fast build-up of a

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

    PubMed Central

    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

  15. Gait event detection for use in FES rehabilitation by radial and tangential foot accelerations.

    PubMed

    Rueterbories, Jan; Spaich, Erika G; Andersen, Ole K

    2014-04-01

    Gait rehabilitation by Functional Electrical Stimulations (FESs) requires a reliable trigger signal to start the stimulations. This could be obtained by a simple switch under the heel or by means of an inertial sensor system. This study provides an algorithm to detect gait events in differential acceleration signals of the foot. The key feature of differential measurements is that they compensate the impact of gravity. The real time detection capability of a rule based algorithm in healthy and hemiparetic individuals was investigated. Detection accuracy and precision compared to signals from foot switches were evaluated. The algorithm detected curve features of the vectorial sum of radial and tangential accelerations and mapped those to discrete gait states. The results showed detection rates for healthy and hemiparetic gait ranging form 84.2% to 108.5%. The sensitivity was between 0.81 and 1, and the specificity between 0.85 and 1, depending on gait phase and group of subjects. The algorithm detected gait phase changes earlier than the reference. Differential acceleration signals combined with the proposed algorithm have the potential to be implemented in a future FES system.

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

    SciTech Connect

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

    2014-12-18

    Background: 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. Results: 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. Conclusions: 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.

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

    DTIC Science & Technology

    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...Automatic burst detection for the EEG of the preterm infant . Physiol Meas 32: 1623. doi:10.1088/0967–3334/32/10/010. 6. Chin-Teng Lin, Che-Jui Chang, Bor

  18. Detection of abnormal resting-state networks in individual patients suffering from focal epilepsy: an initial step toward individual connectivity assessment

    PubMed Central

    Dansereau, Christian L.; Bellec, Pierre; Lee, Kangjoo; Pittau, Francesca; Gotman, Jean; Grova, Christophe

    2014-01-01

    The spatial coherence of spontaneous slow fluctuations in the blood-oxygen-level dependent (BOLD) signal at rest is routinely used to characterize the underlying resting-state networks (RSNs). Studies have demonstrated that these patterns are organized in space and highly reproducible from subject to subject. Moreover, RSNs reorganizations have been suggested in pathological conditions. Comparisons of RSNs organization have been performed between groups of subjects but have rarely been applied at the individual level, a step required for clinical application. Defining the notion of modularity as the organization of brain activity in stable networks, we propose Detection of Abnormal Networks in Individuals (DANI) to identify modularity changes at the individual level. The stability of each RSN was estimated using a spatial clustering method: Bootstrap Analysis of Stable Clusters (BASC) (Bellec et al., 2010). Our contributions consisted in (i) providing functional maps of the most stable cores of each networks and (ii) in detecting “abnormal” individual changes in networks organization when compared to a population of healthy controls. DANI was first evaluated using realistic simulated data, showing that focussing on a conservative core size (50% most stable regions) improved the sensitivity to detect modularity changes. DANI was then applied to resting state fMRI data of six patients with focal epilepsy who underwent multimodal assessment using simultaneous EEG/fMRI acquisition followed by surgery. Only patient with a seizure free outcome were selected and the resected area was identified using a post-operative MRI. DANI automatically detected abnormal changes in 5 out of 6 patients, with excellent sensitivity, showing for each of them at least one “abnormal” lateralized network closely related to the epileptic focus. For each patient, we also detected some distant networks as abnormal, suggesting some remote reorganization in the epileptic brain. PMID

  19. Detection of Visual Events in Underwater Video Using a Neuromorphic Saliency-based Attention System

    NASA Astrophysics Data System (ADS)

    Edgington, D. R.; Walther, D.; Cline, D. E.; Sherlock, R.; Salamy, K. A.; Wilson, A.; Koch, C.

    2003-12-01

    The Monterey Bay Aquarium Research Institute (MBARI) uses high-resolution video equipment on remotely operated vehicles (ROV) to obtain quantitative data on the distribution and abundance of oceanic animals. High-quality video data supplants the traditional approach of assessing the kinds and numbers of animals in the oceanic water column through towing collection nets behind ships. Tow nets are limited in spatial resolution, and often destroy abundant gelatinous animals resulting in species undersampling. Video camera-based quantitative video transects (QVT) are taken through the ocean midwater, from 50m to 4000m, and provide high-resolution data at the scale of the individual animals and their natural aggregation patterns. However, the current manual method of analyzing QVT video by trained scientists is labor intensive and poses a serious limitation to the amount of information that can be analyzed from ROV dives. Presented here is an automated system for detecting marine animals (events) visible in the videos. Automated detection is difficult due to the low contrast of many translucent animals and due to debris ("marine snow") cluttering the scene. Video frames are processed with an artificial intelligence attention selection algorithm that has proven a robust means of target detection in a variety of natural terrestrial scenes. The candidate locations identified by the attention selection module are tracked across video frames using linear Kalman filters. Typically, the occurrence of visible animals in the video footage is sparse in space and time. A notion of "boring" video frames is developed by detecting whether or not there is an interesting candidate object for an animal present in a particular sequence of underwater video -- video frames that do not contain any "interesting" events. If objects can be tracked successfully over several frames, they are stored as potentially "interesting" events. Based on low-level properties, interesting events are

  20. Persistent Homological Sparse Network Approach to Detecting White Matter Abnormality in Maltreated Children: MRI and DTI Multimodal Study

    PubMed Central

    Chung, Moo K.; Hanson, Jamie L.; Lee, Hyekyoung; Adluru, Nagesh; Alexander, Andrew L.; Davidson, Richard J.; Pollak, Seth D.

    2014-01-01

    We present a novel persistent homological sparse network analysis framework for characterizing white matter abnormalities in tensor-based morphometry (TBM) in magnetic resonance imaging (MRI). Traditionally TBM is used in quantifying tissue volume change in each voxel in a massive univariate fashion. However, this obvious approach cannot be used in testing, for instance, if the change in one voxel is related to other voxels. To address this limitation of univariate-TBM, we propose a new persistent homological approach to testing more complex relational hypotheses across brain regions. The proposed methods are applied to characterize abnormal white matter in maltreated children. The results are further validated using fractional anisotropy (FA) values in diffusion tensor imaging (DTI). PMID:24505679

  1. Detecting consciousness in a total locked-in syndrome: an active event-related paradigm.

    PubMed

    Schnakers, Caroline; Perrin, Fabien; Schabus, Manuel; Hustinx, Roland; Majerus, Steve; Moonen, Gustave; Boly, Melanie; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurelie; Laureys, Steven

    2009-08-01

    Total locked-in syndrome is characterized by tetraplegia, anarthria and paralysis of eye motility. In this study, consciousness was detected in a 21-year-old woman who presented a total locked-in syndrome after a basilar artery thrombosis (49 days post-injury) using an active event-related paradigm. The patient was presented sequences of names containing the patient's own name and other names. The patient was instructed to count her own name or to count another target name. Similar to 4 age- and gender-matched healthy controls, the P3 response recorded for the voluntarily counted own name was larger than while passively listening. This P3 response was observed 14 days before the first behavioral signs of consciousness. This study shows that our active event-related paradigm allowed to identify voluntary brain activity in a patient who would behaviorally be diagnosed as comatose.

  2. Shared clonal cytogenetic abnormalities in aberrant mast cells and leukemic myeloid blasts detected by single nucleotide polymorphism microarray-based whole-genome scanning.

    PubMed

    Frederiksen, John K; Shao, Lina; Bixby, Dale L; Ross, Charles W

    2016-04-01

    Systemic mastocytosis (SM) is characterized by a clonal proliferation of aberrant mast cells within extracutaneous sites. In a subset of SM cases, a second associated hematologic non-mast cell disease (AHNMD) is also present, usually of myeloid origin. Polymerase chain reaction and targeted fluorescence in situ hybridization studies have provided evidence that, in at least some cases, the aberrant mast cells are related clonally to the neoplastic cells of the AHNMD. In this work, a single nucleotide polymorphism microarray (SNP-A) was used to characterize the cytogenetics of the aberrant mast cells from a patient with acute myeloid leukemia and concomitant mast cell leukemia associated with a KIT D816A mutation. The results demonstrate the presence of shared cytogenetic abnormalities between the mast cells and myeloid blasts, as well as additional abnormalities within mast cells (copy-neutral loss of heterozygosity) not detectable by routine karyotypic analysis. To our knowledge, this work represents the first application of SNP-A whole-genome scanning to the detection of shared cytogenetic abnormalities between the two components of a case of SM-AHNMD. The findings provide additional evidence of a frequent clonal link between aberrant mast cells and cells of myeloid AHNMDs, and also highlight the importance of direct sequencing for identifying uncommon activating KIT mutations.

  3. Detecting tidal disruption events of massive black holes in normal galaxies with the Einstein Probe

    NASA Astrophysics Data System (ADS)

    Yuan, W.; Komossa, S.; Zhang, C.; Feng, H.; Ling, Z.-X.; Zhao, D. H.; Zhang, S.-N.; Osborne, J. P.; O'Brien, P.; Willingale, R.; Lapington, J.; Lapington

    2016-02-01

    Stars are tidally disrupted and accreted when they approach massive black holes (MBHs) closely, producing a flare of electromagnetic radiation. The majority of the (approximately two dozen) tidal disruption events (TDEs) identified so far have been discovered by their luminous, transient X-ray emission. Once TDEs are detected in much larger numbers, in future dedicated transient surveys, a wealth of new applications will become possible. Here, we present the proposed Einstein Probe mission, which is a dedicated time-domain soft X-ray all-sky monitor aiming at detecting X-ray transients including TDEs in large numbers. The mission consists of a wide-field micro-pore Lobster-eye imager (60° × 60°), and is designed to carry out an all-sky transient survey at energies of 0.5-4 keV. It will also carry a more sensitive telescope for X-ray follow-ups, and will be capable of issuing public transient alerts rapidly. Einstein Probe is expected to revolutionise the field of TDE research by detecting several tens to hundreds of events per year from the early phase of flares, many with long-term, well sampled lightcurves.

  4. Foot contact event detection using kinematic data in cerebral palsy children and normal adults gait.

    PubMed

    Desailly, Eric; Daniel, Yepremian; Sardain, Philippe; Lacouture, Patrick

    2009-01-01

    Initial contact (IC) and toe off (TO) times are essential measurements in the analysis of temporal gait parameters, especially in cerebral palsy (CP) gait analysis. A new gait event detection algorithm, called the high pass algorithm (HPA) has been developed and is discussed in this paper. Kinematics of markers on the heel and metatarsal are used. Their forward components are high pass filtered, to amplify the contact discontinuities, thus the local extrema of the processed signal correspond to IC and TO. The accuracy and precision of HPA are compared with the gold standard of foot contact event detection, that is, force plate measurements. Furthermore HPA is compared with two other kinematics methods. This study has been conducted on 20 CP children and on eight normal adults. For normal subjects all the methods performed equally well. True errors in HPA (mean+/-standard deviation) were found to be 1+/-23 ms for IC and 2+/-25 ms for TO in CP children. These results were significantly (p<0.05) more accurate and precise than those obtained using the other algorithms. Moreover, in the case of pathological gaits, the other methods are not suitable for IC detection when IC is flatfoot or forefoot. In conclusion, the HPA is a simple and robust algorithm, which performs equally well for adults and actually performs better when applied to the gait of CP children. It is therefore recommended as the method of choice.

  5. Femtomolar detection of single mismatches by discriminant analysis of DNA hybridization events using gold nanoparticles.

    PubMed

    Ma, Xingyi; Sim, Sang Jun

    2013-03-21

    Even though DNA-based nanosensors have been demonstrated for quantitative detection of analytes and diseases, hybridization events have never been numerically investigated for further understanding of DNA mediated interactions. Here, we developed a nanoscale platform with well-designed capture and detection gold nanoprobes to precisely evaluate the hybridization events. The capture gold nanoprobes were mono-laid on glass and the detection probes were fabricated via a novel competitive conjugation method. The two kinds of probes combined in a suitable orientation following the hybridization with the target. We found that hybridization efficiency was markedly dependent on electrostatic interactions between DNA strands, which can be tailored by adjusting the salt concentration of the incubation solution. Due to the much lower stability of the double helix formed by mismatches, the hybridization efficiencies of single mismatched (MMT) and perfectly matched DNA (PMT) were different. Therefore, we obtained an optimized salt concentration that allowed for discrimination of MMT from PMT without stringent control of temperature or pH. The results indicated this to be an ultrasensitive and precise nanosensor for the diagnosis of genetic diseases.

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

    NASA Technical Reports Server (NTRS)

    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).

  7. Detectable urogenital schistosome DNA and cervical abnormalities 6 months after single-dose praziquantel in women with Schistosoma haematobium infection.

    PubMed

    Downs, Jennifer A; Kabangila, Rodrick; Verweij, Jaco J; Jaka, Hyasinta; Peck, Robert N; Kalluvya, Samuel E; Changalucha, John M; Johnson, Warren D; van Lieshout, Lisette; Fitzgerald, Daniel W

    2013-09-01

    We explored response to single-dose praziquantel therapy in a cohort of 33 women with Schistosoma haematobium infection in rural Mwanza, Tanzania. Women with S. haematobium infection confirmed both by eggs in urine and by polymerase chain reaction (PCR) received single-dose praziquantel and treatment of concomitant sexually transmitted infections. Macroscopic cervical abnormalities were also quantified. After 6 months, microscopically detectable egg excretion was eliminated, but 8 of 33 women (24%) were persistently positive for S. haematobium by PCR, and 11 (33%) had cervical abnormalities potentially attributable to schistosomiasis. This suggests that praziquantel treatment more frequently than every 6 months may be necessary for complete elimination of the parasite and prevention of genital tissue pathology. This aggressive therapy may in turn play a key role decreasing HIV susceptibility in millions of people living in regions in which S. haematobium is endemic.

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

    PubMed

    Cron, Andrew; Gouttefangeas, Cécile; Frelinger, Jacob; Lin, Lin; Singh, Satwinder K; Britten, Cedrik M; Welters, Marij J P; van der Burg, Sjoerd H; West, Mike; Chan, Cliburn

    2013-01-01

    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 consistent labeling

  9. Automated detection and analysis of depolarization events in human cardiomyocytes using MaDEC.

    PubMed

    Szymanska, Agnieszka F; Heylman, Christopher; Datta, Rupsa; Gratton, Enrico; Nenadic, Zoran

    2016-08-01

    Optical imaging-based methods for assessing the membrane electrophysiology of in vitro human cardiac cells allow for non-invasive temporal assessment of the effect of drugs and other stimuli. Automated methods for detecting and analyzing the depolarization events (DEs) in image-based data allow quantitative assessment of these different treatments. In this study, we use 2-photon microscopy of fluorescent voltage-sensitive dyes (VSDs) to capture the membrane voltage of actively beating human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). We built a custom and freely available Matlab software, called MaDEC, to detect, quantify, and compare DEs of hiPS-CMs treated with the β-adrenergic drugs, propranolol and isoproterenol. The efficacy of our software is quantified by comparing detection results against manual DE detection by expert analysts, and comparing DE analysis results to known drug-induced electrophysiological effects. The software accurately detected DEs with true positive rates of 98-100% and false positive rates of 1-2%, at signal-to-noise ratios (SNRs) of 5 and above. The MaDEC software was also able to distinguish control DEs from drug-treated DEs both immediately as well as 10min after drug administration.

  10. Reduction of net primary productivity in southern China caused by abnormal low-temperature freezing in winter of 2008 detected by a remote sensing-driven ecosystem model

    NASA Astrophysics Data System (ADS)

    Ju, W.; Liu, Y.; Zhou, Y.; Zhu, G.

