Sample records for abnormal event detection

  1. Abnormal global and local event detection in compressive sensing domain

    NASA Astrophysics Data System (ADS)

    Wang, Tian; Qiao, Meina; Chen, Jie; Wang, Chuanyun; Zhang, Wenjia; Snoussi, Hichem

    2018-05-01

    Abnormal event detection, also known as anomaly detection, is one challenging task in security video surveillance. It is important to develop effective and robust movement representation models for global and local abnormal event detection to fight against factors such as occlusion and illumination change. In this paper, a new algorithm is proposed. It can locate the abnormal events on one frame, and detect the global abnormal frame. The proposed algorithm employs a sparse measurement matrix designed to represent the movement feature based on optical flow efficiently. Then, the abnormal detection mission is constructed as a one-class classification task via merely learning from the training normal samples. Experiments demonstrate that our algorithm performs well on the benchmark abnormal detection datasets against state-of-the-art methods.

  2. Video Traffic Analysis for Abnormal Event Detection

    DOT National Transportation Integrated Search

    2010-01-01

    We propose the use of video imaging sensors for the detection and classification of abnormal events to be used primarily for mitigation of traffic congestion. Successful detection of such events will allow for new road guidelines; for rapid deploymen...

  3. Video traffic analysis for abnormal event detection.

    DOT National Transportation Integrated Search

    2010-01-01

    We propose the use of video imaging sensors for the detection and classification of abnormal events to : be used primarily for mitigation of traffic congestion. Successful detection of such events will allow for : new road guidelines; for rapid deplo...

  4. 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

  5. Detection of dominant flow and abnormal events in surveillance video

    NASA Astrophysics Data System (ADS)

    Kwak, Sooyeong; Byun, Hyeran

    2011-02-01

    We propose an algorithm for abnormal event detection in surveillance video. The proposed algorithm is based on a semi-unsupervised learning method, a kind of feature-based approach so that it does not detect the moving object individually. The proposed algorithm identifies dominant flow without individual object tracking using a latent Dirichlet allocation model in crowded environments. It can also automatically detect and localize an abnormally moving object in real-life video. The performance tests are taken with several real-life databases, and their results show that the proposed algorithm can efficiently detect abnormally moving objects in real time. The proposed algorithm can be applied to any situation in which abnormal directions or abnormal speeds are detected regardless of direction.

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

    PubMed Central

    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. PMID:22368486

  7. Online least squares one-class support vector machines-based abnormal visual event detection.

    PubMed

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

    2013-12-12

    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.

  8. 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

  9. 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.

  10. Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics

    NASA Astrophysics Data System (ADS)

    Qi, Lin; Yao, Zhenyu; Li, Li; Dong, Junyu

    2007-11-01

    In this paper we present a novel framework for automatic event recognition and abnormal behavior detection with attribute grammar by learning scene semantics. This framework combines learning scene semantics by trajectory analysis and constructing attribute grammar-based event representation. The scene and event information is learned automatically. Abnormal behaviors that disobey scene semantics or event grammars rules are detected. By this method, an approach to understanding video scenes is achieved. Further more, with this prior knowledge, the accuracy of abnormal event detection is increased.

  11. Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor.

    PubMed

    Al-Naji, Ali; Chahl, Javaan

    2018-03-20

    Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation of cardiopulmonary-signal-and-detection-related abnormal cardiopulmonary events (e.g., tachycardia, bradycardia, tachypnea, bradypnea, and central apnoea) in many possible sleeping postures within varying environmental settings including in total darkness and whether the subject is covered by a blanket or not. The proposed system extracts the signal from the abdominal-thoracic region where cardiopulmonary activity is most pronounced, using a real-time image sequence captured by Kinect v2 sensor. The proposed system shows promising results in any sleep posture, regardless of illumination conditions and unclear ROI even in the presence of a blanket, whilst being reliable, safe, and cost-effective.

  12. Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor

    PubMed Central

    Chahl, Javaan

    2018-01-01

    Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation of cardiopulmonary-signal-and-detection-related abnormal cardiopulmonary events (e.g., tachycardia, bradycardia, tachypnea, bradypnea, and central apnoea) in many possible sleeping postures within varying environmental settings including in total darkness and whether the subject is covered by a blanket or not. The proposed system extracts the signal from the abdominal-thoracic region where cardiopulmonary activity is most pronounced, using a real-time image sequence captured by Kinect v2 sensor. The proposed system shows promising results in any sleep posture, regardless of illumination conditions and unclear ROI even in the presence of a blanket, whilst being reliable, safe, and cost-effective. PMID:29558414

  13. The effectiveness of airline pilot training for abnormal events.

    PubMed

    Casner, Stephen M; Geven, Richard W; Williams, Kent T

    2013-06-01

    To evaluate the effectiveness of airline pilot training for abnormal in-flight events. Numerous accident reports describe situations in which pilots responded to abnormal events in ways that were different from what they had practiced many times before. One explanation for these missteps is that training and testing for these skills have become a highly predictable routine for pilots who arrive to the training environment well aware of what to expect. Under these circumstances, pilots get plentiful practice in responding to abnormal events but may get little practice in recognizing them and deciding which responses to offer. We presented 18 airline pilots with three abnormal events that are required during periodic training and testing. Pilots were presented with each event under the familiar circumstances used during training and also under less predictable circumstances as they might occur during flight. When presented in the routine ways seen during training, pilots gave appropriate responses and showed little variability. However, when the abnormal events were presented unexpectedly, pilots' responses were less appropriate and showed great variability from pilot to pilot. The results suggest that the training and testing practices used in airline training may result in rote-memorized skills that are specific to the training situation and that offer modest generalizability to other situations. We recommend a more complete treatment of abnormal events that allows pilots to practice recognizing the event and choosing and recalling the appropriate response. The results will aid the improvement of existing airline training practices.

  14. 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

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

    PubMed

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

    2018-03-01

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

  16. Varenicline and abnormal sleep related events.

    PubMed

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

    2015-05-01

    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. 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. 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. 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. © 2015 Associated Professional Sleep Societies, LLC.

  17. Ergonomics for enhancing detection of machine abnormalities.

    PubMed

    Illankoon, Prasanna; Abeysekera, John; Singh, Sarbjeet

    2016-10-17

    Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined. This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections. Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics. As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

  18. Detection of Structural Abnormalities Using Neural Nets

    NASA Technical Reports Server (NTRS)

    Zak, M.; Maccalla, A.; Daggumati, V.; Gulati, S.; Toomarian, N.

    1996-01-01

    This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

  19. Proportionate Responses to Life Events Influence Clinicians’ Judgments Of Psychological Abnormality

    PubMed Central

    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; APA, 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. We 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. We presented licensed, practicing clinical psychologists (N=77) 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 (APA, 2000). The rationality of these effects and implications for clinical decision science are discussed. PMID:22142425

  20. Object-Oriented Query Language For Events Detection From Images Sequences

    NASA Astrophysics Data System (ADS)

    Ganea, Ion Eugen

    2015-09-01

    In this paper is presented a method to represent the events extracted from images sequences and the query language used for events detection. Using an object oriented model the spatial and temporal relationships between salient objects and also between events are stored and queried. This works aims to unify the storing and querying phases for video events processing. The object oriented language syntax used for events processing allow the instantiation of the indexes classes in order to improve the accuracy of the query results. The experiments were performed on images sequences provided from sport domain and it shows the reliability and the robustness of the proposed language. To extend the language will be added a specific syntax for constructing the templates for abnormal events and for detection of the incidents as the final goal of the research.

  1. Association of electrocardiogram abnormalities and incident heart failure events.

    PubMed

    Gencer, Baris; Butler, Javed; Bauer, Douglas C; Auer, Reto; Kalogeropoulos, Andreas; Marques-Vidal, Pedro; Applegate, William B; Satterfield, Suzanne; Harris, Tamara; Newman, Anne; Vittinghoff, Eric; Rodondi, Nicolas

    2014-06-01

    Unless effective preventive strategies are implemented, aging of the population will result in a significant worsening of the heart failure (HF) epidemic. Few data exist on whether baseline electrocardiographic (ECG) abnormalities can refine risk prediction for HF. We examined a prospective cohort of 2,915 participants aged 70 to 79 years without preexisting HF, enrolled between April 1997 and June 1998 in the Health, Aging, and Body Composition (Health ABC) study. Minnesota Code was used to define major and minor ECG abnormalities at baseline and at year 4 follow-up. Using Cox models, we assessed (1) the association between ECG abnormalities and incident HF and (2) the incremental value of adding ECG to the Health ABC HF Risk Score using the net reclassification index. At baseline, 380 participants (13.0%) had minor, and 620 (21.3%) had major ECG abnormalities. During a median follow-up of 11.4 years, 485 participants (16.6%) developed incident HF. After adjusting for the Health ABC HF Risk Score variables, the hazard ratio (HR) was 1.27 (95% CI 0.96-1.68) for minor and 1.99 (95% CI 1.61-2.44) for major ECG abnormalities. At year 4, 263 participants developed new and 549 had persistent abnormalities; both were associated with increased subsequent HF risk (HR 1.94, 95% CI 1.38-2.72 for new and HR 2.35, 95% CI 1.82-3.02 for persistent ECG abnormalities). Baseline ECG correctly reclassified 10.5% of patients with HF events, 0.8% of those without HF events, and 1.4% of the overall population. The net reclassification index across the Health ABC HF risk categories was 0.11 (95% CI 0.03-0.19). Among older adults, baseline and new ECG abnormalities are independently associated with increased risk of HF. The contribution of ECG screening for targeted prevention of HF should be evaluated in clinical trials. Copyright © 2014 Mosby, Inc. All rights reserved.

  2. Data based abnormality detection

    NASA Astrophysics Data System (ADS)

    Purwar, Yashasvi

    Data based abnormality detection is a growing research field focussed on extracting information from feature rich data. They are considered to be non-intrusive and non-destructive in nature which gives them a clear advantage over conventional methods. In this study, we explore different streams of data based anomalies detection. We propose extension and revisions to existing valve stiction detection algorithm supported with industrial case study. We also explored the area of image analysis and proposed a complete solution for Malaria diagnosis. The proposed method is tested over images provided by pathology laboratory at Alberta Health Service. We also address the robustness and practicality of the solution proposed.

  3. 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…

  4. High lifetime probability of screen-detected cervical abnormalities.

    PubMed

    Pankakoski, Maiju; Heinävaara, Sirpa; Sarkeala, Tytti; Anttila, Ahti

    2017-12-01

    Objective Regular screening and follow-up is an important key to cervical cancer prevention; however, screening inevitably detects mild or borderline abnormalities that would never progress to a more severe stage. We analysed the cumulative probability and recurrence of cervical abnormalities in the Finnish organized screening programme during a 22-year follow-up. Methods Screening histories were collected for 364,487 women born between 1950 and 1965. Data consisted of 1 207,017 routine screens and 88,143 follow-up screens between 1991 and 2012. Probabilities of cervical abnormalities by age were estimated using logistic regression and generalized estimating equations methodology. Results The probability of experiencing any abnormality at least once at ages 30-64 was 34.0% (95% confidence interval [CI]: 33.3-34.6%) . Probability was 5.4% (95% CI: 5.0-5.8%) for results warranting referral and 2.2% (95% CI: 2.0-2.4%) for results with histologically confirmed findings. Previous occurrences were associated with an increased risk of detecting new ones, specifically in older women. Conclusion A considerable proportion of women experience at least one abnormal screening result during their lifetime, and yet very few eventually develop an actual precancerous lesion. Re-evaluation of diagnostic criteria concerning mild abnormalities might improve the balance of harms and benefits of screening. Special monitoring of women with recurrent abnormalities especially at older ages may also be needed.

  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. A robust real-time abnormal region detection framework from capsule endoscopy images

    NASA Astrophysics Data System (ADS)

    Cheng, Yanfen; Liu, Xu; Li, Huiping

    2009-02-01

    In this paper we present a novel method to detect abnormal regions from capsule endoscopy images. Wireless Capsule Endoscopy (WCE) is a recent technology where a capsule with an embedded camera is swallowed by the patient to visualize the gastrointestinal tract. One challenge is one procedure of diagnosis will send out over 50,000 images, making physicians' reviewing process expensive. Physicians' reviewing process involves in identifying images containing abnormal regions (tumor, bleeding, etc) from this large number of image sequence. In this paper we construct a novel framework for robust and real-time abnormal region detection from large amount of capsule endoscopy images. The detected potential abnormal regions can be labeled out automatically to let physicians review further, therefore, reduce the overall reviewing process. In this paper we construct an abnormal region detection framework with the following advantages: 1) Trainable. Users can define and label any type of abnormal region they want to find; The abnormal regions, such as tumor, bleeding, etc., can be pre-defined and labeled using the graphical user interface tool we provided. 2) Efficient. Due to the large number of image data, the detection speed is very important. Our system can detect very efficiently at different scales due to the integral image features we used; 3) Robust. After feature selection we use a cascade of classifiers to further enforce the detection accuracy.

  7. Extraction of ECG signal with adaptive filter for hearth abnormalities detection

    NASA Astrophysics Data System (ADS)

    Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti

    2018-04-01

    This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.

  8. Toward the detection of abnormal chest radiographs the way radiologists do it

    NASA Astrophysics Data System (ADS)

    Alzubaidi, Mohammad; Patel, Ameet; Panchanathan, Sethuraman; Black, John A., Jr.

    2011-03-01

    Computer Aided Detection (CADe) and Computer Aided Diagnosis (CADx) are relatively recent areas of research that attempt to employ feature extraction, pattern recognition, and machine learning algorithms to aid radiologists in detecting and diagnosing abnormalities in medical images. However, these computational methods are based on the assumption that there are distinct classes of abnormalities, and that each class has some distinguishing features that set it apart from other classes. However, abnormalities in chest radiographs tend to be very heterogeneous. The literature suggests that thoracic (chest) radiologists develop their ability to detect abnormalities by developing a sense of what is normal, so that anything that is abnormal attracts their attention. This paper discusses an approach to CADe that is based on a technique called anomaly detection (which aims to detect outliers in data sets) for the purpose of detecting atypical regions in chest radiographs. However, in order to apply anomaly detection to chest radiographs, it is necessary to develop a basis for extracting features from corresponding anatomical locations in different chest radiographs. This paper proposes a method for doing this, and describes how it can be used to support CADe.

  9. Using State Estimation Residuals to Detect Abnormal SCADA Data

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

    Ma, Jian; Chen, Yousu; Huang, Zhenyu

    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 ismore » 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.« less

  10. Detecting Kidney and Urinary Tract Abnormalities Before Birth

    MedlinePlus

    ... Advocacy Donate A to Z Health Guide Detecting Kidney and Urinary Tract Abnormalities Before Birth Print Email ... in many cases. Do these blockages always cause kidney damage? No. Before birth, the mother's placenta performs ...

  11. 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.

  12. 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

  13. Tansig activation function (of MLP network) for cardiac abnormality detection

    NASA Astrophysics Data System (ADS)

    Adnan, Ja'afar; Daud, Nik Ghazali Nik; Ishak, Mohd Taufiq; Rizman, Zairi Ismael; Rahman, Muhammad Izzuddin Abd

    2018-02-01

    Heart abnormality often occurs regardless of gender, age and races. This problem sometimes does not show any symptoms and it can cause a sudden death to the patient. In general, heart abnormality is the irregular electrical activity of the heart. This paper attempts to develop a program that can detect heart abnormality activity through implementation of Multilayer Perceptron (MLP) network. A certain amount of data of the heartbeat signals from the electrocardiogram (ECG) will be used in this project to train the MLP network by using several training algorithms with Tansig activation function.

  14. A novel scheme for abnormal cell detection in Pap smear images

    NASA Astrophysics Data System (ADS)

    Zhao, Tong; Wachman, Elliot S.; Farkas, Daniel L.

    2004-07-01

    Finding malignant cells in Pap smear images is a "needle in a haystack"-type problem, tedious, labor-intensive and error-prone. It is therefore desirable to have an automatic screening tool in order that human experts can concentrate on the evaluation of the more difficult cases. Most research on automatic cervical screening tries to extract morphometric and texture features at the cell level, in accordance with the NIH "The Bethesda System" rules. Due to variances in image quality and features, such as brightness, magnification and focus, morphometric and texture analysis is insufficient to provide robust cervical cancer detection. Using a microscopic spectral imaging system, we have produced a set of multispectral Pap smear images with wavelengths from 400 nm to 690 nm, containing both spectral signatures and spatial attributes. We describe a novel scheme that combines spatial information (including texture and morphometric features) with spectral information to significantly improve abnormal cell detection. Three kinds of wavelet features, orthogonal, bi-orthogonal and non-orthogonal, are carefully chosen to optimize recognition performance. Multispectral feature sets are then extracted in the wavelet domain. Using a Back-Propagation Neural Network classifier that greatly decreases the influence of spurious events, we obtain a classification error rate of 5%. Cell morphometric features, such as area and shape, are then used to eliminate most remaining small artifacts. We report initial results from 149 cells from 40 separate image sets, in which only one abnormal cell was missed (TPR = 97.6%) and one normal cell was falsely classified as cancerous (FPR = 1%).

  15. A reliable sewage quality abnormal event monitoring system.

    PubMed

    Li, Tianling; Winnel, Melissa; Lin, Hao; Panther, Jared; Liu, Chang; O'Halloran, Roger; Wang, Kewen; An, Taicheng; Wong, Po Keung; Zhang, Shanqing; Zhao, Huijun

    2017-09-15

    With closing water loop through purified recycled water, wastewater becomes a part of source water, requiring reliable wastewater quality monitoring system (WQMS) to manage wastewater source and mitigate potential health risks. However, the development of reliable WQMS is fatally constrained by severe contamination and biofouling of sensors due to the hostile analytical environment of wastewaters, especially raw sewages, that challenges the limit of existing sensing technologies. In this work, we report a technological solution to enable the development of WQMS for real-time abnormal event detection with high reliability and practicality. A vectored high flow hydrodynamic self-cleaning approach and a dual-sensor self-diagnostic concept are adopted for WQMS to effectively encounter vital sensor failing issues caused by contamination and biofouling and ensure the integrity of sensing data. The performance of the WQMS has been evaluated over a 3-year trial period at different sewage catchment sites across three Australian states. It has demonstrated that the developed WQMS is capable of continuously operating in raw sewage for a prolonged period up to 24 months without maintenance and failure, signifying the high reliability and practicality. The demonstrated WQMS capability to reliably acquire real-time wastewater quality information leaps forward the development of effective wastewater source management system. The reported self-cleaning and self-diagnostic concepts should be applicable to other online water quality monitoring systems, opening a new way to encounter the common reliability and stability issues caused by sensor contamination and biofouling. Copyright © 2017 Elsevier Ltd. All rights reserved.

  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. Modeling Concept Dependencies for Event Detection

    DTIC Science & Technology

    2014-04-04

    Gaussian Mixture Model (GMM). Jiang et al . [8] provide a summary of experiments for TRECVID MED 2010 . They employ low-level features such as SIFT and...event detection literature. Ballan et al . [2] present a method to introduce temporal information for video event detection with a BoW (bag-of-words...approach. Zhou et al . [24] study video event detection by encoding a video with a set of bag of SIFT feature vectors and describe the distribution with a

  18. Detection of chromosomal abnormalities, congenital abnormalities and transfusion syndrome in twins.

    PubMed

    Sperling, L; Kiil, C; Larsen, L U; Brocks, V; Wojdemann, K R; Qvist, I; Schwartz, M; Jørgensen, C; Espersen, G; Skajaa, K; Bang, J; Tabor, A

    2007-05-01

    To evaluate the outcome of screening for structural malformations in twins and the outcome of screening for twin-twin transfusion syndrome (TTTS) among monochorionic twins through a number of ultrasound scans from 12 weeks' gestation. Enrolled into this prospective multicenter observational study were women with twin pregnancies diagnosed before 14 + 6 gestational weeks. The monochorionic pregnancies were scanned every second week until 23 weeks in order to rule out early TTTS. All pregnancies had an anomaly scan in week 19 and fetal echocardiography in week 21 that was performed by specialists in fetal echocardiography. Zygosity was determined by DNA analysis in all twin pairs with the same sex. Among the 495 pregnancies the prenatal detection rate for severe structural abnormalities including chromosomal aneuploidies was 83% by the combination of a first-trimester nuchal translucency scan and the anomaly scan in week 19. The incidence of severe structural abnormalities was 2.6% and two-thirds of these anomalies were cardiac. There was no significant difference between the incidence in monozygotic and dizygotic twins, nor between twins conceived naturally or those conceived by assisted reproduction. The incidence of TTTS was 23% from 12 weeks until delivery, and all those monochorionic twin pregnancies that miscarried had signs of TTTS. Twin pregnancies have an increased risk of congenital malformations and one out of four monochorionic pregnancies develops TTTS. Ultrasound screening to assess chorionicity and follow-up of monochorionic pregnancies to detect signs of TTTS, as well as malformation screening, are therefore essential in the antenatal care of twin pregnancies. Copyright (c) 2007 ISUOG.

  19. 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

  20. The Detection Method of Fire Abnormal Based on Directional Drilling in Complex Conditions of Mine

    NASA Astrophysics Data System (ADS)

    Huijun, Duan; Shijun, Hao; Jie, Feng

    2018-06-01

    In the light of more and more urgent hidden fire abnormal detection problem in complex conditions of mine, a method which is used directional drilling technology is put forward. The method can avoid the obstacles in mine, and complete the fire abnormal detection. This paper based on analyzing the trajectory control of directional drilling, measurement while drilling and the characteristic of open branch process, the project of the directional drilling is formulated combination with a complex condition mine, and the detection of fire abnormal is implemented. This method can provide technical support for fire prevention, which also can provide a new way for fire anomaly detection in the similar mine.

  1. 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

  2. A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

    PubMed

    Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

    2017-01-01

    Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

  3. Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions

    NASA Astrophysics Data System (ADS)

    El Houda Thabet, Rihab; Combastel, Christophe; Raïssi, Tarek; Zolghadri, Ali

    2015-09-01

    The paper develops a set membership detection methodology which is applied to the detection of abnormal positions of aircraft control surfaces. Robust and early detection of such abnormal positions is an important issue for early system reconfiguration and overall optimisation of aircraft design. In order to improve fault sensitivity while ensuring a high level of robustness, the method combines a data-driven characterisation of noise and a model-driven approach based on interval prediction. The efficiency of the proposed methodology is illustrated through simulation results obtained based on data recorded in several flight scenarios of a highly representative aircraft benchmark.

  4. 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.

  5. Joint Attributes and Event Analysis for Multimedia Event Detection.

    PubMed

    Ma, Zhigang; Chang, Xiaojun; Xu, Zhongwen; Sebe, Nicu; Hauptmann, Alexander G

    2017-06-15

    Semantic attributes have been increasingly used the past few years for multimedia event detection (MED) with promising results. The motivation is that multimedia events generally consist of lower level components such as objects, scenes, and actions. By characterizing multimedia event videos with semantic attributes, one could exploit more informative cues for improved detection results. Much existing work obtains semantic attributes from images, which may be suboptimal for video analysis since these image-inferred attributes do not carry dynamic information that is essential for videos. To address this issue, we propose to learn semantic attributes from external videos using their semantic labels. We name them video attributes in this paper. In contrast with multimedia event videos, these external videos depict lower level contents such as objects, scenes, and actions. To harness video attributes, we propose an algorithm established on a correlation vector that correlates them to a target event. Consequently, we could incorporate video attributes latently as extra information into the event detector learnt from multimedia event videos in a joint framework. To validate our method, we perform experiments on the real-world large-scale TRECVID MED 2013 and 2014 data sets and compare our method with several state-of-the-art algorithms. The experiments show that our method is advantageous for MED.

  6. Hidden chromosome 8 abnormalities detected by FISH in adult primary myelodysplastic syndromes.

    PubMed

    Panani, Anna D; Pappa, Vasiliki

    2005-01-01

    Acquired clonal chromosomal abnormalities are found in about 30-50% of primary myelodysplastic syndromes (MDS). These abnormalities are predominantly characterized by total/partial chromosomal losses or gains and rarely by balanced structural aberrations. Trisomy 8 represents the most common chromosomal gain. In the present study, the numerical aberration of chromosome 8 was evaluated by the fluorescence in situ hybridization (FISH) technique in MDS, and the results compared with those of conventional cytogenetics. Thirty adult patients with primary MDS, 17 with a normal karyotype and 13 with several chromosomal abnormalities except chromosome 8, were included in this study. On comparing the results of FISH and conventional cytogenetics, a superiority of FISH over the karyotype was detected in 3 cases. In one of them, further cytogenetic analysis confirmed the FISH results. Nevertheless, the FISH technique has limitations, detecting only abnormalities specific for the target FISH probe used In clinical practice, conventional cytogenetics continues to be the basic technique for MDS patient evaluation. However, a large number of metaphases, even those of poor quality, must be analyzed in each case. The FISH technique could be considered to be complementary to achieve a more accurate analysis.

  7. Event detection in an assisted living environment.

    PubMed

    Stroiescu, Florin; Daly, Kieran; Kuris, Benjamin

    2011-01-01

    This paper presents the design of a wireless event detection and in building location awareness system. The systems architecture is based on using a body worn sensor to detect events such as falls where they occur in an assisted living environment. This process involves developing event detection algorithms and transmitting such events wirelessly to an in house network based on the 802.15.4 protocol. The network would then generate alerts both in the assisted living facility and remotely to an offsite monitoring facility. The focus of this paper is on the design of the system architecture and the compliance challenges in applying this technology.

  8. Real-Time Event Detection for Monitoring Natural and Source ...

    EPA Pesticide Factsheets

    The use of event detection systems in finished drinking water systems is increasing in order to monitor water quality in both operational and security contexts. Recent incidents involving harmful algal blooms and chemical spills into watersheds have increased interest in monitoring source water quality prior to treatment. This work highlights the use of the CANARY event detection software in detecting suspected illicit events in an actively monitored watershed in South Carolina. CANARY is an open source event detection software that was developed by USEPA and Sandia National Laboratories. The software works with any type of sensor, utilizes multiple detection algorithms and approaches, and can incorporate operational information as needed. Monitoring has been underway for several years to detect events related to intentional or unintentional dumping of materials into the monitored watershed. This work evaluates the feasibility of using CANARY to enhance the detection of events in this watershed. This presentation will describe the real-time monitoring approach used in this watershed, the selection of CANARY configuration parameters that optimize detection for this watershed and monitoring application, and the performance of CANARY during the time frame analyzed. Further, this work will highlight how rainfall events impacted analysis, and the innovative application of CANARY taken in order to effectively detect the suspected illicit events. This presentation d

  9. Supervised Time Series Event Detector for Building Data

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

    2016-04-13

    A machine learning based approach is developed to detect events that have rarely been seen in the historical data. The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.

  10. Cartan invariants and event horizon detection

    NASA Astrophysics Data System (ADS)

    Brooks, D.; Chavy-Waddy, P. C.; Coley, A. A.; Forget, A.; Gregoris, D.; MacCallum, M. A. H.; McNutt, D. D.

    2018-04-01

    We show that it is possible to locate the event horizon of a black hole (in arbitrary dimensions) by the zeros of certain Cartan invariants. This approach accounts for the recent results on the detection of stationary horizons using scalar polynomial curvature invariants, and improves upon them since the proposed method is computationally less expensive. As an application, we produce Cartan invariants that locate the event horizons for various exact four-dimensional and five-dimensional stationary, asymptotically flat (or (anti) de Sitter), black hole solutions and compare the Cartan invariants with the corresponding scalar curvature invariants that detect the event horizon.

  11. Multi-Station Broad Regional Event Detection Using Waveform Correlation

    NASA Astrophysics Data System (ADS)

    Slinkard, M.; Stephen, H.; Young, C. J.; Eckert, R.; Schaff, D. P.; Richards, P. G.

    2013-12-01

    Previous waveform correlation studies have established the occurrence of repeating seismic events in various regions, and the utility of waveform-correlation event-detection on broad regional or even global scales to find events currently not included in traditionally-prepared bulletins. The computational burden, however, is high, limiting previous experiments to relatively modest template libraries and/or processing time periods. We have developed a distributed computing waveform correlation event detection utility that allows us to process years of continuous waveform data with template libraries numbering in the thousands. We have used this system to process several years of waveform data from IRIS stations in East Asia, using libraries of template events taken from global and regional bulletins. Detections at a given station are confirmed by 1) comparison with independent bulletins of seismicity, and 2) consistent detections at other stations. We find that many of the detected events are not in traditional catalogs, hence the multi-station comparison is essential. In addition to detecting the similar events, we also estimate magnitudes very precisely based on comparison with the template events (when magnitudes are available). We have investigated magnitude variation within detected families of similar events, false alarm rates, and the temporal and spatial reach of templates.

  12. 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.

  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. 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

  15. Self-similarity Clustering Event Detection Based on Triggers Guidance

    NASA Astrophysics Data System (ADS)

    Zhang, Xianfei; Li, Bicheng; Tian, Yuxuan

    Traditional method of Event Detection and Characterization (EDC) regards event detection task as classification problem. It makes words as samples to train classifier, which can lead to positive and negative samples of classifier imbalance. Meanwhile, there is data sparseness problem of this method when the corpus is small. This paper doesn't classify event using word as samples, but cluster event in judging event types. It adopts self-similarity to convergence the value of K in K-means algorithm by the guidance of event triggers, and optimizes clustering algorithm. Then, combining with named entity and its comparative position information, the new method further make sure the pinpoint type of event. The new method avoids depending on template of event in tradition methods, and its result of event detection can well be used in automatic text summarization, text retrieval, and topic detection and tracking.

  16. 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.

  17. Subsurface event detection and classification using Wireless Signal Networks.

    PubMed

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

    2012-11-05

    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.

  18. Improved detection rate of structural abnormalities in the first trimester using an extended examination protocol.

    PubMed

    Iliescu, D; Tudorache, S; Comanescu, A; Antsaklis, P; Cotarcea, S; Novac, L; Cernea, N; Antsaklis, A

    2013-09-01

    To assess the potential of first-trimester sonography in the detection of fetal abnormalities using an extended protocol that is achievable with reasonable resources of time, personnel and ultrasound equipment. This was a prospective two-center 2-year study of 5472 consecutive unselected pregnant women examined at 12 to 13 + 6 gestational weeks. Women were examined using an extended morphogenetic ultrasound protocol that, in addition to the basic evaluation, involved a color Doppler cardiac sweep and identification of early contingent markers for major abnormalities. The prevalence of lethal and severe malformations was 1.39%. The first-trimester scan identified 40.6% of the cases detected overall and 76.3% of major structural defects. The first-trimester detection rate (DR) for major congenital heart disease (either isolated or associated with extracardiac abnormalities) was 90% and that for major central nervous system anomalies was 69.5%. In fetuses with increased nuchal translucency (NT), the first-trimester DR for major anomalies was 96%, and in fetuses with normal NT it was 66.7%. Most (67.1%) cases with major abnormalities presented with normal NT. A detailed first-trimester anomaly scan using an extended protocol is an efficient screening method to detect major fetal structural abnormalities in low-risk pregnancies. It is feasible at 12 to 13 + 6 weeks with ultrasound equipment and personnel already used for routine first-trimester screening. Rate of detection of severe malformations is greater in early- than in mid-pregnancy and on postnatal evaluation. Early heart investigation could be improved by an extended protocol involving use of color Doppler. Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.

  19. 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.

  20. 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.

  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. Extracting foreground ensemble features to detect abnormal crowd behavior in intelligent video-surveillance systems

    NASA Astrophysics Data System (ADS)

    Chan, Yi-Tung; Wang, Shuenn-Jyi; Tsai, Chung-Hsien

    2017-09-01

    Public safety is a matter of national security and people's livelihoods. In recent years, intelligent video-surveillance systems have become important active-protection systems. A surveillance system that provides early detection and threat assessment could protect people from crowd-related disasters and ensure public safety. Image processing is commonly used to extract features, e.g., people, from a surveillance video. However, little research has been conducted on the relationship between foreground detection and feature extraction. Most current video-surveillance research has been developed for restricted environments, in which the extracted features are limited by having information from a single foreground; they do not effectively represent the diversity of crowd behavior. This paper presents a general framework based on extracting ensemble features from the foreground of a surveillance video to analyze a crowd. The proposed method can flexibly integrate different foreground-detection technologies to adapt to various monitored environments. Furthermore, the extractable representative features depend on the heterogeneous foreground data. Finally, a classification algorithm is applied to these features to automatically model crowd behavior and distinguish an abnormal event from normal patterns. The experimental results demonstrate that the proposed method's performance is both comparable to that of state-of-the-art methods and satisfies the requirements of real-time applications.

  3. 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

  4. 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.

  5. 76 FR 22925 - Assumption Buster Workshop: Abnormal Behavior Detection Finds Malicious Actors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-25

    ... Technology Research and Development (NITRD) Program, National Science Foundation. ACTION: Call for... NATIONAL SCIENCE FOUNDATION Assumption Buster Workshop: Abnormal Behavior Detection Finds...: The NCO, on behalf of the Special Cyber Operations Research and Engineering (SCORE) Committee, an...

  6. Abnormal Circulation Changes in the Winter Stratosphere, Detected Through Variations of D Region Ionospheric Absorption

    NASA Technical Reports Server (NTRS)

    Delamorena, B. A.

    1984-01-01

    A method to detect stratospheric warmings using ionospheric absorption records obtained by an Absorption Meter (method A3) is introduced. The activity of the stratospheric circulation and the D region ionospheric absorption as well as other atmospheric parameters during the winter anomaly experience an abnormal variation. A simultaneity was found in the beginning of abnormal variation in the mentioned parameters, using the absorption records for detecting the initiation of the stratospheric warming. Results of this scientific experience of forecasting in the El Arenosillo Range, are presented.

  7. 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.

  8. Sonographic detection of basal ganglia abnormalities in spasmodic dysphonia.

    PubMed

    Walter, U; Blitzer, A; Benecke, R; Grossmann, A; Dressler, D

    2014-02-01

    Abnormalities of the lenticular nucleus (LN) on transcranial sonography (TCS) are a characteristic finding in idiopathic segmental and generalized dystonia. Our intention was to study whether TCS detects basal ganglia abnormalities also in spasmodic dysphonia, an extremely focal form of dystonia. Transcranial sonography of basal ganglia, substantia nigra and ventricles was performed in 14 patients with spasmodic dysphonia (10 women, four men; disease duration 16.5 ± 6.1 years) and 14 age- and sex-matched healthy controls in an investigator-blinded setting. Lenticular nucleus hyperechogenicity was found in 12 spasmodic dysphonia patients but only in one healthy individual (Fisher's exact test, P < 0.001) whilst other TCS findings did not differ. The area of LN hyperechogenic lesions quantified on digitized image analysis correlated with spasmodic dysphonia severity (Spearman test, r = 0.82, P < 0.001). Our findings link the underlying pathology of spasmodic dysphonia to that of more widespread forms of dystonia. © 2013 The Author(s) European Journal of Neurology © 2013 EFNS.

  9. 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.

  10. Improving Abnormality Detection on Chest Radiography Using Game-Like Reinforcement Mechanics.

    PubMed

    Chen, Po-Hao; Roth, Howard; Galperin-Aizenberg, Maya; Ruutiainen, Alexander T; Gefter, Warren; Cook, Tessa S

    2017-11-01

    Despite their increasing prevalence, online textbooks, question banks, and digital references focus primarily on explicit knowledge. Implicit skills such as abnormality detection require repeated practice on clinical service and have few digital substitutes. Using mechanics traditionally deployed in video games such as clearly defined goals, rapid-fire levels, and narrow time constraints may be an effective way to teach implicit skills. We created a freely available, online module to evaluate the ability of individuals to differentiate between normal and abnormal chest radiographs by implementing mechanics, including instantaneous feedback, rapid-fire cases, and 15-second timers. Volunteer subjects completed the modules and were separated based on formal experience with chest radiography. Performance between training and testing sets were measured for each group, and a survey was administered after each session. The module contained 74 cases and took approximately 20 minutes to complete. Thirty-two cases were normal radiographs and 56 cases were abnormal. Of the 60 volunteers recruited, 25 were "never trained" and 35 were "previously trained." "Never trained" users scored 21.9 out of 37 during training and 24.0 out of 37 during testing (59.1% vs 64.9%, P value <.001). "Previously trained" users scored 28.0 out of 37 during training and 28.3 out of 37 during testing phases (75.6% vs 76.4%, P value = .56). Survey results showed that 87% of all subjects agreed the module is an efficient way of learning, and 83% agreed the rapid-fire module is valuable for medical students. A gamified online module may improve the abnormality detection rates of novice interpreters of chest radiography, although experienced interpreters are less likely to derive similar benefits. Users reviewed the educational module favorably. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  11. 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.

  12. 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.

  13. Passive (Micro-) Seismic Event Detection by Identifying Embedded "Event" Anomalies Within Statistically Describable Background Noise

    NASA Astrophysics Data System (ADS)

    Baziw, Erick; Verbeek, Gerald

    2012-12-01

    Among engineers there is considerable interest in the real-time identification of "events" within time series data with a low signal to noise ratio. This is especially true for acoustic emission analysis, which is utilized to assess the integrity and safety of many structures and is also applied in the field of passive seismic monitoring (PSM). Here an array of seismic receivers are used to acquire acoustic signals to monitor locations where seismic activity is expected: underground excavations, deep open pits and quarries, reservoirs into which fluids are injected or from which fluids are produced, permeable subsurface formations, or sites of large underground explosions. The most important element of PSM is event detection: the monitoring of seismic acoustic emissions is a continuous, real-time process which typically runs 24 h a day, 7 days a week, and therefore a PSM system with poor event detection can easily acquire terabytes of useless data as it does not identify crucial acoustic events. This paper outlines a new algorithm developed for this application, the so-called SEED™ (Signal Enhancement and Event Detection) algorithm. The SEED™ algorithm uses real-time Bayesian recursive estimation digital filtering techniques for PSM signal enhancement and event detection.

  14. Efficacy of DSP30-IL2/TPA for detection of cytogenetic abnormalities in chronic lymphocytic leukaemia/small lymphocytic lymphoma.

    PubMed

    Holmes, P J; Peiper, S C; Uppal, G K; Gong, J Z; Wang, Z-X; Bajaj, R

    2016-10-01

    Chronic lymphocytic leukaemia (CLL) is the most prevalent leukaemia in the Western Hemisphere. Cytogenetic abnormalities in CLL are used for diagnosis, prognosis and treatment. However, detecting these is difficult because mature B cells do not readily divide in culture. Here, we present data on two mitogen cocktails: CpG-oligonucleotide DSP30/Interleukin-2 (IL-2) and DSP30/IL-2 in combination with 12-O-tetradecanoylphorbol-13-acetate (TPA). We analysed 165 cases of CLL with FISH and cytogenetics from January 2011 to June 2013. In 2011, three cultures were set-up: unstimulated, DSP30/IL-2-stimulated and TPA-stimulated. In 2012-2013, two cultures were set-up: unstimulated and stimulated with TPA/DSP30/IL-2. In 2011, FISH had a detection rate of 91% and cytogenetics using DSP30/IL2 had a detection rate of 91% (n = 22). In 2012-2013, FISH had a detection rate of 79% and cytogenetics using TPA/DSP30/IL-2 had a detection rate of 98% (n = 40). The percentage of cases with normal FISH but abnormal cytogenetics increased from 9% in 2011 to 21% in 2012-2013. The TPA/DSP30/IL-2 cultures in 2012-2013 detected more novel abnormalities (n = 5) as compared to DSP30/IL-2 alone (n = 3). TPA/DSP30/IL2 was as good as or better than DSP30/IL2 alone. TPA/DSP30/IL-2 offers a high detection rate for CLL abnormalities with a single stimulated culture and may increase detection of clinically significant abnormalities. © 2016 John Wiley & Sons Ltd.

  15. Semantic Context Detection Using Audio Event Fusion

    NASA Astrophysics Data System (ADS)

    Chu, Wei-Ta; Cheng, Wen-Huang; Wu, Ja-Ling

    2006-12-01

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

  16. Fluorescence in situ hybridization of TP53 for the detection of chromosome 17 abnormalities in myelodysplastic syndromes.

    PubMed

    Sánchez-Castro, Judit; Marco-Betés, Víctor; Gómez-Arbonés, Xavier; García-Cerecedo, Tomás; López, Ricard; Talavera, Elisabeth; Fernández-Ruiz, Sara; Ademà, Vera; Marugan, Isabel; Luño, Elisa; Sanzo, Carmen; Vallespí, Teresa; Arenillas, Leonor; Marco Buades, Josefa; Batlle, Ana; Buño, Ismael; Martín Ramos, María Luisa; Blázquez Rios, Beatriz; Collado Nieto, Rosa; Vargas, Ma Teresa; González Martínez, Teresa; Sanz, Guillermo; Solé, Francesc

    2015-01-01

    Conventional G-banding cytogenetics (CC) detects chromosome 17 (chr17) abnormalities in 2% of patients with de novo myelodysplastic syndromes (MDS). We used CC and fluorescence in situ hybridization (FISH) (LSI p53/17p13.1) to assess deletion of 17p in 531 patients with de novo MDS from the Spanish Group of Hematological Cytogenetics. FISH detected - 17 or 17p abnormalities in 13 cases (2.6%) in whom no 17p abnormalities were revealed by CC: 0.9% of patients with a normal karyotype, 0% in non-informative cytogenetics, 50% of patients with a chr17 abnormality without loss of 17p and 4.7% of cases with an abnormal karyotype not involving chr17. Our results suggest that applying FISH of 17p13 to identify the number of copies of the TP53 gene could be beneficial in patients with a complex karyotype. We recommend using FISH of 17p13 in young patients with a normal karyotype or non-informative cytogenetics, and always in isolated del(17p).

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

    PubMed Central

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

    2014-01-01

    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. PMID:25132723

  18. A simple infrared-augmented digital photography technique for detection of pupillary abnormalities.

    PubMed

    Shazly, Tarek A; Bonhomme, G R

    2015-03-01

    The purpose of the study was to describe a simple infrared photography technique to aid in the diagnosis and documentation of pupillary abnormalities. An unmodified 12-megapixel "point and shoot" digital camera was used to obtain binocular still photos and videos under different light conditions with near-infrared illuminating frames. The near-infrared light of 850 nm allows the capture of clear pupil images in both dim and bright light conditions. It also allows easy visualization of the pupil despite pigmented irides by augmenting the contrast between the iris and the pupil. The photos and videos obtained illustrated a variety of pupillary abnormalities using the aforementioned technique. This infrared-augmented photography technique supplements medical education, and aids in the more rapid detection, diagnosis, and documentation of a wide spectrum of pupillary abnormalities. Its portability and ease of use with minimal training complements the education of trainees and facilitates the establishment of difficult diagnoses.

  19. Traditional karyotyping vs copy number variation sequencing for detection of chromosomal abnormalities associated with spontaneous miscarriage.

    PubMed

    Liu, S; Song, L; Cram, D S; Xiong, L; Wang, K; Wu, R; Liu, J; Deng, K; Jia, B; Zhong, M; Yang, F

    2015-10-01

    To compare the performance of traditional G-banding karyotyping with that of copy number variation sequencing (CNV-Seq) for detection of chromosomal abnormalities associated with miscarriage. Products of conception (POC) were collected from spontaneous miscarriages. Chromosomal abnormalities were detected using high-resolution G-banding karyotyping and CNV sequencing. Quantitative fluorescent polymerase chain reaction analysis of maternal and POC DNA for short tandem repeat (STR) markers was used to both monitor maternal cell contamination and confirm the chromosomal status and sex of the miscarriage tissue. A total of 64 samples of POC, comprising 16 with an abnormal and 48 with a normal karyotype, were selected and coded for analysis by CNV-Seq. CNV-Seq results were concordant for 14 (87.5%) of the 16 gross chromosomal abnormalities identified by karyotyping, including 11 autosomal trisomies and three sex chromosomal aneuploidies (45,X). Of the two discordant results, a 69,XXX polyploidy was missed by CNV-Seq, although supporting STR marker analysis confirmed the triploidy. In contrast, CNV-Seq identified a sample with 45,X karyotype as a 45,X/46,XY mosaic. In the remaining 48 samples of POC with a normal karyotype, CNV-Seq detected a 2.58-Mb 22q deletion associated with DiGeorge syndrome and nine different smaller CNVs of no apparent clinical significance. CNV-Seq used in parallel with STR profiling is a reliable and accurate alternative to karyotyping for identifying chromosome copy number abnormalities associated with spontaneous miscarriage. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

  20. 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

  1. Digital stethoscopes compared to standard auscultation for detecting abnormal paediatric breath sounds.

    PubMed

    Kevat, Ajay C; Kalirajah, Anaath; Roseby, Robert

    2017-07-01

    Our study aimed to objectively describe the audiological characteristics of wheeze and crackles in children by using digital stethoscope (DS) auscultation, as well as assess concordance between standard auscultation and two different DS devices in their ability to detect pathological breath sounds. Twenty children were auscultated by a paediatric consultant doctor and digitally recorded using the Littman™ 3200 Digital Electronic Stethoscope and a Clinicloud™ DS with smart device. Using spectrographic analysis, we found those with clinically described wheeze had prominent periodic waveform segments spanning expiration for a period of 0.03-1.2 s at frequencies of 100-1050 Hz, and occasionally spanning shorter inspiratory segments; paediatric crackles were brief discontinuous sounds with a distinguishing waveform. There was moderate concordance with respect to wheeze detection between digital and standard binaural stethoscopes, and 100% concordance for crackle detection. Importantly, DS devices were more sensitive than clinician auscultation in detecting wheeze in our study. Objective definition of audio characteristics of abnormal paediatric breath sounds was achieved using DS technology. We demonstrated superiority of our DS method compared to traditional auscultation for detection of wheeze. What is Known: • The audiological characteristics of abnormal breath sounds have been well-described in adult populations but not in children. • Inter-observer agreement for detection of pathological breath sounds using standard auscultation has been shown to be poor, but the clinical value of now easily available digital stethoscopes has not been sufficiently examined. What is New: • Digital stethoscopes can objectively define the nature of pathological breath sounds such as wheeze and crackles in children. • Paediatric wheeze was better detected by digital stethoscopes than by standard auscultation performed by an expert paediatric clinician.

  2. Exploiting semantics for sensor re-calibration in event detection systems

    NASA Astrophysics Data System (ADS)

    Vaisenberg, Ronen; Ji, Shengyue; Hore, Bijit; Mehrotra, Sharad; Venkatasubramanian, Nalini

    2008-01-01

    Event detection from a video stream is becoming an important and challenging task in surveillance and sentient systems. While computer vision has been extensively studied to solve different kinds of detection problems over time, it is still a hard problem and even in a controlled environment only simple events can be detected with a high degree of accuracy. Instead of struggling to improve event detection using image processing only, we bring in semantics to direct traditional image processing. Semantics are the underlying facts that hide beneath video frames, which can not be "seen" directly by image processing. In this work we demonstrate that time sequence semantics can be exploited to guide unsupervised re-calibration of the event detection system. We present an instantiation of our ideas by using an appliance as an example--Coffee Pot level detection based on video data--to show that semantics can guide the re-calibration of the detection model. This work exploits time sequence semantics to detect when re-calibration is required to automatically relearn a new detection model for the newly evolved system state and to resume monitoring with a higher rate of accuracy.

  3. Longitudinal Analysis of Carcinogenic Human Papillomavirus Infection and Associated Cytologic Abnormalities in the Guanacaste Natural History Study: Looking Ahead to Cotesting

    PubMed Central

    Rodriguez, Ana C.; Burk, Robert D.; Hildesheim, Allan; Herrero, Rolando; Wacholder, Sholom; Hutchinson, Martha; Schiffman, Mark

    2012-01-01

    Background. Few studies have addressed the timing of cervical cytologic abnormalities and human papillomavirus (HPV) positivity during the course of an infection. It remains largely unknown how infections detected by HPV and cytology wax and wane relative to each other. The aim of this analysis was to assess the longitudinal relationship of abnormal cytology and HPV positivity in a 7-year prospective study of 2500 women in Guanacaste, Costa Rica. Methods. At each semiannual or annual visit, cervical specimens were screened using liquid-based cytology and tested for >40 HPV types with use of MY09/MY11 L1 degenerate primer polymerase chain reaction–based methods. On the basis of previous work, we separated prevalent and newly detected infections in younger and older women. Results. Among newly detected HPV- and/or cytology-positive events, HPV and cytology appeared together ∼60% of the time; when discordant, HPV tended to appear before cytology in younger and older women. Combining newly and prevalently detected events, HPV and cytology disappeared at the same time >70% of the time. When discordant, HPV tended to disappear after cytology in younger and older women. Conclusions. Detection of HPV DNA and associated cytological abnormalities tend to come and leave together; however, when discordant, detection of HPV DNA tends to precede and/or last longer than associated cytologic abnormalities. PMID:22147792

  4. An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

    NASA Astrophysics Data System (ADS)

    Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

    2017-07-01

    Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

  5. Piecing together the puzzle: Improving event content coverage for real-time sub-event detection using adaptive microblog crawling

    PubMed Central

    Tokarchuk, Laurissa; Wang, Xinyue; Poslad, Stefan

    2017-01-01

    In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM) framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The novel combination of

  6. Piecing together the puzzle: Improving event content coverage for real-time sub-event detection using adaptive microblog crawling.

