Developing a disease outbreak event corpus.

PubMed

Conway, Mike; Kawazoe, Ai; Chanlekha, Hutchatai; Collier, Nigel

2010-09-28

In recent years, there has been a growth in work on the use of information extraction technologies for tracking disease outbreaks from online news texts, yet publicly available evaluation standards (and associated resources) for this new area of research have been noticeably lacking. This study seeks to create a "gold standard" data set against which to test how accurately disease outbreak information extraction systems can identify the semantics of disease outbreak events. Additionally, we hope that the provision of an annotation scheme (and associated corpus) to the community will encourage open evaluation in this new and growing application area. We developed an annotation scheme for identifying infectious disease outbreak events in news texts. An event--in the context of our annotation scheme--consists minimally of geographical (eg, country and province) and disease name information. However, the scheme also allows for the rich encoding of other domain salient concepts (eg, international travel, species, and food contamination). The work resulted in a 200-document corpus of event-annotated disease outbreak reports that can be used to evaluate the accuracy of event detection algorithms (in this case, for the BioCaster biosurveillance online news information extraction system). In the 200 documents, 394 distinct events were identified (mean 1.97 events per document, range 0-25 events per document). We also provide a download script and graphical user interface (GUI)-based event browsing software to facilitate corpus exploration. In summary, we present an annotation scheme and corpus that can be used in the evaluation of disease outbreak event extraction algorithms. The annotation scheme and corpus were designed both with the particular evaluation requirements of the BioCaster system in mind as well as the wider need for further evaluation resources in this growing research area.

Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

PubMed

Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

2018-01-01

Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

Analysis of signal transduction in cell-free extracts and rafts of Xenopus eggs.

PubMed

Tokmakov, Alexander A; Iwasaki, Tetsushi; Sato, Ken-Ichi; Fukami, Yasuo

2010-05-01

Intracellular signaling during egg activation/fertilization has been extensively studied using intact eggs, which can be manipulated by microinjection of different mRNAs, proteins, or chemical drugs. Furthermore, egg extracts, which retain high CSF activity (CSF-arrested extracts), were developed for studying fertilization/activation signal transduction, which have significant advantages as a model system. The addition of calcium to CSF-arrested extracts initiates a plethora of signaling events that take place during egg activation. Hence, the signaling downstream of calcium mobilization has been successfully studied in the egg extracts. Moreover, despite disruption of membrane-associated signaling compartments and ordered compartmentalization during extract preparation, CSF-arrested extracts can be successfully used to study early signaling events, which occur upstream of calcium release during egg activation/fertilization. In combination with the CSF-arrested extracts, activated egg rafts can reproduce some events of egg activation, including PLCgamma activation, IP3 production, transient calcium release, MAPK inactivation, and meiotic exit. This becomes possible due to complementation of the sperm-induced egg activation signaling machinery present in the rafts with the components of signal transduction system localized in the extracts. Herein, we describe protocols for studying molecular mechanisms of egg fertilization/activation using cell-free extracts and membrane rafts prepared from metaphase-arrested Xenopus eggs.

Automatic signal extraction, prioritizing and filtering approaches in detecting post-marketing cardiovascular events associated with targeted cancer drugs from the FDA Adverse Event Reporting System (FAERS).

PubMed

Xu, Rong; Wang, Quanqiu

2014-02-01

Targeted drugs dramatically improve the treatment outcomes in cancer patients; however, these innovative drugs are often associated with unexpectedly high cardiovascular toxicity. Currently, cardiovascular safety represents both a challenging issue for drug developers, regulators, researchers, and clinicians and a concern for patients. While FDA drug labels have captured many of these events, spontaneous reporting systems are a main source for post-marketing drug safety surveillance in 'real-world' (outside of clinical trials) cancer patients. In this study, we present approaches to extracting, prioritizing, filtering, and confirming cardiovascular events associated with targeted cancer drugs from the FDA Adverse Event Reporting System (FAERS). The dataset includes records of 4,285,097 patients from FAERS. We first extracted drug-cardiovascular event (drug-CV) pairs from FAERS through named entity recognition and mapping processes. We then compared six ranking algorithms in prioritizing true positive signals among extracted pairs using known drug-CV pairs derived from FDA drug labels. We also developed three filtering algorithms to further improve precision. Finally, we manually validated extracted drug-CV pairs using 21 million published MEDLINE records. We extracted a total of 11,173 drug-CV pairs from FAERS. We showed that ranking by frequency is significantly more effective than by the five standard signal detection methods (246% improvement in precision for top-ranked pairs). The filtering algorithm we developed further improved overall precision by 91.3%. By manual curation using literature evidence, we show that about 51.9% of the 617 drug-CV pairs that appeared in both FAERS and MEDLINE sentences are true positives. In addition, 80.6% of these positive pairs have not been captured by FDA drug labeling. The unique drug-CV association dataset that we created based on FAERS could facilitate our understanding and prediction of cardiotoxic events associated with targeted cancer drugs. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Masquerade Detection Using a Taxonomy-Based Multinomial Modeling Approach in UNIX Systems

DTIC Science & Technology

2008-08-25

primarily the modeling of statistical features , such as the frequency of events, the duration of events, the co- occurrence of multiple events...are identified, we can extract features representing such behavior while auditing the user’s behavior. Figure1: Taxonomy of Linux and Unix...achieved when the features are extracted just from simple commands. Method Hit Rate False Positive Rate ocSVM using simple cmds (freq.-based

Features extraction algorithm about typical railway perimeter intrusion event

NASA Astrophysics Data System (ADS)

Zhou, Jieyun; Wang, Chaodong; Liu, Lihai

2017-10-01

Research purposes: Optical fiber vibration sensing system has been widely used in the oil, gas, frontier defence, prison and power industries. But, there are few reports about the application in railway defence. That is because the surrounding environment is complicated and there are many challenges to be overcomed in the optical fiber vibration sensing system application. For example, how to eliminate the effects of vibration caused by train, the natural environments such as wind and rain and how to identify and classify the intrusion events. In order to solve these problems, the feature signals of these events should be extracted firstly. Research conclusions: (1) In optical fiber vibration sensing system based on Sagnac interferometer, the peak-to-peak value, peak-to-average ratio, standard deviation, zero-crossing rate, short-term energy and kurtosis may serve as feature signals. (2) The feature signals of resting state, climbing concrete fence, breaking barbed wire, knocking concrete fence and rainstorm have been extracted, which shows significant difference among each other. (3) The research conclusions can be used in the identification and classification of intrusion events.

Vaccine adverse event text mining system for extracting features from vaccine safety reports.

PubMed

Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

2012-01-01

To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

Information extraction from Italian medical reports: An ontology-driven approach.

PubMed

Viani, Natalia; Larizza, Cristiana; Tibollo, Valentina; Napolitano, Carlo; Priori, Silvia G; Bellazzi, Riccardo; Sacchi, Lucia

2018-03-01

In this work, we propose an ontology-driven approach to identify events and their attributes from episodes of care included in medical reports written in Italian. For this language, shared resources for clinical information extraction are not easily accessible. The corpus considered in this work includes 5432 non-annotated medical reports belonging to patients with rare arrhythmias. To guide the information extraction process, we built a domain-specific ontology that includes the events and the attributes to be extracted, with related regular expressions. The ontology and the annotation system were constructed on a development set, while the performance was evaluated on an independent test set. As a gold standard, we considered a manually curated hospital database named TRIAD, which stores most of the information written in reports. The proposed approach performs well on the considered Italian medical corpus, with a percentage of correct annotations above 90% for most considered clinical events. We also assessed the possibility to adapt the system to the analysis of another language (i.e., English), with promising results. Our annotation system relies on a domain ontology to extract and link information in clinical text. We developed an ontology that can be easily enriched and translated, and the system performs well on the considered task. In the future, it could be successfully used to automatically populate the TRIAD database. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Compressive Information Extraction: A Dynamical Systems Approach

DTIC Science & Technology

2016-01-24

sparsely encoded in very large data streams. (a) Target tracking in an urban canyon; (b) and (c) sample frames showing contextually abnormal events: onset...extraction to identify contextually abnormal se- quences (see section 2.2.3). Formally, the problem of interest can be stated as establishing whether a noisy...relaxations with optimality guarantees can be obtained using tools from semi-algebraic geometry. 2.2 Application: Detecting Contextually Abnormal Events

Can Natural Language Processing Improve the Efficiency of Vaccine Adverse Event Report Review?

PubMed

Baer, B; Nguyen, M; Woo, E J; Winiecki, S; Scott, J; Martin, D; Botsis, T; Ball, R

2016-01-01

Individual case review of spontaneous adverse event (AE) reports remains a cornerstone of medical product safety surveillance for industry and regulators. Previously we developed the Vaccine Adverse Event Text Miner (VaeTM) to offer automated information extraction and potentially accelerate the evaluation of large volumes of unstructured data and facilitate signal detection. To assess how the information extraction performed by VaeTM impacts the accuracy of a medical expert's review of the vaccine adverse event report. The "outcome of interest" (diagnosis, cause of death, second level diagnosis), "onset time," and "alternative explanations" (drug, medical and family history) for the adverse event were extracted from 1000 reports from the Vaccine Adverse Event Reporting System (VAERS) using the VaeTM system. We compared the human interpretation, by medical experts, of the VaeTM extracted data with their interpretation of the traditional full text reports for these three variables. Two experienced clinicians alternately reviewed text miner output and full text. A third clinician scored the match rate using a predefined algorithm; the proportion of matches and 95% confidence intervals (CI) were calculated. Review time per report was analyzed. Proportion of matches between the interpretation of the VaeTM extracted data, compared to the interpretation of the full text: 93% for outcome of interest (95% CI: 91-94%) and 78% for alternative explanation (95% CI: 75-81%). Extracted data on the time to onset was used in 14% of cases and was a match in 54% (95% CI: 46-63%) of those cases. When supported by structured time data from reports, the match for time to onset was 79% (95% CI: 76-81%). The extracted text averaged 136 (74%) fewer words, resulting in a mean reduction in review time of 50 (58%) seconds per report. Despite a 74% reduction in words, the clinical conclusion from VaeTM extracted data agreed with the full text in 93% and 78% of reports for the outcome of interest and alternative explanation, respectively. The limited amount of extracted time interval data indicates the need for further development of this feature. VaeTM may improve review efficiency, but further study is needed to determine if this level of agreement is sufficient for routine use.

HIGH-PRECISION BIOLOGICAL EVENT EXTRACTION: EFFECTS OF SYSTEM AND OF DATA

PubMed Central

Cohen, K. Bretonnel; Verspoor, Karin; Johnson, Helen L.; Roeder, Chris; Ogren, Philip V.; Baumgartner, William A.; White, Elizabeth; Tipney, Hannah; Hunter, Lawrence

2013-01-01

We approached the problems of event detection, argument identification, and negation and speculation detection in the BioNLP’09 information extraction challenge through concept recognition and analysis. Our methodology involved using the OpenDMAP semantic parser with manually written rules. The original OpenDMAP system was updated for this challenge with a broad ontology defined for the events of interest, new linguistic patterns for those events, and specialized coordination handling. We achieved state-of-the-art precision for two of the three tasks, scoring the highest of 24 teams at precision of 71.81 on Task 1 and the highest of 6 teams at precision of 70.97 on Task 2. We provide a detailed analysis of the training data and show that a number of trigger words were ambiguous as to event type, even when their arguments are constrained by semantic class. The data is also shown to have a number of missing annotations. Analysis of a sampling of the comparatively small number of false positives returned by our system shows that major causes of this type of error were failing to recognize second themes in two-theme events, failing to recognize events when they were the arguments to other events, failure to recognize nontheme arguments, and sentence segmentation errors. We show that specifically handling coordination had a small but important impact on the overall performance of the system. The OpenDMAP system and the rule set are available at http://bionlp.sourceforge.net. PMID:25937701

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 coverage in terms of languages and geographic areas. In contrast, in order to detect epidemic events in any language, the Daniel system only requires a list of a few hundreds of disease names and locations, which can actually be acquired automatically. The system can perform consistently well on any language, with precision and recall around 82% on average, according to this paper's evaluation. Daniel's character-based approach is especially interesting for morphologically-rich and low-resourced languages. The lack of resources to be exploited and the state of the art string matching algorithms imply that Daniel can process thousands of documents per minute on a simple laptop. In the context of epidemic surveillance, reactivity and geographic coverage are of primary importance, since no one knows where the next event will strike, and therefore in what vernacular language it will first be reported. By being able to process any language, the Daniel system offers unique coverage for poorly endowed languages, and can complete state of the art techniques for major languages. Copyright © 2015 Elsevier B.V. All rights reserved.

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

PubMed Central

Lee, Gil-beom; Lee, Myeong-jin; Lee, Woo-Kyung; Park, Joo-heon; Kim, Tae-Hwan

2017-01-01

Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos. PMID:28327515

An energy ratio feature extraction method for optical fiber vibration signal

NASA Astrophysics Data System (ADS)

Sheng, Zhiyong; Zhang, Xinyan; Wang, Yanping; Hou, Weiming; Yang, Dan

2018-03-01

The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011.

PubMed

Pyysalo, Sampo; Ohta, Tomoko; Rak, Rafal; Sullivan, Dan; Mao, Chunhong; Wang, Chunxia; Sobral, Bruno; Tsujii, Jun'ichi; Ananiadou, Sophia

2012-06-26

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties.

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011

PubMed Central

2012-01-01

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties. PMID:22759456

Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis

PubMed Central

2015-01-01

Background Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on extending this context to the information automatically gathered from the whole biomedical literature. Thus, our motivation for this study is to explore whether mutually supporting evidence, aggregated across several documents can be utilized to improve the performance of the state-of-the-art event extraction systems. In this paper, we describe our participation in the latest BioNLP Shared Task using the large-scale text mining resource EVEX. We participated in the Genia Event Extraction (GE) and Gene Regulation Network (GRN) tasks with two separate systems. In the GE task, we implemented a re-ranking approach to improve the precision of an existing event extraction system, incorporating features from the EVEX resource. In the GRN task, our system relied solely on the EVEX resource and utilized a rule-based conversion algorithm between the EVEX and GRN formats. Results In the GE task, our re-ranking approach led to a modest performance increase and resulted in the first rank of the official Shared Task results with 50.97% F-score. Additionally, in this paper we explore and evaluate the usage of distributed vector representations for this challenge. In the GRN task, we ranked fifth in the official results with a strict/relaxed SER score of 0.92/0.81 respectively. To try and improve upon these results, we have implemented a novel machine learning based conversion system and benchmarked its performance against the original rule-based system. Conclusions For the GRN task, we were able to produce a gene regulatory network from the EVEX data, warranting the use of such generic large-scale text mining data in network biology settings. A detailed performance and error analysis provides more insight into the relatively low recall rates. In the GE task we demonstrate that both the re-ranking approach and the word vectors can provide slight performance improvement. A manual evaluation of the re-ranking results pinpoints some of the challenges faced in applying large-scale text mining knowledge to event extraction. PMID:26551766

Overview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013

PubMed Central

2015-01-01

Background Since their introduction in 2009, the BioNLP Shared Task events have been instrumental in advancing the development of methods and resources for the automatic extraction of information from the biomedical literature. In this paper, we present the Cancer Genetics (CG) and Pathway Curation (PC) tasks, two event extraction tasks introduced in the BioNLP Shared Task 2013. The CG task focuses on cancer, emphasizing the extraction of physiological and pathological processes at various levels of biological organization, and the PC task targets reactions relevant to the development of biomolecular pathway models, defining its extraction targets on the basis of established pathway representations and ontologies. Results Six groups participated in the CG task and two groups in the PC task, together applying a wide range of extraction approaches including both established state-of-the-art systems and newly introduced extraction methods. The best-performing systems achieved F-scores of 55% on the CG task and 53% on the PC task, demonstrating a level of performance comparable to the best results achieved in similar previously proposed tasks. Conclusions The results indicate that existing event extraction technology can generalize to meet the novel challenges represented by the CG and PC task settings, suggesting that extraction methods are capable of supporting the construction of knowledge bases on the molecular mechanisms of cancer and the curation of biomolecular pathway models. The CG and PC tasks continue as open challenges for all interested parties, with data, tools and resources available from the shared task homepage. PMID:26202570

Information extraction for enhanced access to disease outbreak reports.

PubMed

Grishman, Ralph; Huttunen, Silja; Yangarber, Roman

2002-08-01

Document search is generally based on individual terms in the document. However, for collections within limited domains it is possible to provide more powerful access tools. This paper describes a system designed for collections of reports of infectious disease outbreaks. The system, Proteus-BIO, automatically creates a table of outbreaks, with each table entry linked to the document describing that outbreak; this makes it possible to use database operations such as selection and sorting to find relevant documents. Proteus-BIO consists of a Web crawler which gathers relevant documents; an information extraction engine which converts the individual outbreak events to a tabular database; and a database browser which provides access to the events and, through them, to the documents. The information extraction engine uses sets of patterns and word classes to extract the information about each event. Preparing these patterns and word classes has been a time-consuming manual operation in the past, but automated discovery tools now make this task significantly easier. A small study comparing the effectiveness of the tabular index with conventional Web search tools demonstrated that users can find substantially more documents in a given time period with Proteus-BIO.

Interlaboratory study of DNA extraction from multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for individual kernel detection system of genetically modified maize.

PubMed

Akiyama, Hiroshi; Sakata, Kozue; Makiyma, Daiki; Nakamura, Kosuke; Teshima, Reiko; Nakashima, Akie; Ogawa, Asako; Yamagishi, Toru; Futo, Satoshi; Oguchi, Taichi; Mano, Junichi; Kitta, Kazumi

2011-01-01

In many countries, the labeling of grains, feed, and foodstuff is mandatory if the genetically modified (GM) organism content exceeds a certain level of approved GM varieties. We previously developed an individual kernel detection system consisting of grinding individual kernels, DNA extraction from the individually ground kernels, GM detection using multiplex real-time PCR, and GM event detection using multiplex qualitative PCR to analyze the precise commingling level and varieties of GM maize in real sample grains. We performed the interlaboratory study of the DNA extraction with multiple ground samples, multiplex real-time PCR detection, and multiplex qualitative PCR detection to evaluate its applicability, practicality, and ruggedness for the individual kernel detection system of GM maize. DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR were evaluated by five laboratories in Japan, and all results from these laboratories were consistent with the expected results in terms of the commingling level and event analysis. Thus, the DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for the individual kernel detection system is applicable and practicable in a laboratory to regulate the commingling level of GM maize grain for GM samples, including stacked GM maize.

Accuracy-energy configurable sensor processor and IoT device for long-term activity monitoring in rare-event sensing applications.

PubMed

Park, Daejin; Cho, Jeonghun

2014-01-01

A specially designed sensor processor used as a main processor in IoT (internet-of-thing) device for the rare-event sensing applications is proposed. The IoT device including the proposed sensor processor performs the event-driven sensor data processing based on an accuracy-energy configurable event-quantization in architectural level. The received sensor signal is converted into a sequence of atomic events, which is extracted by the signal-to-atomic-event generator (AEG). Using an event signal processing unit (EPU) as an accelerator, the extracted atomic events are analyzed to build the final event. Instead of the sampled raw data transmission via internet, the proposed method delays the communication with a host system until a semantic pattern of the signal is identified as a final event. The proposed processor is implemented on a single chip, which is tightly coupled in bus connection level with a microcontroller using a 0.18 μm CMOS embedded-flash process. For experimental results, we evaluated the proposed sensor processor by using an IR- (infrared radio-) based signal reflection and sensor signal acquisition system. We successfully demonstrated that the expected power consumption is in the range of 20% to 50% compared to the result of the basement in case of allowing 10% accuracy error.

Making adjustments to event annotations for improved biological event extraction.

PubMed

Baek, Seung-Cheol; Park, Jong C

2016-09-16

Current state-of-the-art approaches to biological event extraction train statistical models in a supervised manner on corpora annotated with event triggers and event-argument relations. Inspecting such corpora, we observe that there is ambiguity in the span of event triggers (e.g., "transcriptional activity" vs. 'transcriptional'), leading to inconsistencies across event trigger annotations. Such inconsistencies make it quite likely that similar phrases are annotated with different spans of event triggers, suggesting the possibility that a statistical learning algorithm misses an opportunity for generalizing from such event triggers. We anticipate that adjustments to the span of event triggers to reduce these inconsistencies would meaningfully improve the present performance of event extraction systems. In this study, we look into this possibility with the corpora provided by the 2009 BioNLP shared task as a proof of concept. We propose an Informed Expectation-Maximization (EM) algorithm, which trains models using the EM algorithm with a posterior regularization technique, which consults the gold-standard event trigger annotations in a form of constraints. We further propose four constraints on the possible event trigger annotations to be explored by the EM algorithm. The algorithm is shown to outperform the state-of-the-art algorithm on the development corpus in a statistically significant manner and on the test corpus by a narrow margin. The analysis of the annotations generated by the algorithm shows that there are various types of ambiguity in event annotations, even though they could be small in number.

A generalizable NLP framework for fast development of pattern-based biomedical relation extraction systems.

PubMed

Peng, Yifan; Torii, Manabu; Wu, Cathy H; Vijay-Shanker, K

2014-08-23

Text mining is increasingly used in the biomedical domain because of its ability to automatically gather information from large amount of scientific articles. One important task in biomedical text mining is relation extraction, which aims to identify designated relations among biological entities reported in literature. A relation extraction system achieving high performance is expensive to develop because of the substantial time and effort required for its design and implementation. Here, we report a novel framework to facilitate the development of a pattern-based biomedical relation extraction system. It has several unique design features: (1) leveraging syntactic variations possible in a language and automatically generating extraction patterns in a systematic manner, (2) applying sentence simplification to improve the coverage of extraction patterns, and (3) identifying referential relations between a syntactic argument of a predicate and the actual target expected in the relation extraction task. A relation extraction system derived using the proposed framework achieved overall F-scores of 72.66% for the Simple events and 55.57% for the Binding events on the BioNLP-ST 2011 GE test set, comparing favorably with the top performing systems that participated in the BioNLP-ST 2011 GE task. We obtained similar results on the BioNLP-ST 2013 GE test set (80.07% and 60.58%, respectively). We conducted additional experiments on the training and development sets to provide a more detailed analysis of the system and its individual modules. This analysis indicates that without increasing the number of patterns, simplification and referential relation linking play a key role in the effective extraction of biomedical relations. In this paper, we present a novel framework for fast development of relation extraction systems. The framework requires only a list of triggers as input, and does not need information from an annotated corpus. Thus, we reduce the involvement of domain experts, who would otherwise have to provide manual annotations and help with the design of hand crafted patterns. We demonstrate how our framework is used to develop a system which achieves state-of-the-art performance on a public benchmark corpus.

Retro-Future

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

Ferrell, Paul; Hanson, Paige; Ardi, Calvin

2016-11-04

A system for processing network packet capture streams, extracting metadata and generating flow records (via Argus). The system can be used by network security operators and analysts to enable forensic investigations for network security events.

Thrombotic events associated with C1 esterase inhibitor products in patients with hereditary angioedema: investigation from the United States Food and Drug Administration adverse event reporting system database.

PubMed

Gandhi, Pranav K; Gentry, William M; Bottorff, Michael B

2012-10-01

To investigate reports of thrombotic events associated with the use of C1 esterase inhibitor products in patients with hereditary angioedema in the United States. Retrospective data mining analysis. The United States Food and Drug Administration (FDA) adverse event reporting system (AERS) database. Case reports of C1 esterase inhibitor products, thrombotic events, and C1 esterase inhibitor product-associated thrombotic events (i.e., combination cases) were extracted from the AERS database, using the time frames of each respective product's FDA approval date through the second quarter of 2011. Bayesian statistical methodology within the neural network architecture was implemented to identify potential signals of a drug-associated adverse event. A potential signal is generated when the lower limit of the 95% 2-sided confidence interval of the information component, denoted by IC₀₂₅ , is greater than zero. This suggests that the particular drug-associated adverse event was reported to the database more often than statistically expected from reports available in the database. Ten combination cases of thrombotic events associated with the use of one C1 esterase inhibitor product (Cinryze) were identified in patients with hereditary angioedema. A potential signal demonstrated by an IC₀₂₅ value greater than zero (IC₀₂₅ = 2.91) was generated for these combination cases. The extracted cases from the AERS indicate continuing reports of thrombotic events associated with the use of one C1 esterase inhibitor product among patients with hereditary angioedema. The AERS is incapable of establishing a causal link and detecting the true frequency of an adverse event associated with a drug; however, potential signals of C1 esterase inhibitor product-associated thrombotic events among patients with hereditary angioedema were identified in the extracted combination cases. © 2012 Pharmacotherapy Publications, Inc.

A systematic review of the safety of kava extract in the treatment of anxiety.

PubMed

Stevinson, Clare; Huntley, Alyson; Ernst, Edzard

2002-01-01

This paper systematically reviews the clinical evidence relating to the safety of extracts of the herbal anxiolytic kava (Piper methysticum). Literature searches were conducted in four electronic databases and the reference lists of all papers located were checked for further relevant publications. Information was also sought from the spontaneous reporting schemes of the WHO and national drug safety bodies and ten manufacturers of kava preparations were contacted. Data from short-term post-marketing surveillance studies and clinical trials suggest that adverse events are, in general, rare, mild and reversible. However, published case reports indicate that serious adverse events are possible including dermatological reactions, neurological complications and, of greatest concern, liver damage. Spontaneous reporting schemes also suggest that the most common adverse events are mild, but that serious ones occur. Controlled trials suggest that kava extracts do not impair cognitive performance and vigilance or potentiate the effects of central nervous system depressants. However, a possible interaction with benzodiazepines has been reported. It is concluded that when taken as a short-term monotherapy at recommended doses, kava extracts appear to be well tolerated by most users. Serious adverse events have been reported and further research is required to determine the nature and frequency of such events.

Accuracy-Energy Configurable Sensor Processor and IoT Device for Long-Term Activity Monitoring in Rare-Event Sensing Applications

PubMed Central

2014-01-01

A specially designed sensor processor used as a main processor in IoT (internet-of-thing) device for the rare-event sensing applications is proposed. The IoT device including the proposed sensor processor performs the event-driven sensor data processing based on an accuracy-energy configurable event-quantization in architectural level. The received sensor signal is converted into a sequence of atomic events, which is extracted by the signal-to-atomic-event generator (AEG). Using an event signal processing unit (EPU) as an accelerator, the extracted atomic events are analyzed to build the final event. Instead of the sampled raw data transmission via internet, the proposed method delays the communication with a host system until a semantic pattern of the signal is identified as a final event. The proposed processor is implemented on a single chip, which is tightly coupled in bus connection level with a microcontroller using a 0.18 μm CMOS embedded-flash process. For experimental results, we evaluated the proposed sensor processor by using an IR- (infrared radio-) based signal reflection and sensor signal acquisition system. We successfully demonstrated that the expected power consumption is in the range of 20% to 50% compared to the result of the basement in case of allowing 10% accuracy error. PMID:25580458

Use of Geophysical and Remote Sensing Data for Assessment of Aquifer Depletion and Related Land Deformation

NASA Astrophysics Data System (ADS)

Othman, Abdullah; Sultan, Mohamed; Becker, Richard; Alsefry, Saleh; Alharbi, Talal; Gebremichael, Esayas; Alharbi, Hassan; Abdelmohsen, Karem

2018-01-01

An integrated approach [field, Interferometric Synthetic Aperture Radar (InSAR), hydrogeology, geodesy, and spatial analysis] was adopted to identify the nature, intensity, and spatial distribution of deformational features (sinkholes, fissures, differential settling) reported over fossil aquifers in arid lands, their controlling factors, and possible remedies. The Lower Mega Aquifer System (area 2 × 106 km2) in central and northern Arabia was used as a test site. Findings suggest that excessive groundwater extraction from the fossil aquifer is the main cause of deformation: (1) deformational features correlated spatially and/or temporally with increased agricultural development and groundwater extraction, and with a decline in water levels and groundwater storage (- 3.7 ± 0.6 km3/year); (2) earthquake events (years 1985-2016; magnitude 1-5) are largely (65% of reported earthquakes) shallow (1-5 km) and increased from 1 event/year in the early 1980s (extraction 1 km3/year), up to 13 events/year in the 1990s (average annual extraction > 6.4 km3). Results indicate that faults played a role in localizing deformation given that deformational sites and InSAR-based high subsidence rates (- 4 to - 15 mm/year) were largely found within, but not outside of, NW-SE-trending grabens bound by the Kahf fault system. Findings from the analysis of Gravity Recovery and Climate Experiment solutions indicate that sustainable extraction could be attained if groundwater extraction was reduced by 3.5-4 km3/year. This study provides replicable and cost-effective methodologies for optimum utilization of fossil aquifers and for minimizing deformation associated with their use.

Analyzing depression tendency of web posts using an event-driven depression tendency warning model.

PubMed

Tung, Chiaming; Lu, Wenhsiang

2016-01-01

The Internet has become a platform to express individual moods/feelings of daily life, where authors share their thoughts in web blogs, micro-blogs, forums, bulletin board systems or other media. In this work, we investigate text-mining technology to analyze and predict the depression tendency of web posts. In this paper, we defined depression factors, which include negative events, negative emotions, symptoms, and negative thoughts from web posts. We proposed an enhanced event extraction (E3) method to automatically extract negative event terms. In addition, we also proposed an event-driven depression tendency warning (EDDTW) model to predict the depression tendency of web bloggers or post authors by analyzing their posted articles. We compare the performance among the proposed EDDTW model, negative emotion evaluation (NEE) model, and the diagnostic and statistical manual of mental disorders-based depression tendency evaluation method. The EDDTW model obtains the best recall rate and F-measure at 0.668 and 0.624, respectively, while the diagnostic and statistical manual of mental disorders-based method achieves the best precision rate of 0.666. The main reason is that our enhanced event extraction method can increase recall rate by enlarging the negative event lexicon at the expense of precision. Our EDDTW model can also be used to track the change or trend of depression tendency for each post author. The depression tendency trend can help doctors to diagnose and even track depression of web post authors more efficiently. This paper presents an E3 method to automatically extract negative event terms in web posts. We also proposed a new EDDTW model to predict the depression tendency of web posts and possibly help bloggers or post authors to early detect major depressive disorder. Copyright © 2015 Elsevier B.V. All rights reserved.

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

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

Stevens, Garrison Nicole; Van Buren, Kendra Lu; Hemez, Francois M.

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, andmore » finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where uncertainty is added to the system through noise in the measurements.« less

Synchronous inversion and charge extraction (SICE): a hybrid switching interface for efficient vibrational energy harvesting

NASA Astrophysics Data System (ADS)

Lallart, Mickaël; Wu, Wen-Jong; Hsieh, Yuchieh; Yan, Linjuan

2017-11-01

This paper aims at proposing an electrical interface taking advantage of nonlinear treatment for both significantly increasing the voltage of a piezoelectric device and extracting the corresponding electrostatic energy in an independent way from the connected electrical load. The principles of the proposed system lies in quickly inverting the piezoelectric voltage on each extremum (synchronized switch on inductor operations) for a given number of extremum occurrences, and then extracting the total electrostatic energy available on the piezoelectric element through the so-called synchronous electric charge extraction (SECE) for energy harvesting purpose. Compared to classical SECE approach, which consists in extracting the energy on each voltage extremum occurrence, the proposed scheme shows a significant improvement in low-coupled systems thanks to a fine control of the trade-off between voltage amplification and number of extraction events.

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.

Automatic optical detection and classification of marine animals around MHK converters using machine vision

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

Brunton, Steven

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robustmore » principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.« less

POM Pulses: Characterizing the Physical and Chemical Properties of Particulate Organic Matter (POM) Mobilized by Large Storm Events and its Influence on Receiving Fluvial Systems

NASA Astrophysics Data System (ADS)

Johnson, E. R.; Rowland, R. D.; Protokowicz, J.; Inamdar, S. P.; Kan, J.; Vargas, R.

2016-12-01

Extreme storm events have tremendous erosive energy which is capable of mobilizing vast amounts of material from watershed sources into fluvial systems. This complex mixture of sediment and particulate organic matter (POM) is a nutrient source, and has the potential to impact downstream water quality. The impact of POM on receiving aquatic systems can vary not only by the total amount exported but also by the various sources involved and the particle sizes of POM. This study examines the composition of POM in potential sources and within-event POM by: (1) determining the amount and quality of dissolved organic matter (DOM) that can be leached from coarse, medium and fine particle classes; (2) assessing the C and N content and isotopic character of within-event POM; and (3) coupling physical and chemical properties to evaluate storm event POM influence on stream water. Storm event POM samples and source sediments were collected from a forested headwater catchment (second order stream) in the Piedmont region of Maryland. Samples were sieved into three particle classes - coarse (2mm-1mm), medium (1mm-250µm) and fine (<250µm). Extractions were performed for three particle class sizes and the resulting fluorescent organic matter was analyzed. Carbon (C) and Nitrogen (N) amount, C:N ratio, and isotopic analysis of 13C and 15N were performed on solid state event and source material. Future work will include examination of microbial communities associated with POM particle size classes. Physical size class separation of within-event POM exhibited differences in C:N ratios, δ15N composition, and extracted DOM lability. Smaller size classes exhibited lower C:N ratios, more enriched δ15N and more recalcitrant properties in leached DOM. Source material had varying C:N ratios and contributions to leached DOM. These results indicate that both source and size class strongly influence the POM contribution to fluvial systems during large storm events.