    2011-12-01

    Terrestrial carbon cycle is an important determinant of global climate change and affected by various factors, including climate, CO2 concentration, atmospheric nitrogen deposition and human activities. Extreme weather events can significantly regulate short-term even long-term carbon exchanges between terrestrial ecosystems and the atmosphere. During the period from the middle January to the middle February 2008, Southern China was seriously hit by abnormal low-temperature freezing, which caused serous damages to forests and crops. However, the reduction of net primary productivity (NPP) of terrestrial ecosystems caused by this extremely abnormal weather event has not been quantitatively investigated. In this study, the Boreal Ecosystem Productivity Simulator (BEPS) model was employed to assess the reduction of NPP in Southern China caused by the abnormal low-temperature freezing. Prior to the regional simulation, the BEPS model was validated using measured NPP in different ecosystems, demonstrating the ability of this model to simulate NPP reliably in China. Then, it was forced using meteorological data interpolated from observations of weather stations and leaf area index inversed from MODIS reflectance data to simulate national wide NPP at a 500 m resolution for the period from 2003 to 2008. The departures of NPP in 2008 from the means during 2003-2007 were used as the indicator of NPP reduction caused by the low-temperature freezing. It was found out that NPP in 2008 decreased significantly in forests of Southern China, especially in Guangdong, Fujian, Zhejiang, Guangxi, Jiangxi, and Hunan Provinces, in which the low-temperature freeing was more serious. The annul reduction of NPP was above 150 g C/m^2/yr in these areas. Key words: Net Primary Productivity, low-temperature freezing, BEPS model, MODIS Correspondence author: Weimin Ju Email:juweimin@nju.edu.cn

  11. Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury

    PubMed Central

    Huang, Ming-Xiong; Nichols, Sharon; Baker, Dewleen G.; Robb, Ashley; Angeles, Annemarie; Yurgil, Kate A.; Drake, Angela; Levy, Michael; Song, Tao; McLay, Robert; Theilmann, Rebecca J.; Diwakar, Mithun; Risbrough, Victoria B.; Ji, Zhengwei; Huang, Charles W.; Chang, Douglas G.; Harrington, Deborah L.; Muzzatti, Laura; Canive, Jose M.; Christopher Edgar, J.; Chen, Yu-Han; Lee, Roland R.

    2014-01-01

    Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI) can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz) that can be measured and localized by resting-state magnetoencephalography (MEG). In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz) from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes), our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes), blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI. PMID:25009772

  12. Detection of planets in extremely weak central perturbation microlensing events via next-generation ground-based surveys

    SciTech Connect

    Chung, Sun-Ju; Lee, Chung-Uk; Koo, Jae-Rim E-mail: leecu@kasi.re.kr

    2014-04-20

    Even though the recently discovered high-magnification event MOA-2010-BLG-311 had complete coverage over its peak, confident planet detection did not happen due to extremely weak central perturbations (EWCPs, fractional deviations of ≲ 2%). For confident detection of planets in EWCP events, it is necessary to have both high cadence monitoring and high photometric accuracy better than those of current follow-up observation systems. The next-generation ground-based observation project, Korea Microlensing Telescope Network (KMTNet), satisfies these conditions. We estimate the probability of occurrence of EWCP events with fractional deviations of ≤2% in high-magnification events and the efficiency of detecting planets in the EWCP events using the KMTNet. From this study, we find that the EWCP events occur with a frequency of >50% in the case of ≲ 100 M {sub E} planets with separations of 0.2 AU ≲ d ≲ 20 AU. We find that for main-sequence and sub-giant source stars, ≳ 1 M {sub E} planets in EWCP events with deviations ≤2% can be detected with frequency >50% in a certain range that changes with the planet mass. However, it is difficult to detect planets in EWCP events of bright stars like giant stars because it is easy for KMTNet to be saturated around the peak of the events because of its constant exposure time. EWCP events are caused by close, intermediate, and wide planetary systems with low-mass planets and close and wide planetary systems with massive planets. Therefore, we expect that a much greater variety of planetary systems than those already detected, which are mostly intermediate planetary systems, regardless of the planet mass, will be significantly detected in the near future.

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

    PubMed

    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.

  14. Detecting event-related recurrences by symbolic analysis: applications to human language processing

    PubMed Central

    beim Graben, Peter; Hutt, Axel

    2015-01-01

    Quasi-stationarity is ubiquitous in complex dynamical systems. In brain dynamics, there is ample evidence that event-related potentials (ERPs) reflect such quasi-stationary states. In order to detect them from time series, several segmentation techniques have been proposed. In this study, we elaborate a recent approach for detecting quasi-stationary states as recurrence domains by means of recurrence analysis and subsequent symbolization methods. We address two pertinent problems of contemporary recurrence analysis: optimizing the size of recurrence neighbourhoods and identifying symbols from different realizations for sequence alignment. As possible solutions for these problems, we suggest a maximum entropy criterion and a Hausdorff clustering algorithm. The resulting recurrence domains for single-subject ERPs are obtained as partition cells reflecting quasi-stationary brain states. PMID:25548270

  15. Predicting Negative Events: Using Post-discharge Data to Detect High-Risk Patients

    PubMed Central

    Sulieman, Lina; Fabbri, Daniel; Wang, Fei; Hu, Jianying; Malin, Bradley A

    2016-01-01

    Predicting negative outcomes, such as readmission or death, and detecting high-risk patients are important yet challenging problems in medical informatics. Various models have been proposed to detect high-risk patients; however, the state of the art relies on patient information collected before or at the time of discharge to predict future outcomes. In this paper, we investigate the effect of including data generated post discharge to predict negative outcomes. Specifically, we focus on two types of patients admitted to the Vanderbilt University Medical Center between 2010-2013: i) those with an acute event - 704 hip fractures and ii) those with chronic problems — 5250 congestive heart failure (CHF) patients. We show that the post-discharge model improved the AUC of the LACE index, a standard readmission scoring function, by 20 - 30%. Moreover, the new model resulted in higher AUCs by 15 - 27% for hip fracture and 10 - 12% for CHF compared to standard models. PMID:28269914

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

    SciTech Connect

    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.

  17. Label-Free Detection of Single Living Bacteria via Electrochemical Collision Event

    PubMed Central

    Lee, Ji Young; Kim, Byung-Kwon; Kang, Mijeong; Park, Jun Hui

    2016-01-01

    We detected single living bacterial cells on ultramicroelectrode (UME) using a single-particle collision method and optical microscopic methods. The number of collision events involving the bacterial cells indicated in current-time (i-t) curves corresponds to the number of bacterial cells (i.e., Escherichia coli) on the UME surface, as observed visually. Simulations were performed to determine the theoretical current response (75 pA) and frequency (0.47 pM−1 s−1) of single Escherichia coli collisions. The experimental current response (83 pA) and frequency (0.26 pM−1 s−1) were on the same order of magnitude as the theoretical values. This single-particle collision approach facilitates detecting living bacteria and determining their concentration in solution and could be widely applied to studying other bacteria and biomolecules. PMID:27435527

  18. Increasing cognitive load to facilitate lie detection: the benefit of recalling an event in reverse order.

    PubMed

    Vrij, Aldert; Mann, Samantha A; Fisher, Ronald P; Leal, Sharon; Milne, Rebecca; Bull, Ray

    2008-06-01

    In two experiments, we tested the hypotheses that (a) the difference between liars and truth tellers will be greater when interviewees report their stories in reverse order than in chronological order, and (b) instructing interviewees to recall their stories in reverse order will facilitate detecting deception. In Experiment 1, 80 mock suspects told the truth or lied about a staged event and did or did not report their stories in reverse order. The reverse order interviews contained many more cues to deceit than the control interviews. In Experiment 2, 55 police officers watched a selection of the videotaped interviews of Experiment 1 and made veracity judgements. Requesting suspects to convey their stories in reverse order improved police observers' ability to detect deception and did not result in a response bias.

  19. Automatic Event Detection and Characterization of solar events with IRIS, SDO/AIA and Hi-C

    NASA Astrophysics Data System (ADS)

    Alexander, Caroline; Fayock, Brian; Winebarger, Amy

    2016-05-01

    Dynamic, low-lying loops with peak temperatures <1 MK are observed throughout the solar transition region. These loops can be observed in SDO/AIA data due to some lower temperature spectral lines in the passbands, but have not been studied in great detail. We have developed a technique to automatically identify events (i.e., brightenings) on a pixel-by-pixel basis applying a set of selection criteria. The pixels are then grouped according to their proximity in space and relative progression of the event. This method allows us to characterize their overall lifetime and the rate at which these events occur. Our current progress includes identification of these groups of events in IRIS data, determination of their existence in AIA data, and characterization based on a comparison between the two. This technique has also been used on Hi-C data in preparation for the rocket re-flight in July 2016. Results on the success of this technique at identifying real structures and sources of heating will be shown.

  20. AKSED: adaptive knowledge-based system for event detection using collaborative unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Wang, X. Sean; Lee, Byung Suk; Sadjadi, Firooz

    2006-05-01

    Advances in sensor technology and image processing have made it possible to equip unmanned aerial vehicles (UAVs) with economical, high-resolution, energy-efficient sensors. Despite the improvements, current UAVs lack autonomous and collaborative operation capabilities, due to limited bandwidth and limited on-board image processing abilities. The situation, however, is changing. In the next generation of UAVs, much image processing can be carried out onboard and communication bandwidth problem will improve. More importantly, with more processing power, collaborative operations among a team of autonomous UAVs can provide more intelligent event detection capabilities. In this paper, we present ideas for developing a system enabling target recognitions by collaborative operations of autonomous UAVs. UAVs are configured in three stages: manufacturing, mission planning, and deployment. Different sets of information are needed at different stages, and the resulting outcome is an optimized event detection code deployed onto a UAV. The envisioned system architecture and the contemplated methodology, together with problems to be addressed, are presented.

  1. Development of electrochemical biosensor for detection of pathogenic microorganism in Asian dust events.

    PubMed

    Yoo, Min-Sang; Shin, Minguk; Kim, Younghun; Jang, Min; Choi, Yoon-E; Park, Si Jae; Choi, Jonghoon; Lee, Jinyoung; Park, Chulhwan

    2017-05-01

    We developed a single-walled carbon nanotubes (SWCNTs)-based electrochemical biosensor for the detection of Bacillus subtilis, one of the microorganisms observed in Asian dust events, which causes respiratory diseases such as asthma and pneumonia. SWCNTs plays the role of a transducer in biological antigen/antibody reaction for the electrical signal while 1-pyrenebutanoic acid succinimidyl ester (1-PBSE) and ant-B. subtilis were performed as a chemical linker and an acceptor, respectively, for the adhesion of target microorganism in the developed biosensor. The detection range (10(2)-10(10) CFU/mL) and the detection limit (10(2) CFU/mL) of the developed biosensor were identified while the response time was 10 min. The amount of target B. subtilis was the highest in the specificity test of the developed biosensor, compared with the other tested microorganisms (Staphylococcus aureus, Flavobacterium psychrolimnae, and Aquabacterium commune). In addition, target B. subtilis detected by the developed biosensor was observed by scanning electron microscope (SEM) analysis.

  2. Endpoint visual detection of three genetically modified rice events by loop-mediated isothermal amplification.

    PubMed

    Chen, Xiaoyun; Wang, Xiaofu; Jin, Nuo; Zhou, Yu; Huang, Sainan; Miao, Qingmei; Zhu, Qing; Xu, Junfeng

    2012-11-07

    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.

  3. The Waveform Correlation Event Detection System project, Phase II: Testing with the IDC primary network

    SciTech Connect

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

    1998-04-01

    Further improvements to the Waveform Correlation Event Detection System (WCEDS) developed by Sandia Laboratory have made it possible to test the system on the accepted Comprehensive Test Ban Treaty (CTBT) seismic monitoring network. For our test interval we selected a 24-hour period from December 1996, and chose to use the Reviewed Event Bulletin (REB) produced by the Prototype International Data Center (PIDC) as ground truth for evaluating the results. The network is heterogeneous, consisting of array and three-component sites, and as a result requires more flexible waveform processing algorithms than were available in the first version of the system. For simplicity and superior performance, we opted to use the spatial coherency algorithm of Wagner and Owens (1996) for both types of sites. Preliminary tests indicated that the existing version of WCEDS, which ignored directional information, could not achieve satisfactory detection or location performance for many of the smaller events in the REB, particularly those in the south Pacific where the network coverage is unusually sparse. To achieve an acceptable level of performance, we made modifications to include directional consistency checks for the correlations, making the regions of high correlation much less ambiguous. These checks require the production of continuous azimuth and slowness streams for each station, which is accomplished by means of FK processing for the arrays and power polarization processing for the three-component sites. In addition, we added the capability to use multiple frequency-banded data streams for each site to increase sensitivity to phases whose frequency content changes as a function of distance.

  4. Microstructural callosal abnormalities in normal-appearing brain of children with developmental delay detected with diffusion tensor imaging.

    PubMed

    Ding, Xiao-Qi; Sun, Yimeng; Kruse, Bernd; Illies, Till; Zeumer, Hermann; Fiehler, Jens; Lanfermann, Heinrich

    2009-06-01

    Callosal fibres play an important role in psychomotor and cognitive functions. The purpose of this study was to investigate possible microstructural abnormalities of the corpus callosum in children with developmental delay, who have normal conventional brain MR imaging results. Seventeen pediatric patients (aged 1-9 years) with developmental delay were studied. Quantitative T2 and fractional anisotropy (FA) values were measured at the genu and splenium of the corpus callosum (CC). Fibre tracking, volumetric determination, as well as fibre density calculations of the CC were also carried out. The results were compared with those of the age-matched healthy subjects. A general elevation of T2 relaxation times (105 ms in patients vs. 95 ms in controls) and reduction of the FA values (0.66 in patients vs. 0.74 in controls) at the genu of the CC were found in patients. Reductions of the fibre numbers (5,464 in patients vs. 8,886 in controls) and volumes (3,415 ml in patients vs. 5,235 ml in controls) of the CC were found only in patients older than 5 years. The study indicates that despite their inconspicuous findings in conventional MRI microstructural brain abnormalities are evident in these pediatric patients suffering from developmental delay.

  5. Diffusion Tensor Imaging Detects Early Cerebral Cortex Abnormalities in Neuronal Architecture Induced by Bilateral Neonatal Enucleation: An Experimental Model in the Ferret

    PubMed Central

    Bock, Andrew S.; Olavarria, Jaime F.; Leigland, Lindsey A.; Taber, Erin N.; Jespersen, Sune N.; Kroenke, Christopher D.