    PubMed

    Tokarchuk, Laurissa; Wang, Xinyue; Poslad, Stefan

    2017-01-01

    In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM) framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The novel combination of

  7. [Combined G-banded karyotyping and multiplex ligation-dependent probe amplification for the detection of chromosomal abnormalities in fetuses with congenital heart defects].

    PubMed

    Liu, Yang; Xie, Jiansheng; Geng, Qian; Xu, Zhiyong; Wu, Weiqin; Luo, Fuwei; Li, Suli; Wang, Qin; Chen, Wubin; Tan, Hongxi; Zhang, Hu

    2017-02-10

    To assess the value of G-banded karyotyping in combination with multiplex ligation-dependent probe amplification (MLPA) as a tool for the detection of chromosomal abnormalities in fetuses with congenital heart defects. The combined method was used to analyze 104 fetuses with heart malformations identified by ultrasonography. Abnormal findings were confirmed with chromosomal microarray analysis (CMA). Nineteen (18%) fetuses were found to harbor chromosomal aberrations by G-banded karyotyping and MLPA. For 93 cases, CMA has detected abnormalities in 14 cases including 10 pathogenic copy number variations (CNVs) and 4 CNVs of uncertain significance (VOUS). MLPA was able to detect all of the pathogenic CNVs and 1 VOUS CNV. Combined use of G-banded karyotyping and MLPA is a rapid, low-cost and effective method to detect chromosomal abnormalities in fetuses with various heart malformations.

  8. Event-Triggered Fault Detection of Nonlinear Networked Systems.

    PubMed

    Li, Hongyi; Chen, Ziran; Wu, Ligang; Lam, Hak-Keung; Du, Haiping

    2017-04-01

    This paper investigates the problem of fault detection for nonlinear discrete-time networked systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is designed to generate a residual signal and detect faults in the system. A novel polynomial event-triggered scheme is proposed to determine the transmission of the signal. A fault detection filter is designed to guarantee that the residual system is asymptotically stable and satisfies the desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions are represented in terms of sum of squares (SOSs) and can be solved by SOS tools in MATLAB environment. A numerical example is provided to demonstrate the effectiveness of the proposed results.

  9. An efficient method for automatic morphological abnormality detection from human sperm images.

    PubMed

    Ghasemian, Fatemeh; Mirroshandel, Seyed Abolghasem; Monji-Azad, Sara; Azarnia, Mahnaz; Zahiri, Ziba

    2015-12-01

    Sperm morphology analysis (SMA) is an important factor in the diagnosis of human male infertility. This study presents an automatic algorithm for sperm morphology analysis (to detect malformation) using images of human sperm cells. The SMA method was used to detect and analyze different parts of the human sperm. First of all, SMA removes the image noises and enhances the contrast of the image to a great extent. Then it recognizes the different parts of sperm (e.g., head, tail) and analyzes the size and shape of each part. Finally, the algorithm classifies each sperm as normal or abnormal. Malformations in the head, midpiece, and tail of a sperm, can be detected by the SMA method. In contrast to other similar methods, the SMA method can work with low resolution and non-stained images. Furthermore, an image collection created for the SMA, has also been described in this study. This benchmark consists of 1457 sperm images from 235 patients, and is known as human sperm morphology analysis dataset (HSMA-DS). The proposed algorithm was tested on HSMA-DS. The experimental results show the high ability of SMA to detect morphological deformities from sperm images. In this study, the SMA algorithm produced above 90% accuracy in sperm abnormality detection task. Another advantage of the proposed method is its low computation time (that is, less than 9s), as such, the expert can quickly decide to choose the analyzed sperm or select another one. Automatic and fast analysis of human sperm morphology can be useful during intracytoplasmic sperm injection for helping embryologists to select the best sperm in real time. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  10. 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.

  11. Pediatric Patients Discharged from the Emergency Department with Abnormal Vital Signs.

    PubMed

    Winter, Josephine; Waxman, Michael J; Waterman, George; Ata, Ashar; Frisch, Adam; Collins, Kevin P; King, Christopher

    2017-08-01

    Children often present to the emergency department (ED) with minor conditions such as fever and have persistently abnormal vital signs. We hypothesized that a significant portion of children discharged from the ED would have abnormal vital signs and that those discharged with abnormal vital signs would experience very few adverse events. We performed a retrospective chart review encompassing a 44-month period of all pediatric patients (aged two months to 17 years) who were discharged from the ED with an abnormal pulse rate, respiratory rate, temperature, or oxygen saturation. We used a local quality assurance database to identify pre-defined adverse events after discharge in this population. Our primary aim was to determine the proportion of children discharged with abnormal vital signs and the frequency and nature of adverse events. Additionally, we performed a sub-analysis comparing the rate of adverse events in children discharged with normal vs. abnormal vital signs, as well as a standardized review of the nature of each adverse event. Of 33,185 children discharged during the study period, 5,540 (17%) of these patients had at least one abnormal vital sign. There were 24/5,540 (0.43%) adverse events in the children with at least one abnormal vital sign vs. 47/27,645 (0.17%) adverse events in the children with normal vital signs [relative risk = 2.5 (95% confidence interval, 1.6 to 2.4)].However, upon review of each adverse event we found only one case that was related to the index visit, was potentially preventable by a 23-hour hospital observation, and caused permanent disability. In our study population, 17% of the children were discharged with at least one abnormal vital sign, and there were very few adverse (0.43%) events associated with this practice. Heart rate was the most common abnormal vital sign leading to an adverse event. Severe adverse events that were potentially related to the abnormal vital sign(s) were exceedingly rare. Additional research is

  12. 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

    DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals Vernon...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...As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and

  13. Diagnostic reliability of 3.0-T MRI for detecting osseous abnormalities of the temporomandibular joint.

    PubMed

    Sawada, Kunihiko; Amemiya, Toshihiko; Hirai, Shigenori; Hayashi, Yusuke; Suzuki, Toshihiro; Honda, Masahiko; Sisounthone, Johnny; Matsumoto, Kunihito; Honda, Kazuya

    2018-01-01

    We compared the diagnostic reliability of 3.0-T magnetic resonance imaging (MRI) for detection of osseous abnormalities of the temporomandibular joint (TMJ) with that of the gold standard, cone-beam computed tomography (CBCT). Fifty-six TMJs were imaged with CBCT and MRI, and images of condyles and fossae were independently assessed for the presence of osseous abnormalities. The accuracy, sensitivity, and specificity of 3.0-T MRI were 0.88, 1.0, and 0.73, respectively, in condyle evaluation and 0.91, 0.75, and 0.95 in fossa evaluation. The McNemar test showed no significant difference (P > 0.05) between MRI and CBCT in the evaluation of osseous abnormalities in condyles and fossae. The present results indicate that 3.0-T MRI is equal to CBCT in the diagnostic evaluation of osseous abnormalities of the mandibular condyle.

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

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

    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.

  15. Detecting Biosphere anomalies hotspots

    NASA Astrophysics Data System (ADS)

    Guanche-Garcia, Yanira; Mahecha, Miguel; Flach, Milan; Denzler, Joachim

    2017-04-01

    The current amount of satellite remote sensing measurements available allow for applying data-driven methods to investigate environmental processes. The detection of anomalies or abnormal events is crucial to monitor the Earth system and to analyze their impacts on ecosystems and society. By means of a combination of statistical methods, this study proposes an intuitive and efficient methodology to detect those areas that present hotspots of anomalies, i.e. higher levels of abnormal or extreme events or more severe phases during our historical records. Biosphere variables from a preliminary version of the Earth System Data Cube developed within the CAB-LAB project (http://earthsystemdatacube.net/) have been used in this study. This database comprises several atmosphere and biosphere variables expanding 11 years (2001-2011) with 8-day of temporal resolution and 0.25° of global spatial resolution. In this study, we have used 10 variables that measure the biosphere. The methodology applied to detect abnormal events follows the intuitive idea that anomalies are assumed to be time steps that are not well represented by a previously estimated statistical model [1].We combine the use of Autoregressive Moving Average (ARMA) models with a distance metric like Mahalanobis distance to detect abnormal events in multiple biosphere variables. In a first step we pre-treat the variables by removing the seasonality and normalizing them locally (μ=0,σ=1). Additionally we have regionalized the area of study into subregions of similar climate conditions, by using the Köppen climate classification. For each climate region and variable we have selected the best ARMA parameters by means of a Bayesian Criteria. Then we have obtained the residuals by comparing the fitted models with the original data. To detect the extreme residuals from the 10 variables, we have computed the Mahalanobis distance to the data's mean (Hotelling's T^2), which considers the covariance matrix of the joint

  16. Automatic Detection and Classification of Audio Events for Road Surveillance Applications.

    PubMed

    Almaadeed, Noor; Asim, Muhammad; Al-Maadeed, Somaya; Bouridane, Ahmed; Beghdadi, Azeddine

    2018-06-06

    This work investigates the problem of detecting hazardous events on roads by designing an audio surveillance system that automatically detects perilous situations such as car crashes and tire skidding. In recent years, research has shown several visual surveillance systems that have been proposed for road monitoring to detect accidents with an aim to improve safety procedures in emergency cases. However, the visual information alone cannot detect certain events such as car crashes and tire skidding, especially under adverse and visually cluttered weather conditions such as snowfall, rain, and fog. Consequently, the incorporation of microphones and audio event detectors based on audio processing can significantly enhance the detection accuracy of such surveillance systems. This paper proposes to combine time-domain, frequency-domain, and joint time-frequency features extracted from a class of quadratic time-frequency distributions (QTFDs) to detect events on roads through audio analysis and processing. Experiments were carried out using a publicly available dataset. The experimental results conform the effectiveness of the proposed approach for detecting hazardous events on roads as demonstrated by 7% improvement of accuracy rate when compared against methods that use individual temporal and spectral features.

  17. 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.

  18. 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.

  19. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Progress in Mathematical Modeling of Gastrointestinal Slow Wave Abnormalities

    PubMed Central

    Du, Peng; Calder, Stefan; Angeli, Timothy R.; Sathar, Shameer; Paskaranandavadivel, Niranchan; O'Grady, Gregory; Cheng, Leo K.

    2018-01-01

    Gastrointestinal (GI) motility is regulated in part by electrophysiological events called slow waves, which are generated by the interstitial cells of Cajal (ICC). Slow waves propagate by a process of “entrainment,” which occurs over a decreasing gradient of intrinsic frequencies in the antegrade direction across much of the GI tract. Abnormal initiation and conduction of slow waves have been demonstrated in, and linked to, a number of GI motility disorders. A range of mathematical models have been developed to study abnormal slow waves and applied to propose novel methods for non-invasive detection and therapy. This review provides a general outline of GI slow wave abnormalities and their recent classification using multi-electrode (high-resolution) mapping methods, with a particular emphasis on the spatial patterns of these abnormal activities. The recently-developed mathematical models are introduced in order of their biophysical scale from cellular to whole-organ levels. The modeling techniques, main findings from the simulations, and potential future directions arising from notable studies are discussed. PMID:29379448

  1. Phase-Space Detection of Cyber Events

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

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

    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 datamore » 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.« less

  2. Compressive sensing-based electrostatic sensor array signal processing and exhausted abnormal debris detecting

    NASA Astrophysics Data System (ADS)

    Tang, Xin; Chen, Zhongsheng; Li, Yue; Yang, Yongmin

    2018-05-01

    When faults happen at gas path components of gas turbines, some sparsely-distributed and charged debris will be generated and released into the exhaust gas. The debris is called abnormal debris. Electrostatic sensors can detect the debris online and further indicate the faults. It is generally considered that, under a specific working condition, a more serious fault generates more and larger debris, and a piece of larger debris carries more charge. Therefore, the amount and charge of the abnormal debris are important indicators of the fault severity. However, because an electrostatic sensor can only detect the superposed effect on the electrostatic field of all the debris, it can hardly identify the amount and position of the debris. Moreover, because signals of electrostatic sensors depend on not only charge but also position of debris, and the position information is difficult to acquire, measuring debris charge accurately using the electrostatic detecting method is still a technical difficulty. To solve these problems, a hemisphere-shaped electrostatic sensors' circular array (HSESCA) is used, and an array signal processing method based on compressive sensing (CS) is proposed in this paper. To research in a theoretical framework of CS, the measurement model of the HSESCA is discretized into a sparse representation form by meshing. In this way, the amount and charge of the abnormal debris are described as a sparse vector. It is further reconstructed by constraining l1-norm when solving an underdetermined equation. In addition, a pre-processing method based on singular value decomposition and a result calibration method based on weighted-centroid algorithm are applied to ensure the accuracy of the reconstruction. The proposed method is validated by both numerical simulations and experiments. Reconstruction errors, characteristics of the results and some related factors are discussed.

  3. Determinants of parental decision to abort or continue after non-aneuploid ultrasound-detected fetal abnormalities.

    PubMed

    Pryde, P G; Isada, N B; Hallak, M; Johnson, M P; Odgers, A E; Evans, M I

    1992-07-01

    This study evaluated factors influencing the decision to abort after abnormalities in the karyotypically normal fetus were found through ultrasonography. We reviewed all pregnancies complicated by ultrasound-detected abnormalities managed on our service from April 1990 through August 1991 (N = 262). Cases with associated karyotypic abnormalities were excluded (N = 35), as were cases diagnosed after the legal gestational age limit for abortion (N = 68). The remaining 159 cases were stratified into prognosis groups of "severe," "uncertain," and "mild." The prognostic severity of the ultrasound abnormality strongly correlated with the decision to abort (P less than .0001). Rates of termination were 0, 12, and 66% in the "mild," "uncertain," and "severe" groups, respectively. The patients' age, gravidity, and parity, and the fetal gestational age at diagnosis did not differ significantly between the groups. 1) In non-aneuploid pregnancies with an ultrasound diagnosis of fetal abnormality, the major predictor of the decision to abort was the severity of fetal prognosis. 2) The gestational age at diagnosis was not an important variable in the decision to abort for fetal structural abnormalities. 3) Parents who had fetuses with abnormalities associated with uncertain prognoses usually opted to continue the pregnancy. This appeared to be particularly true for defects that were potentially correctable in utero or by neonatal intervention (even if investigational).

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

    PubMed

    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.

  5. 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

  6. On-line early fault detection and diagnosis of municipal solid waste incinerators

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

    Zhao Jinsong; Huang Jianchao; Sun Wei

    A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows thatmore » automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.« less

  7. Detecting Seismic Events Using a Supervised Hidden Markov Model

    NASA Astrophysics Data System (ADS)

    Burks, L.; Forrest, R.; Ray, J.; Young, C.

    2017-12-01

    We explore the use of supervised hidden Markov models (HMMs) to detect seismic events in streaming seismogram data. Current methods for seismic event detection include simple triggering algorithms, such as STA/LTA and the Z-statistic, which can lead to large numbers of false positives that must be investigated by an analyst. The hypothesis of this study is that more advanced detection methods, such as HMMs, may decreases false positives while maintaining accuracy similar to current methods. We train a binary HMM classifier using 2 weeks of 3-component waveform data from the International Monitoring System (IMS) that was carefully reviewed by an expert analyst to pick all seismic events. Using an ensemble of simple and discrete features, such as the triggering of STA/LTA, the HMM predicts the time at which transition occurs from noise to signal. Compared to the STA/LTA detection algorithm, the HMM detects more true events, but the false positive rate remains unacceptably high. Future work to potentially decrease the false positive rate may include using continuous features, a Gaussian HMM, and multi-class HMMs to distinguish between types of seismic waves (e.g., P-waves and S-waves). Acknowledgement: Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.SAND No: SAND2017-8154 A

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  9. Multimodal Event Detection in Twitter Hashtag Networks

    DOE PAGES

    Yilmaz, Yasin; Hero, Alfred O.

    2016-07-01

    In this study, event detection in a multimodal Twitter dataset is considered. We treat the hashtags in the dataset as instances with two modes: text and geolocation features. The text feature consists of a bag-of-words representation. The geolocation feature consists of geotags (i.e., geographical coordinates) of the tweets. Fusing the multimodal data we aim to detect, in terms of topic and geolocation, the interesting events and the associated hashtags. To this end, a generative latent variable model is assumed, and a generalized expectation-maximization (EM) algorithm is derived to learn the model parameters. The proposed method is computationally efficient, and lendsmore » itself to big datasets. Lastly, experimental results on a Twitter dataset from August 2014 show the efficacy of the proposed method.« less

  10. Novel Analysis Software for Detecting and Classifying Ca2+ Transient Abnormalities in Stem Cell-Derived Cardiomyocytes

    PubMed Central

    Penttinen, Kirsi; Siirtola, Harri; Àvalos-Salguero, Jorge; Vainio, Tiina; Juhola, Martti; Aalto-Setälä, Katriina

    2015-01-01

    Comprehensive functioning of Ca2+ cycling is crucial for excitation–contraction coupling of cardiomyocytes (CMs). Abnormal Ca2+ cycling is linked to arrhythmogenesis, which is associated with cardiac disorders and heart failure. Accordingly, we have generated spontaneously beating CMs from induced pluripotent stem cells (iPSC) derived from patients with catecholaminergic polymorphic ventricular tachycardia (CPVT), which is an inherited and severe cardiac disease. Ca2+ cycling studies have revealed substantial abnormalities in these CMs. Ca2+ transient analysis performed manually lacks accepted analysis criteria, and has both low throughput and high variability. To overcome these issues, we have developed a software tool, AnomalyExplorer based on interactive visualization, to assist in the classification of Ca2+ transient patterns detected in CMs. Here, we demonstrate the usability and capability of the software, and we also compare the analysis efficiency to manual analysis. We show that AnomalyExplorer is suitable for detecting normal and abnormal Ca2+ transients; furthermore, this method provides more defined and consistent information regarding the Ca2+ abnormality patterns and cell line specific differences when compared to manual analysis. This tool will facilitate and speed up the analysis of CM Ca2+ transients, making it both more accurate and user-independent. AnomalyExplorer can be exploited in Ca2+ cycling analysis to study basic disease pathology and the effects of different drugs. PMID:26308621

  11. Novel Analysis Software for Detecting and Classifying Ca2+ Transient Abnormalities in Stem Cell-Derived Cardiomyocytes.

    PubMed

    Penttinen, Kirsi; Siirtola, Harri; Àvalos-Salguero, Jorge; Vainio, Tiina; Juhola, Martti; Aalto-Setälä, Katriina

    2015-01-01

    Comprehensive functioning of Ca2+ cycling is crucial for excitation-contraction coupling of cardiomyocytes (CMs). Abnormal Ca2+ cycling is linked to arrhythmogenesis, which is associated with cardiac disorders and heart failure. Accordingly, we have generated spontaneously beating CMs from induced pluripotent stem cells (iPSC) derived from patients with catecholaminergic polymorphic ventricular tachycardia (CPVT), which is an inherited and severe cardiac disease. Ca2+ cycling studies have revealed substantial abnormalities in these CMs. Ca2+ transient analysis performed manually lacks accepted analysis criteria, and has both low throughput and high variability. To overcome these issues, we have developed a software tool, AnomalyExplorer based on interactive visualization, to assist in the classification of Ca2+ transient patterns detected in CMs. Here, we demonstrate the usability and capability of the software, and we also compare the analysis efficiency to manual analysis. We show that AnomalyExplorer is suitable for detecting normal and abnormal Ca2+ transients; furthermore, this method provides more defined and consistent information regarding the Ca2+ abnormality patterns and cell line specific differences when compared to manual analysis. This tool will facilitate and speed up the analysis of CM Ca2+ transients, making it both more accurate and user-independent. AnomalyExplorer can be exploited in Ca2+ cycling analysis to study basic disease pathology and the effects of different drugs.

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

    DTIC Science & Technology

    2009-03-01

    using the composite event detection method [Kerman, Jiang, Blumberg , and Buttrey, 2009]. Although the techniques and utility of the...aforementioned method have been clearly demonstrated, there is still much work and research to be conducted within the realm of event detection. This...detection methods . The paragraphs that follow summarize the discoveries of and lessons learned by multiple researchers and authors over many

  13. Selected control events and reporting odds ratio in signal detection methodology.

    PubMed

    Ooba, Nobuhiro; Kubota, Kiyoshi

    2010-11-01

    To know whether the reporting odds ratio (ROR) using "control events" can detect signals hidden behind striking reports on one or more particular events. We used data of 956 drug use investigations (DUIs) conducted between 1970 and 1998 in Japan and domestic spontaneous reports (SRs) between 1998 and 2008. The event terms in DUIs were converted to the preferred terms in Medical Dictionary for Regulatory Activities (MedDRA). We calculated the incidence proportion for various events and selected 20 "control events" with a relatively constant incidence proportion across DUIs and also reported regularly to the spontaneous reporting system. A "signal" was generated for the drug-event combination when the lower limit of 95% confidence interval of the ROR exceeded 1. We also compared the ROR in SRs with the RR in DUIs. The "control events" accounted for 18.2% of all reports. The ROR using "control events" may detect some hidden signals for a drug with the proportion of "control events" lower than the average. The median of the ratios of the ROR using "control events" to RR was around the unity indicating that "control events" roughly represented the exposure distribution though the range of the ratios was so diverse that the individual ROR might not be regarded as the estimate of RR. The use of the ROR with "control events" may give an adjunctive to the traditional signal detection methods to find a signal hidden behind some major events. Copyright © 2010 John Wiley & Sons, Ltd.

  14. 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.

  15. Adaptive Sensor Tuning for Seismic Event Detection in Environment with Electromagnetic Noise

    NASA Astrophysics Data System (ADS)

    Ziegler, Abra E.

    The goal of this research is to detect possible microseismic events at a carbon sequestration site. Data recorded on a continuous downhole microseismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project, were evaluated using machine learning and reinforcement learning techniques to determine their effectiveness at seismic event detection on a dataset with electromagnetic noise. The data were recorded from a passive vertical monitoring array consisting of 16 levels of 3-component 15 Hz geophones installed in the field and continuously recording since January 2014. Electromagnetic and other noise recorded on the array has significantly impacted the utility of the data and it was necessary to characterize and filter the noise in order to attempt event detection. Traditional detection methods using short-term average/long-term average (STA/LTA) algorithms were evaluated and determined to be ineffective because of changing noise levels. To improve the performance of event detection and automatically and dynamically detect seismic events using effective data processing parameters, an adaptive sensor tuning (AST) algorithm developed by Sandia National Laboratories was utilized. AST exploits neuro-dynamic programming (reinforcement learning) trained with historic event data to automatically self-tune and determine optimal detection parameter settings. The key metric that guides the AST algorithm is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The effects that changes in neighborhood configuration have on signal detection were explored, as it was determined that neighborhood-based detections significantly reduce the number of both missed and false detections in ground-truthed data. The performance of the AST algorithm was

  16. 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

  17. 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.

  18. 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.

  19. Molecular Detection of HPV and Chlamydia trachomatis Infections in Brazilian Women with Abnormal Cervical Cytology

    PubMed Central

    de Abreu, André L. P.; Nogara, Paula R. B.; Souza, Raquel P.; da Silva, Mariana C.; Uchimura, Nelson S.; Zanko, Rodrigo L.; Ferreira, Érika C.; Tognim, Maria C. B.; Teixeira, Jorge J. V.; Gimenes, Fabrícia; Consolaro, Marcia E. L.

    2012-01-01

    The question of whether Chlamydia trachomatis (Ct) is a cofactor for human Papillomavirus (HPV) in cervical carcinogenesis is still controversial. We conducted a molecular detection study of both infections in 622 Brazilian women, including 252 women with different grades of abnormal cervical cytology and cervical cancer (CC; cases) and 370 women with normal cytology (controls). Although Ct infection did not seem related to CC carcinogenicity, women with abnormal cytology had a significant high rate of Ct infection. Therefore, it is important to adopt protocols for diagnosis and treatment of this bacterium in conjunction with screening for CC in this population. PMID:23128289

  20. Multilingual event extraction for epidemic detection.

    PubMed

    Lejeune, Gaël; Brixtel, Romain; Doucet, Antoine; Lucas, Nadine

    2015-10-01

    This paper presents a multilingual news surveillance system applied to tele-epidemiology. It has been shown that multilingual approaches improve timeliness in detection of epidemic events across the globe, eliminating the wait for local news to be translated into major languages. We present here a system to extract epidemic events in potentially any language, provided a Wikipedia seed for common disease names exists. The Daniel system presented herein relies on properties that are common to news writing (the journalistic genre), the most useful being repetition and saliency. Wikipedia is used to screen common disease names to be matched with repeated characters strings. Language variations, such as declensions, are handled by processing text at the character-level, rather than at the word level. This additionally makes it possible to handle various writing systems in a similar fashion. As no multilingual ground truth existed to evaluate the Daniel system, we built a multilingual corpus from the Web, and collected annotations from native speakers of Chinese, English, Greek, Polish and Russian, with no connection or interest in the Daniel system. This data set is available online freely, and can be used for the evaluation of other event extraction systems. Experiments for 5 languages out of 17 tested are detailed in this paper: Chinese, English, Greek, Polish and Russian. The Daniel system achieves an average F-measure of 82% in these 5 languages. It reaches 87% on BEcorpus, the state-of-the-art corpus in English, slightly below top-performing systems, which are tailored with numerous language-specific resources. The consistent performance of Daniel on multiple languages is an important contribution to the reactivity and the coverage of epidemiological event detection systems. Most event extraction systems rely on extensive resources that are language-specific. While their sophistication induces excellent results (over 90% precision and recall), it restricts their

  1. 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.

  2. Computer-aided detection system for chest radiography: reducing report turnaround times of examinations with abnormalities.

    PubMed

    Kao, E-Fong; Liu, Gin-Chung; Lee, Lo-Yeh; Tsai, Huei-Yi; Jaw, Twei-Shiun

    2015-06-01

    The ability to give high priority to examinations with pathological findings could be very useful to radiologists with large work lists who wish to first evaluate the most critical studies. A computer-aided detection (CAD) system for identifying chest examinations with abnormalities has therefore been developed. To evaluate the effectiveness of a CAD system on report turnaround times of chest examinations with abnormalities. The CAD system was designed to automatically mark chest examinations with possible abnormalities in the work list of radiologists interpreting chest examinations. The system evaluation was performed in two phases: two radiologists interpreted the chest examinations without CAD in phase 1 and with CAD in phase 2. The time information recorded by the radiology information system was then used to calculate the turnaround times. All chest examinations were reviewed by two other radiologists and were divided into normal and abnormal groups. The turnaround times for the examinations with pathological findings with and without the CAD system assistance were compared. The sensitivity and specificity of the CAD for chest abnormalities were 0.790 and 0.697, respectively, and use of the CAD system decreased the turnaround time for chest examinations with abnormalities by 44%. The turnaround times required for radiologists to identify chest examinations with abnormalities could be reduced by using the CAD system. This system could be useful for radiologists with large work lists who wish to first evaluate the most critical studies. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  3. 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.

  4. Management of low-grade cervical abnormalities detected at screening: which method do women prefer?

    PubMed

    Whynes, D K; Woolley, C; Philips, Z

    2008-12-01

    To establish whether women with low-grade abnormalities detected during screening for cervical cancer prefer to be managed by cytological surveillance or by immediate colposcopy. TOMBOLA (Trial of Management of Borderline and Other Low-grade Abnormal smears) is a randomized controlled trial comparing alternative management strategies following the screen-detection of low-grade cytological abnormalities. At exit, a sample of TOMBOLA women completed a questionnaire eliciting opinions on their management, contingent valuations (CV) of the management methods and preferences. Within-trial quality of life (EQ-5D) data collected for a sample of TOMBOLA women throughout their follow-up enabled the comparison of self-reported health at various time points, by management method. Once management had been initiated, self-reported health in the colposcopy arm rose relative to that in the surveillance arm, although the effect was short-term only. For the majority of women, the satisfaction ratings and the CV indicated approval of the management method to which they had been randomized. Of the minority manifesting a preference for the method which they had not experienced, relatively more would have preferred colposcopy than would have preferred surveillance. The findings must be interpreted in the light of sample bias with respect to preferences, whereby enthusiasm for colposcopy was probably over-represented amongst trial participants. The study suggests that neither of the management methods is preferred unequivocally; rather, individual women have individual preferences, although many would be indifferent between methods.

  5. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Detecting event-related changes in organizational networks using optimized neural network models.

    PubMed

    Li, Ze; Sun, Duoyong; Zhu, Renqi; Lin, Zihan

    2017-01-01

    Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques.

  7. Detecting event-related changes in organizational networks using optimized neural network models

    PubMed Central

    Sun, Duoyong; Zhu, Renqi; Lin, Zihan

    2017-01-01

    Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques. PMID:29190799

  8. [Impact of indirect factors on the growing prevalence of workers with abnormal findings in periodic general health examinations: a survey on the definition and detection of such abnormal workers by occupational health organizations].

    PubMed

    Hoshuyama, T; Takahashi, K; Fujishiro, K; Uchida, K; Okubo, T

    2000-05-01

    The prevalence of workers with abnormal findings in periodic general health examinations (PGHEx) has been growing recently in Japan and reached 41.2% in 1998. To clarify the indirect factors related to such an increase in workers with abnormal findings in the PGHEx, we carried out a questionnaire survey on the content of the statutory notification form of results of the PGHEx among a representative sample of 136 Occupational Health Organizations (OHOs). Questions on how those workers with abnormal findings were defined and detected and when the definition and the reference intervals for total cholesterol became available were included. Of the 107 OHOs which answered the questionnaire, 85 were included in the analyses because they actually calculated the number of workers with abnormal findings in each company and helped the employer fill out the notification form. The results revealed that there was no standardized definition of workers with abnormal findings in the PGHEx. Both reference intervals of items in the PGHEx and algorithm in detecting workers with abnormal findings in the PGHEx varied among the OHOs. When detecting the workers, 13 OHOs (15.3%) selected them taking into consideration medical background factors such as previous results of the PGHEx and current medical treatment. From the late 1980s to the early 1990s, many OHOs modified the definition of workers with abnormal findings, and have tended to reduce the upper limit of the reference interval for serum cholesterol. This is mainly due to amendment of the Industrial Safety and Health Law and a new recommendation for a reference interval/value proposed by the related scientific society. Although the prevalence of workers with abnormal findings in the PGHEx has continuously increased, it is not valid to compare the prevalence over the years because of modification in the definition of such workers. The prevalence of workers with abnormal findings in the PGHEx, which is one of the most important

  9. Abnormal findings in peers during skills learning.

    PubMed

    Wearn, Andy; Nakatsuji, Miriam; Bhoopatkar, Harsh

    2017-02-01

    Peer physical examination (PPE), where students examine each other, is common in contemporary clinical skills learning. A range of benefits and risks have been explored in the literature. One persistent concern has been the identification and management of abnormal physical findings. Two previous studies have attempted to quantify the risk, one through the discussion of two exemplar cases and the other with a retrospective student survey. Here, we report the first prospective study of the number and type of abnormalities encountered as part of early clinical skills learning in a medical programme. We have a formal written consent process for PPE, which includes the management of abnormal findings through the completion of an event form. Our data come from cohorts undertaking years 2 and 3 of the programme between 2003 and 2014. One persistent concern (of PPE) has been the identification and management of abnormal physical findings RESULTS: Nineteen event forms were completed over this period. The incidence rates per year ranged from 0.23 to 1.05 per cent. Abnormal findings included raised blood pressure, heart murmur, abnormal bedside test values, and eye and skin conditions. The low event rate, along with a feasible process for dealing with this issue, goes some way to reassuring those with concerns. We acknowledge that some abnormalities may have been missed, and that some data may have been lost as a result of incorrect process; however, even the highest annual rate is low in absolute terms. We recommend a formal process for managing abnormalities. Ideally this would be part of an overall PPE written policy, communicated to students, enacted by tutors and approved by the local ethics committee. © 2016 John Wiley & Sons Ltd.

  10. 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

  11. 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.

  12. 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.

  13. Exploring polycythaemia vera with fluorescence in situ hybridization: additional cryptic 9p is the most frequent abnormality detected.

    PubMed

    Najfeld, Vesna; Montella, Lya; Scalise, Angela; Fruchtman, Steven

    2002-11-01

    Between 1986 and 2001, 220 patients with polycythaemia vera (PV) were studied using conventional cytogenetics. Of 204 evaluable patients, 52 (25.4%) had clonal abnormalities. The recurrent chromosomal rearrangements were those of chromosome 9 (21.1%), del(20q) (19.2%), trisomy 8 (19.2%), rearrangements of 13q (13.4%), abnormalities of 1q (11.5%), and of chromosomes 5 and 7 (9.6%). Subsequent analysis of 32 patients, performed at follow-up of up to 14.8 years, revealed new clonal abnormalities in five patients and the disappearance of an abnormal clone in four. Eleven patients remained normal up to 11.5 years and seven patients maintained an abnormality for over 10 years. Fifty-three patients were studied retrospectively using interphase fluorescence in situ hybridization (I-FISH), utilizing probes for centromere enumeration of chromosomes 8 and 9, and for 13q14 and 20q12 loci. Conventional cytogenetics demonstrated clonal chromosome abnormalities in 23% of these 53 patients. The addition of I-FISH increased the detection of abnormalities to 29% and permitted clarification of chromosome 9 rearrangements in an additional 5.6% of patients. FISH uncovered rearrangements of chromosome 9 in 53% of patients with an abnormal FISH pattern, which represented the most frequent genomic alteration in this series.

  14. Multimodal Sparse Coding for Event Detection

    DTIC Science & Technology

    2015-10-13

    classification tasks based on single modality. We present multimodal sparse coding for learning feature representations shared across multiple modalities...The shared representa- tions are applied to multimedia event detection (MED) and evaluated in compar- ison to unimodal counterparts, as well as other...and video tracks from the same multimedia clip, we can force the two modalities to share a similar sparse representation whose benefit includes robust

  15. Photogrammetry: an accurate and reliable tool to detect thoracic musculoskeletal abnormalities in preterm infants.

    PubMed

    Davidson, Josy; dos Santos, Amelia Miyashiro N; Garcia, Kessey Maria B; Yi, Liu C; João, Priscila C; Miyoshi, Milton H; Goulart, Ana Lucia

    2012-09-01

    To analyse the accuracy and reproducibility of photogrammetry in detecting thoracic abnormalities in infants born prematurely. Cross-sectional study. The Premature Clinic at the Federal University of São Paolo. Fifty-eight infants born prematurely in their first year of life. Measurement of the manubrium/acromion/trapezius angle (degrees) and the deepest thoracic retraction (cm). Digitised photographs were analysed by two blinded physiotherapists using a computer program (SAPO; http://SAPO.incubadora.fapesp.br) to detect shoulder elevation and thoracic retraction. Physical examinations performed independently by two physiotherapists were used to assess the accuracy of the new tool. Thoracic alterations were detected in 39 (67%) and in 40 (69%) infants by Physiotherapists 1 and 2, respectively (kappa coefficient=0.80). Using a receiver operating characteristic curve, measurement of the manubrium/acromion/trapezius angle and the deepest thoracic retraction indicated accuracy of 0.79 and 0.91, respectively. For measurement of the manubrium/acromion/trapezius angle, the Bland and Altman limits of agreement were -6.22 to 7.22° [mean difference (d)=0.5] for repeated measures by one physiotherapist, and -5.29 to 5.79° (d=0.75) between two physiotherapists. For thoracic retraction, the intra-rater limits of agreement were -0.14 to 0.18cm (d=0.02) and the inter-rater limits of agreement were -0.20 to -0.17cm (d=0.02). SAPO provided an accurate and reliable tool for the detection of thoracic abnormalities in preterm infants. Copyright © 2011 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  16. 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.

  17. Mesh-free based variational level set evolution for breast region segmentation and abnormality detection using mammograms.

    PubMed

    Kashyap, Kanchan L; Bajpai, Manish K; Khanna, Pritee; Giakos, George

    2018-01-01

    Automatic segmentation of abnormal region is a crucial task in computer-aided detection system using mammograms. In this work, an automatic abnormality detection algorithm using mammographic images is proposed. In the preprocessing step, partial differential equation-based variational level set method is used for breast region extraction. The evolution of the level set method is done by applying mesh-free-based radial basis function (RBF). The limitation of mesh-based approach is removed by using mesh-free-based RBF method. The evolution of variational level set function is also done by mesh-based finite difference method for comparison purpose. Unsharp masking and median filtering is used for mammogram enhancement. Suspicious abnormal regions are segmented by applying fuzzy c-means clustering. Texture features are extracted from the segmented suspicious regions by computing local binary pattern and dominated rotated local binary pattern (DRLBP). Finally, suspicious regions are classified as normal or abnormal regions by means of support vector machine with linear, multilayer perceptron, radial basis, and polynomial kernel function. The algorithm is validated on 322 sample mammograms of mammographic image analysis society (MIAS) and 500 mammograms from digital database for screening mammography (DDSM) datasets. Proficiency of the algorithm is quantified by using sensitivity, specificity, and accuracy. The highest sensitivity, specificity, and accuracy of 93.96%, 95.01%, and 94.48%, respectively, are obtained on MIAS dataset using DRLBP feature with RBF kernel function. Whereas, the highest 92.31% sensitivity, 98.45% specificity, and 96.21% accuracy are achieved on DDSM dataset using DRLBP feature with RBF kernel function. Copyright © 2017 John Wiley & Sons, Ltd.

  18. Can we improve the prevention and detection of congenital abnormalities? An audit of early pregnancy care in New Zealand.

    PubMed

    Arroll, Nicola; Sadler, Lynn; Stone, Peter; Masson, Vicki; Farquhar, Cindy

    2013-08-16

    To determine whether there were "quality gaps" in the provision of care during pregnancies that resulted in a perinatal death due to congenital abnormality. Perinatal deaths from congenital cardiovascular, central nervous system or chromosomal abnormality in 2010 were identified retrospectively. Data were extracted by retrospective clinical note review and obtained by independent review of ultrasound scans. There were 137 perinatal deaths due to a congenital cardiovascular (35), central nervous system (29) or chromosomal abnormality (73). First contact with a health professional during pregnancy was predominantly with a general practitioner. First contact occurred within 14 weeks in 85% of pregnancies and there was often a significant delay before booking. Folate supplements were taken by 7% pre-conceptually and 54% of women in the antenatal period. There were 20 perinatal deaths from neural tube defects that could potentially have been prevented through the use of pre-conceptual folate. Antenatal screening was offered to 75% of the women who presented prior to 20 weeks and 84% of these undertook at least one of the available antenatal screening tests. Review of ultrasound images found five abnormalities could have been detected earlier. Delay in booking or failure to offer screening early were the most common reasons for delay in diagnosis of screen detectable abnormalities. The preventative value and timing of (pre-conceptual) folate needs emphasis.

  19. Spatial event cluster detection using an approximate normal distribution.

    PubMed

    Torabi, Mahmoud; Rosychuk, Rhonda J

    2008-12-12

    In geographic surveillance of disease, areas with large numbers of disease cases are to be identified so that investigations of the causes of high disease rates can be pursued. Areas with high rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. Typically cluster detection tests are applied to incident or prevalent cases of disease, but surveillance of disease-related events, where an individual may have multiple events, may also be of interest. Previously, a compound Poisson approach that detects clusters of events by testing individual areas that may be combined with their neighbours has been proposed. However, the relevant probabilities from the compound Poisson distribution are obtained from a recursion relation that can be cumbersome if the number of events are large or analyses by strata are performed. We propose a simpler approach that uses an approximate normal distribution. This method is very easy to implement and is applicable to situations where the population sizes are large and the population distribution by important strata may differ by area. We demonstrate the approach on pediatric self-inflicted injury presentations to emergency departments and compare the results for probabilities based on the recursion and the normal approach. We also implement a Monte Carlo simulation to study the performance of the proposed approach. In a self-inflicted injury data example, the normal approach identifies twelve out of thirteen of the same clusters as the compound Poisson approach, noting that the compound Poisson method detects twelve significant clusters in total. Through simulation studies, the normal approach well approximates the compound Poisson approach for a variety of different population sizes and case and event thresholds. A drawback of the compound Poisson approach is that the relevant probabilities must be determined through a

  20. [Study on the timeliness of detection and reporting on public health emergency events in China].

    PubMed

    Li, Ke-Li; Feng, Zi-Jian; Ni, Da-Xin

    2009-03-01

    To analyze the timeliness of detection and reporting on public health emergency events, and to explore the effective strategies for improving the relative capacity on those issues. We conducted a retrospective survey on 3275 emergency events reported through Public Health Emergency Events Surveillance System from 2005 to the first half of 2006. Developed by county Centers for Disease Control and Prevention, a uniformed self-administrated questionnaire was used to collect data, which would include information on the detection, reporting of the events. For communicable diseases events, the median of time interval between the occurrence of first case and the detection of event was 6 days (P25 = 2, P75 = 13). For food poisoning events and clusters of disease with unknown origin, the medians were 3 hours (P25, P75 = 16) and 1 days (P25 = 0, P75 = 5). 71.54% of the events were reported by the discoverers within 2 hours after the detection. In general, the ranges of time intervals between the occurrence, detection or reporting of the events were different, according to the categories of events. The timeliness of detection and reporting of events could have been improved dramatically if the definition of events, according to their characteristics, had been more reasonable and accessible, as well as the improvement of training program for healthcare staff and teachers.

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

    NASA Astrophysics Data System (ADS)

    Reynen, Andrew; Audet, Pascal

    2017-09-01

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

  2. National Earthquake Information Center Seismic Event Detections on Multiple Scales

    NASA Astrophysics Data System (ADS)

    Patton, J.; Yeck, W. L.; Benz, H.; Earle, P. S.; Soto-Cordero, L.; Johnson, C. E.

    2017-12-01

    The U.S. Geological Survey National Earthquake Information Center (NEIC) monitors seismicity on local, regional, and global scales using automatic picks from more than 2,000 near-real time seismic stations. This presents unique challenges in automated event detection due to the high variability in data quality, network geometries and density, and distance-dependent variability in observed seismic signals. To lower the overall detection threshold while minimizing false detection rates, NEIC has begun to test the incorporation of new detection and picking algorithms, including multiband (Lomax et al., 2012) and kurtosis (Baillard et al., 2014) pickers, and a new bayesian associator (Glass 3.0). The Glass 3.0 associator allows for simultaneous processing of variably scaled detection grids, each with a unique set of nucleation criteria (e.g., nucleation threshold, minimum associated picks, nucleation phases) to meet specific monitoring goals. We test the efficacy of these new tools on event detection in networks of various scales and geometries, compare our results with previous catalogs, and discuss lessons learned. For example, we find that on local and regional scales, rapid nucleation of small events may require event nucleation with both P and higher-amplitude secondary phases (e.g., S or Lg). We provide examples of the implementation of a scale-independent associator for an induced seismicity sequence (local-scale), a large aftershock sequence (regional-scale), and for monitoring global seismicity. Baillard, C., Crawford, W. C., Ballu, V., Hibert, C., & Mangeney, A. (2014). An automatic kurtosis-based P-and S-phase picker designed for local seismic networks. Bulletin of the Seismological Society of America, 104(1), 394-409. Lomax, A., Satriano, C., & Vassallo, M. (2012). Automatic picker developments and optimization: FilterPicker - a robust, broadband picker for real-time seismic monitoring and earthquake early-warning, Seism. Res. Lett. , 83, 531-540, doi: 10

  3. Screening DNA chip and event-specific multiplex PCR detection methods for biotech crops.

    PubMed

    Lee, Seong-Hun

    2014-11-01

    There are about 80 biotech crop events that have been approved by safety assessment in Korea. They have been controlled by genetically modified organism (GMO) and living modified organism (LMO) labeling systems. The DNA-based detection method has been used as an efficient scientific management tool. Recently, the multiplex polymerase chain reaction (PCR) and DNA chip have been developed as simultaneous detection methods for several biotech crops' events. The event-specific multiplex PCR method was developed to detect five biotech maize events: MIR604, Event 3272, LY 038, MON 88017 and DAS-59122-7. The specificity was confirmed and the sensitivity was 0.5%. The screening DNA chip was developed from four endogenous genes of soybean, maize, cotton and canola respectively along with two regulatory elements and seven genes: P35S, tNOS, pat, bar, epsps1, epsps2, pmi, cry1Ac and cry3B. The specificity was confirmed and the sensitivity was 0.5% for four crops' 12 events: one soybean, six maize, three cotton and two canola events. The multiplex PCR and DNA chip can be available for screening, gene-specific and event-specific analysis of biotech crops as efficient detection methods by saving on workload and time. © 2014 Society of Chemical Industry. © 2014 Society of Chemical Industry.

  4. 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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  7. Periventricular Nodular Heterotopia: Detection of Abnormal Microanatomic Fiber Structures with Whole-Brain Diffusion MR Imaging Tractography.

    PubMed

    Farquharson, Shawna; Tournier, J-Donald; Calamante, Fernando; Mandelstam, Simone; Burgess, Rosemary; Schneider, Michal E; Berkovic, Samuel F; Scheffer, Ingrid E; Jackson, Graeme D; Connelly, Alan

    2016-12-01

    Purpose To investigate whether it is possible in patients with periventricular nodular heterotopia (PVNH) to detect abnormal fiber projections that have only previously been reported in the histopathology literature. Materials and Methods Whole-brain diffusion-weighted (DW) imaging data from 14 patients with bilateral PVNH and 14 age- and sex-matched healthy control subjects were prospectively acquired by using 3.0-T magnetic resonance (MR) imaging between August 1, 2008, and December 5, 2012. All participants provided written informed consent. The DW imaging data were processed to generate whole-brain constrained spherical deconvolution (CSD)-based tractography data and super-resolution track-density imaging (TDI) maps. The tractography data were overlaid on coregistered three-dimensional T1-weighted images to visually assess regions of heterotopia. A panel of MR imaging researchers independently assessed each case and indicated numerically (no = 1, yes = 2) as to the presence of abnormal fiber tracks in nodular tissue. The Fleiss κ statistical measure was applied to assess the reader agreement. Results Abnormal fiber tracks emanating from one or more regions of heterotopia were reported by all four readers in all 14 patients with PVNH (Fleiss κ = 1). These abnormal structures were not visible on the tractography data from any of the control subjects and were not discernable on the conventional T1-weighted images of the patients with PVNH. Conclusion Whole-brain CSD-based fiber tractography and super-resolution TDI mapping reveals abnormal fiber projections in nodular tissue suggestive of abnormal organization of white matter (with abnormal fibers both within nodules and projecting to the surrounding white matter) in patients with bilateral PVNH. © RSNA, 2016.

  8. CAFE: an R package for the detection of gross chromosomal abnormalities from gene expression microarray data.

    PubMed

    Bollen, Sander; Leddin, Mathias; Andrade-Navarro, Miguel A; Mah, Nancy

    2014-05-15

    The current methods available to detect chromosomal abnormalities from DNA microarray expression data are cumbersome and inflexible. CAFE has been developed to alleviate these issues. It is implemented as an R package that analyzes Affymetrix *.CEL files and comes with flexible plotting functions, easing visualization of chromosomal abnormalities. CAFE is available from https://bitbucket.org/cob87icW6z/cafe/ as both source and compiled packages for Linux and Windows. It is released under the GPL version 3 license. CAFE will also be freely available from Bioconductor. sander.h.bollen@gmail.com or nancy.mah@mdc-berlin.de Supplementary data are available at Bioinformatics online.

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

    PubMed Central

    Mao, Yingchi; Qi, Hai; Ping, Ping; Li, Xiaofang

    2017-01-01

    Time series data of multiple water quality parameters are obtained from the water sensor networks deployed in the agricultural water supply network. The accurate and efficient detection and warning of contamination events to prevent pollution from spreading is one of the most important issues when pollution occurs. In order to comprehensively reduce the event detection deviation, a spatial–temporal-based event detection approach with multivariate time-series data for water quality monitoring (M-STED) was proposed. The M-STED approach includes three parts. The first part is that M-STED adopts a Rule K algorithm to select backbone nodes as the nodes in the CDS, and forward the sensed data of multiple water parameters. The second part is to determine the state of each backbone node with back propagation neural network models and the sequential Bayesian analysis in the current timestamp. The third part is to establish a spatial model with Bayesian networks to estimate the state of the backbones in the next timestamp and trace the “outlier” node to its neighborhoods to detect a contamination event. The experimental results indicate that the average detection rate is more than 80% with M-STED and the false detection rate is lower than 9%, respectively. The M-STED approach can improve the rate of detection by about 40% and reduce the false alarm rate by about 45%, compared with the event detection with a single water parameter algorithm, S-STED. Moreover, the proposed M-STED can exhibit better performance in terms of detection delay and scalability. PMID:29207535

  10. 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

  11. Machine learning for the automatic detection of anomalous events

    NASA Astrophysics Data System (ADS)

    Fisher, Wendy D.