Real-time Social Internet Data to Guide Forecasting Models

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

Del Valle, Sara Y.

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematicalmore » approaches and heterogeneous data streams.« less

Application of Natural Language Processing and Network Analysis Techniques to Post-market Reports for the Evaluation of Dose-related Anti-Thymocyte Globulin Safety Patterns.

PubMed

Botsis, Taxiarchis; Foster, Matthew; Arya, Nina; Kreimeyer, Kory; Pandey, Abhishek; Arya, Deepa

2017-04-26

To evaluate the feasibility of automated dose and adverse event information retrieval in supporting the identification of safety patterns. We extracted all rabbit Anti-Thymocyte Globulin (rATG) reports submitted to the United States Food and Drug Administration Adverse Event Reporting System (FAERS) from the product's initial licensure in April 16, 1984 through February 8, 2016. We processed the narratives using the Medication Extraction (MedEx) and the Event-based Text-mining of Health Electronic Records (ETHER) systems and retrieved the appropriate medication, clinical, and temporal information. When necessary, the extracted information was manually curated. This process resulted in a high quality dataset that was analyzed with the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA) to explore the association of rATG dosing with post-transplant lymphoproliferative disorder (PTLD). Although manual curation was necessary to improve the data quality, MedEx and ETHER supported the extraction of the appropriate information. We created a final dataset of 1,380 cases with complete information for rATG dosing and date of administration. Analysis in PANACEA found that PTLD was associated with cumulative doses of rATG >8 mg/kg, even in periods where most of the submissions to FAERS reported low doses of rATG. We demonstrated the feasibility of investigating a dose-related safety pattern for a particular product in FAERS using a set of automated tools.

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

Pipeline oil fire detection with MODIS active fire products

NASA Astrophysics Data System (ADS)

Ogungbuyi, M. G.; Martinez, P.; Eckardt, F. D.

2017-12-01

We investigate 85 129 MODIS satellite active fire events from 2007 to 2015 in the Niger Delta of Nigeria. The region is the oil base for Nigerian economy and the hub of oil exploration where oil facilities (i.e. flowlines, flow stations, trunklines, oil wells and oil fields) are domiciled, and from where crude oil and refined products are transported to different Nigerian locations through a network of pipeline systems. Pipeline and other oil facilities are consistently susceptible to oil leaks due to operational or maintenance error, and by acts of deliberate sabotage of the pipeline equipment which often result in explosions and fire outbreaks. We used ground oil spill reports obtained from the National Oil Spill Detection and Response Agency (NOSDRA) database (see www.oilspillmonitor.ng) to validate MODIS satellite data. NOSDRA database shows an estimate of 10 000 spill events from 2007 - 2015. The spill events were filtered to include largest spills by volume and events occurring only in the Niger Delta (i.e. 386 spills). By projecting both MODIS fire and spill as `input vector' layers with `Points' geometry, and the Nigerian pipeline networks as `from vector' layers with `LineString' geometry in a geographical information system, we extracted the nearest MODIS events (i.e. 2192) closed to the pipelines by 1000m distance in spatial vector analysis. The extraction process that defined the nearest distance to the pipelines is based on the global practices of the Right of Way (ROW) in pipeline management that earmarked 30m strip of land to the pipeline. The KML files of the extracted fires in a Google map validated their source origin to be from oil facilities. Land cover mapping confirmed fire anomalies. The aim of the study is to propose a near-real-time monitoring of spill events along pipeline routes using 250 m spatial resolution of MODIS active fire detection sensor when such spills are accompanied by fire events in the study location.

Development of a Novel Motor Imagery Control Technique and Application in a Gaming Environment.

PubMed

Li, Ting; Zhang, Jinhua; Xue, Tao; Wang, Baozeng

2017-01-01

We present a methodology for a hybrid brain-computer interface (BCI) system, with the recognition of motor imagery (MI) based on EEG and blink EOG signals. We tested the BCI system in a 3D Tetris and an analogous 2D game playing environment. To enhance player's BCI control ability, the study focused on feature extraction from EEG and control strategy supporting Game-BCI system operation. We compared the numerical differences between spatial features extracted with common spatial pattern (CSP) and the proposed multifeature extraction. To demonstrate the effectiveness of 3D game environment at enhancing player's event-related desynchronization (ERD) and event-related synchronization (ERS) production ability, we set the 2D Screen Game as the comparison experiment. According to a series of statistical results, the group performing MI in the 3D Tetris environment showed more significant improvements in generating MI-associated ERD/ERS. Analysis results of game-score indicated that the players' scores presented an obvious uptrend in 3D Tetris environment but did not show an obvious downward trend in 2D Screen Game. It suggested that the immersive and rich-control environment for MI would improve the associated mental imagery and enhance MI-based BCI skills.

ADESSA: A Real-Time Decision Support Service for Delivery of Semantically Coded Adverse Drug Event Data

PubMed Central

Duke, Jon D.; Friedlin, Jeff

2010-01-01

Evaluating medications for potential adverse events is a time-consuming process, typically involving manual lookup of information by physicians. This process can be expedited by CDS systems that support dynamic retrieval and filtering of adverse drug events (ADE’s), but such systems require a source of semantically-coded ADE data. We created a two-component system that addresses this need. First we created a natural language processing application which extracts adverse events from Structured Product Labels and generates a standardized ADE knowledge base. We then built a decision support service that consumes a Continuity of Care Document and returns a list of patient-specific ADE’s. Our database currently contains 534,125 ADE’s from 5602 product labels. An NLP evaluation of 9529 ADE’s showed recall of 93% and precision of 95%. On a trial set of 30 CCD’s, the system provided adverse event data for 88% of drugs and returned these results in an average of 620ms. PMID:21346964

Using Computer-Extracted Data from Electronic Health Records to Measure the Quality of Adolescent Well-Care

PubMed Central

Gardner, William; Morton, Suzanne; Byron, Sepheen C; Tinoco, Aldo; Canan, Benjamin D; Leonhart, Karen; Kong, Vivian; Scholle, Sarah Hudson

2014-01-01

Objective To determine whether quality measures based on computer-extracted EHR data can reproduce findings based on data manually extracted by reviewers. Data Sources We studied 12 measures of care indicated for adolescent well-care visits for 597 patients in three pediatric health systems. Study Design Observational study. Data Collection/Extraction Methods Manual reviewers collected quality data from the EHR. Site personnel programmed their EHR systems to extract the same data from structured fields in the EHR according to national health IT standards. Principal Findings Overall performance measured via computer-extracted data was 21.9 percent, compared with 53.2 percent for manual data. Agreement measures were high for immunizations. Otherwise, agreement between computer extraction and manual review was modest (Kappa = 0.36) because computer-extracted data frequently missed care events (sensitivity = 39.5 percent). Measure validity varied by health care domain and setting. A limitation of our findings is that we studied only three domains and three sites. Conclusions The accuracy of computer-extracted EHR quality reporting depends on the use of structured data fields, with the highest agreement found for measures and in the setting that had the greatest concentration of structured fields. We need to improve documentation of care, data extraction, and adaptation of EHR systems to practice workflow. PMID:24471935

Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network.

PubMed

Zhao, Bo; Ding, Ruoxi; Chen, Shoushun; Linares-Barranco, Bernabe; Tang, Huajin

2015-09-01

This paper introduces an event-driven feedforward categorization system, which takes data from a temporal contrast address event representation (AER) sensor. The proposed system extracts bio-inspired cortex-like features and discriminates different patterns using an AER based tempotron classifier (a network of leaky integrate-and-fire spiking neurons). One of the system's most appealing characteristics is its event-driven processing, with both input and features taking the form of address events (spikes). The system was evaluated on an AER posture dataset and compared with two recently developed bio-inspired models. Experimental results have shown that it consumes much less simulation time while still maintaining comparable performance. In addition, experiments on the Mixed National Institute of Standards and Technology (MNIST) image dataset have demonstrated that the proposed system can work not only on raw AER data but also on images (with a preprocessing step to convert images into AER events) and that it can maintain competitive accuracy even when noise is added. The system was further evaluated on the MNIST dynamic vision sensor dataset (in which data is recorded using an AER dynamic vision sensor), with testing accuracy of 88.14%.

NavyTime: Event and Time Ordering from Raw Text

DTIC Science & Technology

2013-06-01

time-time, and event-DCT (DCT is the doc- ument creation time). 74 Event Extraction F1 ATT-1 81.05 NavyTime 80.30 KUL 79.32 cleartk -4 & cleartk -3...71.88 KUL 70.17 cleartk 67.87 NavyTime 67.48 Temp:ESA 54.55 JU-CSE 52.69 Temp:WNet 50.00 FSS-TimEx 42.94 Tense and Aspect Attributes System Tense F1...Aspect F1 cleartk 62.18 70.40 NavyTime 61.67 72.43 ATT 59.47 73.50 JU-CSE 58.62 72.14 KUL 49.70 63.20 not all systems participated Figure 1: Complete

Method, accuracy and limitation of computer interaction in the operating room by a navigated surgical instrument.

PubMed

Hurka, Florian; Wenger, Thomas; Heininger, Sebastian; Lueth, Tim C

2011-01-01

This article describes a new interaction device for surgical navigation systems--the so-called navigation mouse system. The idea is to use a tracked instrument of a surgical navigation system like a pointer to control the software. The new interaction system extends existing navigation systems with a microcontroller-unit. The microcontroller-unit uses the existing communication line to extract the needed 3D-information of an instrument to calculate positions analogous to the PC mouse cursor and click events. These positions and events are used to manipulate the navigation system. In an experimental setup the reachable accuracy with the new mouse system is shown.

Extraction of events and rules of land use/cover change from the policy text

NASA Astrophysics Data System (ADS)

Lin, Guangfa; Xia, Beicheng; Huang, Wangli; Jiang, Huixian; Chen, Youfei

2007-06-01

The database of recording the snapshots of land parcels history is the foundation for the most of the models on simulating land use/cover change (LUCC) process. But the sequences of temporal snapshots are not sufficient to deduce and describe the mechanism of LUCC process. The temporal relationship between scenarios of LUCC we recorded could not be transfer into causal relationship categorically, which was regarded as a key factor in spatial-temporal reasoning. The proprietor of land parcels adapted themselves to the policies from governments and the change of production market, and then made decisions in this or that way. The occurrence of each change of a land parcel in an urban area was often related with one or more decision texts when it was investigated on the local scale with high resolution of the background scene. These decision texts may come from different sections of a hierarchical government system on different levels, such as villages or communities, towns or counties, cities, provinces or even the paramount. All these texts were balance results between advantages and disadvantages of different interest groups. They are the essential forces of LUCC in human dimension. Up to now, a methodology is still wanted for on how to express these forces in a simulation system using GIS as a language. The presented paper was part of our initial research on this topic. The term "Event" is a very important concept in the frame of "Object-Oriented" theory in computer science. While in the domain of temporal GIS, the concept of event was developed in another category. The definitions of the event and their transformation relationship were discussed in this paper on three modeling levels as real world level, conceptual level and programming level. In this context, with a case study of LUCC in recent 30 years in Xiamen city of Fujian province, P. R. China, the paper focused on how to extract information of events and rules from the policy files collected and integrate the information into the LUCC temporal database. The paper concluded by listing the main steps of how to extract events and rules from files and build an event database, and indicating directions for future work about how to develop a spatial-temporal reasoning system on the event-oriented LUCC database.

Observer properties for understanding dynamical displays: Capacities, limitations, and defaults

NASA Technical Reports Server (NTRS)

Proffitt, Dennis R.; Kaiser, Mary K.

1991-01-01

People's ability to extract relevant information while viewing ongoing events is discussed in terms of human capabilities, limitations, and defaults. A taxonomy of event complexity is developed which predicts which dynamical events people can and cannot construe. This taxonomy is related to the distinction drawn in classical mechanics between particle and extended body motions. People's commonsense understandings of simple mechanical systems are impacted little by formal training, but rather reflect heuristical simplifications that focus on a single dimension of perceived dynamical relevance.

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.

An Overview of Biomolecular Event Extraction from Scientific Documents

PubMed Central

Vanegas, Jorge A.; Matos, Sérgio; González, Fabio; Oliveira, José L.

2015-01-01

This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed. PMID:26587051

Event Display for the Visualization of CMS Events

NASA Astrophysics Data System (ADS)

Bauerdick, L. A. T.; Eulisse, G.; Jones, C. D.; Kovalskyi, D.; McCauley, T.; Mrak Tadel, A.; Muelmenstaedt, J.; Osborne, I.; Tadel, M.; Tu, Y.; Yagil, A.

2011-12-01

During the last year the CMS experiment engaged in consolidation of its existing event display programs. The core of the new system is based on the Fireworks event display program which was by-design directly integrated with the CMS Event Data Model (EDM) and the light version of the software framework (FWLite). The Event Visualization Environment (EVE) of the ROOT framework is used to manage a consistent set of 3D and 2D views, selection, user-feedback and user-interaction with the graphics windows; several EVE components were developed by CMS in collaboration with the ROOT project. In event display operation simple plugins are registered into the system to perform conversion from EDM collections into their visual representations which are then managed by the application. Full event navigation and filtering as well as collection-level filtering is supported. The same data-extraction principle can also be applied when Fireworks will eventually operate as a service within the full software framework.

Online Motor Imagery Training Effect for the Appearance of Event Related Desynchronization (ERD)

NASA Astrophysics Data System (ADS)

Takahashi, Mitsuru; Gouko, Manabu; Ito, Koji

Stroke patients have some motor deficits, but they can regain their motor abilities by rehabilitation. In the aspect of rehabilitation, voluntary movement is very important. We propose a system which can make a closed loop in brain for stroke patients like voluntary movement. Event Related Desynchronization (ERD) is used to extract patients' motor intention, and then Functional Electrical Stimulation (FES) stimuls their paralyzed muscles. In many Brain Computer Interface (BCI) researches, subjects are trained for several months or years to do the task, because of the difficulty to extract clear ERD without training. Thinking about applying for stroke patients, motor imagery training should be shorter, because of the brain plasticity. We did a pilot study about the effect of visual feedback training for three days with healthy subjects. The result indicated that ERD could be clearly extracted in three days, but the training effect differs in each subjects.

System Architecture for Temporal Information Extraction, Representation and Reasoning in Clinical Narrative Reports

PubMed Central

Zhou, Li; Friedman, Carol; Parsons, Simon; Hripcsak, George

2005-01-01

Exploring temporal information in narrative Electronic Medical Records (EMRs) is essential and challenging. We propose an architecture for an integrated approach to process temporal information in clinical narrative reports. The goal is to initiate and build a foundation that supports applications which assist healthcare practice and research by including the ability to determine the time of clinical events (e.g., past vs. present). Key components include: (1) a temporal constraint structure for temporal expressions and the development of an associated tagger; (2) a Natural Language Processing (NLP) system for encoding and extracting medical events and associating them with formalized temporal data; (3) a post-processor, with a knowledge-based subsystem to help discover implicit information, that resolves temporal expressions and deals with issues such as granularity and vagueness; and (4) a reasoning mechanism which models clinical reports as Simple Temporal Problems (STPs). PMID:16779164

Fall Detection Using Smartphone Audio Features.

PubMed

Cheffena, Michael

2016-07-01

An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine learning classifiers: k-nearest neighbor classifier (k-NN), support vector machine (SVM), least squares method (LSM), and artificial neural network (ANN) are investigated for distinguishing between fall and no-fall events. For each audio feature, the performance of each classifier in terms of sensitivity, specificity, accuracy, and computational complexity is evaluated. The best performance is achieved using spectrogram features with ANN classifier with sensitivity, specificity, and accuracy all above 98%. The classifier also has acceptable computational requirement for training and testing. The system is applicable in home environments where the phone is placed in the vicinity of the user.

Adverse Events to Food Supplements Containing Red Yeast Rice: Comparative Analysis of FAERS and CAERS Reporting Systems.

PubMed

Raschi, Emanuel; Girardi, Anna; Poluzzi, Elisabetta; Forcesi, Emanuele; Menniti-Ippolito, Francesca; Mazzanti, Gabriela; De Ponti, Fabrizio

2018-03-26

Food supplements containing red yeast rice (RYR) are proposed as an alternative in statin-intolerant patients, although they actually contain natural statin(s) and their safety in clinical practice is still incompletely characterized. We described and compared adverse events (AEs) associated with RYR products submitted to reporting systems maintained by the Food and Drug Administration (FDA), with a focus on liver and muscular events. We extracted RYR-related AEs from the FDA Adverse Event Reporting System (FAERS) [first quarter (Q1)-2004 to Q2-2016], a drug-based archive, and the Center for Food Safety and Applied Nutrition Adverse Event Reporting System (CAERS) (Q1-2004 to Q1-2017). Disproportionality via reporting odds ratio (ROR) with 95% confidence interval (CI) calculation and case-by-case inspection were performed, with a focus on muscular and hepatic AEs. One thousand three hundred AEs were extracted from FAERS (RYR mainly reported as a concomitant agent), whereas only 159 AEs were found in CAERS (RYR recorded mainly as a suspect agent). In FAERS, a large number of reports emerged for "general disorders and administration site conditions," whereas CAERS received also a high number of reports for "investigations" and "musculoskeletal and connective tissue disorders". Disproportionality analyses confirmed higher reporting of serious muscular and liver injuries: in FAERS, five cases of hepatic disorders (ROR = 13.71; 95% CI 5.44-34.57); in CAERS, 27 cases of rhabdomyolysis/myopathy (8.44; 5.44-13.10). Notwithstanding recognized limitations, these findings strengthen the importance of exploring multiple databases in safety assessment of RYR products, which should be monitored by clinicians for muscular and hepatic safety, and call for urgent review by policymakers to harmonize their regulatory status.

The contribution of the vaccine adverse event text mining system to the classification of possible Guillain-Barré syndrome reports.

PubMed

Botsis, T; Woo, E J; Ball, R

2013-01-01

We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines. To evaluate the ability of VaeTM to classify reports to the Vaccine Adverse Event Reporting System (VAERS) of possible Guillain-Barré Syndrome (GBS). We used VaeTM to extract the key diagnostic features from the text of reports in VAERS. Then, we applied the Brighton Collaboration (BC) case definition for GBS, and an information retrieval strategy (i.e. the vector space model) to quantify the specific information that is included in the key features extracted by VaeTM and compared it with the encoded information that is already stored in VAERS as Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms (PTs). We also evaluated the contribution of the primary (diagnosis and cause of death) and secondary (second level diagnosis and symptoms) diagnostic VaeTM-based features to the total VaeTM-based information. MedDRA captured more information and better supported the classification of reports for GBS than VaeTM (AUC: 0.904 vs. 0.777); the lower performance of VaeTM is likely due to the lack of extraction by VaeTM of specific laboratory results that are included in the BC criteria for GBS. On the other hand, the VaeTM-based classification exhibited greater specificity than the MedDRA-based approach (94.96% vs. 87.65%). Most of the VaeTM-based information was contained in the secondary diagnostic features. For GBS, clinical signs and symptoms alone are not sufficient to match MedDRA coding for purposes of case classification, but are preferred if specificity is the priority.

Earth system feedback statistically extracted from the Indian Ocean deep-sea sediments recording Eocene hyperthermals.

PubMed

Yasukawa, Kazutaka; Nakamura, Kentaro; Fujinaga, Koichiro; Ikehara, Minoru; Kato, Yasuhiro

2017-09-12

Multiple transient global warming events occurred during the early Palaeogene. Although these events, called hyperthermals, have been reported from around the globe, geologic records for the Indian Ocean are limited. In addition, the recovery processes from relatively modest hyperthermals are less constrained than those from the severest and well-studied hothouse called the Palaeocene-Eocene Thermal Maximum. In this study, we constructed a new and high-resolution geochemical dataset of deep-sea sediments clearly recording multiple Eocene hyperthermals in the Indian Ocean. We then statistically analysed the high-dimensional data matrix and extracted independent components corresponding to the biogeochemical responses to the hyperthermals. The productivity feedback commonly controls and efficiently sequesters the excess carbon in the recovery phases of the hyperthermals via an enhanced biological pump, regardless of the magnitude of the events. Meanwhile, this negative feedback is independent of nannoplankton assemblage changes generally recognised in relatively large environmental perturbations.

Rigging Test Bed Development for Validation of Multi-Stage Decelerator Extractions

NASA Technical Reports Server (NTRS)

Kenig, Sivan J.; Gallon, John C.; Adams, Douglas S.; Rivellini, Tommaso P.

2013-01-01

The Low Density Supersonic Decelerator project is developing new decelerator systems for Mars entry which would include testing with a Supersonic Flight Dynamics Test Vehicle. One of the decelerator systems being developed is a large supersonic ringsail parachute. Due to the configuration of the vehicle it is not possible to deploy the parachute with a mortar which would be the preferred method for a spacecraft in a supersonic flow. Alternatively, a multi-stage extraction process using a ballute as a pilot is being developed for the test vehicle. The Rigging Test Bed is a test venue being constructed to perform verification and validation of this extraction process. The test bed consists of a long pneumatic piston device capable of providing a constant force simulating the ballute drag force during the extraction events. The extraction tests will take place both inside a high-bay for frequent tests of individual extraction stages and outdoors using a mobile hydraulic crane for complete deployment tests from initial pack pull out to canopy extraction. These tests will measure line tensions and use photogrammetry to track motion of the elements involved. The resulting data will be used to verify packing and rigging as well, as validate models and identify potential failure modes in order to finalize the design of the extraction system.

Development of a Novel Motor Imagery Control Technique and Application in a Gaming Environment

PubMed Central

Xue, Tao

2017-01-01

We present a methodology for a hybrid brain-computer interface (BCI) system, with the recognition of motor imagery (MI) based on EEG and blink EOG signals. We tested the BCI system in a 3D Tetris and an analogous 2D game playing environment. To enhance player's BCI control ability, the study focused on feature extraction from EEG and control strategy supporting Game-BCI system operation. We compared the numerical differences between spatial features extracted with common spatial pattern (CSP) and the proposed multifeature extraction. To demonstrate the effectiveness of 3D game environment at enhancing player's event-related desynchronization (ERD) and event-related synchronization (ERS) production ability, we set the 2D Screen Game as the comparison experiment. According to a series of statistical results, the group performing MI in the 3D Tetris environment showed more significant improvements in generating MI-associated ERD/ERS. Analysis results of game-score indicated that the players' scores presented an obvious uptrend in 3D Tetris environment but did not show an obvious downward trend in 2D Screen Game. It suggested that the immersive and rich-control environment for MI would improve the associated mental imagery and enhance MI-based BCI skills. PMID:28572817

Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

NASA Astrophysics Data System (ADS)

Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

2012-09-01

The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

Algorithm for Screening Phasor Measurement Unit Data for Power System Events and Categories and Common Characteristics for Events Seen in Phasor Measurement Unit Relative Phase-Angle Differences and Frequency Signals

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

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

2013-08-01

A network of multiple phasor measurement units (PMU) was created, set up, and maintained at the University of Texas at Austin to obtain actual power system measurements for power system analysis. Power system analysis in this report covers a variety of time ranges, such as short- term analysis for power system disturbances and their effects on power system behavior and long- term power system behavior using modal analysis. The first objective of this report is to screen the PMU data for events. The second objective of the report is to identify and describe common characteristics extracted from power system eventsmore » as measured by PMUs. The numerical characteristics for each category and how these characteristics are used to create selection rules for the algorithm are also described. Trends in PMU data related to different levels and fluctuations in wind power output are also examined.« less

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.

Groundwater-related Land Deformation over the Mega Aquifer System in Saudi Arabia: Inferences from InSAR, GRACE, Earthquake records, Field, and Spatial Data Analysis.

NASA Astrophysics Data System (ADS)

Othman, A.; Sultan, M.; Becker, R.; Sefry, S.; Alharbi, T.; Alharbi, H.; Gebremichael, E.

2017-12-01

Land deformational features (subsidence, and earth fissures, etc.) are being reported from many locations over the Lower Mega Aquifer System (LMAS) in the central and northern parts of Saudi Arabia. We applied an integrated approach (remote sensing, geodesy, GIS, geology, hydrogeology, and geotechnical) to identify nature, intensity, spatial distribution, and factors controlling the observed deformation. A three-fold approach was adopted to accomplish the following: (1) investigate, identify, and verify the land deformation through fieldwork; (2) assess the spatial and temporal distribution of land deformation and quantify deformation rates using Interferometric Synthetic Aperture Radar (InSAR) and Persistent Scatterer Interferometry (PSI) methods (period: 2003 to 2012); (3) generate a GIS database to host all relevant data and derived products (remote sensing, geology, geotechnical, GPS, groundwater extraction rates, and water levels, etc.) and to correlate these spatial and temporal datasets in search of causal effects. The following observations are consistent with deformational features being caused by excessive groundwater extraction: (1) distribution of deformational features correlated spatially and temporally with increased agricultural development and groundwater extraction, and with the decline in groundwater levels and storage; (2) earthquake events (1.5 - 5.5 M) increased from one event at the beginning of the agricultural development program in 1980 (average annual extraction [ANE]: 1-2 km³/yr), to 13 events per year between 1995 to 2005, the decade that witnessed the largest expansion in groundwater extraction (ANE: >6.4 km³) and land reclamation using groundwater resources; and (3) earthquake epicenters and the deformation sites are found largely within areas bound by the Kahf fault system suggesting that faults play a key role in the deformation phenomenon. Findings from the PSI investigation revealed high, yet irregularly distributed, subsidence rates (-4 to -15 mm/yr) along a NW-SE trending graben within the Wadi As-Sirhan Basin in the northern part of LMAS with the highest subsidence rates being localized within elongated bowls, that are proximal to, or bound by, the major faults and that areas to the east and west of the bounding faults show no, or minimal subsidence.

Ten-year study of postoperative complications following dental extractions in patients with inherited bleeding disorders.

PubMed

Hsieh, J-T; Klein, K; Batstone, M

2017-09-01

Dental extractions challenge the body's haemostatic mechanism. Postoperative bleeding from dental extraction can be prolonged, or even life threatening in patients with inherited bleeding disorders. Pre- and postoperative clotting factor replacements or systemic desmopressin (ddAVP) have been advocated at our institution to prevent bleeding complications in these patients. This study aimed to assess the postoperative bleeding rate in patients with inherited bleeding disorders that underwent dental extractions at our institution between 2003 and 2012. Patients with inherited bleeding disorders such as haemophilia A, haemophilia B, and von Willebrand's disease were included. Retrospective chart review was conducted. The result showed 53 extraction events occurred in 45 patients over the 10-year period. Ten out of 53 extraction events (18.9%) had postoperative bleeding requiring further factor replacement or ddAVP. Postoperative bleeding in one patient with mild haemophilia A was complicated by the development of inhibitors. Type and severity of bleeding disorder, bone removal, and use of a local haemostatic agent did not have any significant effect on postoperative bleeding. Despite the use of perioperative factors and desmopressin, the postoperative bleeding rates remain high for patients with inherited bleeding disorders. More studies are required to assess the safety and effectiveness of using local haemostatic control to achieve haemostasis following extractions. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Do systemic antibiotics prevent dry socket and infection after third molar extraction? A systematic review and meta-analysis.

PubMed

Ramos, Eva; Santamaría, Joseba; Santamaría, Gorka; Barbier, Luis; Arteagoitia, Icíar

2016-10-01

The use of antibiotics to prevent dry socket and infection is a controversial but widespread practice. The aim of the study is to assess the efficacy of systemic antibiotics in reducing the frequencies of these complications after extraction. A systematic review and meta-analysis, according to the PRISMA statement, based on randomized double-blind placebo-controlled trials evaluating systemic antibiotics to prevent dry socket and infection after third molar surgery. Databases were searched up to June 2015. Relative risks (RRs) were calculated with inverse variance-weighted, fixed-effect, or random-effect models. We included 22 papers in the qualitative and 21 in the quantitative review (3304 extractions). Overall-RR was 0.43 (95% confidence interval [CI] 0.33-0.56; P < .0001); number needed to treat, 14 (95% CI 11-19). Penicillins-RR: 0.40 (95% CI 0.27-0.59). Nitroimidazoles-RR: 0.56 (95% CI 0.38-0.82). No serious adverse events were reported. Systemic antibiotics significantly reduce the risk of dry socket and infection in third molar extraction. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Information Extraction from Unstructured Text for the Biodefense Knowledge Center

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

Samatova, N F; Park, B; Krishnamurthy, R

2005-04-29

The Bio-Encyclopedia at the Biodefense Knowledge Center (BKC) is being constructed to allow an early detection of emerging biological threats to homeland security. It requires highly structured information extracted from variety of data sources. However, the quantity of new and vital information available from every day sources cannot be assimilated by hand, and therefore reliable high-throughput information extraction techniques are much anticipated. In support of the BKC, Lawrence Livermore National Laboratory and Oak Ridge National Laboratory, together with the University of Utah, are developing an information extraction system built around the bioterrorism domain. This paper reports two important pieces ofmore » our effort integrated in the system: key phrase extraction and semantic tagging. Whereas two key phrase extraction technologies developed during the course of project help identify relevant texts, our state-of-the-art semantic tagging system can pinpoint phrases related to emerging biological threats. Also we are enhancing and tailoring the Bio-Encyclopedia by augmenting semantic dictionaries and extracting details of important events, such as suspected disease outbreaks. Some of these technologies have already been applied to large corpora of free text sources vital to the BKC mission, including ProMED-mail, PubMed abstracts, and the DHS's Information Analysis and Infrastructure Protection (IAIP) news clippings. In order to address the challenges involved in incorporating such large amounts of unstructured text, the overall system is focused on precise extraction of the most relevant information for inclusion in the BKC.« less

Complex Event Extraction using DRUM

DTIC Science & Technology

2015-10-01

towards tackling these challenges . Figure 9. Evaluation results for eleven teams. The diamond ◆ represents the results of our system. The two topmost...Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/ VLC -2000). The UniProt

DREB1A promotes root development in deep soil layers and increases water extraction under water stress in groundnut.

PubMed

Vadez, V; Rao, J S; Bhatnagar-Mathur, P; Sharma, K K

2013-01-01

Water deficit is a major yield-limiting factor for many crops, and improving the root system has been proposed as a promising breeding strategy, although not in groundnut (Arachis hypogaea L.). The present work was carried out mainly to assess how root traits are influenced under water stress in groundnut, whether transgenics can alter root traits, and whether putative changes lead to water extraction differences. Several transgenic events, transformed with DREB1A driven by the rd29 promoter, along with wild-type JL24, were tested in a lysimeter system that mimics field conditions under both water stress (WS) and well-watered (WW) conditions. The WS treatment increased the maximum rooting depth, although the increase was limited to about 20% in JL24, compared to 50% in RD11. The root dry weight followed a similar trend. Consequently, the root dry weight and length density of transgenics was higher in layers below 100-cm depth (Exp. 1) and below 30 cm (Exp. 2). The root diameter was unchanged under WS treatment, except a slight increase in the 60-90-cm layer. The root diameter increased below 60 cm in both treatments. In the WW treatment, total water extraction of RD33 was higher than in JL24 and other transgenic events, and somewhat lower in RD11 than in JL24. In the WS treatment, water extraction of RD2, RD11 and RD33 was higher than in JL24. These water extraction differences were mostly apparent in the initial 21 days after treatment imposition and were well related to root length density in the 30-60-cm layer (R(2) = 0.68), but not to average root length density. In conclusion, water stress promotes rooting growth more strongly in transgenic events than in the wild type, especially in deep soil layers, and this leads to increased water extraction. This opens an avenue for tapping these characteristics toward the improvement of drought adaptation in deep soil conditions, and toward a better understanding of genes involved in rooting in groundnut. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

Extracting biomedical events from pairs of text entities

PubMed Central

2015-01-01

Background Huge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processing for their registration into organized databases. This organization is instrumental for information retrieval, enabling to answer the advanced queries of researchers and practitioners in biology, medicine, and related fields. Hence, the massive data flow calls for efficient automatic methods of text-mining that extract high-level information, such as biomedical events, from biomedical text. The usual computational tools of Natural Language Processing cannot be readily applied to extract these biomedical events, due to the peculiarities of the domain. Indeed, biomedical documents contain highly domain-specific jargon and syntax. These documents also describe distinctive dependencies, making text-mining in molecular biology a specific discipline. Results We address biomedical event extraction as the classification of pairs of text entities into the classes corresponding to event types. The candidate pairs of text entities are recursively provided to a multiclass classifier relying on Support Vector Machines. This recursive process extracts events involving other events as arguments. Compared to joint models based on Markov Random Fields, our model simplifies inference and hence requires shorter training and prediction times along with lower memory capacity. Compared to usual pipeline approaches, our model passes over a complex intermediate problem, while making a more extensive usage of sophisticated joint features between text entities. Our method focuses on the core event extraction of the Genia task of BioNLP challenges yielding the best result reported so far on the 2013 edition. PMID:26201478

Data Exploration using Unsupervised Feature Extraction for Mixed Micro-Seismic Signals

NASA Astrophysics Data System (ADS)

Meyer, Matthias; Weber, Samuel; Beutel, Jan

2017-04-01

We present a system for the analysis of data originating in a multi-sensor and multi-year experiment focusing on slope stability and its underlying processes in fractured permafrost rock walls undertaken at 3500m a.s.l. on the Matterhorn Hörnligrat, (Zermatt, Switzerland). This system incorporates facilities for the transmission, management and storage of large-scales of data ( 7 GB/day), preprocessing and aggregation of multiple sensor types, machine-learning based automatic feature extraction for micro-seismic and acoustic emission data and interactive web-based visualization of the data. Specifically, a combination of three types of sensors are used to profile the frequency spectrum from 1 Hz to 80 kHz with the goal to identify the relevant destructive processes (e.g. micro-cracking and fracture propagation) leading to the eventual destabilization of large rock masses. The sensors installed for this profiling experiment (2 geophones, 1 accelerometers and 2 piezo-electric sensors for detecting acoustic emission), are further augmented with sensors originating from a previous activity focusing on long-term monitoring of temperature evolution and rock kinematics with the help of wireless sensor networks (crackmeters, cameras, weather station, rock temperature profiles, differential GPS) [Hasler2012]. In raw format, the data generated by the different types of sensors, specifically the micro-seismic and acoustic emission sensors, is strongly heterogeneous, in part unsynchronized and the storage and processing demand is large. Therefore, a purpose-built signal preprocessing and event-detection system is used. While the analysis of data from each individual sensor follows established methods, the application of all these sensor types in combination within a field experiment is unique. Furthermore, experience and methods from using such sensors in laboratory settings cannot be readily transferred to the mountain field site setting with its scale and full exposure to the natural environment. Consequently, many state-of-the-art algorithms for big data analysis and event classification requiring a ground truth dataset cannot be applied. The above mentioned challenges require a tool for data exploration. In the presented system, data exploration is supported by unsupervised feature learning based on convolutional neural networks, which is used to automatically extract common features for preliminary clustering and outlier detection. With this information, an interactive web-tool allows for a fast identification of interesting time segments on which segment-selective algorithms for visualization, feature extraction and statistics can be applied. The combination of manual labeling based and unsupervised feature extraction provides an event catalog for classification of different characteristic events related to internal progression of micro-crack in steep fractured bedrock permafrost. References Hasler, A., S. Gruber, and J. Beutel (2012), Kinematics of steep bedrock permafrost, J. Geophys. Res., 117, F01016, doi:10.1029/2011JF001981.