    2010-01-01

    Diffusion tensor imaging (DTI) is a technique that non-invasively provides quantitative measures of water translational diffusion, including fractional anisotropy (FA), that are sensitive to the shape and orientation of cellular elements, such as axons, dendrites and cell somas. For several neurodevelopmental disorders, histopathological investigations have identified abnormalities in the architecture of pyramidal neurons at early stages of cerebral cortex development. To assess the potential capability of DTI to detect neuromorphological abnormalities within the developing cerebral cortex, we compare changes in cortical FA with changes in neuronal architecture and connectivity induced by bilateral enucleation at postnatal day 7 (BEP7) in ferrets. We show here that the visual callosal pattern in BEP7 ferrets is more irregular and occupies a significantly greater cortical area compared to controls at adulthood. To determine whether development of the cerebral cortex is altered in BEP7 ferrets in a manner detectable by DTI, cortical FA was compared in control and BEP7 animals on postnatal day 31. Visual cortex, but not rostrally adjacent non-visual cortex, exhibits higher FA than control animals, consistent with BEP7 animals possessing axonal and dendritic arbors of reduced complexity than age-matched controls. Subsequent to DTI, Golgi-staining and analysis methods were used to identify regions, restricted to visual areas, in which the orientation distribution of neuronal processes is significantly more concentrated than in control ferrets. Together, these findings suggest that DTI can be of utility for detecting abnormalities associated with neurodevelopmental disorders at early stages of cerebral cortical development, and that the neonatally enucleated ferret is a useful animal model system for systematically assessing the potential of this new diagnostic strategy. PMID:21048904

  6. Slip-Related Changes in Plantar Pressure Distribution, and Parameters for Early Detection of Slip Events

    PubMed Central

    Choi, Seungyoung; Cho, Hyungpil; Kang, Boram; Lee, Dong Hun; Kim, Mi Jung

    2015-01-01

    Objective To investigate differences in plantar pressure distribution between a normal gait and unpredictable slip events to predict the initiation of the slipping process. Methods Eleven male participants were enrolled. Subjects walked onto a wooden tile, and two layers of oily vinyl sheet were placed on the expected spot of the 4th step to induce a slip. An insole pressure-measuring system was used to monitor plantar pressure distribution. This system measured plantar pressure in four regions (the toes, metatarsal head, arch, and heel) for three events: the step during normal gait; the recovered step, when the subject recovered from a slip; and the uncorrected, harmful slipped step. Four variables were analyzed: peak pressure (PP), contact time (CT), the pressure-time integral (PTI), and the instant of peak pressure (IPP). Results The plantar pressure pattern in the heel was unique, as compared with other parts of the sole. In the heel, PP, CT, and PTI values were high in slipped and recovered steps compared with normal steps. The IPP differed markedly among the three steps. The IPPs in the heel for the three events were, in descending order (from latest to earliest), slipped, recovered, and normal steps, whereas in the other regions the order was normal, recovered, and slipped steps. Finally, the metatarsal head-to-heel IPP ratios for the normal, recovered, and slipped steps were 6.1±2.9, 3.1±3.0, and 2.2±2.5, respectively. Conclusion A distinctive plantar pressure pattern in the heel might be useful for early detection of a slip event to prevent slip-related injuries. PMID:26798603

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

    DOE PAGES

    Hruschka, Daniel  J.; Branford, Simon; Smith, Eric  D.; ...

    2014-12-18

    Background: 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. Results: 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 soundmore » 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. Conclusions: 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.« less

  8. Unreported seismic events found far off-shore Mexico using full-waveform, cross-correlation detection method.

    NASA Astrophysics Data System (ADS)

    Solano, ErickaAlinne; Hjorleifsdottir, Vala; Perez-Campos, Xyoli

    2015-04-01

    A large subset of seismic events do not have impulsive arrivals, such as low frequency events in volcanoes, earthquakes in the shallow part of the subduction interface and further down dip from the traditional seismogenic part, glacial events, volcanic and non-volcanic tremors and landslides. A suite of methods can be used to detect these non-impulsive events. One of this methods is the full-waveform detection based on time reversal methods (Solano, et al , submitted to GJI). The method uses continuous observed seismograms, together with Greens functions and moment tensor responses calculated for an arbitrary 3D structure. This method was applied to the 2012 Ometepec-Pinotepa Nacional earthquake sequence in Guerrero, Mexico. During the span time of the study, we encountered three previously unknown events. One of this events was an impulsive earthquake in the Ometepec area, that only has clear arrivals on three stations and was therefore not located and reported by the SSN. The other two events are previously undetected events, very depleted in high frequencies, that occurred far outside the search area. A very rough estimate gives the location of this two events in the portion of the East Pacific Rise around 9 N. These two events are detected despite their distance from the search area, due to favorable move-out on the array of the Mexican National Seismological Service network (SSN). We are expanding the study area to the EPR and to a larger period of time, with the objective of finding more events in that region. We will present an analysis of the newly detected events, as well as any further findings at the meeting.

  9. Use of a Novel High-Resolution Magnetic Resonance Neurography Protocol to Detect Abnormal Dorsal Root Ganglia in Sjögren Patients With Neuropathic Pain

    PubMed Central

    Birnbaum, Julius; Duncan, Trisha; Owoyemi, Kristie; Wang, Kenneth C.; Carrino, John; Chhabra, Avneesh

    2014-01-01

    whose neuropathic pain resolved with intravenous immunoglobulin (IVIg) therapy had improvement of MRN DRG abnormalities. We have developed a novel MRN protocol that can detect DRG abnormalities in SS patients with neuropathic pain who do not have markers of peripheral neuropathy. We found that SS patients with MRN DRG abnormalities had statistically significant, increased IENFD on skin biopsy studies, which may suggest a relationship between trophic mediators and neuropathic pain. Given that our literature review has demonstrated that many SS neuropathic pain patients do not have a neuropathy, our findings suggest an important niche for this MRN DRG technique in the evaluation of broader subsets of SS neuropathic pain patients who may not have underlying neuropathies. The improvement of MRN DRG abnormalities in patients with IVIg-induced remission of neuropathic pain suggests that our MRN protocol may be capturing reversible, immune-mediated mechanisms targeting the DRG. PMID:24797167

  10. Validity assessment of the detection method of maize event Bt10 through investigation of its molecular structure.

    PubMed

    Milcamps, Anne; Rabe, Scott; Cade, Rebecca; De Framond, Anic J; Henriksson, Peter; Kramer, Vance; Lisboa, Duarte; Pastor-Benito, Susana; Willits, Michael G; Lawrence, David; Van den Eede, Guy

    2009-04-22

    In March 2005, U.S. authorities informed the European Commission of the inadvertent release of unauthorized maize GM event Bt10 in their market and subsequently the grain channel. In the United States measures were taken to eliminate Bt10 from seed and grain supplies; in the European Union an embargo for maize gluten and brewer's grain import was implemented unless certified of Bt10 absence with a Bt10-specific PCR detection method. With the aim of assessing the validity of the Bt10 detection method, an in-depth analysis of the molecular organization of the genetic modification of this event was carried out by both the company Syngenta, who produced the event, and the European Commission Joint Research Centre, who validated the detection method. Using a variety of molecular analytical tools, both organizations found the genetic modification of event Bt10 to be very complex in structure, with rearrangements, inversions, and multiple copies of the structural elements (cry1Ab, pat, and the amp gene), interspersed with small genomic maize fragments. Southern blot analyses demonstrated that all Bt10 elements were found tightly linked on one large fragment, including the region that would generate the event-specific PCR amplicon of the Bt10 detection method. This study proposes a hypothetical map of the insert of event Bt10 and concludes that the validated detection method for event Bt10 is fit for its purpose.

  11. Leukocyte abnormalities.

    PubMed

    Gabig, T G

    1980-07-01

    Certain qualitative abnormalities in neutrophils and blood monocytes are associated with frequent, severe, and recurrent bacterial infections leading to fatal sepsis, while other qualitative defects demonstrated in vitro may have few or no clinical sequelae. These qualitative defects are discussed in terms of the specific functions of locomotion, phagocytosis, degranulation, and bacterial killing.

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

    PubMed Central

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

    2016-01-01

    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. PMID:27706086

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

    PubMed Central

    Silva, Rodrigo Tavares; Martinelli Filho, Martino; Peixoto, Giselle de Lima; de Lima, José Jayme Galvão; de Siqueira, Sérgio Freitas; Costa, Roberto; Gowdak, Luís Henrique Wolff; de Paula, Flávio Jota; Kalil Filho, Roberto; Ramires, José Antônio Franchini

    2015-01-01

    Background 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. PMID:26351983

  14. Abnormal myocardial fatty acid metabolism in dilated cardiomyopathy detected by iodine-123 phenylpentadecanoic acid and tomographic imaging

    SciTech Connect

    Ugolini, V.; Hansen, C.L.; Kulkarni, P.V.; Jansen, D.E.; Akers, M.S.; Corbett, J.R.

    1988-11-01

    The radioidinated synthetic fatty acid iodine-123 phenylpentadecanoic acid (IPPA) has proven useful in the identification of regional abnormalities of cardiac metabolism in patients with myocardial ischemia. The present study was performed to test the hypothesis that the myocardial distribution and turnover of fatty acids, assessed noninvasively with IPPA, are altered in patients with cardiomyopathy. Nine normal volunteers and 19 patients with dilated cardiomyopathy of various etiologies underwent cardiac imaging with single-photon emission computed tomography (SPECT) after intravenous injection of IPPA. Apical short-axis and basal short-axis sections were reconstructed and quantitatively analyzed for relative IPPA activity distribution and washout. Patients with congestive cardiomyopathy demonstrated significantly greater heterogeneity of IPPA uptake than normal subjects (maximal percent variation of activity 27 +/- 11 vs 18 +/- 4, p less than 0.01). They also demonstrated a more rapid percent washout rate than control subjects (24 +/- 8 vs 17 +/- 6 for the apical short-axis section, p less than 0.05; 26 +/- 7 vs 18 +/- 5 for the basal short-axis section, p less than 0.01). These abnormalities of fatty acid distribution and turnover were independent of the etiology of the cardiomyopathy. The degree of heterogeneity of IPPA uptake was significantly related to the patients' New York Heart Association functional class (r = 0.64, p less than 0.01). Thus, compared with normal myocardium, the myocardium of patients with congestive cardiomyopathy demonstrates a more heterogeneous distribution of fatty acid uptake, which parallels the clinical severity of the disease. Furthermore, patients with congestive cardiomyopathy demonstrate a more rapid myocardial clearance of the labeled fatty acid, as assessed with SPECT imaging.

  15. The WISE Detection of an Infrared Echo in Tidal Disruption Event ASASSN-14li

    NASA Astrophysics Data System (ADS)

    Jiang, Ning; Dou, Liming; Wang, Tinggui; Yang, Chenwei; Lyu, Jianwei; Zhou, Hongyan

    2016-09-01

    We report the detection of a significant infrared variability of the nearest tidal disruption event (TDE) ASASSN-14li using Wide-field Infrared Survey Explorer and newly released Near-Earth Object WISE Reactivation data. In comparison with the quiescent state, the infrared flux is brightened by 0.12 and 0.16 mag in the W1 (3.4 μm) and W2 (4.6 μm) bands at 36 days after the optical discovery (or ˜110 days after the peak disruption date). The flux excess is still detectable ˜170 days later. Assuming that the flare-like infrared emission is from the dust around the black hole, its blackbody temperature is estimated to be ˜2.1 × 103 K, slightly higher than the dust sublimation temperature, indicating that the dust is likely located close to the dust sublimation radius. The equilibrium between the heating and radiation of the dust claims a bolometric luminosity of ˜1043-1045 erg s-1, comparable with the observed peak luminosity. This result has for the first time confirmed the detection of infrared emission from the dust echoes of TDEs.

  16. Solar Power Ramp Events Detection Using an Optimized Swinging Door Algorithm

    SciTech Connect

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

    2015-08-05

    Solar power ramp events (SPREs) 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 enhance the state of the art in SPRE 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.

  17. Automatic Detection of Swallowing Events by Acoustical Means for Applications of Monitoring of Ingestive Behavior

    PubMed Central

    Sazonov, Edward S.; Makeyev, Oleksandr; Schuckers, Stephanie; Lopez-Meyer, Paulo; Melanson, Edward L.; Neuman, Michael R.

    2010-01-01

    Our understanding of etiology of obesity and overweight is incomplete due to lack of objective and accurate methods for Monitoring of Ingestive Behavior (MIB) in the free living population. Our research has shown that frequency of swallowing may serve as a predictor for detecting food intake, differentiating liquids and solids, and estimating ingested mass. This paper proposes and compares two methods of acoustical swallowing detection from sounds contaminated by motion artifacts, speech and external noise. Methods based on mel-scale Fourier spectrum, wavelet packets, and support vector machines are studied considering the effects of epoch size, level of decomposition and lagging on classification accuracy. The methodology was tested on a large dataset (64.5 hours with a total of 9,966 swallows) collected from 20 human subjects with various degrees of adiposity. Average weighted epoch recognition accuracy for intra-visit individual models was 96.8% which resulted in 84.7% average weighted accuracy in detection of swallowing events. These results suggest high efficiency of the proposed methodology in separation of swallowing sounds from artifacts that originate from respiration, intrinsic speech, head movements, food ingestion, and ambient noise. The recognition accuracy was not related to body mass index, suggesting that the methodology is suitable for obese individuals. PMID:19789095

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

    SciTech Connect

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  20. DADA: Data Assimilation for the Detection and Attribution of Weather and Climate-related Events

    NASA Astrophysics Data System (ADS)

    Hannart, Alexis; Bocquet, Marc; Carrassi, Alberto; Ghil, Michael; Naveau, Philippe; Pulido, Manuel; Ruiz, Juan; Tandeo, Pierre

    2015-04-01

    We describe a new approach allowing for near real time, systematic causal attribution of weather and climate-related events. The method is purposely designed to allow its operability at meteorological centers by synergizing causal attribution with data treatments that are routinely performed when numerically forecasting the weather, thereby taking advantage of their powerful computational and observational capacity. Namely, we show that causal attribution can be obtained as a by-product of the so-called data assimilation procedures that are run on a daily basis to update the meteorological model with new atmospheric observations. We explain the theoretical rationale of this approach and sketch the most prominent features of a "data assimilation-based detection and attribution" (DADA) procedure. The proposal is illustrated in the context of the 3-variables Lorenz model. Several practical and theoretical research questions that need to be addressed to make the proposal readily operational within weather forecasting centers are finally laid out.

  1. Event detection and localization for small mobile robots using reservoir computing.

    PubMed

    Antonelo, E A; Schrauwen, B; Stroobandt, D

    2008-08-01

    Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

  2. Information Systems Developments to Detect and Analyze Chemotherapy-associated Adverse Drug Events

    PubMed Central

    Weiner, Mark G.; Livshits, Alice; Carozzoni, Carol; McMenamin, Erin; Gibson, Gene; Loren, Alison W.; Hennessy, Sean

    2002-01-01

    A difficult balance exists in the use of cancer chemotherapy in which the cytotoxic medicine must act on the cancer without causing neutropenic fever, a condition that is caused by over-suppression of the immune system. An improved understanding of dosing strategies as well as the use of medications to support the immune system has helped to reduce the likelihood of an admission for neutropenic fever following cancer chemotherapy. Therefore, as with any drug therapy, chemotherapy administration that is temporally associated with an unexpected hospitalization for neutropenia is an adverse drug event (ADE). Analogous to other informatics research to monitor and address the occurrence of ADEs, this work develops and validates the information systems infrastructure necessary to detect the occurrence of and analyze the factors contributing to chemotherapy associated ADEs.

  3. Decision support methods for the detection of adverse events in post-marketing data.

    PubMed

    Hauben, M; Bate, A

    2009-04-01

    Spontaneous reporting is a crucial component of post-marketing drug safety surveillance despite its significant limitations. The size and complexity of some spontaneous reporting system databases represent a challenge for drug safety professionals who traditionally have relied heavily on the scientific and clinical acumen of the prepared mind. Computer algorithms that calculate statistical measures of reporting frequency for huge numbers of drug-event combinations are increasingly used to support pharamcovigilance analysts screening large spontaneous reporting system databases. After an overview of pharmacovigilance and spontaneous reporting systems, we discuss the theory and application of contemporary computer algorithms in regular use, those under development, and the practical considerations involved in the implementation of computer algorithms within a comprehensive and holistic drug safety signal detection program.

  4. Prenatal diagnosis of mosaic ring 22 duplication/deletion with terminal 22q13 deletion due to abnormal first trimester screening and choroid plexus cyst detected on ultrasound.

    PubMed

    Koç, Altuğ; Arisoy, Ozgür; Pala, Elif; Erdem, Mehmet; Kaymak, Ayşegül Oztürk; Erkal, Ozgür; Karaoğuz, Meral Yirmibeş

    2009-10-01

    We report a rare case of mosaic ring chromosome 22 duplication/deletion in a fetus for whom karyotype analysis was required because of an abnormal finding in the maternal serum screening test and a choroid plexus cyst detected on prenatal ultrasound. Additional prenatal study of the amniotic fluid by fluorescence in situ hybridization was performed and the terminal 22q13.3 deletion was detected on ring chromosome. The final karyotype was 45,XX,-22[3]/46,XX,r(22)(p11q13.2)[63]/46,XX,idicr(22)(p11q13.2;p11q13.2)[2]dn.ishder(22)(N25+, ARSA-, ter-). The pegnancy was terminated. Cytogenetic analysis of the intracardiac blood also revealed ring 22 mosaicism with only one metaphase spread with idicr(22) as the unstable isodicentric rings are subsequently lost from most cells. We discuss the prenatal diagnosis of this rare condition.