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

  12. Development of a database and processing method for detecting hematotoxicity adverse drug events.

    PubMed

    Shimai, Yoshie; Takeda, Toshihiro; Manabe, Shirou; Teramoto, Kei; Mihara, Naoki; Matsumura, Yasushi

    2015-01-01

    Adverse events are detected by monitoring the patient's status, including blood test results. However, it is difficult to identify all adverse events based on recognition by individual doctors. We developed a system that can be used to detect hematotoxicity adverse events according to blood test results recorded in an electronic medical record system. The blood test results were graded based on Common Terminology Criteria for Adverse Events (CTCAE) and changes in the blood test results (Up, Down, Flat) were assessed according to the variation in the grade. The changes in the blood test and injection data were stored in a database. By comparing the date of injection and start and end dates of the change in the blood test results, adverse events related to a designated drug were detected. Using this method, we searched for the occurrence of serious adverse events (CTCAE Grades 3 or 4) concerning WBC, ALT and creatinine related to paclitaxel at Osaka University Hospital. The rate of occurrence of a decreased WBC count, increased ALT level and increased creatinine level was 36.0%, 0.6% and 0.4%, respectively. This method is useful for detecting and estimating the rate of occurrence of hematotoxicity adverse drug events.

  13. Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases

    PubMed Central

    2014-01-01

    Background Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. Methods We used a set of complex detection rules to take account of the patient’s clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules’ analytical quality was evaluated for ADEs. Results In terms of recall, 89.5% of ADEs with hyperkalaemia “with or without an abnormal symptom” were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. Conclusions The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases. PMID:25212108

  14. Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

    PubMed

    Ficheur, Grégoire; Chazard, Emmanuel; Beuscart, Jean-Baptiste; Merlin, Béatrice; Luyckx, Michel; Beuscart, Régis

    2014-09-12

    Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. We used a set of complex detection rules to take account of the patient's clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules' analytical quality was evaluated for ADEs. In terms of recall, 89.5% of ADEs with hyperkalaemia "with or without an abnormal symptom" were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.

  15. 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.

  16. 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

  17. Automated Detection of Surgical Adverse Events from Retrospective Clinical Data

    ERIC Educational Resources Information Center

    Hu, Zhen

    2017-01-01

    The Detection of surgical adverse events has become increasingly important with the growing demand for quality improvement and public health surveillance with surgery. Event reporting is one of the key steps in determining the impact of postoperative complications from a variety of perspectives and is an integral component of improving…

  18. 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

  19. Cerebellar White Matter Abnormalities following Primary Blast Injury in US Military Personnel

    PubMed Central

    Mac Donald, Christine; Johnson, Ann; Cooper, Dana; Malone, Thomas; Sorrell, James; Shimony, Joshua; Parsons, Matthew; Snyder, Abraham; Raichle, Marcus; Fang, Raymond; Flaherty, Stephen; Russell, Michael; Brody, David L.

    2013-01-01

    Little is known about the effects of blast exposure on the human brain in the absence of head impact. Clinical reports, experimental animal studies, and computational modeling of blast exposure have suggested effects on the cerebellum and brainstem. In US military personnel with isolated, primary blast-related ‘mild’ traumatic brain injury and no other known insult, we found diffusion tensor MRI abnormalities consistent with cerebellar white matter injury in 3 of 4 subjects. No abnormalities in other brain regions were detected. These findings add to the evidence supporting the hypothesis that primary blast exposure contributes to brain injury in the absence of head impact and that the cerebellum may be particularly vulnerable. However, the clinical effects of these abnormalities cannot be determined with certainty; none of the subjects had ataxia or other detected evidence of cerebellar dysfunction. The details of the blast events themselves cannot be disclosed at this time, thus additional animal and computational modeling will be required to dissect the mechanisms underlying primary blast-related traumatic brain injury. Furthermore, the effects of possible subconcussive impacts and other military-related exposures cannot be determined from the data presented. Thus many aspects of topic will require further investigation. PMID:23409052

  20. Computerized lung sound analysis as diagnostic aid for the detection of abnormal lung sounds: a systematic review and meta-analysis.

    PubMed

    Gurung, Arati; Scrafford, Carolyn G; Tielsch, James M; Levine, Orin S; Checkley, William

    2011-09-01

    The standardized use of a stethoscope for chest auscultation in clinical research is limited by its inherent inter-listener variability. Electronic auscultation and automated classification of recorded lung sounds may help prevent some of these shortcomings. We sought to perform a systematic review and meta-analysis of studies implementing computerized lung sound analysis (CLSA) to aid in the detection of abnormal lung sounds for specific respiratory disorders. We searched for articles on CLSA in MEDLINE, EMBASE, Cochrane Library and ISI Web of Knowledge through July 31, 2010. Following qualitative review, we conducted a meta-analysis to estimate the sensitivity and specificity of CLSA for the detection of abnormal lung sounds. Of 208 articles identified, we selected eight studies for review. Most studies employed either electret microphones or piezoelectric sensors for auscultation, and Fourier Transform and Neural Network algorithms for analysis and automated classification of lung sounds. Overall sensitivity for the detection of wheezes or crackles using CLSA was 80% (95% CI 72-86%) and specificity was 85% (95% CI 78-91%). While quality data on CLSA are relatively limited, analysis of existing information suggests that CLSA can provide a relatively high specificity for detecting abnormal lung sounds such as crackles and wheezes. Further research and product development could promote the value of CLSA in research studies or its diagnostic utility in clinical settings. Copyright © 2011 Elsevier Ltd. All rights reserved.

  1. A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

    PubMed

    Oliker, Nurit; Ostfeld, Avi

    2014-03-15

    This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. The Frasnian-Famennian mass killing event(s), methods of identification and evaluation

    NASA Technical Reports Server (NTRS)

    Geldsetzer, H. H. J.

    1988-01-01

    The absence of an abnormally high number of earlier Devonian taxa from Famennian sediments was repeatedly documented and can hardly be questioned. Primary recognition of the event(s) was based on paleontological data, especially common macrofossils. Most paleontologists place the disappearance of these common forms at the gigas/triangularis contact and this boundary was recently proposed as the Frasnian-Famennian (F-F) boundary. Not unexpectedly, alternate F-F positions were suggested caused by temporary Frasnian survivors or sudden post-event radiations of new forms. Secondary supporting evidence for mass killing event(s) is supplied by trace element and stable isotope geochemistry but not with the same success as for the K/T boundary, probably due to additional 300 ma of tectonic and diagenetic overprinting. Another tool is microfacies analysis which is surprisingly rarely used even though it can explain geochemical anomalies or paleontological overlap not detectable by conventional macrofacies analysis. The combination of microfacies analysis and geochemistry was applied at two F-F sections in western Canada and showed how interdependent the two methods are. Additional F-F sections from western Canada, western United States, France, Germany and Australia were sampled or re-sampled and await geochemical/microfacies evaluation.

  3. Diagnostic accuracy of 3D-transvaginal ultrasound in detecting uterine cavity abnormalities in infertile patients as compared with hysteroscopy.

    PubMed

    Apirakviriya, Chayanis; Rungruxsirivorn, Tassawan; Phupong, Vorapong; Wisawasukmongchol, Wirach

    2016-05-01

    To assess diagnostic accuracy of 3D transvaginal ultrasound (3D-TVS) compared with hysteroscopy in detecting uterine cavity abnormalities in infertile women. This prospective observational cross-sectional study was conducted during the July 2013 to December 2013 study period. Sixty-nine women with infertility were enrolled. In the mid to late follicular phase of each subject's menstrual cycle, 3D transvaginal ultrasound and hysteroscopy were performed on the same day in each patient. Hysteroscopy is widely considered to be the gold standard method for investigation of the uterine cavity. Uterine cavity characteristics and abnormalities were recorded. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios were evaluated. Hysteroscopy was successfully performed in all subjects. Hysteroscopy diagnosed pathological findings in 22 of 69 cases (31.8%). There were 18 endometrial polyps, 3 submucous myomas, and 1 septate uterus. Three-dimensional transvaginal ultrasound in comparison with hysteroscopy had 84.1% diagnostic accuracy, 68.2% sensitivity, 91.5% specificity, 79% positive predictive value, and 86% negative predictive value. The positive and negative likelihood ratios were 8.01 and 0.3, respectively. 3D-TVS successfully detected every case of submucous myoma and uterine anomaly. For detection of endometrial polyps, 3D-TVS had 61.1% sensitivity, 91.5% specificity, and 83.1% diagnostic accuracy. 3D-TVS demonstrated 84.1% diagnostic accuracy for detecting uterine cavity abnormalities in infertile women. A significant percentage of infertile patients had evidence of uterine cavity pathology. Hysteroscopy is, therefore, recommended for accurate detection and diagnosis of uterine cavity lesion. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

    DTIC Science & Technology

    2015-07-25

    sources and can be shared among many different events, including unseen ones. Based on this idea, events can be detected by inspect- ing the individual...2013]. Partial success along this vein has also been achieved in the zero-shot setting, e.g. [Habibian et al., 2014; Wu et al., 2014], but the...candle”, “birthday cake” and “applaud- ing”. Since concepts are shared among many different classes (events) and each concept classifier can be trained

  5. Detection of Epileptic Seizure Event and Onset Using EEG

    PubMed Central

    Ahammad, Nabeel; Fathima, Thasneem; Joseph, Paul

    2014-01-01

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

  6. 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.

  7. 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

  8. CpG Oligonucleotide and Interleukin 2 stimulation enables higher cytogenetic abnormality detection rates than 12-o-tetradecanolyphorbol-13-acetate in Asian patients with B-cell chronic lymphocytic leukemia (B-CLL).

    PubMed

    Liaw, Fiona Pui San; Lau, Lai Ching; Lim, Alvin Soon Tiong; Lim, Tse Hui; Lee, Geok Yee; Tien, Sim Leng

    2014-12-01

    The present study was designed to compare abnormality detection rates using DSP30 + IL2 and 12-O-Tetradecanoylphorbol-13-acetate (TPA) in Asian patients with B-CLL. Hematological specimens from 47 patients (29 newly diagnosed, 18 relapsed) were established as 72 h-DSP30 + IL2 and TPA cultures. Standard methods were employed to identify clonal aberrations by conventional cytogenetics (CC). The B-CLL fluorescence in situ hybridization (FISH) panel comprised ATM, CEP12, D13S25, and TP53 probes. DSP30 + IL2 cultures had a higher chromosomal abnormality detection rate (67 %) compared to TPA (44 %, p < 0.001). The mean number of analyzable metaphases and abnormal metaphases per slide was also higher (p < 0.005, p < 0.001, respectively). Culture success rate, percentage of complex karyotype, and percentage of non-clonal abnormal cell were not significantly different (p > 0.05). Thirteen cases with abnormalities were found exclusively in DSP30 + IL2 cultures compared to one found solely in TPA cultures. DSP30 + IL2 cultures were comparable to the FISH panel in detecting 11q-, +12 and 17p- but not 13q-. It also has a predilection for 11q- bearing leukemic cells compared to TPA. FISH had a higher abnormality detection rate (84.1 %) compared to CC (66.0 %) with borderline significance (p = 0.051), albeit limited by its coverage. In conclusion, DSP30 + IL2 showed a higher abnormality detection rate. However, FISH is indispensable to circumvent low mitotic indices and detect subtle abnormalities.

  9. 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

  10. Cardiac abnormality prediction using HMLP network

    NASA Astrophysics Data System (ADS)

    Adnan, Ja'afar; Ahmad, K. A.; Mat, Muhamad Hadzren; Rizman, Zairi Ismael; Ahmad, Shahril

    2018-02-01

    Cardiac abnormality often occurs regardless of gender, age and races but depends on the lifestyle. This problem sometimes does not show any symptoms and usually detected once it already critical which lead to a sudden death to the patient. Basically, cardiac abnormality is the irregular electrical signal that generate by the pacemaker of the heart. This paper attempts to develop a program that can detect cardiac abnormality activity through implementation of Hybrid Multilayer Perceptron (HMLP) network. A certain amount of data of the heartbeat signals from the electrocardiogram (ECG) will be used in this project to train the MLP and HMLP network by using Modified Recursive Prediction Error (MRPE) algorithm and to test the network performance.

  11. Dysmorphometrics: the modelling of morphological abnormalities.

    PubMed

    Claes, Peter; Daniels, Katleen; Walters, Mark; Clement, John; Vandermeulen, Dirk; Suetens, Paul

    2012-02-06

    The study of typical morphological variations using quantitative, morphometric descriptors has always interested biologists in general. However, unusual examples of form, such as abnormalities are often encountered in biomedical sciences. Despite the long history of morphometrics, the means to identify and quantify such unusual form differences remains limited. A theoretical concept, called dysmorphometrics, is introduced augmenting current geometric morphometrics with a focus on identifying and modelling form abnormalities. Dysmorphometrics applies the paradigm of detecting form differences as outliers compared to an appropriate norm. To achieve this, the likelihood formulation of landmark superimpositions is extended with outlier processes explicitly introducing a latent variable coding for abnormalities. A tractable solution to this augmented superimposition problem is obtained using Expectation-Maximization. The topography of detected abnormalities is encoded in a dysmorphogram. We demonstrate the use of dysmorphometrics to measure abrupt changes in time, asymmetry and discordancy in a set of human faces presenting with facial abnormalities. The results clearly illustrate the unique power to reveal unusual form differences given only normative data with clear applications in both biomedical practice & research.

  12. Time to foster a rational approach to preventing cardiovascular morbid events.

    PubMed

    Cohn, Jay N; Duprez, Daniel A

    2008-07-29

    Efforts to prevent atherosclerotic morbid events have focused primarily on risk factor prevention and intervention. These approaches, based on the statistical association of risk factors with events, have dominated clinical practice in the last generation. Because the cardiovascular abnormalities eventuating in morbid events are detectable in the arteries and heart before the development of symptomatic disease, recent efforts have focused on identifying the presence of these abnormalities as a more sensitive and specific guide to the need for therapy. Advances in noninvasive techniques for studying the vasculature and the left ventricle now provide the opportunity to use early disease rather than risk factors as the tool for clinical decision making. A disease scoring system has been developed using 10 tests of vascular and cardiac function and structure. More extensive data to confirm the sensitivity and specificity of this scoring system and to demonstrate its utility in tracking the response to therapy are needed to justify widespread application in clinical practice.

  13. 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.

  14. Detection of abnormal living patterns for elderly living alone using support vector data description.

    PubMed

    Shin, Jae Hyuk; Lee, Boreom; Park, Kwang Suk

    2011-05-01

    In this study, we developed an automated behavior analysis system using infrared (IR) motion sensors to assist the independent living of the elderly who live alone and to improve the efficiency of their healthcare. An IR motion-sensor-based activity-monitoring system was installed in the houses of the elderly subjects to collect motion signals and three different feature values, activity level, mobility level, and nonresponse interval (NRI). These factors were calculated from the measured motion signals. The support vector data description (SVDD) method was used to classify normal behavior patterns and to detect abnormal behavioral patterns based on the aforementioned three feature values. The simulation data and real data were used to verify the proposed method in the individual analysis. A robust scheme is presented in this paper for optimally selecting the values of different parameters especially that of the scale parameter of the Gaussian kernel function involving in the training of the SVDD window length, T of the circadian rhythmic approach with the aim of applying the SVDD to the daily behavior patterns calculated over 24 h. Accuracies by positive predictive value (PPV) were 95.8% and 90.5% for the simulation and real data, respectively. The results suggest that the monitoring system utilizing the IR motion sensors and abnormal-behavior-pattern detection with SVDD are effective methods for home healthcare of elderly people living alone.

  15. 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

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

    PubMed

    Mackinlay, Andrew; Martinez, David; Baldwin, Timothy

    2012-04-30

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

  17. Visualizing how cancer chromosome abnormalities form in living cells

    Cancer.gov

    For the first time, scientists have directly observed events that lead to the formation of a chromosome abnormality that is often found in cancer cells. The abnormality, called a translocation, occurs when part of a chromosome breaks off and becomes attac

  18. Event detection for car park entries by video-surveillance

    NASA Astrophysics Data System (ADS)

    Coquin, Didier; Tailland, Johan; Cintract, Michel

    2007-10-01

    Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting car park entries, using an adaptive background learning algorithm and two indicators representing activity and identity to overcome the difficulty of tracking objects.

  19. Computerized Lung Sound Analysis as diagnostic aid for the detection of abnormal lung sounds: a systematic review and meta-analysis

    PubMed Central

    Gurung, Arati; Scrafford, Carolyn G; Tielsch, James M; Levine, Orin S; Checkley, William

    2011-01-01

    Rationale The standardized use of a stethoscope for chest auscultation in clinical research is limited by its inherent inter-listener variability. Electronic auscultation and automated classification of recorded lung sounds may help prevent some these shortcomings. Objective We sought to perform a systematic review and meta-analysis of studies implementing computerized lung sounds analysis (CLSA) to aid in the detection of abnormal lung sounds for specific respiratory disorders. Methods We searched for articles on CLSA in MEDLINE, EMBASE, Cochrane Library and ISI Web of Knowledge through July 31, 2010. Following qualitative review, we conducted a meta-analysis to estimate the sensitivity and specificity of CLSA for the detection of abnormal lung sounds. Measurements and Main Results Of 208 articles identified, we selected eight studies for review. Most studies employed either electret microphones or piezoelectric sensors for auscultation, and Fourier Transform and Neural Network algorithms for analysis and automated classification of lung sounds. Overall sensitivity for the detection of wheezes or crackles using CLSA was 80% (95% CI 72–86%) and specificity was 85% (95% CI 78–91%). Conclusions While quality data on CLSA are relatively limited, analysis of existing information suggests that CLSA can provide a relatively high specificity for detecting abnormal lung sounds such as crackles and wheezes. Further research and product development could promote the value of CLSA in research studies or its diagnostic utility in clinical setting. PMID:21676606

  20. Machine intelligence-based decision-making (MIND) for automatic anomaly detection

    NASA Astrophysics Data System (ADS)

    Prasad, Nadipuram R.; King, Jason C.; Lu, Thomas

    2007-04-01

    Any event deemed as being out-of-the-ordinary may be called an anomaly. Anomalies by virtue of their definition are events that occur spontaneously with no prior indication of their existence or appearance. Effects of anomalies are typically unknown until they actually occur, and their effects aggregate in time to show noticeable change from the original behavior. An evolved behavior would in general be very difficult to correct unless the anomalous event that caused such behavior can be detected early, and any consequence attributed to the specific anomaly. Substantial time and effort is required to back-track the cause for abnormal behavior and to recreate the event sequence leading to abnormal behavior. There is a critical need therefore to automatically detect anomalous behavior as and when they may occur, and to do so with the operator in the loop. Human-machine interaction results in better machine learning and a better decision-support mechanism. This is the fundamental concept of intelligent control where machine learning is enhanced by interaction with human operators, and vice versa. The paper discusses a revolutionary framework for the characterization, detection, identification, learning, and modeling of anomalous behavior in observed phenomena arising from a large class of unknown and uncertain dynamical systems.

  1. 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.

  2. Radiologists' confidence in detecting abnormalities on chest images and their subjective judgments of image quality

    NASA Astrophysics Data System (ADS)

    King, Jill L.; Gur, David; Rockette, Howard E.; Curtin, Hugh D.; Obuchowski, Nancy A.; Thaete, F. Leland; Britton, Cynthia A.; Metz, Charles E.

    1991-07-01

    The relationship between subjective judgments of image quality for the performance of specific detection tasks and radiologists' confidence level in arriving at correct diagnoses was investigated in two studies in which 12 readers, using a total of three different display environments, interpreted a series of 300 PA chest images. The modalities used were conventional films, laser-printed films, and high-resolution CRT display of digitized images. For the detection of interstitial disease, nodules, and pneumothoraces, there was no statistically significant correlation (Spearman rho) between subjective ratings of quality and radiologists' confidence in detecting these abnormalities. However, in each study, for all modalities and all readers but one, a small but statistically significant correlation was found between the radiologists' ability to correctly and confidently rule out interstitial disease and their subjective ratings of image quality.

  3. Automatic detection of freezing of gait events in patients with Parkinson's disease.

    PubMed

    Tripoliti, Evanthia E; Tzallas, Alexandros T; Tsipouras, Markos G; Rigas, George; Bougia, Panagiota; Leontiou, Michael; Konitsiotis, Spiros; Chondrogiorgi, Maria; Tsouli, Sofia; Fotiadis, Dimitrios I

    2013-04-01

    The aim of this study is to detect freezing of gait (FoG) events in patients suffering from Parkinson's disease (PD) using signals received from wearable sensors (six accelerometers and two gyroscopes) placed on the patients' body. For this purpose, an automated methodology has been developed which consists of four stages. In the first stage, missing values due to signal loss or degradation are replaced and then (second stage) low frequency components of the raw signal are removed. In the third stage, the entropy of the raw signal is calculated. Finally (fourth stage), four classification algorithms have been tested (Naïve Bayes, Random Forests, Decision Trees and Random Tree) in order to detect the FoG events. The methodology has been evaluated using several different configurations of sensors in order to conclude to the set of sensors which can produce optimal FoG episode detection. Signals recorded from five healthy subjects, five patients with PD who presented the symptom of FoG and six patients who suffered from PD but they do not present FoG events. The signals included 93 FoG events with 405.6s total duration. The results indicate that the proposed methodology is able to detect FoG events with 81.94% sensitivity, 98.74% specificity, 96.11% accuracy and 98.6% area under curve (AUC) using the signals from all sensors and the Random Forests classification algorithm. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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

    DOE PAGES

    Pilger, Christoph; Ceranna, Lars; Ross, J. Ole; ...

    2015-03-18

    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 individualmore » 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. As a result, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.« less

  5. Solar Demon: near real-time solar eruptive event detection on SDO/AIA images

    NASA Astrophysics Data System (ADS)

    Kraaikamp, Emil; Verbeeck, Cis

    Solar flares, dimmings and EUV waves have been observed routinely in extreme ultra-violet (EUV) images of the Sun since 1996. These events are closely associated with coronal mass ejections (CMEs), and therefore provide useful information for early space weather alerts. The Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) generates such a massive dataset that it becomes impossible to find most of these eruptive events manually. Solar Demon is a set of automatic detection algorithms that attempts to solve this problem by providing both near real-time warnings of eruptive events and a catalog of characterized events. Solar Demon has been designed to detect and characterize dimmings, EUV waves, as well as solar flares in near real-time on SDO/AIA data. The detection modules are running continuously at the Royal Observatory of Belgium on both quick-look data and synoptic science data. The output of Solar Demon can be accessed in near real-time on the Solar Demon website, and includes images, movies, light curves, and the numerical evolution of several parameters. Solar Demon is the result of collaboration between the FP7 projects AFFECTS and COMESEP. Flare detections of Solar Demon are integrated into the COMESEP alert system. Here we present the Solar Demon detection algorithms and their output. We will focus on the algorithm and its operational implementation. Examples of interesting flare, dimming and EUV wave events, and general statistics of the detections made so far during solar cycle 24 will be presented as well.

  6. LAN attack detection using Discrete Event Systems.

    PubMed

    Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

    2011-01-01

    Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Four families with immunodeficiency and chromosome abnormalities.

    PubMed Central

    Candy, D C; Hayward, A R; Hughes, D T; Layward, L; Soothill, J F

    1979-01-01

    Six children, with severe deficiency of some or all of the immunoglobulins and minor somatic abnormalities, had chromosomal abnormalities: (1) 45,XY,t(13q/18q), (2) 46,XY,21ps +, (3) two brothers 46,XY (inv. 7) (4) 45,X,t(11p/10p)/46X,iXq,t(11p/10p) and, (5) in addendum, 45,XX,-18;46,XX, r18. The chromosome abnormalities were detected in B- as well as T-lymphocytes (as evidenced by using both PHA- and PWM-stimulated cultures) in all probands, but one was mosaic in PHA culture, although all his PWM-stimulated cells were abnormal. Chromosomal variants were also detected in relatives of three and immunodeficiency in relatives of two. Images Fig. 1 Fig. 3 PMID:314782

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  9. Improved detection rate of cytogenetic abnormalities in chronic lymphocytic leukemia and other mature B-cell neoplasms with use of CpG-oligonucleotide DSP30 and interleukin 2 stimulation.

    PubMed

    Shi, Min; Cipollini, Matthew J; Crowley-Bish, Patricia A; Higgins, Anne W; Yu, Hongbo; Miron, Patricia M

    2013-05-01

    Detection of cytogenetic abnormalities requires successful culture of the clonal population to obtain metaphase chromosomes for study, and as such, has been hampered by low mitotic indices of mature B cells in culture. Our study presents data on the improved abnormality detection rate with the use of a CpG-oligonucleotide/interleukin 2 (OL/IL-2) culture protocol for mature B-cell neoplasms, including chronic lymphocytic leukemia (CLL) and non-CLL specimens. The increased detection rate of abnormalities, compared with unstimulated culture and traditional pokeweed mitogen culture, was statistically significant for both CLL and non-CLL neoplasms. For CLL specimens, our data also showed that for cytogenetically visible aberrations, OL/IL-2 was as, if not more, sensitive than detection with interphase fluorescence in situ hybridization (iFISH). Use of OL/IL-2 allowed a number of abnormalities to be detected, which were not covered by specific iFISH panels, especially balanced translocations. Therefore, OL/IL-2 stimulation improves diagnostic sensitivity and increases discovery rate of novel prognostic findings.

  10. 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

  11. Autonomous Detection of Eruptions, Plumes, and Other Transient Events in the Outer Solar System

    NASA Astrophysics Data System (ADS)

    Bunte, M. K.; Lin, Y.; Saripalli, S.; Bell, J. F.

    2012-12-01

    The outer solar system abounds with visually stunning examples of dynamic processes such as eruptive events that jettison materials from satellites and small bodies into space. The most notable examples of such events are the prominent volcanic plumes of Io, the wispy water jets of Enceladus, and the outgassing of comet nuclei. We are investigating techniques that will allow a spacecraft to autonomously detect those events in visible images. This technique will allow future outer planet missions to conduct sustained event monitoring and automate prioritization of data for downlink. Our technique detects plumes by searching for concentrations of large local gradients in images. Applying a Scale Invariant Feature Transform (SIFT) to either raw or calibrated images identifies interest points for further investigation based on the magnitude and orientation of local gradients in pixel values. The interest points are classified as possible transient geophysical events when they share characteristics with similar features in user-classified images. A nearest neighbor classification scheme assesses the similarity of all interest points within a threshold Euclidean distance and classifies each according to the majority classification of other interest points. Thus, features marked by multiple interest points are more likely to be classified positively as events; isolated large plumes or multiple small jets are easily distinguished from a textured background surface due to the higher magnitude gradient of the plume or jet when compared with the small, randomly oriented gradients of the textured surface. We have applied this method to images of Io, Enceladus, and comet Hartley 2 from the Voyager, Galileo, New Horizons, Cassini, and Deep Impact EPOXI missions, where appropriate, and have successfully detected up to 95% of manually identifiable events that our method was able to distinguish from the background surface and surface features of a body. Dozens of distinct features

  12. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. The rate of transient beta frequency events predicts behavior across tasks and species

    PubMed Central

    Law, Robert; Tsutsui, Shawn; Moore, Christopher I; Jones, Stephanie R

    2017-01-01

    Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and/or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations. PMID:29106374

  14. Real-time surveillance for abnormal events: the case of influenza outbreaks.

    PubMed

    Rao, Yao; McCabe, Brendan

    2016-06-15

    This paper introduces a method of surveillance using deviations from probabilistic forecasts. Realised observations are compared with probabilistic forecasts, and the "deviation" metric is based on low probability events. If an alert is declared, the algorithm continues to monitor until an all-clear is announced. Specifically, this article addresses the problem of syndromic surveillance for influenza (flu) with the intention of detecting outbreaks, due to new strains of viruses, over and above the normal seasonal pattern. The syndrome is hospital admissions for flu-like illness, and hence, the data are low counts. In accordance with the count properties of the observations, an integer-valued autoregressive process is used to model flu occurrences. Monte Carlo evidence suggests the method works well in stylised but somewhat realistic situations. An application to real flu data indicates that the ideas may have promise. The model estimated on a short run of training data did not declare false alarms when used with new observations deemed in control, ex post. The model easily detected the 2009 H1N1 outbreak. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  15. Psychopathic traits associated with abnormal hemodynamic activity in salience and default mode networks during auditory oddball task.

    PubMed

    Anderson, Nathaniel E; Maurer, J Michael; Steele, Vaughn R; Kiehl, Kent A

    2018-06-01

    Psychopathy is a personality disorder accompanied by abnormalities in emotional processing and attention. Recent theoretical applications of network-based models of cognition have been used to explain the diverse range of abnormalities apparent in psychopathy. Still, the physiological basis for these abnormalities is not well understood. A significant body of work has examined psychopathy-related abnormalities in simple attention-based tasks, but these studies have largely been performed using electrocortical measures, such as event-related potentials (ERPs), and they often have been carried out among individuals with low levels of psychopathic traits. In this study, we examined neural activity during an auditory oddball task using functional magnetic resonance imaging (fMRI) during a simple auditory target detection (oddball) task among 168 incarcerated adult males, with psychopathic traits assessed via the Hare Psychopathy Checklist-Revised (PCL-R). Event-related contrasts demonstrated that the largest psychopathy-related effects were apparent between the frequent standard stimulus condition and a task-off, implicit baseline. Negative correlations with interpersonal-affective dimensions (Factor 1) of the PCL-R were apparent in regions comprising default mode and salience networks. These findings support models of psychopathy describing impaired integration across functional networks. They additionally corroborate reports which have implicated failures of efficient transition between default mode and task-positive networks. Finally, they demonstrate a neurophysiological basis for abnormal mobilization of attention and reduced engagement with stimuli that have little motivational significance among those with high psychopathic traits.

  16. Detection of planets in extremely weak central perturbation microlensing events via next-generation ground-based surveys

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

    Chung, Sun-Ju; Lee, Chung-Uk; Koo, Jae-Rim, E-mail: sjchung@kasi.re.kr, E-mail: leecu@kasi.re.kr, E-mail: koojr@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 EWCPmore » 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.« less

  17. 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.

  18. The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers.

    PubMed

    Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Hunninghake, Gary M; Putman, Rachel K; Onieva, Jorge; Martinez, Fernando J; Choi, Augustine M; Lynch, David A; Hatabu, Hiroto; Rosas, Ivan O; Estepar, Raul San Jose; Washko, George R

    2017-08-01

    Previous investigation suggests that visually detected interstitial changes in the lung parenchyma of smokers are highly clinically relevant and predict outcomes, including death. Visual subjective analysis to detect these changes is time-consuming, insensitive to subtle changes, and requires training to enhance reproducibility. Objective detection of such changes could provide a method of disease identification without these limitations. The goal of this study was to develop and test a fully automated image processing tool to objectively identify radiographic features associated with interstitial abnormalities in the computed tomography scans of a large cohort of smokers. An automated tool that uses local histogram analysis combined with distance from the pleural surface was used to detect radiographic features consistent with interstitial lung abnormalities in computed tomography scans from 2257 individuals from the Genetic Epidemiology of COPD study, a longitudinal observational study of smokers. The sensitivity and specificity of this tool was determined based on its ability to detect the visually identified presence of these abnormalities. The tool had a sensitivity of 87.8% and a specificity of 57.5% for the detection of interstitial lung abnormalities, with a c-statistic of 0.82, and was 100% sensitive and 56.7% specific for the detection of the visual subtype of interstitial abnormalities called fibrotic parenchymal abnormalities, with a c-statistic of 0.89. In smokers, a fully automated image processing tool is able to identify those individuals who have interstitial lung abnormalities with moderate sensitivity and specificity. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  19. Options for managing low grade cervical abnormalities detected at screening: cost effectiveness study.

    PubMed

    2009-07-28

    To estimate the cost effectiveness of alternative methods of managing low grade cervical cytological abnormalities detected at routine screening. Design Cost analysis within multicentre individually randomised controlled trial. Grampian, Tayside, and Nottingham. 4201 women with low grade abnormalities. Cytological surveillance or referral to colposcopy for biopsy and recall if necessary or referral to colposcopy with immediate treatment based on colposcopic appearance. Data on resource use collected from participants throughout the duration of the trial (36 months), enabling the estimation of both the direct (health care) and indirect (time and travel) costs of management. Quality of life assessed at recruitment and at 12, 18, 24, and 30 months, using the EQ-5D instrument. Economic outcomes expressed as costs per case of cervical intraepithelial neoplasia (grade II or worse) detected, by trial arm, as confirmed at exit, and cost utility ratios (cost per quality adjusted life year (QALY) gained) for the three pairwise comparisons of trial arms. The mean three year discounted costs of surveillance, immediate treatment, and biopsy and recall were pound150.20 (euro177, $249), pound240.30 (euro283, $415), and pound241.10 (euro284, $4000), respectively, viewed from the health service perspective. From the social perspective, mean discounted costs were pound204.40 (euro241, $339), pound339.90 (euro440, $563), and pound327.50 (euro386, $543), respectively. Estimated at the means, the incremental cost effectiveness ratios indicated that immediate treatment was dominated by the other two management methods, although it did offer the lowest cost per case of cervical intraepithelial neoplasia detected and treated. The pronounced skews in the distributions indicated that probabilistic uncertainty analysis would offer more meaningful estimates of cost effectiveness. The observed differences in the cost effectiveness ratios between trial arms were not significant. Judged within

  20. Abnormal Mitochondrial Dynamics and Synaptic Degeneration as Early Events in Alzheimer’s Disease: Implications to Mitochondria-Targeted Antioxidant Therapeutics

    PubMed Central

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

    2011-01-01

    Synaptic pathology and mitochondrial oxidative damage are early events in Alzheimer’s disease (AD) progression. Loss of synapses and synaptic damage are the best correlate of cognitive deficits found in AD patients. Recent research on amyloid bet (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 that 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. PMID:22037588

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

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

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.

    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.

  2. Very low frequency earthquakes (VLFEs) detected during episodic tremor and slip (ETS) events in Cascadia using a match filter method indicate repeating events

    NASA Astrophysics Data System (ADS)

    Hutchison, A. A.; Ghosh, A.

    2016-12-01

    Very low frequency earthquakes (VLFEs) occur in transitional zones of faults, releasing seismic energy in the 0.02-0.05 Hz frequency band over a 90 s duration and typically have magntitudes within the range of Mw 3.0-4.0. VLFEs can occur down-dip of the seismogenic zone, where they can transfer stress up-dip potentially bringing the locked zone closer to a critical failure stress. VLFEs also occur up-dip of the seismogenic zone in a region along the plate interface that can rupture coseismically during large megathrust events, such as the 2011 Tohoku-Oki earthquake [Ide et al., 2011]. VLFEs were first detected in Cascadia during the 2011 episodic tremor and slip (ETS) event, occurring coincidentally with tremor [Ghosh et al., 2015]. However, during the 2014 ETS event, VLFEs were spatially and temporally asynchronous with tremor activity [Hutchison and Ghosh, 2016]. Such contrasting behaviors remind us that the mechanics behind such events remain elusive, yet they are responsible for the largest portion of the moment release during an ETS event. Here, we apply a match filter method using known VLFEs as template events to detect additional VLFEs. Using a grid-search centroid moment tensor inversion method, we invert stacks of the resulting match filter detections to ensure moment tensor solutions are similar to that of the respective template events. Our ability to successfully employ a match filter method to VLFE detection in Cascadia intrinsically indicates that these events can be repeating, implying that the same asperities are likely responsible for generating multiple VLFEs.

  3. Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records.

    PubMed

    Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane

    2015-01-01

    We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.

  4. Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records

    PubMed Central

    Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane

    2015-01-01

    We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events. PMID:26536596

  5. 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.

  6. Description and detection of burst events in turbulent flows

    NASA Astrophysics Data System (ADS)

    Schmid, P. J.; García-Gutierrez, A.; Jiménez, J.

    2018-04-01

    A mathematical and computational framework is developed for the detection and identification of coherent structures in turbulent wall-bounded shear flows. In a first step, this data-based technique will use an embedding methodology to formulate the fluid motion as a phase-space trajectory, from which state-transition probabilities can be computed. Within this formalism, a second step then applies repeated clustering and graph-community techniques to determine a hierarchy of coherent structures ranked by their persistencies. This latter information will be used to detect highly transitory states that act as precursors to violent and intermittent events in turbulent fluid motion (e.g., bursts). Used as an analysis tool, this technique allows the objective identification of intermittent (but important) events in turbulent fluid motion; however, it also lays the foundation for advanced control strategies for their manipulation. The techniques are applied to low-dimensional model equations for turbulent transport, such as the self-sustaining process (SSP), for varying levels of complexity.

  7. Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

    NASA Astrophysics Data System (ADS)

    Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.

    2017-12-01

    Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.

  8. Biochemical abnormalities in neonatal seizures.

    PubMed

    Sood, Arvind; Grover, Neelam; Sharma, Roshan

    2003-03-01

    The presence of seizure does not constitute a diagnoses but it is a symptom of an underlying central nervous system disorder due to systemic or biochemical disturbances. Biochemical disturbances occur frequently in the neonatal seizures either as an underlying cause or as an associated abnormality. In their presence, it is difficult to control seizure and there is a risk of further brain damage. Early recognition and treatment of biochemical disturbances is essential for optimal management and satisfactory long term outcome. The present study was conducted in the department of pediatrics in IGMC Shimla on 59 neonates. Biochemical abnormalities were detected in 29 (49.15%) of cases. Primary metabolic abnormalities occurred in 10(16.94%) cases of neonatal seizures, most common being hypocalcaemia followed by hypoglycemia, other metabolic abnormalities include hypomagnesaemia and hyponateremia. Biochemical abnormalities were seen in 19(38.77%) cases of non metabolic seizure in neonates. Associated metabolic abnormalities were observed more often with Hypoxic-ischemic-encephalopathy (11 out of 19) cases and hypoglycemia was most common in this group. No infant had hyponateremia, hyperkelemia or low zinc level.

  9. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Detecting Noisy Events Using Waveform Cross-Correlation at Superarrays of Seismic Stations

    NASA Astrophysics Data System (ADS)

    von Seggern, D. H.; Tibuleac, I. M.

    2007-12-01

    Cross-correlation using master events, followed by stacking of the correlation series, has been shown to dramatically improve detection thresholds of small-to-medium seismic arrays. With the goal of lowering the detection threshold, determining relative magnitudes or moments, and characterizing sources by empirical Green's functions, we extend the cross-correlation methodology to include "superarrays" of seismic stations. The superarray concept naturally brings further benefits over conventional arrays and single-stations due to the fact that many distances and azimuths can be sampled. This extension is straightforward given the ease with which regional or global data from various stations or arrays can be currently accessed and combined into a single database. We demonstrate the capability of superarrays to detect and analyze events which lie below the detection threshold. This is aided by applying an F-statistic detector to the superarray cross-correlation stack and its components. Our first example illustrates the use of a superarray consisting of the Southern Great Basin Digital Seismic Network, a small-aperture array (NVAR) in Mina, Nevada and the Earthscope Transportable Array to detect events in California-Nevada areas. In our second example, we use a combination of small-to-medium arrays and single stations to study the rupture of the great Sumatra earthquake of 26 December 2004 and to detect its early aftershocks. The location and times of "detected" events are confirmed using a frequency- wavenumber method at the small-to-medium arrays. We propose that ad hoc superarrays can be used in many studies where conventional approaches previously used only single arrays or groups of single stations. The availability of near-real-time data from many networks and of archived data from, for instance, IRIS makes possible the easy assembly of superarrays. Furthermore, the continued improvement of seismic data availability and the continued growth in the number of

  11. Congenital left ventricular wall abnormalities in adults detected by gated cardiac multidetector computed tomography: clefts, aneurysms, diverticula and terminology problems.

    PubMed

    Erol, Cengiz; Koplay, Mustafa; Olcay, Ayhan; Kivrak, Ali Sami; Ozbek, Seda; Seker, Mehmet; Paksoy, Yahya

    2012-11-01

    Our aim was to evaluate congenital left ventricular wall abnormalities (clefts, aneurysms and diverticula), describe and illustrate imaging features, discuss terminology problems and determine their prevalence detected by cardiac CT in a single center. Coronary CT angiography images of 2093 adult patients were evaluated retrospectively in order to determine congenital left ventricular wall abnormalities. The incidence of left ventricular clefts (LVC) was 6.7% (141 patients) and statistically significant difference was not detected between the sexes regarding LVC (P=0.5). LVCs were single in 65.2% and multiple in 34.8% of patients. They were located at the basal to mid inferoseptal segment of the left ventricle in 55.4%, the basal to mid anteroseptal segment in 24.1%, basal to mid inferior segment in 17% and septal-apical septal segment in 3.5% of cases. The cleft length ranged from 5 to 22 mm (mean 10.5 mm) and they had a narrow connection with the left ventricle (mean 2.5 mm). They were contractile with the left ventricle and obliterated during systole. Congenital left ventricular septal aneurysm that was located just under the aortic valve was detected in two patients (0.1%). No case of congenital left ventricular diverticulum was detected. Cardiac CT allows us to recognize congenital left ventricular wall abnormalities which have been previously overlooked in adults. LVC is a congenital structural variant of the myocardium, is seen more frequently than previously reported and should be differentiated from aneurysm and diverticulum for possible catastrophic complications of the latter two. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  12. 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.

  13. Advances in understanding paternally transmitted Chromosomal Abnormalities

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

    Marchetti, F; Sloter, E; Wyrobek, A J

    2001-03-01

    Multicolor FISH has been adapted for detecting the major types of chromosomal abnormalities in human sperm including aneuploidies for clinically-relevant chromosomes, chromosomal aberrations including breaks and rearrangements, and other numerical abnormalities. The various sperm FISH assays have been used to evaluate healthy men, men of advanced age, and men who have received mutagenic cancer therapy. The mouse has also been used as a model to investigate the mechanism of paternally transmitted genetic damage. Sperm FISH for the mouse has been used to detect chromosomally abnormal mouse sperm, while the PAINT/DAPI analysis of mouse zygotes has been used to evaluate themore » types of chromosomal defects that can be paternally transmitted to the embryo and their effects on embryonic development.« less

  14. Fluorescence immunophenotyping and interphase cytogenetics (FICTION) detects BCL6 abnormalities, including gene amplification, in most cases of nodular lymphocyte-predominant Hodgkin lymphoma.

    PubMed

    Bakhirev, Alexei G; Vasef, Mohammad A; Zhang, Qian-Yun; Reichard, Kaaren K; Czuchlewski, David R

    2014-04-01

    BCL6 translocations are a frequent finding in B-cell lymphomas of diverse subtypes, including some cases of nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL). However, reliable analysis of BCL6 rearrangements using fluorescence in situ hybridization is difficult in NLPHL because of the relative paucity of neoplastic cells. Combined immunofluorescence microscopy and fluorescence in situ hybridization, or fluorescence immunophenotyping and interphase cytogenetics as a tool for the investigation of neoplasms (FICTION), permits targeted analysis of neoplastic cells. To better define the spectrum of BCL6 abnormalities in NLPHL using FICTION analysis. We performed an optimized FICTION analysis of 24 lymph nodes, including 11 NLPHL, 5 follicular hyperplasia with prominent progressive transformation of germinal centers, and 8 follicular hyperplasia without progressive transformation of germinal centers. BCL6 rearrangement was identified in 5 of 11 cases of NLPHL (46%). In addition, BCL6 gene amplification, with large clusters of BCL6 signals in the absence of chromosome 3 aneuploidy, was detected in 3 of 11 cases of NLPHL (27%). One NLPHL showed extra copies of BCL6 present in conjunction with multiple copies of chromosome 3. Altogether, we detected BCL6 abnormalities in 9 of 11 cases of NLPHL (82%). None of the progressive transformation of germinal centers or follicular hyperplasia cases showed BCL6 abnormalities by FICTION. To our knowledge, this is the first report of BCL6 gene amplification in NLPHL. Our optimized protocol for FICTION permits detection of cytogenetic abnormalities in most NLPHL cases and may represent a useful ancillary diagnostic technique.

  15. Electrocardiographic abnormalities and relative bradycardia in patients with hantavirus-induced nephropathia epidemica.

    PubMed

    Kitterer, Daniel; Greulich, Simon; Grün, Stefan; Segerer, Stephan; Mustonen, Jukka; Alscher, M Dominik; Braun, Niko; Latus, Joerg

    2016-09-01

    Nephropathia epidemica (NE), caused by Puumala virus (PUUV), is characterized by acute kidney injury (AKI) and thrombocytopenia. Cardiac involvement with electrocardiographic (ECG) abnormalities has been previously reported in NE; however, its prognostic value is unknown. Relative bradycardia is an important clinical sign in various infectious diseases, and previous smaller studies have described pulse-temperature deficit in patients with PUUV infection. We performed a cross-sectional survey of 471 adult patients with serologically confirmed NE. Data were collected retrospectively from medical records and prospectively at follow-up visits. Patients for whom ECGs were recorded during the acute phase of disease were enrolled retrospectively (n=263). Three patients were excluded because of documented pre-existing ECG abnormalities prior to NE. All patients with ECG abnormalities during the acute phase underwent follow-up. A total of 46 patients had ECG abnormalities at the time of admission to hospital (18%). T-wave inversion was the most frequent ECG abnormality (n=31 patients), followed by ST segment changes (nine patients with elevation and six with depression). No major adverse cardiac events occurred during follow-up (median 37months; range 34-63months). Of note, ECG abnormalities reverted to normal in the majority of the patients during follow-up. During the acute phase of NE, 149 of 186 patients had relative bradycardia, without implications for disease course. Transient ECG abnormalities were detected in 18% of patients during acute NE but were not associated with negative cardiovascular outcome. Relative bradycardia was identified in 80% of the patients with acute NE. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

  16. Automated lung sound analysis for detecting pulmonary abnormalities.

    PubMed

    Datta, Shreyasi; Dutta Choudhury, Anirban; Deshpande, Parijat; Bhattacharya, Sakyajit; Pal, Arpan

    2017-07-01

    Identification of pulmonary diseases comprises of accurate auscultation as well as elaborate and expensive pulmonary function tests. Prior arts have shown that pulmonary diseases lead to abnormal lung sounds such as wheezes and crackles. This paper introduces novel spectral and spectrogram features, which are further refined by Maximal Information Coefficient, leading to the classification of healthy and abnormal lung sounds. A balanced lung sound dataset, consisting of publicly available data and data collected with a low-cost in-house digital stethoscope are used. The performance of the classifier is validated over several randomly selected non-overlapping training and validation samples and tested on separate subjects for two separate test cases: (a) overlapping and (b) non-overlapping data sources in training and testing. The results reveal that the proposed method sustains an accuracy of 80% even for non-overlapping data sources in training and testing.

  17. Easiness of use and validity testing of VS-SENSE device for detection of abnormal vaginal flora and bacterial vaginosis.

    PubMed

    Donders, Gilbert G G; Marconi, Camila; Bellen, Gert

    2010-01-01

    Accessing vaginal pH is fundamental during gynaecological visit for the detection of abnormal vaginal flora (AVF), but use of pH strips may be time-consuming and difficult to interpret. The aim of this study was to evaluate the VS-SENSE test (Common Sense Ltd, Caesarea, Israel) as a tool for the diagnosis of AVF and its correlation with abnormal pH and bacterial vaginosis (BV). The study population consisted of 45 women with vaginal pH ≥ 4.5 and 45 women with normal pH. Vaginal samples were evaluated by VS-SENSE test, microscopy and microbiologic cultures. Comparing with pH strips results, VS-SENSE test specificity was 97.8% and sensitivity of 91%. All severe cases of BV and aerobic vaginitis (AV) were detected by the test. Only one case with normal pH had an unclear result. Concluding, VS-SENSE test is easy to perform, and it correlates with increased pH, AVF, and the severe cases of BV and AV.

  18. Development of an algorithm for automatic detection and rating of squeak and rattle events

    NASA Astrophysics Data System (ADS)

    Chandrika, Unnikrishnan Kuttan; Kim, Jay H.

    2010-10-01

    A new algorithm for automatic detection and rating of squeak and rattle (S&R) events was developed. The algorithm utilizes the perceived transient loudness (PTL) that approximates the human perception of a transient noise. At first, instantaneous specific loudness time histories are calculated over 1-24 bark range by applying the analytic wavelet transform and Zwicker loudness transform to the recorded noise. Transient specific loudness time histories are then obtained by removing estimated contributions of the background noise from instantaneous specific loudness time histories. These transient specific loudness time histories are summed to obtain the transient loudness time history. Finally, the PTL time history is obtained by applying Glasberg and Moore temporal integration to the transient loudness time history. Detection of S&R events utilizes the PTL time history obtained by summing only 18-24 barks components to take advantage of high signal-to-noise ratio in the high frequency range. A S&R event is identified when the value of the PTL time history exceeds the detection threshold pre-determined by a jury test. The maximum value of the PTL time history is used for rating of S&R events. Another jury test showed that the method performs much better if the PTL time history obtained by summing all frequency components is used. Therefore, r ating of S&R events utilizes this modified PTL time history. Two additional jury tests were conducted to validate the developed detection and rating methods. The algorithm developed in this work will enable automatic detection and rating of S&R events with good accuracy and minimum possibility of false alarm.