Extraction and Separation Modeling of Orion Test Vehicles with ADAMS Simulation

NASA Technical Reports Server (NTRS)

Fraire, Usbaldo, Jr.; Anderson, Keith; Cuthbert, Peter A.

2013-01-01

The Capsule Parachute Assembly System (CPAS) project has increased efforts to demonstrate the performance of fully integrated parachute systems at both higher dynamic pressures and in the presence of wake fields using a Parachute Compartment Drop Test Vehicle (PCDTV) and a Parachute Test Vehicle (PTV), respectively. Modeling the extraction and separation events has proven challenging and an understanding of the physics is required to reduce the risk of separation malfunctions. The need for extraction and separation modeling is critical to a successful CPAS test campaign. Current PTV-alone simulations, such as Decelerator System Simulation (DSS), require accurate initial conditions (ICs) drawn from a separation model. Automatic Dynamic Analysis of Mechanical Systems (ADAMS), a Commercial off the Shelf (COTS) tool, was employed to provide insight into the multi-body six degree of freedom (DOF) interaction between parachute test hardware and external and internal forces. Components of the model include a composite extraction parachute, primary vehicle (PTV or PCDTV), platform cradle, a release mechanism, aircraft ramp, and a programmer parachute with attach points. Independent aerodynamic forces were applied to the mated test vehicle/platform cradle and the separated test vehicle and platform cradle. The aero coefficients were determined from real time lookup tables which were functions of both angle of attack ( ) and sideslip ( ). The atmospheric properties were also determined from a real time lookup table characteristic of the Yuma Proving Grounds (YPG) atmosphere relative to the planned test month. Representative geometries were constructed in ADAMS with measured mass properties generated for each independent vehicle. Derived smart separation parameters were included in ADAMS as sensors with defined pitch and pitch rate criteria used to refine inputs to analogous avionics systems for optimal separation conditions. Key design variables were dispersed in a Monte Carlo analysis to provide the maximum expected range of the state variables at programmer deployment to be used as ICs in DSS. Extensive comparisons were made with Decelerator System Simulation Application (DSSA) to validate the mated portion of the ADAMS extraction trajectory. Results of the comparisons improved the fidelity of ADAMS with a ramp pitch profile update from DSSA. Post-test reconstructions resulted in improvements to extraction parachute drag area knock-down factors, extraction line modeling, and the inclusion of ball-to-socket attachments used as a release mechanism on the PTV. Modeling of two Extraction parachutes was based on United States Air Force (USAF) tow test data and integrated into ADAMS for nominal and Monte Carlo trajectory assessments. Video overlay of ADAMS animations and actual C-12 chase plane test videos supported analysis and observation efforts of extraction and separation events. The COTS ADAMS simulation has been integrated with NASA based simulations to provide complete end to end trajectories with a focus on the extraction, separation, and programmer deployment sequence. The flexibility of modifying ADAMS inputs has proven useful for sensitivity studies and extraction/separation modeling efforts. 1

McClellan AFB, California. Operable Unit B, Engineering Evaluation/Cost Analysis - Environmental Assessment

DTIC Science & Technology

1991-02-01

however, ’the daily flow rate can dramatically increase during storm events due to rainwater infiltration, to the system . Treatment processes include...132 has been restricted from supplying water to the local distribution system , except in emergency situations. This well was being threatened by...the near surface aquifer upgradient from the production well. The extracted groundwater will be treated in a granular activated carbon system and

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.

HELIOGate, a Portal for the Heliophysics Community

NASA Astrophysics Data System (ADS)

Pierantoni; Gabriele; Carley, Eoin

2014-10-01

Heliophysics is the branch of physics that investigates the interactions between the Sun and the other bodies of the solar system. Heliophysicists rely on data collected from numerous sources scattered across the Solar System. The data collected from these sources is processed to extract metadata and the metadata extracted in this fashion is then used to build indexes of features and events called catalogues. Heliophysicists also develop conceptual and mathematical models of the phenomena and the environment of the Solar System. More specifically, they investigate the physical characteristics of the phenomena and they simulate how they propagate throughout the Solar System with mathematical and physical abstractions called propagation models. HELIOGate aims at addressing the need to combine and orchestrate existing web services in a flexible and easily configurable fashion to tackle different scientific questions. HELIOGate also offers a tool capable of connecting to size! able computation and storage infrastructures to execute data processing codes that are needed to calibrate raw data and to extract metadata.

Nuclear events of apoptosis in vitro in cell-free mitotic extracts: a model system for analysis of the active phase of apoptosis

PubMed Central

1993-01-01

We have developed a cell-free system that induces the morphological transformations characteristic of apoptosis in isolated nuclei. The system uses extracts prepared from mitotic chicken hepatoma cells following a sequential S phase/M phase synchronization. When nuclei are added to these extracts, the chromatin becomes highly condensed into spherical domains that ultimately extrude through the nuclear envelope, forming apoptotic bodies. The process is highly synchronous, and the structural changes are completed within 60 min. Coincident with these morphological changes, the nuclear DNA is cleaved into a nucleosomal ladder. Both processes are inhibited by Zn2+, an inhibitor of apoptosis in intact cells. Nuclear lamina disassembly accompanies these structural changes in added nuclei, and we show that lamina disassembly is a characteristic feature of apoptosis in intact cells of mouse, human and chicken. This system may provide a powerful means of dissecting the biochemical mechanisms underlying the final stages of apoptosis. PMID:8408207

Information sciences experiment system

NASA Technical Reports Server (NTRS)

Katzberg, Stephen J.; Murray, Nicholas D.; Benz, Harry F.; Bowker, David E.; Hendricks, Herbert D.

1990-01-01

The rapid expansion of remote sensing capability over the last two decades will take another major leap forward with the advent of the Earth Observing System (Eos). An approach is presented that will permit experiments and demonstrations in onboard information extraction. The approach is a non-intrusive, eavesdropping mode in which a small amount of spacecraft real estate is allocated to an onboard computation resource. How such an approach allows the evaluation of advanced technology in the space environment, advanced techniques in information extraction for both Earth science and information science studies, direct to user data products, and real-time response to events, all without affecting other on-board instrumentation is discussed.

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 additional, supplemental data source to have a more comprehensive estimate of disease burden. Copyright © 2017 Elsevier B.V. All rights reserved.

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

AllamehZadeh, Mostafa, E-mail: dibaparima@yahoo.com

A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neuralmore » system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.« less

Aligning observed and modelled behaviour based on workflow decomposition

NASA Astrophysics Data System (ADS)

Wang, Lu; Du, YuYue; Liu, Wei

2017-09-01

When business processes are mostly supported by information systems, the availability of event logs generated from these systems, as well as the requirement of appropriate process models are increasing. Business processes can be discovered, monitored and enhanced by extracting process-related information. However, some events cannot be correctly identified because of the explosion of the amount of event logs. Therefore, a new process mining technique is proposed based on a workflow decomposition method in this paper. Petri nets (PNs) are used to describe business processes, and then conformance checking of event logs and process models is investigated. A decomposition approach is proposed to divide large process models and event logs into several separate parts that can be analysed independently; while an alignment approach based on a state equation method in PN theory enhances the performance of conformance checking. Both approaches are implemented in programmable read-only memory (ProM). The correctness and effectiveness of the proposed methods are illustrated through experiments.

Simulation and study of small numbers of random events

NASA Technical Reports Server (NTRS)

Shelton, R. D.

1986-01-01

Random events were simulated by computer and subjected to various statistical methods to extract important parameters. Various forms of curve fitting were explored, such as least squares, least distance from a line, maximum likelihood. Problems considered were dead time, exponential decay, and spectrum extraction from cosmic ray data using binned data and data from individual events. Computer programs, mostly of an iterative nature, were developed to do these simulations and extractions and are partially listed as appendices. The mathematical basis for the compuer programs is given.

Beam Energy Scan of Specific Heat Through Temperature Fluctuations in Heavy Ion Collisions

NASA Astrophysics Data System (ADS)

Basu, Sumit; Nandi, Basanta K.; Chatterjee, Sandeep; Chatterjee, Rupa; Nayak, Tapan

2016-01-01

Temperature fluctuations may have two distinct origins, first, quantum fluctuations that are initial state fluctuations, and second, thermodynamical fluctuations. We discuss a method of extracting the thermodynamic temperature from the mean transverse momentum of pions, by using controllable parameters such as centrality of the system, and range of the transverse momenta. Event-by-event fluctuations in global temperature over a large phase space provide the specific heat of the system. We present Beam Energy Scan of specific heat from data, AMPT and HRG model prediction. Experimental results from NA49, STAR, PHENIX, PHOBOS and ALICE are combined to obtain the specific heat as a function of beam energy. These results are compared to calculations from AMPT event generator, HRG model and lattice calculations, respectively.

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

The Contribution of the Vaccine Adverse Event Text Mining System to the Classification of Possible Guillain-Barré Syndrome Reports

PubMed Central

Botsis, T.; Woo, E. J.; Ball, R.

2013-01-01

Background We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines. Objective To evaluate the ability of VaeTM to classify reports to the Vaccine Adverse Event Reporting System (VAERS) of possible Guillain-Barré Syndrome (GBS). Methods We used VaeTM to extract the key diagnostic features from the text of reports in VAERS. Then, we applied the Brighton Collaboration (BC) case definition for GBS, and an information retrieval strategy (i.e. the vector space model) to quantify the specific information that is included in the key features extracted by VaeTM and compared it with the encoded information that is already stored in VAERS as Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms (PTs). We also evaluated the contribution of the primary (diagnosis and cause of death) and secondary (second level diagnosis and symptoms) diagnostic VaeTM-based features to the total VaeTM-based information. Results MedDRA captured more information and better supported the classification of reports for GBS than VaeTM (AUC: 0.904 vs. 0.777); the lower performance of VaeTM is likely due to the lack of extraction by VaeTM of specific laboratory results that are included in the BC criteria for GBS. On the other hand, the VaeTM-based classification exhibited greater specificity than the MedDRA-based approach (94.96% vs. 87.65%). Most of the VaeTM-based information was contained in the secondary diagnostic features. Conclusion For GBS, clinical signs and symptoms alone are not sufficient to match MedDRA coding for purposes of case classification, but are preferred if specificity is the priority. PMID:23650490

A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports.

PubMed

Liu, Xiao; Chen, Hsinchun

2015-12-01

Social media offer insights of patients' medical problems such as drug side effects and treatment failures. Patient reports of adverse drug events from social media have great potential to improve current practice of pharmacovigilance. However, extracting patient adverse drug event reports from social media continues to be an important challenge for health informatics research. In this study, we develop a research framework with advanced natural language processing techniques for integrated and high-performance patient reported adverse drug event extraction. The framework consists of medical entity extraction for recognizing patient discussions of drug and events, adverse drug event extraction with shortest dependency path kernel based statistical learning method and semantic filtering with information from medical knowledge bases, and report source classification to tease out noise. To evaluate the proposed framework, a series of experiments were conducted on a test bed encompassing about postings from major diabetes and heart disease forums in the United States. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Our framework significantly outperforms prior work. Published by Elsevier Inc.

A la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge.

PubMed

Cherry, Colin; Zhu, Xiaodan; Martin, Joel; de Bruijn, Berry

2013-01-01

An analysis of the timing of events is critical for a deeper understanding of the course of events within a patient record. The 2012 i2b2 NLP challenge focused on the extraction of temporal relationships between concepts within textual hospital discharge summaries. The team from the National Research Council Canada (NRC) submitted three system runs to the second track of the challenge: typifying the time-relationship between pre-annotated entities. The NRC system was designed around four specialist modules containing statistical machine learning classifiers. Each specialist targeted distinct sets of relationships: local relationships, 'sectime'-type relationships, non-local overlap-type relationships, and non-local causal relationships. The best NRC submission achieved a precision of 0.7499, a recall of 0.6431, and an F1 score of 0.6924, resulting in a statistical tie for first place. Post hoc improvements led to a precision of 0.7537, a recall of 0.6455, and an F1 score of 0.6954, giving the highest scores reported on this task to date. Methods for general relation extraction extended well to temporal relations, and gave top-ranked state-of-the-art results. Careful ordering of predictions within result sets proved critical to this success.

Extreme event statistics in a drifting Markov chain

NASA Astrophysics Data System (ADS)

Kindermann, Farina; Hohmann, Michael; Lausch, Tobias; Mayer, Daniel; Schmidt, Felix; Widera, Artur

2017-07-01

We analyze extreme event statistics of experimentally realized Markov chains with various drifts. Our Markov chains are individual trajectories of a single atom diffusing in a one-dimensional periodic potential. Based on more than 500 individual atomic traces we verify the applicability of the Sparre Andersen theorem to our system despite the presence of a drift. We present detailed analysis of four different rare-event statistics for our system: the distributions of extreme values, of record values, of extreme value occurrence in the chain, and of the number of records in the chain. We observe that, for our data, the shape of the extreme event distributions is dominated by the underlying exponential distance distribution extracted from the atomic traces. Furthermore, we find that even small drifts influence the statistics of extreme events and record values, which is supported by numerical simulations, and we identify cases in which the drift can be determined without information about the underlying random variable distributions. Our results facilitate the use of extreme event statistics as a signal for small drifts in correlated trajectories.

Development and validation of Aviation Causal Contributors for Error Reporting Systems (ACCERS).

PubMed

Baker, David P; Krokos, Kelley J

2007-04-01

This investigation sought to develop a reliable and valid classification system for identifying and classifying the underlying causes of pilot errors reported under the Aviation Safety Action Program (ASAP). ASAP is a voluntary safety program that air carriers may establish to study pilot and crew performance on the line. In ASAP programs, similar to the Aviation Safety Reporting System, pilots self-report incidents by filing a short text description of the event. The identification of contributors to errors is critical if organizations are to improve human performance, yet it is difficult for analysts to extract this information from text narratives. A taxonomy was needed that could be used by pilots to classify the causes of errors. After completing a thorough literature review, pilot interviews and a card-sorting task were conducted in Studies 1 and 2 to develop the initial structure of the Aviation Causal Contributors for Event Reporting Systems (ACCERS) taxonomy. The reliability and utility of ACCERS was then tested in studies 3a and 3b by having pilots independently classify the primary and secondary causes of ASAP reports. The results provided initial evidence for the internal and external validity of ACCERS. Pilots were found to demonstrate adequate levels of agreement with respect to their category classifications. ACCERS appears to be a useful system for studying human error captured under pilot ASAP reports. Future work should focus on how ACCERS is organized and whether it can be used or modified to classify human error in ASAP programs for other aviation-related job categories such as dispatchers. Potential applications of this research include systems in which individuals self-report errors and that attempt to extract and classify the causes of those events.

Coupling geodynamic with thermodynamic modelling for reconstructions of magmatic systems

NASA Astrophysics Data System (ADS)

Rummel, Lisa; Kaus, Boris J. P.; White, Richard

2016-04-01

Coupling geodynamic with petrological models is fundamental for understanding magmatic systems from the melting source in the mantle to the point of magma crystallisation in the upper crust. Most geodynamic codes use very simplified petrological models consisting of a single, fixed, chemistry. Here, we develop a method to better track the petrological evolution of the source rock and corresponding volcanic and plutonic rocks by combining a geodynamic code with a thermodynamic model for magma generation and evolution. For the geodynamic modelling a finite element code (MVEP2) solves the conservation of mass, momentum and energy equations. The thermodynamic modelling of phase equilibria in magmatic systems is performed with pMELTS for mantle-like bulk compositions. The thermodynamic dependent properties calculated by pMELTS are density, melt fraction and the composition of the liquid and solid phase in the chemical system: SiO2-TiO2-Al2O3-Fe2O3-Cr2O3-FeO-MgO-CaO-Na2O-K2O-P2O5-H2O. In order to take into account the chemical depletion of the source rock with increasing melt extraction events, calculation of phase diagrams is performed in two steps: 1) With an initial rock composition density, melt fraction as well as liquid and solid composition are computed over the full upper mantle P-T range. 2) Once the residual rock composition (equivalent to the solid composition after melt extraction) is significantly different from the initial rock composition and the melt fraction is lower than a critical value, the residual composition is used for next calculations with pMELTS. The implementation of several melt extraction events take the change in chemistry into account until the solidus is shifted to such high temperatures that the rock cannot be molten anymore under upper mantle conditions. An advantage of this approach is that we can track the change of melt chemistry with time, which can be compared with natural constraints. In the thermo-mechanical code the thermodynamic dependent properties from pre-computed phase diagrams are carried by each particle using marker-in-cell method . Thus the physical and chemical properties can change locally as a function of previous melt extraction events, pressure and temperature conditions. After each melt extraction event, the residual rock composition is compared with the bulk composition of previous computed phase diagrams, so that the used phase diagram is replaced by the phase diagram with the closest bulk chemistry. In the thermo-mechanical code, the melt is extracted directly to the surface as volcanites and within the crust as plutonites. The density of the crust and new generated crust is calculated with the thermodynamic modelling tool Perple_X. We have investigated the influence of several input parameters on the magma composition to compare it with real rock samples from Eifel (West-Germany). In order to take the very inhomogeneous chemistry of European mantle into account, we include not only primitive mantle but also metasomatised mantle fragments in the melting source of a plume (Eifel plume).

Quantum random number generation for loophole-free Bell tests

NASA Astrophysics Data System (ADS)

Mitchell, Morgan; Abellan, Carlos; Amaya, Waldimar

2015-05-01

We describe the generation of quantum random numbers at multi-Gbps rates, combined with real-time randomness extraction, to give very high purity random numbers based on quantum events at most tens of ns in the past. The system satisfies the stringent requirements of quantum non-locality tests that aim to close the timing loophole. We describe the generation mechanism using spontaneous-emission-driven phase diffusion in a semiconductor laser, digitization, and extraction by parity calculation using multi-GHz logic chips. We pay special attention to experimental proof of the quality of the random numbers and analysis of the randomness extraction. In contrast to widely-used models of randomness generators in the computer science literature, we argue that randomness generation by spontaneous emission can be extracted from a single source.

Event extraction of bacteria biotopes: a knowledge-intensive NLP-based approach

PubMed Central

2012-01-01

Background Bacteria biotopes cover a wide range of diverse habitats including animal and plant hosts, natural, medical and industrial environments. The high volume of publications in the microbiology domain provides a rich source of up-to-date information on bacteria biotopes. This information, as found in scientific articles, is expressed in natural language and is rarely available in a structured format, such as a database. This information is of great importance for fundamental research and microbiology applications (e.g., medicine, agronomy, food, bioenergy). The automatic extraction of this information from texts will provide a great benefit to the field. Methods We present a new method for extracting relationships between bacteria and their locations using the Alvis framework. Recognition of bacteria and their locations was achieved using a pattern-based approach and domain lexical resources. For the detection of environment locations, we propose a new approach that combines lexical information and the syntactic-semantic analysis of corpus terms to overcome the incompleteness of lexical resources. Bacteria location relations extend over sentence borders, and we developed domain-specific rules for dealing with bacteria anaphors. Results We participated in the BioNLP 2011 Bacteria Biotope (BB) task with the Alvis system. Official evaluation results show that it achieves the best performance of participating systems. New developments since then have increased the F-score by 4.1 points. Conclusions We have shown that the combination of semantic analysis and domain-adapted resources is both effective and efficient for event information extraction in the bacteria biotope domain. We plan to adapt the method to deal with a larger set of location types and a large-scale scientific article corpus to enable microbiologists to integrate and use the extracted knowledge in combination with experimental data. PMID:22759462

Event extraction of bacteria biotopes: a knowledge-intensive NLP-based approach.

PubMed

Ratkovic, Zorana; Golik, Wiktoria; Warnier, Pierre

2012-06-26

Bacteria biotopes cover a wide range of diverse habitats including animal and plant hosts, natural, medical and industrial environments. The high volume of publications in the microbiology domain provides a rich source of up-to-date information on bacteria biotopes. This information, as found in scientific articles, is expressed in natural language and is rarely available in a structured format, such as a database. This information is of great importance for fundamental research and microbiology applications (e.g., medicine, agronomy, food, bioenergy). The automatic extraction of this information from texts will provide a great benefit to the field. We present a new method for extracting relationships between bacteria and their locations using the Alvis framework. Recognition of bacteria and their locations was achieved using a pattern-based approach and domain lexical resources. For the detection of environment locations, we propose a new approach that combines lexical information and the syntactic-semantic analysis of corpus terms to overcome the incompleteness of lexical resources. Bacteria location relations extend over sentence borders, and we developed domain-specific rules for dealing with bacteria anaphors. We participated in the BioNLP 2011 Bacteria Biotope (BB) task with the Alvis system. Official evaluation results show that it achieves the best performance of participating systems. New developments since then have increased the F-score by 4.1 points. We have shown that the combination of semantic analysis and domain-adapted resources is both effective and efficient for event information extraction in the bacteria biotope domain. We plan to adapt the method to deal with a larger set of location types and a large-scale scientific article corpus to enable microbiologists to integrate and use the extracted knowledge in combination with experimental data.

A Framework for Collaborative Review of Candidate Events in High Data Rate Streams: the V-Fastr Experiment as a Case Study

NASA Astrophysics Data System (ADS)

Hart, Andrew F.; Cinquini, Luca; Khudikyan, Shakeh E.; Thompson, David R.; Mattmann, Chris A.; Wagstaff, Kiri; Lazio, Joseph; Jones, Dayton

2015-01-01

“Fast radio transients” are defined here as bright millisecond pulses of radio-frequency energy. These short-duration pulses can be produced by known objects such as pulsars or potentially by more exotic objects such as evaporating black holes. The identification and verification of such an event would be of great scientific value. This is one major goal of the Very Long Baseline Array (VLBA) Fast Transient Experiment (V-FASTR), a software-based detection system installed at the VLBA. V-FASTR uses a “commensal” (piggy-back) approach, analyzing all array data continually during routine VLBA observations and identifying candidate fast transient events. Raw data can be stored from a buffer memory, which enables a comprehensive off-line analysis. This is invaluable for validating the astrophysical origin of any detection. Candidates discovered by the automatic system must be reviewed each day by analysts to identify any promising signals that warrant a more in-depth investigation. To support the timely analysis of fast transient detection candidates by V-FASTR scientists, we have developed a metadata-driven, collaborative candidate review framework. The framework consists of a software pipeline for metadata processing composed of both open source software components and project-specific code written expressly to extract and catalog metadata from the incoming V-FASTR data products, and a web-based data portal that facilitates browsing and inspection of the available metadata for candidate events extracted from the VLBA radio data.

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

DOE PAGES

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo; ...

2017-07-14

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations

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

Azim, Riyasat; Li, Fangxing; Xue, Yaosuo

Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only whenmore » the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.« less

Accounting for unintended binding events in the analysis of quartz crystal microbalance kinetic data.

PubMed

Heller, Gabriella T; Zwang, Theodore J; Sarapata, Elizabeth A; Haber, Michael A; Sazinsky, Matthew H; Radunskaya, Ami E; Johal, Malkiat S

2014-05-01

Previous methods for analyzing protein-ligand binding events using the quartz crystal microbalance with dissipation monitoring (QCM-D) fail to account for unintended binding that inevitably occurs during surface measurements and obscure kinetic information. In this article, we present a system of differential equations that accounts for both reversible and irreversible unintended interactions. This model is tested on three protein-ligand systems, each of which has different features, to establish the feasibility of using the QCM-D for protein binding analysis. Based on this analysis, we were able to obtain kinetic information for the intended interaction that is consistent with those obtained in literature via bulk-phase methods. In the appendix, we include a method for decoupling these from the intended binding events and extracting relevant affinity information. Copyright © 2014 Elsevier B.V. All rights reserved.

Research on Crowdsourcing Emergency Information Extraction of Based on Events' Frame

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Jizhou; Ma, Weijun; Mao, Xi

2018-01-01

At present, the common information extraction method cannot extract the structured emergency event information accurately; the general information retrieval tool cannot completely identify the emergency geographic information; these ways also do not have an accurate assessment of these results of distilling. So, this paper proposes an emergency information collection technology based on event framework. This technique is to solve the problem of emergency information picking. It mainly includes emergency information extraction model (EIEM), complete address recognition method (CARM) and the accuracy evaluation model of emergency information (AEMEI). EIEM can be structured to extract emergency information and complements the lack of network data acquisition in emergency mapping. CARM uses a hierarchical model and the shortest path algorithm and allows the toponomy pieces to be joined as a full address. AEMEI analyzes the results of the emergency event and summarizes the advantages and disadvantages of the event framework. Experiments show that event frame technology can solve the problem of emergency information drawing and provides reference cases for other applications. When the emergency disaster is about to occur, the relevant departments query emergency's data that has occurred in the past. They can make arrangements ahead of schedule which defense and reducing disaster. The technology decreases the number of casualties and property damage in the country and world. This is of great significance to the state and society.

Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic web technologies.

PubMed

Jiang, Guoqian; Wang, Liwei; Liu, Hongfang; Solbrig, Harold R; Chute, Christopher G

2013-01-01

A semantically coded knowledge base of adverse drug events (ADEs) with severity information is critical for clinical decision support systems and translational research applications. However it remains challenging to measure and identify the severity information of ADEs. The objective of the study is to develop and evaluate a semantic web based approach for building a knowledge base of severe ADEs based on the FDA Adverse Event Reporting System (AERS) reporting data. We utilized a normalized AERS reporting dataset and extracted putative drug-ADE pairs and their associated outcome codes in the domain of cardiac disorders. We validated the drug-ADE associations using ADE datasets from SIDe Effect Resource (SIDER) and the UMLS. We leveraged the Common Terminology Criteria for Adverse Event (CTCAE) grading system and classified the ADEs into the CTCAE in the Web Ontology Language (OWL). We identified and validated 2,444 unique Drug-ADE pairs in the domain of cardiac disorders, of which 760 pairs are in Grade 5, 775 pairs in Grade 4 and 2,196 pairs in Grade 3.

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Proxy records of Holocene storm events in coastal barrier systems: Storm-wave induced markers

NASA Astrophysics Data System (ADS)

Goslin, Jérôme; Clemmensen, Lars B.

2017-10-01

Extreme storm events in the coastal zone are one of the main forcing agents of short-term coastal system behavior. As such, storms represent a major threat to human activities concentrated along the coasts worldwide. In order to better understand the frequency of extreme events like storms, climate science must rely on longer-time records than the century-scale records of instrumental weather data. Proxy records of storm-wave or storm-wind induced activity in coastal barrier systems deposits have been widely used worldwide in recent years to document past storm events during the last millennia. This review provides a detailed state-of-the-art compilation of the proxies available from coastal barrier systems to reconstruct Holocene storm chronologies (paleotempestology). The present paper aims (I) to describe the erosional and depositional processes caused by storm-wave action in barrier and back-barrier systems (i.e. beach ridges, storm scarps and washover deposits), (ii) to understand how storm records can be extracted from barrier and back-barrier sedimentary bodies using stratigraphical, sedimentological, micro-paleontological and geochemical proxies and (iii) to show how to obtain chronological control on past storm events recorded in the sedimentary successions. The challenges that paleotempestology studies still face in the reconstruction of representative and reliable storm-chronologies using these various proxies are discussed, and future research prospects are outlined.

Applications of KHZ-CW Lidar in Ecological Entomology

NASA Astrophysics Data System (ADS)

Malmqvist, Elin; Brydegaard, Mikkel

2016-06-01

The benefits of kHz lidar in ecological entomology are explained. Results from kHz-measurements on insects, carried out with a CW-lidar system, employing the Scheimpflug principle to obtain range resolution, are presented. A method to extract insect events and analyze the large amount of lidar data is also described.

Extracting the Textual and Temporal Structure of Supercomputing Logs

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

Jain, S; Singh, I; Chandra, A

2009-05-26

Supercomputers are prone to frequent faults that adversely affect their performance, reliability and functionality. System logs collected on these systems are a valuable resource of information about their operational status and health. However, their massive size, complexity, and lack of standard format makes it difficult to automatically extract information that can be used to improve system management. In this work we propose a novel method to succinctly represent the contents of supercomputing logs, by using textual clustering to automatically find the syntactic structures of log messages. This information is used to automatically classify messages into semantic groups via an onlinemore » clustering algorithm. Further, we describe a methodology for using the temporal proximity between groups of log messages to identify correlated events in the system. We apply our proposed methods to two large, publicly available supercomputing logs and show that our technique features nearly perfect accuracy for online log-classification and extracts meaningful structural and temporal message patterns that can be used to improve the accuracy of other log analysis techniques.« less

Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

NASA Astrophysics Data System (ADS)

Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

2018-04-01

To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

Adaptive neuro-fuzzy inference systems for semi-automatic discrimination between seismic events: a study in Tehran region

NASA Astrophysics Data System (ADS)

Vasheghani Farahani, Jamileh; Zare, Mehdi; Lucas, Caro

2012-04-01

Thisarticle presents an adaptive neuro-fuzzy inference system (ANFIS) for classification of low magnitude seismic events reported in Iran by the network of Tehran Disaster Mitigation and Management Organization (TDMMO). ANFIS classifiers were used to detect seismic events using six inputs that defined the seismic events. Neuro-fuzzy coding was applied using the six extracted features as ANFIS inputs. Two types of events were defined: weak earthquakes and mining blasts. The data comprised 748 events (6289 signals) ranging from magnitude 1.1 to 4.6 recorded at 13 seismic stations between 2004 and 2009. We surveyed that there are almost 223 earthquakes with M ≤ 2.2 included in this database. Data sets from the south, east, and southeast of the city of Tehran were used to evaluate the best short period seismic discriminants, and features as inputs such as origin time of event, distance (source to station), latitude of epicenter, longitude of epicenter, magnitude, and spectral analysis (fc of the Pg wave) were used, increasing the rate of correct classification and decreasing the confusion rate between weak earthquakes and quarry blasts. The performance of the ANFIS model was evaluated for training and classification accuracy. The results confirmed that the proposed ANFIS model has good potential for determining seismic events.

Reaction Event Counting Statistics of Biopolymer Reaction Systems with Dynamic Heterogeneity.