  5. Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

    NASA Astrophysics Data System (ADS)

    Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

    2016-12-01

    Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

  6. Detecting binarity of GW150914-like lenses in gravitational microlensing events

    NASA Astrophysics Data System (ADS)

    Kesden, Michael; Eilbott, Daniel; Riley, Alexander; Cohn, Jonathan; King, Lindsay

    2017-01-01

    The recent discovery of gravitational waves from stellar-mass binary black holes (BBHs) provided direct evidence of the existence of these systems. These BBHs would have gravitational microlensing signatures that are, due to their large masses and small separations, distinct from single-lens signals. We apply Bayesian statistics to examine the distinguishability of BBH microlensing events from single-lens events under ideal observing conditions, using modern photometric and astrometric capabilities. Given one year of ideal observations, a source star at the Galactic center, a GW150914-like BBH lens (total mass 65 solar masses, mass ratio 0.8) at half that distance, and an impact parameter of 0.4 Einstein radii, we find that BBHs with separations down to 0.00634 Einstein radii are detectable, marginally below the separation at which such systems would merge due to gravitational radiation with the age of the Universe. Supported by Alfred P Sloan Foundation Grant No. RG- 2015-65299 and NSF Grant No. PHY-1607031.

  7. Using the AHRQ PSIs to Detect Post-Discharge Adverse Events in the Veterans Health Administration

    PubMed Central

    Mull, Hillary J.; Borzecki, Ann M.; Chen, Qi; Shin, Marlena H.; Rosen, Amy K.

    2015-01-01

    Background PSIs use inpatient administrative data to flag cases with potentially preventable adverse events (AEs) attributable to hospital care. We explored how many AEs the PSIs identified in the 30 days post-discharge. Methods We ran the PSI software (version 3.1a) on VA 2003–2007 administrative data for ten recently validated PSIs. Among PSI-eligible index hospitalizations not flagged with an AE, we evaluated how many AEs occurred within 1–14 and 15–30 days post-discharge using inpatient and outpatient administrative data. Results Considering all PSI-eligible index hospitalizations, we identified 11,141 post-discharge AEs, compared to 40,578 inpatient-flagged AEs. More than 60% of post-discharge AEs were detected within 14 days of discharge. The majority of post-discharge AEs were decubitus ulcers and postoperative pulmonary embolisms or deep vein thromboses. Conclusions Extending PSI algorithms to the post-discharge period may provide a more complete picture of hospital quality. Future work should use chart review to validate post-discharge PSI events. PMID:23939485

  8. Energy efficient data representation and aggregation with event region detection in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Banerjee, Torsha

    Detection (PERD) for WSNs. When a single event occurs, a child of the tree sends a Flagged Polynomial (FP) to its parent, if the readings approximated by it falls outside the data range defining the existing phenomenon. After the aggregation process is over, the root having the two polynomials, P and FP can be queried for FP (approximating the new event region) instead of flooding the whole network. For multiple such events, instead of computing a polynomial corresponding to each new event, areas with same data range are combined by the corresponding tree nodes and the aggregated coefficients are passed on. Results reveal that a new event can be detected by PERD while error in detection remains constant and is less than a threshold of 10%. As the node density increases, accuracy and delay for event detection are found to remain almost constant, making PERD highly scalable. Whenever an event occurs in a WSN, data is generated by closeby sensors and relaying the data to the base station (BS) make sensors closer to the BS run out of energy at a much faster rate than sensors in other parts of the network. This gives rise to an unequal distribution of residual energy in the network and makes those sensors with lower remaining energy level die at much faster rate than others. We propose a scheme for enhancing network Lifetime using mobile cluster heads (CH) in a WSN. To maintain remaining energy more evenly, some energy-rich nodes are designated as CHs which move in a controlled manner towards sensors rich in energy and data. This eliminates multihop transmission required by the static sensors and thus increases the overall lifetime of the WSN. We combine the idea of clustering and mobile CH to first form clusters of static sensor nodes. A collaborative strategy among the CHs further increases the lifetime of the network. Time taken for transmitting data to the BS is reduced further by making the CHs follow a connectivity strategy that always maintain a connected path to the BS

  9. Applying a New Event Detection Algorithm to an Ocean Bottom Seismometer Dataset Recorded Offshore Southern California

    NASA Astrophysics Data System (ADS)

    Bishop, J.; Kohler, M. D.; Bunn, J.; Chandy, K. M.

    2015-12-01

    A number of active southern California offshore faults are capable of M>6 earthquakes, and the only permanent Southern California Seismic Network stations that can contribute to ongoing, small-magnitude earthquake detection and location are those located on the coastline and islands. To obtain a more detailed picture of the seismicity of the region, an array of 34 ocean bottom seismometers (OBSs) was deployed to record continuous waveform data off the coast of Southern California for 12 months (2010-2011) as part of the ALBACORE (Asthenospheric and Lithospheric Broadband Architecture from the California Offshore Region Experiment) project. To obtain a local event catalog based on OBS data, we make use of a newly developed data processing platform based on Python. The data processing procedure comprises a multi-step analysis that starts with the identification of significant signals above the time-adjusted noise floor for each sensor. This is followed by a time-dependent statistical estimate of the likelihood of an earthquake based on the aggregated signals in the array. For periods with elevated event likelihood, an adaptive grid-fitting procedure is used that yields candidate earthquake hypocenters with confidence estimates that best match the observed sensor signals. The results are validated with synthetic travel times and manual picks. Using results from ALBACORE, we have created a more complete view of active faulting in the California Borderland.

  10. Recurrent chromosome 6 abnormalities in malignant mesothelioma.

    PubMed

    Ribotta, M; Roseo, F; Salvio, M; Castagneto, B; Carbone, M; Procopio, A; Giordano, A; Mutti, L

    1998-04-01

    The long latency period between asbestos exposure and the onset of malignant mesothelioma (MM) suggests that a multistep tumorigenesis process occurs whilst the capability of asbestos fibres to interfere directly with chromosomes focuses on the critical role of the chromosomal abnormalities in this neoplasm. The aim of our study was to identify any recurrent chromosomal changes in ten primary MM cell cultures derived from pleural effusions of patients with MM from the same geographic area and environmental and/or occupational exposure to asbestos fibers. Cytogenetic analysis was performed in accordance with International System for Human Cytogenetic Nomenclature. Our results confirmed a great number of cytogenetic abnormalities in MM cells. Recurrent loss of the long arms of chromosome 6 (6q-) was the most frequent abnormality detected (four epithelial and two mixed subtypes) while, on the whole, abnormalities of chromosome 6 were found in nine out of ten cases whereas chromosome 6 was normal only in the case with fibromatous subtype. Monosomy 13 and 17 was found in five cases, monosomy 14 in four cases and 22 in three cases. Since deletion of 6q- was detected even in relatively undisturbed karyotype, we hypothesize a multistep carcinogenic process in which deletion of 6q- is an early event in the development and progression of malignant mesothelioma.

  11. Detection of Chromosomal Abnormalities with Different In Situ Hybridisation Techniques--the Usefulness in the Qualification of Cancer Patients for Molecularly-Targeted Therapies.

    PubMed

    Nicoś, Marcin; Wojas-Krawczyk, Kamila; Krawczyk, Paweł; Milanowski, Janusz

    2015-01-01

    Proper qualification of patients with cancer for an effective treatment regiment is essential to rationalize therapy benefit and costs. The early detection of genetic disorders that are responsible for the stimulation of uncontrolled cancer cells proliferation makes it possible to select a group of patients with a high probability of response to molecularly-targeted therapy. Data has shown that careful analysis of genes mutation using different PCR and sequencing techniques or chromosomal aberrations using in situ hybridization (ISH) techniques have a predictive value for drug targeted therapy. Overexpression of receptors and gene amplification has been reported in various cancers. Their detection is still a considerable challenge, which is connected with the unsatisfactory quality of DNA and low mutated cells percentage compared to cells with no genetic abnormalities in tested material. Different techniques of standardization were performed to prevent false negative results and to increase the sensitivity of qualitative and quantitative evaluation of chromosomal abnormalities. Immunohistochemistry (IHC) technique is useful in the screening of receptor expression in paraffin-embedded tissue samples in different malignant diseases. Whereas ISH techniques, especially fluorescence in situ hybridization (FISH), are now considered the diagnostic gold standard method in detection chromosomal aberrations. Moreover, molecular biology techniques, which are using molecular probes and real-time PCR and quantitative PCR techniques, were also applied for the detection of chromosomal changes. In order to identify the best genetic marker for treatment regiment, it is important to compare results of different studies, which are evaluating the sensitivity of diagnostic techniques and treatment response after a suitable selection factors based on genetic aberrations profile.

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

    PubMed Central

    Mukhi, Shamir N

    2016-01-01

    Objectives: 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. Methods: 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. Results: 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%). Discussion: Literature suggests the need for internet based monitoring and surveillance systems that are customizable

  13. Using GPS to Rapidly Detect and Model Earthquakes and Transient Deformation Events

    NASA Astrophysics Data System (ADS)

    Crowell, Brendan W.

    The rapid modeling and detection of earthquakes and transient deformation is a problem of extreme societal importance for earthquake early warning and rapid hazard response. To date, GPS data is not used in earthquake early warning or rapid source modeling even in Japan or California where the most extensive geophysical networks exist. This dissertation focuses on creating algorithms for automated modeling of earthquakes and transient slip events using GPS data in the western United States and Japan. First, I focus on the creation and use of high-rate GPS and combined seismogeodetic data for applications in earthquake early warning and rapid slip inversions. Leveraging data from earthquakes in Japan and southern California, I demonstrate that an accurate magnitude estimate can be made within seconds using P wave displacement scaling, and that a heterogeneous static slip model can be generated within 2-3 minutes. The preliminary source characterization is sufficiently robust to independently confirm the extent of fault slip used for rapid assessment of strong ground motions and improved tsunami warning in subduction zone environments. Secondly, I investigate the automated detection of transient slow slip events in Cascadia using daily positional estimates from GPS. Proper geodetic characterization of transient deformation is necessary for studies of regional interseismic, coseismic and postseismic tectonics, and miscalculations can affect our understanding of the regional stress field. I utilize the relative strength index (RSI) from financial forecasting to create a complete record of slow slip from continuous GPS stations in the Cascadia subduction zone between 1996 and 2012. I create a complete history of slow slip across the Cascadia subduction zone, fully characterizing the timing, progression, and magnitude of events. Finally, using a combination of continuous and campaign GPS measurements, I characterize the amount of extension, shear and subsidence in the

  14. PREFACE: Fourth Symposium on Large TPCs for Low Energy Rare Event Detection

    NASA Astrophysics Data System (ADS)

    Irastorza, Igor G.; Colas, Paul; Giomataris, Ioannis

    2009-07-01

    The Fourth International Symposium on large TPCs for low-energy rare-event detection was held at the Hermite auditorium of the Insitute Henri Poincaréte, 11 rue Pierre et Marie Curie in Paris on 18-19 December 2008. As in previous instances of the meeting, held always in Paris in 2006, 2004 and 2002, it gathered a significant community of physicists involved in rare event searches and/or development of time projection chambers (TPCs). The purpose of the meeting was to present and discuss the status of current experiments or projects involving the use of large TPCs for the search of rare events, like low-energy neutrinos, double beta decay, dark matter or axion experiments, as well as to discuss new results and ideas in the framework of the last developments of Micro Pattern Gaseous Detectors (MPGD), and how these are being - or could be - applied to the mentioned searches. The rapid evolvement of these devices and the relevance of their latest results need to be efficiently transferred to the rare event community. The creation of this series of meetings followed the motivation of bringing together both know-hows and it is proving to be a fruitful area of collaboration. Once more, the format of the meeting proved to be a success. A short (2 days) and relatively informal program with some recent highlighted results, rather than exhaustive reviews, attracted the interest of the audience. The symposium, fourth of the series, is becoming consolidated as a regular meeting place for the synergic interplay between the fields of rare events and TPC development. Apart from the usual topics central to the conference subject, like the status of some low-energy neutrino physics and double beta decay experiments, dark matter experiments (and in general physics in underground laboratories), axion searches, or development results, every year the conference programme is enriched with original slightly off-topic contributions that trigger the curiosity and stimulate further thought

  15. Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

    NASA Technical Reports Server (NTRS)

    Gupta, U. K.; Ali, M.

    1988-01-01

    The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

  16. The ADENOMA Study. Accuracy of Detection using Endocuff Vision™ Optimization of Mucosal Abnormalities: study protocol for randomized controlled trial

    PubMed Central

    Bevan, Roisin; Ngu, Wee Sing; Saunders, Brian P.; Tsiamoulos, Zacharias; Bassett, Paul; Hoare, Zoe; Rees, Colin J.

    2016-01-01

    Background: Colonoscopy is the gold standard investigation for the diagnosis of bowel pathology and colorectal cancer screening. Adenoma detection rate is a marker of high quality colonoscopy and a high adenoma detection rate is associated with a lower incidence of interval cancers. Several technological advancements have been explored to improve adenoma detection rate. A new device called Endocuff Vision™ has been shown to improve adenoma detection rate in pilot studies. Methods/Design: This is a prospective, multicenter, randomized controlled trial comparing the adenoma detection rate in patients undergoing Endocuff Vision™-assisted colonoscopy with standard colonoscopy. All patients above 18 years of age referred for screening, surveillance, or diagnostic colonoscopy who are able to consent are invited to the study. Patients with absolute contraindications to colonoscopy, large bowel obstruction or pseudo-obstruction, colon cancer or polyposis syndromes, colonic strictures, severe diverticular segments, active colitis, anticoagulant therapy, or pregnancy are excluded. Patients are randomized according to site, age, sex, and bowel cancer screening status to receive Endocuff Vision™-assisted colonoscopy or standard colonoscopy on the day of procedure. Baseline data, colonoscopy, and polyp data including histology are collected. Nurse assessment of patient comfort and patient comfort questionnaires are completed post procedure. Patients are followed up at 21 days and complete a patient experience questionnaire. This study will take place across seven NHS Hospital Trusts: one in London and six within the Northern Region Endoscopy Group. A maximum of 10 colonoscopists per site will recruit a total of 1772 patients, with a maximum of four bowel screening colonoscopists permitted per site. Discussion: This is the first trial to evaluate the adenoma detection rate of Endocuff Vision™ in all screening, surveillance, and diagnostic patient groups. This timely

  17. Implementation and performance results of neural network for power quality event detection

    NASA Astrophysics Data System (ADS)

    Huang, Weijian; Tian, Wenzhi

    2008-10-01

    A novel method to detect power quality event in distributed power system combing wavelet network with the improved back-propagation algorithm is presented. The paper tries to explain to design complex supported orthogonal wavelets by compactly supported orthogonal real wavelets, and then explore the extraction of disturbance signal to obtain the feature information, and finally propose several novel wavelet combined information to analyze the disturbance signal, superior to real wavelet analysis result. The feature obtained from WT coefficients are inputted into wavelet network for power quality disturbance pattern recognition. The power quality disturbance recognition model is established and the improved back-propagation algorithm is used to fulfill the network parameter initialization. By means of choosing enough samples to train the recognition model, the type of disturbance can be obtained when signal representing fault is inputted to the trained network. The results of simulation analysis show that the complex wavelet transform combined with wavelet network are more sensitive to signal singularity, and found to be significant improvement over current methods in real-time detection.

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

    SciTech Connect

    Carmichael, Joshua Daniel; Carr, Christina; Pettit, Erin C.

    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.