  19. Ontology-based knowledge management for personalized adverse drug events detection.

    PubMed

    Cao, Feng; Sun, Xingzhi; Wang, Xiaoyuan; Li, Bo; Li, Jing; Pan, Yue

    2011-01-01

    Since Adverse Drug Event (ADE) has become a leading cause of death around the world, there arises high demand for helping clinicians or patients to identify possible hazards from drug effects. Motivated by this, we present a personalized ADE detection system, with the focus on applying ontology-based knowledge management techniques to enhance ADE detection services. The development of electronic health records makes it possible to automate the personalized ADE detection, i.e., to take patient clinical conditions into account during ADE detection. Specifically, we define the ADE ontology to uniformly manage the ADE knowledge from multiple sources. We take advantage of the rich semantics from the terminology SNOMED-CT and apply it to ADE detection via the semantic query and reasoning.

  20. 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

  1. 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.

  2. 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

  3. Eventogram: A Visual Representation of Main Events in Biomedical Signals.

    PubMed

    Elgendi, Mohamed

    2016-09-22

    Biomedical signals carry valuable physiological information and many researchers have difficulty interpreting and analyzing long-term, one-dimensional, quasi-periodic biomedical signals. Traditionally, biomedical signals are analyzed and visualized using periodogram, spectrogram, and wavelet methods. However, these methods do not offer an informative visualization of main events within the processed signal. This paper attempts to provide an event-related framework to overcome the drawbacks of the traditional visualization methods and describe the main events within the biomedical signal in terms of duration and morphology. Electrocardiogram and photoplethysmogram signals are used in the analysis to demonstrate the differences between the traditional visualization methods, and their performance is compared against the proposed method, referred to as the " eventogram " in this paper. The proposed method is based on two event-related moving averages that visualizes the main time-domain events in the processed biomedical signals. The traditional visualization methods were unable to find dominant events in processed signals while the eventogram was able to visualize dominant events in signals in terms of duration and morphology. Moreover, eventogram -based detection algorithms succeeded with detecting main events in different biomedical signals with a sensitivity and positive predictivity >95%. The output of the eventogram captured unique patterns and signatures of physiological events, which could be used to visualize and identify abnormal waveforms in any quasi-periodic signal.

  4. 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

  5. Enhanced Detection of Chromosomal Abnormalities in Chronic Lymphocytic Leukemia by Conventional Cytogenetics Using CpG Oligonucleotide in Combination with Pokeweed Mitogen and Phorbol Myristate Acetate

    PubMed Central

    Muthusamy, Natarajan; Breidenbach, Heather; Andritsos, Leslie; Flynn, Joseph; Jones, Jeffrey; Ramanunni, Asha; Mo, Xiaokui; Jarjoura, David; Byrd, John C.; Heerema, Nyla A.

    2011-01-01

    Reproducible cytogenetic analysis in CLL has been limited by the inability to obtain reliable metaphase cells for analysis. CpG oligonucleotide and cytokine stimulation have been shown to improve metaphase analysis of CLL cytogenetic abnormalities, but is limited by variability in the cytokine receptor levels, stability and biological activity of the cytokine in culture conditions and high costs associated with these reagents. We report here use of a novel, stable CpG, GNKG168 along with pokeweed mitogen (PWM) and phorbol 12-myristate 13-acetate (PMA) for conventional cytogenetic assessment in CLL. We demonstrate that the combined use of GNKG168+PWM/PMA increased the sensitivity of detection of chromosomal abnormalities compared to PWM/PMA (n=207, odds ratio=2.2, p=0.0002) and GNKG168 (n=219, odds ratio=1.5, p=0.0452). Further, a significant increase in sensitivity to detect complexity ≥3 with GNKG168+PWM/PMA compared to GNKG168 alone (odds ratio 8.0, p=0.0022) or PWM/PMA alone (odds ratio 9.6, p=0.0007) was observed. The trend toward detection of higher complexity was significantly greater with GNKG168+PWM/PMA compared to GNKG168 alone (p=0.0412). The increased sensitivity was mainly attributed to the addition of PWM/PMA with GNKG168 because GNKG168 alone showed no difference in sensitivity for detection of complex abnormalities (p=0.17). Comparison of fluorescence in situ hybridization (FISH) results with karyotypic results showed a high degree of consistency, although some complex karyotypes were present in cases with no adverse FISH abnormality. These studies provide evidence for potential use of GNKG168 in combination with PWM and PMA in karyotypic analysis of CLL patient samples to better identify chromosomal abnormalities for risk stratification. PMID:21494579

  6. 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

  7. How study of respiratory physiology aided our understanding of abnormal brain function in panic disorder.

    PubMed

    Sinha, S; Papp, L A; Gorman, J M

    2000-12-01

    There is a substantial body of literature demonstrating that stimulation of respiration (hyperventilation) is a common event in panic disorder patients during panic attack episodes. Further, a number of abnormalities in respiration, such as enhanced CO2 sensitivity, have been detected in panic patients. This led some to posit that there is a fundamental abnormality in the physiological mechanisms that control breathing in panic disorder and that this abnormality is central to illness etiology. More recently, however, evidence has accumulated suggesting that respiratory physiology is normal in panic patients and that their tendency to hyperventilate and to react with panic to respiratory stimulants like CO2 represents the triggering of a hypersensitive fear network. The fear network anatomy is taken from preclinical studies that have identified the brain pathways that subserve the acquisition and maintenance of conditioned fear. Included are the amygdala and its brain stem projections, the hippocampus, and the medial prefrontal cortex. Although attempts to image this system in patients during panic attacks have been difficult, the theory that the fear network is operative and hyperactive in panic patients explains why both medication and psychosocial therapies are clearly effective. Studies of respiration in panic disorder are an excellent example of the way in which peripheral markers have guided researchers in developing a more complete picture of the neural events that occur in psychopathological states.

  8. 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. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Expanding the 2011 Prague, OK Event Catalog: Detections, Relocations, and Stress Drop Estimates

    NASA Astrophysics Data System (ADS)

    Clerc, F.; Cochran, E. S.; Dougherty, S. L.; Keranen, K. M.; Harrington, R. M.

    2016-12-01

    The Mw 5.6 earthquake occurring on 6 Nov. 2011, near Prague, OK, is thought to have been triggered by a Mw 4.8 foreshock, which was likely induced by fluid injection into local wastewater disposal wells [Keranen et al., 2013; Sumy et al., 2014]. Previous stress drop estimates for the sequence have suggested values lower than those for most Central and Eastern U.S. tectonic events of similar magnitudes [Hough, 2014; Sun & Hartzell, 2014; Sumy & Neighbors et al., 2016]. Better stress drop estimates allow more realistic assessment of seismic hazard and more effective regulation of wastewater injection. More reliable estimates of source properties may help to differentiate induced events from natural ones. Using data from local and regional networks, we perform event detections, relocations, and stress drop calculations of the Prague aftershock sequence. We use the Match & Locate method, a variation on the matched-filter method which detects events of lower magnitudes by stacking cross-correlograms from different stations [Zhang & Wen, 2013; 2015], in order to create a more complete catalog from 6 Nov to 31 Dec 2011. We then relocate the detected events using the HypoDD double-difference algorithm. Using our enhanced catalog and relocations, we examine the seismicity distribution for evidence of migration and investigate implications for triggering mechanisms. To account for path and site effects, we calculate stress drops using the Empirical Green's Function (EGF) spectral ratio method, beginning with 2730 previously relocated events. We determine whether there is a correlation between the stress drop magnitudes and the spatial and temporal distribution of events, including depth, position relative to existing faults, and proximity to injection wells. Finally, we consider the range of stress drop values and scaling with respect to event magnitudes within the context of previously published work for the Prague sequence as well as other induced and natural sequences.

  10. Automated Identification of Abnormal Adult EEGs

    PubMed Central

    López, S.; Suarez, G.; Jungreis, D.; Obeid, I.; Picone, J.

    2016-01-01

    The interpretation of electroencephalograms (EEGs) is a process that is still dependent on the subjective analysis of the examiners. Though interrater agreement on critical events such as seizures is high, it is much lower on subtler events (e.g., when there are benign variants). The process used by an expert to interpret an EEG is quite subjective and hard to replicate by machine. The performance of machine learning technology is far from human performance. We have been developing an interpretation system, AutoEEG, with a goal of exceeding human performance on this task. In this work, we are focusing on one of the early decisions made in this process – whether an EEG is normal or abnormal. We explore two baseline classification algorithms: k-Nearest Neighbor (kNN) and Random Forest Ensemble Learning (RF). A subset of the TUH EEG Corpus was used to evaluate performance. Principal Components Analysis (PCA) was used to reduce the dimensionality of the data. kNN achieved a 41.8% detection error rate while RF achieved an error rate of 31.7%. These error rates are significantly lower than those obtained by random guessing based on priors (49.5%). The majority of the errors were related to misclassification of normal EEGs. PMID:27195311

  11. 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.

  12. Energy Reconstruction for Events Detected in TES X-ray Detectors

    NASA Astrophysics Data System (ADS)

    Ceballos, M. T.; Cardiel, N.; Cobo, B.

    2015-09-01

    The processing of the X-ray events detected by a TES (Transition Edge Sensor) device (such as the one that will be proposed in the ESA AO call for instruments for the Athena mission (Nandra et al. 2013) as a high spectral resolution instrument, X-IFU (Barret et al. 2013)), is a several step procedure that starts with the detection of the current pulses in a noisy signal and ends up with their energy reconstruction. For this last stage, an energy calibration process is required to convert the pseudo energies measured in the detector to the real energies of the incoming photons, accounting for possible nonlinearity effects in the detector. We present the details of the energy calibration algorithm we implemented as the last part of the Event Processing software that we are developing for the X-IFU instrument, that permits the calculation of the calibration constants in an analytical way.

  13. Insertable cardiac event recorder in detection of atrial fibrillation after cryptogenic stroke: an audit report.

    PubMed

    Etgen, Thorleif; Hochreiter, Manfred; Mundel, Markus; Freudenberger, Thomas

    2013-07-01

    Atrial fibrillation (AF) is the most frequent risk factor in ischemic stroke but often remains undetected. We analyzed the value of insertable cardiac event recorder in detection of AF in a 1-year cohort of patients with cryptogenic ischemic stroke. All patients with cryptogenic stroke and eligibility for oral anticoagulation were offered the insertion of a cardiac event recorder. Regular follow-up for 1 year recorded the incidence of AF. Of the 393 patients with ischemic stroke, 65 (16.5%) had a cryptogenic stroke, and in 22 eligible patients, an event recorder was inserted. After 1 year, in 6 of 22 patients (27.3%), AF was detected. These preliminary data show that insertion of cardiac event recorder was eligible in approximately one third of patients with cryptogenic stroke and detected in approximately one quarter of these patients new AF.

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

    NASA Astrophysics Data System (ADS)

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

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

  15. 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

  16. Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

    PubMed

    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.

  17. An Unsupervised Anomalous Event Detection and Interactive Analysis Framework for Large-scale Satellite Data

    NASA Astrophysics Data System (ADS)

    LIU, Q.; Lv, Q.; Klucik, R.; Chen, C.; Gallaher, D. W.; Grant, G.; Shang, L.

    2016-12-01

    Due to the high volume and complexity of satellite data, computer-aided tools for fast quality assessments and scientific discovery are indispensable for scientists in the era of Big Data. In this work, we have developed a framework for automated anomalous event detection in massive satellite data. The framework consists of a clustering-based anomaly detection algorithm and a cloud-based tool for interactive analysis of detected anomalies. The algorithm is unsupervised and requires no prior knowledge of the data (e.g., expected normal pattern or known anomalies). As such, it works for diverse data sets, and performs well even in the presence of missing and noisy data. The cloud-based tool provides an intuitive mapping interface that allows users to interactively analyze anomalies using multiple features. As a whole, our framework can (1) identify outliers in a spatio-temporal context, (2) recognize and distinguish meaningful anomalous events from individual outliers, (3) rank those events based on "interestingness" (e.g., rareness or total number of outliers) defined by users, and (4) enable interactively query, exploration, and analysis of those anomalous events. In this presentation, we will demonstrate the effectiveness and efficiency of our framework in the application of detecting data quality issues and unusual natural events using two satellite datasets. The techniques and tools developed in this project are applicable for a diverse set of satellite data and will be made publicly available for scientists in early 2017.

  18. 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

  19. Detecting Micro-seismicity and Long-duration Tremor-like Events from the Oklahoma Wavefield Experiment

    NASA Astrophysics Data System (ADS)

    Li, C.; Li, Z.; Peng, Z.; Zhang, C.; Nakata, N.

    2017-12-01

    Oklahoma has experienced abrupt increase of induced seismicity in the last decade. An important way to fully understand seismic activities in Oklahoma is to obtain more complete earthquake catalogs and detect different types of seismic events. The IRIS Community Wavefield Demonstration Experiment was deployed near Enid, Oklahoma in Summer of 2016. The dataset from this ultra-dense array provides an excellent opportunity for detecting microseismicity in that region with wavefield approaches. Here we examine continuous waveforms recorded by 3 seismic lines using local coherence for ultra-dense arrays (Li et al., 2017), which is a measure of cross-correlation of waveform at each station with its nearby stations. So far we have detected more than 5,000 events from 06/22/2016 to 07/20/2016, and majority of them are not listed on the regional catalog of Oklahoma or global catalogs, indicating that they are local events. We also identify 15-20 long-period long-duration events, some of them lasting for more than 500 s. Such events have been found at major plate-boundary faults (also known as deep tectonic tremor), as well as during hydraulic fracturing, slow-moving landslides and glaciers. Our next step is to locate these possible tremor-like events with their relative arrival times across the array and compare their occurrence times with solid-earth tides and injection histories to better understand their driving mechanisms.

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

    PubMed

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

    2017-03-24

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

  1. Prediction of heart abnormality using MLP network

    NASA Astrophysics Data System (ADS)

    Hashim, Fakroul Ridzuan; Januar, Yulni; Mat, Muhammad Hadzren; Rizman, Zairi Ismael; Awang, Mat Kamil

    2018-02-01

    Heart abnormality does not choose gender, age and races when it strikes. With no warning signs or symptoms, it can result to a sudden death of the patient. Generally, heart's irregular electrical activity is defined as heart abnormality. Via implementation of Multilayer Perceptron (MLP) network, this paper tries to develop a program that allows the detection of heart abnormality activity. Utilizing several training algorithms with Purelin activation function, an amount of heartbeat signals received through the electrocardiogram (ECG) will be employed to condition the MLP network.

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

    PubMed

    Pineau, Joelle; 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.

  3. Abnormalities in amphibian populations inhabiting agroecosystems in Northeastern Buenos Aires Province, Argentina.

    PubMed

    Agostini, M G; Kacoliris, F; Demetrio, P; Natale, G S; Bonetto, C; Ronco, A E

    2013-05-27

    The occurrence of abnormalities in amphibians has been reported in many populations, and its increase could be related to environmental pollution and habitat degradation. We evaluated the type and prevalence of abnormalities in 5 amphibian populations from agroecosystems with different degrees of agricultural disturbance (cultivated and reference areas). We detected 9 types of abnormalities, of which the most frequent were those occurring in limbs. The observed prevalence of abnormality in assessed populations from cultivated and reference areas was as follows: Rhinella fernandezae (37.1 and 10.2%, respectively), Leptodactylus latrans adults (28.1 and 9.2%) and juveniles (32.9 and 15.3%), and Hypsiboas pulchellus (11.6 and 2.8%). Scinax granulatus populations did not show abnormalities. Pseudis minuta, which was only detected in the reference area, exhibited a prevalence of 13.3%. For R. fernandezae, L. latrans, and H. pulchellus, generalized linear mixed models showed that prevalence of abnormalities was significantly higher (p < 0.05) in cultivated than in reference areas. L. latrans juveniles were more vulnerable to abnormalities than adults (p < 0.05). The presence of abnormalities in some species inhabiting different agroecosystems suggests that environmental stress factors might be responsible for their occurrence. While we detected pesticides (endosulfan, cypermethrin, and chlorpyrifos) and lower dissolved oxygen levels in ponds of the cultivated area, no data are currently available on how other factors, such as injuries from predators and parasite infections, vary by land use. Further research will be necessary to evaluate possible causes of abnormalities detected in the present study mainly in the context of factor interactions.

  4. Easiness of Use and Validity Testing of VS-SENSE Device for Detection of Abnormal Vaginal Flora and Bacterial Vaginosis

    PubMed Central

    Donders, Gilbert G. G.; Marconi, Camila; Bellen, Gert

    2010-01-01

    Accessing vaginal pH is fundamental during gynaecological visit for the detection of abnormal vaginal flora (AVF), but use of pH strips may be time-consuming and difficult to interpret. The aim of this study was to evaluate the VS-SENSE test (Common Sense Ltd, Caesarea, Israel) as a tool for the diagnosis of AVF and its correlation with abnormal pH and bacterial vaginosis (BV). The study population consisted of 45 women with vaginal pH ≥ 4.5 and 45 women with normal pH. Vaginal samples were evaluated by VS-SENSE test, microscopy and microbiologic cultures. Comparing with pH strips results, VS-SENSE test specificity was 97.8% and sensitivity of 91%. All severe cases of BV and aerobic vaginitis (AV) were detected by the test. Only one case with normal pH had an unclear result. Concluding, VS-SENSE test is easy to perform, and it correlates with increased pH, AVF, and the severe cases of BV and AV. PMID:20953405

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

    PubMed

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

    2016-10-01

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

  6. 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

  7. Effect of parameters in moving average method for event detection enhancement using phase sensitive OTDR

    NASA Astrophysics Data System (ADS)

    Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum

    2017-04-01

    We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.

  8. Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

    PubMed

    Housh, Mashor; Ohar, Ziv

    2017-03-01

    The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. 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.

  10. 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

  11. Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

    NASA Astrophysics Data System (ADS)

    Missif, Lial Raja; Kadhum, Mohammad M.

    2017-09-01

    Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

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

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

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

    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 backgroundmore » 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.« less

  13. Track-based event recognition in a realistic crowded environment

    NASA Astrophysics Data System (ADS)

    van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

    2014-10-01

    Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

  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. Event-specific real-time detection and quantification of genetically modified Roundup Ready soybean.

    PubMed

    Huang, Chia-Chia; Pan, Tzu-Ming

    2005-05-18

    The event-specific real-time detection and quantification of Roundup Ready soybean (RRS) using an ABI PRISM 7700 sequence detection system with light upon extension (LUX) primer was developed in this study. The event-specific primers were designed, targeting the junction of the RRS 5' integration site and the endogenous gene lectin1. Then, a standard reference plasmid was constructed that carried both of the targeted sequences for quantitative analysis. The detection limit of the LUX real-time PCR system was 0.05 ng of 100% RRS genomic DNA, which was equal to 20.5 copies. The range of quantification was from 0.1 to 100%. The sensitivity and range of quantification successfully met the requirement of the labeling rules in the European Union and Taiwan.

  16. Prevalence and prognostic impact of electrocardiographic abnormalities in outpatients with extracardiac artery disease.

    PubMed

    Hysing, Per; Jonason, Tommy; Leppert, Jerzy; Hedberg, Pär

    2017-11-24

    Identifying cardiac disease in patients with extracardiac artery disease (ECAD) is essential for clinical decision-making. Electrocardiography (ECG) is an easily accessible tool to unmask subclinical cardiac disease and to risk stratify patient with or without manifest cardiovascular disease (CV). We aimed to examine the prevalence and prognostic impact of ECG changes in outpatients with ECAD. Outpatients with carotid or lower extremity artery disease (n = 435) and community-based controls (n = 397) underwent resting ECG. The patients were followed during a median of 4·8 years for CV events (hospitalization or death caused by ischaemic heart disease, cardiac arrest, heart failure, or stroke). ECG abnormalities were classified according to the Minnesota Code. Major (33% versus 15%, P<0·001) but not minor ECG abnormalities (23% versus 26%, P = 0·42) were significantly more common in patients versus controls. During the follow-up, 141 patients experienced CV events. Both major ECG abnormalities [hazard ratio (HR) 1·58, 95% confidence interval (CI) 1·11-2·25, P = 0·012] and any ECG abnormalities (HR 1·57, 95% CI 1·06-2·33, P = 0·024) were significantly associated with CV events after adjustment for potential risk factors. In conclusion, ECG abnormalities were common in these outpatients with ECAD. Major and any ECG abnormalities were independent predictors of CV events. Addition of easily accessible ECG information might be useful in risk stratification for such patients. © 2017 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

  17. 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.

  18. 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.

  19. 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

  20. Secure access control and large scale robust representation for online multimedia event detection.

    PubMed

    Liu, Changyu; Lu, Bin; 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.

  1. Automated Electroglottographic Inflection Events Detection. A Pilot Study.

    PubMed

    Codino, Juliana; Torres, María Eugenia; Rubin, Adam; Jackson-Menaldi, Cristina

    2016-11-01

    Vocal-fold vibration can be analyzed in a noninvasive way by registering impedance changes within the glottis, through electroglottography. The morphology of the electroglottographic (EGG) signal is related to different vibratory patterns. In the literature, a characteristic knee in the descending portion of the signal has been reported. Some EGG signals do not exhibit this particular knee and have other types of events (inflection events) throughout the ascending and/or descending portion of the vibratory cycle. The goal of this work is to propose an automatic method to identify and classify these events. A computational algorithm was developed based on the mathematical properties of the EGG signal, which detects and reports events throughout the contact phase. Retrospective analysis of EGG signals obtained during routine voice evaluation of adult individuals with a variety of voice disorders was performed using the algorithm as well as human raters. Two judges, both experts in clinical voice analysis, and three general speech pathologists performed manual and visual evaluation of the sample set. The results obtained by the automatic method were compared with those of the human raters. Statistical analysis revealed a significant level of agreement. This automatic tool could allow professionals in the clinical setting to obtain an automatic quantitative and qualitative report of such events present in a voice sample, without having to manually analyze the whole EGG signal. In addition, it might provide the speech pathologist with more information that would complement the standard voice evaluation. It could also be a valuable tool in voice research. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  2. A novel CUSUM-based approach for event detection in smart metering

    NASA Astrophysics Data System (ADS)

    Zhu, Zhicheng; Zhang, Shuai; Wei, Zhiqiang; Yin, Bo; Huang, Xianqing

    2018-03-01

    Non-intrusive load monitoring (NILM) plays such a significant role in raising consumer awareness on household electricity use to reduce overall energy consumption in the society. With regard to monitoring low power load, many researchers have introduced CUSUM into the NILM system, since the traditional event detection method is not as effective as expected. Due to the fact that the original CUSUM faces limitations given the small shift is below threshold, we therefore improve the test statistic which allows permissible deviation to gradually rise as the data size increases. This paper proposes a novel event detection and corresponding criterion that could be used in NILM systems to recognize transient states and to help the labelling task. Its performance has been tested in a real scenario where eight different appliances are connected to main line of electric power.

  3. In Vivo Detection of Choroidal Abnormalities Related to NF1: Feasibility and Comparison With Standard NIH Diagnostic Criteria in Pediatric Patients.

    PubMed

    Parrozzani, Raffaele; Clementi, Maurizio; Frizziero, Luisa; Miglionico, Giacomo; Perrini, Pierdavide; Cavarzeran, Fabiano; Kotsafti, Olympia; Comacchio, Francesco; Trevisson, Eva; Convento, Enrica; Fusetti, Stefano; Midena, Edoardo

    2015-09-01

    To evaluate the feasibility of near-infrared (NIR) imaging acquisition in a large sample of consecutive pediatric patients with neurofibromatosis type 1 (NF1), to evaluate the diagnostic performance of NF1-related choroidal abnormalities as a diagnostic criterion of the disease, and to compare this criterion with other standard National Institutes of Health (NIH) diagnostic criteria. A total of 140 consecutive pediatric patients (0-16 years old) affected by NF1 (at least two diagnostic criteria), 59 suspected (a single diagnostic criterion), and 42 healthy subjects (no diagnostic criterion) were consecutively included. Each patient underwent genetic, dermatologic, and ophthalmologic examination to evaluate the presence/absence of each NIH diagnostic criterion. The presence of NF1-related choroidal abnormalities was investigated using NIR confocal ophthalmoscopy. Two masked operators assessed Lisch nodules and NF1-related choroidal abnormalities. Neurofibromatosis type 1-related choroidal abnormalities were detected in 72 affected (60.5%) and 1 suspected (2.4%) child. No healthy subject had choroidal abnormalities. Feasibility rate of this sign was 82%. Sensitivity, specificity, and positive and negative predictive values of NF1-related choroidal abnormalities were 0.60, 0.97, 0.98, and 0.46, respectively. Compared with standard NIH criteria, the presence of NF1-related choroidal abnormalities was the third parameter for positive predictive value and the fourth for sensitivity, specificity, and negative predictive value. Compared with Lisch nodules, NF1-related choroidal abnormalities were characterized by higher specificity and positive predictive value. The interoperator agreement for Lisch nodules and NF1-related choroidal abnormalities was 0.67 (substantial) and 0.97 (almost perfect), respectively. The use of this sign moved one patient from the suspected to the affected group (0.5%). Neurofibromatosis type 1-related choroidal abnormalities represent a new

  4. Salivary glands abnormalities in oculo-auriculo-vertebral spectrum.

    PubMed

    Brotto, Davide; Manara, Renzo; Vio, Stefania; Ghiselli, Sara; Cantone, Elena; Mardari, Rodica; Toldo, Irene; Stritoni, Valentina; Castiglione, Alessandro; Lovo, Elisa; Trevisi, Patrizia; Bovo, Roberto; Martini, Alessandro

    2018-01-01

    Feeding and swallowing impairment are present in up to 80% of oculo-auriculo-vertebral spectrum (OAVS) patients. Salivary gland abnormalities have been reported in OAVS patients but their rate, features, and relationship with phenotype severity have yet to be defined. Parotid and submandibular salivary gland hypo/aplasia was evaluated on head MRI of 25 OAVS patients (16 with severe phenotype, Goldenhar syndrome) and 11 controls. All controls disclosed normal salivary glands. Abnormal parotid glands were found exclusively ipsilateral to facial microsomia in 21/25 OAVS patients (84%, aplasia in six patients) and showed no association with phenotype severity (14/16 patients with Goldenhar phenotype vs 7/9 patients with milder phenotype, p = 0.6). Submandibular salivary gland hypoplasia was detected in six OAVS patients, all with concomitant ipsilateral severe involvement of the parotid gland (p < 0.001). Submandibular salivary gland hypoplasia was associated to Goldenhar phenotype (p < 0.05). Parotid gland abnormalities were associated with ipsilateral fifth (p < 0.001) and seventh cranial nerve (p = 0.001) abnormalities. No association was found between parotid gland anomaly and ipsilateral internal carotid artery, inner ear, brain, eye, or spine abnormalities (p > 0.6). Salivary gland abnormalities are strikingly common in OAVS. Their detection might help the management of OAVS-associated swallowing and feeding impairment.

  5. Detection and analysis of high-temperature events in the BIRD mission

    NASA Astrophysics Data System (ADS)

    Zhukov, Boris; Briess, Klaus; Lorenz, Eckehard; Oertel, Dieter; Skrbek, Wolfgang

    2005-01-01

    The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite is detection and quantitative analysis of high-temperature events like fires and volcanoes. An absence of saturation in the BIRD infrared channels makes it possible to improve false alarm rejection as well as to retrieve quantitative characteristics of hot targets, including their effective fire temperature, area and the radiative energy release. Examples are given of detection and analysis of wild and coal seam fires, of volcanic activity as well as of oil fires in Iraq. The smallest fires detected by BIRD, which were verified on ground, had an area of 12m2 at daytime and 4m2 at night.

  6. [Incidence and risk factors for mental abnormalities in children of psychiatric inpatients].

    PubMed

    Stelzig-Schöler, Renate; Hasselbring, Laura; Yazdi, Kurosch; Thun-Hohenstein, Leonhard; Stuppäck, Christoph; Aichhorn, Wolfgang

    2011-01-01

    Children of mentally ill parents are exposed to a variety of stress- and harmful life events. To which extent the mental illness of one or both parents affects their children's mental development is barely studied. Therefore, over a period of 6 months 142 patients with children below the age of 18 (n=237 children), who were admitted to the Dept. for Psychiatry and Psychotherapy 1 of the Paracelsus Medical University Salzburg, were questioned for abnormalities in their children's mental development. Additionally all these patients were assessed for their family situation, demographic data and psychiatric disorder. 38.4% (n=91) of the children showed mental abnormalities. The most common one were emotional (n=41), social (n=41) and learning (n=34) disabilities. Parental duration of the illness (p=0.001), age of the children (p=0.044), illness of both parents (p=0.008), longlasting family conflicts (p=0.003) and living with only one parent (p=0.012) were correlated significantly with mental abnormalities in children. The results confirm an increase risk for mental abnormalities in children of psychiatric patients. This risk varies with existing risk and protective factors, which can be partially influenced. Therefore children of mentally ill parents with problems in their mental development should be detected early. Even if genetic risk factors cannot be changed reducing known psychosocial risk factors and promotion protective factors can significantly influence a healthy development of these vulnerable children.

  7. Association of abnormal morphology and altered gene expression in human preimplantation embryos.

    PubMed

    Wells, Dagan; Bermúdez, Mercedes G; Steuerwald, Nury; Malter, Henry E; Thornhill, Alan R; Cohen, Jacques

    2005-08-01

    We set out to characterize the expression of nine genes in human preimplantation embryos and determine whether abnormal morphology is associated with altered gene activity. Reverse transcription and real-time polymerase chain reaction were used to quantify the expression of multiple genes in each embryo. The genes studied have various important cellular roles (e.g., cell cycle regulation, DNA repair, and apoptosis). Research laboratory working closely with a clinical IVF practice. Over 50 embryos were donated by infertile patients (various etiologies). Among these, all major stages of preimplantation development and a variety of common morphologic abnormalities were represented. None. Quantification of mRNA transcripts. We detected an association between certain forms of abnormal morphology and disturbances of gene activity. Cellular fragmentation was associated with altered expression of several genes, including TP53, suggesting that fragmenting blastomeres are suffering stress of a type monitored by p53, possibly as a consequence of suboptimal culture conditions. Appropriate gene expression is vital for the regulation of metabolic pathways and key developmental events. Our data indicates a possible causal relationship between changes in gene expression and the formation of clinically relevant abnormal embryo morphologies. We hypothesize that embryos with expression profiles characteristic of good morphology and appropriate for their developmental stage have the greatest potential for implantation. If confirmed, this could lead to a new generation of preimplantation genetic diagnosis (PGD) tests for assessing embryo viability and predicting implantation potential.

  8. Predictive modeling of structured electronic health records for adverse drug event detection.

    PubMed

    Zhao, Jing; Henriksson, Aron; Asker, Lars; Boström, Henrik

    2015-01-01

    The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and

  9. Predictive modeling of structured electronic health records for adverse drug event detection

    PubMed Central

    2015-01-01

    Background The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Methods Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Results Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both

  10. Report to Congress on abnormal occurrences, October--December 1993. Volume 16, No. 4

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

    Not Available

    1994-04-01

    Section 208 of the Energy Reorganization Act of 1974 identifies an abnormal occurrence as an unscheduled incident or event that the Nuclear Regulatory Commission determines to be significant from the standpoint of public health or safety and requires a quarterly report of such events to be made to Congress. This report covers the period from October 1 through December 31, 1993. This report discusses six abnormal occurrences at NRC-licensed facilities. Five involved medical brachytherapy misadministrations, and one involved an overexposure to a nursing infant. Seven abnormal occurrences that were reported by the Agreement States are also discussed, based on informationmore » provided by the Agreement States as of February 28, 1994. Of these events, three involved brachytherapy misadministrations, one involved a teletherapy misadministration, one involved a theft of radioactive material during transport and improper disposal, and two involved lost sources.« less

  11. Detection of visual events along the apparent motion trace in patients with paranoid schizophrenia.

    PubMed

    Sanders, Lia Lira Olivier; Muckli, Lars; de Millas, Walter; Lautenschlager, Marion; Heinz, Andreas; Kathmann, Norbert; Sterzer, Philipp

    2012-07-30

    Dysfunctional prediction in sensory processing has been suggested as a possible causal mechanism in the development of delusions in patients with schizophrenia. Previous studies in healthy subjects have shown that while the perception of apparent motion can mask visual events along the illusory motion trace, such motion masking is reduced when events are spatio-temporally compatible with the illusion, and, therefore, predictable. Here we tested the hypothesis that this specific detection advantage for predictable target stimuli on the apparent motion trace is reduced in patients with paranoid schizophrenia. Our data show that, although target detection along the illusory motion trace is generally impaired, both patients and healthy control participants detect predictable targets more often than unpredictable targets. Patients had a stronger motion masking effect when compared to controls. However, patients showed the same advantage in the detection of predictable targets as healthy control subjects. Our findings reveal stronger motion masking but intact prediction of visual events along the apparent motion trace in patients with paranoid schizophrenia and suggest that the sensory prediction mechanism underlying apparent motion is not impaired in paranoid schizophrenia. Copyright © 2012. Published by Elsevier Ireland Ltd.

  12. 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.

  13. Gastric emptying abnormal in duodenal ulcer

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

    Holt, S.; Heading, R.C.; Taylor, T.V.

    1986-07-01

    To investigate the possibility that an abnormality of gastric emptying exists in duodenal ulcer and to determine if such an abnormality persists after ulcer healing, scintigraphic gastric emptying measurements were undertaken in 16 duodenal ulcer patients before, during, and after therapy with cimetidine; in 12 patients with pernicious anemia, and in 12 control subjects. No difference was detected in the rate or pattern of gastric emptying in duodenal ulcer patients before and after ulcer healing with cimetidine compared with controls, but emptying of the solid component of the test meal was more rapid during treatment with the drug. Comparison ofmore » emptying patterns obtained in duodenal ulcer subjects during and after cimetidine treatment with those obtained in pernicious anemia patients and controls revealed a similar relationship that was characterized by a tendency for reduction in the normal differentiation between the emptying of solid and liquid from the stomach. The similarity in emptying patterns in these groups of subjects suggests that gastric emptying of solids may be influenced by changes in the volume of gastric secretion. The failure to detect an abnormality of gastric emptying in duodenal ulcer subjects before and after ulcer healing calls into question the widespread belief that abnormally rapid gastric emptying is a feature with pathogenetic significance in duodenal ulcer disease.« less

  14. Detection of Abnormal Operation Noise Using CHLAC of Sound Spectrograph and Continuous DP Matching

    NASA Astrophysics Data System (ADS)

    Hattori, Koosuke; Ohmi, Taishi; Taguchi, Ryo; Umezaki, Taizo

    It is a general way that the industrial product is tested by individual inspector. If the product involves sound factors, each inspector will evaluate the test product to sort out a strange engine noise from the natural sound. However, it is hard to cover the consistency in evaluation criteria due to the personal equation referred to the idea that every individual had an inherent bias, plus a physical and mental conditions can be a negative effect on his/her evaluation criteria. It would be ideal if the criteria would not be affected by anyone, anywhere, circumstances; accordingly the quality of products must be equated. In this paper, we propose a noise detection method based on Cubic Higher-order Local Auto-Correlation (CHLAC) scheme and DP Matching provided by Cepstrum Analysis to extract the correct solution. This technique is practically used for detecting any human abnormal movements out of a monitored video clip and identifying individual persons by voice. The study results are shown to be highly effective in our proposed method.

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

    PubMed

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

    2017-07-05

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

  16. Could quantitative longitudinal peak systolic strain help in the detection of left ventricular wall motion abnormalities in our daily echocardiographic practice?

    PubMed

    Benyounes, Nadia; Lang, Sylvie; Gout, Olivier; Ancédy, Yann; Etienney, Arnaud; Cohen, Ariel

    2016-10-01

    Transthoracic echocardiography is the most commonly used tool for the detection of left ventricular wall motion (LVWM) abnormalities using "naked eye evaluation". This subjective and operator-dependent technique requires a high level of clinical training and experience. Two-dimensional speckle-tracking echocardiography (2D-STE), which is less operator-dependent, has been proposed for this purpose. However, the role of on-line segmental longitudinal peak systolic strain (LPSS) values in the prediction of LVWM has not been fully evaluated. To test segmental LPSS for predicting LVWM abnormalities in routine echocardiography laboratory practice. LVWM was evaluated by an experienced cardiologist, during routine practice, in 620 patients; segmental LPSS values were then calculated. In this work, reflecting real life, 99.6% of segments were successfully tracked. Mean (95% confidence interval [CI]) segmental LPSS values for normal basal (n=3409), mid (n=3468) and apical (n=3466) segments were -16.7% (-16.9% to -16.5%), -18.2% (-18.3% to -18.0%) and -21.1% (-21.3% to -20.9%), respectively. Mean (95% CI) segmental LPSS values for hypokinetic basal (n=114), mid (n=116) and apical (n=90) segments were -7.7% (-9.0% to -6.3%), -10.1% (-11.1% to -9.0%) and -9.3% (-10.5% to -8.1%), respectively. Mean (95% CI) segmental LPSS values for akinetic basal (n=128), mid (n=95) and apical (n=91) segments were -6.6% (-8.0% to -5.1%), -6.1% (-7.7% to -4.6%) and -4.2% (-5.4% to -3.0%), respectively. LPSS allowed the differentiation between normal and abnormal segments at basal, mid and apical levels. An LPSS value≥-12% detected abnormal segmental motion with a sensitivity of 78% for basal, 70% for mid and 82% for apical segments. Segmental LPSS values may help to differentiate between normal and abnormal left ventricular segments. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  17. A method for detecting and locating geophysical events using groups of arrays

    NASA Astrophysics Data System (ADS)

    de Groot-Hedlin, Catherine D.; Hedlin, Michael A. H.

    2015-11-01

    We have developed a novel method to detect and locate geophysical events that makes use of any sufficiently dense sensor network. This method is demonstrated using acoustic sensor data collected in 2013 at the USArray Transportable Array (TA). The algorithm applies Delaunay triangulation to divide the sensor network into a mesh of three-element arrays, called triads. Because infrasound waveforms are incoherent between the sensors within each triad, the data are transformed into envelopes, which are cross-correlated to find signals that satisfy a consistency criterion. The propagation azimuth, phase velocity and signal arrival time are computed for each signal. Triads with signals that are consistent with a single source are bundled as an event group. The ensemble of arrival times and azimuths of detected signals within each group are used to locate a common source in space and time. A total of 513 infrasonic stations that were active for part or all of 2013 were divided into over 2000 triads. Low (0.5-2 Hz) and high (2-8 Hz) catalogues of infrasonic events were created for the eastern USA. The low-frequency catalogue includes over 900 events and reveals several highly active source areas on land that correspond with coal mining regions. The high-frequency catalogue includes over 2000 events, with most occurring offshore. Although their cause is not certain, most events are clearly anthropogenic as almost all occur during regular working hours each week. The regions to which the TA is most sensitive vary seasonally, with the direction of reception dependent on the direction of zonal winds. The catalogue has also revealed large acoustic events that may provide useful insight into the nature of long-range infrasound propagation in the atmosphere.

  18. Individual differences in event-based prospective memory: Evidence for multiple processes supporting cue detection.

    PubMed

    Brewer, Gene A; Knight, Justin B; Marsh, Richard L; Unsworth, Nash

    2010-04-01

    The multiprocess view proposes that different processes can be used to detect event-based prospective memory cues, depending in part on the specificity of the cue. According to this theory, attentional processes are not necessary to detect focal cues, whereas detection of nonfocal cues requires some form of controlled attention. This notion was tested using a design in which we compared performance on a focal and on a nonfocal prospective memory task by participants with high or low working memory capacity. An interaction was found, such that participants with high and low working memory performed equally well on the focal task, whereas the participants with high working memory performed significantly better on the nonfocal task than did their counterparts with low working memory. Thus, controlled attention was only necessary for detecting event-based prospective memory cues in the nonfocal task. These results have implications for theories of prospective memory, the processes necessary for cue detection, and the successful fulfillment of intentions.

  19. Closing the Loop in ICU Decision Support: Physiologic Event Detection, Alerts, and Documentation

    PubMed Central

    Norris, Patrick R.; Dawant, Benoit M.

    2002-01-01

    Automated physiologic event detection and alerting is a challenging task in the ICU. Ideally care providers should be alerted only when events are clinically significant and there is opportunity for corrective action. However, the concepts of clinical significance and opportunity are difficult to define in automated systems, and effectiveness of alerting algorithms is difficult to measure. This paper describes recent efforts on the Simon project to capture information from ICU care providers about patient state and therapy in response to alerts, in order to assess the value of event definitions and progressively refine alerting algorithms. Event definitions for intracranial pressure and cerebral perfusion pressure were studied by implementing a reliable system to automatically deliver alerts to clinical users’ alphanumeric pagers, and to capture associated documentation about patient state and therapy when the alerts occurred. During a 6-month test period in the trauma ICU at Vanderbilt University Medical Center, 530 alerts were detected in 2280 hours of data spanning 14 patients. Clinical users electronically documented 81% of these alerts as they occurred. Retrospectively classifying documentation based on therapeutic actions taken, or reasons why actions were not taken, provided useful information about ways to potentially improve event definitions and enhance system utility.

  20. Closing the loop in ICU decision support: physiologic event detection, alerts, and documentation.

    PubMed Central

    Norris, P. R.; Dawant, B. M.

    2001-01-01

    Automated physiologic event detection and alerting is a challenging task in the ICU. Ideally care providers should be alerted only when events are clinically significant and there is opportunity for corrective action. However, the concepts of clinical significance and opportunity are difficult to define in automated systems, and effectiveness of alerting algorithms is difficult to measure. This paper describes recent efforts on the Simon project to capture information from ICU care providers about patient state and therapy in response to alerts, in order to assess the value of event definitions and progressively refine alerting algorithms. Event definitions for intracranial pressure and cerebral perfusion pressure were studied by implementing a reliable system to automatically deliver alerts to clinical users alphanumeric pagers, and to capture associated documentation about patient state and therapy when the alerts occurred. During a 6-month test period in the trauma ICU at Vanderbilt University Medical Center, 530 alerts were detected in 2280 hours of data spanning 14 patients. Clinical users electronically documented 81% of these alerts as they occurred. Retrospectively classifying documentation based on therapeutic actions taken, or reasons why actions were not taken, provided useful information about ways to potentially improve event definitions and enhance system utility. PMID:11825238

  1. Bronchial abnormalities found in a consecutive series of 40 brachycephalic dogs.

    PubMed

    De Lorenzi, Davide; Bertoncello, Diana; Drigo, Michele

    2009-10-01

    To detect abnormalities of the lower respiratory tract (trachea, principal bronchi, and lobar bronchi) in brachycephalic dogs by use of endoscopy, evaluate the correlation between laryngeal collapse and bronchial abnormalities, and determine whether dogs with bronchial abnormalities have a less favorable postsurgical long-term outcome following correction of brachycephalic syndrome. Prospective case series study. 40 client-owned brachycephalic dogs with stertorous breathing and clinical signs of respiratory distress. Brachycephalic dogs anesthetized for pharyngoscopy and laryngoscopy between January 2007 and June 2008 underwent flexible bronchoscopy for systematic evaluation of the principal and lobar bronchi. For dogs that underwent surgical correction of any component of brachycephalic syndrome, owners rated surgical outcome during a follow-up telephone survey. Correlation between laryngeal collapse and bronchial abnormalities and association between bronchial abnormalities and long-term outcome were assessed. Pugs (n = 20), English Bulldogs (13), and French Bulldogs (7) were affected. A fixed bronchial collapse was recognized in 35 of 40 dogs with a total of 94 bronchial stenoses. Abnormalities were irregularly distributed between hemithoraces; 15 of 94 bronchial abnormalities were detected in the right bronchial system, and 79 of 94 were detected in the left. The left cranial bronchus was the most commonly affected structure, and Pugs were the most severely affected breed. Laryngeal collapse was significantly correlated with severe bronchial collapse; no significant correlation was found between severity of bronchial abnormalities and postsurgical outcome. Bronchial collapse was a common finding in brachycephalic dogs, and long-term postsurgical outcome was not affected by bronchial stenosis.

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

    PubMed Central

    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. PMID:26869966

  3. 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.

  4. 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%.

  5. Infrasound's capability to detect and characterise volcanic events, from local to regional scale.

    NASA Astrophysics Data System (ADS)

    Taisne, Benoit; Perttu, Anna

    2017-04-01

    Local infrasound and seismic networks have been successfully used for identification and quantification of explosions at single volcanoes. However the February, 2014 eruption of Kelud volcano, Indonesia, destroyed most of the local monitoring network. The use of remote seismic and infrasound sensors proved to be essential in the reconstruction of the eruptive sequence. The first recorded explosive event, with relatively weak seismic and infrasonic signature, was followed by a 2 hour sustained signal detected as far away as 11,000 km by infrasound sensors and up to 2,300 km away by seismometers. The volcanic intensity derived from these observations places the 2014 Kelud eruption between the intensity of the 1980 Mount St. Helens and the 1991 Pinatubo eruptions. The use of remote seismic stations and infrasound arrays in deriving valuable information about the onset, evolution, and intensity of volcanic eruptions is clear from the Kelud example. After this eruption the Singapore Infrasound Array became operational. This array, along with the other regional infrasound arrays which are part of the International Monitoring System, have recorded events from fireballs and regional volcanoes. The detection capability of this network for any specific volcanic event is not only dependent on the amplitude of the source, but also the propagation effects, noise level at each station, and characteristics of the regional persistent noise sources (like the microbarum). Combining the spatial and seasonal characteristics of this noise, within the same frequency band as significant eruptive events, with the probability of such events to occur, gives us a comprehensive understanding of detection capability for any of the 750 active or potentially active volcanoes in Southeast Asia.

  6. Guidelines to identify abnormalities after childhood urinary tract infections: a prospective audit.

    PubMed

    Coulthard, Malcolm G; Lambert, Heather J; Vernon, Susan J; Hunter, Elizabeth W; Keir, Michael J

    2014-05-01

    To compare the childhood urinary tract infection (UTI) guidelines from the Royal College of Physicians (RCP) in 1991 and from National Institute of Health and Care Excellence (NICE) (CG54) in 2007 by measuring their efficiency at detecting urinary tract abnormalities. Children with UTIs within the Newcastle Primary Care Trust (population 70,800 children) were referred and imaged according to the RCP guidelines during 2008, and these were compared to the activity that would have been undertaken if we had implemented the CG54 guidelines, including following them through 2011 to identify those with recurrent UTIs. The numbers of children imaged, the imaging burden and efficiency, and urinary tract abnormalities detected by each guideline. Fewer children would have been imaged by CG54 than RCP (150 vs 427), but its sensitivity was lower, at 44% for detecting scarring, 10% for identifying vesicoureteric reflux and 40% for other abnormalities. Overall, it would have only detected one-quarter of the abnormal cases (8 vs 32) and would have missed five of nine children with scarring, including three with multiple lesions and one with renal impairment. Imposing an age restriction of <8 years to the RCP guidelines would reduce its screening rate by 20% and still detect 90% of the abnormalities. The CG54 guidelines do not alter the imaging efficiency compared to the RCP guidelines, but they are considerably less sensitive.

  7. Commonality of drug-associated adverse events detected by 4 commonly used data mining algorithms.

    PubMed

    Sakaeda, Toshiyuki; Kadoyama, Kaori; Minami, Keiko; Okuno, Yasushi

    2014-01-01

    Data mining algorithms have been developed for the quantitative detection of drug-associated adverse events (signals) from a large database on spontaneously reported adverse events. In the present study, the commonality of signals detected by 4 commonly used data mining algorithms was examined. A total of 2,231,029 reports were retrieved from the public release of the US Food and Drug Administration Adverse Event Reporting System database between 2004 and 2009. The deletion of duplicated submissions and revision of arbitrary drug names resulted in a reduction in the number of reports to 1,644,220. Associations with adverse events were analyzed for 16 unrelated drugs, using the proportional reporting ratio (PRR), reporting odds ratio (ROR), information component (IC), and empirical Bayes geometric mean (EBGM). All EBGM-based signals were included in the PRR-based signals as well as IC- or ROR-based ones, and PRR- and IC-based signals were included in ROR-based ones. The PRR scores of PRR-based signals were significantly larger for 15 of 16 drugs when adverse events were also detected as signals by the EBGM method, as were the IC scores of IC-based signals for all drugs; however, no such effect was observed in the ROR scores of ROR-based signals. The EBGM method was the most conservative among the 4 methods examined, which suggested its better suitability for pharmacoepidemiological studies. Further examinations should be performed on the reproducibility of clinical observations, especially for EBGM-based signals.

  8. Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.

    PubMed

    Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R

    2016-03-01

    This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

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

    PubMed

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

    2015-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

  11. Psychosocial stress predicts abnormal glucose metabolism: the Australian Diabetes, Obesity and Lifestyle (AusDiab) study.