PubMed

Lim, Yu Rim; Park, Seong Jun; Park, Bo Jung; Cao, Jianshu; Silbey, Robert J; Sung, Jaeyoung

2012-04-10

We investigate the reaction event counting statistics (RECS) of an elementary biopolymer reaction in which the rate coefficient is dependent on states of the biopolymer and the surrounding environment and discover a universal kinetic phase transition in the RECS of the reaction system with dynamic heterogeneity. From an exact analysis for a general model of elementary biopolymer reactions, we find that the variance in the number of reaction events is dependent on the square of the mean number of the reaction events when the size of measurement time is small on the relaxation time scale of rate coefficient fluctuations, which does not conform to renewal statistics. On the other hand, when the size of the measurement time interval is much greater than the relaxation time of rate coefficient fluctuations, the variance becomes linearly proportional to the mean reaction number in accordance with renewal statistics. Gillespie's stochastic simulation method is generalized for the reaction system with a rate coefficient fluctuation. The simulation results confirm the correctness of the analytic results for the time dependent mean and variance of the reaction event number distribution. On the basis of the obtained results, we propose a method of quantitative analysis for the reaction event counting statistics of reaction systems with rate coefficient fluctuations, which enables one to extract information about the magnitude and the relaxation times of the fluctuating reaction rate coefficient, without a bias that can be introduced by assuming a particular kinetic model of conformational dynamics and the conformation dependent reactivity. An exact relationship is established between a higher moment of the reaction event number distribution and the multitime correlation of the reaction rate for the reaction system with a nonequilibrium initial state distribution as well as for the system with the equilibrium initial state distribution.

Installation Restoration Program (IRP) Stage 3, Operable Unit B engineering Evaluation/Cost Analysis - Environmental Assessment for McClellan AFB/EM, McClellan AFB, California

DTIC Science & Technology

1990-12-01

Force ......,,...Human Systems Division (AFSC) .................. . . .. . . RP Pr ra -Offic (HSDIYAO) .............. ........... Brooks Air Force...intra- system piping. Six months to one year would be required to complete and integrate these components. EECA/021491/jlh 6-39 RADIAN COlVOR AT 1O IN... system capacity has been exceeded. It is a possibility that during severe storm events, the groundwater extraction wells will be shut down to avoid

Psychiatric disorders, acne and systemic retinoids: comparison of risks.

PubMed

Le Moigne, M; Bulteau, S; Grall-Bronnec, Marie; Gerardin, M; Fournier, Jean-Pascal; Jonville-Bera, A P; Jolliet, Pascale; Dreno, Brigitte; Victorri-Vigneau, C

2017-09-01

The link between isotretinoin, treatment of a severe form of acne, and psychiatric disorders remains controversial, as acne itself could explain the occurrence of psychiatric disorders. This study aims at assessing the disproportionality of psychiatric adverse events reported with isotretinoin in the French National PharmacoVigilance Database, compared with other systemic acne treatments and systemic retinoids. Data were extracted from the French National PharmacoVigilance Database for systemic acne treatments, systemic retinoids and drugs used as comparators. Each report was subjected to double-blind analysis by two psychiatric experts. A disproportionality analysis was performed, calculating the number of psychiatric ADRs divided by the total number of notifications for each drug of interest. Concerning acne systemic treatments: all 71 reports of severe psychiatric disorders involved isotretinoin, the highest proportion of mild/moderate psychiatric adverse events was reported with isotretinoin (14.1%). Among systemic retinoids, the highest proportion of severe and mild/moderate psychiatric events occurred with isotretinoin and alitretinoin. Our study raises the hypothesis that psychiatric disorders associated with isotretinoin are related to a class effect of retinoids, as a signal emerges for alitretinoin. Complementary studies are necessary to estimate the risk and further determine at-risk populations.

EventThread: Visual Summarization and Stage Analysis of Event Sequence Data.

PubMed

Guo, Shunan; Xu, Ke; Zhao, Rongwen; Gotz, David; Zha, Hongyuan; Cao, Nan

2018-01-01

Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analysis might reveal frequently used care plans for treating a disease, typical publishing patterns of professors, and the patterns of service that result in a well-maintained car. It is challenging, however, to visually explore large numbers of event sequences, or sequences with large numbers of event types. Existing methods focus on extracting explicitly matching patterns of events using statistical analysis to create stages of event progression over time. However, these methods fail to capture latent clusters of similar but not identical evolutions of event sequences. In this paper, we introduce a novel visualization system named EventThread which clusters event sequences into threads based on tensor analysis and visualizes the latent stage categories and evolution patterns by interactively grouping the threads by similarity into time-specific clusters. We demonstrate the effectiveness of EventThread through usage scenarios in three different application domains and via interviews with an expert user.

System and method for generating micro-seismic events and characterizing properties of a medium with non-linear acoustic interactions

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

Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A.

2015-12-29

A method and system includes generating a first coded acoustic signal including pulses each having a modulated signal at a central frequency; and a second coded acoustic signal each pulse of which includes a modulated signal a central frequency of which is a fraction d of the central frequency of the modulated signal for the corresponding pulse in the first plurality of pulses. A receiver detects a third signal generated by a non-linear mixing process in the mixing zone and the signal is processed to extract the third signal to obtain an emulated micro-seismic event signal occurring at the mixingmore » zone; and to characterize properties of the medium or creating a 3D image of the properties of the medium, or both, based on the emulated micro-seismic event signal.« less

monitoring la Soufrière de Guadeloupe phreatic system with muon tomography

NASA Astrophysics Data System (ADS)

Jourde, Kevin; Gibert, Dominique; Marteau, Jacques; de Bremond d'Ars, Jean; Ianigro, Jean-Christophe; Gardien, Serge; Girerd, Claude

2015-04-01

Muon tomography is a novel geophysics imaging technique that measures the flux of cosmic muons crossing geological bodies. Its attenuation is directly related to their thickness and density. On la Soufrière de Guadeloupe volcano, we could extract tiny particle flux fluctuations from the tomography signal of long-term acquisitions (a few months). We prove that atmospheric fluctuations or solar activity, which are the usual candidates for cosmic particles time modulations, cannot explain these changes leaving the volcanic dome phreatic system as the only explanation. Moreover the temporal trends we extracted from the different observation axes of our instrument show a good spatial and temporal correlation with events occuring at the surface of the volcano.

Liver-related safety assessment of green tea extracts in humans: a systematic review of randomized controlled trials

PubMed Central

Isomura, T; Suzuki, S; Origasa, H; Hosono, A; Suzuki, M; Sawada, T; Terao, S; Muto, Y; Koga, T

2016-01-01

There remain liver-related safety concerns, regarding potential hepatotoxicity in humans, induced by green tea intake, despite being supposedly beneficial. Although many randomized controlled trials (RCTs) of green tea extracts have been reported in the literature, the systematic reviews published to date were only based on subjective assessment of case reports. To more objectively examine the liver-related safety of green tea intake, we conducted a systematic review of published RCTs. A systematic literature search was conducted using three databases (PubMed, EMBASE and Cochrane Central Register of Controlled Trials) in December 2013 to identify RCTs of green tea extracts. Data on liver-related adverse events, including laboratory test abnormalities, were abstracted from the identified articles. Methodological quality of RCTs was assessed. After excluding duplicates, 561 titles and abstracts and 119 full-text articles were screened, and finally 34 trials were identified. Of these, liver-related adverse events were reported in four trials; these adverse events involved seven subjects (eight events) in the green tea intervention group and one subject (one event) in the control group. The summary odds ratio, estimated using a meta-analysis method for sparse event data, for intervention compared with placebo was 2.1 (95% confidence interval: 0.5–9.8). The few events reported in both groups were elevations of liver enzymes. Most were mild, and no serious liver-related adverse events were reported. Results of this review, although not conclusive, suggest that liver-related adverse events after intake of green tea extracts are expected to be rare. PMID:27188915

Artillery/mortar round type classification to increase system situational awareness

NASA Astrophysics Data System (ADS)

Desai, Sachi; Grasing, David; Morcos, Amir; Hohil, Myron

2008-04-01

Feature extraction methods based on the statistical analysis of the change in event pressure levels over a period and the level of ambient pressure excitation facilitate the development of a robust classification algorithm. The features reliably discriminates mortar and artillery variants via acoustic signals produced during the launch events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants as type A, etcetera through analysis of the waveform. Distinct characteristics arise within the different mortar/artillery variants because varying HE mortar payloads and related charges emphasize varying size events at launch. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing and data mining techniques can employed to classify a given type. The skewness and other statistical processing techniques are used to extract the predominant components from the acoustic signatures at ranges exceeding 3000m. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of statistical coefficients, frequency spectrum, and higher frequency details found within different energy bands. The processes that are described herein extend current technologies, which emphasis acoustic sensor systems to provide such situational awareness.

Adverse events reported to the Food and Drug Administration from 2004 to 2016 for cosmetics and personal care products marketed to newborns and infants.

PubMed

Cornell, Erika; Kwa, Michael; Paller, Amy S; Xu, Shuai

2018-03-01

Despite their ubiquitous use and several recent health controversies involving cosmetics and personal care products for children, the Food and Drug Administration has little oversight of these products and relies on consumer-submitted adverse event reports. We assessed the recently released Center for Food Safety and Applied Nutrition's Adverse Event Reporting System database for adverse event reports submitted to the Food and Drug Administration for baby personal care products and to determine whether useful insights can be derived. We extracted the Center for Food Safety and Applied Nutrition's Adverse Event Reporting System data file from 2004 to 2016 and examined the subset classified according to the Food and Drug Administration-designated product class as a baby product. Events were manually categorized into product type and symptom type to assess for trends. Only 166 total adverse events were reported to the Food and Drug Administration for baby products from 2004 to 2016. The majority of reports indicated rash or other skin reaction; 46% of reported events led to a health care visit. Pediatric dermatologists should consider submitting cosmetics and personal care product adverse event reports and encouraging consumers to do so likewise in situations in which a product adversely affects a child's health. © 2018 Wiley Periodicals, Inc.

A framework for collaborative review of candidate events in high data rate streams: The V-FASTR experiment as a case study

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

Hart, Andrew F.; Cinquini, Luca; Khudikyan, Shakeh E.

2015-01-01

“Fast radio transients” are defined here as bright millisecond pulses of radio-frequency energy. These short-duration pulses can be produced by known objects such as pulsars or potentially by more exotic objects such as evaporating black holes. The identification and verification of such an event would be of great scientific value. This is one major goal of the Very Long Baseline Array (VLBA) Fast Transient Experiment (V-FASTR), a software-based detection system installed at the VLBA. V-FASTR uses a “commensal” (piggy-back) approach, analyzing all array data continually during routine VLBA observations and identifying candidate fast transient events. Raw data can be storedmore » from a buffer memory, which enables a comprehensive off-line analysis. This is invaluable for validating the astrophysical origin of any detection. Candidates discovered by the automatic system must be reviewed each day by analysts to identify any promising signals that warrant a more in-depth investigation. To support the timely analysis of fast transient detection candidates by V-FASTR scientists, we have developed a metadata-driven, collaborative candidate review framework. The framework consists of a software pipeline for metadata processing composed of both open source software components and project-specific code written expressly to extract and catalog metadata from the incoming V-FASTR data products, and a web-based data portal that facilitates browsing and inspection of the available metadata for candidate events extracted from the VLBA radio data.« less

Acoustic signature recognition technique for Human-Object Interactions (HOI) in persistent surveillance systems

NASA Astrophysics Data System (ADS)

Alkilani, Amjad; Shirkhodaie, Amir

2013-05-01

Handling, manipulation, and placement of objects, hereon called Human-Object Interaction (HOI), in the environment generate sounds. Such sounds are readily identifiable by the human hearing. However, in the presence of background environment noises, recognition of minute HOI sounds is challenging, though vital for improvement of multi-modality sensor data fusion in Persistent Surveillance Systems (PSS). Identification of HOI sound signatures can be used as precursors to detection of pertinent threats that otherwise other sensor modalities may miss to detect. In this paper, we present a robust method for detection and classification of HOI events via clustering of extracted features from training of HOI acoustic sound waves. In this approach, salient sound events are preliminary identified and segmented from background via a sound energy tracking method. Upon this segmentation, frequency spectral pattern of each sound event is modeled and its features are extracted to form a feature vector for training. To reduce dimensionality of training feature space, a Principal Component Analysis (PCA) technique is employed to expedite fast classification of test feature vectors, a kd-tree and Random Forest classifiers are trained for rapid classification of training sound waves. Each classifiers employs different similarity distance matching technique for classification. Performance evaluations of classifiers are compared for classification of a batch of training HOI acoustic signatures. Furthermore, to facilitate semantic annotation of acoustic sound events, a scheme based on Transducer Mockup Language (TML) is proposed. The results demonstrate the proposed approach is both reliable and effective, and can be extended to future PSS applications.

Creative Analytics of Mission Ops Event Messages

NASA Technical Reports Server (NTRS)

Smith, Dan

2017-01-01

Historically, tremendous effort has been put into processing and displaying mission health and safety telemetry data; and relatively little attention has been paid to extracting information from missions time-tagged event log messages. Todays missions may log tens of thousands of messages per day and the numbers are expected to dramatically increase as satellite fleets and constellations are launched, as security monitoring continues to evolve, and as the overall complexity of ground system operations increases. The logs may contain information about orbital events, scheduled and actual observations, device status and anomalies, when operators were logged on, when commands were resent, when there were data drop outs or system failures, and much much more. When dealing with distributed space missions or operational fleets, it becomes even more important to systematically analyze this data. Several advanced information systems technologies make it appropriate to now develop analytic capabilities which can increase mission situational awareness, reduce mission risk, enable better event-driven automation and cross-mission collaborations, and lead to improved operations strategies: Industry Standard for Log Messages. The Object Management Group (OMG) Space Domain Task Force (SDTF) standards organization is in the process of creating a formal standard for industry for event log messages. The format is based on work at NASA GSFC. Open System Architectures. The DoD, NASA, and others are moving towards common open system architectures for mission ground data systems based on work at NASA GSFC with the full support of the commercial product industry and major integration contractors. Text Analytics. A specific area of data analytics which applies statistical, linguistic, and structural techniques to extract and classify information from textual sources. This presentation describes work now underway at NASA to increase situational awareness through the collection of non-telemetry mission operations information into a common log format and then providing display and analytics tools to provide in-depth assessment of the log contents. The work includes: Common interface formats for acquiring time-tagged text messages Conversion of common files for schedules, orbital events, and stored commands to the common log format Innovative displays to depict thousands of messages on a single display Structured English text queries against the log message data store, extensible to a more mature natural language query capability Goal of speech-to-text and text-to-speech additions to create a personal mission operations assistant to aid on-console operations. A wide variety of planned uses identified by the mission operations teams will be discussed.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment.

PubMed

Besmer, Michael D; Epting, Jannis; Page, Rebecca M; Sigrist, Jürg A; Huggenberger, Peter; Hammes, Frederik

2016-12-07

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL -1 . The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

PubMed Central

Besmer, Michael D.; Epting, Jannis; Page, Rebecca M.; Sigrist, Jürg A.; Huggenberger, Peter; Hammes, Frederik

2016-01-01

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL−1. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems. PMID:27924920

Renewal Processes in the Critical Brain

NASA Astrophysics Data System (ADS)

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Gemignani, Angelo

We describe herein a multidisciplinary research, as it developes and applies concepts of the theory of complexity, in turn stemming from recent advancements of statistical physics, onto cognitive neuroscience. We discuss (define) complexity, and how the human brain is a paradigm of it. We discuss how the hypothesis of brain activity dynamically behaving as a critical system is taking momentum in literature, then we focus on a feature of critical systems (hence of the brain), which is the intermittent passage between metastable states, marked by events, locally resetting the memory, but giving rise to correlation functions with infinite correlation times. The events, extracted from multi-channel ElectroEncephaloGrams, mark (are interpreted as) a birth/death process of cooperation, namely of system elements being recruited into collective states. Finally we discuss a recently discovered form of control (in the form of a new Linear Response Theory), that allows an optimized information transmission between complex systems, named Complexity Matching.

Stochastic modeling of total suspended solids (TSS) in urban areas during rain events.

PubMed

Rossi, Luca; Krejci, Vladimir; Rauch, Wolfgang; Kreikenbaum, Simon; Fankhauser, Rolf; Gujer, Willi

2005-10-01

The load of total suspended solids (TSS) is one of the most important parameters for evaluating wet-weather pollution in urban sanitation systems. In fact, pollutants such as heavy metals, polycyclic aromatic hydrocarbons (PAHs), phosphorous and organic compounds are adsorbed onto these particles so that a high TSS load indicates the potential impact on the receiving waters. In this paper, a stochastic model is proposed to estimate the TSS load and its dynamics during rain events. Information on the various simulated processes was extracted from different studies of TSS in urban areas. The model thus predicts the probability of TSS loads arising from combined sewer overflows (CSOs) in combined sewer systems as well as from stormwater in separate sewer systems in addition to the amount of TSS retained in treatment devices in both sewer systems. The results of this TSS model illustrate the potential of the stochastic modeling approach for assessing environmental problems.

OSA severity assessment based on sleep breathing analysis using ambient microphone.

PubMed

Dafna, E; Tarasiuk, A; Zigel, Y

2013-01-01

In this paper, an audio-based system for severity estimation of obstructive sleep apnea (OSA) is proposed. The system estimates the apnea-hypopnea index (AHI), which is the average number of apneic events per hour of sleep. This system is based on a Gaussian mixture regression algorithm that was trained and validated on full-night audio recordings. Feature selection process using a genetic algorithm was applied to select the best features extracted from time and spectra domains. A total of 155 subjects, referred to in-laboratory polysomnography (PSG) study, were recruited. Using the PSG's AHI score as a gold-standard, the performances of the proposed system were evaluated using a Pearson correlation, AHI error, and diagnostic agreement methods. Correlation of R=0.89, AHI error of 7.35 events/hr, and diagnostic agreement of 77.3% were achieved, showing encouraging performances and a reliable non-contact alternative method for OSA severity estimation.

A highly efficient, cell-free translation/translocation system prepared from Xenopus eggs.

PubMed Central

Matthews, G; Colman, A

1991-01-01

We describe the use of a Xenopus laevis egg extract for the in vitro translation and post translational modification of membrane and secretory proteins. This extract is capable of the translation and segregation into membranes of microgram per millilitre levels of protein from added mRNAs. Signal sequences of segregated proteins are efficiently cleaved and appropriate N-linked glycosylation patterns are produced. The extract also supports the quantitative assembly of murine immunoglobulin heavy and light chains into tetramers, and two events which take place beyond the endoplasmic reticulum, mannose 6 phosphorylation of murine cathepsin D and O-linked glycosylation of coronavirus E1 protein, also occur, but at reduced efficiency. The stability of the membranes allows protease protection studies and quantitative centrifugal fractionation of segregated and unsegregated proteins to be performed. Conditions for the use of stored extract have also been determined. Images PMID:1754376

Embedded security system for multi-modal surveillance in a railway carriage

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

2015-10-01

Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

Chronodes: Interactive Multifocus Exploration of Event Sequences

PubMed Central

POLACK, PETER J.; CHEN, SHANG-TSE; KAHNG, MINSUK; DE BARBARO, KAYA; BASOLE, RAHUL; SHARMIN, MOUSHUMI; CHAU, DUEN HORNG

2018-01-01

The advent of mobile health (mHealth) technologies challenges the capabilities of current visualizations, interactive tools, and algorithms. We present Chronodes, an interactive system that unifies data mining and human-centric visualization techniques to support explorative analysis of longitudinal mHealth data. Chronodes extracts and visualizes frequent event sequences that reveal chronological patterns across multiple participant timelines of mHealth data. It then combines novel interaction and visualization techniques to enable multifocus event sequence analysis, which allows health researchers to interactively define, explore, and compare groups of participant behaviors using event sequence combinations. Through summarizing insights gained from a pilot study with 20 behavioral and biomedical health experts, we discuss Chronodes’s efficacy and potential impact in the mHealth domain. Ultimately, we outline important open challenges in mHealth, and offer recommendations and design guidelines for future research. PMID:29515937

Antenna Measurements: Test & Analysis of the Radiated Emissions from the NASA/Orion Spacecraft - Parachute System Simulator

NASA Technical Reports Server (NTRS)

Norgard, John D.

2012-01-01

For future NASA Manned Space Exploration of the Moon and Mars, a blunt body capsule, called the Orion Crew Exploration Vehicle (CEV), composed of a Crew Module (CM) and a Service Module (SM), with a parachute decent assembly is planned for reentry back to Earth. A Capsule Parachute Assembly System (CPAS) is being developed for preliminary parachute drop tests at the Yuma Proving Ground (YPG) to simulate high-speed reentry to Earth from beyond Low-Earth-Orbit (LEO) and to provide measurements of landing parameters and parachute loads. The avionics systems on CPAS also provide mission critical firing events to deploy, reef, and release the parachutes in three stages (extraction, drogues, mains) using mortars and pressure cartridge assemblies. In addition, a Mid-Air Delivery System (MDS) is used to separate the capsule from the sled that is used to eject the capsule from the back of the drop plane. Also, high-speed and high-definition cameras in a Video Camera System (VCS) are used to film the drop plane extraction and parachute landing events. To verify Electromagnetic Compatibility (EMC) of the CPAS system from unintentional radiation, Electromagnetic Interference (EMI) measurements are being made inside a semi-anechoic chamber at NASA/JSC at 1m from the electronic components of the CPAS system. In addition, EMI measurements of the integrated CPAS system are being made inside a hanger at YPG. These near-field B-Dot probe measurements on the surface of a parachute simulator (DART) are being extrapolated outward to the 1m standard distance for comparison to the MIL-STD radiated emissions limit.

Visual traffic jam analysis based on trajectory data.

PubMed

Wang, Zuchao; Lu, Min; Yuan, Xiaoru; Zhang, Junping; van de Wetering, Huub

2013-12-01

In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.

Cataloging the biomedical world of pain through semi-automated curation of molecular interactions

PubMed Central

Jamieson, Daniel G.; Roberts, Phoebe M.; Robertson, David L.; Sidders, Ben; Nenadic, Goran

2013-01-01

The vast collection of biomedical literature and its continued expansion has presented a number of challenges to researchers who require structured findings to stay abreast of and analyze molecular mechanisms relevant to their domain of interest. By structuring literature content into topic-specific machine-readable databases, the aggregate data from multiple articles can be used to infer trends that can be compared and contrasted with similar findings from topic-independent resources. Our study presents a generalized procedure for semi-automatically creating a custom topic-specific molecular interaction database through the use of text mining to assist manual curation. We apply the procedure to capture molecular events that underlie ‘pain’, a complex phenomenon with a large societal burden and unmet medical need. We describe how existing text mining solutions are used to build a pain-specific corpus, extract molecular events from it, add context to the extracted events and assess their relevance. The pain-specific corpus contains 765 692 documents from Medline and PubMed Central, from which we extracted 356 499 unique normalized molecular events, with 261 438 single protein events and 93 271 molecular interactions supplied by BioContext. Event chains are annotated with negation, speculation, anatomy, Gene Ontology terms, mutations, pain and disease relevance, which collectively provide detailed insight into how that event chain is associated with pain. The extracted relations are visualized in a wiki platform (wiki-pain.org) that enables efficient manual curation and exploration of the molecular mechanisms that underlie pain. Curation of 1500 grouped event chains ranked by pain relevance revealed 613 accurately extracted unique molecular interactions that in the future can be used to study the underlying mechanisms involved in pain. Our approach demonstrates that combining existing text mining tools with domain-specific terms and wiki-based visualization can facilitate rapid curation of molecular interactions to create a custom database. Database URL: ••• PMID:23707966

Cataloging the biomedical world of pain through semi-automated curation of molecular interactions.

PubMed

Jamieson, Daniel G; Roberts, Phoebe M; Robertson, David L; Sidders, Ben; Nenadic, Goran

2013-01-01

The vast collection of biomedical literature and its continued expansion has presented a number of challenges to researchers who require structured findings to stay abreast of and analyze molecular mechanisms relevant to their domain of interest. By structuring literature content into topic-specific machine-readable databases, the aggregate data from multiple articles can be used to infer trends that can be compared and contrasted with similar findings from topic-independent resources. Our study presents a generalized procedure for semi-automatically creating a custom topic-specific molecular interaction database through the use of text mining to assist manual curation. We apply the procedure to capture molecular events that underlie 'pain', a complex phenomenon with a large societal burden and unmet medical need. We describe how existing text mining solutions are used to build a pain-specific corpus, extract molecular events from it, add context to the extracted events and assess their relevance. The pain-specific corpus contains 765 692 documents from Medline and PubMed Central, from which we extracted 356 499 unique normalized molecular events, with 261 438 single protein events and 93 271 molecular interactions supplied by BioContext. Event chains are annotated with negation, speculation, anatomy, Gene Ontology terms, mutations, pain and disease relevance, which collectively provide detailed insight into how that event chain is associated with pain. The extracted relations are visualized in a wiki platform (wiki-pain.org) that enables efficient manual curation and exploration of the molecular mechanisms that underlie pain. Curation of 1500 grouped event chains ranked by pain relevance revealed 613 accurately extracted unique molecular interactions that in the future can be used to study the underlying mechanisms involved in pain. Our approach demonstrates that combining existing text mining tools with domain-specific terms and wiki-based visualization can facilitate rapid curation of molecular interactions to create a custom database. Database URL: •••

Investigation of the use of various plant extracts activity in ruminant

NASA Astrophysics Data System (ADS)

Yüca, Songül; Gül, Mehmet; Ćaǧlayan, Alper

2016-04-01

The prohibition of the use of antibiotics and as a result of the adverse effect on health of synthetic products, research has focused on natural feed additives. In recent years, the diet of farm animals many feed additives have been used for various purposes or continues. These include as used in ruminant rations as plant extract thyme, anise, pepper, mint, garlic, rosemary, cinnamon, parsley, bay leaf, coconut, like used herbal extracts and their effects on the performance of ruminants was investigated. Antioxidant, antifungal, antiviral, anti-inflamaotry is known to have effects of plant extract. By stimulating the digestive system of ruminants, they increase the activity of digestive enzymes, to prevent environmental pollution caused by manure, regulations rumen fermentation, inhibition of methane formation and protein degradability in the rumen as well as the animal is known to have many benefits. The structure of essential oils and plant extracts in this collection, examining the use of ruminant livestock events and the importance of the use in animal nutrition into practice will be discussed.

Extraction of AE events to estimate their b values under a triaxial compressive condition Examination using continuous broadband records

NASA Astrophysics Data System (ADS)

Yoneda, N.; Kawakata, H.; Hirano, S.; Yoshimitsu, N.; Takahashi, N.

2017-12-01

Seismic b values estimated in previous laboratory compressive tests had been utilized for natural earthquake studies. Randomly sampled enough number of events over a wide magnitude range are essential for accurate b value estimation. In former triaxial tests, PZTs had sensitivity only in a narrow frequency range. In addition, the recording system could not extract all signals because of mask times or threshold setting. Recently, Yoshimitsu et al. (2014) enabled to use broadband transducers under triaxial conditions and achieved to acquire waveforms continuously in several hours. With such a system, they estimated the seismic moment of AE at very small magnitude scale. We expected that their continuous broadband recording system made it possible to record much more AE with a wider magnitude range for credible b value estimation in a laboratory. In this study, we performed a compressive test under a higher confining pressure as an updated experiment of Yoshimitsu et al. (2014) and extracted an enough amount of AE. We prepared an intact cylindrical Westerly Granite sample, 100 mm long by 50 mm in diameter. We conducted a triaxial compressive test under a confining pressure of 50 MPa, at a room temperature with drying conditions. Seven broadband transducers (sensitive range; 100 kHz - 1,000 kHz) were located in different height, respectively. Besides, a PZT was mounted to transmit elastic waves for velocity estimation during the experiment. At first, we increased the confining pressure and then started the loading. We switched the load control method from the axial load control to the circumferential displacement one. After exceeding the peak stress, compressive stress was unloaded with a high speed and the sample was recovered. A potential fault was observed on the recovered sample surface. Waveform recording was continued throughout the test for more than 200 minutes. The result of extracting signals by an STA/LTA ratio method for the waveforms recorded by each transducer, we detected about 2,170,000 signals at the most and about 450,000 at the minimum. Recorded waveforms may also include the elastic waves from the PZT and electrical noises. To find the combination of the signals derived from the same event, we used the largest differences in travel times for all transducer pairs. Finally, we obtained about 450,000 combinations.

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

PubMed

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

2017-12-20

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

Emergency Medical Considerations in a Space-Suited Patient.

PubMed

Garbino, Alejandro; Nusbaum, Derek M; Buckland, Daniel M; Menon, Anil S; Clark, Jonathan B; Antonsen, Erik L

The Stratex Project is a high altitude balloon flight that culminated in a freefall from 41,422 m (135,890 ft), breaking the record for the highest freefall to date. Crew recovery operations required an innovative approach due to the unique nature of the event as well as the equipment involved. The parachutist donned a custom space suit similar to a NASA Extravehicular Mobility Unit (EMU), with life support system mounted to the front and a parachute on the back. This space suit had a metal structure around the torso, which, in conjunction with the parachute and life support assembly, created a significant barrier to extraction from the suit in the event of a medical emergency. For this reason the Medical Support Team coordinated with the pressure suit assembly engineer team for integration, training in suit removal, definition of a priori contingency leadership on site, creation of color-coded extraction scenarios, and extraction drills with a suit mock-up that provided insight into limitations to immediate access. This paper discusses novel extraction processes and contrasts the required medical preparation for this type of equipment with the needs of the prior record-holding jump that used a different space suit with easier immediate access. Garbino A, Nusbaum DM, Buckland DM, Menon AS, Clark JB, Antonsen EL. Emergency medical considerations in a space-suited patient. Aerosp Med Hum Perform. 2016; 87(11):958-962.

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

Extraction-Separation Performance and Dynamic Modeling of Orion Test Vehicles with Adams Simulation: 2nd Edition

NASA Technical Reports Server (NTRS)

Fraire, Usbaldo, Jr.; Anderson, Keith; Varela, Jose G.; Bernatovich, Michael A.

2015-01-01

NASA's Orion Capsule Parachute Assembly System (CPAS) project has advanced into the third generation of its parachute test campaign and requires technically comprehensive modeling capabilities to simulate multi-body dynamics (MBD) of test articles released from a C-17. Safely extracting a 30,000 lbm mated test article from a C-17 and performing stable mid-air separation maneuvers requires an understanding of the interaction between elements in the test configuration and how they are influenced by extraction parachute performance, aircraft dynamics, aerodynamics, separation dynamics, and kinetic energy experienced by the system. During the real-time extraction and deployment sequences, these influences can be highly unsteady and difficult to bound. An avionics logic window based on time, pitch, and pitch rate is used to account for these effects and target a favorable separation state in real time. The Adams simulation has been employed to fine-tune this window, as well as predict and reconstruct the coupled dynamics of the Parachute Test Vehicle (PTV) and Cradle Platform Separation System (CPSS) from aircraft extraction through the mid-air separation event. The test-technique for the extraction of CPAS test articles has evolved with increased complexity and requires new modeling concepts to ensure the test article is delivered to a stable test condition for the programmer phase. Prompted by unexpected dynamics and hardware malfunctions in drop tests, these modeling improvements provide a more accurate loads prediction by incorporating a spring-damper line-model derived from the material properties. The qualification phase of CPAS testing is on the horizon and modeling increasingly complex test-techniques with Adams is vital to successfully qualify the Orion parachute system for human spaceflight.

Identification and Progression of Heart Disease Risk Factors in Diabetic Patients from Longitudinal Electronic Health Records.

PubMed

Jonnagaddala, Jitendra; Liaw, Siaw-Teng; Ray, Pradeep; Kumar, Manish; Dai, Hong-Jie; Hsu, Chien-Yeh

2015-01-01

Heart disease is the leading cause of death worldwide. Therefore, assessing the risk of its occurrence is a crucial step in predicting serious cardiac events. Identifying heart disease risk factors and tracking their progression is a preliminary step in heart disease risk assessment. A large number of studies have reported the use of risk factor data collected prospectively. Electronic health record systems are a great resource of the required risk factor data. Unfortunately, most of the valuable information on risk factor data is buried in the form of unstructured clinical notes in electronic health records. In this study, we present an information extraction system to extract related information on heart disease risk factors from unstructured clinical notes using a hybrid approach. The hybrid approach employs both machine learning and rule-based clinical text mining techniques. The developed system achieved an overall microaveraged F-score of 0.8302.

The BioLexicon: a large-scale terminological resource for biomedical text mining

PubMed Central

2011-01-01

Background Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. Results This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard. Conclusions The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring. PMID:21992002

The BioLexicon: a large-scale terminological resource for biomedical text mining.

PubMed

Thompson, Paul; McNaught, John; Montemagni, Simonetta; Calzolari, Nicoletta; del Gratta, Riccardo; Lee, Vivian; Marchi, Simone; Monachini, Monica; Pezik, Piotr; Quochi, Valeria; Rupp, C J; Sasaki, Yutaka; Venturi, Giulia; Rebholz-Schuhmann, Dietrich; Ananiadou, Sophia

2011-10-12

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard. The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.

Assessing the Impacts of Flooding Caused by Extreme Rainfall Events Through a Combined Geospatial and Numerical Modeling Approach

NASA Astrophysics Data System (ADS)

Santillan, J. R.; Amora, A. M.; Makinano-Santillan, M.; Marqueso, J. T.; Cutamora, L. C.; Serviano, J. L.; Makinano, R. M.