  19. Noise Reduction for Detecting Event-Related Potential by Processing in Dipole Space

    NASA Astrophysics Data System (ADS)

    Fukami, Tadanori; Shimada, Takamasa; Ishikawa, Fumito; Ishikawa, Bunnoshin; Saito, Yoichi

    2007-06-01

    Averaged responses are generally used to detect event-related potentials (ERPs) by supressing the background electroencephalography (EEG) wave, the ERP component of a single-trial response, or the average of a small number of responses is used to assess time variation in a subjects’ state in detail. We therefore proposed a new method of reducing the noise component including the background wave in a single-trial response. In this study, our target is a component such as N100 approximated by one dipole. The method was performed by modifying the dipole position in the brain and detecting the projected components with reference to the dipole estimated from an averaged response. Results of simulation indicate that the proposed method could improve signal-to-noise ratio by 7.6 dB and decrease the error in N100 peak latency 6.7 ms by suppressing the influence of the background wave. In the EEG experiment, eight healthy subjects paticipated and their results show that the sway of waveforms by the background wave is suppressed and that the peak of the N100 component becomes prominent compared with that of the original single-trial response.

  20. Chromosome Abnormalities

    MedlinePlus

    ... Database Newsroom Calendar of Events Current News Releases Image Gallery GenomeTV Media Contacts Media Resources NHGRI-Related News Journal Articles from NHGRI Social Media Careers Educational Programs Health Professional Education Intramural ...

  1. Validity of acoustic quantification colour kinesis for detection of left ventricular regional wall motion abnormalities: a transoesophageal echocardiographic study.

    PubMed

    Hartmann, T; Kolev, N; Blaicher, A; Spiss, C; Zimpfer, M

    1997-10-01

    Transoesophageal echocardiography is a sensitive monitor for intraoperative myocardial ischaemia. Colour kinesis is a new technology for echocardiographic assessment of regional wall motion based on acoustic quantification. We have examined the feasibility and accuracy of quantitative segmental analysis of colour kinesis images to provide objective evaluation of systolic regional wall motion during the perioperative period using transoesophageal echocardiography (TOE). Two-dimensional echocardiograms were obtained in the transgastric short-axis and long-axis views in 60 patients with coronary artery disease undergoing noncardiac surgery. End-systolic colour overlays superimposed on the grey scale images were obtained with colour kinesis to colour encode left ventricular endocardial motion throughout systole. These colour-encoded images were divided into segments and compared with corresponding conventional two-dimensional images. Six hundred of a potential 720 left ventricular wall segments were of sufficient resolution for grading by experts; they diagnosed wall motion abnormalities in 61 of these segments by a conventional method. In comparing the conventional TOE method with colour kinesis, there were 60 true positives, 482 true negatives, 57 false positives and 1 false negative result. This yielded a sensitivity of 98%, specificity of 89%, positive predictive value of 51% and negative predictive value of 100%. Translational and rotational movement of the heart and papillary muscle interference were common problems accounting for false positive diagnoses. We conclude that colour kinesis provides a basis for objective and on-line evaluation of left ventricular regional wall motion which is a sensitive but non-specific method. It may be a useful aid for the less experienced because it can potentially direct the anaesthetist's attention towards specific segments.

  2. Giant magenetoresistive sensors. 2. Detection of biorecognition events at self-referencing and magnetically tagged arrays.

    PubMed

    Millen, Rachel L; Nordling, John; Bullen, Heather A; Porter, Marc D; Tondra, Mark; Granger, Michael C

    2008-11-01

    Microfabricated devices formed from alternating layers of magnetic and nonmagnetic materials at combined thicknesses of a few hundred nanometers exhibit a phenomenon known as the giant magnetoresistance effect. Devices based on this effect are known as giant magnetoresistive (GMR) sensors. The resistance of a GMR is dependent on the strength of an external magnetic field, which has resulted in the widespread usage of such platforms in high-speed, high-data density storage drives. The same attributes (i.e., sensitivity, small size, and speed) are also important embodiments of many types of bioanalytical sensors, pointing to an intriguing opportunity via an integration of GMR technology, magnetic labeling strategies, and biorecognition elements (e.g., antibodies). This paper describes the utilization of GMRs for the detection of streptavidin-coated magnetic particles that are selectively captured by biotinylated gold addresses on a 2 x 0.3 cm sample stick. A GMR sensor network reads the addresses on a sample stick in a manner that begins to emulate that of a "card-swipe" system. This study also takes advantage of on-sample magnetic addresses that function as references for internal calibration of the GMR response and as a facile means to account for small variations in the gap between the sample stick and sensor. The magnetic particle surface coverage at the limit of detection was determined to be approximately 2%, which corresponds to approximately 800 binding events over the 200 x 200 microm capture address. These findings, along with the potential use of streptavidin-coated magnetic particles as a universal label for antigen detection in, for example, heterogeneous assays, are discussed.

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

    PubMed Central

    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

  4. Sudden Event Recognition: A Survey

    PubMed Central

    Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

    2013-01-01

    Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

  5. The Development of Prostate Palpation Skills through Simulation Training May Impact Early Detection of Prostate Abnormalities and Early Management

    DTIC Science & Technology

    2011-05-01

    PhD, School of Engineering and two co-Is Reba Moyer Childress, MSN, FNP , School of Nursing and Marcus L. Martin, MD, School of Medicine. We have...the support and clinical guidanceofMarcusL.Martin,M.D. (SchoolofMedicine,Universityof Virginia) and Reba Moyer Childress, SN, FNP , APRN-BC (School of...Childress, MSN, FNP -BC; Marcus L. Martin, MD Introduction: Prostate carcinoma (and other prostate irregularities and abnormali- ties) is detected in part

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

    NASA Astrophysics Data System (ADS)

    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

  7. Using tensor-based morphometry to detect structural brain abnormalities in rats with adolescent intermittent alcohol exposure

    NASA Astrophysics Data System (ADS)

    Paniagua, Beatriz; Ehlers, Cindy; Crews, Fulton; Budin, Francois; Larson, Garrett; Styner, Martin; Oguz, Ipek

    2011-03-01

    Understanding the effects of adolescent binge drinking that persist into adulthood is a crucial public health issue. Adolescent intermittent ethanol exposure (AIE) is an animal model that can be used to investigate these effects in rodents. In this work, we investigate the application of a particular image analysis technique, tensor-based morphometry, for detecting anatomical differences between AIE and control rats using Diffusion Tensor Imaging (DTI). Deformation field analysis is a popular method for detecting volumetric changes analyzing Jacobian determinants calculated on deformation fields. Recent studies showed that computing deformation field metrics on the full deformation tensor, often referred to as tensor-based morphometry (TBM), increases the sensitivity to anatomical differences. In this paper we conduct a comprehensive TBM study for precisely locating differences between control and AIE rats. Using a DTI RARE sequence designed for minimal geometric distortion, 12-directional images were acquired postmortem for control and AIE rats (n=9). After preprocessing, average images for the two groups were constructed using an unbiased atlas building approach. We non-rigidly register the two atlases using Large Deformation Diffeomorphic Metric Mapping, and analyze the resulting deformation field using TBM. In particular, we evaluate the tensor determinant, geodesic anisotropy, and deformation direction vector (DDV) on the deformation field to detect structural differences. This yields data on the local amount of growth, shrinkage and the directionality of deformation between the groups. We show that TBM can thus be used to measure group morphological differences between rat populations, demonstrating the potential of the proposed framework.

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

    PubMed

    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

  9. Detection of air pollution events over Évora-Portugal during 2009

    NASA Astrophysics Data System (ADS)

    Filipa Domingues, Ana; Bortoli, Daniele; Silva, Ana Maria; Kulkarni, Pavan; Antón, Manuel

    2010-05-01

    All over the world pollutant industries, traffic and other natural and anthropogenic sources are responsible for air pollution affecting health and also the climate. At the moment the monitoring of air quality in urban and country regions become an urgent concern in the atmospheric studies due to the impact of global air pollution on climate and on the environment. One of the evidences of the global character of air pollution is that it not only affects industrialized countries but also reaches less developed countries with pollution gases and particles generated for elsewhere. The development and the employment of instruments and techniques for measure the variation of atmospheric trace gases and perform their monitoring are crucial for the improvement of the air quality and the control of pollutants emissions. One of the instruments able to perform the air quality monitoring is the Spectrometer for Atmospheric TRacers Measurements (SPATRAM) and it is installed at the CGÉs Observatory in Évora (38.5° N, 7.9° W, 300 m asl). This UV-VIS Spectrometer is used to carry out measurements of the zenith scattered radiation (290- 900 nm) to retrieve the vertical content of some atmospheric trace gases such as O3 and NO2 in stratosphere, using Differential Optical Absorption Spectroscopy (DOAS) methodology. Although SPATRAM, in its actual geometric and operational configuration - zenith sky looking and passive mode measurements, is not able to detect small variations of tracers in the troposphere it is possible to identify enhancements in the pollution loads due to air masses movements from polluted sites. In spite of the fact that Evora is a quite unpolluted city the deep analysis of the DOAS output, namely the quantity of gas (in this case NO2) present along the optical path of measurements (SCD - Slant Column Density) allows for the detection of unpredicted variations in the diurnal NO2 cycle. The SPATRAḾs data allows the identification of polluting events which

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

    USGS Publications Warehouse

    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.

  11. Detection of Rapid Events at Mantle Depth by Future Gravity Missions

    NASA Astrophysics Data System (ADS)

    Ivins, Erik; Watkins, Michael

    2015-04-01

    The robust detection of gravity changes associated with relatively shallow subduction zone earthquakes (0-50 km depth co-seismic rupture) has been one of the success stories of the GRACE (e.g., Han et al. 2013, JGR-B, doi:10.1002/jgrb.50116) and GOCE (e.g., Fuchs et al., 2013, JGR-B, doi: 10.1002/jgrb.50381) missions. This surprise is a testament to the sensitivity of the measurement system, for the satellites must map the gravity potential field changes while flying at orbital altitudes exceeding 400 km (in the case of GRACE). It is clear that these observations contribute to advancing our understanding of large subduction zone earthquakes, if for no other reason than they allow comprehensive observation over the ocean covered solid Earth. The observations aid studies of both the mass transport associated with coseismic and post-seismic. Measurement capability for missions proposed to be flown after GRACE-2 are anticipated to be an order of magnitude, or greater, in accuracy and resolution (e.g., Wiese et al., 2012, J. Geodesy, doi: 10.1007/s00190-011-0493-8; Elsaka et al. 2014, J. Geodesy, doi: 10.1007/s00190-013-0665-9). Deep subduction zone earthquakes have not been detected, nor have any other non-seismic solid Earth deformations - with the exception of the glacial isostatic adjustment vertical response to the last glacial age. We examine the possibility that earthquakes occurring at, or near, the major transition zone in the mantle should be detected in the region where mantle phases become unstable and undergoes transition to a stable perovskite phase below 660 km depth. The Mw 8.2 1994 Bolivian Earthquake and the May 24, 2013 Mw 8.3 earthquake beneath the Sea of Okhotsk, Russia, are prototypes of events that can be studied with future gravity missions. Observation of gravity changes associated with deep subduction zone earthquakes could provide new clues on the enigmatic questions currently in debate over faulting mechanism (e.g., Zhan et al., 2014, Science

  12. Computer aided detection of transient inflation events at Alaskan volcanoes using GPS measurements from 2005-2015

    NASA Astrophysics Data System (ADS)

    Li, Justin D.; Rude, Cody M.; Blair, David M.; Gowanlock, Michael G.; Herring, Thomas A.; Pankratius, Victor

    2016-11-01

    Analysis of transient deformation events in time series data observed via networks of continuous Global Positioning System (GPS) ground stations provide insight into the magmatic and tectonic processes that drive volcanic activity. Typical analyses of spatial positions originating from each station require careful tuning of algorithmic parameters and selection of time and spatial regions of interest to observe possible transient events. This iterative, manual process is tedious when attempting to make new discoveries and does not easily scale with the number of stations. Addressing this challenge, we introduce a novel approach based on a computer-aided discovery system that facilitates the discovery of such potential transient events. The advantages of this approach are demonstrated by actual detections of transient deformation events at volcanoes selected from the Alaska Volcano Observatory database using data recorded by GPS stations from the Plate Boundary Observatory network. Our technique successfully reproduces the analysis of a transient signal detected in the first half of 2008 at Akutan volcano and is also directly applicable to 3 additional volcanoes in Alaska, with the new detection of 2 previously unnoticed inflation events: in early 2011 at Westdahl and in early 2013 at Shishaldin. This study also discusses the benefits of our computer-aided discovery approach for volcanology in general. Advantages include the rapid analysis on multi-scale resolutions of transient deformation events at a large number of sites of interest and the capability to enhance reusability and reproducibility in volcano studies.

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

    PubMed

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

    2016-05-18

    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.

  14. Liqui-Prep® versus conventional Papanicolaou smear to detect cervical cells abnormality by split-sample technique: a randomized double-blind controlled trial.

    PubMed

    Jesdapatarakul, Somnuek; Tangjitgamol, Siriwan; Nguansangiam, Sudarat; Manusirivithaya, Sumonmal

    2011-01-01

    To assess the diagnostic performances of LiquiPrep® (LP) to detect cervical cellular abnormality in comparison to Papanicolaou (Pap) smear in 194 women with abnormal cervical cytology who were scheduled for colposcopy at the institution between January 2008 and November 2008. The women were randomized to undergo a repeated cervical cytologic evaluation by Pap smear followed by LP, or the two methods in alternating order. The pathologist was blinded to previous cytologic diagnosis and the pair of slides assigned for each woman. Cytologic results from each method were compared to subsequent histopathology. Mean screening time for each LP and Pap slides were 4.3 ± 1.2 minutes and 5.4 ± 1.1 minutes, respectively (P < 0.001). From 194 cases, ASC or AGC were diagnosed in 72 cases (37.1%) from LP and 68 cases (35.1%) from Pap smear. After excluding the ASC/AGC group, the overall cytologic diagnostic agreement between the two tests were 69 of 87 cases (73.6%) while the agreements with histologic diagnoses were 39/87 cases from LP (44.8%) and 41 (47.1%) from Pap smear (P = 0.824). The accuracy of LP was not significantly different from Pap test, 43.4% (95% confidence interval [CI]: 34.8-52.1%) compared to 44.4% (95% CI: 35.7-53.1%). LP did not have superior performance over Pap test to detect high-grade lesions (≥ cervical intraepithelial neoplasia II) using ASC/AGC as the threshold with the sensitivity of 70.5% (95% CI: 64.0-76.9%) versus 77.3% (95% CI: 71.4-83.2%), respectively.

  15. Abnormal segregation of alleles in CEPH pedigree DNAs arising from allele loss in lymphoblastoid DNA

    SciTech Connect

    Royle, N.J.; Armour, J.A.L.; Crosier, M.; Jeffreys, A.J. )

    1993-01-01

    Somatic events that result in the reduction to hemior homozygosity at all loci affected by the event have been identified in lymphoblastoid DNA from mothers of two CEPH families. Using suitably informative probes, the allele deficiencies were detected by the abnormal transmission of alleles from grandparents to grandchildren, with the apparent absence of the alleles from the parent. Undetected somatic deficiencies in family DNAs could result in misscoring of recombination events and consequently introduce errors into linkage analysis. 15 refs., 2 figs.

  16. An engineered nano-plasmonic biosensing surface for colorimetric and SERS detection of DNA-hybridization events

    NASA Astrophysics Data System (ADS)

    Heydari, Esmaeil; Thompson, David; Graham, Duncan; Cooper, Jonathan M.; Clark, Alasdair W.

    2015-03-01

    We report a versatile nanophotonic biosensing platform that enables both colorimetric detection and enhanced Raman spectroscopy detection of molecular binding events. Through the integration of electron-beam lithography, dip-pennanolithography and molecular self-assembly, we demonstrate plasmonic nanostructures which change geometry and plasmonic properties in response to molecularly-mediated nanoparticle binding events. These biologically-active nanostructured surfaces hold considerable potential for use as multiplexed sensor platforms for point-of-care diagnostics, and as scaffolds for a new generation of molecularly dynamic metamaterials.