    PubMed

    Williams, Emily D; Magliano, Dianna J; Tapp, Robyn J; Oldenburg, Brian F; Shaw, Jonathan E

    2013-08-01

    The evidence supporting a relationship between stress and diabetes has been inconsistent. This study examined the effects of stress on abnormal glucose metabolism, using a population-based sample of 3,759, with normoglycemia at baseline, from the Australian Diabetes, Obesity and Lifestyle study. Perceived stress and stressful life events were measured at baseline, with health behavior and anthropometric information also collected. Oral glucose tolerance tests were undertaken at baseline and 5-year follow-up. The primary outcome was the development of abnormal glucose metabolism (impaired fasting glucose, impaired glucose tolerance, and type 2 diabetes), according to WHO 1999 criteria. Perceived stress predicted incident abnormal glucose metabolism in women but not men, after multivariate adjustment. Life events showed an inconsistent relationship with abnormal glucose metabolism. Perceived stress predicted abnormal glucose metabolism in women. Healthcare professionals should consider psychosocial adversity when assessing risk factor profiles for the development of diabetes.

  12. 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

    2017-07-01

    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.

  13. Polygraph lie detection on real events in a laboratory setting.

    PubMed

    Bradley, M T; Cullen, M C

    1993-06-01

    This laboratory study dealt with real-life intense emotional events. Subjects generated embarrassing stories from their experience, then submitted to polygraph testing and, by lying, denied their stories and, by telling the truth, denied a randomly assigned story. Money was given as an incentive to be judged innocent on each story. An interrogator, blind to the stories, used Control Question Tests and found subjects more deceptive when lying than when truthful. Stories interacted with order such that lying on the second story was more easily detected than lying on the first. Embarrassing stories provide an alternative to the use of mock crimes to study lie detection in the laboratory.

  14. Detecting gait abnormalities after concussion or mild traumatic brain injury: A systematic review of single-task, dual-task, and complex gait.

    PubMed

    Fino, Peter C; Parrington, Lucy; Pitt, Will; Martini, Douglas N; Chesnutt, James C; Chou, Li-Shan; King, Laurie A

    2018-05-01

    While a growing number of studies have investigated the effects of concussion or mild traumatic brain injury (mTBI) on gait, many studies use different experimental paradigms and outcome measures. The path for translating experimental studies for objective clinical assessments of gait is unclear. This review asked 2 questions: 1) is gait abnormal after concussion/mTBI, and 2) what gait paradigms (single-task, dual-task, complex gait) detect abnormalities after concussion. Data sources included MEDLINE/PubMed, Scopus, Web of Science, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) accessed on March 14, 2017. Original research articles reporting gait outcomes in people with concussion or mTBI were included. Studies of moderate, severe, or unspecified TBI, and studies without a comparator were excluded. After screening 233 articles, 38 studies were included and assigned to one or more sections based on the protocol and reported outcomes. Twenty-six articles reported single-task simple gait outcomes, 24 reported dual-task simple gait outcomes, 21 reported single-task complex gait outcomes, and 10 reported dual-task complex gait outcomes. Overall, this review provides evidence for two conclusions: 1) gait is abnormal acutely after concussion/mTBI but generally resolves over time; and 2) the inconsistency of findings, small sample sizes, and small number of studies examining homogenous measures at the same time-period post-concussion highlight the need for replication across independent populations and investigators. Future research should concentrate on dual-task and complex gait tasks, as they showed promise for detecting abnormal locomotor function outside of the acute timeframe. Additionally, studies should provide detailed demographic and clinical characteristics to enable more refined comparisons across studies. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Microarray detection of human papilloma virus genotypes among Turkish women with abnormal cytology at a colposcopy unit

    PubMed Central

    Uzun Çilingir, Işıl; Bengisu, Ergin; Ağaçfidan, Ali; Koksal, Muammer Osman; Topuz, Samet; Berkman, Sinan; İyibozkurt, Ahmet Cem

    2013-01-01

    Objective: There is a well-known association between human papilloma virus (HPV) and cervical neoplasia. The aim of this study was to investigate the types of HPV DNA and to compare the results with colposcopic findings among women with abnormal cytology. Material and Methods: A series of 76 consecutive women attending the clinic with the usual referral indications (ASC-US or higher in Pap) were examined by the conventional diagnostic tools (PAP smear, colposcopy,punch biopsy) and subjected to HPV testing. For HPV genotyping, we used a commercially avaliable HPV DNA chip (Genomica-CLART) which is a PCR based microarray system.The HPV test detected 35types of HPV (HPV-6/-11/-16/-18/-26/-31/-33/-35/-39/-40/-42/-43/-44/-45/-51/-52/-53/-54/-56/-58/-59/-61/-62/-66/-70/-71/-72/-73/-81/-83/84/-85/-89). Results: Overall, 44.7% of all patients were HPV positive. HPV was positive in 35%, 51.9%, 77.7% of the ASCUS, LSIL and HSIL groups respectively and HPV 16 was the most prevalent type in all groups. 6 %of patients had mutiple infections. 57.8% of biopsy proven SIL’s were HPV positive. The most prevalent HPV type was HPV 16 (54.5%).Colposcopic assessment revealed pathologic findings in 94.7% of biopsy proven SIL cases. Conclusion: Although it has been reported that the prevalence of HPV in the general population is lower than Western countries, and the prevalence and distribution of genotypes are smilar in patients with abnormal cytology. Further population based studies are needed to determine the prevalance and type distribution of HPV with normal and abnormal cytology in Turkish women. Despite the new technological progress in HPV virion, colposcopy is still very important diagnostic tool in the management of abnormal smears. PMID:24592066

  16. Sensitivity and specificity of a urinary screening test used in an emergency setting to detect abnormal first trimester pregnancies.

    PubMed

    Teixeira, João L G; Rabaioli, Paola; Savaris, Ricardo F

    2015-01-01

    To evaluate the performance of a commercial urinary test to screen for abnormal first trimester pregnancies in women presenting to an emergency room. In this prospective observational cohort, women with a confirmed first trimester pregnancy (gestational age <12 weeks) provided a urine sample for diagnosing the viability of their gestation. Pregnancy viability and location testing were confirmed by ultrasound and/or laparoscopy. From 815 eligible patients for the study, 12 were excluded for not having a confirmed pregnancy (n = 6) or were lost to follow-up (n = 6). A total of 803 patients underwent testing and completed follow-up. The pretest probability of an abnormal pregnancy was 44% (9% for ectopic pregnancy and 35% for miscarriage). The test had the following parameters to identify an abnormal first-trimester pregnancy (sensitivity, 13%; 95% confidence interval [CI], 10-17; specificity, 82%; 95% CI, 78-86; positive predictive value, 36; 95% CI, 28-46; negative predictive value, 54; 95% CI, 50-58; accuracy, 47%; positive likelihood ratio, 0.74; 95% CI, 0.53-1.03; negative likelihood ratio, 1.06; 95% CI, 1-1.12). The reproducibility of the test in our study was high (kappa index between readers, 0.89; 95% CI, 0.77-1). In our emergency setting, we were not able to confirm that the commercial test is adequate to detect or exclude an abnormal first-trimester pregnancy. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Assessing Reliability of Medical Record Reviews for the Detection of Hospital Adverse Events.

    PubMed

    Ock, Minsu; Lee, Sang-il; Jo, Min-Woo; Lee, Jin Yong; Kim, Seon-Ha

    2015-09-01

    The purpose of this study was to assess the inter-rater reliability and intra-rater reliability of medical record review for the detection of hospital adverse events. We conducted two stages retrospective medical records review of a random sample of 96 patients from one acute-care general hospital. The first stage was an explicit patient record review by two nurses to detect the presence of 41 screening criteria (SC). The second stage was an implicit structured review by two physicians to identify the occurrence of adverse events from the positive cases on the SC. The inter-rater reliability of two nurses and that of two physicians were assessed. The intra-rater reliability was also evaluated by using test-retest method at approximately two weeks later. In 84.2% of the patient medical records, the nurses agreed as to the necessity for the second stage review (kappa, 0.68; 95% confidence interval [CI], 0.54 to 0.83). In 93.0% of the patient medical records screened by nurses, the physicians agreed about the absence or presence of adverse events (kappa, 0.71; 95% CI, 0.44 to 0.97). When assessing intra-rater reliability, the kappa indices of two nurses were 0.54 (95% CI, 0.31 to 0.77) and 0.67 (95% CI, 0.47 to 0.87), whereas those of two physicians were 0.87 (95% CI, 0.62 to 1.00) and 0.37 (95% CI, -0.16 to 0.89). In this study, the medical record review for detecting adverse events showed intermediate to good level of inter-rater and intra-rater reliability. Well organized training program for reviewers and clearly defining SC are required to get more reliable results in the hospital adverse event study.

  18. Regional Cerebral Abnormalities Measured by Frequency-Domain Near-Infrared Spectroscopy in Pediatric Patients During Extracorporeal Membrane Oxygenation.

    PubMed

    Tian, Fenghua; Jenks, Christopher; Potter, Donald; Miles, Darryl; Raman, Lakshmi

    Extracorporeal membrane oxygenation (ECMO) is a form of advanced cardiorespiratory support provided to critically ill patients with severe respiratory or cardiovascular failure. While children undergoing ECMO therapy have significant risk for neurological morbidity, currently there is a lack of reliable bedside tool to detect the neurologic events for patients on ECMO. This study assessed the feasibility of frequency-domain near-infrared spectroscopy (NIRS) for detection of intracranial complications during ECMO therapy. The frequency-domain NIRS device measured the absorption coefficient (µa) and reduced scattering coefficient (µs') at six cranial positions from seven pediatric patients (0-16 years) during ECMO support and five healthy controls (2-14 years). Regional abnormalities in both absorption and scattering were identified among ECMO patients. A main finding in this study is that the abnormalities in scattering appear to be associated with lower-than-normal µs' values in regional areas of the brain. Because light scattering originates from the intracellular structures (such as nuclei and mitochondria), a reduction in scattering primarily reflects loss or decreased density of the brain matter. The results from this study indicate a potential to use the frequency-domain NIRS as a safe and complementary technology for detection of intracranial complications during ECMO therapy.

  19. Optical recording of action potentials and other discrete physiological events: a perspective from signal detection theory.

    PubMed

    Sjulson, Lucas; Miesenböck, Gero

    2007-02-01

    Optical imaging of physiological events in real time can yield insights into biological function that would be difficult to obtain by other experimental means. However, the detection of all-or-none events, such as action potentials or vesicle fusion events, in noisy single-trial data often requires a careful balance of tradeoffs. The analysis of such experiments, as well as the design of optical reporters and instrumentation for them, is aided by an understanding of the principles of signal detection. This review illustrates these principles, using as an example action potential recording with optical voltage reporters.

  20. Guidelines to identify abnormalities after childhood urinary tract infections: a prospective audit

    PubMed Central

    Coulthard, Malcolm G; Lambert, Heather J; Vernon, Susan J; Hunter, Elizabeth W; Keir, Michael J

    2014-01-01

    Objective To compare the childhood urinary tract infection (UTI) guidelines from the Royal College of Physicians (RCP) in 1991 and from National Institute of Health and Care Excellence (NICE) (CG54) in 2007 by measuring their efficiency at detecting urinary tract abnormalities. Design Children with UTIs within the Newcastle Primary Care Trust (population 70 800 children) were referred and imaged according to the RCP guidelines during 2008, and these were compared to the activity that would have been undertaken if we had implemented the CG54 guidelines, including following them through 2011 to identify those with recurrent UTIs. Main outcome measures The numbers of children imaged, the imaging burden and efficiency, and urinary tract abnormalities detected by each guideline. Results Fewer children would have been imaged by CG54 than RCP (150 vs 427), but its sensitivity was lower, at 44% for detecting scarring, 10% for identifying vesicoureteric reflux and 40% for other abnormalities. Overall, it would have only detected one-quarter of the abnormal cases (8 vs 32) and would have missed five of nine children with scarring, including three with multiple lesions and one with renal impairment. Imposing an age restriction of <8 years to the RCP guidelines would reduce its screening rate by 20% and still detect 90% of the abnormalities. Interpretation The CG54 guidelines do not alter the imaging efficiency compared to the RCP guidelines, but they are considerably less sensitive. PMID:24436366

  1. 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.

  2. A quantitative estimate of schema abnormality in socially anxious and non-anxious individuals.

    PubMed

    Wenzel, Amy; Brendle, Jennifer R; Kerr, Patrick L; Purath, Donna; Ferraro, F Richard

    2007-01-01

    Although cognitive theories of anxiety suggest that anxious individuals are characterized by abnormal threat-relevant schemas, few empirical studies have estimated the nature of these cognitive structures using quantitative methods that lend themselves to inferential statistical analysis. In the present study, socially anxious (n = 55) and non-anxious (n = 62) participants completed 3 Q-Sort tasks to assess their knowledge of events that commonly occur in social or evaluative scenarios. Participants either sorted events according to how commonly they personally believe the events occur (i.e. "self" condition), or to how commonly they estimate that most people believe they occur (i.e. "other" condition). Participants' individual Q-Sorts were correlated with mean sorts obtained from a normative sample to obtain an estimate of schema abnormality, with lower correlations representing greater levels of abnormality. Relative to non-anxious participants, socially anxious participants' sorts were less strongly associated with sorts of the normative sample, particularly in the "self" condition, although secondary analyses suggest that some significant results might be explained, in part, by depression and experience with the scenarios. These results provide empirical support for the theoretical notion that threat-relevant self-schemas of anxious individuals are characterized by some degree of abnormality.

  3. Development and application of absolute quantitative detection by duplex chamber-based digital PCR of genetically modified maize events without pretreatment steps.

    PubMed

    Zhu, Pengyu; Fu, Wei; Wang, Chenguang; Du, Zhixin; Huang, Kunlun; Zhu, Shuifang; Xu, Wentao

    2016-04-15

    The possibility of the absolute quantitation of GMO events by digital PCR was recently reported. However, most absolute quantitation methods based on the digital PCR required pretreatment steps. Meanwhile, singleplex detection could not meet the demand of the absolute quantitation of GMO events that is based on the ratio of foreign fragments and reference genes. Thus, to promote the absolute quantitative detection of different GMO events by digital PCR, we developed a quantitative detection method based on duplex digital PCR without pretreatment. Moreover, we tested 7 GMO events in our study to evaluate the fitness of our method. The optimized combination of foreign and reference primers, limit of quantitation (LOQ), limit of detection (LOD) and specificity were validated. The results showed that the LOQ of our method for different GMO events was 0.5%, while the LOD is 0.1%. Additionally, we found that duplex digital PCR could achieve the detection results with lower RSD compared with singleplex digital PCR. In summary, the duplex digital PCR detection system is a simple and stable way to achieve the absolute quantitation of different GMO events. Moreover, the LOQ and LOD indicated that this method is suitable for the daily detection and quantitation of GMO events. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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

    Schmid, T E; Brinkworth, M H; Hill, F

    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 DNAmore » 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.« less

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

    EPA Science Inventory

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

  6. 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.

  7. Distributed Events in Sentinel: Design and Implementation of a Global Event Detector

    DTIC Science & Technology

    1999-01-01

    local event detector and a global event detector to detect events. Global event detector in this case plays the role of a message sending/receiving than...significant in this case . The system performance will decrease with increase in the number of applications involved in global event detection. Yet from a...Figure 8: A Global event tree (2) 1. Global composite event is detected at the GED In this case , the whole global composite event tree is sent to the

  8. Simultaneous Event-Triggered Fault Detection and Estimation for Stochastic Systems Subject to Deception Attacks.

    PubMed

    Li, Yunji; Wu, QingE; Peng, Li

    2018-01-23

    In this paper, a synthesized design of fault-detection filter and fault estimator is considered for a class of discrete-time stochastic systems in the framework of event-triggered transmission scheme subject to unknown disturbances and deception attacks. A random variable obeying the Bernoulli distribution is employed to characterize the phenomena of the randomly occurring deception attacks. To achieve a fault-detection residual is only sensitive to faults while robust to disturbances, a coordinate transformation approach is exploited. This approach can transform the considered system into two subsystems and the unknown disturbances are removed from one of the subsystems. The gain of fault-detection filter is derived by minimizing an upper bound of filter error covariance. Meanwhile, system faults can be reconstructed by the remote fault estimator. An recursive approach is developed to obtain fault estimator gains as well as guarantee the fault estimator performance. Furthermore, the corresponding event-triggered sensor data transmission scheme is also presented for improving working-life of the wireless sensor node when measurement information are aperiodically transmitted. Finally, a scaled version of an industrial system consisting of local PC, remote estimator and wireless sensor node is used to experimentally evaluate the proposed theoretical results. In particular, a novel fault-alarming strategy is proposed so that the real-time capacity of fault-detection is guaranteed when the event condition is triggered.

  9. Chromosomal abnormalities as a cause of recurrent abortions in Egypt

    PubMed Central

    El-Dahtory, Faeza Abdel Mogib

    2011-01-01

    BACKGROUND: In 4%-8% of couples with recurrent abortion, at least one of the partners has chromosomal abnormality. Most spontaneous miscarriages which happen in the first and second trimesters are caused by chromosomal abnormalities. These chromosomal abnormalities may be either numerical or structural. MATERIAL AND METHODS: Cytogenetic study was done for 73 Egyptian couples who presented with recurrent abortion at Genetic Unit of Children Hospital, Mansoura University. RESULTS: We found that the frequency of chromosomal abnormalities was not significantly different from that reported worldwide. Chromosomal abnormalities were detected in 9 (6.1%) of 73 couples. Seven of chromosomal abnormalities were structural and two of them were numerical. CONCLUSION: Our results showed that 6.1% of the couples with recurrent abortion had chromosomal abnormalities, with no other abnormalities. We suggest that it is necessary to perform cytogenetic in vestigation for couples who have recurrent abortion. PMID:22090718

  10. Association of recurrent pregnancy loss with chromosomal abnormalities and hereditary thrombophilias.

    PubMed

    Ocak, Z; Özlü, T; Ozyurt, O

    2013-06-01

    Recurrent pregnancy loss (RPL) which is generally known as >3 consecutive pregnancy losses before 20 weeks' gestation is seen in 0.5-2% of women. To evaluate the association of parental and fetal chromosomal abnormalities with recurrent pregnancy loss in our area and to analyze the frequency of three types of hereditary thrombophilia's; (MTHFR C677T polymorphisms, FV Leiden G1691A mutation and Prothrombin (factor II) G20210A mutation) in these female patients. The present case-control retrospective study was performed between February 2007 and December 2011 on 495 couples, who had two or more consecutive pregnancy losses before 20 weeks' gestation. We used conventional cytogenetic analysis and polymerase chain reaction-restriction fragment length polymorphism. Parental chromosomal abnormality was detected in 28 cases (2.8% of all cases, 5.7% of the couples) most of which (92.9%) were structural abnormalities. All of the structural abnormalities were balanced chromosomal translocations. Chromosomal analysis performed from the abortion materials detected a major chromosomal abnormality in 31.9% of the cases. The most frequently observed alteration in the hereditary thrombophilia genes was heterozygote mutation for the MTHFR C677T polymorphisms (n=55). Balanced translocations are the most commonly detected chromosomal abnormalities in couples being evaluated for recurrent pregnancy loss and these patients are the best candidates for offering prenatal genetic diagnosis by the help of which there is a possibility of obtaining a better reproductive outcome.

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

    PubMed Central

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

    2017-01-01

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

  12. Automatic detection of lexical change: an auditory event-related potential study.

    PubMed

    Muller-Gass, Alexandra; Roye, Anja; Kirmse, Ursula; Saupe, Katja; Jacobsen, Thomas; Schröger, Erich

    2007-10-29

    We investigated the detection of rare task-irrelevant changes in the lexical status of speech stimuli. Participants performed a nonlinguistic task on word and pseudoword stimuli that occurred, in separate conditions, rarely or frequently. Task performance for pseudowords was deteriorated relative to words, suggesting unintentional lexical analysis. Furthermore, rare word and pseudoword changes had a similar effect on the event-related potentials, starting as early as 165 ms. This is the first demonstration of the automatic detection of change in lexical status that is not based on a co-occurring acoustic change. We propose that, following lexical analysis of the incoming stimuli, a mental representation of the lexical regularity is formed and used as a template against which lexical change can be detected.

  13. Detecting, Monitoring, and Reporting Possible Adverse Drug Events Using an Arden-Syntax-based Rule Engine.

    PubMed

    Fehre, Karsten; Plössnig, Manuela; Schuler, Jochen; Hofer-Dückelmann, Christina; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2015-01-01

    The detection of adverse drug events (ADEs) is an important aspect of improving patient safety. The iMedication system employs predefined triggers associated with significant events in a patient's clinical data to automatically detect possible ADEs. We defined four clinically relevant conditions: hyperkalemia, hyponatremia, renal failure, and over-anticoagulation. These are some of the most relevant ADEs in internal medical and geriatric wards. For each patient, ADE risk scores for all four situations are calculated, compared against a threshold, and judged to be monitored, or reported. A ward-based cockpit view summarizes the results.

  14. The HAWC Real-time Flare Monitor for Rapid Detection of Transient Events

    NASA Astrophysics Data System (ADS)

    Abeysekara, A. U.; Alfaro, R.; Alvarez, C.; Álvarez, J. D.; Arceo, R.; Arteaga-Velázquez, J. C.; Avila Rojas, D.; Ayala Solares, H. A.; Barber, A. S.; Bautista-Elivar, N.; Becerra Gonzalez, J.; Becerril, A.; Belmont-Moreno, E.; BenZvi, S. Y.; Bernal, A.; Braun, J.; Brisbois, C.; Caballero-Mora, K. S.; Capistrán, T.; Carramiñana, A.; Casanova, S.; Castillo, M.; Cotti, U.; Cotzomi, J.; Coutiño de León, S.; De la Fuente, E.; De León, C.; Díaz-Vélez, J. C.; Dingus, B. L.; DuVernois, M. A.; Ellsworth, R. W.; Engel, K.; Fiorino, D. W.; Fraija, N.; García-González, J. A.; Garfias, F.; Gerhardt, M.; González, M. M.; González Muñoz, A.; Goodman, J. A.; Hampel-Arias, Z.; Harding, J. P.; Hernandez, S.; Hernandez-Almada, A.; Hona, B.; Hui, C. M.; Hüntemeyer, P.; Iriarte, A.; Jardin-Blicq, A.; Joshi, V.; Kaufmann, S.; Kieda, D.; Lauer, R. J.; Lee, W. H.; Lennarz, D.; León Vargas, H.; Linnemann, J. T.; Longinotti, A. L.; López-Cámara, D.; López-Coto, R.; Raya, G. Luis; Luna-García, R.; Malone, K.; Marinelli, S. S.; Martinez, O.; Martinez-Castellanos, I.; Martínez-Castro, J.; Martínez-Huerta, H.; Matthews, J. A.; Miranda-Romagnoli, P.; Moreno, E.; Mostafá, M.; Nellen, L.; Newbold, M.; Nisa, M. U.; Noriega-Papaqui, R.; Pelayo, R.; Pérez-Pérez, E. G.; Pretz, J.; Ren, Z.; Rho, C. D.; Rivière, C.; Rosa-González, D.; Rosenberg, M.; Ruiz-Velasco, E.; Salazar, H.; Salesa Greus, F.; Sandoval, A.; Schneider, M.; Schoorlemmer, H.; Sinnis, G.; Smith, A. J.; Springer, R. W.; Surajbali, P.; Taboada, I.; Tibolla, O.; Tollefson, K.; Torres, I.; Ukwatta, T. N.; Vianello, G.; Weisgarber, T.; Westerhoff, S.; Wisher, I. G.; Wood, J.; Yapici, T.; Younk, P. W.; Zepeda, A.; Zhou, H.

    2017-07-01

    We present the development of a real-time flare monitor for the High Altitude Water Cherenkov (HAWC) observatory. The flare monitor has been fully operational since 2017 January and is designed to detect very high energy (VHE; E ≳ 100 GeV) transient events from blazars on timescales lasting from 2 minutes to 10 hr in order to facilitate multiwavelength and multimessenger studies. These flares provide information for investigations into the mechanisms that power the blazars’ relativistic jets and accelerate particles within them, and they may also serve as probes of the populations of particles and fields in intergalactic space. To date, the detection of blazar flares in the VHE range has relied primarily on pointed observations by imaging atmospheric Cherenkov telescopes. The recently completed HAWC observatory offers the opportunity to study VHE flares in survey mode, scanning two-thirds of the entire sky every day with a field of view of ˜1.8 steradians. In this work, we report on the sensitivity of the HAWC real-time flare monitor and demonstrate its capabilities via the detection of three high-confidence VHE events in the blazars Markarian 421 and Markarian 501.

  15. Fusion of local and global detection systems to detect tuberculosis in chest radiographs.

    PubMed

    Hogeweg, Laurens; Mol, Christian; de Jong, Pim A; Dawson, Rodney; Ayles, Helen; van Ginneken, Bramin

    2010-01-01

    Automatic detection of tuberculosis (TB) on chest radiographs is a difficult problem because of the diverse presentation of the disease. A combination of detection systems for abnormalities and normal anatomy is used to improve detection performance. A textural abnormality detection system operating at the pixel level is combined with a clavicle detection system to suppress false positive responses. The output of a shape abnormality detection system operating at the image level is combined in a next step to further improve performance by reducing false negatives. Strategies for combining systems based on serial and parallel configurations were evaluated using the minimum, maximum, product, and mean probability combination rules. The performance of TB detection increased, as measured using the area under the ROC curve, from 0.67 for the textural abnormality detection system alone to 0.86 when the three systems were combined. The best result was achieved using the sum and product rule in a parallel combination of outputs.

  16. 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.

  17. Determining sensitivity/specificity of virtual reality-based neuropsychological tool for detecting residual abnormalities following sport-related concussion.

    PubMed

    Teel, Elizabeth; Gay, Michael; Johnson, Brian; Slobounov, Semyon

    2016-05-01

    Computer-based neuropsychological (NP) evaluation is an effective clinical tool used to assess cognitive function which complements the clinical diagnosis of a concussion. However, some researchers and clinicians argue its lack of ecological validity places limitations on externalizing results to a sensory rich athletic environment. Virtual reality-based NP assessment offers clinical advantages using an immersive environment and evaluating domains not typically assessed by traditional NP assessments. The sensitivity and specificity of detecting lingering cognitive abnormalities was examined on components of a virtual reality-based NP assessment battery to cohort affiliation (concussed vs. controls). Data were retrospectively gathered on 128 controls (no concussion) and 24 concussed college-age athletes on measures of spatial navigation, whole body reaction, attention, and balance in a virtual environment. Concussed athletes were tested within 10 days (M = 8.33, SD = 1.06) of concussion and were clinically asymptomatic at the time of testing. A priori alpha level was set at 0.05 for all tests. Spatial navigation (sensitivity 95.8%/specificity 91.4%, d = 1.89), whole body reaction time (sensitivity 95.2%/specificity 89.1%, d = 1.50) and combined virtual reality modules (sensitivity 95.8%,/specificity 96.1%, d = 3.59) produced high sensitivity/specificity values when determining performance-based variability between groups. Use of a virtual reality-based NP platform can detect lingering cognitive abnormalities resulting from concussion in clinically asymptomatic participants. Virtual reality NP platforms may compliment the traditional concussion assessment battery by providing novel information. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  18. Applying a Hidden Markov Model-Based Event Detection and Classification Algorithm to Apollo Lunar Seismic Data

    NASA Astrophysics Data System (ADS)

    Knapmeyer-Endrun, B.; Hammer, C.

    2014-12-01

    The seismometers that the Apollo astronauts deployed on the Moon provide the only recordings of seismic events from any extra-terrestrial body so far. These lunar events are significantly different from ones recorded on Earth, in terms of both signal shape and source processes. Thus they are a valuable test case for any experiment in planetary seismology. In this study, we analyze Apollo 16 data with a single-station event detection and classification algorithm in view of NASA's upcoming InSight mission to Mars. InSight, scheduled for launch in early 2016, has the goal to investigate Mars' internal structure by deploying a seismometer on its surface. As the mission does not feature any orbiter, continuous data will be relayed to Earth at a reduced rate. Full range data will only be available by requesting specific time-windows within a few days after the receipt of the original transmission. We apply a recently introduced algorithm based on hidden Markov models that requires only a single example waveform of each event class for training appropriate models. After constructing the prototypes we detect and classify impacts and deep and shallow moonquakes. Initial results for 1972 (year of station installation with 8 months of data) indicate a high detection rate of over 95% for impacts, of which more than 80% are classified correctly. Deep moonquakes, which occur in large amounts, but often show only very weak signals, are detected with less certainty (~70%). As there is only one weak shallow moonquake covered, results for this event class are not statistically significant. Daily adjustments of the background noise model help to reduce false alarms, which are mainly erroneous deep moonquake detections, by about 25%. The algorithm enables us to classify events that were previously listed in the catalog without classification, and, through the combined use of long period and short period data, identify some unlisted local impacts as well as at least two yet unreported

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

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

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

    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–Rmore » 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.« less

  20. An efficient approach to detection of weak seismic events at the Groningen gas field in the Netherlands

    NASA Astrophysics Data System (ADS)

    Wyer, P.; Zurek, B.

    2017-12-01

    Extensive additions to the Royal Dutch Meteorological Institute (KNMI) seismic monitoring network over recent years have yielded corresponding gains in detection of low magnitude seismicity induced by production of the Groningen gas field. A review of the weakest events in the seismic catalog demonstrates that waveforms from individual stations in the 30 x 35 km network area overlap sufficiently for normalized analytic envelopes to be constructively stacked without compensation for moveout, detection of individual station triggers or the need for more advanced approaches such as template matching. This observation opens the possibility of updating the historical catalog to current detection levels without having to implement more computationally expensive steps when reprocessing the legacy continuous data. A more consistent long term catalog would better constrain the frequency-size distribution (Gutenberg-Richter relationship) and provide a richer dataset for calibration of geomechanical and seismological models. To test the viability of a direct stacking approach, normalized waveform envelopes are partitioned by station into two discrete RMS stacks. Candidate seismic events are then identified as simultaneous STA/LTA triggers on both stacks. This partitioning has a minor impact on signal, but avoids the majority of false detections otherwise obtained on a single stack. Undesired detection of anthropogenic sources and earthquakes occurring outside the field can be further minimized by tuning the waveform frequency filters and trigger configuration. After minimal optimization, data from as few as 14 legacy stations are sufficient for robust automatic detection of known events approaching ML0 from the recent catalog. Ongoing work will determine residual false detection rates and whether previously unknown past events can be detected with sensitivities comparable to the modern KNMI catalog.

  1. 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

    2017-04-01

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

  2. Dynamic Fault Detection Chassis

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

    Mize, Jeffery J

    2007-01-01

    Abstract The high frequency switching megawatt-class High Voltage Converter Modulator (HVCM) developed by Los Alamos National Laboratory for the Oak Ridge National Laboratory's Spallation Neutron Source (SNS) is now in operation. One of the major problems with the modulator systems is shoot-thru conditions that can occur in a IGBTs H-bridge topology resulting in large fault currents and device failure in a few microseconds. The Dynamic Fault Detection Chassis (DFDC) is a fault monitoring system; it monitors transformer flux saturation using a window comparator and dV/dt events on the cathode voltage caused by any abnormality such as capacitor breakdown, transformer primarymore » turns shorts, or dielectric breakdown between the transformer primary and secondary. If faults are detected, the DFDC will inhibit the IGBT gate drives and shut the system down, significantly reducing the possibility of a shoot-thru condition or other equipment damaging events. In this paper, we will present system integration considerations, performance characteristics of the DFDC, and discuss its ability to significantly reduce costly down time for the entire facility.« less

  3. 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

  4. Automatic Multi-sensor Data Quality Checking and Event Detection for Environmental Sensing

    NASA Astrophysics Data System (ADS)

    LIU, Q.; Zhang, Y.; Zhao, Y.; Gao, D.; Gallaher, D. W.; Lv, Q.; Shang, L.

    2017-12-01

    With the advances in sensing technologies, large-scale environmental sensing infrastructures are pervasively deployed to continuously collect data for various research and application fields, such as air quality study and weather condition monitoring. In such infrastructures, many sensor nodes are distributed in a specific area and each individual sensor node is capable of measuring several parameters (e.g., humidity, temperature, and pressure), providing massive data for natural event detection and analysis. However, due to the dynamics of the ambient environment, sensor data can be contaminated by errors or noise. Thus, data quality is still a primary concern for scientists before drawing any reliable scientific conclusions. To help researchers identify potential data quality issues and detect meaningful natural events, this work proposes a novel algorithm to automatically identify and rank anomalous time windows from multiple sensor data streams. More specifically, (1) the algorithm adaptively learns the characteristics of normal evolving time series and (2) models the spatial-temporal relationship among multiple sensor nodes to infer the anomaly likelihood of a time series window for a particular parameter in a sensor node. Case studies using different data sets are presented and the experimental results demonstrate that the proposed algorithm can effectively identify anomalous time windows, which may resulted from data quality issues and natural events.

  5. Developing Fluorescence Sensor Systems for Early Detection of Nitrification Events in Chloraminated Drinking Water Distribution Systems

    EPA Science Inventory

    Detection of nitrification events in chloraminated drinking water distribution systems remains an ongoing challenge for many drinking water utilities, including Dallas Water Utilities (DWU) and the City of Houston (CoH). Each year, these utilities experience nitrification events ...

  6. Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis

    PubMed Central

    Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul

    2011-01-01

    Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238

  7. Application of the FICTION technique for the simultaneous detection of immunophenotype and chromosomal abnormalities in routinely fixed, paraffin wax embedded bone marrow trephines

    PubMed Central

    Korać, P; Jones, M; Dominis, M; Kušec, R; Mason, D Y; Banham, A H; Ventura, R A

    2005-01-01

    The use of interphase fluorescence in situ hybridisation (FISH) to study cytogenetic abnormalities in routinely fixed paraffin wax embedded tissue has become commonplace over the past decade. However, very few studies have applied FISH to routinely fixed bone marrow trephines (BMTs). This may be because of the acid based decalcification methods that are commonly used during the processing of BMTs, which may adversely affect the suitability of the sample for FISH analysis. For the first time, this report describes the simultaneous application of FISH and immunofluorescent staining (the FICTION technique) to formalin fixed, EDTA decalcified and paraffin wax embedded BMTs. This technique allows the direct correlation of genetic abnormalities to immunophenotype, and therefore will be particularly useful for the identification of genetic abnormalities in specific tumour cells present in BMTs. The application of this to routine clinical practice will assist diagnosis and the detection of minimal residual disease. PMID:16311361

  8. The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation

    NASA Astrophysics Data System (ADS)

    Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.

    2017-12-01

    In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long

  9. A Novel Event-Based Incipient Slip Detection Using Dynamic Active-Pixel Vision Sensor (DAVIS)

    PubMed Central

    Rigi, Amin

    2018-01-01

    In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments. PMID:29364190

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

    PubMed

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

    2015-09-15

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

  11. Sources of Infrasound events listed in IDC Reviewed Event Bulletin

    NASA Astrophysics Data System (ADS)

    Bittner, Paulina; Polich, Paul; Gore, Jane; Ali, Sherif; Medinskaya, Tatiana; Mialle, Pierrick

    2017-04-01

    Until 2003 two waveform technologies, i.e. seismic and hydroacoustic were used to detect and locate events included in the International Data Centre (IDC) Reviewed Event Bulletin (REB). The first atmospheric event was published in the REB in 2003, however automatic processing required significant improvements to reduce the number of false events. In the beginning of 2010 the infrasound technology was reintroduced to the IDC operations and has contributed to both automatic and reviewed IDC bulletins. The primary contribution of infrasound technology is to detect atmospheric events. These events may also be observed at seismic stations, which will significantly improve event location. Examples sources of REB events, which were detected by the International Monitoring System (IMS) infrasound network were fireballs (e.g. Bangkok fireball, 2015), volcanic eruptions (e.g. Calbuco, Chile 2015) and large surface explosions (e.g. Tjanjin, China 2015). Query blasts (e.g. Zheleznogorsk) and large earthquakes (e.g. Italy 2016) belong to events primarily recorded at seismic stations of the IMS network but often detected at the infrasound stations. In case of earthquakes analysis of infrasound signals may help to estimate the area affected by ground vibration. Infrasound associations to query blast events may help to obtain better source location. The role of IDC analysts is to verify and improve location of events detected by the automatic system and to add events which were missed in the automatic process. Open source materials may help to identify nature of some events. Well recorded examples may be added to the Reference Infrasound Event Database to help in analysis process. This presentation will provide examples of events generated by different sources which were included in the IDC bulletins.

  12. Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

    PubMed Central

    Akram, M. Usman; Khan, Shoab A.; Javed, Muhammad Younus

    2014-01-01

    National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. PMID:25136674

  13. Transient Volcano Deformation Event Detection over Variable Spatial Scales in Alaska

    NASA Astrophysics Data System (ADS)

    Li, J. D.; Rude, C. M.; Gowanlock, M.; Herring, T.; Pankratius, V.

    2016-12-01

    Transient deformation events driven by volcanic activity can be monitored using increasingly dense networks of continuous Global Positioning System (GPS) ground stations. The wide spatial extent of GPS networks, the large number of GPS stations, and the spatially and temporally varying scale of deformation events result in the mixing of signals from multiple sources. Typical analysis then necessitates manual identification of times and regions of volcanic activity for further study and the careful tuning of algorithmic parameters to extract possible transient events. Here we present a computer-aided discovery system that facilitates the discovery of potential transient deformation events at volcanoes by providing a framework for selecting varying spatial regions of interest and for tuning the analysis parameters. This site specification step in the framework reduces the spatial mixing of signals from different volcanic sources before applying filters to remove interfering signals originating from other geophysical processes. We analyze GPS data recorded by the Plate Boundary Observatory network and volcanic activity logs from the Alaska Volcano Observatory to search for and characterize transient inflation events in Alaska. We find 3 transient inflation events between 2008 and 2015 at the Akutan, Westdahl, and Shishaldin volcanoes in the Aleutian Islands. The inflation event detected in the first half of 2008 at Akutan is validated other studies, while the inflation events observed in early 2011 at Westdahl and in early 2013 at Shishaldin are previously unreported. Our analysis framework also incorporates modelling of the transient inflation events and enables a comparison of different magma chamber inversion models. Here, we also estimate the magma sources that best describe the deformation observed by the GPS stations at Akutan, Westdahl, and Shishaldin. We acknowledge support from NASA AIST-NNX15AG84G (PI: V. Pankratius).

  14. Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field

    PubMed Central

    Jeong, Myeong-Hun; Duckham, Matt

    2015-01-01

    This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes’ coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks. PMID:26343672

  15. Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field.

    PubMed

    Jeong, Myeong-Hun; Duckham, Matt

    2015-08-28

    This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes' coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks.

  16. [INDIVIDUAL EVALUATION OF LORETA ABNORMALITIES IN IDIOPATHIC GENERALIZED EPILEPSY].

    PubMed

    Clemens, Béla; Puskás, Szilvia; Besenyei, Mónika; Kondákor, István; Hollódy, Katalin; Fogarasi, Andrós; Bense, Katalin; Emri, Miklós; Opposits Gábor; Kovács, Noémi Zsuzsanna; Fekete, István

    2016-03-30

    Contemporary neuroimaging methods disclosed structural and functional cerebral abnormalities in idiopathic generalized epilepsies (IGEs). However, individual electrical (EEG) abnormalities have not been evaluated yet in IGE patients. IGE patients were investigated in the drug-free condition and after 3-6 month of antiepileptic treatment. To estimate the reproducibility of qEEG variables a retrospective recruited cohort of IGE patients was investigated. 19-channel resting state EEG activity was recorded. For each patient a total of 2 minutes EEG activity was analyzed by LORETA (Low Resolution Electromagnetic Tomography). Raw LORETA values were Z-transformed and projected to a MRI template. Z-values outside within the [+3Z] to [-3Z] range were labelled as statistically abnormal. 1. In drug-free condition, 41-50% of IGE patients showed abnormal LORETA values. 2. Abnormal LORETA findings showed great inter-individual variability. 3. Most abnormal LORETA-findings were symmetrical. 4. Most maximum Z-values were localized to frontal or temporal cortex. 5. Succesfull treatment was mostly coupled with disappearence of LORETA-abnormality, persistent seizures were accompanied by persistent LORETA abnormality. 1. LORETA abnormalities detected in the untreated condition reflect seizure-generating property of the cortex in IGE patients. 2. Maximum LORETA-Z abnormalities were topographically congruent with structural abnormalities reported by other research groups. 3. LORETA might help to investigate drug effects at the whole-brain level.

  17. Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG.

    PubMed

    Shafi, Mouhsin M; Westover, M Brandon; Cole, Andrew J; Kilbride, Ronan D; Hoch, Daniel B; Cash, Sydney S

    2012-10-23

    To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary.

  18. Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG

    PubMed Central

    Westover, M. Brandon; Cole, Andrew J.; Kilbride, Ronan D.; Hoch, Daniel B.; Cash, Sydney S.

    2012-01-01

    Objective: To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. Methods: We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Results: Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. Conclusions: In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary. PMID:23054233

  19. VASCULAR ABNORMALITIES IN DIABETIC RETINOPATHY ASSESSED WITH SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY WIDEFIELD IMAGING.

    PubMed

    Schaal, Karen B; Munk, Marion R; Wyssmueller, Iris; Berger, Lieselotte E; Zinkernagel, Martin S; Wolf, Sebastian

    2017-11-10

    To detect vascular abnormalities in diabetic retinopathy using swept-source optical coherence tomography angiography (SS-OCTA) widefield images, and to compare the findings with color fundus photographs (CFPs) using Early Treatment Diabetic Retinopathy Study severity grading. 3 mm × 3 mm and 12 mm × 12 mm scans were acquired to cover 70° to 80° of the posterior pole using a 100-kHz SS-OCTA instrument. Two masked graders assessed the presence of vascular abnormalities on SS-OCTA and the Early Treatment Diabetic Retinopathy Study level on CFP. The grading results were then compared. A total of 120 diabetic eyes (60 patients) were imaged with the SS-OCTA instrument. Cohort 1 (91 eyes; SS-OCTA grading only) showed microaneurysms in 91% (n = 83), intraretinal microvascular abnormalities in 79% (n = 72), and neovascularization in 21% (n = 19) of cases. Cohort 2 (52 eyes; CFP grading compared with SS-OCTA) showed microaneurysms on CFP in 90% (n = 47) and on SS-OCTA in 96% (n = 50) of cases. Agreement in intraretinal microvascular abnormality detection was fair (k = 0.2). Swept-source optical coherence tomography angiography detected 50% of intraretinal microvascular abnormality cases (n = 26), which were missed on CFP. Agreement in detecting neovascularization was moderate (k = 0.5). Agreement in detection of diabetic retinopathy features on CFP and SS-OCTA varies depending on the vascular changes examined. Swept-source optical coherence tomography angiography shows a higher detection rate of intraretinal microvascular abnormalities (P = 0.039), compared with Early Treatment Diabetic Retinopathy Study grading.

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

    PubMed Central

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

    2011-01-01

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

  1. Spine abnormalities depicted by magnetic resonance imaging in adolescent rowers.

    PubMed

    Maurer, Marvin; Soder, Ricardo Bernardi; Baldisserotto, Matteo

    2011-02-01

    Most lesions of the spine of athletes, which often are detected incidentally, do not cause important symptoms or make the athletes discontinue their physical activities. To better understand the significance of these lesions, new imaging studies have been conducted with asymptomatic athletes in several sports, aiming to detect potentially deleterious and disabling abnormalities. To compare the magnetic resonance imaging (MRI) lumbar spine findings in a group of asymptomatic adolescent rowers and in a control group of adolescents matched according to age and sex who do not practice any regular physical activity. Cohort study (prevalence); Level of evidence, 3. Our study evaluated 44 asymptomatic adolescent boys distributed in 2 groups of 22 rowers and 22 control subjects. All the examinations were performed using a 0.35-T open-field MRI unit and evaluated by 2 experienced radiologists blinded to the study groups. Each MRI scan was analyzed for the presence of disc degeneration/desiccation, herniated or bulging disc, pars interarticularis stress reaction, and spondylolysis. The Student t test and the Fisher exact test were used for statistical analyses. Nine rowers (40.9%) had at least 1 abnormality detected by MRI in the lumbar spine, whereas only 2 participants (9.1%) in the control group had at least 1 MRI abnormality (P = .03). Seven disc changes (31.8%) and 6 pars abnormalities (27.3%) were found in the group of elite rowers. In the control group, 3 disc changes (13.6%) and no pars abnormalities were found in the MR scans. The comparison between groups showed statistically significant differences in stress reaction of the pars articularis. Disc disease and pars interarticularis stress reaction are prevalent abnormalities of the lumbar spine of high-performance rowers.

  2. 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).

  3. Abnormal Superior Temporal Connectivity During Fear Perception in Schizophrenia

    PubMed Central

    Leitman, David I.; Loughead, James; Wolf, Daniel H.; Ruparel, Kosha; Kohler, Christian G.; Elliott, Mark A.; Bilker, Warren B.; Gur, Raquel E.; Gur, Ruben C.

    2008-01-01

    Patients with schizophrenia have difficulty in decoding facial affect. A study using event–related functional neuroimaging indicated that errors in fear detection in schizophrenia are associated with paradoxically higher activation in the amygdala and an associated network implicated in threat detection. Furthermore, this exaggerated activation to fearful faces correlated with severity of flat affect. These findings suggest that abnormal threat detection processing may reflect disruptions between nodes that comprise the affective appraisal circuit. Here we examined connectivity within this network by determining the pattern of intercorrelations among brain regions (regions of interest) significantly activated during fear identification in both healthy controls and patients using a novel procedure CORANOVA. This analysis tests differences in the interregional correlation strength between schizophrenia and healthy controls. Healthy subjects' task activation was principally characterized by robust correlations between medial structures like thalamus (THA) and amygdala (AMY) and middle frontal (MF), inferior frontal (IF), and prefrontal cortical (PFC) regions. In contrast, schizophrenia patients displayed no significant correlations between the medial regions and either MF or IF. Further, patients had significantly higher correlations between occipital lingual gyrus and superior temporal gyrus than healthy subjects. These between-group connectivity differences suggest that schizophrenia threat detection impairment may stem from abnormal stimulus integration. Such abnormal integration may disrupt the evaluation of threat within fronto-cortical regions. PMID:18550592

  4. The value of HEAD-US system in detecting subclinical abnormalities in joints of patients with hemophilia.

    PubMed

    De la Corte-Rodriguez, Hortensia; Rodriguez-Merchan, E Carlos; Alvarez-Roman, M Teresa; Martin-Salces, Mónica; Martinoli, Carlo; Jimenez-Yuste, Víctor

    2018-03-01

    Prevention of hemarthrosis is the key factor in the adequate management of people with hemophilia (PWH). If hemarthrosis occurs, early diagnosis of joint damage is essential to make personalized treatments. This study is aimed at gaining an understanding of the ability of point-of-care ultrasound (US) using the `Hemophilia Early Arthropathy Detection with Ultrasound´ (HEAD-US) protocol to detect abnormalities in joints without history of hemarthrosis and clinically asymptomatic joints of PWH. The sample included 976 joints from 167 PWH (mean age 24.86 years). Data were collected from routine practice over a 3-year period and analyzed based on history of hemarthrosis and results of clinical (HJHS 2.1) and HEAD-US examinations. In our series, 14% of patients exhibited HEAD-US signs of incipient arthropathy in joints with no history of bleeding and with a HJHS 2.1 score of 0. The most severely involved joint was the right ankle. Synovitis, articular cartilage and subchondral bone damage scores in joints with subclinical findings were slower than in joints with previous hemarthroses or HJHS 2.1 > 1 Conclusions: Our study demonstrates that HEAD-US is better than hemarthrosis records and the HJHS 2.1 scale in detecting the early signs of joint damage in PWH.

  5. The value of subtraction MRI in detection of amyloid-related imaging abnormalities with oedema or effusion in Alzheimer's patients: An interobserver study.

    PubMed

    Martens, Roland M; Bechten, Arianne; Ingala, Silvia; van Schijndel, Ronald A; Machado, Vania B; de Jong, Marcus C; Sanchez, Esther; Purcell, Derk; Arrighi, Michael H; Brashear, Robert H; Wattjes, Mike P; Barkhof, Frederik

    2018-03-01

    Immunotherapeutic treatments targeting amyloid-β plaques in Alzheimer's disease (AD) are associated with the presence of amyloid-related imaging abnormalities with oedema or effusion (ARIA-E), whose detection and classification is crucial to evaluate subjects enrolled in clinical trials. To investigate the applicability of subtraction MRI in the ARIA-E detection using an established ARIA-E-rating scale. We included 75 AD patients receiving bapineuzumab treatment, including 29 ARIA-E cases. Five neuroradiologists rated their brain MRI-scans with and without subtraction images. The accuracy of evaluating the presence of ARIA-E, intraclass correlation coefficient (ICC) and specific agreement was calculated. Subtraction resulted in higher sensitivity (0.966) and lower specificity (0.970) than native images (0.959, 0.991, respectively). Individual rater detection was excellent. ICC scores ranged from excellent to good, except for gyral swelling (moderate). Excellent negative and good positive specific agreement among all ARIA-E imaging features was reported in both groups. Combining sulcal hyperintensity and gyral swelling significantly increased positive agreement for subtraction images. Subtraction MRI has potential as a visual aid increasing the sensitivity of ARIA-E assessment. However, in order to improve its usefulness isotropic acquisition and enhanced training are required. The ARIA-E rating scale may benefit from combining sulcal hyperintensity and swelling. • Subtraction technique can improve detection amyloid-related imaging-abnormalities with edema/effusion in Alzheimer's patients. • The value of ARIA-E detection, classification and monitoring using subtraction was assessed. • Validation of an established ARIA-E rating scale, recommendations for improvement are reported. • Complementary statistical methods were employed to measure accuracy, inter-rater-reliability and specific agreement.