2016-06-01

In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.

Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives

PubMed Central

Polepalli Ramesh, Balaji; Belknap, Steven M; Li, Zuofeng; Frid, Nadya; West, Dennis P

2014-01-01

Background The Food and Drug Administration’s (FDA) Adverse Event Reporting System (FAERS) is a repository of spontaneously-reported adverse drug events (ADEs) for FDA-approved prescription drugs. FAERS reports include both structured reports and unstructured narratives. The narratives often include essential information for evaluation of the severity, causality, and description of ADEs that are not present in the structured data. The timely identification of unknown toxicities of prescription drugs is an important, unsolved problem. Objective The objective of this study was to develop an annotated corpus of FAERS narratives and biomedical named entity tagger to automatically identify ADE related information in the FAERS narratives. Methods We developed an annotation guideline and annotate medication information and adverse event related entities on 122 FAERS narratives comprising approximately 23,000 word tokens. A named entity tagger using supervised machine learning approaches was built for detecting medication information and adverse event entities using various categories of features. Results The annotated corpus had an agreement of over .9 Cohen’s kappa for medication and adverse event entities. The best performing tagger achieves an overall performance of 0.73 F1 score for detection of medication, adverse event and other named entities. Conclusions In this study, we developed an annotated corpus of FAERS narratives and machine learning based models for automatically extracting medication and adverse event information from the FAERS narratives. Our study is an important step towards enriching the FAERS data for postmarketing pharmacovigilance. PMID:25600332

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.

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

Semantic Importance Sampling for Statistical Model Checking

DTIC Science & Technology

2014-10-18

we implement SIS in a tool called osmosis and use it to verify a number of stochastic systems with rare events. Our results indicate that SIS reduces...background definitions and concepts. Section 4 presents SIS, and Section 5 presents our tool osmosis . In Section 6, we present our experiments and results...Syntactic Extraction ∗( ) dReal + Refinement ∗ |∗| , Monte-Carlo , Fig. 5. Architecture of osmosis

Developing Performance Measures for Army Aviation Collective Training

DTIC Science & Technology

2011-05-01

simulation-based training, such as ATX, is determined by performance improvement of participants within the virtual-training environment (Bell & Waag ...of the collective behavior (Bell & Waag , 1998). In ATX, system-based (i.e., simulator) data can be used to extract measures such as timing of events...to CABs. 20 21 References Bell, H. H., & Waag , W. L. (1998). Evaluating the effectiveness of flight simulators for training combat

TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries.

PubMed

Chang, Yung-Chun; Dai, Hong-Jie; Wu, Johnny Chi-Yang; Chen, Jian-Ming; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

2013-12-01

Patient discharge summaries provide detailed medical information about individuals who have been hospitalized. To make a precise and legitimate assessment of the abundant data, a proper time layout of the sequence of relevant events should be compiled and used to drive a patient-specific timeline, which could further assist medical personnel in making clinical decisions. The process of identifying the chronological order of entities is called temporal relation extraction. In this paper, we propose a hybrid method to identify appropriate temporal links between a pair of entities. The method combines two approaches: one is rule-based and the other is based on the maximum entropy model. We develop an integration algorithm to fuse the results of the two approaches. All rules and the integration algorithm are formally stated so that one can easily reproduce the system and results. To optimize the system's configuration, we used the 2012 i2b2 challenge TLINK track dataset and applied threefold cross validation to the training set. Then, we evaluated its performance on the training and test datasets. The experiment results show that the proposed TEMPTING (TEMPoral relaTion extractING) system (ranked seventh) achieved an F-score of 0.563, which was at least 30% better than that of the baseline system, which randomly selects TLINK candidates from all pairs and assigns the TLINK types. The TEMPTING system using the hybrid method also outperformed the stage-based TEMPTING system. Its F-scores were 3.51% and 0.97% better than those of the stage-based system on the training set and test set, respectively. Copyright © 2013 Elsevier Inc. All rights reserved.

Timing matters: the processing of pitch relations

PubMed Central

Weise, Annekathrin; Grimm, Sabine; Trujillo-Barreto, Nelson J.; Schröger, Erich

2014-01-01

The human central auditory system can automatically extract abstract regularities from a variant auditory input. To this end, temporarily separated events need to be related. This study tested whether the timing between events, falling either within or outside the temporal window of integration (~350 ms), impacts the extraction of abstract feature relations. We utilized tone pairs for which tones within but not across pairs revealed a constant pitch relation (e.g., pitch of second tone of a pair higher than pitch of first tone, while absolute pitch values varied across pairs). We measured the mismatch negativity (MMN; the brain’s error signal to auditory regularity violations) to second tones that rarely violated the pitch relation (e.g., pitch of second tone lower). A Short condition in which tone duration (90 ms) and stimulus onset asynchrony between the tones of a pair were short (110 ms) was compared to two conditions, where this onset asynchrony was long (510 ms). In the Long Gap condition, the tone durations were identical to Short (90 ms), but the silent interval was prolonged by 400 ms. In Long Tone, the duration of the first tone was prolonged by 400 ms, while the silent interval was comparable to Short (20 ms). Results show a frontocentral MMN of comparable amplitude in all conditions. Thus, abstract pitch relations can be extracted even when the within-pair timing exceeds the integration period. Source analyses indicate MMN generators in the supratemporal cortex. Interestingly, they were located more anterior in Long Gap than in Short and Long Tone. Moreover, frontal generator activity was found for Long Gap and Long Tone. Thus, the way in which the system automatically registers irregular abstract pitch relations depends on the timing of the events to be linked. Pending that the current MMN data mirror established abstract rule representations coding the regular pitch relation, neural processes building these templates vary with timing. PMID:24966823

Using multiplicity as a fractional cross-section estimation for centrality in PHOBOS

NASA Astrophysics Data System (ADS)

Hollis, Richard S.; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Halliwell, C.; Hamblen, J.; Hauer, M.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Holylnski, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Khan, N.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Reed, C.; Roland, C.; Roland, G.; Sagerer, J.; Seals, H.; Sedykh, I.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tonjes, M. B.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Wenger, E.; Wolfs, F. L. H.; Wosiek, B.; Wozniak, K.; Wyslouch, B.; PHOBOS Collaboration

2005-01-01

Collision centrality is a valuable parameter used in relativistic nuclear physics which relates to geometrical quantities such as the number of participating nucleons. PHOBOS utilizes a multiplicity measurement as a means to estimate fractional cross-section of a collision event-by-event. From this, the centrality of this collision can be deduced. The details of the centrality determination depend both on the collision system and collision energy. Presented here are the techniques developed over the course of the RHIC program that are used by PHOBOS to extract the centrality. Possible biases that have to be overcome before a final measurement can be interpreted are discussed.

A Neutral Network based Early Eathquake Warning model in California region

NASA Astrophysics Data System (ADS)

Xiao, H.; MacAyeal, D. R.

2016-12-01

Early Earthquake Warning systems could reduce loss of lives and other economic impact resulted from natural disaster or man-made calamity. Current systems could be further enhanced by neutral network method. A 3 layer neural network model combined with onsite method was deployed in this paper to improve the recognition time and detection time for large scale earthquakes.The 3 layer neutral network early earthquake warning model adopted the vector feature design for sample events happened within 150 km radius of the epicenters. Dataset used in this paper contained both destructive events and small scale events. All the data was extracted from IRIS database to properly train the model. In the training process, backpropagation algorithm was used to adjust the weight matrices and bias matrices during each iteration. The information in all three channels of the seismometers served as the source in this model. Through designed tests, it was indicated that this model could identify approximately 90 percent of the events' scale correctly. And the early detection could provide informative evidence for public authorities to make further decisions. This indicated that neutral network model could have the potential to strengthen current early warning system, since the onsite method may greatly reduce the responding time and save more lives in such disasters.

A neural joint model for entity and relation extraction from biomedical text.

PubMed

Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

2017-03-31

Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

Feature extraction and identification in distributed optical-fiber vibration sensing system for oil pipeline safety monitoring

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Tang, Chenghao

2017-12-01

High sensitivity of a distributed optical-fiber vibration sensing (DOVS) system based on the phase-sensitivity optical time domain reflectometry (Φ-OTDR) technology also brings in high nuisance alarm rates (NARs) in real applications. In this paper, feature extraction methods of wavelet decomposition (WD) and wavelet packet decomposition (WPD) are comparatively studied for three typical field testing signals, and an artificial neural network (ANN) is built for the event identification. The comparison results prove that the WPD performs a little better than the WD for the DOVS signal analysis and identification in oil pipeline safety monitoring. The identification rate can be improved up to 94.4%, and the nuisance alarm rate can be effectively controlled as low as 5.6% for the identification network with the wavelet packet energy distribution features.

Wrong-Site Surgery, Retained Surgical Items, and Surgical Fires : A Systematic Review of Surgical Never Events.

PubMed

Hempel, Susanne; Maggard-Gibbons, Melinda; Nguyen, David K; Dawes, Aaron J; Miake-Lye, Isomi; Beroes, Jessica M; Booth, Marika J; Miles, Jeremy N V; Shanman, Roberta; Shekelle, Paul G

2015-08-01

Serious, preventable surgical events, termed never events, continue to occur despite considerable patient safety efforts. To examine the incidence and root causes of and interventions to prevent wrong-site surgery, retained surgical items, and surgical fires in the era after the implementation of the Universal Protocol in 2004. We searched 9 electronic databases for entries from 2004 through June 30, 2014, screened references, and consulted experts. Two independent reviewers identified relevant publications in June 2014. One reviewer used a standardized form to extract data and a second reviewer checked the data. Strength of evidence was established by the review team. Data extraction was completed in January 2015. Incidence of wrong-site surgery, retained surgical items, and surgical fires. We found 138 empirical studies that met our inclusion criteria. Incidence estimates for wrong-site surgery in US settings varied by data source and procedure (median estimate, 0.09 events per 10,000 surgical procedures). The median estimate for retained surgical items was 1.32 events per 10,000 procedures, but estimates varied by item and procedure. The per-procedure surgical fire incidence is unknown. A frequently reported root cause was inadequate communication. Methodologic challenges associated with investigating changes in rare events limit the conclusions of 78 intervention evaluations. Limited evidence supported the Universal Protocol (5 studies), education (4 studies), and team training (4 studies) interventions to prevent wrong-site surgery. Limited evidence exists to prevent retained surgical items by using data-matrix-coded sponge-counting systems (5 pertinent studies). Evidence for preventing surgical fires was insufficient, and intervention effects were not estimable. Current estimates for wrong-site surgery and retained surgical items are 1 event per 100,000 and 1 event per 10,000 procedures, respectively, but the precision is uncertain, and the per-procedure prevalence of surgical fires is not known. Root-cause analyses suggest the need for improved communication. Despite promising approaches and global Universal Protocol evaluations, empirical evidence for interventions is limited.

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 our proposed adaptive crawler and our stream division/recombination technique provides significant gains in event recall (44.44%) and event precision (9.57%). The addition of these sub-events or pieces, allows us to get closer to solving the event puzzle. PMID:29107976

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 our proposed adaptive crawler and our stream division/recombination technique provides significant gains in event recall (44.44%) and event precision (9.57%). The addition of these sub-events or pieces, allows us to get closer to solving the event puzzle.

The Evaluation of a Temporal Reasoning System in Processing Clinical Discharge Summaries

PubMed Central

Zhou, Li; Parsons, Simon; Hripcsak, George

2008-01-01

Context TimeText is a temporal reasoning system designed to represent, extract, and reason about temporal information in clinical text. Objective To measure the accuracy of the TimeText for processing clinical discharge summaries. Design Six physicians with biomedical informatics training served as domain experts. Twenty discharge summaries were randomly selected for the evaluation. For each of the first 14 reports, 5 to 8 clinically important medical events were chosen. The temporal reasoning system generated temporal relations about the endpoints (start or finish) of pairs of medical events. Two experts (subjects) manually generated temporal relations for these medical events. The system and expert-generated results were assessed by four other experts (raters). All of the twenty discharge summaries were used to assess the system’s accuracy in answering time-oriented clinical questions. For each report, five to ten clinically plausible temporal questions about events were generated. Two experts generated answers to the questions to serve as the gold standard. We wrote queries to retrieve answers from system’s output. Measurements Correctness of generated temporal relations, recall of clinically important relations, and accuracy in answering temporal questions. Results The raters determined that 97% of subjects’ 295 generated temporal relations were correct and that 96.5% of the system’s 995 generated temporal relations were correct. The system captured 79% of 307 temporal relations determined to be clinically important by the subjects and raters. The system answered 84% of the temporal questions correctly. Conclusion The system encoded the majority of information identified by experts, and was able to answer simple temporal questions. PMID:17947618

Aircraft Operations Classification System

NASA Technical Reports Server (NTRS)

Harlow, Charles; Zhu, Weihong

2001-01-01

Accurate data is important in the aviation planning process. In this project we consider systems for measuring aircraft activity at airports. This would include determining the type of aircraft such as jet, helicopter, single engine, and multiengine propeller. Some of the issues involved in deploying technologies for monitoring aircraft operations are cost, reliability, and accuracy. In addition, the system must be field portable and acceptable at airports. A comparison of technologies was conducted and it was decided that an aircraft monitoring system should be based upon acoustic technology. A multimedia relational database was established for the study. The information contained in the database consists of airport information, runway information, acoustic records, photographic records, a description of the event (takeoff, landing), aircraft type, and environmental information. We extracted features from the time signal and the frequency content of the signal. A multi-layer feed-forward neural network was chosen as the classifier. Training and testing results were obtained. We were able to obtain classification results of over 90 percent for training and testing for takeoff events.

Characterizing and analyzing ramping events in wind power, solar power, load, and netload

DOE PAGES

Cui, Mingjian; Zhang, Jie; Feng, Cong; ...

2017-04-07

Here, one of the biggest concerns associated with integrating a large amount of renewable energy into the power grid is the ability to handle large ramps in the renewable power output. For the sake of system reliability and economics, it is essential for power system operators to better understand the ramping features of renewable, load, and netload. An optimized swinging door algorithm (OpSDA) is used and extended to accurately and efficiently detect ramping events. For wind power ramps detection, a process of merging 'bumps' (that have a different changing direction) into adjacent ramping segments is included to improve the performancemore » of the OpSDA method. For solar ramps detection, ramping events that occur in both clear-sky and measured (or forecasted) solar power are removed to account for the diurnal pattern of solar generation. Ramping features are extracted and extensively compared between load and netload under different renewable penetration levels (9.77%, 15.85%, and 51.38%). Comparison results show that (i) netload ramp events with shorter durations and smaller magnitudes occur more frequently when renewable penetration level increases, and the total number of ramping events also increases; and (ii) different ramping characteristics are observed in load and netload even with a low renewable penetration level.« less

Bridging the semantic gap in sports

NASA Astrophysics Data System (ADS)

Li, Baoxin; Errico, James; Pan, Hao; Sezan, M. Ibrahim

2003-01-01

One of the major challenges facing current media management systems and the related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

Video-tracker trajectory analysis: who meets whom, when and where

NASA Astrophysics Data System (ADS)

Jäger, U.; Willersinn, D.

2010-04-01

Unveiling unusual or hostile events by observing manifold moving persons in a crowd is a challenging task for human operators, especially when sitting in front of monitor walls for hours. Typically, hostile events are rare. Thus, due to tiredness and negligence the operator may miss important events. In such situations, an automatic alarming system is able to support the human operator. The system incorporates a processing chain consisting of (1) people tracking, (2) event detection, (3) data retrieval, and (4) display of relevant video sequence overlaid by highlighted regions of interest. In this paper we focus on the event detection stage of the processing chain mentioned above. In our case, the selected event of interest is the encounter of people. Although being based on a rather simple trajectory analysis, this kind of event embodies great practical importance because it paves the way to answer the question "who meets whom, when and where". This, in turn, forms the basis to detect potential situations where e.g. money, weapons, drugs etc. are handed over from one person to another in crowded environments like railway stations, airports or busy streets and places etc.. The input to the trajectory analysis comes from a multi-object video-based tracking system developed at IOSB which is able to track multiple individuals within a crowd in real-time [1]. From this we calculate the inter-distances between all persons on a frame-to-frame basis. We use a sequence of simple rules based on the individuals' kinematics to detect the event mentioned above to output the frame number, the persons' IDs from the tracker and the pixel coordinates of the meeting position. Using this information, a data retrieval system may extract the corresponding part of the recorded video image sequence and finally allows for replaying the selected video clip with a highlighted region of interest to attract the operator's attention for further visual inspection.

Reconstructing particle masses in events with displaced vertices

NASA Astrophysics Data System (ADS)

Cottin, Giovanna

2018-03-01

We propose a simple way to extract particle masses given a displaced vertex signature in event topologies where two long-lived mother particles decay to visible particles and an invisible daughter. The mother could be either charged or neutral and the neutral daughter could correspond to a dark matter particle in different models. The method allows to extract the parent and daughter masses by using on-shell conditions and energy-momentum conservation, in addition to the displaced decay positions of the parents, which allows to solve the kinematic equations fully on an event-by-event basis. We show the validity of the method by means of simulations including detector effects. If displaced events are seen in discovery searches at the Large Hadron Collider (LHC), this technique can be applied.

Psychotropic Effects of an Alcoholic Extract from the Leaves of Albizia zygia (Leguminosae-Mimosoideae)

PubMed Central

Kukuia, Kennedy Kwami Edem; Adjei, Samuel; Akure, Obed Awintuma; Agbemelo-Tsomafo, Constance; Adu-Poku, Shirley Nyarko; Agyeman-Badu, Kenneth Yaw

2017-01-01

Background Albizia zygia is used in Ghanaian traditional medicine for the management of mental disorders. The present study tested the hypothesis that an extract of the leaves of Albizia zygia (AZE) may possess antipsychotic and antidepressant properties. Method The novelty- and apomorphine-induced locomotor and rearing behaviours of AZE in mice were explored in an open-field observational test system. The effects of AZE in apomorphine-induced cage climbing test, extract-induced catalepsy, and haloperidol-induced catalepsy on mice were also investigated. Lastly, the forced swimming and tail suspension tests in mice were employed to screen the possible antidepressant effects of AZE. Results AZE (100–3000 mg/kg) showed signs of central nervous system (CNS) depression under observation, with no lethality, 24 h after treatment in mice. AZE (100–1000 mg/kg) produced a significant decrease in the frequency of novelty- and apomorphine-induced locomotor activities in mice. The extract also significantly decreased the frequency and duration of apomorphine-induced climbing activities in mice. AZE, while failing to produce any cataleptic event in naïve mice, significantly enhanced haloperidol-induced catalepsy at a dose of 1000 mg/kg. However, AZE did not produce any significant antidepressant effects in the test models employed. Conclusion The extract of Albizia zygia exhibited an antipsychotic-like activity in mice. PMID:29234443

Investigating herb-drug interactions: the effect of Citrus aurantium fruit extract on the pharmacokinetics of amiodarone in rats.

PubMed

Rodrigues, Márcio; Alves, Gilberto; Falcão, Amílcar

2013-10-01

Citrus aurantium extract has been largely used in weight loss and sports performance dietary supplements. However, the safety of C. aurantium-containing products has been questioned mainly due to the association of its use with adverse events in the cardiovascular system. Therefore, this work aimed to assess the potential for herb-drug interactions among a standardized C. aurantium extract (GMP certificate) and amiodarone (narrow therapeutic index drug) in rats. In a first pharmacokinetic study, rats were simultaneously co-administered with a single-dose of C. aurantium (164 mg/kg, p.o.) and amiodarone (50 mg/kg, p.o.); in a second study, rats were pre-treated during 14 days with C. aurantium (164 mg/kg/day, p.o.) and received amiodarone (50 mg/kg, p.o.) on the 15th day. Rats of the control groups received the corresponding volume of vehicle. Overall, after analysis of the pharmacokinetic data, it deserves to be highlighted the significant increase of the peak plasma concentration of amiodarone in rats pre-treated with C. aurantium extract, while the extent of systemic exposure was comparable between both groups. This paper reports, for the first time, data on the potential of herb-drug interaction between C. aurantium extract and amiodarone. However, specific clinical trials should be performed to confirm these results in humans. Copyright © 2013 Elsevier Ltd. All rights reserved.

An ethanolic extract of Desmodium adscendens exhibits antipsychotic-like activity in mice.

PubMed

Amoateng, Patrick; Adjei, Samuel; Osei-Safo, Dorcas; Kukuia, Kennedy K E; Karikari, Thomas K; Nyarko, Alexander K

2017-09-26

Desmodium adscendens extract (DAE) is used traditionally in Ghana for the management of psychosis. The present study aimed at providing pharmacological evidence for its ethnomedical use by testing the hypothesis that an ethanolic extract of Desmodium adscendens may possess antipsychotic properties. The primary behavioral effects of DAE on the central nervous system of mice were investigated using Irwin's test paradigm. Novelty-induced and apomorphine-induced locomotor and rearing behaviors in mice were explored in an open-field observational test system. Apomorphine-induced cage climbing test in mice was used as the antipsychotic animal model. The ability of DAE to induce catalepsy and enhance haloperidol-induced catalepsy was also investigated in mice. The DAE produced sedation, cholinergic-, and serotonergic-like effects in mice when evaluated using the Irwin's test. No lethality was observed after 24 h post-treatment. The LD50 in mice was estimated to be greater than 3000 mg/kg. The DAE significantly decreased the frequency of novelty- and apomorphine-induced rearing and locomotor activities in mice. It also significantly lowered the frequency and duration of apomorphine-induced climbing activities in mice. It did not induce any cataleptic event in naïve mice but only significantly enhanced haloperidol-induced catalepsy at a dose of 1000 mg/kg. The ethanolic extract of Desmodium adscendens exhibited antipsychotic-like activities in mice. Motor side effects are only likely to develop at higher doses of the extract.

Effects of DNA extraction and purification methods on real-time quantitative PCR analysis of Roundup Ready soybean.

PubMed

Demeke, Tigst; Ratnayaka, Indira; Phan, Anh

2009-01-01

The quality of DNA affects the accuracy and repeatability of quantitative PCR results. Different DNA extraction and purification methods were compared for quantification of Roundup Ready (RR) soybean (event 40-3-2) by real-time PCR. DNA was extracted using cetylmethylammonium bromide (CTAB), DNeasy Plant Mini Kit, and Wizard Magnetic DNA purification system for food. CTAB-extracted DNA was also purified using the Zymo (DNA Clean & Concentrator 25 kit), Qtip 100 (Qiagen Genomic-Tip 100/G), and QIAEX II Gel Extraction Kit. The CTAB extraction method provided the largest amount of DNA, and the Zymo purification kit resulted in the highest percentage of DNA recovery. The Abs260/280 and Abs260/230 ratios were less than the expected values for some of the DNA extraction and purification methods used, indicating the presence of substances that could inhibit PCR reactions. Real-time quantitative PCR results were affected by the DNA extraction and purification methods used. Further purification or dilution of the CTAB DNA was required for successful quantification of RR soybean. Less variability of quantitative PCR results was observed among experiments and replications for DNA extracted and/or purified by CTAB, CTAB+Zymo, CTAB+Qtip 100, and DNeasy methods. Correct and repeatable results for real-time PCR quantification of RR soybean were achieved using CTAB DNA purified with Zymo and Qtip 100 methods.

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

Cui, Mingjian; Zhang, Jie; Feng, Cong

Here, one of the biggest concerns associated with integrating a large amount of renewable energy into the power grid is the ability to handle large ramps in the renewable power output. For the sake of system reliability and economics, it is essential for power system operators to better understand the ramping features of renewable, load, and netload. An optimized swinging door algorithm (OpSDA) is used and extended to accurately and efficiently detect ramping events. For wind power ramps detection, a process of merging 'bumps' (that have a different changing direction) into adjacent ramping segments is included to improve the performancemore » of the OpSDA method. For solar ramps detection, ramping events that occur in both clear-sky and measured (or forecasted) solar power are removed to account for the diurnal pattern of solar generation. Ramping features are extracted and extensively compared between load and netload under different renewable penetration levels (9.77%, 15.85%, and 51.38%). Comparison results show that (i) netload ramp events with shorter durations and smaller magnitudes occur more frequently when renewable penetration level increases, and the total number of ramping events also increases; and (ii) different ramping characteristics are observed in load and netload even with a low renewable penetration level.« less

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.

Fusion and reaction mechanism evolution in 24Mg+12C at intermediate energies

NASA Astrophysics Data System (ADS)

Samri, M.; Grenier, F.; Ball, G. C.; Beaulieu, L.; Gingras, L.; Horn, D.; Larochelle, Y.; Moustabchir, R.; Roy, R.; St-Pierre, C.; Theriault, D.

2002-06-01

The formation and deexcitation of fusionlike events selected in events with a total charge equal or greater than 16 in 24Mg+12C system has been investigated at 25, 35, and 45 MeV/nucleon with a large multidetector array. Central single-source events are selected by use of the statistical discriminant analysis method applied to a set of 26 global variables. The fusion cross section has been extracted for the three bombarding energies and compared to other experimental data and to theoretical predictions. The total multiplicity is found to first increase to a maximum value and then decrease with increasing beam energy. It is shown that this behavior is connected to the opening of multifragmentation channels at 45 MeV/nucleon and the disappearance of channels with only light charged particles.

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events

PubMed Central

Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals’ daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient. PMID:28076375

SensibleSleep: A Bayesian Model for Learning Sleep Patterns from Smartphone Events.

PubMed

Cuttone, Andrea; Bækgaard, Per; Sekara, Vedran; Jonsson, Håkan; Larsen, Jakob Eg; Lehmann, Sune

2017-01-01

We propose a Bayesian model for extracting sleep patterns from smartphone events. Our method is able to identify individuals' daily sleep periods and their evolution over time, and provides an estimation of the probability of sleep and wake transitions. The model is fitted to more than 400 participants from two different datasets, and we verify the results against ground truth from dedicated armband sleep trackers. We show that the model is able to produce reliable sleep estimates with an accuracy of 0.89, both at the individual and at the collective level. Moreover the Bayesian model is able to quantify uncertainty and encode prior knowledge about sleep patterns. Compared with existing smartphone-based systems, our method requires only screen on/off events, and is therefore much less intrusive in terms of privacy and more battery-efficient.

A fuzzy Petri-net-based mode identification algorithm for fault diagnosis of complex systems

NASA Astrophysics Data System (ADS)

Propes, Nicholas C.; Vachtsevanos, George

2003-08-01

Complex dynamical systems such as aircraft, manufacturing systems, chillers, motor vehicles, submarines, etc. exhibit continuous and event-driven dynamics. These systems undergo several discrete operating modes from startup to shutdown. For example, a certain shipboard system may be operating at half load or full load or may be at start-up or shutdown. Of particular interest are extreme or "shock" operating conditions, which tend to severely impact fault diagnosis or the progression of a fault leading to a failure. Fault conditions are strongly dependent on the operating mode. Therefore, it is essential that in any diagnostic/prognostic architecture, the operating mode be identified as accurately as possible so that such functions as feature extraction, diagnostics, prognostics, etc. can be correlated with the predominant operating conditions. This paper introduces a mode identification methodology that incorporates both time- and event-driven information about the process. A fuzzy Petri net is used to represent the possible successive mode transitions and to detect events from processed sensor signals signifying a mode change. The operating mode is initialized and verified by analysis of the time-driven dynamics through a fuzzy logic classifier. An evidence combiner module is used to combine the results from both the fuzzy Petri net and the fuzzy logic classifier to determine the mode. Unlike most event-driven mode identifiers, this architecture will provide automatic mode initialization through the fuzzy logic classifier and robustness through the combining of evidence of the two algorithms. The mode identification methodology is applied to an AC Plant typically found as a component of a shipboard system.

Using ProMED-Mail and MedWorm blogs for cross-domain pattern analysis in epidemic intelligence.

PubMed

Stewart, Avaré; Denecke, Kerstin

2010-01-01

In this work we motivate the use of medical blog user generated content for gathering facts about disease reporting events to support biosurveillance investigation. Given the characteristics of blogs, the extraction of such events is made more difficult due to noise and data abundance. We address the problem of automatically inferring disease reporting event extraction patterns in this more noisy setting. The sublanguage used in outbreak reports is exploited to align with the sequences of disease reporting sentences in blogs. Based our Cross Domain Pattern Analysis Framework, experimental results show that Phase-Level sequences tend to produce more overlap across the domains than Word-Level sequences. The cross domain alignment process is effective at filtering noisy sequences from blogs and extracting good candidate sequence patterns from an abundance of text.

Investigating the Capability to Extract Impulse Response Functions From Ambient Seismic Noise Using a Mine Collapse Event

NASA Astrophysics Data System (ADS)

Kwak, Sangmin; Song, Seok Goo; Kim, Geunyoung; Cho, Chang Soo; Shin, Jin Soo

2017-10-01

Using recordings of a mine collapse event (Mw 4.2) in South Korea in January 2015, we demonstrated that the phase and amplitude information of impulse response functions (IRFs) can be effectively retrieved using seismic interferometry. This event is equivalent to a single downward force at shallow depth. Using quantitative metrics, we compared three different seismic interferometry techniques—deconvolution, coherency, and cross correlation—to extract the IRFs between two distant stations with ambient seismic noise data. The azimuthal dependency of the source distribution of the ambient noise was also evaluated. We found that deconvolution is the best method for extracting IRFs from ambient seismic noise within the period band of 2-10 s. The coherency method is also effective if appropriate spectral normalization or whitening schemes are applied during the data processing.

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).

A new Bayesian Inference-based Phase Associator for Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Meier, Men-Andrin; Heaton, Thomas; Clinton, John; Wiemer, Stefan

2013-04-01

State of the art network-based Earthquake Early Warning (EEW) systems can provide warnings for large magnitude 7+ earthquakes. Although regions in the direct vicinity of the epicenter will not receive warnings prior to damaging shaking, real-time event characterization is available before the destructive S-wave arrival across much of the strongly affected region. In contrast, in the case of the more frequent medium size events, such as the devastating 1994 Mw6.7 Northridge, California, earthquake, providing timely warning to the smaller damage zone is more difficult. For such events the "blind zone" of current systems (e.g. the CISN ShakeAlert system in California) is similar in size to the area over which severe damage occurs. We propose a faster and more robust Bayesian inference-based event associator, that in contrast to the current standard associators (e.g. Earthworm Binder), is tailored to EEW and exploits information other than only phase arrival times. In particular, the associator potentially allows for reliable automated event association with as little as two observations, which, compared to the ShakeAlert system, would speed up the real-time characterizations by about ten seconds and thus reduce the blind zone area by up to 80%. We compile an extensive data set of regional and teleseismic earthquake and noise waveforms spanning a wide range of earthquake magnitudes and tectonic regimes. We pass these waveforms through a causal real-time filterbank with passband filters between 0.1 and 50Hz, and, updating every second from the event detection, extract the maximum amplitudes in each frequency band. Using this dataset, we define distributions of amplitude maxima in each passband as a function of epicentral distance and magnitude. For the real-time data, we pass incoming broadband and strong motion waveforms through the same filterbank and extract an evolving set of maximum amplitudes in each passband. We use the maximum amplitude distributions to check whether the incoming waveforms are consistent with amplitude and frequency patterns of local earthquakes by means of a maximum likelihood approach. If such a single-station event likelihood is larger than a predefined threshold value we check whether there are neighboring stations that also have single-station event likelihoods above the threshold. If this is the case for at least one other station, we evaluate whether the respective relative arrival times are in agreement with a common earthquake origin (assuming a simple velocity model and using an Equal Differential Time location scheme). Additionally we check if there are stations where, given the preliminary location, observations would be expected but were not reported ("not-yet-arrived data"). Together, the single-station event likelihood functions and the location likelihood function constitute the multi-station event likelihood function. This function can then be combined with various types of prior information (such as station noise levels, preceding seismicity, fault proximity, etc.) to obtain a Bayesian posterior distribution, representing the degree of belief that the ensemble of the current real-time observations correspond to a local earthquake, rather than to some other signal source irrelevant for EEW. Additional to the reduction of the blind zone size, this approach facilitates the eventual development of an end-to-end probabilistic framework for an EEW system that provides systematic real-time assessment of the risk of false alerts, which enables end users of EEW to implement damage mitigation strategies only above a specified certainty level.

Artificially intelligent recognition of Arabic speaker using voice print-based local features

NASA Astrophysics Data System (ADS)

Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

2016-11-01

Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

Artificial bee colony algorithm for single-trial electroencephalogram analysis.

PubMed

Hsu, Wei-Yen; Hu, Ya-Ping

2015-04-01

In this study, we propose an analysis system combined with feature selection to further improve the classification accuracy of single-trial electroencephalogram (EEG) data. Acquiring event-related brain potential data from the sensorimotor cortices, the system comprises artifact and background noise removal, feature extraction, feature selection, and feature classification. First, the artifacts and background noise are removed automatically by means of independent component analysis and surface Laplacian filter, respectively. Several potential features, such as band power, autoregressive model, and coherence and phase-locking value, are then extracted for subsequent classification. Next, artificial bee colony (ABC) algorithm is used to select features from the aforementioned feature combination. Finally, selected subfeatures are classified by support vector machine. Comparing with and without artifact removal and feature selection, using a genetic algorithm on single-trial EEG data for 6 subjects, the results indicate that the proposed system is promising and suitable for brain-computer interface applications. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Application of quantum-behaved particle swarm optimization to motor imagery EEG classification.