  17. Block-adaptive filtering and its application to seismic-event detection

    SciTech Connect

    Clark, G.A.

    1981-04-01

    Block digital filtering involves the calculation of a block or finite set of filter output samples from a block of input samples. The motivation for block processing arises from computational advantages of the technique. Block filters take good advantage of parallel processing architectures, which are becoming more and more attractive with the advent of very large scale integrated (VLSI) circuits. This thesis extends the block technique to Wiener and adaptive filters, both of which are statistical filters. The key ingredient to this extension turns out to be the definition of a new performance index, block mean square error (BMSE), which combines the well known sum square error (SSE) and mean square error (MSE). A block adaptive filtering procedure is derived in which the filter coefficients are adjusted once per each output block in accordance with a generalized block least mean-square (BLMS) algorithm. Convergence properties of the BLMS algorithm are studied, including conditions for guaranteed convergence, convergence speed, and convergence accuracy. Simulation examples are given for clarity. Convergence properties of the BLMS and LMS algorithms are analyzed and compared. They are shown to be analogous, and under the proper circumstances, equivalent. The block adaptive filter was applied to the problem of detecting small seismic events in microseismic background noise. The predictor outperformed the world-wide standardized seismograph network (WWSSN) seismometers in improving signal-to-noise ratio (SNR).

  18. PREFACE: 7th International Symposium on Large TPCs for Low-Energy Rare Event Detection

    NASA Astrophysics Data System (ADS)

    Colas, P.; Giomataris, I.; Irastorza, I.; Patzak, Th

    2015-11-01

    The seventh "International Symposium on Large TPCs for Low-Energy Rare Event Detection", took place in Paris between the 15th and 17th of December 2014 at the Institute of Astroparticle Physics (APC) campus - Paris Diderot University. As usual the conference was organized during the week before Christmas, which seems to be convenient for most of the people and occurs every two years with almost 120 participants attending. Many people contributed to the success of the conference, but the organizers would particularly like to thank the management of APC for providing the nice Buffon auditorium and infrastructure. We also acknowledge the valuable support of DSM-Irfu and the University of Zaragoza. The scientific program consisted of plenary sessions including the following topics with theoretical and experimental lectures: • Low energy neutrino physics • Neutrinoless double beta decay process • Dark matter searches • Axion and especially solar axion searches • Space experiments and gamma-ray polarimetry • New detector R&D and future experiments

  19. PREFACE: Sixth Symposium on Large TPCs for Low Energy Rare Event Detection

    NASA Astrophysics Data System (ADS)

    Irastorza, Igor G.; Colas, Paul; Giomataris, Ioannis

    2013-10-01

    For the sixth time the International Symposium on large TPCs for Low-Energy Rare-Event Detection has been organized in Paris on 17-19 December 2012. As for the previous conference, we were welcomed in the Astroparticle and Cosmology Laboratory (APC). Around one hundred physicists from all over the world gathered to discuss progress in the dark matter and low-energy neutrino search. The new results from the LHC were also widely discussed. The Higgs discovery at 125 GeV, without any sign of other new heavy particles, does not provide us with any information on the nature of dark mater. Alternatives to the favored SUSY model, in which the role of the WIMP is played by a stable neutralino, predict low mass candidates below a few GeV. Developing low threshold detectors at sub-keV energies becomes mandatory, and interest for Axion or Axion-like particles as dark matter is revived. We have seen increasing activity in the field and new infrastructures for these searches have been developed. We heard news of activities in the Canfranc laboratory in Spain, Jinping in China, SURF in the USA and about the extension project of Fréjus (LSM) laboratory. We would like to thank the organizing and advisory committees as well as the session chairpersons: J Zinn-Justin, G Wormser, D Nygren, G Chardin, F Vannucci, D Attié, T Patzak and S Jullian. I Giomataris, P Colas and I G Irastorza Group picture

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

    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

  2. The Functional Mobility Scale: ability to detect change following single event multilevel surgery.

    PubMed

    Harvey, Adrienne; Graham, H Kerr; Morris, Meg E; Baker, Richard; Wolfe, Rory

    2007-08-01

    The aim of this study was to examine the ability of the Functional Mobility Scale (FMS) to detect change in children with cerebral palsy (CP) undergoing single event multilevel surgery (SEMLS). A retrospective study was conducted of gait laboratory records and video assessments for a consecutive sample of children with CP aged 4 to 18 years who were managed by multilevel surgery. FMS ratings and Gross Motor Function Classification System (GMFCS) levels were recorded preoperatively and at regular postoperative time points. The sample comprised 66 children (32 females, 34 males) with spastic diplegia, GMFCS Levels I (n=18), II (n=24), and III (n=24). The mean age at surgery was 10 years (SD 2y 6mo, range 6-16y). For each FMS distance (5, 50, and 500m) odds ratios showed significant deterioration in mobility at 3 and 6 months postoperatively. Mobility then improved to baseline levels by 12 months and improved further by 24 months postoperatively. GMFCS level remained stable throughout most of the postoperative period for children classified as GMFCS Level III preoperatively but not for children classified as Levels I or II. The FMS was found to be a clinically feasible tool for quantifying change after SEMLS in children with CP.

  3. Elastomeric optical fiber sensors and method for detecting and measuring events occurring in elastic materials

    DOEpatents

    Muhs, Jeffrey D.; Capps, Gary J.; Smith, David B.; White, Clifford P.

    1994-01-01

    Fiber optic sensing means for the detection and measurement of events such as dynamic loadings imposed upon elastic materials including cementitious materials, elastomers, and animal body components and/or the attrition of such elastic materials are provided. One or more optical fibers each having a deformable core and cladding formed of an elastomeric material such as silicone rubber are embedded in the elastic material. Changes in light transmission through any of the optical fibers due the deformation of the optical fiber by the application of dynamic loads such as compression, tension, or bending loadings imposed on the elastic material or by the attrition of the elastic material such as by cracking, deterioration, aggregate break-up, and muscle, tendon, or organ atrophy provide a measurement of the dynamic loadings and attrition. The fiber optic sensors can be embedded in elastomers subject to dynamic loadings and attrition such as commonly used automobiles and in shoes for determining the amount and frequency of the dynamic loadings and the extent of attrition. The fiber optic sensors are also useable in cementitious material for determining the maturation thereof.

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

    NASA Technical Reports Server (NTRS)

    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.

  5. Analysis of different device-based intrathoracic impedance vectors for detection of heart failure events (from the Detect Fluid Early from Intrathoracic Impedance Monitoring study).

    PubMed

    Heist, E Kevin; Herre, John M; Binkley, Philip F; Van Bakel, Adrian B; Porterfield, James G; Porterfield, Linda M; Qu, Fujian; Turkel, Melanie; Pavri, Behzad B

    2014-10-15

    Detect Fluid Early from Intrathoracic Impedance Monitoring (DEFEAT-PE) is a prospective, multicenter study of multiple intrathoracic impedance vectors to detect pulmonary congestion (PC) events. Changes in intrathoracic impedance between the right ventricular (RV) coil and device can (RVcoil→Can) of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy ICDs (CRT-Ds) are used clinically for the detection of PC events, but other impedance vectors and algorithms have not been studied prospectively. An initial 75-patient study was used to derive optimal impedance vectors to detect PC events, with 2 vector combinations selected for prospective analysis in DEFEAT-PE (ICD vectors: RVring→Can + RVcoil→Can, detection threshold 13 days; CRT-D vectors: left ventricular ring→Can + RVcoil→Can, detection threshold 14 days). Impedance changes were considered true positive if detected <30 days before an adjudicated PC event. One hundred sixty-two patients were enrolled (80 with ICDs and 82 with CRT-Ds), all with ≥1 previous PC event. One hundred forty-four patients provided study data, with 214 patient-years of follow-up and 139 PC events. Sensitivity for PC events of the prespecified algorithms was as follows: ICD: sensitivity 32.3%, false-positive rate 1.28 per patient-year; CRT-D: sensitivity 32.4%, false-positive rate 1.66 per patient-year. An alternative algorithm, ultimately approved by the US Food and Drug Administration (RVring→Can + RVcoil→Can, detection threshold 14 days), resulted in (for all patients) sensitivity of 21.6% and a false-positive rate of 0.9 per patient-year. The CRT-D thoracic impedance vector algorithm selected in the derivation study was not superior to the ICD algorithm RVring→Can + RVcoil→Can when studied prospectively. In conclusion, to achieve an acceptably low false-positive rate, the intrathoracic impedance algorithms studied in DEFEAT-PE resulted in low sensitivity for the prediction of heart

  6. Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy

    PubMed Central

    Holmes, Holly E.; Powell, Nick M.; Ma, Da; Ismail, Ozama; Harrison, Ian F.; Wells, Jack A.; Colgan, Niall; O'Callaghan, James M.; Johnson, Ross A.; Murray, Tracey K.; Ahmed, Zeshan; Heggenes, Morten; Fisher, Alice; Cardoso, M. Jorge; Modat, Marc; O'Neill, Michael J.; Collins, Emily C.; Fisher, Elizabeth M. C.; Ourselin, Sébastien; Lythgoe, Mark F.

    2017-01-01

    With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.

  7. A complex interplay of genetic and epigenetic events leads to abnormal expression of the DUX4 gene in facioscapulohumeral muscular dystrophy.

    PubMed

    Gatica, Laura Virginia; Rosa, Alberto Luis

    2016-12-01

    Facioscapulohumeral muscular dystrophy (FSHD), a prevalent inherited human myopathy, develops following a complex interplay of genetic and epigenetic events. FSHD1, the more frequent genetic form, is associated with: (1) deletion of an integral number of 3.3 Kb (D4Z4) repeated elements at the chromosomal region 4q35, (2) a specific 4q35 subtelomeric haplotype denominated 4qA, and (3) decreased methylation of cytosines at the 4q35-linked D4Z4 units. FSHD2 is most often caused by mutations at the SMCHD1 (Structural Maintenance of Chromosomes Hinge Domain 1) gene, on chromosome 18p11.32. FSHD2 individuals also carry the 4qA haplotype and decreased methylation of D4Z4 cytosines. Each D4Z4 unit contains a copy of the retrotransposed gene DUX4 (double homeobox containing protein 4). DUX4 gene functionality was questioned in the past because of its pseudogene-like structure, its location on repetitive telomeric DNA sequences (i.e. junk DNA), and the elusive nature of both the DUX4 transcript and the encoded protein, DUX4. It is now known that DUX4 is a nuclear-located transcription factor, which is normally expressed in germinal tissues. Aberrant DUX4 expression triggers a deregulation cascade inhibiting muscle differentiation, sensitizing cells to oxidative stress, and inducing muscle atrophy. A unifying pathogenic model for FSHD emerged with the recognition that the FSHD-permissive 4qA haplotype corresponds to a polyadenylation signal that stabilizes the DUX4 mRNA, allowing the toxic protein DUX4 to be expressed. This working hypothesis for FSHD pathogenesis highlights the intrinsic epigenetic nature of the molecular mechanism underlying FSHD as well as the pathogenic pathway connecting FSHD1 and FSHD2. Pharmacological control of either DUX4 gene expression or the activity of the DUX4 protein constitutes current potential rational therapeutic approaches to treat FSHD.

  8. Gait event detection using linear accelerometers or angular velocity transducers in able-bodied and spinal-cord injured individuals.

    PubMed

    Jasiewicz, Jan M; Allum, John H J; Middleton, James W; Barriskill, Andrew; Condie, Peter; Purcell, Brendan; Li, Raymond Che Tin

    2006-12-01

    We report on three different methods of gait event detection (toe-off and heel strike) using miniature linear accelerometers and angular velocity transducers in comparison to using standard pressure-sensitive foot switches. Detection was performed with normal and spinal-cord injured subjects. The detection of end contact (EC), normally toe-off, and initial contact (IC) normally, heel strike was based on either foot linear accelerations or foot sagittal angular velocity or shank sagittal angular velocity. The results showed that all three methods were as accurate as foot switches in estimating times of IC and EC for normal gait patterns. In spinal-cord injured subjects, shank angular velocity was significantly less accurate (p<0.02). We conclude that detection based on foot linear accelerations or foot angular velocity can correctly identify the timing of IC and EC events in both normal and spinal-cord injured subjects.

  9. Congenital abnormalities and selective abortion.

    PubMed

    Seller, M J

    1976-09-01

    The technique of amniocentesis, by which an abnormal fetus can be detected in utero, has brought a technological advance in medical science but attendant medical and moral problems. Dr Seller describes those congenital disabilities which can be detected in the fetus before birth, for which the "remedy" is selective abortion. She then discusses the arguments for and against selective abortion, for the issue is not simple, even in the strictly genetic sense of attempting to ensure a population free of congenital abnormality.

  10. Detecting Visual Function Abnormality with a Contrast-Dependent Visual Test in Patients with Type 2 Diabetes.

    PubMed

    Tsai, Li-Ting; Liao, Kuo-Meng; Jang, Yuh; Hu, Fu-Chang; Wu, Wei-Chi

    2016-01-01

    In addition to diabetic retinopathy, diabetes also causes early retinal neurodegeneration and other eye problems, which cause various types of visual deficits. This study used a computer-based visual test (Macular Multi-Function Assessment (MMFA)) to assess contrast-dependent macular visual function in patients with type 2 diabetes to collect more visual information than possible with only the visual acuity test. Because the MMFA is a newly developed test, this study first compared the agreement and discriminative ability of the MMFA and the Early Treatment Diabetic Retinopathy Study (ETDRS) contrast acuity charts. Then symbol discrimination performances of diabetic patients and controls were evaluated at 4 contrast levels using the MMFA. Seventy-seven patients and 45 controls participated. The agreement between MMFA and ETDRS scores was examined by fitting three-level linear mixed-effect models to estimate the intraclass correlation coefficients (ICCs). The estimated areas under the receiver operating characteristic (ROC) curve were used to compare the discriminative ability of diseased versus non-diseased participants between the two tests. The MMFA scores of patients and controls were compared with multiple linear regression analysis after adjusting the effects of age, sex, hypertension and cataract. Results showed that the scores of the MMFA and ETDRS tests displayed high levels of agreement and acceptable and similar discriminative ability. The MMFA performance was correlated with the severity of diabetic retinopathy. Most of the MMFA scores differed significantly between the diabetic patients and controls. In the low contrast condition, the MMFA scores were significantly lower for 006Eon-DR patients than for controls. The potential utility of the MMFA as an easy screening tool for contrast-dependent visual function and for detecting early functional visual change in patients with type 2 diabetes is discussed.

  11. Detection of abnormalities in the superficial zone of cartilage repaired using a tissue engineered construct derived from synovial stem cells.

    PubMed

    Ando, Wataru; Fujie, Hiromichi; Moriguchi, Yu; Nansai, Ryosuke; Shimomura, Kazunori; Hart, David A; Yoshikawa, Hideki; Nakamura, Norimasa

    2012-09-28

    The present study investigated the surface structure and mechanical properties of repair cartilage generated from a tissue engineered construct (TEC) derived from synovial mesenchymal stem cells at six months post-implantation compared to those of uninjured cartilage. TEC-mediated repair tissue was cartilaginous with Safranin O staining, and had comparable macro-scale compressive properties with uninjured cartilage. However, morphological assessments revealed that the superficial zone of TEC-mediated tissue was more fibrocartilage-like, in contrast to the middle or deep zones that were more hyaline cartilage-like with Safranin O staining. Histological scoring of the TEC-mediated tissue was significantly lower in the superficial zone than in the middle and deep zones. Scanning electron microscopy showed a thick tangential bundle of collagen fibres at the most superficial layer of uninjured cartilage, while no corresponding structure was detected at the surface of TEC-mediated tissue. Immunohistochemical analysis revealed that PRG4 was localised in the superficial area of uninjured cartilage, as well as the TEC-mediated tissue. Friction testing showed that the lubrication properties of the two tissues was similar, however, micro-indentation analysis revealed that the surface stiffness of the TEC-repair tissue was significantly lower than that of uninjured cartilage. Permeability testing indicated that the TEC-mediated tissue exhibited lower water retaining capacity than did uninjured cartilage, specifically at the superficial zone. Thus, TEC-mediated tissue exhibited compromised mechanical properties at the superficial zone, properties which need improvement in the future for maintenance of long term repair cartilage integrity.