  6. Hypothalamic mitochondrial abnormalities occur downstream of inflammation in diet-induced obesity.

    PubMed

    Carraro, Rodrigo S; Souza, Gabriela F; Solon, Carina; Razolli, Daniela S; Chausse, Bruno; Barbizan, Roberta; Victorio, Sheila C; Velloso, Licio A

    2018-01-15

    Hypothalamic dysfunction is a common feature of experimental obesity. Studies have identified at least three mechanisms involved in the development of hypothalamic neuronal defects in diet-induced obesity: i, inflammation; ii, endoplasmic reticulum stress; and iii, mitochondrial abnormalities. However, which of these mechanisms is activated earliest in response to the consumption of large portions of dietary fats is currently unknown. Here, we used immunoblot, real-time PCR, mitochondrial respiration assays and transmission electron microscopy to evaluate markers of inflammation, endoplasmic reticulum stress and mitochondrial abnormalities in the hypothalamus of Swiss mice fed a high-fat diet for up to seven days. In the present study we show that the expression of the inflammatory chemokine fractalkine was the earliest event detected. Its hypothalamic expression increased as early as 3 h after the introduction of a high-fat diet and was followed by the increase of cytokines. GPR78, an endoplasmic reticulum chaperone, was increased 6 h after the introduction of a high-fat diet, however the actual triggering of endoplasmic reticulum stress was only detected three days later, when IRE-1α was increased. Mitofusin-2, a protein involved in mitochondrial fusion and tethering of mitochondria to the endoplasmic reticulum, underwent a transient reduction 24 h after the introduction of a high-fat diet and then increased after seven days. There were no changes in hypothalamic mitochondrial respiration during the experimental period, however there were reductions in mitochondria/endoplasmic reticulum contact sites, beginning three days after the introduction of a high-fat diet. The inhibition of TNF-α with infliximab resulted in the normalization of mitofusin-2 levels 24 h after the introduction of the diet. Thus, inflammation is the earliest mechanism activated in the hypothalamus after the introduction of a high-fat diet and may play a mechanistic role in the

  7. An Event-Based Verification Scheme for the Real-Time Flare Detection System at Kanzelhöhe Observatory

    NASA Astrophysics Data System (ADS)

    Pötzi, W.; Veronig, A. M.; Temmer, M.

    2018-06-01

    In the framework of the Space Situational Awareness program of the European Space Agency (ESA/SSA), an automatic flare detection system was developed at Kanzelhöhe Observatory (KSO). The system has been in operation since mid-2013. The event detection algorithm was upgraded in September 2017. All data back to 2014 was reprocessed using the new algorithm. In order to evaluate both algorithms, we apply verification measures that are commonly used for forecast validation. In order to overcome the problem of rare events, which biases the verification measures, we introduce a new event-based method. We divide the timeline of the Hα observations into positive events (flaring period) and negative events (quiet period), independent of the length of each event. In total, 329 positive and negative events were detected between 2014 and 2016. The hit rate for the new algorithm reached 96% (just five events were missed) and a false-alarm ratio of 17%. This is a significant improvement of the algorithm, as the original system had a hit rate of 85% and a false-alarm ratio of 33%. The true skill score and the Heidke skill score both reach values of 0.8 for the new algorithm; originally, they were at 0.5. The mean flare positions are accurate within {±} 1 heliographic degree for both algorithms, and the peak times improve from a mean difference of 1.7± 2.9 minutes to 1.3± 2.3 minutes. The flare start times that had been systematically late by about 3 minutes as determined by the original algorithm, now match the visual inspection within -0.47± 4.10 minutes.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  9. Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands

    PubMed Central

    Groot, Anne; Bots, Michiel L; Rutten, Frans H; den Ruijter, Hester M; Numans, Mattijs E; Vaartjes, Ilonca

    2015-01-01

    Background GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. Aim To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a primary care population. Design and setting A cohort study of patients enlisted with academic general practices in the Netherlands (the Utrecht Health Project [UHP]). Method Incident CV events were extracted from the GP records. MEANS algorithm was used to assess ECG abnormalities. Cox proportional hazards modelling was applied to relate ECG abnormalities to CV events. For a prediction model only with SCORE variables, and a model with SCORE+ECG abnormalities, the discriminative value (area under the receiver operator curve [AUC]) and the net reclassification improvement (NRI) were estimated. Results A total of 2370 participants aged 38–74 years were included, all eligible for CV risk assessment. During a mean follow-up of 7.8 years, 172 CV events occurred. In 19% of the participants at least one ECG abnormality was found (Lausanne criteria). Presence of atrial fibrillation/flutter (AF) and myocardial infarction (MI) were significantly related to CV events. The AUC of the SCORE risk factors was 0.75 (95% CI = 0.71 to 0.79). Addition of MI or AF resulted in an AUC of 0.76 (95% CI = 0.72 to 0.79) and 0.75 (95% CI = 0.72 to 0.79), respectively. The NRI with the addition of ECG abnormalities was small (MI 1.0%; 95% CI = −3.2% to 6.9%; AF 0.5%; 95% CI = −3.5% to 3.3%). Conclusion Performing a resting ECG in a primary care population does not seem to improve risk classification when SCORE information — age, sex, smoking, systolic blood pressure, and total cholesterol/HDL ratio — is already available. PMID:25548311

  10. Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands.

    PubMed

    Groot, Anne; Bots, Michiel L; Rutten, Frans H; den Ruijter, Hester M; Numans, Mattijs E; Vaartjes, Ilonca

    2015-01-01

    GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a primary care population. A cohort study of patients enlisted with academic general practices in the Netherlands (the Utrecht Health Project [UHP]). Incident CV events were extracted from the GP records. MEANS algorithm was used to assess ECG abnormalities. Cox proportional hazards modelling was applied to relate ECG abnormalities to CV events. For a prediction model only with SCORE variables, and a model with SCORE+ECG abnormalities, the discriminative value (area under the receiver operator curve [AUC]) and the net reclassification improvement (NRI) were estimated. A total of 2370 participants aged 38-74 years were included, all eligible for CV risk assessment. During a mean follow-up of 7.8 years, 172 CV events occurred. In 19% of the participants at least one ECG abnormality was found (Lausanne criteria). Presence of atrial fibrillation/flutter (AF) and myocardial infarction (MI) were significantly related to CV events. The AUC of the SCORE risk factors was 0.75 (95% CI = 0.71 to 0.79). Addition of MI or AF resulted in an AUC of 0.76 (95% CI = 0.72 to 0.79) and 0.75 (95% CI = 0.72 to 0.79), respectively. The NRI with the addition of ECG abnormalities was small (MI 1.0%; 95% CI = -3.2% to 6.9%; AF 0.5%; 95% CI = -3.5% to 3.3%). Performing a resting ECG in a primary care population does not seem to improve risk classification when SCORE information - age, sex, smoking, systolic blood pressure, and total cholesterol/HDL ratio - is already available. © British Journal of General Practice 2015.

  11. Automatic Detection of Whole Night Snoring Events Using Non-Contact Microphone

    PubMed Central

    Dafna, Eliran; Tarasiuk, Ariel; Zigel, Yaniv

    2013-01-01

    Objective Although awareness of sleep disorders is increasing, limited information is available on whole night detection of snoring. Our study aimed to develop and validate a robust, high performance, and sensitive whole-night snore detector based on non-contact technology. Design Sounds during polysomnography (PSG) were recorded using a directional condenser microphone placed 1 m above the bed. An AdaBoost classifier was trained and validated on manually labeled snoring and non-snoring acoustic events. Patients Sixty-seven subjects (age 52.5±13.5 years, BMI 30.8±4.7 kg/m2, m/f 40/27) referred for PSG for obstructive sleep apnea diagnoses were prospectively and consecutively recruited. Twenty-five subjects were used for the design study; the validation study was blindly performed on the remaining forty-two subjects. Measurements and Results To train the proposed sound detector, >76,600 acoustic episodes collected in the design study were manually classified by three scorers into snore and non-snore episodes (e.g., bedding noise, coughing, environmental). A feature selection process was applied to select the most discriminative features extracted from time and spectral domains. The average snore/non-snore detection rate (accuracy) for the design group was 98.4% based on a ten-fold cross-validation technique. When tested on the validation group, the average detection rate was 98.2% with sensitivity of 98.0% (snore as a snore) and specificity of 98.3% (noise as noise). Conclusions Audio-based features extracted from time and spectral domains can accurately discriminate between snore and non-snore acoustic events. This audio analysis approach enables detection and analysis of snoring sounds from a full night in order to produce quantified measures for objective follow-up of patients. PMID:24391903

  12. Automatic detection of whole night snoring events using non-contact microphone.

    PubMed

    Dafna, Eliran; Tarasiuk, Ariel; Zigel, Yaniv

    2013-01-01

    Although awareness of sleep disorders is increasing, limited information is available on whole night detection of snoring. Our study aimed to develop and validate a robust, high performance, and sensitive whole-night snore detector based on non-contact technology. Sounds during polysomnography (PSG) were recorded using a directional condenser microphone placed 1 m above the bed. An AdaBoost classifier was trained and validated on manually labeled snoring and non-snoring acoustic events. Sixty-seven subjects (age 52.5 ± 13.5 years, BMI 30.8 ± 4.7 kg/m(2), m/f 40/27) referred for PSG for obstructive sleep apnea diagnoses were prospectively and consecutively recruited. Twenty-five subjects were used for the design study; the validation study was blindly performed on the remaining forty-two subjects. To train the proposed sound detector, >76,600 acoustic episodes collected in the design study were manually classified by three scorers into snore and non-snore episodes (e.g., bedding noise, coughing, environmental). A feature selection process was applied to select the most discriminative features extracted from time and spectral domains. The average snore/non-snore detection rate (accuracy) for the design group was 98.4% based on a ten-fold cross-validation technique. When tested on the validation group, the average detection rate was 98.2% with sensitivity of 98.0% (snore as a snore) and specificity of 98.3% (noise as noise). Audio-based features extracted from time and spectral domains can accurately discriminate between snore and non-snore acoustic events. This audio analysis approach enables detection and analysis of snoring sounds from a full night in order to produce quantified measures for objective follow-up of patients.

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

    PubMed

    Bendixen, Alexandra; Andersen, Søren K

    2013-05-01

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

  14. Detecting adverse events in surgery: comparing events detected by the Veterans Health Administration Surgical Quality Improvement Program and the Patient Safety Indicators.

    PubMed

    Mull, Hillary J; Borzecki, Ann M; Loveland, Susan; Hickson, Kathleen; Chen, Qi; MacDonald, Sally; Shin, Marlena H; Cevasco, Marisa; Itani, Kamal M F; Rosen, Amy K

    2014-04-01

    The Patient Safety Indicators (PSIs) use administrative data to screen for select adverse events (AEs). In this study, VA Surgical Quality Improvement Program (VASQIP) chart review data were used as the gold standard to measure the criterion validity of 5 surgical PSIs. Independent chart review was also used to determine reasons for PSI errors. The sensitivity, specificity, and positive predictive value of PSI software version 4.1a were calculated among Veterans Health Administration hospitalizations (2003-2007) reviewed by VASQIP (n = 268,771). Nurses re-reviewed a sample of hospitalizations for which PSI and VASQIP AE detection disagreed. Sensitivities ranged from 31% to 68%, specificities from 99.1% to 99.8%, and positive predictive values from 31% to 72%. Reviewers found that coding errors accounted for some PSI-VASQIP disagreement; some disagreement was also the result of differences in AE definitions. These results suggest that the PSIs have moderate criterion validity; however, some surgical PSIs detect different AEs than VASQIP. Future research should explore using both methods to evaluate surgical quality. Published by Elsevier Inc.

  15. 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.

  16. A Patch-Based Method for Repetitive and Transient Event Detection in Fluorescence Imaging

    PubMed Central

    Boulanger, Jérôme; Gidon, Alexandre; Kervran, Charles; Salamero, Jean

    2010-01-01

    Automatic detection and characterization of molecular behavior in large data sets obtained by fast imaging in advanced light microscopy become key issues to decipher the dynamic architectures and their coordination in the living cell. Automatic quantification of the number of sudden and transient events observed in fluorescence microscopy is discussed in this paper. We propose a calibrated method based on the comparison of image patches expected to distinguish sudden appearing/vanishing fluorescent spots from other motion behaviors such as lateral movements. We analyze the performances of two statistical control procedures and compare the proposed approach to a frame difference approach using the same controls on a benchmark of synthetic image sequences. We have then selected a molecular model related to membrane trafficking and considered real image sequences obtained in cells stably expressing an endocytic-recycling trans-membrane protein, the Langerin-YFP, for validation. With this model, we targeted the efficient detection of fast and transient local fluorescence concentration arising in image sequences from a data base provided by two different microscopy modalities, wide field (WF) video microscopy using maximum intensity projection along the axial direction and total internal reflection fluorescence microscopy. Finally, the proposed detection method is briefly used to statistically explore the effect of several perturbations on the rate of transient events detected on the pilot biological model. PMID:20976222

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  18. 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.

  19. Neural conduction abnormality in the brain stem and prevalence of the abnormality in late preterm infants with perinatal problems.

    PubMed

    Jiang, Ze Dong

    2013-08-01

    Neurodevelopment in late preterm infants has recently attracted considerable interest. The prevalence of brain stem conduction abnormality remains unknown. We examined maximum length sequence brain stem auditory evoked response in 163 infants, born at 33-36 weeks gestation, who had various perinatal problems. Compared with 49 normal term infants without problems, the late preterm infants showed a significant increase in III-V and I-V interpeak intervals at all 91-910/s clicks, particularly at 455 and 910/s (p < 0.01-0.001). The I-III interval was slightly increased, without statistically significant difference from the controls at any click rates. These results suggest that neural conduction along the, mainly more central or rostral part of, auditory brain stem is abnormal in late preterm infants with perinatal problems. Of the 163 late preterm infant, the number (and percentage rate) of infants with abnormal I-V interval at 91, 227, 455, and 910/s clicks was, respectively, 11 (6.5%), 17 (10.2%), 37 (22.3%), and 31 (18.7%). The number (and percentage rate) of infants with abnormal III-V interval at these rates was, respectively, 10 (6.0%), 17 (10.2%), 28 (16.9), and 36 (21.2%). Apparently, the abnormal rates were much higher at 455 and 910/s clicks than at lower rates 91 and 227/s. In total, 42 (25.8%) infants showed abnormal I-V and/or III-V intervals. Conduction in, mainly in the more central part, the brain stem is abnormal in late preterm infants with perinatal problems. The abnormality is more detectable at high- than at low-rate sensory stimulation. A quarter of late preterm infants with perinatal problems have brain stem conduction abnormality.

  20. Temporal lobe developmental malformations and epilepsy: dual pathology and bilateral hippocampal abnormalities.

    PubMed

    Ho, S S; Kuzniecky, R I; Gilliam, F; Faught, E; Morawetz, R

    1998-03-01

    Temporal lobe developmental malformations (TLDM) with focal cortical dysplasia and balloon cells may coexist with mesial temporal sclerosis. The true incidence of this dual pathology is unknown. Our aim was to assess the frequency of amygdala (AM)-hippocampal abnormality in a homogeneous population with this specific developmental malformation. MRI-based volumetry of the AM and hippocampal formation (HF) in 30 patients with unilateral TLDM and intractable partial epilepsy was performed. A volume normalization process defined a normal range of HF and AM volumes in control subjects, and enabled the detection of bilateral volume loss. Normalized volumes detected HF atrophy in 26 patients (nine unilateral and 17 bilateral) and AM atrophy in 18 patients (three unilateral and 15 bilateral). Visual analysis detected unilateral HF abnormality in 21 patients and bilateral abnormality in two. When compared with a group of patients with temporal lobe epilepsy and pure hippocampal sclerosis (N = 92), where volumetry revealed bilateral HF atrophy in 18%, a significant difference in the frequency of bilateral HF atrophy was found (p < 0.0001). Dual pathology is frequent in patients with TLDM (87%), and the AM-HF abnormality is often bilateral (57%). Our data suggest that more widespread and potentially epileptogenic lesions coexist with visibly detectable unilateral TLDM. This has implications for the selection of patients for temporal lobe surgery and may influence surgical strategies.

  1. SmartFABER: Recognizing fine-grained abnormal behaviors for early detection of mild cognitive impairment.

    PubMed

    Riboni, Daniele; Bettini, Claudio; Civitarese, Gabriele; Janjua, Zaffar Haider; Helaoui, Rim

    2016-02-01

    In an ageing world population more citizens are at risk of cognitive impairment, with negative consequences on their ability of independent living, quality of life and sustainability of healthcare systems. Cognitive neuroscience researchers have identified behavioral anomalies that are significant indicators of cognitive decline. A general goal is the design of innovative methods and tools for continuously monitoring the functional abilities of the seniors at risk and reporting the behavioral anomalies to the clinicians. SmartFABER is a pervasive system targeting this objective. A non-intrusive sensor network continuously acquires data about the interaction of the senior with the home environment during daily activities. A novel hybrid statistical and knowledge-based technique is used to analyses this data and detect the behavioral anomalies, whose history is presented through a dashboard to the clinicians. Differently from related works, SmartFABER can detect abnormal behaviors at a fine-grained level. We have fully implemented the system and evaluated it using real datasets, partly generated by performing activities in a smart home laboratory, and partly acquired during several months of monitoring of the instrumented home of a senior diagnosed with MCI. Experimental results, including comparisons with other activity recognition techniques, show the effectiveness of SmartFABER in terms of recognition rates. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Unsupervised Pattern Classifier for Abnormality-Scaling of Vibration Features for Helicopter Gearbox Fault Diagnosis

    NASA Technical Reports Server (NTRS)

    Jammu, Vinay B.; Danai, Kourosh; Lewicki, David G.

    1996-01-01

    A new unsupervised pattern classifier is introduced for on-line detection of abnormality in features of vibration that are used for fault diagnosis of helicopter gearboxes. This classifier compares vibration features with their respective normal values and assigns them a value in (0, 1) to reflect their degree of abnormality. Therefore, the salient feature of this classifier is that it does not require feature values associated with faulty cases to identify abnormality. In order to cope with noise and changes in the operating conditions, an adaptation algorithm is incorporated that continually updates the normal values of the features. The proposed classifier is tested using experimental vibration features obtained from an OH-58A main rotor gearbox. The overall performance of this classifier is then evaluated by integrating the abnormality-scaled features for detection of faults. The fault detection results indicate that the performance of this classifier is comparable to the leading unsupervised neural networks: Kohonen's Feature Mapping and Adaptive Resonance Theory (AR72). This is significant considering that the independence of this classifier from fault-related features makes it uniquely suited to abnormality-scaling of vibration features for fault diagnosis.

  3. Cervical cytology of atypical squamous cells, cannot exclude high-grade squamous intra-epithelial lesion: significance of age, human papillomavirus DNA detection and previous abnormal cytology on follow-up outcomes.

    PubMed

    Sung, Chang Ohk; Oh, Young Lyun; Song, Sang Yong

    2011-11-01

    Despite the usefulness of Pap tests for cancer screening, outcomes can be difficult to predict when atypical squamous cells (ASCs) are identified. According to the 2001 Bethesda system, ASCs can be subdivided into two groups: ASCs of undetermined significance (ASC-US); and ASCs, cannot exclude high-grade squamous intra-epithelial lesion (ASC-H). ASC-H interpretations are uncommon, and studies involving this type of lesion are based on small numbers of cases. Cross-sectional, retrospective study of 392 ASC-H cases. The follow-up outcomes of ASC-H cases that were diagnosed during routine primary screening between 2002 and 2008 were investigated, and relationships between clinicopathological parameters were assessed, particularly positive test for high-risk HPV (HPV) DNA, patient age at diagnosis and previous abnormal cytology. Of the 392 cases, high-grade squamous intra-epithelial lesion (HSIL) was detected in 111 (28.3%) cases, squamous cell carcinoma was detected in 15 (3.8%) cases, low-grade squamous intra-epithelial lesion was detected in 37 (9.4%) cases, reactive change was detected in 178 (45.4%) cases, atrophy was detected in 47 (12.0%) cases, and adenocarcinoma was detected in four (1.0%) cases. The prevalence of HSIL or greater was 27.8% for women aged ≥ 40 years, and 52.3% for women aged <40 years (p<0.001). HPV positivity in ASC-H smears was significantly associated with HSIL or greater, irrespective of age (<40 years, p=0.003; ≥ 40 years, p<0.001). ASC-H with previous abnormal cytology greater than ASC-US showed a significantly higher detection rate for HSIL or greater at follow-up (p<0.001). Patient age, positive HPV DNA test and previous abnormal cytology are useful predictors of underlying HSIL or greater in women with ASC-H. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  4. 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.

  5. Integrated hydraulic and organophosphate pesticide injection simulations for enhancing event detection in water distribution systems.

    PubMed

    Schwartz, Rafi; Lahav, Ori; Ostfeld, Avi

    2014-10-15

    As a complementary step towards solving the general event detection problem of water distribution systems, injection of the organophosphate pesticides, chlorpyrifos (CP) and parathion (PA), were simulated at various locations within example networks and hydraulic parameters were calculated over 24-h duration. The uniqueness of this study is that the chemical reactions and byproducts of the contaminants' oxidation were also simulated, as well as other indicative water quality parameters such as alkalinity, acidity, pH and the total concentration of free chlorine species. The information on the change in water quality parameters induced by the contaminant injection may facilitate on-line detection of an actual event involving this specific substance and pave the way to development of a generic methodology for detecting events involving introduction of pesticides into water distribution systems. Simulation of the contaminant injection was performed at several nodes within two different networks. For each injection, concentrations of the relevant contaminants' mother and daughter species, free chlorine species and water quality parameters, were simulated at nodes downstream of the injection location. The results indicate that injection of these substances can be detected at certain conditions by a very rapid drop in Cl2, functioning as the indicative parameter, as well as a drop in alkalinity concentration and a small decrease in pH, both functioning as supporting parameters, whose usage may reduce false positive alarms. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Volume estimation of brain abnormalities in MRI data

    NASA Astrophysics Data System (ADS)

    Suprijadi, Pratama, S. H.; Haryanto, F.

    2014-02-01

    The abnormality of brain tissue always becomes a crucial issue in medical field. This medical condition can be recognized through segmentation of certain region from medical images obtained from MRI dataset. Image processing is one of computational methods which very helpful to analyze the MRI data. In this study, combination of segmentation and rendering image were used to isolate tumor and stroke. Two methods of thresholding were employed to segment the abnormality occurrence, followed by filtering to reduce non-abnormality area. Each MRI image is labeled and then used for volume estimations of tumor and stroke-attacked area. The algorithms are shown to be successful in isolating tumor and stroke in MRI images, based on thresholding parameter and stated detection accuracy.

  7. A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram.

    PubMed

    Chu, Catherine J; Chan, Arthur; Song, Dan; Staley, Kevin J; Stufflebeam, Steven M; Kramer, Mark A

    2017-02-01

    High frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. The new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. We evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. The proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. Accurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram

    PubMed Central

    Chu, Catherine. J.; Chan, Arthur; Song, Dan; Staley, Kevin J.; Stufflebeam, Steven M.; Kramer, Mark A.

    2017-01-01

    Summary Background High frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. New Method The new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. Results We evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. Comparison with Existing Method The proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. Conclusions Accurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable. PMID:27988323

  9. 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.

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

    PubMed

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

    2015-08-01

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

  11. Women's experiences receiving abnormal prenatal chromosomal microarray testing results.

    PubMed

    Bernhardt, Barbara A; Soucier, Danielle; Hanson, Karen; Savage, Melissa S; Jackson, Laird; Wapner, Ronald J

    2013-02-01

    Genomic microarrays can detect copy-number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy-number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Participants were a subset of women participating in a multicenter prospective study "Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis." Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. As prenatal microarray testing is increasingly used, uncertain findings will be common, resulting in greater need for careful pre- and posttest counseling, and more education of and resources for providers so they can adequately support the women who are undergoing testing.

  12. Prescription-event monitoring: developments in signal detection.

    PubMed

    Ferreira, Germano

    2007-01-01

    Prescription-event monitoring (PEM) is a non-interventional intensive method for post-marketing drug safety monitoring of newly licensed medicines. PEM studies are cohort studies where exposure is obtained from a centralised service and outcomes from simple questionnaires completed by general practitioners. Follow-up forms are sent for selected events. Because PEM captures all events and not only the suspected adverse drug reactions, PEM cohorts potentially differ in respect to the distribution of number of events per person depending on the nature of the drug under study. This variance can be related either with the condition for which the drug is prescribed (e.g. a condition causing high morbidity will have, in average, a higher number of events per person compared with a condition with lower morbidity) or with the drug effect itself. This paper describes an exploratory investigation of the distortion caused by product-related variations of the number of events to the interpretation of the proportional reporting ratio (PRR) values ("the higher the PRR, the greater the strength of the signal") computed using drug-cohort data. We studied this effect by assessing the agreement between the PRR based on events (event of interest vs all other events) and PRR based on cases (cases with the event of interest vs cases with any other events). PRR were calculated for all combinations reported to ten selected drugs against a comparator of 81 other drugs. Three of the ten drugs had a cohort with an apparent higher proportion of patients with lower number of events. The PRRs based on events were systematically higher than the PRR based on cases for the combinations reported to these three drugs. Additionally, when applying the threshold criteria for signal screening (n > or =3, PRR > or =1.5 and Chi-squared > or =4), the binary agreement was generally high but apparently lower for these three drugs. In conclusion, the distribution of events per patient in drug cohorts shall be

  13. Non Conventional Seismic Events Along the Himalayan Arc Detected in the Hi-Climb Dataset

    NASA Astrophysics Data System (ADS)

    Vergne, J.; Nàbĕlek, J. L.; Rivera, L.; Bollinger, L.; Burtin, A.

    2008-12-01

    From September 2002 to August 2005, more than 200 broadband seismic stations were operated across the Himalayan arc and the southern Tibetan plateau in the framework of the Hi-Climb project. Here, we take advantage of the high density of stations along the main profile to look for coherent seismic wave arrivals that can not be attributed to ordinary tectonic events. An automatic detection algorithm is applied to the continuous data streams filtered between 1 and 10 Hz, followed by a visual inspection of all detections. We discovered about one hundred coherent signals that cannot be attributed to local, regional or teleseismic earthquakes and which are characterized by emergent arrivals and long durations ranging from one minute to several hours. Most of these non conventional seismic events have a low signal to noise ratio and are thus only observed above 1 Hz in the frequency band where the seismic noise is the lowest. However, a small subset of them are strong enough to be observed in a larger frequency band and show an enhancement of long periods compared to standard earthquakes. Based on the analysis of the relative amplitude measured at each station or, when possible, on the correlation of the low frequency part of the signals, most of these events appear to be located along the High Himalayan range. But, because of their emergent character and the main orientation of the seismic profile, their longitude and depth remain poorly constrained. The origin of these non conventional seismic events is still unsealed but their seismic signature shares several characteristics with non volcanic tremors, glacial earthquakes and/or debris avalanches. All these phenomena may occur along the Himalayan range but were not seismically detected before. Here we discuss the pros and cons for each of these postulated candidates based on the analysis of the recorded waveforms and slip models.

  14. Benign chronic neutropenia with abnormalities involving 16q22, affecting mother and daughter.

    PubMed

    Glasser, Lewis; Meloni-Ehrig, Aurelia; Joseph, Plakyil; Mendiola, Jennifer

    2006-04-01

    We report a case of familial, chronic, benign neutropenia in a 17-year-old female showing (1) the spontaneous expression of a heritable rare fragile site at 16q22 and (2) a deletion at the same region. The del(16)(q22), which most likely originated from the fragile site, was the main clonal abnormality detected in the patient's bone marrow cells, whereas a few cells with either del(16)(q22) or fra(16)(q22) were seen in the patient's peripheral blood. Interestingly, the del(16q) was also detected in the patient's uncultured cells, as demonstrated by FISH, excluding an in vitro origin of the del(16q) during culture. The bone marrow was hypocellular with decreased neutrophils and their precursors. Absolute neutrophil counts ranged from (0.62 to 1.24) x 10(9)/L with a median value of 1.02 x 10(9)/L. The patient had a more severe neutropenia than her mother, which correlated with the presence of more cells with del(16q) in the marrow. The patient's mother, who was also diagnosed with neutropenia, revealed only a few cells with the rare fra(16)(q22) in her peripheral blood cells, whereas her bone marrow showed cells with both fra(16)(q22) and del(16)(q22), although the del(16q) was present in only 2/20 cells. Some possible candidate genes contributing to the pathogenesis of the neutropenia are discussed. Chromosome abnormalities involving the 16q22 breakpoint have been observed in myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). In this patient, the del(16)(q22) risk factor is unknown for subsequent development of MDS or AML. Another point to consider is the need to determine the origin of a chromosome abnormality, particularly when the clinical picture does not fit the chromosome findings. Although, the observation of a constitutional structural abnormality in a mosaic form is an extremely rare event, it is somewhat different in the case of a fragile site expression, which can, as in this case, be present in some cells and not in others. Copyright 2006

  15. Comparison of automated versus manual neutrophil counts for the detection of cellular abnormalities in dogs receiving chemotherapy: 50 cases (May to June 2008).

    PubMed

    Cora, Michelle C; Neel, Jennifer A; Grindem, Carol B; Kissling, Grace E; Hess, Paul R

    2013-06-01

    To determine the frequency of clinically relevant abnormalities missed by failure to perform a blood smear evaluation in a specific subset of dogs receiving chemotherapy and to compare automated and manual neutrophil counts in the same population. Retrospective case series. 50 dogs receiving chemotherapy with a total nucleated cell count > 4,000 nucleated cells/μL. 50 blood smears were evaluated for abnormalities that have strong potential to change the medical plan for a patient: presence of blast cells, band neutrophils, nucleated RBCs, toxic change, hemoparasites, schistocytes, and spherocytes. Automated and manual neutrophil counts were compared. Blood smears from 10 (20%) patients had ≥ 1 abnormalities. Blast cells were identified on 4 (8%) blood smears, increased nucleated RBCs were identified on 5 (10%), and very mild toxic change was identified on 2 (4%). Correlation coefficient of the neutrophil counts was 0.96. Analysis revealed a slight bias between the automated and manual neutrophil counts (mean ± SD difference, -0.43 × 10(3)/μL ± 1.10 × 10(3)/μL). In this series of patients, neutrophil count correlation was very good. Clinically relevant abnormalities were found on 20% of the blood smears. An automated CBC appears to be accurate for neutrophil counts, but a microscopic examination of the corresponding blood smear is still recommended; further studies are needed to determine whether the detection or frequency of these abnormalities would differ dependent on chemotherapy protocol, neoplastic disease, and decision thresholds used by the oncologist in the ordering of a CBC without a blood smear evaluation.

  16. Mining Recent Temporal Patterns for Event Detection in Multivariate Time Series Data

    PubMed Central

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

    2015-01-01

    Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes. PMID:25937993

  17. A phase II clinical study to assess the feasibility of self and partner anal examinations to detect anal canal abnormalities including anal cancer.

    PubMed

    Nyitray, Alan G; Hicks, Joseph T; Hwang, Lu-Yu; Baraniuk, Sarah; White, Margaret; Millas, Stefanos; Onwuka, Nkechi; Zhang, Xiaotao; Brown, Eric L; Ross, Michael W; Chiao, Elizabeth Y

    2018-03-01

    Anal cancer is a common cancer among men who have sex with men (MSM); however, there is no standard screening protocol for anal cancer. We conducted a phase II clinical trial to assess the feasibility of teaching MSM to recognise palpable masses in the anal canal which is a common sign of anal cancer in men. A clinician skilled in performing digital anorectal examinations (DARE) used a pelvic manikin to train 200 MSM, aged 27-78 years, how to do a self-anal examination (SAE) for singles or a partner anal examination (PAE) for couples. The clinician then performed a DARE without immediately disclosing results, after which the man or couple performed an SAE or PAE, respectively. Percentage agreement with the clinician DARE in addition to sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the SAE, PAE and overall. Men had a median age of 52 years, 42.5% were African American and 60.5% were HIV positive. DARE detected abnormalities in 12 men while the men's SAE/PAEs detected 9 of these. A total of 93.0% of men classified the health of their anal canal correctly (95% CI 89.5 to 96.5). Overall percentage agreement, sensitivity and specificity were 93.0%, 75.0% and 94.2%, respectively, while PPV and NPV were 45.0% and 98.3%, respectively. The six men who detected the abnormality had nodules/masses ≥3 mm in size. More than half of men (60.5%) reported never checking their anus for an abnormality; however, after performing an SAE/PAE, 93.0% said they would repeat it in the future. These results suggest that tumours of ≥3 mm may be detectable by self or partner palpation among MSM and encourage further investigation given literature suggesting a high cure rate for anal cancer tumours ≤10 mm. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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

    PubMed

    Muller-Gass, Alexandra; Campbell, Kenneth

    2014-08-01

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

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

    PubMed

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

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

  20. Termination of pregnancy for fetal abnormality: a meta-ethnography of women's experiences.

    PubMed

    Lafarge, Caroline; Mitchell, Kathryn; Fox, Pauline

    2014-11-01

    Due to technological advances in antenatal diagnosis of fetal abnormalities, more women face the prospect of terminating pregnancies on these grounds. Much existing research focuses on women's psychological adaptation to this event. However, there is a lack of holistic understanding of women's experiences. This article reports a systematic review of qualitative studies into women's experiences of pregnancy termination for fetal abnormality. Eight databases were searched up to April 2014 for peer-reviewed studies, written in English, that reported primary or secondary data, used identifiable and interpretative qualitative methods, and offered a valuable contribution to the synthesis. Altogether, 4,281 records were screened; 14 met the inclusion criteria. The data were synthesised using meta-ethnography. Four themes were identified: a shattered world, losing and regaining control, the role of health professionals and the power of cultures. Pregnancy termination for fetal abnormality can be considered as a traumatic event that women experience as individuals, in their contact with the health professional community, and in the context of their politico-socio-legal environment. The range of emotions and experiences that pregnancy termination for fetal abnormality generates goes beyond the abortion paradigm and encompasses a bereavement model. Coordinated care pathways are needed that enable women to make their own decisions and receive supportive care. Copyright © 2014 Reproductive Health Matters. Published by Elsevier Ltd. All rights reserved.

  1. High Frequency of Neuroimaging Abnormalities Among Pediatric Patients With Sepsis Who Undergo Neuroimaging.

    PubMed

    Sandquist, Mary K; Clee, Mark S; Patel, Smruti K; Howard, Kelli A; Yunger, Toni; Nagaraj, Usha D; Jones, Blaise V; Fei, Lin; Vadivelu, Sudhakar; Wong, Hector R

    2017-07-01

    This study was intended to describe and correlate the neuroimaging findings in pediatric patients after sepsis. Retrospective chart review. Single tertiary care PICU. Patients admitted to Cincinnati Children's Hospital Medical Center with a discharge diagnosis of sepsis or septic shock between 2004 and 2013 were crossmatched with patients who underwent neuroimaging during the same time period. All neuroimaging studies that occurred during or subsequent to a septic event were reviewed, and all new imaging findings were recorded and classified. As many patients experienced multiple septic events and/or had multiple neuroimaging studies after sepsis, our statistical analysis utilized the most recent or "final" imaging study available for each patient so that only brain imaging findings that persisted were included. A total of 389 children with sepsis and 1,705 concurrent or subsequent neuroimaging studies were included in the study. Median age at first septic event was 3.4 years (interquartile range, 0.7-11.5). Median time from first sepsis event to final neuroimaging was 157 days (interquartile range, 10-1,054). The most common indications for final imaging were follow-up (21%), altered mental status (18%), and fever/concern for infection (15%). Sixty-three percentage (n = 243) of final imaging studies demonstrated abnormal findings, the most common of which were volume loss (39%) and MRI signal and/or CT attenuation abnormalities (21%). On multivariable logistic regression, highest Pediatric Risk of Mortality score and presence of oncologic diagnosis/organ transplantation were independently associated with any abnormal final neuroimaging study findings (odds ratio, 1.032; p = 0.048 and odds ratio, 1.632; p = 0.041), although early timing of neuroimaging demonstrated a negative association (odds ratio, 0.606; p = 0.039). The most common abnormal finding of volume loss was independently associated with highest Pediatric Risk of Mortality score (odds ratio, 1.037; p

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

    PubMed

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

    2011-09-21

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

  3. Saliency Detection as a Reactive Process: Unexpected Sensory Events Evoke Corticomuscular Coupling

    PubMed Central

    Kilintari, Marina; Srinivasan, Mandayam; Haggard, Patrick

    2018-01-01

    Survival in a fast-changing environment requires animals not only to detect unexpected sensory events, but also to react. In humans, these salient sensory events generate large electrocortical responses, which have been traditionally interpreted within the sensory domain. Here we describe a basic physiological mechanism coupling saliency-related cortical responses with motor output. In four experiments conducted on 70 healthy participants, we show that salient substartle sensory stimuli modulate isometric force exertion by human participants, and that this modulation is tightly coupled with electrocortical activity elicited by the same stimuli. We obtained four main results. First, the force modulation follows a complex triphasic pattern consisting of alternating decreases and increases of force, time-locked to stimulus onset. Second, this modulation occurs regardless of the sensory modality of the eliciting stimulus. Third, the magnitude of the force modulation is predicted by the amplitude of the electrocortical activity elicited by the same stimuli. Fourth, both neural and motor effects are not reflexive but depend on contextual factors. Together, these results indicate that sudden environmental stimuli have an immediate effect on motor processing, through a tight corticomuscular coupling. These observations suggest that saliency detection is not merely perceptive but reactive, preparing the animal for subsequent appropriate actions. SIGNIFICANCE STATEMENT Salient events occurring in the environment, regardless of their modalities, elicit large electrical brain responses, dominated by a widespread “vertex” negative-positive potential. This response is the largest synchronization of neural activity that can be recorded from a healthy human being. Current interpretations assume that this vertex potential reflects sensory processes. Contrary to this general assumption, we show that the vertex potential is strongly coupled with a modulation of muscular activity

  4. [Congenital abnormalities of the aorta in children and adolescents].

    PubMed

    Eichhorn, J G; Ley, S

    2007-11-01

    Aortic abnormalities are common cardiovascular malformations accounting for 15-20% of all congenital heart disease. Ultrafast CT and MR imaging are noninvasive, accurate and robust techniques that can be used in the diagnosis of aortic malformations. While their sensitivity in detecting vascular abnormalities seems to be as good as that of conventional catheter angiocardiography, at over 90%, they are superior in the diagnosis of potentially life-threatening complications, such as tracheal, bronchial, or esophageal compression. It has been shown that more than 80% of small children with aortic abnormalities benefit directly from the use of noninvasive imaging: either cardiac catheterization is no longer necessary or radiation doses and periods of general anesthesia for interventional catheterization procedures can be much reduced. The most important congenital abnormalities of the aorta in children and adolescents are presented with reference to examples, and the value of CT and MR angiography is documented.

  5. Prevalence of abnormalities in knees detected by MRI in adults without knee osteoarthritis: population based observational study (Framingham Osteoarthritis Study).

    PubMed

    Guermazi, Ali; Niu, Jingbo; Hayashi, Daichi; Roemer, Frank W; Englund, Martin; Neogi, Tuhina; Aliabadi, Piran; McLennan, Christine E; Felson, David T

    2012-08-29

    To examine use of magnetic resonance imaging (MRI) of knees with no radiographic evidence of osteoarthritis to determine the prevalence of structural lesions associated with osteoarthritis and their relation to age, sex, and obesity. Population based observational study. Community cohort in Framingham, MA, United States (Framingham osteoarthritis study). 710 people aged >50 who had no radiographic evidence of knee osteoarthritis (Kellgren-Lawrence grade 0) and who underwent MRI of the knee. Prevalence of MRI findings that are suggestive of knee osteoarthritis (osteophytes, cartilage damage, bone marrow lesions, subchondral cysts, meniscal lesions, synovitis, attrition, and ligamentous lesions) in all participants and after stratification by age, sex, body mass index (BMI), and the presence or absence of knee pain. Pain was assessed by three different questions and also by WOMAC questionnaire. Of the 710 participants, 393 (55%) were women, 660 (93%) were white, and 206 (29%) had knee pain in the past month. The mean age was 62.3 years and mean BMI was 27.9. Prevalence of "any abnormality" was 89% (631/710) overall. Osteophytes were the most common abnormality among all participants (74%, 524/710), followed by cartilage damage (69%, 492/710) and bone marrow lesions (52%, 371/710). The higher the age, the higher the prevalence of all types of abnormalities detectable by MRI. There were no significant differences in the prevalence of any of the features between BMI groups. The prevalence of at least one type of pathology ("any abnormality") was high in both painful (90-97%, depending on pain definition) and painless (86-88%) knees. MRI shows lesions in the tibiofemoral joint in most middle aged and elderly people in whom knee radiographs do not show any features of osteoarthritis, regardless of pain.

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

    PubMed

    Khandelwal, Siddhartha; Wickstrom, Nicholas

    2016-12-01

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

  7. Temporal Structure and Complexity Affect Audio-Visual Correspondence Detection

    PubMed Central

    Denison, Rachel N.; Driver, Jon; Ruff, Christian C.

    2013-01-01

    Synchrony between events in different senses has long been considered the critical temporal cue for multisensory integration. Here, using rapid streams of auditory and visual events, we demonstrate how humans can use temporal structure (rather than mere temporal coincidence) to detect multisensory relatedness. We find psychophysically that participants can detect matching auditory and visual streams via shared temporal structure for crossmodal lags of up to 200 ms. Performance on this task reproduced features of past findings based on explicit timing judgments but did not show any special advantage for perfectly synchronous streams. Importantly, the complexity of temporal patterns influences sensitivity to correspondence. Stochastic, irregular streams – with richer temporal pattern information – led to higher audio-visual matching sensitivity than predictable, rhythmic streams. Our results reveal that temporal structure and its complexity are key determinants for human detection of audio-visual correspondence. The distinctive emphasis of our new paradigms on temporal patterning could be useful for studying special populations with suspected abnormalities in audio-visual temporal perception and multisensory integration. PMID:23346067

  8. Abnormalities of P300 cortical current density in unmedicated depressed patients revealed by LORETA analysis of event-related potentials.

    PubMed

    Kawasaki, Toshihiko; Tanaka, Shin; Wang, Jijun; Hokama, Hiroto; Hiramatsu, Kenichi

    2004-02-01

    The purpose of the present study was to investigate the neural substrates underlying event-related potential (ERP) abnormalities, with respect to the generators of the ERP components in depressed patients. Using an oddball paradigm, ERP from auditory stimuli were recorded from 22 unmedicated patients with current depressive episodes and compared with those from 22 age- and gender-matched normal controls. Cortical current densities of the N100 and P300 components were analyzed using low-resolution electromagnetic tomography (LORETA). Group differences in cortical current density were mapped on a 3-D cortex model. The results revealed that N100 cortical current densities did not differ between the two groups, while P300 cortical current densities were significantly lower in depressed patients over the bilateral temporal lobes, the left frontal region, and the right temporal-parietal area. Furthermore, the cortical area in which the group difference in P300 current density had been identified was remarkably larger over the right than the left hemisphere, thus supporting the hypothesis of right hemisphere dysfunction in depression.

  9. Chromosomal abnormalities are associated with aging and cancer

    Cancer.gov

    Two new studies have found that large structural abnormalities in chromosomes, some of which have been associated with increased risk of cancer, can be detected in a small fraction of people without a prior history of cancer. The studies found that these

  10. An abattoir survey of equine dental abnormalities in Queensland, Australia.

    PubMed

    Chinkangsadarn, T; Wilson, G J; Greer, R M; Pollitt, C C; Bird, P S

    2015-06-01

    A cadaver study to estimate the prevalence of dental disorders in horses presented at an abattoir in Queensland, Australia. Cadaver heads at a Queensland abattoir were examined for the presence of dental abnormalities and categorised into age groups. The prevalence of abnormalities was analysed by binomial observation of observed proportion, Pearson's Chi-square test or Fisher's exact correlation test. Strength of association was evaluated using Cramer's V test. Heads from horses (n=400) estimated to be between 1 and 30 years of age were placed into four age groups. The most common abnormalities were sharp enamel points (55.3%) and hooks (43%). The highest frequency of dental diseases and abnormalities were in horses 11-15 years old (97.5%). Common abnormalities were found in all groups and the prevalence increased with age. This study suggests that all horses should have regular complete dental examinations to detect and treat dental disorders in order to limit more severe dental pathologies later in life. © 2015 Australian Veterinary Association.

  11. Respiratory and psychiatric abnormalities in chronic symptomatic hyperventilation.

    PubMed Central

    Bass, C; Gardner, W N

    1985-01-01

    Many physicians believe that the hyperventilation syndrome is invariably associated with anxiety or undiagnosed organic disease such as asthma and pulmonary embolus, or both. Twenty one patients referred by specialist physicians with unexplained somatic symptoms and unequivocal chronic hypocapnia (resting end tidal Pco2 less than or equal to 4 kPa (30 mm Hg) on repeated occasions during prolonged measurement) were investigated. All but one complained of inability to take a satisfying breath. Standard lung function test results and chest radiographs were normal in all patients, but histamine challenge showed bronchial hyper-reactivity in two of 20 patients tested, and skin tests to common allergens were positive in three of 18. Ventilation-perfusion scanning was abnormal in a further three of 15 patients studied, with unmatched perfusion defects in two and isolated ventilation defects in one. None of the 21 had thyrotoxicosis, severe coronary heart disease, or other relevant cardiovascular abnormalities. Ten of the 21 patients were neurotic and suffered from chronic psychiatric disturbance characterised by anxiety, panic, and phobic symptoms. The remainder had no detectable psychiatric disorders but reported proportionately more somatic than anxiety symptoms. Severe hyperventilation can occur in the absence of formal psychiatric or detectable respiratory or other organic abnormalities. Asthma and pulmonary embolus must be specifically excluded. PMID:3922504

  12. Subtle abnormalities of gait detected early in vitamin B6 deficiency in aged and weanling rats with hind leg gait analysis.

    PubMed

    Schaeffer, M C; Cochary, E F; Sadowski, J A

    1990-04-01

    Motor abnormalities have been observed in every species made vitamin B6 deficient, and have been detected and quantified early in vitamin B6 deficiency in young adult female Long-Evans rats with hind leg gait analysis. Our objective was to determine if hind leg gait analysis could be used to detect vitamin B6 deficiency in weanling (3 weeks) and aged (23 months) Fischer 344 male rats. Rats (n = 10 per group) were fed: the control diet ad libitum (AL-CON); the control diet devoid of added pyridoxine hydrochloride (DEF); or the control diet pair-fed to DEF (PF-CON). At 10 weeks, plasma pyridoxal phosphate concentration confirmed deficiency in both age groups. Gait abnormalities were detected in the absence of gross motor disturbances in both aged and weanling DEF rats at 2-3 weeks. Width of step was significantly reduced (16%, p less than 0.003) in DEF aged rats compared to AL- and PF-CON. This pattern of response was similar to that reported previously in young adult rats. In weanling rats, pair feeding alone reduced mean width of step (+/- SEM) by 25% compared to ad libitum feeding (2.7 +/- 0.1 vs 3.6 +/- 0.1 cm for PF- vs AL-CON, respectively, p less than 0.05). In DEF weanling rats, width (3.0 +/- 0.1 cm) was increased compared to PF-CON (11%, p less than 0.05) but decreased compared to AL-CON (16%, p less than 0.05). Width of step was significantly altered early in B6 deficiency in rats of different ages and strains and in both sexes.(ABSTRACT TRUNCATED AT 250 WORDS)

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

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

    Botvinick, E.H.; Frais, M.A.; Shosa, D.W.

    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 andmore » 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.« less

  14. 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.

  15. Abnormal Canine Bone Development Associated with Hypergravity Exposure

    NASA Technical Reports Server (NTRS)

    Morgan, J. P.; Fisher, G. L.; McNeill, K. L.; Oyama, J.

    1979-01-01

    Chronic centrifugation of 85- to 92-day-old Beagles at 2.0 x g and 2.6 x g for 26 weeks during the time of active skeletal growth caused skeletal abnormalities in the radius and the ulna of ten of 11 dogs. The pattern of change mimicked that found in naturally occurring and experimentally induced premature distal ulnar physeal closure or delayed growth at this physis. Minimal changes in bone density were detected by sensitive photon absorptiometric techniques. Skeletal abnormalities also were found in five of the six cage-control dogs, although the run-control dogs were radiographically normal.