PubMed

Hsu, Wei-Yen

2013-12-01

In this study, we propose a recognition system for single-trial analysis of motor imagery (MI) electroencephalogram (EEG) data. Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system chiefly consists of automatic artifact elimination, feature extraction, feature selection and classification. In addition to the use of independent component analysis, a similarity measure is proposed to further remove the electrooculographic (EOG) artifacts automatically. Several potential features, such as wavelet-fractal features, are then extracted for subsequent classification. Next, quantum-behaved particle swarm optimization (QPSO) is used to select features from the feature combination. Finally, selected sub-features are classified by support vector machine (SVM). Compared with without artifact elimination, feature selection using a genetic algorithm (GA) and feature classification with Fisher's linear discriminant (FLD) on MI data from two data sets for eight subjects, the results indicate that the proposed method is promising in brain-computer interface (BCI) applications.

Oil shale retorting and combustion system

DOEpatents

Pitrolo, Augustine A.; Mei, Joseph S.; Shang, Jerry Y.

1983-01-01

The present invention is directed to the extraction of energy values from l shale containing considerable concentrations of calcium carbonate in an efficient manner. The volatiles are separated from the oil shale in a retorting zone of a fluidized bed where the temperature and the concentration of oxygen are maintained at sufficiently low levels so that the volatiles are extracted from the oil shale with minimal combustion of the volatiles and with minimal calcination of the calcium carbonate. These gaseous volatiles and the calcium carbonate flow from the retorting zone into a freeboard combustion zone where the volatiles are burned in the presence of excess air. In this zone the calcination of the calcium carbonate occurs but at the expense of less BTU's than would be required by the calcination reaction in the event both the retorting and combustion steps took place simultaneously. The heat values in the products of combustion are satisfactorily recovered in a suitable heat exchange system.

Querying and Extracting Timeline Information from Road Traffic Sensor Data

PubMed Central

Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

2016-01-01

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset. PMID:27563900

A Scintillation Counter System Design To Detect Antiproton Annihilation using the High Performance Antiproton Trap(HiPAT)

NASA Technical Reports Server (NTRS)

Martin, James J.; Lewis, Raymond A.; Stanojev, Boris

2003-01-01

The High Performance Antiproton Trap (HiPAT), a system designed to hold up to l0(exp 12) charge particles with a storage half-life of approximately 18 days, is a tool to support basic antimatter research. NASA's interest stems from the energy density represented by the annihilation of matter with antimatter, 10(exp 2)MJ/g. The HiPAT is configured with a Penning-Malmberg style electromagnetic confinement region with field strengths up to 4 Tesla, and 20kV. To date a series of normal matter experiments, using positive and negative ions, have been performed evaluating the designs performance prior to operations with antiprotons. The primary methods of detecting and monitoring stored normal matter ions and antiprotons within the trap includes a destructive extraction technique that makes use of a micro channel plate (MCP) device and a non-destractive radio frequency scheme tuned to key particle frequencies. However, an independent means of detecting stored antiprotons is possible by making use of the actual annihilation products as a unique indicator. The immediate yield of the annihilation event includes photons and pie mesons, emanating spherically from the point of annihilation. To "count" these events, a hardware system of scintillators, discriminators, coincident meters and multi channel scalars (MCS) have been configured to surround much of the HiPAT. Signal coincidence with voting logic is an essential part of this system, necessary to weed out the single cosmic ray events from the multi-particle annihilation shower. This system can be operated in a variety of modes accommodating various conditions. The first is a low-speed sampling interval that monitors the background loss or "evaporation" rate of antiprotons held in the trap during long storage periods; provides an independent method of validating particle lifetimes. The second is a high-speed sample rate accumulating information on a microseconds time-scale; useful when trapped antiparticles are extracted against a target, providing an indication of quantity. This paper details the layout of this system, setup of the hardware components around HiPAT, and applicable checkouts using normal matter radioactive sources.

Towards fully automated Identification of Vesicle-Membrane Fusion Events in TIRF Microscopy

NASA Astrophysics Data System (ADS)

Vallotton, Pascal; James, David E.; Hughes, William E.

2007-11-01

Total Internal Reflection Fluorescence Microscopy (TIRFM) is imposing itself as the tool of choice for studying biological activity in close proximity to the plasma membrane. For example, the exquisite selectivity of TIRFM allows monitoring the diffusion of GFP-phogrin vesicles and their recruitment to the plasma membrane in pancreatic β-cells. We present a novel computer vision system for automatically identifying the elusive fusion events of GFP-phogrin vesicles with the plasma membrane. Our method is based on robust object tracking and matched filtering. It should accelerate the quantification of TIRFM data and allow the extraction of more biological information from image data to support research in diabetes and obesity.

A Miniaturized Video System for Monitoring Drosophila Behavior

NASA Technical Reports Server (NTRS)

Bhattacharya, Sharmila; Inan, Omer; Kovacs, Gregory; Etemadi, Mozziyar; Sanchez, Max; Marcu, Oana

2011-01-01

Long-term spaceflight may induce a variety of harmful effects in astronauts, resulting in altered motor and cognitive behavior. The stresses experienced by humans in space - most significantly weightlessness (microgravity) and cosmic radiation - are difficult to accurately simulate on Earth. In fact, prolonged and concomitant exposure to microgravity and cosmic radiation can only be studied in space. Behavioral studies in space have focused on model organisms, including Drosophila melanogaster. Drosophila is often used due to its short life span and generational cycle, small size, and ease of maintenance. Additionally, the well-characterized genetics of Drosophila behavior on Earth can be applied to the analysis of results from spaceflights, provided that the behavior in space is accurately recorded. In 2001, the BioExplorer project introduced a low-cost option for researchers: the small satellite. While this approach enabled multiple inexpensive launches of biological experiments, it also imposed stringent restrictions on the monitoring systems in terms of size, mass, data bandwidth, and power consumption. Suggested parameters for size are on the order of 100 mm3 and 1 kg mass for the entire payload. For Drosophila behavioral studies, these engineering requirements are not met by commercially available systems. One system that does meet many requirements for behavioral studies in space is the actimeter. Actimeters use infrared light gates to track the number of times a fly crosses a boundary within a small container (3x3x40 mm). Unfortunately, the apparatus needed to monitor several flies at once would be larger than the capacity of the small satellite. A system is presented, which expands on the actimeter approach to achieve a highly compact, low-power, ultra-low bandwidth solution for simultaneous monitoring of the behavior of multiple flies in space. This also provides a simple, inexpensive alternative to the current systems for monitoring Drosophila populations in terrestrial experiments, and could be especially useful in field experiments in remote locations. Two practical limitations of the system should be noted: first, only walking flies can be observed - not flying - and second, although it enables population studies, tracking individual flies within the population is not currently possible. The system used video recording and an analog circuit to extract the average light changes as a function of time. Flies were held in a 5-cm diameter Petri dish and illuminated from below by a uniform light source. A miniature, monochrome CMOS (complementary metal-oxide semiconductor) video camera imaged the flies. This camera had automatic gain control, and this did not affect system performance. The camera was positioned 5-7 cm above the Petri dish such that the imaging area was 2.25 sq cm. With this basic setup, still images and continuous video of 15 flies at one time were obtained. To reduce the required data bandwidth by several orders of magnitude, a band-pass filter (0.3-10 Hz) circuit compressed the video signal and extracted changes in image luminance over time. The raw activity signal output of this circuit was recorded on a computer and digitally processed to extract the fly movement "events" from the waveform. These events corresponded to flies entering and leaving the image and were used for extracting activity parameters such as inter-event duration. The efficacy of the system in quantifying locomotor activity was evaluated by varying environmental temperature, then measuring the activity level of the flies.

Systems toxicology-based assessment of the candidate modified risk tobacco product THS2.2 for the adhesion of monocytic cells to human coronary arterial endothelial cells.

PubMed

Poussin, Carine; Laurent, Alexandra; Peitsch, Manuel C; Hoeng, Julia; De Leon, Hector

2016-01-02

Alterations of endothelial adhesive properties by cigarette smoke (CS) can progressively favor the development of atherosclerosis which may cause cardiovascular disorders. Modified risk tobacco products (MRTPs) are tobacco products developed to reduce smoking-related risks. A systems biology/toxicology approach combined with a functional in vitro adhesion assay was used to assess the impact of a candidate heat-not-burn technology-based MRTP, Tobacco Heating System (THS) 2.2, on the adhesion of monocytic cells to human coronary arterial endothelial cells (HCAECs) compared with a reference cigarette (3R4F). HCAECs were treated for 4h with conditioned media of human monocytic Mono Mac 6 (MM6) cells preincubated with low or high concentrations of aqueous extracts from THS2.2 aerosol or 3R4F smoke for 2h (indirect treatment), unconditioned media (direct treatment), or fresh aqueous aerosol/smoke extracts (fresh direct treatment). Functional and molecular investigations revealed that aqueous 3R4F smoke extract promoted the adhesion of MM6 cells to HCAECs via distinct direct and indirect concentration-dependent mechanisms. Using the same approach, we identified significantly reduced effects of aqueous THS2.2 aerosol extract on MM6 cell-HCAEC adhesion, and reduced molecular changes in endothelial and monocytic cells. Ten- and 20-fold increased concentrations of aqueous THS2.2 aerosol extract were necessary to elicit similar effects to those measured with 3R4F in both fresh direct and indirect exposure modalities, respectively. Our systems toxicology study demonstrated reduced effects of an aqueous aerosol extract from the candidate MRTP, THS2.2, using the adhesion of monocytic cells to human coronary endothelial cells as a surrogate pathophysiologically relevant event in atherogenesis. Copyright © 2015 Z. Published by Elsevier Ireland Ltd.. All rights reserved.

Towards a global flood detection system using social media

NASA Astrophysics Data System (ADS)

de Bruijn, Jens; de Moel, Hans; Jongman, Brenden; Aerts, Jeroen

2017-04-01

It is widely recognized that an early warning is critical in improving international disaster response. Analysis of social media in real-time can provide valuable information about an event or help to detect unexpected events. For successful and reliable detection systems that work globally, it is important that sufficient data is available and that the algorithm works both in data-rich and data-poor environments. In this study, both a new geotagging system and multi-level event detection system for flood hazards was developed using Twitter data. Geotagging algorithms that regard one tweet as a single document are well-studied. However, no algorithms exist that combine several sequential tweets mentioning keywords regarding a specific event type. Within the time frame of an event, multiple users use event related keywords that refer to the same place name. This notion allows us to treat several sequential tweets posted in the last 24 hours as one document. For all these tweets, we collect a series of spatial indicators given in the tweet metadata and extract additional topological indicators from the text. Using these indicators, we can reduce ambiguity and thus better estimate what locations are tweeted about. Using these localized tweets, Bayesian change-point analysis is used to find significant increases of tweets mentioning countries, provinces or towns. In data-poor environments detection of events on a country level is possible, while in other, data-rich, environments detection on a city level is achieved. Additionally, on a city-level we analyse the spatial dependence of mentioned places. If multiple places within a limited spatial extent are mentioned, detection confidence increases. We run the algorithm using 2 years of Twitter data with flood related keywords in 13 major languages and validate against a flood event database. We find that the geotagging algorithm yields significantly more data than previously developed algorithms and successfully deals with ambiguous place names. In addition, we show that our detection system can both quickly and reliably detect floods, even in countries where data is scarce, while achieving high detail in countries where more data is available.

Using uncertainty to link and rank evidence from biomedical literature for model curation

PubMed Central

Zerva, Chrysoula; Batista-Navarro, Riza; Day, Philip; Ananiadou, Sophia

2017-01-01

Abstract Motivation In recent years, there has been great progress in the field of automated curation of biomedical networks and models, aided by text mining methods that provide evidence from literature. Such methods must not only extract snippets of text that relate to model interactions, but also be able to contextualize the evidence and provide additional confidence scores for the interaction in question. Although various approaches calculating confidence scores have focused primarily on the quality of the extracted information, there has been little work on exploring the textual uncertainty conveyed by the author. Despite textual uncertainty being acknowledged in biomedical text mining as an attribute of text mined interactions (events), it is significantly understudied as a means of providing a confidence measure for interactions in pathways or other biomedical models. In this work, we focus on improving identification of textual uncertainty for events and explore how it can be used as an additional measure of confidence for biomedical models. Results We present a novel method for extracting uncertainty from the literature using a hybrid approach that combines rule induction and machine learning. Variations of this hybrid approach are then discussed, alongside their advantages and disadvantages. We use subjective logic theory to combine multiple uncertainty values extracted from different sources for the same interaction. Our approach achieves F-scores of 0.76 and 0.88 based on the BioNLP-ST and Genia-MK corpora, respectively, making considerable improvements over previously published work. Moreover, we evaluate our proposed system on pathways related to two different areas, namely leukemia and melanoma cancer research. Availability and implementation The leukemia pathway model used is available in Pathway Studio while the Ras model is available via PathwayCommons. Online demonstration of the uncertainty extraction system is available for research purposes at http://argo.nactem.ac.uk/test. The related code is available on https://github.com/c-zrv/uncertainty_components.git. Details on the above are available in the Supplementary Material. Contact sophia.ananiadou@manchester.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:29036627

Using uncertainty to link and rank evidence from biomedical literature for model curation.

PubMed

Zerva, Chrysoula; Batista-Navarro, Riza; Day, Philip; Ananiadou, Sophia

2017-12-01

In recent years, there has been great progress in the field of automated curation of biomedical networks and models, aided by text mining methods that provide evidence from literature. Such methods must not only extract snippets of text that relate to model interactions, but also be able to contextualize the evidence and provide additional confidence scores for the interaction in question. Although various approaches calculating confidence scores have focused primarily on the quality of the extracted information, there has been little work on exploring the textual uncertainty conveyed by the author. Despite textual uncertainty being acknowledged in biomedical text mining as an attribute of text mined interactions (events), it is significantly understudied as a means of providing a confidence measure for interactions in pathways or other biomedical models. In this work, we focus on improving identification of textual uncertainty for events and explore how it can be used as an additional measure of confidence for biomedical models. We present a novel method for extracting uncertainty from the literature using a hybrid approach that combines rule induction and machine learning. Variations of this hybrid approach are then discussed, alongside their advantages and disadvantages. We use subjective logic theory to combine multiple uncertainty values extracted from different sources for the same interaction. Our approach achieves F-scores of 0.76 and 0.88 based on the BioNLP-ST and Genia-MK corpora, respectively, making considerable improvements over previously published work. Moreover, we evaluate our proposed system on pathways related to two different areas, namely leukemia and melanoma cancer research. The leukemia pathway model used is available in Pathway Studio while the Ras model is available via PathwayCommons. Online demonstration of the uncertainty extraction system is available for research purposes at http://argo.nactem.ac.uk/test. The related code is available on https://github.com/c-zrv/uncertainty_components.git. Details on the above are available in the Supplementary Material. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Bayesian Monitoring Systems for the CTBT: Historical Development and New Results

NASA Astrophysics Data System (ADS)

Russell, S.; Arora, N. S.; Moore, D.

2016-12-01

A project at Berkeley, begun in 2009 in collaboration with CTBTO andmore recently with LLNL, has reformulated the global seismicmonitoring problem in a Bayesian framework. A first-generation system,NETVISA, has been built comprising a spatial event prior andgenerative models of event transmission and detection, as well as aMonte Carlo inference algorithm. The probabilistic model allows forseamless integration of various disparate sources of information,including negative information (the absence of detections). Workingfrom arrivals extracted by traditional station processing fromInternational Monitoring System (IMS) data, NETVISA achieves areduction of around 60% in the number of missed events compared withthe currently deployed network processing system. It also finds manyevents that are missed by the human analysts who postprocess the IMSoutput. Recent improvements include the integration of models forinfrasound and hydroacoustic detections and a global depth model fornatural seismicity trained from ISC data. NETVISA is now fullycompatible with the CTBTO operating environment. A second-generation model called SIGVISA extends NETVISA's generativemodel all the way from events to raw signal data, avoiding theerror-prone bottom-up detection phase of station processing. SIGVISA'smodel automatically captures the phenomena underlying existingdetection and location techniques such as multilateration, waveformcorrelation matching, and double-differencing, and integrates theminto a global inference process that also (like NETVISA) handles denovo events. Initial results for the Western US in early 2008 (whenthe transportable US Array was operating) shows that SIGVISA finds,from IMS data only, more than twice the number of events recorded inthe CTBTO Late Event Bulletin (LEB). For mb 1.0-2.5, the ratio is more than10; put another way, for this data set, SIGVISA lowers the detectionthreshold by roughly one magnitude compared to LEB. The broader message of this work is that probabilistic inference basedon a vertically integrated generative model that directly expressesgeophysical knowledge can be a much more effective approach forinterpreting scientific data than the traditional bottom-up processingpipeline.

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Dynamic Policy Evaluation for Containing Network Attacks (DEFCN)

DTIC Science & Technology

2005-03-01

API reads policy information from the target users ".ssh" directory and applies those policies to determine whether remote login is allowed to a...types of events that can be controlled by the threshold detectors and reported by the GAA-API include the number of failed login attempts within a given...other uses of the system. Emerald architecture [2] includes a data- collection module integrated with Apache Web server. The module extracts the request

Comprehensive analysis of alternative splicing and functionality in neuronal differentiation of P19 cells.

PubMed

Suzuki, Hitoshi; Osaki, Ken; Sano, Kaori; Alam, A H M Khurshid; Nakamura, Yuichiro; Ishigaki, Yasuhito; Kawahara, Kozo; Tsukahara, Toshifumi

2011-02-18

Alternative splicing, which produces multiple mRNAs from a single gene, occurs in most human genes and contributes to protein diversity. Many alternative isoforms are expressed in a spatio-temporal manner, and function in diverse processes, including in the neural system. The purpose of the present study was to comprehensively investigate neural-splicing using P19 cells. GeneChip Exon Array analysis was performed using total RNAs purified from cells during neuronal cell differentiation. To efficiently and readily extract the alternative exon candidates, 9 filtering conditions were prepared, yielding 262 candidate exons (236 genes). Semiquantitative RT-PCR results in 30 randomly selected candidates suggested that 87% of the candidates were differentially alternatively spliced in neuronal cells compared to undifferentiated cells. Gene ontology and pathway analyses suggested that many of the candidate genes were associated with neural events. Together with 66 genes whose functions in neural cells or organs were reported previously, 47 candidate genes were found to be linked to 189 events in the gene-level profile of neural differentiation. By text-mining for the alternative isoform, distinct functions of the isoforms of 9 candidate genes indicated by the result of Exon Array were confirmed. Alternative exons were successfully extracted. Results from the informatics analyses suggested that neural events were primarily governed by genes whose expression was increased and whose transcripts were differentially alternatively spliced in the neuronal cells. In addition to known functions in neural cells or organs, the uninvestigated alternative splicing events of 11 genes among 47 candidate genes suggested that cell cycle events are also potentially important. These genes may help researchers to differentiate the roles of alternative splicing in cell differentiation and cell proliferation.

Radiation Damage to Nervous System: Designing Optimal Models for Realistic Neuron Morphology in Hippocampus

NASA Astrophysics Data System (ADS)

Batmunkh, Munkhbaatar; Bugay, Alexander; Bayarchimeg, Lkhagvaa; Lkhagva, Oidov

2018-02-01

The present study is focused on the development of optimal models of neuron morphology for Monte Carlo microdosimetry simulations of initial radiation-induced events of heavy charged particles in the specific types of cells of the hippocampus, which is the most radiation-sensitive structure of the central nervous system. The neuron geometry and particles track structures were simulated by the Geant4/Geant4-DNA Monte Carlo toolkits. The calculations were made for beams of protons and heavy ions with different energies and doses corresponding to real fluxes of galactic cosmic rays. A simple compartmental model and a complex model with realistic morphology extracted from experimental data were constructed and compared. We estimated the distribution of the energy deposition events and the production of reactive chemical species within the developed models of CA3/CA1 pyramidal neurons and DG granule cells of the rat hippocampus under exposure to different particles with the same dose. Similar distributions of the energy deposition events and concentration of some oxidative radical species were obtained in both the simplified and realistic neuron models.

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

PubMed Central

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B.

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks. PMID:26909015

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

PubMed

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

A novel fiber-optical vibration defending system with on-line intelligent identification function

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Xie, Xin; Li, Hanyu; Li, Xiaoyu; Wu, Yu; Gong, Yuan; Rao, Yunjiang

2013-09-01

Capacity of the sensor network is always a bottleneck problem for the novel FBG-based quasi-distributed fiberoptical defending system. In this paper, a highly sensitive sensing network with FBG vibration sensors is presented to relieve stress of the capacity and the system cost. However, higher sensitivity may cause higher Nuisance Alarm Rates (NARs) in practical uses. It is necessary to further classify the intrusion pattern or threat level and determine the validity of an unexpected event. Then an intelligent identification method is proposed by extracting the statistical features of the vibration signals in the time domain, and inputting them into a 3-layer Back-Propagation(BP) Artificial Neural Network to classify the events of interest. Experiments of both simulation and field tests are carried out to validate its effectiveness. The results show the recognition rate can be achieved up to 100% for the simulation signals and as high as 96.03% in the real tests.

Systems analysis of arrestin pathway functions.

PubMed

Maudsley, Stuart; Siddiqui, Sana; Martin, Bronwen

2013-01-01

To fully appreciate the diversity and specificity of complex cellular signaling events, such as arrestin-mediated signaling from G protein-coupled receptor activation, a complex systems-level investigation currently appears to be the best option. A rational combination of transcriptomics, proteomics, and interactomics, all coherently integrated with applied next-generation bioinformatics, is vital for the future understanding of the development, translation, and expression of GPCR-mediated arrestin signaling events in physiological contexts. Through a more nuanced, systems-level appreciation of arrestin-mediated signaling, the creation of arrestin-specific molecular response "signatures" should be made simple and ultimately amenable to drug discovery processes. Arrestin-based signaling paradigms possess important aspects, such as its specific temporal kinetics and ability to strongly affect transcriptional activity, that make it an ideal test bed for next-generation of drug discovery bioinformatic approaches such as multi-parallel dose-response analysis, data texturization, and latent semantic indexing-based natural language data processing and feature extraction. Copyright © 2013 Elsevier Inc. All rights reserved.

Heatwave early warning systems and adaptation advice to reduce human health consequences of heatwaves.

PubMed

Lowe, Dianne; Ebi, Kristie L; Forsberg, Bertil

2011-12-01

With climate change, there has been an increase in the frequency, intensity and duration of heatwave events. In response to the devastating mortality and morbidity of recent heatwave events, many countries have introduced heatwave early warning systems (HEWS). HEWS are designed to reduce the avoidable human health consequences of heatwaves through timely notification of prevention measures to vulnerable populations. To identify the key characteristics of HEWS in European countries to help inform modification of current, and development of, new systems and plans. We searched the internet to identify HEWS policy or government documents for 33 European countries and requested information from relevant organizations. We translated the HEWS documents and extracted details on the trigger indicators, thresholds for action, notification strategies, message intermediaries, communication and dissemination strategies, prevention strategies recommended and specified target audiences. Twelve European countries have HEWS. Although there are many similarities among the HEWS, there also are differences in key characteristics that could inform improvements in heatwave early warning plans.

Sea Ice, Hydrocarbon Extraction, Rain-on-Snow and Tundra Reindeer Nomadism in Arctic Russia

NASA Astrophysics Data System (ADS)

Forbes, B. C.; Kumpula, T.; Meschtyb, N.; Laptander, R.; Macias-Fauria, M.; Zetterberg, P.; Verdonen, M.

2015-12-01

It is assumed that retreating sea ice in the Eurasian Arctic will accelerate hydrocarbon development and associated tanker traffic along Russia's Northern Sea Route. However, oil and gas extraction along the Kara and Barents Sea coasts will likely keep developing rapidly regardless of whether the Northwest Eurasian climate continues to warm. Less certain are the real and potential linkages to regional biota and social-ecological systems. Reindeer nomadism continues to be a vitally important livelihood for indigenous tundra Nenets and their large herds of semi-domestic reindeer. Warming summer air temperatures over the NW Russian Arctic have been linked to increases in tundra productivity, longer growing seasons, and accelerated growth of tall deciduous shrubs. These temperature increases have, in turn, been linked to more frequent and sustained summer high-pressure systems over West Siberia, but not to sea ice retreat. At the same time, winters have been warming and rain-on-snow (ROS) events have become more frequent and intense, leading to record-breaking winter and spring mortality of reindeer. What is driving this increase in ROS frequency and intensity is not clear. Recent modelling and simulation have found statistically significant near-surface atmospheric warming and precipitation increases during autumn and winter over Arctic coastal lands in proximity to regions of sea-ice loss. During the winter of 2013-14 an extensive and lasting ROS event led to the starvation of 61,000 reindeer out of a population of ca. 300,000 animals on Yamal Peninsula, West Siberia. Historically, this is the region's largest recorded mortality episode. More than a year later, participatory fieldwork with nomadic herders during spring-summer 2015 revealed that the ecological and socio-economic impacts from this extreme event will unfold for years to come. There is an urgent need to understand whether and how ongoing Barents and Kara Sea ice retreat may affect the region's ancient and unique social-ecological systems. If sea ice retreat is contributing to increasingly severe ROS events and high reindeer mortality, it has major implications for the future of reindeer nomadism. At the same time, rapid oil and gas infrastructure expansion has strong potential to limit the movement of large herds during extreme events.

Evaluation of Natural Language Processing (NLP) Systems to Annotate Drug Product Labeling with MedDRA Terminology.

PubMed

Ly, Thomas; Pamer, Carol; Dang, Oanh; Brajovic, Sonja; Haider, Shahrukh; Botsis, Taxiarchis; Milward, David; Winter, Andrew; Lu, Susan; Ball, Robert

2018-05-31

The FDA Adverse Event Reporting System (FAERS) is a primary data source for identifying unlabeled adverse events (AEs) in a drug or biologic drug product's postmarketing phase. Many AE reports must be reviewed by drug safety experts to identify unlabeled AEs, even if the reported AEs are previously identified, labeled AEs. Integrating the labeling status of drug product AEs into FAERS could increase report triage and review efficiency. Medical Dictionary for Regulatory Activities (MedDRA) is the standard for coding AE terms in FAERS cases. However, drug manufacturers are not required to use MedDRA to describe AEs in product labels. We hypothesized that natural language processing (NLP) tools could assist in automating the extraction and MedDRA mapping of AE terms in drug product labels. We evaluated the performance of three NLP systems, (ETHER, I2E, MetaMap) for their ability to extract AE terms from drug labels and translate the terms to MedDRA Preferred Terms (PTs). Pharmacovigilance-based annotation guidelines for extracting AE terms from drug labels were developed for this study. We compared each system's output to MedDRA PT AE lists, manually mapped by FDA pharmacovigilance experts using the guidelines, for ten drug product labels known as the "gold standard AE list" (GSL) dataset. Strict time and configuration conditions were imposed in order to test each system's capabilities under conditions of no human intervention and minimal system configuration. Each NLP system's output was evaluated for precision, recall and F measure in comparison to the GSL. A qualitative error analysis (QEA) was conducted to categorize a random sample of each NLP system's false positive and false negative errors. A total of 417, 278, and 250 false positive errors occurred in the ETHER, I2E, and MetaMap outputs, respectively. A total of 100, 80, and 187 false negative errors occurred in ETHER, I2E, and MetaMap outputs, respectively. Precision ranged from 64% to 77%, recall from 64% to 83% and F measure from 67% to 79%. I2E had the highest precision (77%), recall (83%) and F measure (79%). ETHER had the lowest precision (64%). MetaMap had the lowest recall (64%). The QEA found that the most prevalent false positive errors were context errors such as "Context error/General term", "Context error/Instructions or monitoring parameters", "Context error/Medical history preexisting condition underlying condition risk factor or contraindication", and "Context error/AE manifestations or secondary complication". The most prevalent false negative errors were in the "Incomplete or missed extraction" error category. Missing AE terms were typically due to long terms, or terms containing non-contiguous words which do not correspond exactly to MedDRA synonyms. MedDRA mapping errors were a minority of errors for ETHER and I2E but were the most prevalent false positive errors for MetaMap. The results demonstrate that it may be feasible to use NLP tools to extract and map AE terms to MedDRA PTs. However, the NLP tools we tested would need to be modified or reconfigured to lower the error rates to support their use in a regulatory setting. Tools specific for extracting AE terms from drug labels and mapping the terms to MedDRA PTs may need to be developed to support pharmacovigilance. Conducting research using additional NLP systems on a larger, diverse GSL would also be informative. Copyright © 2018. Published by Elsevier Inc.

A Warning System for Rainfall-Induced Debris Flows: A Integrated Remote Sensing and Data Mining Approach

NASA Astrophysics Data System (ADS)

Elkadiri, R.; Sultan, M.; Nurmemet, I.; Al Harbi, H.; Youssef, A.; Elbayoumi, T.; Zabramwi, Y.; Alzahrani, S.; Bahamil, A.

2014-12-01

We developed methodologies that heavily rely on observations extracted from a wide-range of remote sensing data sets (TRMM, Landsat ETM, ENVISAT, ERS, SPOT, Orbview, GeoEye) to develop a warning system for rainfall-induced debris flows in the Jazan province in the Red Sea Hills. The developed warning system integrates static controlling factors and dynamic triggering factors. The algorithm couples a susceptibility map with a rainfall I-D curve, both are developed using readily available remote sensing datasets. The static susceptibility map was constructed as follows: (1) an inventory was compiled for debris flows identified from high spatial resolution datasets and field verified; (2) 10 topographical and land cover predisposing factors (i.e. slope angle, slope aspect, normalized difference vegetation index, topographical position index, stream power index, flow accumulation, distance to drainage line, soil weathering index, elevation and topographic wetness index) were generated; (3) an artificial neural network model (ANN) was constructed, optimized and validated; (4) a debris-flow susceptibility map was generated using the ANN model and refined (using differential backscatter coefficient radar images). The rainfall threshold curve was derived as follows: (1) a spatial database was generated to host temporal co-registered and radiometrically and atmospherically corrected Landsat images; (2) temporal change detection images were generated for pairs of successively acquired Landsat images and criteria were established to identify "the change" related to debris flows, (3) the duration and intensity of the precipitation event that caused each of the identified debris flow events was assumed to be that of the most intense event within the investigated period; and (4) the I-D curve was extracted using data (intensity and duration of precipitation) for the inventoried events. Our findings include: (1) the spatial controlling factors with the highest predictive power of debris-flow locations are: topographic position index, slope, NDVI and distance to drainage line; (2) the ANN model showed an excellent prediction performance (area under receiver operating characteristic [ROC] curve: 0.961); 3) the preliminary I-D curve is I=39.797×D-0.7355 (I: Intensity and D: duration).

Event Recognition Based on Deep Learning in Chinese Texts

PubMed Central

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%. PMID:27501231

Event Recognition Based on Deep Learning in Chinese Texts.

PubMed

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

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

PubMed

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

2017-09-21

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

Scavenging and recombination kinetics in a radiation spur: The successive ordered scavenging events

NASA Astrophysics Data System (ADS)

Al-Samra, Eyad H.; Green, Nicholas J. B.

2018-03-01

This study describes stochastic models to investigate the successive ordered scavenging events in a spur of four radicals, a model system based on a radiation spur. Three simulation models have been developed to obtain the probabilities of the ordered scavenging events: (i) a Monte Carlo random flight (RF) model, (ii) hybrid simulations in which the reaction rate coefficient is used to generate scavenging times for the radicals and (iii) the independent reaction times (IRT) method. The results of these simulations are found to be in agreement with one another. In addition, a detailed master equation treatment is also presented, and used to extract simulated rate coefficients of the ordered scavenging reactions from the RF simulations. These rate coefficients are transient, the rate coefficients obtained for subsequent reactions are effectively equal, and in reasonable agreement with the simple correction for competition effects that has recently been proposed.

A logic programming approach to medical errors in imaging.