  12. Detecting Visual Function Abnormality with a Contrast-Dependent Visual Test in Patients with Type 2 Diabetes

    PubMed Central

    Jang, Yuh; Hu, Fu-Chang; Wu, Wei-Chi

    2016-01-01

    In addition to diabetic retinopathy, diabetes also causes early retinal neurodegeneration and other eye problems, which cause various types of visual deficits. This study used a computer-based visual test (Macular Multi-Function Assessment (MMFA)) to assess contrast-dependent macular visual function in patients with type 2 diabetes to collect more visual information than possible with only the visual acuity test. Because the MMFA is a newly developed test, this study first compared the agreement and discriminative ability of the MMFA and the Early Treatment Diabetic Retinopathy Study (ETDRS) contrast acuity charts. Then symbol discrimination performances of diabetic patients and controls were evaluated at 4 contrast levels using the MMFA. Seventy-seven patients and 45 controls participated. The agreement between MMFA and ETDRS scores was examined by fitting three-level linear mixed-effect models to estimate the intraclass correlation coefficients (ICCs). The estimated areas under the receiver operating characteristic (ROC) curve were used to compare the discriminative ability of diseased versus non-diseased participants between the two tests. The MMFA scores of patients and controls were compared with multiple linear regression analysis after adjusting the effects of age, sex, hypertension and cataract. Results showed that the scores of the MMFA and ETDRS tests displayed high levels of agreement and acceptable and similar discriminative ability. The MMFA performance was correlated with the severity of diabetic retinopathy. Most of the MMFA scores differed significantly between the diabetic patients and controls. In the low contrast condition, the MMFA scores were significantly lower for 006Eon-DR patients than for controls. The potential utility of the MMFA as an easy screening tool for contrast-dependent visual function and for detecting early functional visual change in patients with type 2 diabetes is discussed. PMID:27611680

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

    PubMed

    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%) were lower than those during dry weather conditions (>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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

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

    PubMed Central

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

    2013-01-01

    Background 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. Objective To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. Methods 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. Results 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. Conclusion 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

  18. Novel Logistic Regression Model of Chest CT Attenuation Coefficient Distributions for the Automated Detection of Abnormal (Emphysema or ILD) versus Normal Lung

    PubMed Central

    Chan, Kung-Sik; Jiao, Feiran; Mikulski, Marek A.; Gerke, Alicia; Guo, Junfeng; Newell, John D; Hoffman, Eric A.; Thompson, Brad; Lee, Chang Hyun; Fuortes, Laurence J.

    2015-01-01

    Rationale and Objectives We evaluated the role of automated quantitative computed tomography (CT) scan interpretation algorithm in detecting Interstitial Lung Disease (ILD) and/or emphysema in a sample of elderly subjects with mild lung disease.ypothesized that the quantification and distributions of CT attenuation values on lung CT, over a subset of Hounsfield Units (HU) range [−1000 HU, 0 HU], can differentiate early or mild disease from normal lung. Materials and Methods We compared results of quantitative spiral rapid end-exhalation (functional residual capacity; FRC) and end-inhalation (total lung capacity; TLC) CT scan analyses in 52 subjects with radiographic evidence of mild fibrotic lung disease to 17 normal subjects. Several CT value distributions were explored, including (i) that from the peripheral lung taken at TLC (with peels at 15 or 65mm), (ii) the ratio of (i) to that from the core of lung, and (iii) the ratio of (ii) to its FRC counterpart. We developed a fused-lasso logistic regression model that can automatically identify sub-intervals of [−1000 HU, 0 HU] over which a CT value distribution provides optimal discrimination between abnormal and normal scans. Results The fused-lasso logistic regression model based on (ii) with 15 mm peel identified the relative frequency of CT values over [−1000, −900] and that over [−450,−200] HU as a means of discriminating abnormal versus normal, resulting in a zero out-sample false positive rate and 15%false negative rate of that was lowered to 12% by pooling information. Conclusions We demonstrated the potential usefulness of this novel quantitative imaging analysis method in discriminating ILD and/or emphysema from normal lungs. PMID:26776294

  19. A new method for producing automated seismic bulletins: Probabilistic event detection, association, and location

    SciTech Connect

    Draelos, Timothy J.; Ballard, Sanford; Young, Christopher J.; Brogan, Ronald

    2015-10-01

    Given a set of observations within a specified time window, a fitness value is calculated at each grid node by summing station-specific conditional fitness values. Assuming each observation was generated by a refracted P wave, these values are proportional to the conditional probabilities that each observation was generated by a seismic event at the grid node. The node with highest fitness value is accepted as a hypothetical event location, subject to some minimal fitness value, and all arrivals within a longer time window consistent with that event are associated with it. During the association step, a variety of different phases are considered. In addition, once associated with an event, an arrival is removed from further consideration. While unassociated arrivals remain, the search for other events is repeated until none are identified.

  20. A new method for producing automated seismic bulletins: Probabilistic event detection, association, and location

    DOE PAGES

    Draelos, Timothy J.; Ballard, Sanford; Young, Christopher J.; ...

    2015-10-01

    Given a set of observations within a specified time window, a fitness value is calculated at each grid node by summing station-specific conditional fitness values. Assuming each observation was generated by a refracted P wave, these values are proportional to the conditional probabilities that each observation was generated by a seismic event at the grid node. The node with highest fitness value is accepted as a hypothetical event location, subject to some minimal fitness value, and all arrivals within a longer time window consistent with that event are associated with it. During the association step, a variety of different phasesmore » are considered. In addition, once associated with an event, an arrival is removed from further consideration. While unassociated arrivals remain, the search for other events is repeated until none are identified.« less

  1. Rapid and Highly Sensitive Detection of Variant Creutzfeldt - Jakob Disease Abnormal Prion Protein on Steel Surfaces by Protein Misfolding Cyclic Amplification: Application to Prion Decontamination Studies

    PubMed Central

    Belondrade, Maxime; Nicot, Simon; Béringue, Vincent; Coste, Joliette; Lehmann, Sylvain; Bougard, Daisy

    2016-01-01

    The prevalence of variant Creutzfeldt-Jakob disease (vCJD) in the population remains uncertain, although it has been estimated that 1 in 2000 people in the United Kingdom are positive for abnormal prion protein (PrPTSE) by a recent survey of archived appendix tissues. The prominent lymphotropism of vCJD prions raises the possibility that some surgical procedures may be at risk of iatrogenic vCJD transmission in healthcare facilities. It is therefore vital that decontamination procedures applied to medical devices before their reprocessing are thoroughly validated. A current limitation is the lack of a rapid model permissive to human prions. Here, we developed a prion detection assay based on protein misfolding cyclic amplification (PMCA) technology combined with stainless-steel wire surfaces as carriers of prions (Surf-PMCA). This assay allowed the specific detection of minute quantities (10−8 brain dilution) of either human vCJD or ovine scrapie PrPTSE adsorbed onto a single steel wire, within a two week timeframe. Using Surf-PMCA we evaluated the performance of several reference and commercially available prion-specific decontamination procedures. Surprisingly, we found the efficiency of several marketed reagents to remove human vCJD PrPTSE was lower than expected. Overall, our results demonstrate that Surf-PMCA can be used as a rapid and ultrasensitive assay for the detection of human vCJD PrPTSE adsorbed onto a metallic surface, therefore facilitating the development and validation of decontamination procedures against human prions. PMID:26800081

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

    PubMed

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

    2012-01-01

    The increased variations of temporal gait events when pathology is present are good candidate features for objective diagnostic tests. We hypothesised that the gait events hoof-on/off and stance can be detected accurately and precisely using features from trunk and distal limb-mounted Inertial 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. 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 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.

  3. The truth will out: interrogative polygraphy ("lie detection") with event-related brain potentials.

    PubMed

    Farwell, L A; Donchin, E

    1991-09-01

    The feasibility of using Event Related Brain Potentials (ERPs) in Interrogative Polygraphy ("Lie Detection") was tested by examining the effectiveness of the Guilty Knowledge Test designed by Farwell and Donchin (1986, 1988). The subject is assigned an arbitrary task requiring discrimination between experimenter-designated targets and other, irrelevant stimuli. A group of diagnostic items ("probes"), which to the unwitting are indistinguishable from the irrelevant items, are embedded among the irrelevant. For subjects who possess "guilty knowledge" these probes are distinct from the irrelevants and are likely to elicit a P300, thus revealing their possessing the special knowledge that allows them to differentiate the probes from the irrelevants. We report two experiments in which this paradigm was tested. In Experiment 1, 20 subjects participated in one of two mock espionage scenarios and were tested for their knowledge of both scenarios. All stimuli consisted of short phrases presented for 300 ms each at an interstimulus interval of 1550 ms. A set of items were designated as "targets" and appeared on 17% of the trials. Probes related to the scenarios also appeared on 17% of the trials. The rest of the items were irrelevants. Subjects responded by pressing one switch following targets, and the other following irrelevants (and, of course, probes). ERPs were recorded from FZ, CZ, and PZ. As predicted, targets elicited large P300s in all subjects. Probes associated with a given scenario elicited a P300 in subjects who participated in that scenario. A bootstrapping method was used to assess the quality of the decision for each subject. The algorithm declared the decision indeterminate in 12.5% of the cases. In all other cases a decision was made. There were no false positives and no false negatives: whenever a determination was made it was accurate. The second experiment was virtually identical to the first, with identical results, except that this time 4 subjects were

  4. Wavelet packet transform for detection of single events in acoustic emission signals

    NASA Astrophysics Data System (ADS)

    Bianchi, Davide; Mayrhofer, Erwin; Gröschl, Martin; Betz, Gerhard; Vernes, András

    2015-12-01

    Acoustic emission signals in tribology can be used for monitoring the state of bodies in contact and relative motion. The recorded signal includes information which can be associated with different events, such as the formation and propagation of cracks, appearance of scratches and so on. One of the major challenges in analyzing these acoustic emission signals is to identify parts of the signal which belong to such an event and discern it from noise. In this contribution, a wavelet packet decomposition within the framework of multiresolution analysis theory is considered to analyze acoustic emission signals to investigate the failure of tribological systems. By applying the wavelet packet transform a method for the extraction of single events in rail contact fatigue test is proposed. The extraction of such events at several stages of the test permits a classification and the analysis of the evolution of cracks in the rail.

  5. Hard X-ray Detectability of Small Impulsive Heating Events in the Solar Corona

    NASA Astrophysics Data System (ADS)

    Glesener, L.; Klimchuk, J. A.; Bradshaw, S. J.; Marsh, A.; Krucker, S.; Christe, S.

    2015-12-01

    Impulsive heating events ("nanoflares") are a candidate to supply the solar corona with its ~2 MK temperature. These transient events can be studied using extreme ultraviolet and soft X-ray observations, among others. However, the impulsive events may occur in tenuous loops on small enough timescales that the heating is essentially not observed due to ionization timescales, and only the cooling phase is observed. Bremsstrahlung hard X-rays could serve as a more direct and prompt indicator of transient heating events. A hard X-ray spacecraft based on the direct-focusing technology pioneered by the Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket could search for these direct signatures. In this work, we use the hydrodynamical EBTEL code to simulate differential emission measures produced by individual heating events and by ensembles of such events. We then directly predict hard X-ray spectra and consider their observability by a future spaceborne FOXSI, and also by the RHESSI and NuSTAR spacecraft.

  6. Utility of Clinical Breast Exams in Detecting Local-Regional Breast Events after Breast-Conservation in Women with a Personal History of High-risk Breast Cancer

    PubMed Central

    Neuman, Heather B.; Schumacher, Jessica R.; Francescatti, Amanda B.; Adesoye, Taiwo; SB, Edge; ES, Burnside; DJ, Vanness; M, Yu; Y, Si; D, McKellar; DP, Winchester; Greenberg, Caprice C.

    2016-01-01

    Introduction Although breast cancer follow-up guidelines emphasize the importance of clinical exams, prior studies suggest a small fraction of local-regional events occurring after breast conservation are detected by exam alone. Our objective was to examine how local-regional events are detected in a contemporary, national cohort of high-risk breast cancer survivors. Methods A stage-stratified sample of stage II/III breast cancer patients diagnosed in 2006-2007 (n=11,099) were identified from 1,217 facilities within the National Cancer Data Base. Additional data on local-regional and distant breast events, method of event detection, imaging received, and mortality was collected. We further limited the cohort to patients with breast conservation (n=4,854). Summary statistics describe local-regional event rates and detection method. Results Local-regional events were detected in 5.5% (n=265). 83% were ipsilateral or contralateral in-breast events, and 17% within ipsilateral lymph nodes. 48% of local-regional events were detected on asymptomatic breast imaging, 29% by patients, and 10% on clinical exam. Overall, 0.5% of the 4,854 patients had a local-regional event detected on exam. Exams detected a higher proportion of lymph node (8/45) compared to in-breast events (18/220). No factors were associated with method of event detection. Discussion Clinical exams, as an adjunct to screening mammography, have a modest effect on local-regional event detection. This contradicts current belief that exams are a critical adjunct to mammographic screening. These findings can help to streamline follow-up care, potentially improving follow-up efficiency and quality. PMID:27491784

  7. Repetitive Model of Mild Traumatic Brain Injury Produces Cortical Abnormalities Detectable by Magnetic Resonance Diffusion Imaging (DTI/DKI), Histopathology, and Behavior.

    PubMed

    Yu, Fengshan; Shukla, Dinesh K; Armstrong, Regina C; Marion, Christina M; Radomski, Kryslaine L; Selwyn, Reed G; Dardzinski, Bernard J

    2016-12-20

    Noninvasive detection of mild traumatic brain injury (mTBI) is important for evaluating acute through chronic effects of head injuries, particularly after repetitive impacts. To better detect abnormalities from mTBI, we performed longitudinal studies (baseline, 3, 6, and 42 days) using magnetic resonance diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) in adult mice after repetitive mTBI (r-mTBI; daily × 5) or sham procedure. This r-mTBI produced righting reflex delay and was first characterized in the corpus callosum to demonstrate low levels of axon damage, astrogliosis, and microglial activation, without microhemorrhages. High-resolution DTI-DKI was then combined with post-imaging pathological validation along with behavioral assessments targeted for the impact regions. In the corpus callosum, only DTI fractional anisotropy at 42 days showed significant change post-injury. Conversely, cortical regions under the impact site (M1-M2, anterior cingulate) had reduced axial diffusivity (AD) at all time points with a corresponding increase in axial kurtosis (Ka) at 6 days. Post-imaging neuropathology showed microglial activation in both the corpus callosum and cortex at 42 days after r-mTBI. Increased cortical microglial activation correlated with decreased cortical AD after r-mTBI (r = -0.853; n = 5). Using Thy1-YFP-16 mice to fluorescently label neuronal cell bodies and processes revealed low levels of axon damage in the cortex after r-mTBI. Finally, r-mTBI produced social deficits consistent with the function of this anterior cingulate region of cortex. Overall, vulnerability of cortical regions is demonstrated after mild repetitive injury, with underlying differences of DTI and DKI, microglial activation, and behavioral deficits.