  16. Karyotype versus microarray testing for genetic abnormalities after stillbirth.

    PubMed

    Reddy, Uma M; Page, Grier P; Saade, George R; Silver, Robert M; Thorsten, Vanessa R; Parker, Corette B; Pinar, Halit; Willinger, Marian; Stoll, Barbara J; Heim-Hall, Josefine; Varner, Michael W; Goldenberg, Robert L; Bukowski, Radek; Wapner, Ronald J; Drews-Botsch, Carolyn D; O'Brien, Barbara M; Dudley, Donald J; Levy, Brynn

    2012-12-06

    Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).

  17. Performing an Event Study: An Exercise for Finance Students

    ERIC Educational Resources Information Center

    Reese, William A., Jr.; Robins, Russell P.

    2017-01-01

    This exercise helps instructors teach students how to perform a simple event study. The study tests to see if stocks earn abnormal returns when added to the S&P 500. Students select a random sample of stocks that were added to the index between January 2000 and July 2015. The accompanying spreadsheet calculates cumulative abnormal returns and…

  18. Hospital staff should use more than one method to detect adverse events and potential adverse events: incident reporting, pharmacist surveillance and local real‐time record review may all have a place

    PubMed Central

    Olsen, Sisse; Neale, Graham; Schwab, Kat; Psaila, Beth; Patel, Tejal; Chapman, E Jane; Vincent, Charles

    2007-01-01

    Background Over the past five years, in most hospitals in England and Wales, incident reporting has become well established but it remains unclear how well reports match clinical adverse events. International epidemiological studies of adverse events are based on retrospective, multi‐hospital case record review. In this paper the authors describe the use of incident reporting, pharmacist surveillance and local real‐time record review for the recognition of clinical risks associated with hospital inpatient care. Methodology Data on adverse events were collected prospectively on 288 patients discharged from adult acute medical and surgical units in an NHS district general hospital using incident reports, active surveillance of prescription charts by pharmacists and record review at time of discharge. Results Record review detected 26 adverse events (AEs) and 40 potential adverse events (PAEs) occurring during the index admission. In contrast, in the same patient group, incident reporting detected 11 PAEs and no AEs. Pharmacy surveillance found 10 medication errors all of which were PAEs. There was little overlap in the nature of events detected by the three methods. Conclusion The findings suggest that incident reporting does not provide an adequate assessment of clinical adverse events and that this method needs to be supplemented with other more systematic forms of data collection. Structured record review, carried out by clinicians, provides an important component of an integrated approach to identifying risk in the context of developing a safety and quality improvement programme. PMID:17301203

  19. 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.

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

    PubMed

    O'Shea, Jesse

    2017-05-01

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

  1. Detecting continuity violations in infancy: a new account and new evidence from covering and tube events.

    PubMed

    Wang, Su-hua; Baillargeon, Renée; Paterson, Sarah

    2005-03-01

    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. J., & Baillargeon, R. (2001). Knowledge about containment events in very young infants. Cognition 78, 207-245; Luo, Y., & Baillargeon, R. (in press). When the ordinary seems unexpected: Evidence for rule-based reasoning in young infants. Cognition; Wilcox, T., Nadel, L., & Rosser, R. (1996). Location memory in healthy preterm and full-term infants. Infant Behavior & Development 19, 309-323, others are not detected until much later e.g. Baillargeon, R., & DeVos, J. (1991). Object permanence in young infants: Further evidence. Child Development 62, 1227-1246; Hespos, S. J., & Baillargeon, R. (2001). Infants' knowledge about occlusion and containment events: A surprising discrepancy. Psychological Science 12, 140-147; Luo, Y., & Baillargeon, R. (2004). Infants' reasoning about events involving transparent occluders and containers. Manuscript in preparation; Wilcox, T. (1999). Object individuation: Infants' use of shape, size, pattern, and color. Cognition 72, 125-166. The present research focused on events involving covers or tubes, and brought to light additional examples of early and late successes in infants' ability to detect continuity violations. In Experiment 1, 2.5- to 3-month-old infants were surprised (1) when a cover was lowered over an object, slid to the right, and lifted to reveal no object; and (2) when a cover was lowered over an object, slid behind the left half of a screen, lifted above the screen, moved to the right, lowered behind the right half of the screen, slid past the screen, and finally lifted to reveal the object. In Experiments 2 and 3, 9- and 11-month-old infants were not surprised when a short

  2. 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.

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

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

    Facciolo, Rosa Maria, E-mail: rm.facciolo@unical.i; Crudo, Michele; Giusi, Giuseppina

    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 treatmentmore » 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.« less

  4. Glaucoma progression detection: agreement, sensitivity, and specificity of expert visual field evaluation, event analysis, and trend analysis.

    PubMed

    Antón, Alfonso; Pazos, Marta; Martín, Belén; Navero, José Manuel; Ayala, Miriam Eleonora; Castany, Marta; Martínez, Patricia; Bardavío, Javier

    2013-01-01

    To assess sensitivity, specificity, and agreement among automated event analysis, automated trend analysis, and expert evaluation to detect glaucoma progression. This was a prospective study that included 37 eyes with a follow-up of 36 months. All had glaucomatous disks and fields and performed reliable visual fields every 6 months. Each series of fields was assessed with 3 different methods: subjective assessment by 2 independent teams of glaucoma experts, glaucoma/guided progression analysis (GPA) event analysis, and GPA (visual field index-based) trend analysis. Kappa agreement coefficient between methods and sensitivity and specificity for each method using expert opinion as gold standard were calculated. The incidence of glaucoma progression was 16% to 18% in 3 years but only 3 cases showed progression with all 3 methods. Kappa agreement coefficient was high (k=0.82) between subjective expert assessment and GPA event analysis, and only moderate between these two and GPA trend analysis (k=0.57). Sensitivity and specificity for GPA event and GPA trend analysis were 71% and 96%, and 57% and 93%, respectively. The 3 methods detected similar numbers of progressing cases. The GPA event analysis and expert subjective assessment showed high agreement between them and moderate agreement with GPA trend analysis. In a period of 3 years, both methods of GPA analysis offered high specificity, event analysis showed 83% sensitivity, and trend analysis had a 66% sensitivity.

  5. Surface Management System Departure Event Data Analysis

    NASA Technical Reports Server (NTRS)

    Monroe, Gilena A.

    2010-01-01

    This paper presents a data analysis of the Surface Management System (SMS) performance of departure events, including push-back and runway departure events.The paper focuses on the detection performance, or the ability to detect departure events, as well as the prediction performance of SMS. The results detail a modest overall detection performance of push-back events and a significantly high overall detection performance of runway departure events. The overall detection performance of SMS for push-back events is approximately 55%.The overall detection performance of SMS for runway departure events nears 100%. This paper also presents the overall SMS prediction performance for runway departure events as well as the timeliness of the Aircraft Situation Display for Industry data source for SMS predictions.

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

    PubMed

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

    2013-11-01

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

  7. Spent fuel behavior under abnormal thermal transients during dry storage

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

    Stahl, D.; Landow, M.P.; Burian, R.J.

    1986-01-01

    This study was performed to determine the effects of abnormally high temperatures on spent fuel behavior. Prior to testing, calculations using the CIRFI3 code were used to determine the steady-state fuel and cask component temperatures. The TRUMP code was used to determine transient heating rates under postulated abnormal events during which convection cooling of the cask surfaces was obstructed by a debris bed covering the cask. The peak rate of temperature rise during the first 6 h was calculated to be about 15/sup 0/C/h, followed by a rate of about 1/sup 0/C/h. A Turkey Point spent fuel rod segment wasmore » heated to approx. 800/sup 0/C. The segment deformed uniformly with an average strain of 17% at failure and a local strain of 60%. Pretest characterization of the spent fuel consisted of visual examination, profilometry, eddy-current examination, gamma scanning, fission gas collection, void volume measurement, fission gas analysis, hydrogen analysis of the cladding, burnup analysis, cladding metallography, and fuel ceramography. Post-test characterization showed that the failure was a pinhole cladding breach. The results of the tests showed that spent fuel temperatures in excess of 700/sup 0/C are required to produce a cladding breach in fuel rods pressurized to 500 psing (3.45 MPa) under postulated abnormal thermal transient cask conditions. The pinhole cladding breach that developed would be too small to compromise the confinement of spent fuel particles during an abnormal event or after normal cooling conditions are restored. This behavior is similar to that found in other slow ramp tests with irradiated and nonirradiated rod sections and nonirradiated whole rods under conditions that bracketed postulated abnormal heating rates. This similarity is attributed to annealing of the irradiation-strengthened Zircaloy cladding during heating. In both cases, the failure was a benign, ductile pinhole rupture.« less

  8. Chromosome and molecular abnormalities in myelodysplastic syndromes.

    PubMed

    Fenaux, Pierre

    2001-06-01

    Cytogenetic abnormalities are seen in approximately 50% of cases of myelodysplastic syndrome (MDS) and 80% of cases of secondary MDS (following chemotherapy or radiotherapy). These abnormalities generally consist of partial or complete chromosome deletion or addition (del5q, -7, +8, -Y, del20q), whereas balanced or unbalanced translocations are rarely found in MDS. Fluorescence hybridization techniques (fluorescence in situ hybridization [FISH], multiplex FISH, and spectral karyotyping) are useful in detecting chromosomal anomalies in cases in which few mitoses are obtained or rearrangements are complex. Ras mutations are the molecular abnormalities most frequently found in MDS, followed by p15 gene hypermethylation, FLT3 duplications, and p53 mutations, but none of these abnormalities are specific for MDS. The rare cases of balanced translocations in MDS have allowed the identification of genes whose rearrangements appear to play a role in the pathogenesis of some cases of MDS. These genes include MDS1-EVI1 in t(3;3) or t(3;21) translocations, TEL in t(5;12), HIP1 in t(5;7), MLF1 in t(3;5), and MEL1 in t(1;3). Genes more frequently implicated in the pathogenesis of MDS cases, such as those involving del5q, remain unknown, although some candidate genes are currently being studied. Cytogenetic and known molecular abnormalities generally carry a poor prognosis in MDS and can be incorporated into prognostic scoring systems such as the International Prognostic Scoring System.

  9. Bacterial flora in abnormalities of the female genital tract

    PubMed Central

    Gordon, A. M.; Hughes, H. E.; Barr, G. T. D.

    1966-01-01

    The bacterial flora associated with certain common abnormalities of the female genital tract were studied. The abnormalities included were trichomonal infestation of the vagina, the epithelial inflammation and cellular atypia associated with protozoal infestation, and erosions of the cervix. Trichomonas vaginalis infestation and marked epithelial inflammation were associated with a very varied bacterial flora in which Mycoplasma species, streptococci, and `Haemophilus vaginalis' (Gardner and Dukes, 1955) were often prominent. No cases of vaginitis attributable to Haemophilus vaginalis were detected. An essentially normal bacterial flora accompanied erosions of the cervix. PMID:5919354

  10. Strategies for rare-event detection: an approach for automated fetal cell detection in maternal blood.

    PubMed Central

    Oosterwijk, J C; Knepflé, C F; Mesker, W E; Vrolijk, H; Sloos, W C; Pattenier, H; Ravkin, I; van Ommen, G J; Kanhai, H H; Tanke, H J

    1998-01-01

    This article explores the feasibility of the use of automated microscopy and image analysis to detect the presence of rare fetal nucleated red blood cells (NRBCs) circulating in maternal blood. The rationales for enrichment and for automated image analysis for "rare-event" detection are reviewed. We also describe the application of automated image analysis to 42 maternal blood samples, using a protocol consisting of one-step enrichment followed by immunocytochemical staining for fetal hemoglobin (HbF) and FISH for X- and Y-chromosomal sequences. Automated image analysis consisted of multimode microscopy and subsequent visual evaluation of image memories containing the selected objects. The FISH results were compared with the results of conventional karyotyping of the chorionic villi. By use of manual screening, 43% of the slides were found to be positive (>=1 NRBC), with a mean number of 11 NRBCs (range 1-40). By automated microscopy, 52% were positive, with on average 17 NRBCs (range 1-111). There was a good correlation between both manual and automated screening, but the NRBC yield from automated image analysis was found to be superior to that from manual screening (P=.0443), particularly when the NRBC count was >15. Seven (64%) of 11 XY fetuses were correctly diagnosed by FISH analysis of automatically detected cells, and all discrepancies were restricted to the lower cell-count range. We believe that automated microscopy and image analysis reduce the screening workload, are more sensitive than manual evaluation, and can be used to detect rare HbF-containing NRBCs in maternal blood. PMID:9837832

  11. Only a minority of sex chromosome abnormalities are detected by a national prenatal screening program for Down syndrome.

    PubMed

    Viuff, Mette Hansen; Stochholm, Kirstine; Uldbjerg, Niels; Nielsen, Birgitte Bruun; Gravholt, Claus Højbjerg

    2015-10-01

    How does a national prenatal screening program for Down syndrome (DS) perform in detecting sex chromosome abnormalities (SCAs)-Turner syndrome (TS), Klinefelter syndrome, 47,XXX and 47,XYY syndromes. The SCA detection rate resulting from DS screening was below 50% for all four groups of SCAs. The detection rates of SCAs are higher in countries with DS screening. TS is associated with greater nuchal translucency (NT) and lower pregnancy-associated plasma protein-A (PAPP-A). However, specific detection rates of SCAs using prenatal DS screening have not been determined. No clear trend in PAPP-A, free beta human chorionic gonadotropin (β-hCG) and NT has been found in the remaining SCAs. Several lines of inquiry suggest that it would be advantageous for individuals with SCA to be detected early in life, leading to prevention or treatment of accompanying conditions. There is limited information about pre- and perinatal status that distinguishes SCA embryogenesis from normal fetal development. A register-based case-control study from the Danish Central Cytogenetic Register (DCCR), cross-linked with the Danish Fetal Medicine Database (DFMD), was performed from 2008 to 2012. Groups of SCAs were compared with DS and then matched with non-SCA controls to assess differences between these groups in prenatal markers and birth outcomes. We included cases with prenatal and post-natal SCA karyotypes (n = 213), DS (n = 802) and 168 056 controls. We screened 275 037 individuals examined prenatally. We retrieved information regarding maternal age, NT, β-hCG and PAPP-A, as well as details regarding maternal and newborn characteristics. The DS screening procedure detected 87 per 100 000 TS (42% of expected), 19 per 100 000 Klinefelter syndrome (13% of expected), 16 per 100 000 47,XXX (16% of cases) and 5 per 100 000 47,XYY (5% of expected) SCAs, with an overall detection rate of 27%. Compared with controls, all four SCA groups showed significantly higher NT and lower PAPP-A compared

  12. 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

  13. 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.

  14. Feeling Abnormal: Simulation of Deviancy in Abnormal and Exceptionality Courses.

    ERIC Educational Resources Information Center

    Fernald, Charles D.

    1980-01-01

    Describes activity in which student in abnormal psychology and psychology of exceptional children classes personally experience being judged abnormal. The experience allows the students to remember relevant research, become sensitized to the feelings of individuals classified as deviant, and use caution in classifying individuals as abnormal.…

  15. 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

  16. Neurochemical abnormalities in premanifest and early spinocerebellar ataxias.

    PubMed

    Joers, James M; Deelchand, Dinesh K; Lyu, Tianmeng; Emir, Uzay E; Hutter, Diane; Gomez, Christopher M; Bushara, Khalaf O; Eberly, Lynn E; Öz, Gülin

    2018-04-01

    To investigate whether early neurochemical abnormalities are detectable by high-field magnetic resonance spectroscopy (MRS) in individuals with spinocerebellar ataxias (SCAs) 1, 2, 3, and 6, including patients without manifestation of ataxia. A cohort of 100 subjects (N = 18-21 in each SCA group, including premanifest mutation carriers; mean score on the Scale for the Assessment and Rating of Ataxia [SARA] <10 for all genotypes, and 22 matched controls) was scanned at 7 Tesla to obtain neurochemical profiles of the cerebellum and brainstem. A novel multivariate approach (distance-weighted discrimination) was used to combine regional profiles into an "MRS score." MRS scores robustly distinguished individuals with SCA from controls, with misclassification rates of 0% (SCA2), 2% (SCA3), 5% (SCA1), and 17% (SCA6). Premanifest mutation carriers with estimated disease onset within 10 years had MRS scores in the range of early-manifest SCA subjects. Levels of neuronal and glial markers significantly correlated with SARA and an Activities of Daily Living score in subjects with SCA. Regional neurochemical alterations were different between SCAs at comparable disease severity, with SCA2 displaying the most extensive neurochemical abnormalities, followed by SCA1, SCA3, and SCA6. Neurochemical abnormalities are detectable in individuals before manifest disease, which may allow premanifest enrollment in future SCA trials. Correlations with ataxia and quality-of-life scores show that neurochemical levels can serve as clinically meaningful endpoints in trials. Ranking of SCA types by degree of neurochemical abnormalities indicates that the neurochemistry may reflect synaptic function or density. Ann Neurol 2018;83:816-829. © 2018 American Neurological Association.

  17. Abnormal Uterine Bleeding

    MedlinePlus

    ... abnormal uterine bleeding? Abnormal uterine bleeding is any heavy or unusual bleeding from the uterus (through your ... one symptom of abnormal uterine bleeding. Having extremely heavy bleeding during your period can also be considered ...

  18. A Case-Study Assignment to Teach Theoretical Perspectives in Abnormal Psychology.

    ERIC Educational Resources Information Center

    Perkins, David V.

    1991-01-01

    Describes an assignment that requires students to organize, prepare, and revise a case study in abnormal behavior. Explains that students employ a single theoretical perspective in preparing a report on a figure from history, literature, the arts, or current events. Discusses the value of the assignment for students. (SG)

  19. 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

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

    PubMed

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

    2015-01-05

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

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

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

    Hruschka, Daniel  J.; Branford, Simon; Smith, Eric  D.

    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

  2. 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.

  3. Orbit Determination and Maneuver Detection Using Event Representation with Thrust-Fourier-Coefficients

    NASA Astrophysics Data System (ADS)

    Lubey, D.; Ko, H.; Scheeres, D.

    The classical orbit determination (OD) method of dealing with unknown maneuvers is to restart the OD process with post-maneuver observations. However, it is also possible to continue the OD process through such unknown maneuvers by representing those unknown maneuvers with an appropriate event representation. It has been shown in previous work (Ko & Scheeres, JGCD 2014) that any maneuver performed by a satellite transitioning between two arbitrary orbital states can be represented as an equivalent maneuver connecting those two states using Thrust-Fourier-Coefficients (TFCs). Event representation using TFCs rigorously provides a unique control law that can generate the desired secular behavior for a given unknown maneuver. This paper presents applications of this representation approach to orbit prediction and maneuver detection problem across unknown maneuvers. The TFCs are appended to a sequential filter as an adjoint state to compensate unknown perturbing accelerations and the modified filter estimates the satellite state and thrust coefficients by processing OD across the time of an unknown maneuver. This modified sequential filter with TFCs is capable of fitting tracking data and maintaining an OD solution in the presence of unknown maneuvers. Also, the modified filter is found effective in detecting a sudden change in TFC values which indicates a maneuver. In order to illustrate that the event representation approach with TFCs is robust and sufficiently general to be easily adjustable, different types of measurement data are processed with the filter in a realistic LEO setting. Further, cases with mis-modeling of non-gravitational force are included in our study to verify the versatility and efficiency of our presented algorithm. Simulation results show that the modified sequential filter with TFCs can detect and estimate the orbit and thrust parameters in the presence of unknown maneuvers with or without measurement data during maneuvers. With no measurement

  4. The ability of an electrocardiogram to predict fatal and non-fatal cardiac events in asymptomatic middle-aged subjects.

    PubMed

    Terho, Henri K; Tikkanen, Jani T; Kenttä, Tuomas V; Junttila, M Juhani; Aro, Aapo L; Anttonen, Olli; Kerola, Tuomas; Rissanen, Harri A; Knekt, Paul; Reunanen, Antti; Huikuri, Heikki V

    2016-11-01

    The long-term prognostic value of a standard 12-lead electrocardiogram (ECG) for predicting cardiac events in apparently healthy middle-aged subjects is not well defined. A total of 9511 middle-aged subjects (mean age 43 ± 8.2 years, 52% males) without a known cardiac disease and with a follow-up 40 years were included in the study. Fatal and non-fatal cardiac events were collected from the national registries. The predictive value of ECG was separately analyzed for 10 and 30 years. Major ECG abnormalities were classified according to the Minnesota code. Subjects with major ECG abnormalities (N = 1131) had an increased risk of cardiac death after 10-years (adjusted hazard ratio [HR] 1.7; 95% confidence interval [95% CI], 1.1-2.5, p = 0.009) and 30-years of follow-up (HR 1.3, 95% CI, 1.1-1.5, p < 0.001). Model discrimination measured with the C-index showed only a minor improvement with the inclusion of ECG abnormalities: 0.851 versus 0.853 and 0.742 versus 0.743 for 10- and 30-year follow-up, respectively. ECG did not predict non-fatal cardiac events after 10-years or 30-years of follow-up. Major ECG abnormalities are associated with an increased risk of short and long-term cardiac mortality in middle-aged subjects. However, the improvement in discrimination between subjects with and without fatal cardiac events was marginal with abnormal ECG. Abnormalities observed on 12-lead electrocardiogram are shown to have prognostic significance for cardiac events in elderly subjects without known cardiac disease. Our results suggest that ECG abnormalities increase the risk of fatal cardiac events also in middle-aged healthy subjects.

  5. 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.

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

    PubMed

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

    2017-05-15

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

  7. 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.

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

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

    Savchenko, V.; Ferrigno, C.; Bozzo, E.

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

  9. 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.

    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.

  10. An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection.

    PubMed

    Putra, I Putu Edy Suardiyana; Brusey, James; Gaura, Elena; Vesilo, Rein

    2017-12-22

    The fixed-size non-overlapping sliding window (FNSW) and fixed-size overlapping sliding window (FOSW) approaches are the most commonly used data-segmentation techniques in machine learning-based fall detection using accelerometer sensors. However, these techniques do not segment by fall stages (pre-impact, impact, and post-impact) and thus useful information is lost, which may reduce the detection rate of the classifier. Aligning the segment with the fall stage is difficult, as the segment size varies. We propose an event-triggered machine learning (EvenT-ML) approach that aligns each fall stage so that the characteristic features of the fall stages are more easily recognized. To evaluate our approach, two publicly accessible datasets were used. Classification and regression tree (CART), k -nearest neighbor ( k -NN), logistic regression (LR), and the support vector machine (SVM) were used to train the classifiers. EvenT-ML gives classifier F-scores of 98% for a chest-worn sensor and 92% for a waist-worn sensor, and significantly reduces the computational cost compared with the FNSW- and FOSW-based approaches, with reductions of up to 8-fold and 78-fold, respectively. EvenT-ML achieves a significantly better F-score than existing fall detection approaches. These results indicate that aligning feature segments with fall stages significantly increases the detection rate and reduces the computational cost.

  11. Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

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

    Teuton, Jeremy R.; Griswold, Richard L.; Mehdi, Beata L.

    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 datamore » 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.« less

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

    PubMed Central

    Park, Kyounghoon; Soukavong, Mick; Kim, Jungmee; Kwon, Kyoung-eun; Jin, Xue-mei; Lee, Joongyub; Yang, Bo Ram

    2017-01-01

    Purpose To detect signals of adverse drug events after imipenem treatment using the Korea Institute of Drug Safety & Risk Management-Korea adverse event reporting system database (KIDS-KD). Materials and Methods We performed data mining using KIDS-KD, which was constructed using spontaneously reported adverse event (AE) reports between December 1988 and June 2014. We detected signals calculated the proportional reporting ratio, reporting odds ratio, and information component of imipenem. We defined a signal as any AE that satisfied all three indices. The signals were compared with drug labels of nine countries. Results There were 807582 spontaneous AEs reports in the KIDS-KD. Among those, the number of antibiotics related AEs was 192510; 3382 reports were associated with imipenem. The most common imipenem-associated AE was the drug eruption; 353 times. We calculated the signal by comparing with all other antibiotics and drugs; 58 and 53 signals satisfied the three methods. We compared the drug labelling information of nine countries, including the USA, the UK, Japan, Italy, Switzerland, Germany, France, Canada, and South Korea, and discovered that the following signals were currently not included in drug labels: hypokalemia, cardiac arrest, cardiac failure, Parkinson's syndrome, myocardial infarction, and prostate enlargement. Hypokalemia was an additional signal compared with all other antibiotics, and the other signals were not different compared with all other antibiotics and all other drugs. Conclusion We detected new signals that were not listed on the drug labels of nine countries. However, further pharmacoepidemiologic research is needed to evaluate the causality of these signals. PMID:28332362

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

    PubMed

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

    2017-05-01

    To detect signals of adverse drug events after imipenem treatment using the Korea Institute of Drug Safety & Risk Management-Korea adverse event reporting system database (KIDS-KD). We performed data mining using KIDS-KD, which was constructed using spontaneously reported adverse event (AE) reports between December 1988 and June 2014. We detected signals calculated the proportional reporting ratio, reporting odds ratio, and information component of imipenem. We defined a signal as any AE that satisfied all three indices. The signals were compared with drug labels of nine countries. There were 807582 spontaneous AEs reports in the KIDS-KD. Among those, the number of antibiotics related AEs was 192510; 3382 reports were associated with imipenem. The most common imipenem-associated AE was the drug eruption; 353 times. We calculated the signal by comparing with all other antibiotics and drugs; 58 and 53 signals satisfied the three methods. We compared the drug labelling information of nine countries, including the USA, the UK, Japan, Italy, Switzerland, Germany, France, Canada, and South Korea, and discovered that the following signals were currently not included in drug labels: hypokalemia, cardiac arrest, cardiac failure, Parkinson's syndrome, myocardial infarction, and prostate enlargement. Hypokalemia was an additional signal compared with all other antibiotics, and the other signals were not different compared with all other antibiotics and all other drugs. We detected new signals that were not listed on the drug labels of nine countries. However, further pharmacoepidemiologic research is needed to evaluate the causality of these signals. © Copyright: Yonsei University College of Medicine 2017

  14. Psychosocial correlates, outcome, and stability of abnormal adolescent eating behavior in community samples of young people.

    PubMed

    Steinhausen, Hans-Christoph; Gavez, Silvia; Winkler Metzke, Christa

    2005-03-01

    The current study investigated psychosocial correlates of abnormal adolescent eating behavior at three times during adolescence and young adulthood and its association with psychiatric diagnosis in young adulthood in a community sample. Sixty-four (10.5%) high-risk subjects (mean age 15 years) with abnormal eating behavior were identified at Time 1, another 252 (16.9%) were identified at Time 2 (mean age 16.2 years), and 164 (16.9%) were identified at Time 3 (mean age 19.7 years) and compared with three control groups matched for age and gender. Dependent measures included emotional and behavioral problems, life events, coping capacities, self-related cognition, social network, and family functions. Outcome was measured additionally by structured psychiatric interviews, and stability of abnormal eating behavior was studied in a longitudinal sample of 330 subjects. Few subjects showed more than one of five criteria of abnormal eating behavior. High-risk subjects shared a very similar pattern at all three times. They were characterized by higher scores for emotional and behavioral problems, more life events including more negative impact, less active coping, lower self-esteem, and less family cohesion. Among 10 major psychiatric disorders, only clinical eating disorders at Time 3 shared a significant association with abnormal eating disorder at the same time whereas high-risk status at Times 1 and 2 did not predict any psychiatric disorder at Time 3. Stability of abnormal eating behavior across time was very low. Stability of abnormal eating behavior across time was very low. Abnormal eating behavior in adolescence and young adulthood is clearly associated with various indicators of psychosocial maladaption. In adolescence, it does not significantly predict any psychiatric disorder including eating disorder in young adulthood and it is predominantly a transient feature. (c) 2005 by Wiley Periodicals, Inc.

  15. The accuracy of ultrasound in the diagnosis of congenital abnormalities.

    PubMed

    Munim, Shama; Nadeem, Salva; Khuwaja, Nadya Ali

    2006-01-01

    To determine the accuracy of ultrasound in the diagnosis of congenital abnormalities at the Aga Khan University Hospital, Karachi. The data of congenital abnormalities was obtained from the obstetrical database and medical records of all cases complicated by congenital abnormalities, delivering from January 2001 to December 2003 and was reviewed. Antenatal ultrasounds had been performed by operators with different level of experience. In addition this data was retrieved from the termination and Congenital anomaly register. A structured data collection form was used to collect information of different variables of interest. Congenital abnormalities, complicated 2.8% (n=170), of all deliveries, including all cases of termination of pregnancy, stillbirth and live births. Out of the total, 11.6% occurred in women above the age of 35 years. Consanguinity was found in 18.2% cases. Prenatal diagnosis was made in just under half of the cases (48.8%). Central nervous system and renal abnormalities were commonly diagnosed. However, facial defects, heart defects or skeletal defects were more commonly missed. Antenatal ultrasound successfully diagnosed foetal abnormalities in 48.8% of cases, and more than 90% Central Nervous system defects and renal abnormalities. In contrast about a quarter of Cardiac defects and none of the facial defects were detected. Based on these findings we recommend that the Sonologist should incorporate four chamber view of the heart and also look at the face carefully.

  16. Using narrow-band imaging with conventional hysteroscopy increases the detection of chronic endometritis in abnormal uterine bleeding and postmenopausal bleeding.

    PubMed

    Ozturk, Mustafa; Ulubay, Mustafa; Alanbay, Ibrahim; Keskin, Uğur; Karasahin, Emre; Yenen, Müfit Cemal

    2016-01-01

    A preliminary study was designed to evaluate whether a narrow-band imaging (NBI) endoscopic light source could detect chronic endometritis that was not identifiable with a white light hysteroscope. A total of 86 patients with endometrial pathology (71 abnormal uterine bleeding and 15 postmenopausal bleeding) were examined by NBI endoscopy and white light hysteroscopy between February 2010 and February 2011. The surgeon initially observed the uterine cavity using white light hysteroscopy and made a diagnostic impression, which was recorded. Subsequently, after pressing a button on the telescope, NBI was used to reevaluate the endometrial mucosa. The median age of the patients was 40 years (range: 30-60 years). Endometritis was diagnosed histologically. Six cases of abnormal uterine bleeding (6/71, 8.4%, 95% confidence interval [CI] 0.03-0.17) and one case of postmenopausal bleeding (1/15, 6%, 95%CI 0.01-0.29) were only diagnosed with chronic endometritis by NBI (7/86, 8.1%, 95%CI 0.04-0.15). Capillary patterns of the endometrium can be observed by NBI and this method can be used to assess chronic endometritis. © 2015 Japan Society of Obstetrics and Gynecology.

  17. 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

  18. Gait-Event-Based Synchronization Method for Gait Rehabilitation Robots via a Bioinspired Adaptive Oscillator.

    PubMed

    Chen, Gong; Qi, Peng; Guo, Zhao; Yu, Haoyong

    2017-06-01

    In the field of gait rehabilitation robotics, achieving human-robot synchronization is very important. In this paper, a novel human-robot synchronization method using gait event information is proposed. This method includes two steps. First, seven gait events in one gait cycle are detected in real time with a hidden Markov model; second, an adaptive oscillator is utilized to estimate the stride percentage of human gait using any one of the gait events. Synchronous reference trajectories for the robot are then generated with the estimated stride percentage. This method is based on a bioinspired adaptive oscillator, which is a mathematical tool, first proposed to explain the phenomenon of synchronous flashing among fireflies. The proposed synchronization method is implemented in a portable knee-ankle-foot robot and tested in 15 healthy subjects. This method has the advantages of simple structure, flexible selection of gait events, and fast adaptation. Gait event is the only information needed, and hence the performance of synchronization holds when an abnormal gait pattern is involved. The results of the experiments reveal that our approach is efficient in achieving human-robot synchronization and feasible for rehabilitation robotics application.

  19. Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition

    PubMed Central

    Cui, Zhiming; Zhao, Pengpeng

    2014-01-01

    A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045

  20. Granulocyte, monocyte and blast immunophenotype abnormalities in acute myeloid leukemia with myelodysplasia-related changes.

    PubMed

    Ayar, Sonali P; Ravula, Sreelakshmi; Polski, Jacek M

    2014-01-01

    Little literature exists regarding granulocyte and monocyte immunophenotype abnormalities in Acute Myeloid Leukemia (AML). We hypothesized that granulocyte and monocyte immunophenotype abnormalities are common in AML, and especially in AML with myelodysplasia-related changes (AMLMRC). Bone marrow or peripheral blood specimens from 48 cases of AML and 22 cases of control specimens were analyzed by flow cytometric immunophenotyping. Granulocyte, monocyte, and blast immunophenotype abnormalities were compared between cases of AML versus controls and AMLMRC versus AML without myelodysplasia. The results revealed that granulocyte, monocyte, and blast abnormalities were more common in AMLMRC than in AML without myelodysplasia or control cases. The difference reached statistical significance for abnormalities of granulocytes and abnormalities in all cells of interest. From the numerous individual abnormalities, only CD25 expression in blasts was significantly more prevalent in AMLMRC in this study. We conclude that detection of granulocyte, monocyte, and blast immunophenotype abnormalities can contribute to the diagnosis of AMLMRC.

  1. DNA methylation abnormalities in congenital heart disease.

    PubMed

    Serra-Juhé, Clara; Cuscó, Ivon; Homs, Aïda; Flores, Raquel; Torán, Núria; Pérez-Jurado, Luis A

    2015-01-01

    Congenital heart defects represent the most common malformation at birth, occurring also in ∼50% of individuals with Down syndrome. Congenital heart defects are thought to have multifactorial etiology, but the main causes are largely unknown. We have explored the global methylation profile of fetal heart DNA in comparison to blood DNA from control subjects: an absolute correlation with the type of tissue was detected. Pathway analysis revealed a significant enrichment of differential methylation at genes related to muscle contraction and cardiomyopathies in the developing heart DNA. We have also searched for abnormal methylation profiles on developing heart-tissue DNA of syndromic and non-syndromic congenital heart defects. On average, 3 regions with aberrant methylation were detected per sample and 18 regions were found differentially methylated between groups. Several epimutations were detected in candidate genes involved in growth regulation, apoptosis and folate pathway. A likely pathogenic hypermethylation of several intragenic sites at the MSX1 gene, involved in outflow tract morphogenesis, was found in a fetus with isolated heart malformation. In addition, hypermethylation of the GATA4 gene was present in fetuses with Down syndrome with or without congenital heart defects, as well as in fetuses with isolated heart malformations. Expression deregulation of the abnormally methylated genes was detected. Our data indicate that epigenetic alterations of relevant genes are present in developing heart DNA in fetuses with both isolated and syndromic heart malformations. These epimutations likely contribute to the pathogenesis of the malformation by cis-acting effects on gene expression.

  2. Failure of pre-natal ultrasonography to prevent urinary infection associated with underlying urological abnormalities.

    PubMed

    Lakhoo, K; Thomas, D F; Fuenfer, M; D'Cruz, A J

    1996-06-01

    To analyse the reasons underlying the failure of routine pre-natal ultrasonography to prevent the subsequent development of urinary tract infection (UTI) in children with predisposing urological abnormalities. This retrospective study comprised 39 children (22 females and 17 males) who had at least one documented UTI, the presence of an anatomical anomaly of the urinary tract recognized as predisposing to UTI and had undergone ultrasonography of the urinary tract undertaken in fetal life as part of routine maternal ante-natal ultrasonography. Four categories of patients were defined: Group A, those with normal findings on pre-natal ultrasonography and no urological abnormality detected; Group B, those with a urological abnormality detected but where there was a subsequent failure of communication among clinicians; Group C, those with a urological abnormality but who received inappropriate or sub-optimal post-natal management and; Group D, those with a urological abnormality but who had a UTI despite appropriate post-natal management. In each case, the most severe documented episode of UTI was categorized as: Grade I, asymptomatic bacteriuria; Grade II, mild/moderate symptomatic UTI and; Grade III, severe symptomatic UTI necessitating hospital admission. Group A comprised 22 (56%), Group B three (9%), Group C two (5%) and Group D 12 children (31%). Of the 22 children in Group A, nine experienced a UTI of sufficient severity to necessitate hospital admission. Of the 12 children in Group D only one required hospital admission. The failure of pre-natal ultrasonography to identify the underlying predisposing urological abnormality was the most important factor contributing to subsequent UTI in post-natal life. Failure of communication and inappropriate post-natal management were numerically unimportant. In some children, UTI occurred despite pre-natal detection of their underlying anomaly and appropriate post-natal management. However, in this group the UTI was less

  3. Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

    PubMed

    Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

    2005-05-18

    To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

  4. Can Signal Abnormalities Detected with MR Imaging in Knee Articular Cartilage Be Used to Predict Development of Morphologic Cartilage Defects? 48-Month Data from the Osteoarthritis Initiative

    PubMed Central

    Gersing, Alexandra S.; Mbapte Wamba, John; Nevitt, Michael C.; McCulloch, Charles E.; Link, Thomas M.

    2016-01-01

    significantly more likely in any of the subgrades (P = .98) and was significantly associated with progression of bone marrow abnormalities (P = .002). Conclusion Knee cartilage signal abnormalities detected with MR imaging are precursors of morphologic defects with osteoarthritis and may serve as imaging biomarkers with which to assess risk for cartilage degeneration. © RSNA, 2016 PMID:27135833

  5. Abnormal grain growth in AISI 304L stainless steel

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

    Shirdel, M., E-mail: mshirdel1989@ut.ac.ir; Mirzadeh, H., E-mail: hmirzadeh@ut.ac.ir; Advanced Metalforming and Thermomechanical Processing Laboratory, School of Metallurgy and Materials Engineering, University of Tehran, Tehran

    2014-11-15

    The microstructural evolution during abnormal grain growth (secondary recrystallization) in 304L stainless steel was studied in a wide range of annealing temperatures and times. At relatively low temperatures, the grain growth mode was identified as normal. However, at homologous temperatures between 0.65 (850 °C) and 0.7 (900 °C), the observed transition in grain growth mode from normal to abnormal, which was also evident from the bimodality in grain size distribution histograms, was detected to be caused by the dissolution/coarsening of carbides. The microstructural features such as dispersed carbides were characterized by optical metallography, X-ray diffraction, scanning electron microscopy, energy dispersivemore » X-ray analysis, and microhardness. Continued annealing to a long time led to the completion of secondary recrystallization and the subsequent reappearance of normal growth mode. Another instance of abnormal grain growth was observed at homologous temperatures higher than 0.8, which may be attributed to the grain boundary faceting/defaceting phenomenon. It was also found that when the size of abnormal grains reached a critical value, their size will not change too much and the grain growth behavior becomes practically stagnant. - Highlights: • Abnormal grain growth (secondary recrystallization) in AISI 304L stainless steel • Exaggerated grain growth due to dissolution/coarsening of carbides • The enrichment of carbide particles by titanium • Abnormal grain growth due to grain boundary faceting at very high temperatures • The stagnancy of abnormal grain growth by annealing beyond a critical time.« less

  6. Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops.

    PubMed

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming

    2015-12-03

    Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi(®) Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops.

  7. Abnormal Condition Monitoring of Workpieces Based on RFID for Wisdom Manufacturing Workshops

    PubMed Central

    Zhang, Cunji; Yao, Xifan; Zhang, Jianming

    2015-01-01

    Radio Frequency Identification (RFID) technology has been widely used in many fields. However, previous studies have mainly focused on product life cycle tracking, and there are few studies on real-time status monitoring of workpieces in manufacturing workshops. In this paper, a wisdom manufacturing model is introduced, a sensing-aware environment for a wisdom manufacturing workshop is constructed, and RFID event models are defined. A synthetic data cleaning method is applied to clean the raw RFID data. The Complex Event Processing (CEP) technology is adopted to monitor abnormal conditions of workpieces in real time. The RFID data cleaning method and data mining technology are examined by simulation and physical experiments. The results show that the synthetic data cleaning method preprocesses data well. The CEP based on the Rifidi® Edge Server technology completed abnormal condition monitoring of workpieces in real time. This paper reveals the importance of RFID spatial and temporal data analysis in real-time status monitoring of workpieces in wisdom manufacturing workshops. PMID:26633418

  8. Next generation sequencing identifies abnormal Y chromosome and candidate causal variants in premature ovarian failure patients.

    PubMed

    Lee, Yujung; Kim, Changshin; Park, YoungJoon; Pyun, Jung-A; Kwack, KyuBum

    2016-12-01

    Premature ovarian failure (POF) is characterized by heterogeneous genetic causes such as chromosomal abnormalities and variants in causal genes. Recently, development of techniques made next generation sequencing (NGS) possible to detect genome wide variants including chromosomal abnormalities. Among 37 Korean POF patients, XY karyotype with distal part deletions of Y chromosome, Yp11.32-31 and Yp12 end part, was observed in two patients through NGS. Six deleterious variants in POF genes were also detected which might explain the pathogenesis of POF with abnormalities in the sex chromosomes. Additionally, the two POF patients had no mutation in SRY but three non-synonymous variants were detected in genes regarding sex reversal. These findings suggest candidate causes of POF and sex reversal and show the propriety of NGS to approach the heterogeneous pathogenesis of POF. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. 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. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Multiple-Array Detection, Association and Location of Infrasound and Seismo-Acoustic Events - Utilization of Ground Truth Information

    DTIC Science & Technology

    2010-09-01

    MULTIPLE-ARRAY DETECTION, ASSOCIATION AND LOCATION OF INFRASOUND AND SEISMO-ACOUSTIC EVENTS – UTILIZATION OF GROUND TRUTH INFORMATION Stephen J...and infrasound data from seismo-acoustic arrays and apply the methodology to regional networks for validation with ground truth information. In the...initial year of the project automated techniques for detecting, associating and locating infrasound signals were developed. Recently, the location

  11. Detector for flow abnormalities in gaseous diffusion plant compressors

    DOEpatents

    Smith, Stephen F.; Castleberry, Kim N.

    1998-01-01

    A detector detects a flow abnormality in a plant compressor which outputs a motor current signal. The detector includes a demodulator/lowpass filter demodulating and filtering the motor current signal producing a demodulated signal, and first, second, third and fourth bandpass filters connected to the demodulator/lowpass filter, and filtering the demodulated signal in accordance with first, second, third and fourth bandpass frequencies generating first, second, third and fourth filtered signals having first, second, third and fourth amplitudes. The detector also includes first, second, third and fourth amplitude detectors connected to the first, second, third and fourth bandpass filters respectively, and detecting the first, second, third and fourth amplitudes, and first and second adders connected to the first and fourth amplitude detectors and the second and third amplitude detectors respectively, and adding the first and fourth amplitudes and the second and third amplitudes respectively generating first and second added signals. Finally, the detector includes a comparator, connected to the first and second adders, and comparing the first and second added signals and detecting the abnormal condition in the plant compressor when the second added signal exceeds the first added signal by a predetermined value.

  12. Detector for flow abnormalities in gaseous diffusion plant compressors

    DOEpatents

    Smith, S.F.; Castleberry, K.N.

    1998-06-16

    A detector detects a flow abnormality in a plant compressor which outputs a motor current signal. The detector includes a demodulator/lowpass filter demodulating and filtering the motor current signal producing a demodulated signal, and first, second, third and fourth bandpass filters connected to the demodulator/lowpass filter, and filtering the demodulated signal in accordance with first, second, third and fourth bandpass frequencies generating first, second, third and fourth filtered signals having first, second, third and fourth amplitudes. The detector also includes first, second, third and fourth amplitude detectors connected to the first, second, third and fourth bandpass filters respectively, and detecting the first, second, third and fourth amplitudes, and first and second adders connected to the first and fourth amplitude detectors and the second and third amplitude detectors respectively, and adding the first and fourth amplitudes and the second and third amplitudes respectively generating first and second added signals. Finally, the detector includes a comparator, connected to the first and second adders, and comparing the first and second added signals and detecting the abnormal condition in the plant compressor when the second added signal exceeds the first added signal by a predetermined value. 6 figs.

  13. Detecting Regional Myocardial Abnormalities in Patients With Wolff-Parkinson-White Syndrome With the Use of ECG-Gated Cardiac MDCT.

    PubMed

    Lee, Hye-Jeong; Uhm, Jae-Sun; Joung, Boyoung; Hong, Yoo Jin; Hur, Jin; Choi, Byoung Wook; Kim, Young Jin

    2016-04-01

    Myocardial dyskinesia caused by the accessory pathway and related reversible heart failure have been well documented in echocardiographic studies of pediatric patients with Wolff-Parkinson-White (WPW) syndrome. However, the long-term effects of dyskinesia on the myocardium of adult patients have not been studied in depth. The goal of the present study was to evaluate regional myocardial abnormalities on cardiac CT examinations of adult patients with WPW syndrome. Of 74 patients with WPW syndrome who underwent cardiac CT from January 2006 through December 2013, 58 patients (mean [± SD] age, 52.2 ± 12.7 years), 36 (62.1%) of whom were men, were included in the study after the presence of combined cardiac disease was excluded. Two observers blindly evaluated myocardial thickness and attenuation on cardiac CT scans. On the basis of CT findings, patients were classified as having either normal or abnormal findings. We compared the two groups for other clinical findings, including observations from ECG, echocardiography, and electrophysiologic study. Of the 58 patients studied, 16 patients (27.6%) were found to have myocardial abnormalities (i.e., abnormal wall thinning with or without low attenuation). All abnormal findings corresponded with the location of the accessory pathway. Patients with abnormal findings had statistically significantly decreased left ventricular function, compared with patients with normal findings (p < 0.001). The frequency of regional wall motion abnormality was statistically significantly higher in patients with abnormal findings (p = 0.043). However, echocardiography documented structurally normal hearts in all patients. A relatively high frequency (27.6%) of regional myocardial abnormalities was observed on the cardiac CT examinations of adult patients with WPW syndrome. These abnormal findings might reflect the long-term effects of dyskinesia, suggesting irreversible myocardial injury that ultimately causes left ventricular dysfunction.

  14. 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).

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

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

    Pal, Helena J. van der, E-mail: h.j.vanderpal@amc.uva.nl; Department of Pediatric Oncology, Emma Children's Hospital/Academic Medical Center, Amsterdam; Dijk, Irma W. van

    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 multivariablemore » 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

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

    PubMed

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

    2014-08-15

    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. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  17. 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

  18. Meiotic abnormalities

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

    NONE

    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.

  19. High levels of bcl-2 protein expression do not correlate with genetic abnormalities but predict worse prognosis in patients with lymphoblastic lymphoma.

    PubMed

    Gu, Yajun; Pan, Yi; Meng, Bin; Guan, Bingxin; Fu, Kai; Sun, Baocun; Zheng, Fang

    2013-06-01

    We aimed to investigate bcl-2, bcl-6, and c-myc rearrangements in patients with lymphoblastic lymphoma (LBL), especially focus on the correlation of protein expression with genetic abnormalities. Moreover, their prognostic significance was further analyzed in LBL. Protein expression and genetic abnormalities of bcl-2, bcl-6, and c-myc were investigated in microarrayed tumors from 33 cases of T cell LBL and eight cases of B cell lineage. Immunohistochemical (IHC) staining was performed to evaluate protein expression, including bcl-2, bcl-6, c-myc, TdT, CD1α, CD34, Ki-67, PAX-5, CD2, CD3, CD4, CD8, and CD20. Genetic abnormalities of bcl-2, bcl-6, and c-myc were detected by dual color fluorescence in situ hybridization (FISH). Bcl-2 protein was positive in 51.2 % (21/41) of the patients, bcl-6 protein in 7.3 % (three out of 41), and c-myc protein in 78.0 % (32/41). Bcl-2 breakpoint was found in two cases by FISH analysis. There was no evidence of bcl-6 or c-myc rearrangement in patients with LBL. However, both gene gain and loss events occurred in bcl-2, bcl-6, and c-myc. A univariate analysis showed that stage III or IV, elevated lactate dehydrogenase (LDH), and positivity for bcl-2 protein were associated with shorter survival (p<0.05). Enhanced protein expression and detectable genetic abnormalities of bcl-2, bcl-6, and c-myc were observed in patients with LBL. No statistical correlation was found between IHC results and cytogenetic findings. Stage III or IV, elevated LDH, and positivity for bcl-2 protein were identified as adverse prognostic factors. The patients with more adverse factors would have increasingly worse prognosis.

  20. 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.

  1. Accuracy of saline contrast sonohysterography in detection of endometrial polyps and submucosal leiomyomas in women of reproductive age with abnormal uterine bleeding: systematic review and meta-analysis.