PubMed

Rodrigues, Susana; Brandão, Paulo; Nelas, Luís; Neves, José; Alves, Victor

2011-09-01

In 2000, the Institute of Medicine reported disturbing numbers on the scope it covers and the impact of medical error in the process of health delivery. Nevertheless, a solution to this problem may lie on the adoption of adverse event reporting and learning systems that can help to identify hazards and risks. It is crucial to apply models to identify the adverse events root causes, enhance the sharing of knowledge and experience. The efficiency of the efforts to improve patient safety has been frustratingly slow. Some of this insufficiency of progress may be assigned to the lack of systems that take into account the characteristic of the information about the real world. In our daily lives, we formulate most of our decisions normally based on incomplete, uncertain and even forbidden or contradictory information. One's knowledge is less based on exact facts and more on hypothesis, perceptions or indications. From the data collected on our adverse event treatment and learning system on medical imaging, and through the use of Extended Logic Programming to knowledge representation and reasoning, and the exploitation of new methodologies for problem solving, namely those based on the perception of what is an agent and/or multi-agent systems, we intend to generate reports that identify the most relevant causes of error and define improvement strategies, concluding about the impact, place of occurrence, form or type of event recorded in the healthcare institutions. The Eindhoven Classification Model was extended and adapted to the medical imaging field and used to classify adverse events root causes. Extended Logic Programming was used for knowledge representation with defective information, allowing for the modelling of the universe of discourse in terms of data and knowledge default. A systematization of the evolution of the body of knowledge about Quality of Information embedded in the Root Cause Analysis was accomplished. An adverse event reporting and learning system was developed based on the presented approach to medical errors in imaging. This system was deployed in two Portuguese healthcare institutions, with an appealing outcome. The system enabled to verify that the majority of occurrences were concentrated in a few events that could be avoided. The developed system allowed automatic knowledge extraction, enabling report generation with strategies for the improvement of quality-of-care. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.

PubMed

Liu, Jing; Zhao, Songzheng; Wang, Gang

2018-01-01

With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., drug indication and beneficial effect) could hold between the drug and adverse event mentions, making ADE relation extraction - distinguishing ADE relationship from other relation types - necessary. However, conducting ADE relation extraction in social media environment is not a trivial task because of the expertise-dependent, time-consuming and costly annotation process, and the feature space's high-dimensionality attributed to intrinsic characteristics of social media data. This study aims to develop a framework for ADE relation extraction using patient-generated content in social media with better performance than that delivered by previous efforts. To achieve the objective, a general semi-supervised ensemble learning framework, SSEL-ADE, was developed. The framework exploited various lexical, semantic, and syntactic features, and integrated ensemble learning and semi-supervised learning. A series of experiments were conducted to verify the effectiveness of the proposed framework. Empirical results demonstrate the effectiveness of each component of SSEL-ADE and reveal that our proposed framework outperforms most of existing ADE relation extraction methods The SSEL-ADE can facilitate enhanced ADE relation extraction performance, thereby providing more reliable support for pharmacovigilance. Moreover, the proposed semi-supervised ensemble methods have the potential of being applied to effectively deal with other social media-based problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Therapeutic effectiveness of a Calendula officinalis extract in venous leg ulcer healing.

PubMed

Buzzi, M; de Freitas, F; de Barros Winter, M

2016-12-02

Non-healing venous leg ulcers (VLUs) have a significant effect on patients' quality of life and substantially increase expenditures in health-care systems. The aim of this study was to evaluate the clinical efficacy of the Calendula officinalis extract, Plenusdermax, in the treatment of VLUs. Patients treated with Calendula officinalis extract (n=38) and control patients (n=19) were evaluated every two weeks for 30 weeks or until their ulcers healed. Assessments included determination of the wound area by planimetry, infection control, and evaluation of the clinical aspects of the wounds. The percentage of healing velocity per week (%HVw), taking the initial area at baseline into account, was also determined. The proportion of the treatment patients achieving complete epithelialisation was 72 % and 32 % in the treatment and control groups, respectively. The average healing time was approximately 12 weeks in the treatment group and 25 % in control patients. Patients with ulcers treated with Calendula officinalis extract had a significant 4-fold increase in percentage healing velocity per week, 7.4 %, compared with 1.7 % in the control group. No adverse events were observed during the Calendula officinalis extract treatment. Our findings indicate that Calendula officinalis extract is an effective treatment for VLUs. The authors have no conflict of interest.

Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review.

PubMed

Tricco, Andrea C; Zarin, Wasifa; Lillie, Erin; Jeblee, Serena; Warren, Rachel; Khan, Paul A; Robson, Reid; Pham, Ba'; Hirst, Graeme; Straus, Sharon E

2018-06-14

A scoping review to characterize the literature on the use of conversations in social media as a potential source of data for detecting adverse events (AEs) related to health products. Our specific research questions were (1) What social media listening platforms exist to detect adverse events related to health products, and what are their capabilities and characteristics? (2) What is the validity and reliability of data from social media for detecting these adverse events? MEDLINE, EMBASE, Cochrane Library, and relevant websites were searched from inception to May 2016. Any type of document (e.g., manuscripts, reports) that described the use of social media data for detecting health product AEs was included. Two reviewers independently screened citations and full-texts, and one reviewer and one verifier performed data abstraction. Descriptive synthesis was conducted. After screening 3631 citations and 321 full-texts, 70 unique documents with 7 companion reports available from 2001 to 2016 were included. Forty-six documents (66%) described an automated or semi-automated information extraction system to detect health product AEs from social media conversations (in the developmental phase). Seven pre-existing information extraction systems to mine social media data were identified in eight documents. Nineteen documents compared AEs reported in social media data with validated data and found consistent AE discovery in all except two documents. None of the documents reported the validity and reliability of the overall system, but some reported on the performance of individual steps in processing the data. The validity and reliability results were found for the following steps in the data processing pipeline: data de-identification (n = 1), concept identification (n = 3), concept normalization (n = 2), and relation extraction (n = 8). The methods varied widely, and some approaches yielded better results than others. Our results suggest that the use of social media conversations for pharmacovigilance is in its infancy. Although social media data has the potential to supplement data from regulatory agency databases; is able to capture less frequently reported AEs; and can identify AEs earlier than official alerts or regulatory changes, the utility and validity of the data source remains under-studied. Open Science Framework ( https://osf.io/kv9hu/ ).

Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.

PubMed

Ibrahim, Heba; Saad, Amr; Abdo, Amany; Sharaf Eldin, A

2016-04-01

Pharmacovigilance (PhV) is an important clinical activity with strong implications for population health and clinical research. The main goal of PhV is the timely detection of adverse drug events (ADEs) that are novel in their clinical nature, severity and/or frequency. Drug interactions (DI) pose an important problem in the development of new drugs and post marketing PhV that contribute to 6-30% of all unexpected ADEs. Therefore, the early detection of DI is vital. Spontaneous reporting systems (SRS) have served as the core data collection system for post marketing PhV since the 1960s. The main objective of our study was to particularly identify signals of DI from SRS. In addition, we are presenting an optimized tailored mining algorithm called "hybrid Apriori". The proposed algorithm is based on an optimized and modified association rule mining (ARM) approach. A hybrid Apriori algorithm has been applied to the SRS of the United States Food and Drug Administration's (U.S. FDA) adverse events reporting system (FAERS) in order to extract significant association patterns of drug interaction-adverse event (DIAE). We have assessed the resulting DIAEs qualitatively and quantitatively using two different triage features: a three-element taxonomy and three performance metrics. These features were applied on two random samples of 100 interacting and 100 non-interacting DIAE patterns. Additionally, we have employed logistic regression (LR) statistic method to quantify the magnitude and direction of interactions in order to test for confounding by co-medication in unknown interacting DIAE patterns. Hybrid Apriori extracted 2933 interacting DIAE patterns (including 1256 serious ones) and 530 non-interacting DIAE patterns. Referring to the current knowledge using four different reliable resources of DI, the results showed that the proposed method can extract signals of serious interacting DIAEs. Various association patterns could be identified based on the relationships among the elements which composed a pattern. The average performance of the method showed 85% precision, 80% negative predictive value, 81% sensitivity and 84% specificity. The LR modeling could provide the statistical context to guard against spurious DIAEs. The proposed method could efficiently detect DIAE signals from SRS data as well as, identifying rare adverse drug reactions (ADRs). Copyright © 2016 Elsevier Inc. All rights reserved.

Beyond Event Segmentation: Spatial- and Social-Cognitive Processes in Verb-to-Action Mapping

ERIC Educational Resources Information Center

Friend, Margaret; Pace, Amy

2011-01-01

The present article investigates spatial- and social-cognitive processes in toddlers' mapping of concepts to real-world events. In 2 studies we explore how event segmentation might lay the groundwork for extracting actions from the event stream and conceptually mapping novel verbs to these actions. In Study 1, toddlers demonstrated the ability to…

A Unified Approach to Abductive Inference

DTIC Science & Technology

2014-09-30

learning in “ Big data ” domains. COMBINING MARKOV LOGIC AND SUPPORT VECTOR MACHINES FOR EVENT EXTRACTION Event extraction is the task of...and                          achieves state­of­the­art performance. This makes it an ideal candidate for learning in “ Big data ...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the

Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information.

PubMed

Kim, Seokyeon; Jeong, Seongmin; Woo, Insoo; Jang, Yun; Maciejewski, Ross; Ebert, David S

2018-03-01

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.

Classifiers utilized to enhance acoustic based sensors to identify round types of artillery/mortar

NASA Astrophysics Data System (ADS)

Grasing, David; Desai, Sachi; Morcos, Amir

2008-04-01

Feature extraction methods based on the statistical analysis of the change in event pressure levels over a period and the level of ambient pressure excitation facilitate the development of a robust classification algorithm. The features reliably discriminates mortar and artillery variants via acoustic signals produced during the launch events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants as type A, etcetera through analysis of the waveform. Distinct characteristics arise within the different mortar/artillery variants because varying HE mortar payloads and related charges emphasize varying size events at launch. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing and data mining techniques can employed to classify a given type. The skewness and other statistical processing techniques are used to extract the predominant components from the acoustic signatures at ranges exceeding 3000m. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of statistical coefficients, frequency spectrum, and higher frequency details found within different energy bands. The processes that are described herein extend current technologies, which emphasis acoustic sensor systems to provide such situational awareness.

Artillery/mortar type classification based on detected acoustic transients

NASA Astrophysics Data System (ADS)

Morcos, Amir; Grasing, David; Desai, Sachi

2008-04-01

Feature extraction methods based on the statistical analysis of the change in event pressure levels over a period and the level of ambient pressure excitation facilitate the development of a robust classification algorithm. The features reliably discriminates mortar and artillery variants via acoustic signals produced during the launch events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants as type A, etcetera through analysis of the waveform. Distinct characteristics arise within the different mortar/artillery variants because varying HE mortar payloads and related charges emphasize varying size events at launch. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing and data mining techniques can employed to classify a given type. The skewness and other statistical processing techniques are used to extract the predominant components from the acoustic signatures at ranges exceeding 3000m. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of statistical coefficients, frequency spectrum, and higher frequency details found within different energy bands. The processes that are described herein extend current technologies, which emphasis acoustic sensor systems to provide such situational awareness.

Non-contact assessment of obstructive sleep apnea cardiovascular biomarkers using photoplethysmography imaging

NASA Astrophysics Data System (ADS)

Amelard, Robert; Pfisterer, Kaylen J.; Jagani, Shubh; Clausi, David A.; Wong, Alexander

2018-02-01

Obstructive sleep apnea (OSA) affects 20% of the adult population, and is associated with cardiovascular and cognitive morbidities. However, it is estimated that up to 80% of treatable OSA cases remain undiagnosed. Cur- rent methods for diagnosing OSA are expensive, labor-intensive, and involve uncomfortable wearable sensors. This study explored the feasibility of non-contact biophotonic assessment of OSA cardiovascular biomarkers via photoplethysmography imaging (PPGI). In particular, PPGI was used to monitor the hemodynamic response to obstructive respiratory events. Sleep apnea onset was simulated using Muller's maneuver in which breathing was obstructed by a respiratory clamp. A custom PPGI system, coded hemodynamic imaging (CHI), was positioned 1 m above the bed and illuminated the participant's head with 850 nm light, providing non-intrusive illumination for night-time monitoring. A video was recorded before, during and following an apnea event at 60 fps, yielding 17 ms temporal resolution. Per-pixel absorbance signals were extracted using a Beer-Lambert derived light transport model, and subsequently denoised. The extracted hemodynamic signal exhibited dynamic temporal modulation during and following the apnea event. In particular, the pulse wave amplitude (PWA) decreased during obstructed breathing, indicating vasoconstriction. Upon successful inhalation, the PWA gradually increased toward homeostasis following a temporal phase delay. This temporal vascular tone modulation provides insight into autonomic and vascular response, and may be used to assess sleep apnea using non-contact biophotonic imaging.

Meta-analysis of published transcriptional and translational fold changes reveals a preference for low-fold inductions.

PubMed

Wren, Jonathan D; Conway, Tyrrell

2006-01-01

The goals of this study were to gain a better quantitative understanding of the dynamic range of transcriptional and translational response observed in biological systems and to examine the reporting of regulatory events for trends and biases. A straightforward pattern-matching routine extracted 3,408 independent observations regarding transcriptional fold-changes and 1,125 regarding translational fold-changes from over 15 million MEDLINE abstracts. Approximately 95% of reported changes were > or =2-fold. Further, the historical trend of reporting individual fold-changes is declining in favor of high-throughput methods for transcription but not translation. Where it was possible to compare the average fold-changes in transcription and translation for the same gene/product (203 examples), approximately 53% were a < or =2-fold difference, suggesting a loose tendency for the two to be coupled in magnitude. We found also that approximately three-fourths of reported regulatory events have been at the transcriptional level. The frequency distribution appears to be normally distributed and peaks near 2-fold, suggesting that nature selects for a low-energy solution to regulatory responses. Because high-throughput technologies ordinarily sacrifice measurement quality for quantity, this also suggests that many regulatory events may not be reliably detectable by such technologies. Text mining of regulatory events and responses provides additional information incorporable into microarray analysis, such as prior fold-change observations and flagging genes that are regulated post-transcription. All extracted regulation and response patterns can be downloaded at the following website: www.ou.edu/microarray/ oumcf/Meta_analysis.xls.

Three-year outcomes of root canal treatment: Mining an insurance database.

PubMed

Raedel, Michael; Hartmann, Andrea; Bohm, Steffen; Walter, Michael H

2015-04-01

There is doubt whether success rates of root canal treatments reported from clinical trials are achievable outside of standardized study populations. The aim of this study was to analyse the outcome of a large number of root canal treatments conducted in general practice. The data was collected from the digital database of a major German national health insurance company. All teeth with complete treatment data were included. Only patients who had been insurance members for the whole 3-year period from 2010 to 2012 were eligible. Kaplan-Meier survival analyses were conducted based on completed root canal treatments. Target events were re-interventions as (1) retreatment of the root canal treatment, (2) apical root resection (apicoectomy) and (3) extraction. The influences of vitality status and root numbers on survival were tested with the log-rank test. A total of 556,067 root canal treatments were included. The cumulative overall survival rate for all target events combined was 84.3% for 3 years. The survival rate for nonvital teeth (82.6%) was significantly lower than for vital teeth (85.6%; p<0.001). The survival rate for single rooted teeth (83.4%) was significantly lower than for multi-rooted teeth (85.5%; p<0.001). The most frequent target event was extraction followed by apical root resection and retreatment. Based on these 3-year outcomes, root canal treatment is considered a reliable treatment in practice routine under the conditions of the German national health insurance system. Root canal treatment can be considered as a reliable treatment option suitable to salvage most of the affected teeth. This statement applies to treatments that in the vast majority of cases were delivered by general practitioners under the terms and conditions of a nationwide health insurance system. Copyright © 2015 Elsevier Ltd. All rights reserved.

West-Coast Wide Expansion and Testing of the Geodetic Alarm System (G-larmS)

NASA Astrophysics Data System (ADS)

Ruhl, C. J.; Grapenthin, R.; Melgar, D.; Aranha, M. A.; Allen, R. M.

2016-12-01

The Geodetic Alarm System (G-larmS) was developed in collaboration between the Berkeley Seismological Laboratory (BSL) and New Mexico Tech for real-time Earthquake Early Warning (EEW). G-larmS has been in continuous operation at the BSL since 2014 using event triggers from the ShakeAlert EEW system and real-time position time series from a fully triangulated network consisting of BARD, PBO and USGS stations across northern California (CA). G-larmS has been extended to include southern CA and Cascadia, providing continuous west-coast wide coverage. G-larmS currently uses high rate (1 Hz), low latency (< 5 s), accurate positioning (cm level) time series data from a regional GPS network and P-wave event triggers from the ShakeAlert EEW system. It extracts static offsets from real-time GPS time series upon S-wave arrival and performs a least squares inversion on these offsets to determine slip on a finite fault. A key issue with geodetic EEW approaches is that unlike seismology-based algorithms that are routinely tested using frequent small-magnitude events, geodetic systems are not regularly exercised. Scenario ruptures are therefore important for testing the performance of G-larmS. We discuss results from scenario events on several large faults (capable of M>6.5) in CA and Cascadia built from realistic 3D geometries. Synthetic long-period 1Hz displacement waveforms were obtained from a new stochastic kinematic slip distribution generation method. Waveforms are validated by direct comparison to peak P-wave displacement scaling laws and to PGD GMPEs obtained from high-rate GPS observations of large events worldwide. We run the scenarios on real-time streams to systematically test the recovery of slip and magnitude by G-larmS. In addition to presenting these results, we will discuss new capabilities, such as implementing 2D geometry and the applicability of these results to GPS enhanced tsunami warning systems.

Upgrade to a programmable timing system for the KOMAC proton linac and multi-purpose beam lines

NASA Astrophysics Data System (ADS)

Song, Young-Gi

2016-09-01

The KOMAC facility consists of low-energy components, including a 50-keV ion source, a lowenergy beam transport (LEBT), a 3-MeV radio-frequency quadrupole (RFQ), and a 20-MeV drift tube linac (DTL), as well as high-energy components, including seven DTL tanks for the 100-MeV proton beam. The KOMAC includes ten beam lines, five for 20-MeV beams and five for 100-MeV beams. The peak beam current and the maximum beam duty are 20 mA and 24% for the 20-MeV linac and 20 mA and 8% for the 100-MeV linac, respectively. Four high-voltage convertor modulators are used. Each modulator drives two or three klystrons. The peak output power is 5.8 MW, and the average power is 520 kW with a duty of 9%. The pulse width and repetition rate are 1.5 ms and 60 Hz, respectively. Each component of the pulsed operation mode has a timing trigger signal with precision synchronization. A timing system for beam extraction and for diagnostic components is required to provide precise pulse signals synchronized with a 300-MHz RF reference frequency. In addition, the timing parameters should be capable of real-time changes in accordance with the beam power. The KOMAC timing system has been upgraded to a programmable Micro Research Finland (MRF) event timing system that is synchronized with the RF, AC main frequency and with the global positioning system (GPS) 1-PPS signal. The event timing system consists of an event generator (EVG) and an event receiver (EVR). The event timing system is integrated with the KOMAC control system by using experimental physics and industrial control system (EPICS) software. For preliminary hardware and software testing, a long operation test with a synchronization of 300-MHz RF reference and 60-Hz AC has been completed successfully. In this paper, we will describe the software implementation, the testing, and the installation of the new timing system.

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

Identification of research hypotheses and new knowledge from scientific literature.

PubMed

Shardlow, Matthew; Batista-Navarro, Riza; Thompson, Paul; Nawaz, Raheel; McNaught, John; Ananiadou, Sophia

2018-06-25

Text mining (TM) methods have been used extensively to extract relations and events from the literature. In addition, TM techniques have been used to extract various types or dimensions of interpretative information, known as Meta-Knowledge (MK), from the context of relations and events, e.g. negation, speculation, certainty and knowledge type. However, most existing methods have focussed on the extraction of individual dimensions of MK, without investigating how they can be combined to obtain even richer contextual information. In this paper, we describe a novel, supervised method to extract new MK dimensions that encode Research Hypotheses (an author's intended knowledge gain) and New Knowledge (an author's findings). The method incorporates various features, including a combination of simple MK dimensions. We identify previously explored dimensions and then use a random forest to combine these with linguistic features into a classification model. To facilitate evaluation of the model, we have enriched two existing corpora annotated with relations and events, i.e., a subset of the GENIA-MK corpus and the EU-ADR corpus, by adding attributes to encode whether each relation or event corresponds to Research Hypothesis or New Knowledge. In the GENIA-MK corpus, these new attributes complement simpler MK dimensions that had previously been annotated. We show that our approach is able to assign different types of MK dimensions to relations and events with a high degree of accuracy. Firstly, our method is able to improve upon the previously reported state of the art performance for an existing dimension, i.e., Knowledge Type. Secondly, we also demonstrate high F1-score in predicting the new dimensions of Research Hypothesis (GENIA: 0.914, EU-ADR 0.802) and New Knowledge (GENIA: 0.829, EU-ADR 0.836). We have presented a novel approach for predicting New Knowledge and Research Hypothesis, which combines simple MK dimensions to achieve high F1-scores. The extraction of such information is valuable for a number of practical TM applications.

Crustal Structure of Khövsgöl, Mongolia

NASA Astrophysics Data System (ADS)

Scott, A. M.; Meltzer, A.; Stachnik, J.; Russo, R.; Munkhuu, U.; Tsagaan, B.

2017-12-01

Mongolia is part of the Central Asian Orogenic Belt, an accretionary event that spanned 800 million years from the mid-Proterozoic to mid-Phanerozoic. As a result of the past collisional and rifting events, the modern Khövsgöl rift system of northern Mongolia contains a heterogeneous lithospheric structure. The current rift system has three parallel N-S trending basins that roughly align with terrane boundaries. Structures inherited during the accretionary events may be a factor influencing regional deformation. The forces that drive local deformation are not well understood, but varying processes have been proposed: far-field effects of India-Eurasian plate convergence, westward subduction of the Pacific plate, magmatic underplating at the base of the crust, mantle plume activity, and asthenospheric mantle convection. Determining the nature of crustal features within this poorly understood region may illuminate processes that control rifting within intracontinental settings. A network of 26 broadband seismic stations encompassing 200 square kilometers of the Khövsgöl rift system were deployed from August 2014 to June 2016. More than 2100 events were detected, and most earthquakes were concentrated near rift structures. Events between Busiin-Gol and Darkhad, the westernmost and central basins of the Khövsgöl rift system, are distributed within the crust. An active fault is outlined along the eastern border of the Darkhad basin. Khövsgöl earthquakes bound both sides of the rift. Along the northern border of Lake Khövsgöl, seismic events define a shallow active fault orthogonal to the basin. The largest event recorded within the network was a magnitude ml=5.2 located near the northeastern border of Lake Khövsgöl on 12-05-2014. The focal mechanism of this earthquake is predominantly strike-slip, but also includes an extensional component. This work focuses on earthquake relocation and calculating moment tensors and focal mechanisms of larger regional events to extract additional information about the local faults and their relationship to preexisting structures.

A High Throughput Method for Measuring Polycyclic Aromatic Hydrocarbons in Seafood Using QuEChERS Extraction and SBSE.

PubMed

Pfannkoch, Edward A; Stuff, John R; Whitecavage, Jacqueline A; Blevins, John M; Seely, Kathryn A; Moran, Jeffery H

2015-01-01

National Oceanic and Atmospheric Administration (NOAA) Method NMFS-NWFSC-59 2004 is currently used to quantitatively analyze seafood for polycyclic aromatic hydrocarbon (PAH) contamination, especially following events such as the Deepwater Horizon oil rig explosion that released millions of barrels of crude oil into the Gulf of Mexico. This method has limited throughput capacity; hence, alternative methods are necessary to meet analytical demands after such events. Stir bar sorptive extraction (SBSE) is an effective technique to extract trace PAHs in water and the quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction strategy effectively extracts PAHs from complex food matrices. This study uses SBSE to concentrate PAHs and eliminate matrix interference from QuEChERS extracts of seafood, specifically oysters, fish, and shrimp. This method provides acceptable recovery (65-138%) linear calibrations and is sensitive (LOD = 0.02 ppb, LOQ = 0.06 ppb) while providing higher throughput and maintaining equivalency between NOAA 2004 as determined by analysis of NIST SRM 1974b mussel tissue.

Analyzing and Identifying Teens' Stressful Periods and Stressor Events From a Microblog.

PubMed

Li, Qi; Xue, Yuanyuan; Zhao, Liang; Jia, Jia; Feng, Ling

2017-09-01

Increased health problems among adolescents caused by psychological stress have aroused worldwide attention. Long-standing stress without targeted assistance and guidance negatively impacts the healthy growth of adolescents, threatening the future development of our society. So far, research focused on detecting adolescent psychological stress revealed from each individual post on microblogs. However, beyond stressful moments, identifying teens' stressful periods and stressor events that trigger each stressful period is more desirable to understand the stress from appearance to essence. In this paper, we define the problem of identifying teens' stressful periods and stressor events from the open social media microblog. Starting from a case study of adolescents' posting behaviors during stressful school events, we build a Poisson-based probability model for the correlation between stressor events and stressful posting behaviors through a series of posts on Tencent Weibo (referred to as the microblog throughout the paper). With the model, we discover teens' maximal stressful periods and further extract details of possible stressor events that cause the stressful periods. We generalize and present the extracted stressor events in a hierarchy based on common stress dimensions and event types. Taking 122 scheduled stressful study-related events in a high school as the ground truth, we test the approach on 124 students' posts from January 1, 2012 to February 1, 2015 and obtain some promising experimental results: (stressful periods: recall 0.761, precision 0.737, and F 1 -measure 0.734) and (top-3 stressor events: recall 0.763, precision 0.756, and F 1 -measure 0.759). The most prominent stressor events extracted are in the self-cognition domain, followed by the school life domain. This conforms to the adolescent psychological investigation result that problems in school life usually accompanied with teens' inner cognition problems. Compared with the state-of-the-art top-1 personal life event detection approach, our stressor event detection method is 13.72% higher in precision, 19.18% higher in recall, and 16.50% higher in F 1 -measure, demonstrating the effectiveness of our proposed framework.

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

The First Planetary Microlensing Event with Two Microlensed Source Stars

NASA Astrophysics Data System (ADS)

Bennett, D. P.; Udalski, A.; Han, C.; Bond, I. A.; Beaulieu, J.-P.; Skowron, J.; Gaudi, B. S.; Koshimoto, N.; Abe, F.; Asakura, Y.; Barry, R. K.; Bhattacharya, A.; Donachie, M.; Evans, P.; Fukui, A.; Hirao, Y.; Itow, Y.; Li, M. C. A.; Ling, C. H.; Masuda, K.; Matsubara, Y.; Muraki, Y.; Nagakane, M.; Ohnishi, K.; Oyokawa, H.; Ranc, C.; Rattenbury, N. J.; Rosenthal, M. M.; Saito, To.; Sharan, A.; Sullivan, D. J.; Sumi, T.; Suzuki, D.; Tristram, P. J.; Yonehara, A.; The MOA Collaboration; Szymański, M. K.; Poleski, R.; Soszyński, I.; Ulaczyk, K.; Wyrzykowski, Ł.; The OGLE Collaboration; DePoy, D.; Gould, A.; Pogge, R. W.; Yee, J. C.; The μFUN Collaboration; Albrow, M. D.; Bachelet, E.; Batista, V.; Bowens-Rubin, R.; Brillant, S.; Caldwell, J. A. R.; Cole, A.; Coutures, C.; Dieters, S.; Dominis Prester, D.; Donatowicz, J.; Fouqué, P.; Horne, K.; Hundertmark, M.; Kains, N.; Kane, S. R.; Marquette, J.-B.; Menzies, J.; Pollard, K. R.; Ranc, C.; Sahu, K. C.; Wambsganss, J.; Williams, A.; Zub, M.; The PLANET Collaboration

2018-03-01

We present the analysis of the microlensing event MOA-2010-BLG-117, and show that the light curve can only be explained by the gravitational lensing of a binary source star system by a star with a Jupiter-mass ratio planet. It was necessary to modify standard microlensing modeling methods to find the correct light curve solution for this binary source, binary-lens event. We are able to measure a strong microlensing parallax signal, which yields the masses of the host star, M * = 0.58 ± 0.11 M ⊙, and planet, m p = 0.54 ± 0.10M Jup, at a projected star–planet separation of a ⊥ = 2.42 ± 0.26 au, corresponding to a semimajor axis of a=2.9≥nfrac{}{}{0em}{}{+1.6}{-0.6} au. Thus, the system resembles a half-scale model of the Sun–Jupiter system with a half-Jupiter0mass planet orbiting a half-solar-mass star at very roughly half of Jupiter’s orbital distance from the Sun. The source stars are slightly evolved, and by requiring them to lie on the same isochrone, we can constrain the source to lie in the near side of the bulge at a distance of D S = 6.9 ± 0.7 kpc, which implies a distance to the planetary lens system of D L = 3.5 ± 0.4 kpc. The ability to model unusual planetary microlensing events, like this one, will be necessary to extract precise statistical information from the planned large exoplanet microlensing surveys, such as the WFIRST microlensing survey.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Time-resolved single-shot terahertz time-domain spectroscopy for ultrafast irreversible processes

NASA Astrophysics Data System (ADS)

Zhai, Zhao-Hui; Zhong, Sen-Cheng; Li, Jun; Zhu, Li-Guo; Meng, Kun; Li, Jiang; Liu, Qiao; Peng, Qi-Xian; Li, Ze-Ren; Zhao, Jian-Heng

2016-09-01

Pulsed terahertz spectroscopy is suitable for spectroscopic diagnostics of ultrafast events. However, the study of irreversible or single shot ultrafast events requires ability to record transient properties at multiple time delays, i.e., time resolved at single shot level, which is not available currently. Here by angular multiplexing use of femtosecond laser pulses, we developed and demonstrated a time resolved, transient terahertz time domain spectroscopy technique, where burst mode THz pulses were generated and then detected in a single shot measurement manner. The burst mode THz pulses contain 2 sub-THz pulses, and the time gap between them is adjustable up to 1 ns with picosecond accuracy, thus it can be used to probe the single shot event at two different time delays. The system can detect the sub-THz pulses at 0.1 THz-2.5 THz range with signal to noise ratio (SNR) of ˜400 and spectrum resolution of 0.05 THz. System design was described here, and optimizations of single shot measurement of THz pulses were discussed in detail. Methods to improve SNR were also discussed in detail. A system application was demonstrated where pulsed THz signals at different time delays of the ultrafast process were successfully acquired within single shot measurement. This time resolved transient terahertz time domain spectroscopy technique provides a new diagnostic tool for irreversible or single shot ultrafast events where dynamic information can be extracted at terahertz range within one-shot experiment.

Time-resolved single-shot terahertz time-domain spectroscopy for ultrafast irreversible processes.

PubMed

Zhai, Zhao-Hui; Zhong, Sen-Cheng; Li, Jun; Zhu, Li-Guo; Meng, Kun; Li, Jiang; Liu, Qiao; Peng, Qi-Xian; Li, Ze-Ren; Zhao, Jian-Heng

2016-09-01

Pulsed terahertz spectroscopy is suitable for spectroscopic diagnostics of ultrafast events. However, the study of irreversible or single shot ultrafast events requires ability to record transient properties at multiple time delays, i.e., time resolved at single shot level, which is not available currently. Here by angular multiplexing use of femtosecond laser pulses, we developed and demonstrated a time resolved, transient terahertz time domain spectroscopy technique, where burst mode THz pulses were generated and then detected in a single shot measurement manner. The burst mode THz pulses contain 2 sub-THz pulses, and the time gap between them is adjustable up to 1 ns with picosecond accuracy, thus it can be used to probe the single shot event at two different time delays. The system can detect the sub-THz pulses at 0.1 THz-2.5 THz range with signal to noise ratio (SNR) of ∼400 and spectrum resolution of 0.05 THz. System design was described here, and optimizations of single shot measurement of THz pulses were discussed in detail. Methods to improve SNR were also discussed in detail. A system application was demonstrated where pulsed THz signals at different time delays of the ultrafast process were successfully acquired within single shot measurement. This time resolved transient terahertz time domain spectroscopy technique provides a new diagnostic tool for irreversible or single shot ultrafast events where dynamic information can be extracted at terahertz range within one-shot experiment.

Classification of speech dysfluencies using LPC based parameterization techniques.

PubMed

Hariharan, M; Chee, Lim Sin; Ai, Ooi Chia; Yaacob, Sazali

2012-06-01

The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients (WLPCC) for recognizing the stuttered events. Speech samples from the University College London Archive of Stuttered Speech (UCLASS) were used for our analysis. The stuttered events were identified through manual segmentation and were used for feature extraction. Two simple classifiers namely, k-nearest neighbour (kNN) and Linear Discriminant Analysis (LDA) were employed for speech dysfluencies classification. Conventional validation method was used for testing the reliability of the classifier results. The study on the effect of different frame length, percentage of overlapping, value of ã in a first order pre-emphasizer and different order p were discussed. The speech dysfluencies classification accuracy was found to be improved by applying statistical normalization before feature extraction. The experimental investigation elucidated LPC, LPCC and WLPCC features can be used for identifying the stuttered events and WLPCC features slightly outperforms LPCC features and LPC features.

Extracting rate changes in transcriptional regulation from MEDLINE abstracts.