  8. Decaplex and real-time PCR based detection of MON531 and MON15985 Bt cotton events.

    PubMed

    Randhawa, Gurinder Jit; Chhabra, Rashmi; Singh, Monika

    2010-09-22

    The genetically modified (GM) Bt crops expressing delta-endotoxins from Bacillus thuringiensis provide protection against a wide range of lepidopteron insect pests throughout the growing season of the plant. Bt cotton is the only commercialized crop in India that is planted on an area of 7.6 million hectares. With the increase in development and commercialization of transgenic crops, it is necessary to develop appropriate qualitative and quantitative methods for detection of different transgenic events. The present study reports on the development of a decaplex polymerase chain reaction (PCR) assay for simultaneous detection of transgene sequences, specific transgene constructs, and endogenous stearoyl acyl desaturase (Sad1) gene in two events of Bt cotton, i.e., MON531 and MON15985. The decaplex PCR assay is an efficient tool to identify and discriminate the two major commercialized events of Bt cotton, i.e., MON531 and MON15985, in India. Real-time PCR assays were also developed for quantification of cry1Ac and cry2Ab genes being employed in these two events. The quantitative method was developed using seven serial dilutions containing different levels of Bt cotton DNA mixed with a non-Bt counterpart ranging from 0.01 to 100%. The results revealed that the biases from the true value and the relative standard deviations were all within the range of ±20%. The limit of quantification (LOQ) of the developed real-time PCR method has also been established up to 0.01%.

  9. Characterization and Quantification of Nanoparticle-Antibody Conjugates on Cells Using C60 ToF SIMS in the Event-By-Event Bombardment/Detection Mode

    PubMed Central

    Chen, Li-Jung; Shah, Sunny S.; Silangcruz, Jaime; Eller, Michael J.; Verkhoturov, Stanislav V.; Revzin, Alexander; Schweikert, Emile A.

    2011-01-01

    Cluster C60 ToF-SIMS (time-of-flight secondary ion mass spectrometry) operated in the event-by-event bombardment-detection method has been applied to: a) quantify the binding density of Au nanoparticles (AuNPs)-antiCD4 conjugates on the cell surface; b) identify the binding sites between AuNPs and antibody. Briefly, our method consists of recording the secondary ions, SIs, individually emitted from a single C601,2+ impact. From the cumulative mass spectral data we selected events where a specific SI was detected. The selected records revealed the SIs co-ejected from the nanovolume impacted by an individual C60 with an emission area of ~ 10nm in diameter as an emission depth of 5–10 nm. The fractional coverage is obtained as the ratio of the effective number of projectile impacts on a specified sampling area (Ne) to the total number of impacts (N0). In the negative ion mass spectrum, the palmitate (C16H31O2−) and oletate (C18H33O2−) fatty acid ions present signals from lipid membrane of the cells. The signals at m/z 197 (Au−) and 223 (AuCN−) originate from the AuNPs labeled antibodies (antiCD4) bound to the cell surface antigens. The characteristic amino acid ions validate the presence of antiCD4. A coincidence mass spectrum extracted with ion at m/z 223 (AuCN−) reveals the presence of cysteine at m/z 120, documenting the closeness of cysteine and the AuNP. Their proximity suggests that the binding site for AuNP on the antibody is the sulfur-terminal cysteine. The fractional coverage of membrane lipid was determined to be ~23% of the cell surfaces while the AuNPs was found to be ~21%. The novel method can be implemented on smaller size NPs, it should thus be applicable for studies on size dependent binding of NP-antibody conjugates. PMID:21691427

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

    SciTech Connect

    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.

  11. Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

    SciTech Connect

    Teuton, Jeremy R.; Griswold, Richard L.; Mehdi, Beata L.; Browning, Nigel D.

    2015-09-23

    Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the data into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.

  12. Hard X-Ray Burst Detected From Caltech Plasma Jet Experiment Magnetic Reconnection Event

    NASA Astrophysics Data System (ADS)

    Marshall, Ryan S.; Bellan, Paul M.

    2016-10-01

    In the Caltech plasma jet experiment a 100 kA MHD driven jet becomes kink unstable leading to a Rayleigh-Taylor instability that quickly causes a magnetic reconnection event. Movies show that the Rayleigh-Taylor instability is simultaneous with voltage spikes across the electrodes that provide the current that drives the jet. Hard x-rays between 4 keV and 9 keV have now been observed using an x-ray scintillator detector mounted just outside of a kapton window on the vacuum chamber. Preliminary results indicate that the timing of the x-ray burst coincides with a voltage spike on the electrodes occurring in association with the Rayleigh-Taylor event. The x-ray signal accompanies the voltage spike and Rayleigh-Taylor event in approximately 50% of the shots. A possible explanation for why the x-ray signal is sometimes missing is that the magnetic reconnection event may be localized to a specific region of the plasma outside the line of sight of the scintillator. The x-ray signal has also been seen accompanying the voltage spike when no Rayleigh-Taylor is observed. This may be due to the interframe timing on the camera being longer than the very short duration of the Rayleigh-Taylor instability.

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

    ERIC Educational Resources Information Center

    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. Best practice for single-trial detection of event-related potentials: Application to brain-computer interfaces.

    PubMed

    Cecotti, Hubert; Ries, Anthony J

    2017-01-01

    The detection of event-related potentials (ERPs) in the electroencephalogram (EEG) signal is a fundamental component in non-invasive brain-computer interface (BCI) research, and in modern cognitive neuroscience studies. Whereas the grand average response across trials provides an estimation of essential characteristics of a brain-evoked response, an estimation of the differences between trials for a particular type of stimulus can provide key insight about the brain dynamics and possible origins of the brain response. The research in ERP single-trial detection has been mainly driven by applications in biomedical engineering, with an interest from machine learning and signal processing groups that test novel methods on noisy signals. Efficient single-trial detection techniques require processing steps that include temporal filtering, spatial filtering, and classification. In this paper, we review the current state-of-the-art methods for single-trial detection of event-related potentials with applications in BCI. Efficient single-trial detection techniques should embed simple yet efficient functions requiring as few hyper-parameters as possible. The focus of this paper is on methods that do not include a large number of hyper-parameters and can be easily implemented with datasets containing a limited number of trials. A benchmark of different classification methods is proposed on a database recorded from sixteen healthy subjects during a rapid serial visual presentation task. The results support the conclusion that single-trial detection can be achieved with an area under the ROC curve superior to 0.9 with less than ten sensors and 20 trials corresponding to the presentation of a target. Whereas the number of sensors is not a key element for efficient single-trial detection, the number of trials must be carefully chosen for creating a robust classifier.

  15. Real-time detection of organic contamination events in water distribution systems by principal components analysis of ultraviolet spectral data.

    PubMed

    Zhang, Jian; Hou, Dibo; Wang, Ke; Huang, Pingjie; Zhang, Guangxin; Loáiciga, Hugo

    2017-04-01

    The detection of organic contaminants in water distribution systems is essential to protect public health from potential harmful compounds resulting from accidental spills or intentional releases. Existing methods for detecting organic contaminants are based on quantitative analyses such as chemical testing and gas/liquid chromatography, which are time- and reagent-consuming and involve costly maintenance. This study proposes a novel procedure based on discrete wavelet transform and principal component analysis for detecting organic contamination events from ultraviolet spectral data. Firstly, the spectrum of each observation is transformed using discrete wavelet with a coiflet mother wavelet to capture the abrupt change along the wavelength. Principal component analysis is then employed to approximate the spectra based on capture and fusion features. The significant value of Hotelling's T(2) statistics is calculated and used to detect outliers. An alarm of contamination event is triggered by sequential Bayesian analysis when the outliers appear continuously in several observations. The effectiveness of the proposed procedure is tested on-line using a pilot-scale setup and experimental data.

  16. A new PCR-CGE (size and color) method for simultaneous detection of genetically modified maize events.

    PubMed

    Nadal, Anna; Coll, Anna; La Paz, Jose-Luis; Esteve, Teresa; Pla, Maria

    2006-10-01

    We present a novel multiplex PCR assay for simultaneous detection of multiple transgenic events in maize. Initially, five PCR primers pairs specific to events Bt11, GA21, MON810, and NK603, and Zea mays L. (alcohol dehydrogenase) were included. The event specificity was based on amplification of transgene/plant genome flanking regions, i.e., the same targets as for validated real-time PCR assays. These short and similarly sized amplicons were selected to achieve high and similar amplification efficiency for all targets; however, its unambiguous identification was a technical challenge. We achieved a clear distinction by a novel CGE approach that combined the identification by size and color (CGE-SC). In one single step, all five targets were amplified and specifically labeled with three different fluorescent dyes. The assay was specific and displayed an LOD of 0.1% of each genetically modified organism (GMO). Therefore, it was adequate to fulfill legal thresholds established, e.g., in the European Union. Our CGE-SC based strategy in combination with an adequate labeling design has the potential to simultaneously detect higher numbers of targets. As an example, we present the detection of up to eight targets in a single run. Multiplex PCR-CGE-SC only requires a conventional sequencer device and enables automation and high throughput. In addition, it proved to be transferable to a different laboratory. The number of authorized GMO events is rapidly growing; and the acreage of genetically modified (GM) varieties cultivated and commercialized worldwide is rapidly increasing. In this context, our multiplex PCR-CGE-SC can be suitable for screening GM contents in food.

  17. Detecting specific health-related events using an integrated sensor system for vital sign monitoring.

    PubMed

    Adnane, Mourad; Jiang, Zhongwei; Choi, Samjin; Jang, Hoyoung

    2009-01-01

    In this paper, a new method for the detection of apnea/hypopnea periods in physiological data is presented. The method is based on the intelligent combination of an integrated sensor system for long-time cardiorespiratory signal monitoring and dedicated signal-processing packages. Integrated sensors are a PVDF film and conductive fabric sheets. The signal processing package includes dedicated respiratory cycle (RC) and QRS complex detection algorithms and a new method using the respiratory cycle variability (RCV) for detecting apnea/hypopnea periods in physiological data. Results show that our method is suitable for online analysis of long time series data.

  18. Chronic sensory stroke with and without central pain is associated with bilaterally distributed sensory abnormalities as detected by quantitative sensory testing.

    PubMed

    Krause, Thomas; Asseyer, Susanna; Geisler, Frederik; Fiebach, Jochen B; Oeltjenbruns, Jochen; Kopf, Andreas; Villringer, Kersten; Villringer, Arno; Jungehulsing, Gerhard J

    2016-01-01

    Approximately 20% of patients suffering from stroke with pure or predominant sensory symptoms (referred to as sensory stroke patients) develop central poststroke pain (CPSP). It is largely unknown what distinguishes these patients from those who remain pain free. Using quantitative sensory testing (QST), we analyzed the somatosensory profiles of 50 patients with chronic sensory stroke, of which 25 suffered from CPSP. As compared with reference data from healthy controls, patients with CPSP showed alterations of thermal and mechanical thresholds on the body area contralateral to their stroke (P < 0.01). Patients with sensory stroke but without CPSP (non-pain sensory stroke [NPSS] patients) exhibited similar albeit less pronounced contralesional changes. Paradoxical heat sensation (PHS) and dynamic mechanical allodynia (DMA) showed higher values in CPSP, and an elevated cold detection threshold (CDT) was seen more often in CPSP than in patients with NPSS (P < 0.05). In patients with CPSP, changes in CDT, PHS, dynamic mechanical allodynia, and temporal pain summation (wind-up ratio) each correlated with the presence of pain (P < 0.05). On the homologous ipsilesional body area, both patient groups showed additional significant abnormalities as compared with the reference data, which strongly resembled the contralesional changes. In summary, our analysis reveals that CPSP is associated with impaired temperature perception and positive sensory signs, but differences between patients with CPSP and NPSS are subtle. Both patients with CPSP and NPSS show considerable QST changes on the ipsilesional body side. These results are in part paralleled by recent findings of bilaterally spread cortical atrophy in CPSP and might reflect chronic maladaptive cortical plasticity, particularly in patients with CPSP.

  19. Event detection and control co-design of sampled-data systems

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyu; Chen, Tongwen

    2014-04-01

    This paper proposes event detector and controller co-design criteria for sampled-data systems in which static or dynamic output feedback controllers are used. The resulting criteria provide sufficient conditions to ensure the asymptotic stability of the closed-loop system with reduced communication rates among sensors, controllers, and actuators. The transmissions are mediated by event detectors at both sensor and controller nodes. For static output feedback control, the sufficient condition is given in terms of the feasibility of bilinear matrix inequalities (BMIs). The BMI feasibility problem is converted into a nonlinear optimisation problem involving linear matrix inequalities (LMIs), which is solved via the complementarity linearisation algorithm. For dynamic output feedback control, the sufficient condition is formulated into an LMI feasibility problem, which is readily solved with existing tools. Numerical examples are included to show the effectiveness of the proposed methods.

  20. Data-Driven Multimodal Sleep Apnea Events Detection : Synchrosquezing Transform Processing and Riemannian Geometry Classification Approaches.

    PubMed

    Rutkowski, Tomasz M

    2016-07-01

    A novel multimodal and bio-inspired approach to biomedical signal processing and classification is presented in the paper. This approach allows for an automatic semantic labeling (interpretation) of sleep apnea events based the proposed data-driven biomedical signal processing and classification. The presented signal processing and classification methods have been already successfully applied to real-time unimodal brainwaves (EEG only) decoding in brain-computer interfaces developed by the author. In the current project the very encouraging results are obtained using multimodal biomedical (brainwaves and peripheral physiological) signals in a unified processing approach allowing for the automatic semantic data description. The results thus support a hypothesis of the data-driven and bio-inspired signal processing approach validity for medical data semantic interpretation based on the sleep apnea events machine-learning-related classification.

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

    DTIC Science & Technology

    2006-03-01

    recognition. While domain-specific methodologies have garnered varying success levels, a general approach for this complex task has yet to be found...robust event pattern recognition. While domain-specific methodologies have garnered varying success levels, a general approach for this complex...task has yet to be found and therefore motivates this research effort. The overall research goal is to develop, test, and validate a robust generic

  2. Detection of Olfactory Dysfunction Using Olfactory Event Related Potentials in Young Patients with Multiple Sclerosis

    PubMed Central

    Caminiti, Fabrizia; De Salvo, Simona; De Cola, Maria Cristina; Russo, Margherita; Bramanti, Placido; Marino, Silvia; Ciurleo, Rosella

    2014-01-01

    Background Several studies reported olfactory dysfunction in patients with multiple sclerosis. The estimate of the incidence of olfactory deficits in multiple sclerosis is uncertain; this may arise from different testing methods that may be influenced by patients' response bias and clinical, demographic and cognitive features. Aims To evaluate objectively the olfactory function using Olfactory Event Related Potentials. Materials and Methods We tested the olfactory function of 30 patients with relapsing remitting multiple sclerosis (mean age of 36.03±6.96 years) and of 30 age, sex and smoking–habit matched healthy controls by using olfactory potentials. A selective and controlled stimulation of the olfactory system to elicit the olfactory event related potentials was achieved by a computer-controlled olfactometer linked directly with electroencephalograph. Relationships between olfactory potential results and patients' clinical characteristics, such as gender, disability status score, disease-modifying therapy, and disease duration, were evaluated. Results Seven of 30 patients did not show olfactory event related potentials. Sixteen of remaining 23 patients had a mean value of amplitude significantly lower than control group (p<0.01). The presence/absence of olfactory event related potentials was associated with dichotomous expanded disability status scale (p = 0.0433), as well as inversely correlated with the disease duration (r = −0.3641, p = 0.0479). Conclusion Unbiased olfactory dysfunction of different severity found in multiple sclerosis patients suggests an organic impairment which could be related to neuroinflammatory and/or neurodegenerative processes of olfactory networks, supporting the recent findings on neurophysiopathology of disease. PMID:25047369

  3. Enriched Encoding: Reward Motivation Organizes Cortical Networks for Hippocampal Detection of Unexpected Events

    PubMed Central

    Murty, Vishnu P.; Adcock, R. Alison

    2014-01-01

    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. PMID:23529005

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

    PubMed

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

    Learning how to obtain rewards requires learnin