    PubMed

    Bittencourt, C A; Dos Santos Simões, R; Bernardo, W M; Fuchs, L F P; Soares Júnior, J M; Pastore, A R; Baracat, E C

    2017-07-01

    To analyze the diagnostic accuracy of two- (2D) and three- (3D) dimensional saline contrast sonohysterography (SCSH) in the detection of endometrial polyps and submucosal uterine leiomyomas in women of reproductive age with abnormal uterine bleeding compared with gold standard hysteroscopy. A systematic review of diagnostic studies that compared 2D- and/or 3D-SCSH with hysteroscopy and anatomopathology was conducted according to PRISMA and SEDATE recommendations. The databases MEDLINE, EMBASE and The Cochrane Library were searched electronically using specific terms with no restriction on language or publication year. Quality assessment of included studies was performed using the QUADAS-2 tool. Meta-analysis was performed with the Meta-DiSk program and data presented as forest plots and summary receiver-operating characteristics (SROC) curves. Pooled sensitivity, specificity and positive (LR+) and negative (LR-) likelihood ratios of SCSH in the detection of uterine cavity abnormalities were calculated. A total of 1398 citations were identified and five studies were included in the systematic review and meta-analysis. Pooled sensitivity and specificity of 2D-SCSH in detecting endometrial polyps were 93% (95% CI, 89-96%) and 81% (95% CI, 76-86%), respectively, with pooled LR+ of 5.41 (95% CI, 2.60-11.28) and LR- of 0.10 (95% CI, 0.06-0.17). In the detection of submucosal uterine leiomyomas, pooled sensitivity and specificity were 94% (95% CI, 89-97%) and 81% (95% CI, 76-86%), respectively, with pooled LR+ of 4.25 (95% CI, 2.20-8.21) and LR- of 0.11 (95% CI, 0.05-0.22). 2D-SCSH had good accuracy in detecting endometrial polyps and submucosal uterine leiomyomas, with areas under the SROC curves of 0.97 ± 0.02 and 0.97 ± 0.03, respectively. Studies that analyzed the diagnostic accuracy of 3D-SCSH could not be compared due to high heterogeneity related to menopausal status, type of technique used and primary outcome being investigation of infertility. 2D

  2. Risk of Newly Detected Infections and Cervical Abnormalities in Women Seropositive for Naturally Acquired Human Papillomavirus Type 16/18 Antibodies: Analysis of the Control Arm of PATRICIA

    PubMed Central

    Castellsagué, Xavier; Naud, Paulo; Chow, Song-Nan; Wheeler, Cosette M.; Germar, Maria Julieta V.; Lehtinen, Matti; Paavonen, Jorma; Jaisamrarn, Unnop; Garland, Suzanne M.; Salmerón, Jorge; Apter, Dan; Kitchener, Henry; Teixeira, Julio C.; Skinner, S. Rachel; Limson, Genara; Szarewski, Anne; Romanowski, Barbara; Aoki, Fred Y.; Schwarz, Tino F.; Poppe, Willy A. J.; Bosch, F. Xavier; de Carvalho, Newton S.; Peters, Klaus; Tjalma, Wiebren A. A.; Safaeian, Mahboobeh; Raillard, Alice; Descamps, Dominique; Struyf, Frank; Dubin, Gary; Rosillon, Dominique; Baril, Laurence

    2014-01-01

    Background. We examined risk of newly detected human papillomavirus (HPV) infection and cervical abnormalities in relation to HPV type 16/18 antibody levels at enrollment in PATRICIA (Papilloma Trial Against Cancer in Young Adults; NCT00122681). Methods. Using Poisson regression, we compared risk of newly detected infection and cervical abnormalities associated with HPV-16/18 between seronegative vs seropositive women (15–25 years) in the control arm (DNA negative at baseline for the corresponding HPV type [HPV-16: n = 8193; HPV-18: n = 8463]). Results. High titers of naturally acquired HPV-16 antibodies and/or linear trend for increasing antibody levels were significantly associated with lower risk of incident and persistent infection, atypical squamous cells of undetermined significance or greater (ASCUS+), and cervical intraepithelial neoplasia grades 1/2 or greater (CIN1+, CIN2+). For HPV-18, although seropositivity was associated with lower risk of ASCUS+ and CIN1+, no association between naturally acquired antibodies and infection was demonstrated. Naturally acquired HPV-16 antibody levels of 371 (95% confidence interval [CI], 242–794), 204 (95% CI, 129–480), and 480 (95% CI, 250–5756) EU/mL were associated with 90% reduction of incident infection, 6-month persistent infection, and ASCUS+, respectively. Conclusions. Naturally acquired antibodies to HPV-16, and to a lesser extent HPV-18, are associated with some reduced risk of subsequent infection and cervical abnormalities associated with the same HPV type. PMID:24610876

  3. Development of a triage engine enabling behavior recognition and lethal arrhythmia detection for remote health care system.

    PubMed

    Sugano, Hiroto; Hara, Shinsuke; Tsujioka, Tetsuo; Inoue, Tadayuki; Nakajima, Shigeyoshi; Kozaki, Takaaki; Namkamura, Hajime; Takeuchi, Kazuhide

    2011-01-01

    For ubiquitous health care systems which continuously monitor a person's vital signs such as electrocardiogram (ECG), body surface temperature and three-dimensional (3D) acceleration by wireless, it is important to accurately detect the occurrence of an abnormal event in the data and immediately inform a medical doctor of its detail. In this paper, we introduce a remote health care system, which is composed of a wireless vital sensor, multiple receivers and a triage engine installed in a desktop personal computer (PC). The middleware installed in the receiver, which was developed in C++, supports reliable data handling of vital data to the ethernet port. On the other hand, the human interface of the triage engine, which was developed in JAVA, shows graphics on his/her ECG data, 3D acceleration data, body surface temperature data and behavior status in the display of the desktop PC and sends an urgent e-mail containing the display data to a pre-registered medical doctor when it detects the occurrence of an abnormal event. In the triage engine, the lethal arrhythmia detection algorithm based on short time Fourier transform (STFT) analysis can achieve 100 % sensitivity and 99.99 % specificity, and the behavior recognition algorithm based on the combination of the nearest neighbor method and the Naive Bayes method can achieve more than 71 % classification accuracy.

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

    PubMed

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

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

  5. 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.

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

    DOEpatents

    Odell, D.M.C.

    1994-10-11

    An apparatus and method are disclosed 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. 4 figs.

  7. The Prevalence and Significance of Abnormal Vital Signs Prior to In-Hospital Cardiac Arrest

    PubMed Central

    Andersen, Lars W.; Kim, Won Young; Chase, Maureen; Berg, Katherine; Mortensen, Sharri J.; Moskowitz, Ari; Novack, Victor; Cocchi, Michael N.; Donnino, Michael W.

    2015-01-01

    Background Patients suffering in-hospital cardiac arrest often show signs of physiological deterioration before the event. The purpose of this study was to determine the prevalence of abnormal vital signs 1–4 hours before cardiac arrest, and to evaluate the association between these vital sign abnormalities and inhospital mortality. Methods We included adults from the Get With the Guidelines® - Resuscitation registry with an in-hospital cardiac arrest. We used two a priori definitions for vital signs: abnormal (heart rate (HR) ≤ 60 or ≥ 100 min−1, respiratory rate (RR) ≤ 10 or > 20 min−1 and systolic blood pressure (SBP) ≤ 90 mm Hg) and severely abnormal (HR ≤ 50 or ≥ 130 min−1, RR ≤ 8 or ≥ 30 min−1 and SBP ≤80 mm Hg). We evaluated the association between the number of abnormal vital signs and in-hospital mortality using a multivariable logistic regression model. Results 7,851 patients were included. Individual vital signs were associated with in-hospital mortality. The majority of patients (59.4%) had at least one abnormal vital sign 1–4 hours before the arrest and 13.4% had at least one severely abnormal sign. We found a step-wise increase in mortality with increasing number of abnormal vital signs within the abnormal (odds ratio (OR) 1.53 (CI: 1.42 – 1.64) and severely abnormal groups (OR 1.62 [CI: 1.38 – 1.90]). This remained in multivariable analysis (abnormal: OR 1.38 [CI: 1.28 – 1.48], and severely abnormal: OR 1.40 [CI: 1.18 – 1.65]). Conclusion Abnormal vital signs are prevalent 1–4 hours before in-hospital cardiac arrest on hospital wards. Inhospital mortality increases with increasing number of pre-arrest abnormal vital signs as well as increased severity of vital sign derangements. PMID:26362486

  8. Abnormal branching and regression of the notochord and its relationship to foregut abnormalities.

    PubMed

    Vleesch Dubois, V N; Quan Qi, B; Beasley, S W; Williams, A

    2002-04-01

    An abnormally positioned notochord has been reported in embryos that develop foregut abnormalities, vertebral defects and other abnormalities of the VATER association. This study examines the patterns of regression of the abnormal notochord in the rat model of the VATER association and investigates the relationship between developmental abnormalities of the notochord and those of the vertebra and foregut. Timed-pregnant Sprague-Dawley rats were given daily intraperitoneal injections of 1.75 mg/kg adriamycin on gestational days 6 - 9 inclusive. Rats were sacrificed between days 14 and 20 and their embryos harvested, histologically sectioned and stained and examined serially. The location and appearance of the degenerating notochord and its relationship to regional structural defects were analysed. All 26 embryos exposed to adriamycin developed foregut abnormalities and had an abnormal notochord. The notochord disappeared by a process of apoptotic degeneration that lagged behind that of the normal embryo: the notochord persisted in the abnormal embryo beyond day 17, whereas in the normal rat it had already disappeared. Similarly, formation of the nucleus pulposus was delayed. Vertebral abnormalities occurred when the notochord was ventrally-positioned. The notochord disappears during day 16 in the normal embryo whereas abnormal branches of the notochord persist until day 19 in the adriamycin-treated embryo. Degeneration of the notochord is dominated by apoptosis. An excessively ventrally-placed notochord is closely associated with abnormalities of the vertebral column, especially hemivertebrae.

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

    DOEpatents

    De Geronimo, Gianluigi [Syosset, NY; Bolotnikov, Aleksey E [South Setauket, NY; Carini, Gabriella [Port Jefferson, NY

    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.

  10. Detectable clonal mosaicism and its relationship to aging and cancer

    PubMed Central

    Jacobs, Kevin B; Yeager, Meredith; Zhou, Weiyin; Wacholder, Sholom; Wang, Zhaoming; Rodriguez-Santiago, Benjamin; Hutchinson, Amy; Deng, Xiang; Liu, Chenwei; Horner, Marie-Josephe; Cullen, Michael; Epstein, Caroline G; Burdett, Laurie; Dean, Michael C; Chatterjee, Nilanjan; Sampson, Joshua; Chung, Charles C; Kovaks, Joseph; Gapstur, Susan M; Stevens, Victoria L; Teras, Lauren T; Gaudet, Mia M; Albanes, Demetrius; Weinstein, Stephanie J; Virtamo, Jarmo; Taylor, Philip R; Freedman, Neal D; Abnet, Christian C; Goldstein, Alisa M; Hu, Nan; Yu, Kai; Yuan, Jian-Min; Liao, Linda; Ding, Ti; Qiao, You-Lin; Gao, Yu-Tang; Koh, Woon-Puay; Xiang, Yong-Bing; Tang, Ze-Zhong; Fan, Jin-Hu; Aldrich, Melinda C; Amos, Christopher; Blot, William J; Bock, Cathryn H; Gillanders, Elizabeth M; Harris, Curtis C; Haiman, Christopher A; Henderson, Brian E; Kolonel, Laurence N; Le Marchand, Loic; McNeill, Lorna H; Rybicki, Benjamin A; Schwartz, Ann G; Signorello, Lisa B; Spitz, Margaret R; Wiencke, John K; Wrensch, Margaret; Wu, Xifeng; Zanetti, Krista A; Ziegler, Regina G; Figueroa, Jonine D; Garcia-Closas, Montserrat; Malats, Nuria; Marenne, Gaelle; Prokunina-Olsson, Ludmila; Baris, Dalsu; Schwenn, Molly; Johnson, Alison; Landi, Maria Teresa; Goldin, Lynn; Consonni, Dario; Bertazzi, Pier Alberto; Rotunno, Melissa; Rajaraman, Preetha; Andersson, Ulrika; Freeman, Laura E Beane; Berg, Christine D; Buring, Julie E; Butler, Mary A; Carreon, Tania; Feychting, Maria; Ahlbom, Anders; Gaziano, J Michael; Giles, Graham G; Hallmans, Goran; Hankinson, Susan E; Hartge, Patricia; Henriksson, Roger; Inskip, Peter D; Johansen, Christoffer; Landgren, Annelie; McKean-Cowdin, Roberta; Michaud, Dominique S; Melin, Beatrice S; Peters, Ulrike; Ruder, Avima M; Sesso, Howard D; Severi, Gianluca; Shu, Xiao-Ou; Visvanathan, Kala; White, Emily; Wolk, Alicja; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Silverman, Debra T; Kogevinas, Manolis; Gonzalez, Juan R; Villa, Olaya; Li, Donghui; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Kooperberg, Charles; Wolpin, Brian M; Jiao, Li; Hassan, Manal; Wheeler, William; Arslan, Alan A; Bas Bueno-de-Mesquita, H; Fuchs, Charles S; Gallinger, Steven; Gross, Myron D; Holly, Elizabeth A; Klein, Alison P; LaCroix, Andrea; Mandelson, Margaret T; Petersen, Gloria; Boutron-Ruault, Marie-Christine; Bracci, Paige M; Canzian, Federico; Chang, Kenneth; Cotterchio, Michelle; Giovannucci, Edward L; Goggins, Michael; Bolton, Judith A Hoffman; Jenab, Mazda; Khaw, Kay-Tee; Krogh, Vittorio; Kurtz, Robert C; McWilliams, Robert R; Mendelsohn, Julie B; Rabe, Kari G; Riboli, Elio; Tjønneland, Anne; Tobias, Geoffrey S; Trichopoulos, Dimitrios; Elena, Joanne W; Yu, Herbert; Amundadottir, Laufey; Stolzenberg-Solomon, Rachael Z; Kraft, Peter; Schumacher, Fredrick; Stram, Daniel; Savage, Sharon A; Mirabello, Lisa; Andrulis, Irene L; Wunder, Jay S; García, Ana Patiño; Sierrasesúmaga, Luis; Barkauskas, Donald A; Gorlick, Richard G; Purdue, Mark; Chow, Wong-Ho; Moore, Lee E; Schwartz, Kendra L; Davis, Faith G; Hsing, Ann W; Berndt, Sonja I; Black, Amanda; Wentzensen, Nicolas; Brinton, Louise A; Lissowska, Jolanta; Peplonska, Beata; McGlynn, Katherine A; Cook, Michael B; Graubard, Barry I; Kratz, Christian P; Greene, Mark H; Erickson, Ralph L; Hunter, David J; Thomas, Gilles; Hoover, Robert N; Real, Francisco X; Fraumeni, Joseph F; Caporaso, Neil E; Tucker, Margaret; Rothman, Nathaniel; Pérez-Jurado, Luis A; Chanock, Stephen J

    2012-01-01

    In an analysis of 31,717 cancer cases and 26,136 cancer-free controls drawn from 13 genome-wide association studies (GWAS), we observed large chromosomal abnormalities in a subset of clones from DNA obtained from blood or buccal samples. Mosaic chromosomal abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of size >2 Mb were observed in autosomes of 517 individuals (0.89%) with abnormal cell proportions between 7% and 95%. In cancer-free individuals, the frequency increased with age; 0.23% under 50 and 1.91% between 75 and 79 (p=4.8×10−8). Mosaic abnormalities were more frequent in individuals with solid-tumors (0.97% versus 0.74% in cancer-free individuals, OR=1.25, p=0.016), with a stronger association for cases who had DNA collected prior to diagnosis or treatment (OR=1.45, p=0.0005). Detectable clonal mosaicism was common in individuals for whom DNA was collected at least one year prior to diagnosis of leukemia compared to cancer-free individuals (OR=35.4, p=3.8×10−11). These findings underscore the importance of the role and time-dependent nature of somatic events in the etiology of cancer and other late-onset diseases. PMID:22561519

  11. Investigation of frog abnormalities on national wildlife refuges in the Northeast U.S.

    USGS Publications Warehouse

    Eaton-Poole, L.; Pinkney, A.E.; Green, D.E.; Sutherland, D.R.; Babbitt, K.J.; ,

    2003-01-01

    To address concerns about frog abnormalities, the U.S. Fish and Wildlife Service examined over 3,643 frogs and toads on National Wildlife Refuges (NWRs) in the Northeast U.S. The objectives were to: 1) determine if certain refuges had sites where abnormalities were frequently observed; 2) evaluate if the prevalence of abnormalities at a site was consistent within a season and among years; and 3) investigate possible causes. Sampling was conducted from 1999 through 2001. A complete sample from a site consisted of ???50 metamorphs of one species. The prevalence of abnormalities ranged from 0 to 15% and fluctuated within season and among years. The most common external abnormalities were truncated limbs, and missing limbs, feet, and digits. Frogs with duplication of limb segments were rare (6). Based on radiographical examinations of 89 abnormal frogs, 55 had abnormalities due to trauma, 22 due to malformations, and 12 could not be classified. Metacercariae of the trematode Ribeiroia were detected in substantial numbers in two species from Iroquois NWR, with one specimen having supernumerary hindlimbs. We recommend continued sampling and integrated, causal evaluations on NWRs where the prevalence of abnormalities exceeds 5% or where the types of abnormalities warrant further study.

  12. Detection of eardrum abnormalities using ensemble deep learning approaches

    NASA Astrophysics Data System (ADS)

    Senaras, Caglar; Moberly, Aaron C.; Teknos, Theodoros; Essig, Garth; Elmaraghy, Charles; Taj-Schaal, Nazhat; Yua, Lianbo; Gurcan, Metin N.

    2018-02-01

    In this study, we proposed an approach to report the condition of the eardrum as "normal" or "abnormal" by ensembling two different deep learning architectures. In the first network (Network 1), we applied transfer learning to the Inception V3 network by using 409 labeled samples. As a second network (Network 2), we designed a convolutional neural network to take advantage of auto-encoders by using additional 673 unlabeled eardrum samples. The individual classification accuracies of the Network 1 and Network 2 were calculated as 84.4%(+/- 12.1%) and 82.6% (+/- 11.3%), respectively. Only 32% of the errors of the two networks were the same, making it possible to combine two approaches to achieve better classification accuracy. The proposed ensemble method allows us to achieve robust classification because it has high accuracy (84.4%) with the lowest standard deviation (+/- 10.3%).

  13. Stock market returns and clinical trial results of investigational compounds: an event study analysis of large biopharmaceutical companies.

    PubMed

    Hwang, Thomas J

    2013-01-01

    For biopharmaceutical companies, investments in research and development are risky, and the results from clinical trials are key inflection points in the process. Few studies have explored how and to what extent the public equity market values clinical trial results. Our study dataset matched announcements of clinical trial results for investigational compounds from January 2011 to May 2013 with daily stock market returns of large United States-listed pharmaceutical and biotechnology companies. Event study methodology was used to examine the relationship between clinical research events and changes in stock returns. We identified public announcements for clinical trials of 24 investigational compounds, including 16 (67%) positive and 8 (33%) negative events. The majority of announcements were for Phase 3 clinical trials (N = 13, 54%), and for oncologic (N = 7, 29%) and neurologic (N = 6, 24%) indications. The median cumulative abnormal returns on the day of the announcement were 0.8% (95% confidence interval [CI]: -2.3, 13.4%; P = 0.02) for positive events and -2.0% (95% CI: -9.1, 0.7%; P = 0.04) for negative events, with statistically significant differences from zero. In the day immediately following the announcement, firms with positive events were associated with stock price corrections, with median cumulative abnormal returns falling to 0.4% (95% CI: -3.8, 12.3%; P = 0.33). For firms with negative announcements, the median cumulative abnormal returns were -1.7% (95% CI: -9.5, 1.0%; P = 0.03), and remained significantly negative over the two day event window. The magnitude of abnormal returns did not differ statistically by indication, by trial phase, or between biotechnology and pharmaceutical firms. The release of clinical trial results is an economically significant event and has meaningful effects on market value for large biopharmaceutical companies. Stock return underperformance due to negative events is greater in magnitude and persists longer than

  14. Stock Market Returns and Clinical Trial Results of Investigational Compounds: An Event Study Analysis of Large Biopharmaceutical Companies

    PubMed Central

    Hwang, Thomas J.

    2013-01-01

    Background For biopharmaceutical companies, investments in research and development are risky, and the results from clinical trials are key inflection points in the process. Few studies have explored how and to what extent the public equity market values clinical trial results. Methods Our study dataset matched announcements of clinical trial results for investigational compounds from January 2011 to May 2013 with daily stock market returns of large United States-listed pharmaceutical and biotechnology companies. Event study methodology was used to examine the relationship between clinical research events and changes in stock returns. Results We identified public announcements for clinical trials of 24 investigational compounds, including 16 (67%) positive and 8 (33%) negative events. The majority of announcements were for Phase 3 clinical trials (N = 13, 54%), and for oncologic (N = 7, 29%) and neurologic (N = 6, 24%) indications. The median cumulative abnormal returns on the day of the announcement were 0.8% (95% confidence interval [CI]: –2.3, 13.4%; P = 0.02) for positive events and –2.0% (95% CI: –9.1, 0.7%; P = 0.04) for negative events, with statistically significant differences from zero. In the day immediately following the announcement, firms with positive events were associated with stock price corrections, with median cumulative abnormal returns falling to 0.4% (95% CI: –3.8, 12.3%; P = 0.33). For firms with negative announcements, the median cumulative abnormal returns were –1.7% (95% CI: –9.5, 1.0%; P = 0.03), and remained significantly negative over the two day event window. The magnitude of abnormal returns did not differ statistically by indication, by trial phase, or between biotechnology and pharmaceutical firms. Conclusions The release of clinical trial results is an economically significant event and has meaningful effects on market value for large biopharmaceutical companies. Stock return

  15. 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

  16. Prevalence and distribution of congenital abnormalities in Turkey: differences between the prenatal and postnatal periods.

    PubMed

    Oztarhan, Kazim; Gedikbasi, Ali; Yildirim, Dogukan; Arslan, Oguz; Adal, Erdal; Kavuncuoglu, Sultan; Ozbek, Sibel; Ceylan, Yavuz

    2010-12-01

    The aim of this study was to determine the distribution of cases associated with congenital abnormalities during the following three periods: pregnancy, birth, and the neonatal period. This was a retrospective study of cases between 2002 and 2006. All abnormal pregnancies, elective terminations of pregnancies, stillbirths, and births with congenital abnormalities managed in the Neonatology Unit were classified based on the above distribution scheme. During the 5-year study period, 1906 cases with congenital abnormalities were recruited, as follows: 640 prenatally detected and terminated cases, with most abnormalities related to the central nervous system, chromosomes, and urogenital system (56.7%, 12.7%, and 8.9%, respectively); 712 neonates with congenital abnormalities (congenital heart disease [49.2%], central nervous system abnormalities [14.7%], and urogenital system abnormalities [12.9%]); and hospital stillbirths, of which 34.2% had malformations (220 prenatal cases [34.4%] had multiple abnormalities, whereas 188 liveborn cases [26.4%] had multiple abnormalities). The congenital abnormalities rate between 2002 and 2006 was 2.07%. Systematic screening for fetal anomalies is the primary means for identification of affected pregnancies. © 2010 The Authors. Congenital Anomalies © 2010 Japanese Teratology Society.

  17. Event-Ready Bell Test Using Entangled Atoms Simultaneously Closing Detection and Locality Loopholes

    NASA Astrophysics Data System (ADS)

    Rosenfeld, Wenjamin; Burchardt, Daniel; Garthoff, Robert; Redeker, Kai; Ortegel, Norbert; Rau, Markus; Weinfurter, Harald

    2017-07-01

    An experimental test of Bell's inequality allows ruling out any local-realistic description of nature by measuring correlations between distant systems. While such tests are conceptually simple, there are strict requirements concerning the detection efficiency of the involved measurements, as well as the enforcement of spacelike separation between the measurement events. Only very recently could both loopholes be closed simultaneously. Here we present a statistically significant, event-ready Bell test based on combining heralded entanglement of atoms separated by 398 m with fast and efficient measurements of the atomic spin states closing essential loopholes. We obtain a violation with S =2.221 ±0.033 (compared to the maximal value of 2 achievable with models based on local hidden variables) which allows us to refute the hypothesis of local realism with a significance level P <2.57 ×10-9.

  18. Event schemas in autism spectrum disorders: the role of theory of mind and weak central coherence.

    PubMed

    Loth, Eva; Gómez, Juan Carlos; Happé, Francesca

    2008-03-01

    Event schemas (generalized knowledge of what happens at common real-life events, e.g., a birthday party) are an important cognitive tool for social understanding: They provide structure for social experiences while accounting for many variable aspects. Using an event narratives task, this study tested the hypotheses that theory of mind (ToM) deficits and weak central coherence (WCC, a local processing bias) undermine different aspects of event knowledge in people with autism spectrum disorder (ASD). Event narratives of ASD ToM-failers were overall significantly impaired. ASD ToM-passers showed more specific abnormalities relating to variable activities, and some of these were significantly associated to WCC. Abnormalities in event knowledge might help linking ASD-typical social deficits in real-life situations and the adherence to inflexible routines.

  19. Dobutamine cardiovascular magnetic resonance for the detection of myocardial ischemia with the use of myocardial tagging.

    PubMed

    Kuijpers, Dirkjan; Ho, Kai Yiu J A M; van Dijkman, Paul R M; Vliegenthart, Rozemarijn; Oudkerk, Matthijs

    2003-04-01

    The purpose of this study was to assess the value of high-dose dobutamine cardiovascular magnetic resonance (CMR) with myocardial tagging for the detection of wall motion abnormalities as a measure of myocardial ischemia in patients with known or suspected coronary artery disease. Two hundred eleven consecutive patients with chest pain underwent dobutamine-CMR 4 days after antianginal medication was stopped. Dobutamine-CMR was performed at rest and during increasing doses of dobutamine. Cine-images were acquired during breath-hold with and without myocardial tagging at 3 short-axis levels. Regional wall motion was assessed in a 16-segment short-axis model. Patients with new wall motion abnormalities (NWMA) were examined by coronary angiography. Dobutamine-CMR was successfully performed in 194 patients. Dobutamine-CMR without tagging detected NWMA in 58 patients, whereas NWMA were detected in 68 patients with tagging (P=0.002, McNemar). Coronary angiography showed coronary artery disease in 65 (96%) of these 68 patients. All but 3 of the 65 patients needed revascularization. In the 112 patients with a negative dobutamine-CMR study, without baseline wall motion abnormalities, the cardiovascular occurrence-free survival rate was 98.2% during the mean follow-up period of 17.3 months (range, 7 to 31). Dobutamine-CMR with myocardial tagging detected more NWMA compared with dobutamine-CMR without tagging and reliably separated patients with a normal life expectancy from those at increased risk of major adverse cardiac events.

  20. Abnormal pupillary light reflex with chromatic pupillometry in Gaucher disease.

    PubMed

    Narita, Aya; Shirai, Kentarou; Kubota, Norika; Takayama, Rumiko; Takahashi, Yukitoshi; Onuki, Takanori; Numakura, Chikahiko; Kato, Mitsuhiro; Hamada, Yusuke; Sakai, Norio; Ohno, Atsuko; Asami, Maya; Matsushita, Shoko; Hayashi, Anri; Kumada, Tomohiro; Fujii, Tatsuya; Horino, Asako; Inoue, Takeshi; Kuki, Ichiro; Asakawa, Ken; Ishikawa, Hitoshi; Ohno, Koyo; Nishimura, Yoko; Tamasaki, Akiko; Maegaki, Yoshihiro; Ohno, Kousaku

    2014-02-01

    The hallmark of neuronopathic Gaucher disease (GD) is oculomotor abnormalities, but ophthalmological assessment is difficult in uncooperative patients. Chromatic pupillometry is a quantitative method to assess the pupillary light reflex (PLR) with minimal patient cooperation. Thus, we investigated whether chromatic pupillometry could be useful for neurological evaluations in GD. In our neuronopathic GD patients, red light-induced PLR was markedly impaired, whereas blue light-induced PLR was relatively spared. In addition, patients with non-neuronopathic GD showed no abnormalities. These novel findings show that chromatic pupillometry is a convenient method to detect neurological signs and monitor the course of disease in neuronopathic GD.

  1. Event-triggered fault detection for a class of discrete-time linear systems using interval observers.

    PubMed

    Zhang, Zhi-Hui; Yang, Guang-Hong

    2017-05-01

    This paper provides a novel event-triggered fault detection (FD) scheme for discrete-time linear systems. First, an event-triggered interval observer is proposed to generate the upper and lower residuals by taking into account the influence of the disturbances and the event error. Second, the robustness of the residual interval against the disturbances and the fault sensitivity are improved by introducing l 1 and H ∞ performances. Third, dilated linear matrix inequalities are used to decouple the Lyapunov matrices from the system matrices. The nonnegative conditions for the estimation error variables are presented with the aid of the slack matrix variables. This technique allows considering a more general Lyapunov function. Furthermore, the FD decision scheme is proposed by monitoring whether the zero value belongs to the residual interval. It is shown that the information communication burden is reduced by designing the event-triggering mechanism, while the FD performance can still be guaranteed. Finally, simulation results demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  2. 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. © 2013.

  3. ACR appropriateness criteria(®) on abnormal vaginal bleeding.

    PubMed

    Bennett, Genevieve L; Andreotti, Rochelle F; Lee, Susanna I; Dejesus Allison, Sandra O; Brown, Douglas L; Dubinsky, Theodore; Glanc, Phyllis; Mitchell, Donald G; Podrasky, Ann E; Shipp, Thomas D; Siegel, Cary Lynn; Wong-You-Cheong, Jade J; Zelop, Carolyn M

    2011-07-01

    In evaluating a woman with abnormal vaginal bleeding, imaging cannot replace definitive histologic diagnosis but often plays an important role in screening, characterization of structural abnormalities, and directing appropriate patient care. Transvaginal ultrasound (TVUS) is generally the initial imaging modality of choice, with endometrial thickness a well-established predictor of endometrial disease in postmenopausal women. Endometrial thickness measurements of ≤5 mm and ≤4 mm have been advocated as appropriate upper threshold values to reasonably exclude endometrial carcinoma in postmenopausal women with vaginal bleeding; however, the best upper threshold endometrial thickness in the asymptomatic postmenopausal patient remains a subject of debate. Endometrial thickness in a premenopausal patient is a less reliable indicator of endometrial pathology since this may vary widely depending on the phase of menstrual cycle, and an upper threshold value for normal has not been well-established. Transabdominal ultrasound is generally an adjunct to TVUS and is most helpful when TVUS is not feasible or there is poor visualization of the endometrium. Hysterosonography may also allow for better delineation of both the endometrium and focal abnormalities in the endometrial cavity, leading to hysteroscopically directed biopsy or resection. Color and pulsed Doppler may provide additional characterization of a focal endometrial abnormality by demonstrating vascularity. MRI may also serve as an important problem-solving tool if the endometrium cannot be visualized on TVUS and hysterosonography is not possible, as well as for pretreatment planning of patients with suspected endometrial carcinoma. CT is generally not warranted for the evaluation of patients with abnormal bleeding, and an abnormal endometrium incidentally detected on CT should be further evaluated with TVUS. Copyright © 2011 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  4. A review for identification of initiating events in event tree development process on nuclear power plants

    NASA Astrophysics Data System (ADS)

    Riyadi, Eko H.

    2014-09-01

    Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.

  5. Isolated cortical visual loss with subtle brain MRI abnormalities in a case of hypoxic-ischemic encephalopathy.

    PubMed

    Margolin, Edward; Gujar, Sachin K; Trobe, Jonathan D

    2007-12-01

    A 16-year-old boy who was briefly asystolic and hypotensive after a motor vehicle accident complained of abnormal vision after recovering consciousness. Visual acuity was normal, but visual fields were severely constricted without clear hemianopic features. The ophthalmic examination was otherwise normal. Brain MRI performed 11 days after the accident showed no pertinent abnormalities. At 6 months after the event, brain MRI demonstrated brain volume loss in the primary visual cortex and no other abnormalities. One year later, visual fields remained severely constricted; neurologic examination, including formal neuropsychometric testing, was normal. This case emphasizes the fact that hypoxic-ischemic encephalopathy (HIE) may cause enduring damage limited to primary visual cortex and that the MRI abnormalities may be subtle. These phenomena should be recognized in the management of patients with HIE.

  6. Prevalence, distribution, and progression of radiographic abnormalities in the lungs of cold-stunned Kemp's ridley sea turtles (Lepidochelys kempii): 89 cases (2002-2005).

    PubMed

    Stockman, Jonathan; Innis, Charles J; Solano, Mauricio; O'Sullivan Brisson, Jennifer; Kass, Philip H; Tlusty, Michael F; Weber, E Scott

    2013-03-01

    To evaluate the prevalence, distribution, and progression of radiographic abnormalities in the lungs of cold-stunned Kemp's ridley sea turtles (Lepidochelys kempii) and associations between these abnormalities and body weight, carapace length, and hematologic and plasma biochemical variables. Retrospective case series. 89 cold-stunned juvenile Kemp's ridley sea turtles. Medical records were reviewed. Dorsoventral and horizontal beam craniocaudal radiographs were evaluated for the presence, distribution, and progression of lung abnormalities. Turtles were categorized as having radiographically normal or abnormal lungs; those with abnormalities detected were further categorized according to the distribution of abnormalities (left lung, right lung, or both affected). Body weight, carapace length, and hematologic and plasma biochemical data were compared among categories. 48 of 89 (54%) turtles had radiographic abnormalities of the lungs. Unilateral abnormalities of the right or left lung were detected in 14 (16%) and 2 (2%), respectively; both lungs were affected in 32 (36%). Prevalence of unilateral abnormalities was significantly greater for the right lung than for the left lung. Evaluation of follow-up radiographs indicated clinical improvement over time for most (18/31 [58%]) turtles. Prevalence of bilateral radiographic abnormalities was positively correlated with body weight and carapace length. There was no significant association between radiographic category and hematologic or plasma biochemical variables. Radiographic abnormalities of the lungs were commonly detected in cold-stunned Kemp's ridley turtles. Results of this study may aid clinicians in developing effective diagnostic and treatment plans for these patients.

  7. Evaluation of force-sensing resistors for gait event detection to trigger electrical stimulation to improve walking in the child with cerebral palsy.

    PubMed

    Smith, Brian T; Coiro, Daniel J; Finson, Richard; Betz, Randal R; McCarthy, James

    2002-03-01

    Force-sensing resistors (FSRs) were used to detect the transitions between five main phases of gait for the control of electrical stimulation (ES) while walking with seven children with spastic diplegia, cerebral palsy. The FSR positions within each child's insoles were customized based on plantar pressure profiles determined using a pressure-sensitive membrane array (Tekscan Inc., Boston, MA). The FSRs were placed in the insoles so that pressure transitions coincided with an ipsilateral or contralateral gait event. The transitions between the following gait phases were determined: loading response, mid- and terminal stance, and pre- and initial swing. Following several months of walking on a regular basis with FSR-triggered intramuscular ES to the hip and knee extensors, hip abductors, and ankle dorsi and plantar flexors, the accuracy and reliability of the FSRs to detect gait phase transitions were evaluated. Accuracy was evaluated with four of the subjects by synchronizing the output of the FSR detection scheme with a VICON (Oxford Metrics, U.K.) motion analysis system, which was used as the gait event reference. While mean differences between each FSR-detected gait event and that of the standard (VICON) ranged from +35 ms (indicating that the FSR detection scheme recognized the event before it actually happened) to -55 ms (indicating that the FSR scheme recognized the event after it occurred), the difference data was widely distributed, which appeared to be due in part to both intrasubject (step-to-step) and intersubject variability. Terminal stance exhibited the largest mean difference and standard deviation, while initial swing exhibited the smallest deviation and preswing the smallest mean difference. To determine step-to-step reliability, all seven children walked on a level walkway for at least 50 steps. Of 642 steps, there were no detection errors in 94.5% of the steps. Of the steps that contained a detection error, 80% were due to the failure of the FSR

  8. The onset and evolution of fatigue-induced abnormal grain growth in nanocrystalline Ni–Fe

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

    Furnish, T. A.; Mehta, A.; Van Campen, D.

    Conventional structural metals suffer from fatigue-crack initiation through dislocation activity which forms persistent slip bands leading to notch-like extrusions and intrusions. Ultrafine-grained and nanocrystalline metals can potentially exhibit superior fatigue-crack initiation resistance by suppressing these cumulative dislocation activities. Prior studies on these metals have confirmed improved high-cycle fatigue performance. In the case of nano-grained metals, analyses of subsurface crack initiation sites have indicated that the crack nucleation is associated with abnormally large grains. But, these post-mortem analyses have led to only speculation about when abnormal grain growth occurs (e.g., during fatigue, after crack initiation, or during crack growth). In thismore » study, a recently developed synchrotron X-ray diffraction technique was used to detect the onset and progression of abnormal grain growth during stress-controlled fatigue loading. Our study provides the first direct evidence that the grain coarsening is cyclically induced and occurs well before final fatigue failure—our results indicate that the first half of the fatigue life was spent prior to the detectable onset of abnormal grain growth, while the second half was spent coarsening the nanocrystalline structure and cyclically deforming the abnormally large grains until crack initiation. Post-mortem fractography, coupled with cycle-dependent diffraction data, provides the first details regarding the kinetics of this abnormal grain growth process during high-cycle fatigue testing. Finally, precession electron diffraction images collected in a transmission electron microscope after the in situ fatigue experiment also confirm the X-ray evidence that the abnormally large grains contain substantial misorientation gradients and sub-grain boundaries.« less

  9. The onset and evolution of fatigue-induced abnormal grain growth in nanocrystalline Ni–Fe

    DOE PAGES

    Furnish, T. A.; Mehta, A.; Van Campen, D.; ...

    2016-10-11

    Conventional structural metals suffer from fatigue-crack initiation through dislocation activity which forms persistent slip bands leading to notch-like extrusions and intrusions. Ultrafine-grained and nanocrystalline metals can potentially exhibit superior fatigue-crack initiation resistance by suppressing these cumulative dislocation activities. Prior studies on these metals have confirmed improved high-cycle fatigue performance. In the case of nano-grained metals, analyses of subsurface crack initiation sites have indicated that the crack nucleation is associated with abnormally large grains. But, these post-mortem analyses have led to only speculation about when abnormal grain growth occurs (e.g., during fatigue, after crack initiation, or during crack growth). In thismore » study, a recently developed synchrotron X-ray diffraction technique was used to detect the onset and progression of abnormal grain growth during stress-controlled fatigue loading. Our study provides the first direct evidence that the grain coarsening is cyclically induced and occurs well before final fatigue failure—our results indicate that the first half of the fatigue life was spent prior to the detectable onset of abnormal grain growth, while the second half was spent coarsening the nanocrystalline structure and cyclically deforming the abnormally large grains until crack initiation. Post-mortem fractography, coupled with cycle-dependent diffraction data, provides the first details regarding the kinetics of this abnormal grain growth process during high-cycle fatigue testing. Finally, precession electron diffraction images collected in a transmission electron microscope after the in situ fatigue experiment also confirm the X-ray evidence that the abnormally large grains contain substantial misorientation gradients and sub-grain boundaries.« less

  10. A habituation based approach for detection of visual changes in surveillance camera

    NASA Astrophysics Data System (ADS)

    Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

    2017-09-01

    This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

  11. Risk of newly detected infections and cervical abnormalities in women seropositive for naturally acquired human papillomavirus type 16/18 antibodies: analysis of the control arm of PATRICIA.

    PubMed

    Castellsagué, Xavier; Naud, Paulo; Chow, Song-Nan; Wheeler, Cosette M; Germar, Maria Julieta V; Lehtinen, Matti; Paavonen, Jorma; Jaisamrarn, Unnop; Garland, Suzanne M; Salmerón, Jorge; Apter, Dan; Kitchener, Henry; Teixeira, Julio C; Skinner, S Rachel; Limson, Genara; Szarewski, Anne; Romanowski, Barbara; Aoki, Fred Y; Schwarz, Tino F; Poppe, Willy A J; Bosch, F Xavier; de Carvalho, Newton S; Peters, Klaus; Tjalma, Wiebren A A; Safaeian, Mahboobeh; Raillard, Alice; Descamps, Dominique; Struyf, Frank; Dubin, Gary; Rosillon, Dominique; Baril, Laurence

    2014-08-15

    We examined risk of newly detected human papillomavirus (HPV) infection and cervical abnormalities in relation to HPV type 16/18 antibody levels at enrollment in PATRICIA (Papilloma Trial Against Cancer in Young Adults; NCT00122681). Using Poisson regression, we compared risk of newly detected infection and cervical abnormalities associated with HPV-16/18 between seronegative vs seropositive women (15-25 years) in the control arm (DNA negative at baseline for the corresponding HPV type [HPV-16: n = 8193; HPV-18: n = 8463]). High titers of naturally acquired HPV-16 antibodies and/or linear trend for increasing antibody levels were significantly associated with lower risk of incident and persistent infection, atypical squamous cells of undetermined significance or greater (ASCUS+), and cervical intraepithelial neoplasia grades 1/2 or greater (CIN1+, CIN2+). For HPV-18, although seropositivity was associated with lower risk of ASCUS+ and CIN1+, no association between naturally acquired antibodies and infection was demonstrated. Naturally acquired HPV-16 antibody levels of 371 (95% confidence interval [CI], 242-794), 204 (95% CI, 129-480), and 480 (95% CI, 250-5756) EU/mL were associated with 90% reduction of incident infection, 6-month persistent infection, and ASCUS+, respectively. Naturally acquired antibodies to HPV-16, and to a lesser extent HPV-18, are associated with some reduced risk of subsequent infection and cervical abnormalities associated with the same HPV type. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

  12. Abnormal soluble CD40 ligand and C-reactive protein concentrations in hypertension: relationship to indices of angiogenesis.

    PubMed

    Patel, Jeetesh V; Lim, Hoong Sern; Nadar, Sunil; Tayebjee, Muzahir; Hughes, Elizabeth A; Lip, Gregory Yh

    2006-01-01

    Abnormal inflammation, platelets and angiogenesis are involved in the pathophysiology of cardiovascular disease (CVD). To test the hypothesis that concentrations of high sensitive C-reactive protein (CRP, an index of inflammation) and soluble CD40 ligand (sCD40L, an index of platelet activation) would be abnormal in hypertension, and in turn, be related to plasma indices of angiogenesis, the angiopoietins-1 and -2, and vascular endothelial growth factor (VEGF), in addition to the presence or absence of CVD. Using a cross-sectional approach, we measured plasma concentrations of CRP, sCD40L, VEGF, and angiopoietins-1 and -2 in 147 patients with hypertension (85 with a history of CVD event/s, 62 CVD event-free) and 68 age- and sex-matched healthy controls. Concentrations of sCD40L (P = 0.039), CRP (P < 0.001), angiopoietin-1 (P < 0.001), angiopoietin-2 (P = 0.003) and VEGF (P < 0.001) were all greater amongst hypertensive patients than in controls. There were no significant differences in sCD40L and VEGF concentrations between hypertensive individuals with and without CVD events, but CRP and angiopoietin-1 concentrations were significantly greater amongst those with CVD events. On multiple regression analysis, sCD40L was associated with angiopoietin-2 (P = 0.01) and VEGF (P = 0.007) in hypertensive individuals, but no such associations were found within the healthy control group. In patients with hypertension, sCD40L was associated with increased circulating markers of abnormal angiogenesis (angiopoietin-2, VEGF). The interaction between sCD40L and angiogenesis may contribute to the pathophysiology of CVD in hypertension.

  13. Abnormal Uterine Bleeding FAQ

    MedlinePlus

    ... Abnormal Uterine Bleeding • What is a normal menstrual cycle? • When is bleeding abnormal? • At what ages is ... abnormal bleeding? •Glossary What is a normal menstrual cycle? The normal length of the menstrual cycle is ...

  14. Standardization of infrared breast thermogram acquisition protocols and abnormality analysis of breast thermograms

    NASA Astrophysics Data System (ADS)

    Bhowmik, Mrinal Kanti; Gogoi, Usha Rani; Das, Kakali; Ghosh, Anjan Kumar; Bhattacharjee, Debotosh; Majumdar, Gautam

    2016-05-01

    The non-invasive, painless, radiation-free and cost-effective infrared breast thermography (IBT) makes a significant contribution to improving the survival rate of breast cancer patients by early detecting the disease. This paper presents a set of standard breast thermogram acquisition protocols to improve the potentiality and accuracy of infrared breast thermograms in early breast cancer detection. By maintaining all these protocols, an infrared breast thermogram acquisition setup has been established at the Regional Cancer Centre (RCC) of Government Medical College (AGMC), Tripura, India. The acquisition of breast thermogram is followed by the breast thermogram interpretation, for identifying the presence of any abnormality. However, due to the presence of complex vascular patterns, accurate interpretation of breast thermogram is a very challenging task. The bilateral symmetry of the thermal patterns in each breast thermogram is quantitatively computed by statistical feature analysis. A series of statistical features are extracted from a set of 20 thermograms of both healthy and unhealthy subjects. Finally, the extracted features are analyzed for breast abnormality detection. The key contributions made by this paper can be highlighted as -- a) the designing of a standard protocol suite for accurate acquisition of breast thermograms, b) creation of a new breast thermogram dataset by maintaining the protocol suite, and c) statistical analysis of the thermograms for abnormality detection. By doing so, this proposed work can minimize the rate of false findings in breast thermograms and thus, it will increase the utilization potentiality of breast thermograms in early breast cancer detection.

  15. Using State Estimation Residuals to Detect Abnormal SCADA Data

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

    Ma, Jian; Chen, Yousu; Huang, Zhenyu

    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 asmore » 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.« less

  16. The Automatic Recognition of the Abnormal Sky-subtraction Spectra Based on Hadoop

    NASA Astrophysics Data System (ADS)

    An, An; Pan, Jingchang

    2017-10-01

    The skylines, superimposing on the target spectrum as a main noise, If the spectrum still contains a large number of high strength skylight residuals after sky-subtraction processing, it will not be conducive to the follow-up analysis of the target spectrum. At the same time, the LAMOST can observe a quantity of spectroscopic data in every night. We need an efficient platform to proceed the recognition of the larger numbers of abnormal sky-subtraction spectra quickly. Hadoop, as a distributed parallel data computing platform, can deal with large amounts of data effectively. In this paper, we conduct the continuum normalization firstly and then a simple and effective method will be presented to automatic recognize the abnormal sky-subtraction spectra based on Hadoop platform. Obtain through the experiment, the Hadoop platform can implement the recognition with more speed and efficiency, and the simple method can recognize the abnormal sky-subtraction spectra and find the abnormal skyline positions of different residual strength effectively, can be applied to the automatic detection of abnormal sky-subtraction of large number of spectra.

  17. Anterior ocular abnormalities of captive Asian elephants (Elephas maximus indicus) in Thailand.

    PubMed

    Kraiwong, Natapong; Sanyathitiseree, Pornchai; Boonprasert, Khajohnpat; Diskul, Phiphatanachatr; Charoenphan, Patara; Pintawong, Weerasak; Thayananuphat, Aree

    2016-07-01

    To survey and classify anterior ocular abnormalities in 1478 captive Asian elephants (Elephas maximus indicus) in six regions of Thailand. Anterior ocular examination was performed in both eyes (n = 2956) of 1478 elephants selected from the annual health check program involving 2958 animals within six regions of Thailand from January to November 2013. Lesions were described and compared between age and gender. A total of 17.83% (527/2956) of examined eyes from 24.97% (369/1478) of examined elephants had anterior ocular abnormalities. The most common lesions in these examined eyes were frothy ocular discharge (5.85%), corneal edema (5.31%), and conjunctivitis (5.18%). In addition, epiphora, phthisis bulbi, other corneal abnormalities, anterior uveitis, and lens abnormalities were noted. Almost all lesions increased in frequency with age (P < 0.01). Regular ophthalmic examination in elephants should be included in their annual health check program. Early detection and treatment of any ocular abnormality may avoid the development of subsequent irreversible ocular pathology. © 2015 American College of Veterinary Ophthalmologists.

  18. Risk Factors for Abnormal Anal Cytology over Time in HIV-infected Women

    PubMed Central

    BARANOSKI, Amy S; TANDON, Richa; WEINBERG, Janice; HUANG, Faye; STIER, Elizabeth A

    2012-01-01

    Objectives To assess incidence of, and risk factors for abnormal anal cytology and anal intraepithelial neoplasia (AIN) 2–3 in HIV-infected women. Study Design This prospective study assessed 100 HIV-infected women with anal and cervical specimens for cytology and high risk HPV testing over three semi-annual visits. Results Thirty-three women were diagnosed with an anal cytologic abnormality at least once. Anal cytology abnormality was associated with current CD4 count <200 cells/mm3, anal HPV infection and history of other sexually transmitted infections (STIs). Twelve subjects were diagnosed with AIN2-3: four after AIN1 diagnosis and four after ≥1 negative anal cytology. AIN2-3 trended towards an association with history of cervical cytologic abnormality and history of STI. Conclusions Repeated annual anal cytology screening for HIV-infected women, particularly for those with increased immunosuppression, anal and/or cervical HPV, history of other STIs, or abnormal cervical cytology, will increase the likelihood of detecting AIN2-3. PMID:22520651

  19. Urine - abnormal color

    MedlinePlus

    ... medlineplus.gov/ency/article/003139.htm Urine - abnormal color To use the sharing features on this page, please enable JavaScript. The usual color of urine is straw-yellow. Abnormally colored urine ...

  20. 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