PubMed

Liu, Wenting; Miao, Kui; Li, Guangxia; Chang, Kuiyu; Zheng, Jie; Rajapakse, Jagath C

2014-01-01

Time delays are important factors that are often neglected in gene regulatory network (GRN) inference models. Validating time delays from knowledge bases is a challenge since the vast majority of biological databases do not record temporal information of gene regulations. Biological knowledge and facts on gene regulations are typically extracted from bio-literature with specialized methods that depend on the regulation task. In this paper, we mine evidences for time delays related to the transcriptional regulation of yeast from the PubMed abstracts. Since the vast majority of abstracts lack quantitative time information, we can only collect qualitative evidences of time delays. Specifically, the speed-up or delay in transcriptional regulation rate can provide evidences for time delays (shorter or longer) in GRN. Thus, we focus on deriving events related to rate changes in transcriptional regulation. A corpus of yeast regulation related abstracts was manually labeled with such events. In order to capture these events automatically, we create an ontology of sub-processes that are likely to result in transcription rate changes by combining textual patterns and biological knowledge. We also propose effective feature extraction methods based on the created ontology to identify the direct evidences with specific details of these events. Our ontologies outperform existing state-of-the-art gene regulation ontologies in the automatic rule learning method applied to our corpus. The proposed deterministic ontology rule-based method can achieve comparable performance to the automatic rule learning method based on decision trees. This demonstrates the effectiveness of our ontology in identifying rate-changing events. We also tested the effectiveness of the proposed feature mining methods on detecting direct evidence of events. Experimental results show that the machine learning method on these features achieves an F1-score of 71.43%. The manually labeled corpus of events relating to rate changes in transcriptional regulation for yeast is available in https://sites.google.com/site/wentingntu/data. The created ontologies summarized both biological causes of rate changes in transcriptional regulation and corresponding positive and negative textual patterns from the corpus. They are demonstrated to be effective in identifying rate-changing events, which shows the benefits of combining textual patterns and biological knowledge on extracting complex biological events.

Neural computing for numeric-to-symbolic conversion in control systems

NASA Technical Reports Server (NTRS)

Passino, Kevin M.; Sartori, Michael A.; Antsaklis, Panos J.

1989-01-01

A type of neural network, the multilayer perceptron, is used to classify numeric data and assign appropriate symbols to various classes. This numeric-to-symbolic conversion results in a type of information extraction, which is similar to what is called data reduction in pattern recognition. The use of the neural network as a numeric-to-symbolic converter is introduced, its application in autonomous control is discussed, and several applications are studied. The perceptron is used as a numeric-to-symbolic converter for a discrete-event system controller supervising a continuous variable dynamic system. It is also shown how the perceptron can implement fault trees, which provide useful information (alarms) in a biological system and information for failure diagnosis and control purposes in an aircraft example.

FPGA-based trigger system for the LUX dark matter experiment

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Bradley, A.; Bramante, R.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Chapman, J. J.; Chiller, A. A.; Chiller, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; de Viveiros, L.; Dobi, A.; Dobson, J. E. Y.; Druszkiewicz, E.; Edwards, B. N.; Faham, C. H.; Fiorucci, S.; Gaitskell, R. J.; Gehman, V. M.; Ghag, C.; Gibson, K. R.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Ihm, M.; Jacobsen, R. G.; Ji, W.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lee, C.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Malling, D. C.; Manalaysay, A. G.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O`Sullivan, K.; Oliver-Mallory, K. C.; Ott, R. A.; Palladino, K. J.; Pangilinan, M.; Pease, E. K.; Phelps, P.; Reichhart, L.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Skulski, W.; Solovov, V. N.; Sorensen, P.; Stephenson, S.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Yin, J.; Young, S. K.; Zhang, C.

2016-05-01

LUX is a two-phase (liquid/gas) xenon time projection chamber designed to detect nuclear recoils resulting from interactions with dark matter particles. Signals from the detector are processed with an FPGA-based digital trigger system that analyzes the incoming data in real-time, with just a few microsecond latency. The system enables first pass selection of events of interest based on their pulse shape characteristics and 3D localization of the interactions. It has been shown to be > 99 % efficient in triggering on S2 signals induced by only few extracted liquid electrons. It is continuously and reliably operating since its full underground deployment in early 2013. This document is an overview of the systems capabilities, its inner workings, and its performance.

Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

PubMed

Elayavilli, Ravikumar Komandur; Liu, Hongfang

2016-01-01

Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological framework. The ICEPO ontology is available for download at http://openbionlp.org/mutd/supplementarydata/ICEPO/ICEPO.owl.

An event database for rotational seismology

NASA Astrophysics Data System (ADS)

Salvermoser, Johannes; Hadziioannou, Celine; Hable, Sarah; Chow, Bryant; Krischer, Lion; Wassermann, Joachim; Igel, Heiner

2016-04-01

The ring laser sensor (G-ring) located at Wettzell, Germany, routinely observes earthquake-induced rotational ground motions around a vertical axis since its installation in 2003. Here we present results from a recently installed event database which is the first that will provide ring laser event data in an open access format. Based on the GCMT event catalogue and some search criteria, seismograms from the ring laser and the collocated broadband seismometer are extracted and processed. The ObsPy-based processing scheme generates plots showing waveform fits between rotation rate and transverse acceleration and extracts characteristic wavefield parameters such as peak ground motions, noise levels, Love wave phase velocities and waveform coherence. For each event, these parameters are stored in a text file (json dictionary) which is easily readable and accessible on the website. The database contains >10000 events starting in 2007 (Mw>4.5). It is updated daily and therefore provides recent events at a time lag of max. 24 hours. The user interface allows to filter events for epoch, magnitude, and source area, whereupon the events are displayed on a zoomable world map. We investigate how well the rotational motions are compatible with the expectations from the surface wave magnitude scale. In addition, the website offers some python source code examples for downloading and processing the openly accessible waveforms.

VHDL implementation of feature-extraction algorithm for the PANDA electromagnetic calorimeter

NASA Astrophysics Data System (ADS)

Guliyev, E.; Kavatsyuk, M.; Lemmens, P. J. J.; Tambave, G.; Löhner, H.; Panda Collaboration

2012-02-01

A simple, efficient, and robust feature-extraction algorithm, developed for the digital front-end electronics of the electromagnetic calorimeter of the PANDA spectrometer at FAIR, Darmstadt, is implemented in VHDL for a commercial 16 bit 100 MHz sampling ADC. The source-code is available as an open-source project and is adaptable for other projects and sampling ADCs. Best performance with different types of signal sources can be achieved through flexible parameter selection. The on-line data-processing in FPGA enables to construct an almost dead-time free data acquisition system which is successfully evaluated as a first step towards building a complete trigger-less readout chain. Prototype setups are studied to determine the dead-time of the implemented algorithm, the rate of false triggering, timing performance, and event correlations.

MedEx/J: A One-Scan Simple and Fast NLP Tool for Japanese Clinical Texts.

PubMed

Aramaki, Eiji; Yano, Ken; Wakamiya, Shoko

2017-01-01

Because of recent replacement of physical documents with electronic medical records (EMR), the importance of information processing in the medical field has increased. In light of this trend, we have been developing MedEx/J, which retrieves important Japanese language information from medical reports. MedEx/J executes two tasks simultaneously: (1) term extraction, and (2) positive and negative event classification. We designate this approach as a one-scan approach, providing simplicity of systems and reasonable accuracy. MedEx/J performance on the two tasks is described herein: (1) term extraction (Fβ = 1 = 0.87) and (2) positive-negative classification (Fβ = 1 = 0.63). This paper also presents discussion and explains remaining issues in the medical natural language processing field.

Computer vision in cell biology.

PubMed

Danuser, Gaudenz

2011-11-23

Computer vision refers to the theory and implementation of artificial systems that extract information from images to understand their content. Although computers are widely used by cell biologists for visualization and measurement, interpretation of image content, i.e., the selection of events worth observing and the definition of what they mean in terms of cellular mechanisms, is mostly left to human intuition. This Essay attempts to outline roles computer vision may play and should play in image-based studies of cellular life. Copyright © 2011 Elsevier Inc. All rights reserved.

The Redox-sensitive Induction of the Local Angiotensin System Promotes Both Premature and Replicative Endothelial Senescence: Preventive Effect of a Standardized Crataegus Extract.

PubMed

Khemais-Benkhiat, Sonia; Idris-Khodja, Noureddine; Ribeiro, Thais Porto; Silva, Grazielle Caroline; Abbas, Malak; Kheloufi, Marouane; Lee, Jung-Ok; Toti, Florence; Auger, Cyril; Schini-Kerth, Valérie B

2016-12-01

Endothelial senescence, characterized by an irreversible cell cycle arrest, oxidative stress, and downregulation of endothelial nitric oxide synthase (eNOS), has been shown to promote endothelial dysfunction leading to the development of age-related vascular disorders. This study has assessed the possibility that the local angiotensin system promotes endothelial senescence in coronary artery endothelial cells and also the protective effect of the Crataegus extract WS1442, a quantified hawthorn extract. Serial passaging from P1 to P4 (replicative senescence) and treatment of P1 endothelial cells with the eNOS inhibitor L-NAME (premature senescence) promoted acquisition of markers of senescence, enhanced ROS formation, decreased eNOS expression, and upregulation of angiotensin-converting enzyme (ACE) and AT1 receptors. Increased SA-β-gal activity and the upregulation of ACE and AT1R in senescent cells were prevented by antioxidants, an ACE inhibitor, and by an AT1 receptor blocker. WS1442 prevented SA-β-gal activity, the downregulation of eNOS, and oxidative stress in P3 cells. These findings indicate that the impairment of eNOS-derived nitric oxide formation favors a pro-oxidant response triggering the local angiotensin system, which, in turn, promotes endothelial senescence. Such a sequence of events can be effectively inhibited by a standardized polyphenol-rich extract mainly by targeting the oxidative stress. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Inclusion of angular momentum in FREYA

DOE PAGES

Randrup, Jørgen; Vogt, Ramona

2015-05-18

The event-by-event fission model FREYA generates large samples of complete fission events from which any observable can extracted, including fluctuations of the observables and the correlations between them. We describe here how FREYA was recently refined to include angular momentum throughout. Subsequently we present some recent results for both neutron and photon observables.

Extraction of a group-pair relation: problem-solving relation from web-board documents.

PubMed

Pechsiri, Chaveevan; Piriyakul, Rapepun

2016-01-01

This paper aims to extract a group-pair relation as a Problem-Solving relation, for example a DiseaseSymptom-Treatment relation and a CarProblem-Repair relation, between two event-explanation groups, a problem-concept group as a symptom/CarProblem-concept group and a solving-concept group as a treatment-concept/repair concept group from hospital-web-board and car-repair-guru-web-board documents. The Problem-Solving relation (particularly Symptom-Treatment relation) including the graphical representation benefits non-professional persons by supporting knowledge of primarily solving problems. The research contains three problems: how to identify an EDU (an Elementary Discourse Unit, which is a simple sentence) with the event concept of either a problem or a solution; how to determine a problem-concept EDU boundary and a solving-concept EDU boundary as two event-explanation groups, and how to determine the Problem-Solving relation between these two event-explanation groups. Therefore, we apply word co-occurrence to identify a problem-concept EDU and a solving-concept EDU, and machine-learning techniques to solve a problem-concept EDU boundary and a solving-concept EDU boundary. We propose using k-mean and Naïve Bayes to determine the Problem-Solving relation between the two event-explanation groups involved with clustering features. In contrast to previous works, the proposed approach enables group-pair relation extraction with high accuracy.

Monitoring and evaluating civil structures using measured vibration

NASA Astrophysics Data System (ADS)

Straser, Erik G.; Kiremidjian, Anne S.

1996-04-01

The need for a rapid assessment of the state of critical and conventional civil structures, such as bridges, control centers, airports, and hospitals, among many, has been amply demonstrated during recent natural disasters. Research is underway at Stanford University to develop a state-of-the-art automated damage monitoring system for long term and extreme event monitoring based on both ambient and forced response measurements. Such research requires a multi-disciplinary approach harnessing the talents and expertise of civil, electrical, and mechanical engineering to arrive at a novel hardware and software solution. Recent advances in silicon micro-machining and microprocessor design allow for the economical integration of sensing, processing, and communication components. Coupling these technological advances with parameter identification algorithms allows for the realization of extreme event damage monitoring systems for civil structures. This paper addresses the first steps toward the development of a near real-time damage diagnostic and monitoring system based on structural response to extreme events. Specifically, micro-electro-mechanical- structures (MEMS) and microcontroller embedded systems (MES) are demonstrated to be an effective platform for the measurement and analysis of civil structures. Experimental laboratory tests with small scale model specimens and a preliminary sensor module are used to evaluate hardware and obtain structural response data from input accelerograms. A multi-step analysis procedure employing ordinary least squares (OLS), extended Kalman filtering (EKF), and a substructuring approach is conducted to extract system characteristics of the model. Results from experimental tests and system identification (SI) procedures as well as fundamental system design issues are presented.

Topological properties of flat electroencephalography's state space

NASA Astrophysics Data System (ADS)

Ken, Tan Lit; Ahmad, Tahir bin; Mohd, Mohd Sham bin; Ngien, Su Kong; Suwa, Tohru; Meng, Ong Sie

2016-02-01

Neuroinverse problem are often associated with complex neuronal activity. It involves locating problematic cell which is highly challenging. While epileptic foci localization is possible with the aid of EEG signals, it relies greatly on the ability to extract hidden information or pattern within EEG signals. Flat EEG being an enhancement of EEG is a way of viewing electroencephalograph on the real plane. In the perspective of dynamical systems, Flat EEG is equivalent to epileptic seizure hence, making it a great platform to study epileptic seizure. Throughout the years, various mathematical tools have been applied on Flat EEG to extract hidden information that is hardly noticeable by traditional visual inspection. While these tools have given worthy results, the journey towards understanding seizure process completely is yet to be succeeded. Since the underlying structure of Flat EEG is dynamic and is deemed to contain wealthy information regarding brainstorm, it would certainly be appealing to explore in depth its structures. To better understand the complex seizure process, this paper studies the event of epileptic seizure via Flat EEG in a more general framework by means of topology, particularly, on the state space where the event of Flat EEG lies.

Auditory object salience: human cortical processing of non-biological action sounds and their acoustic signal attributes

PubMed Central

Lewis, James W.; Talkington, William J.; Tallaksen, Katherine C.; Frum, Chris A.

2012-01-01

Whether viewed or heard, an object in action can be segmented as a distinct salient event based on a number of different sensory cues. In the visual system, several low-level attributes of an image are processed along parallel hierarchies, involving intermediate stages wherein gross-level object form and/or motion features are extracted prior to stages that show greater specificity for different object categories (e.g., people, buildings, or tools). In the auditory system, though relying on a rather different set of low-level signal attributes, meaningful real-world acoustic events and “auditory objects” can also be readily distinguished from background scenes. However, the nature of the acoustic signal attributes or gross-level perceptual features that may be explicitly processed along intermediate cortical processing stages remain poorly understood. Examining mechanical and environmental action sounds, representing two distinct non-biological categories of action sources, we had participants assess the degree to which each sound was perceived as object-like versus scene-like. We re-analyzed data from two of our earlier functional magnetic resonance imaging (fMRI) task paradigms (Engel et al., 2009) and found that scene-like action sounds preferentially led to activation along several midline cortical structures, but with strong dependence on listening task demands. In contrast, bilateral foci along the superior temporal gyri (STG) showed parametrically increasing activation to action sounds rated as more “object-like,” independent of sound category or task demands. Moreover, these STG regions also showed parametric sensitivity to spectral structure variations (SSVs) of the action sounds—a quantitative measure of change in entropy of the acoustic signals over time—and the right STG additionally showed parametric sensitivity to measures of mean entropy and harmonic content of the environmental sounds. Analogous to the visual system, intermediate stages of the auditory system appear to process or extract a number of quantifiable low-order signal attributes that are characteristic of action events perceived as being object-like, representing stages that may begin to dissociate different perceptual dimensions and categories of every-day, real-world action sounds. PMID:22582038

Ionospheric gravity wave measurements with the USU dynasonde

NASA Technical Reports Server (NTRS)

Berkey, Frank T.; Deng, Jun Yuan

1992-01-01

A method for the measurement of ionospheric Gravity Wave (GW) using the USU Dynasonde is outlined. This method consists of a series of individual procedures, which includes functions for data acquisition, adaptive scaling, polarization discrimination, interpolation and extrapolation, digital filtering, windowing, spectrum analysis, GW detection, and graphics display. Concepts of system theory are applied to treat the ionosphere as a system. An adaptive ionogram scaling method was developed for automatically extracting ionogram echo traces from noisy raw sounding data. The method uses the well known Least Mean Square (LMS) algorithm to form a stochastic optimal estimate of the echo trace which is then used to control a moving window. The window tracks the echo trace, simultaneously eliminating the noise and interference. Experimental results show that the proposed method functions as designed. Case studies which extract GW from ionosonde measurements were carried out using the techniques described. Geophysically significant events were detected and the resultant processed results are illustrated graphically. This method was also developed for real time implementation in mind.

Situational Awareness from a Low-Cost Camera System

NASA Technical Reports Server (NTRS)

Freudinger, Lawrence C.; Ward, David; Lesage, John

2010-01-01

A method gathers scene information from a low-cost camera system. Existing surveillance systems using sufficient cameras for continuous coverage of a large field necessarily generate enormous amounts of raw data. Digitizing and channeling that data to a central computer and processing it in real time is difficult when using low-cost, commercially available components. A newly developed system is located on a combined power and data wire to form a string-of-lights camera system. Each camera is accessible through this network interface using standard TCP/IP networking protocols. The cameras more closely resemble cell-phone cameras than traditional security camera systems. Processing capabilities are built directly onto the camera backplane, which helps maintain a low cost. The low power requirements of each camera allow the creation of a single imaging system comprising over 100 cameras. Each camera has built-in processing capabilities to detect events and cooperatively share this information with neighboring cameras. The location of the event is reported to the host computer in Cartesian coordinates computed from data correlation across multiple cameras. In this way, events in the field of view can present low-bandwidth information to the host rather than high-bandwidth bitmap data constantly being generated by the cameras. This approach offers greater flexibility than conventional systems, without compromising performance through using many small, low-cost cameras with overlapping fields of view. This means significant increased viewing without ignoring surveillance areas, which can occur when pan, tilt, and zoom cameras look away. Additionally, due to the sharing of a single cable for power and data, the installation costs are lower. The technology is targeted toward 3D scene extraction and automatic target tracking for military and commercial applications. Security systems and environmental/ vehicular monitoring systems are also potential applications.

Analysis of mechanical system of extreme rainfall events using backward tracking on information from the atmosphere circulation pattern for the 2000-2015 precipitation record in South Korea

NASA Astrophysics Data System (ADS)

So, B. J.; Kwon, H. H.

2016-12-01

A natural disaster for flood and drought have occurred in different parts of the world, and the disasters caused by significant extreme hydrological event in past years. Several studies examining stochastic analysis based nonstationary analysis reported for forecasting and outlook for extreme hydrological events, but there is the procedure to select predictor variables. In this study, we analyzed mechanical system of extreme rainfall events using backward tracking to determine the predictors of nonstationary considering the atmosphere circulation pattern. First, observed rainfall data of KMA (Korea Meteorological Administration) and ECMWF ERA-Interm data were constructed during the 2000-2015 period. Then, the 7day backward tracking were performed to establish the path of air mass using the LAGRANTO Tool considering the observed rainfall stations located in S. Korea as a starting point, The tracking information for rainfall event were clustered and then, we extracts the main influence factor based on the categorized tracking path considering to information of rainfall magnitude (e.g,, mega-sized, medium-sized). Finally, the nonstationary predictors are determined through a combination of factors affecting the nonstationary rainfall simulation techniques. The predictors based on a mechanical structure is expected to be able to respond to external factors such as climate change. In addition, this method can be used to determine the prediction factor in different geographical areas by different position.

Clustering and classification of infrasonic events at Mount Etna using pattern recognition techniques

NASA Astrophysics Data System (ADS)

Cannata, A.; Montalto, P.; Aliotta, M.; Cassisi, C.; Pulvirenti, A.; Privitera, E.; Patanè, D.

2011-04-01

Active volcanoes generate sonic and infrasonic signals, whose investigation provides useful information for both monitoring purposes and the study of the dynamics of explosive phenomena. At Mt. Etna volcano (Italy), a pattern recognition system based on infrasonic waveform features has been developed. First, by a parametric power spectrum method, the features describing and characterizing the infrasound events were extracted: peak frequency and quality factor. Then, together with the peak-to-peak amplitude, these features constituted a 3-D ‘feature space’; by Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN) three clusters were recognized inside it. After the clustering process, by using a common location method (semblance method) and additional volcanological information concerning the intensity of the explosive activity, we were able to associate each cluster to a particular source vent and/or a kind of volcanic activity. Finally, for automatic event location, clusters were used to train a model based on Support Vector Machine, calculating optimal hyperplanes able to maximize the margins of separation among the clusters. After the training phase this system automatically allows recognizing the active vent with no location algorithm and by using only a single station.

A new approach for bioassays based on frequency- and time-domain measurements of magnetic nanoparticles.

PubMed

Oisjöen, Fredrik; Schneiderman, Justin F; Astalan, Andrea Prieto; Kalabukhov, Alexey; Johansson, Christer; Winkler, Dag

2010-01-15

We demonstrate a one-step wash-free bioassay measurement system capable of tracking biochemical binding events. Our approach combines the high resolution of frequency- and high speed of time-domain measurements in a single device in combination with a fast one-step bioassay. The one-step nature of our magnetic nanoparticle (MNP) based assay reduces the time between sample extraction and quantitative results while mitigating the risks of contamination related to washing steps. Our method also enables tracking of binding events, providing the possibility of, for example, investigation of how chemical/biological environments affect the rate of a binding process or study of the action of certain drugs. We detect specific biological binding events occurring on the surfaces of fluid-suspended MNPs that modify their magnetic relaxation behavior. Herein, we extrapolate a modest sensitivity to analyte of 100 ng/ml with the present setup using our rapid one-step bioassay. More importantly, we determine the size-distributions of the MNP systems with theoretical fits to our data obtained from the two complementary measurement modalities and demonstrate quantitative agreement between them. Copyright 2009 Elsevier B.V. All rights reserved.

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.

A Re-Os Study of Depleted Trench Peridotites from Northern Mariana

NASA Astrophysics Data System (ADS)

Ghosh, T.; Snow, J. E.; Heri, A. R.; Brandon, A. D.; Ishizuka, O.

2017-12-01

Trench peridotites provide information about the influence of subduction initiation on the extent of mantle wedge melting. They preserve melting records throughout subduction history, and as a result, likely experience multiple melt extraction events leading to successive depletion of melt/fluid mobile major and trace elements. To track melting histories of trench peridotites, Re-Os and PGEs can be used as reliable tracers to constrain early melt extraction or re-fertilization events. The Izu-Bonin-Mariana arc, being the largest intra-oceanic subduction system, provides an excellent area to study the formation of supra-subduction zone mantle and crust. Residual peridotite (harzburgite and dunite) samples were collected by dredging from the landward slope of the northern Mariana Trench. The samples are serpentinized to various extents (typical of abyssal peridotites), leaving behind relict grains of spinel, enstatite and olivine embedded within a serpentine matrix along with occasional interstitial diopside. Major element analyses of primary minerals reveal a wide range of variations in Cr# of spinels from 0.31-0.85 indicating 16-20% of melt fraction with dunites apparently experiencing the highest amount of partial melting. For Re-Os and PGE geochemistry, samples with high amounts of spinel (>4 vol %) and variable Cr# were chosen. Initial results show that bulk rock 187Os/188Os ratios range from 0.1113 to 0.1272. All of the samples are sub-chondritic, but in some cases, they are more radiogenic than average abyssal peridotites. Os abundances vary from 1-9 ppb. Sub-chondritic values can be attributed to the samples having evolved from a Re-depleted mantle source indicating a previous melt-extraction event. The cpx-harzburgites, having lower Cr# ( 0.4) are more radiogenic than ultra depleted dunites (Cr# 0.8), which might indicate preferential removal of Os during an apparent higher degree of partial melting experienced by dunites. The higher 187Os/188Os ratios of cpx-harzburgites possibly imply a late stage melt-rock interaction event, which had refertilized the depleted samples in radiogenic Os. Since there are only trace amounts of sediments in the accretionary prism of N. Mariana, Os ratios of these trench peridotites are not influenced by Os from sediments.

PASBio: predicate-argument structures for event extraction in molecular biology

PubMed Central

Wattarujeekrit, Tuangthong; Shah, Parantu K; Collier, Nigel

2004-01-01

Background The exploitation of information extraction (IE), a technology aiming to provide instances of structured representations from free-form text, has been rapidly growing within the molecular biology (MB) research community to keep track of the latest results reported in literature. IE systems have traditionally used shallow syntactic patterns for matching facts in sentences but such approaches appear inadequate to achieve high accuracy in MB event extraction due to complex sentence structure. A consensus in the IE community is emerging on the necessity for exploiting deeper knowledge structures such as through the relations between a verb and its arguments shown by predicate-argument structure (PAS). PAS is of interest as structures typically correspond to events of interest and their participating entities. For this to be realized within IE a key knowledge component is the definition of PAS frames. PAS frames for non-technical domains such as newswire are already being constructed in several projects such as PropBank, VerbNet, and FrameNet. Knowledge from PAS should enable more accurate applications in several areas where sentence understanding is required like machine translation and text summarization. In this article, we explore the need to adapt PAS for the MB domain and specify PAS frames to support IE, as well as outlining the major issues that require consideration in their construction. Results We introduce PASBio by extending a model based on PropBank to the MB domain. The hypothesis we explore is that PAS holds the key for understanding relationships describing the roles of genes and gene products in mediating their biological functions. We chose predicates describing gene expression, molecular interactions and signal transduction events with the aim of covering a number of research areas in MB. Analysis was performed on sentences containing a set of verbal predicates from MEDLINE and full text journals. Results confirm the necessity to analyze PAS specifically for MB domain. Conclusions At present PASBio contains the analyzed PAS of over 30 verbs, publicly available on the Internet for use in advanced applications. In the future we aim to expand the knowledge base to cover more verbs and the nominal form of each predicate. PMID:15494078

How Safe Are Common Analgesics for the Treatment of Acute Pain for Children? A Systematic Review.

PubMed

Hartling, Lisa; Ali, Samina; Dryden, Donna M; Chordiya, Pritam; Johnson, David W; Plint, Amy C; Stang, Antonia; McGrath, Patrick J; Drendel, Amy L

2016-01-01

Background . Fear of adverse events and occurrence of side effects are commonly cited by families and physicians as obstructive to appropriate use of pain medication in children. We examined evidence comparing the safety profiles of three groups of oral medications, acetaminophen, nonsteroidal anti-inflammatory drugs, and opioids, to manage acute nonsurgical pain in children (<18 years) treated in ambulatory settings. Methods . A comprehensive search was performed to July 2015, including review of national data registries. Two reviewers screened articles for inclusion, assessed methodological quality, and extracted data. Risks (incidence rates) were pooled using a random effects model. Results . Forty-four studies were included; 23 reported on adverse events. Based on limited current evidence, acetaminophen, ibuprofen, and opioids have similar nausea and vomiting profiles. Opioids have the greatest risk of central nervous system adverse events. Dual therapy with a nonopioid/opioid combination resulted in a lower risk of adverse events than opioids alone. Conclusions . Ibuprofen and acetaminophen have similar reported adverse effects and notably less adverse events than opioids. Dual therapy with a nonopioid/opioid combination confers a protective effect for adverse events over opioids alone. This research highlights challenges in assessing medication safety, including lack of more detailed information in registry data, and inconsistent reporting in trials.

Integration of launch/impact discrimination algorithm with the UTAMS platform

NASA Astrophysics Data System (ADS)

Desai, Sachi; Morcos, Amir; Tenney, Stephen; Mays, Brian

2008-04-01

An acoustic array, integrated with an algorithm to discriminate potential Launch (LA) or Impact (IM) events, was augmented by employing the Launch Impact Discrimination (LID) algorithm for mortar events. We develop an added situational awareness capability to determine whether the localized event is a mortar launch or mortar impact at safe standoff distances. The algorithm utilizes a discrete wavelet transform to exploit higher harmonic components of various sub bands of the acoustic signature. Additional features are extracted via the frequency domain exploiting harmonic components generated by the nature of event, i.e. supersonic shrapnel components at impact. The further extrapolations of these features are employed with a neural network to provide a high level of confidence for discrimination and classification. The ability to discriminate between these events is of great interest on the battlefield. Providing more information and developing a common picture of situational awareness. Algorithms exploit the acoustic sensor array to provide detection and identification of IM/LA events at extended ranges. The integration of this algorithm with the acoustic sensor array for mortar detection provides an early warning detection system giving greater battlefield information for field commanders. This paper will describe the integration of the algorithm with a candidate sensor and resulting field tests.

Space station integrated wall damage and penetration damage control. Task 5: Space debris measurement, mapping and characterization system

NASA Technical Reports Server (NTRS)

Lempriere, B. M.

1987-01-01

The procedures and results of a study of a conceptual system for measuring the debris environment on the space station is discussed. The study was conducted in two phases: the first consisted of experiments aimed at evaluating location of impact through panel response data collected from acoustic emission sensors; the second analyzed the available statistical description of the environment to determine the probability of the measurement system producing useful data, and analyzed the results of the previous tests to evaluate the accuracy of location and the feasibility of extracting impactor characteristics from the panel response. The conclusions were that for one panel the system would not be exposed to any event, but that the entire Logistics Module would provide a modest amount of data. The use of sensors with higher sensitivity than those used in the tests could be advantageous. The impact location could be found with sufficient accuracy from panel response data. The waveforms of the response were shown to contain information on the impact characteristics, but the data set did not span a sufficient range of the variables necessary to evaluate the feasibility of extracting the information.

A Content-Adaptive Analysis and Representation Framework for Audio Event Discovery from "Unscripted" Multimedia

NASA Astrophysics Data System (ADS)

Radhakrishnan, Regunathan; Divakaran, Ajay; Xiong, Ziyou; Otsuka, Isao

2006-12-01

We propose a content-adaptive analysis and representation framework to discover events using audio features from "unscripted" multimedia such as sports and surveillance for summarization. The proposed analysis framework performs an inlier/outlier-based temporal segmentation of the content. It is motivated by the observation that "interesting" events in unscripted multimedia occur sparsely in a background of usual or "uninteresting" events. We treat the sequence of low/mid-level features extracted from the audio as a time series and identify subsequences that are outliers. The outlier detection is based on eigenvector analysis of the affinity matrix constructed from statistical models estimated from the subsequences of the time series. We define the confidence measure on each of the detected outliers as the probability that it is an outlier. Then, we establish a relationship between the parameters of the proposed framework and the confidence measure. Furthermore, we use the confidence measure to rank the detected outliers in terms of their departures from the background process. Our experimental results with sequences of low- and mid-level audio features extracted from sports video show that "highlight" events can be extracted effectively as outliers from a background process using the proposed framework. We proceed to show the effectiveness of the proposed framework in bringing out suspicious events from surveillance videos without any a priori knowledge. We show that such temporal segmentation into background and outliers, along with the ranking based on the departure from the background, can be used to generate content summaries of any desired length. Finally, we also show that the proposed framework can be used to systematically select "key audio classes" that are indicative of events of interest in the chosen domain.

Testing the event witnessing status of micro-bloggers from evidence in their micro-blogs

PubMed Central

2017-01-01

This paper demonstrates a framework of processes for identifying potential witnesses of events from evidence they post to social media. The research defines original evidence models for micro-blog content sources, the relative uncertainty of different evidence types, and models for testing evidence by combination. Methods to filter and extract evidence using automated and semi-automated means are demonstrated using a Twitter case study event. Further, an implementation to test extracted evidence using Dempster Shafer Theory of Evidence are presented. The results indicate that the inclusion of evidence from micro-blog text and linked image content can increase the number of micro-bloggers identified at events, in comparison to the number of micro-bloggers identified from geotags alone. Additionally, the number of micro-bloggers that can be tested for evidence corroboration or conflict, is increased by incorporating evidence identified in their posting history. PMID:29232395

The use of analytical sedimentation velocity to extract thermodynamic linkage.

PubMed

Cole, James L; Correia, John J; Stafford, Walter F

2011-11-01

For 25 years, the Gibbs Conference on Biothermodynamics has focused on the use of thermodynamics to extract information about the mechanism and regulation of biological processes. This includes the determination of equilibrium constants for macromolecular interactions by high precision physical measurements. These approaches further reveal thermodynamic linkages to ligand binding events. Analytical ultracentrifugation has been a fundamental technique in the determination of macromolecular reaction stoichiometry and energetics for 85 years. This approach is highly amenable to the extraction of thermodynamic couplings to small molecule binding in the overall reaction pathway. In the 1980s this approach was extended to the use of sedimentation velocity techniques, primarily by the analysis of tubulin-drug interactions by Na and Timasheff. This transport method necessarily incorporates the complexity of both hydrodynamic and thermodynamic nonideality. The advent of modern computational methods in the last 20 years has subsequently made the analysis of sedimentation velocity data for interacting systems more robust and rigorous. Here we review three examples where sedimentation velocity has been useful at extracting thermodynamic information about reaction stoichiometry and energetics. Approaches to extract linkage to small molecule binding and the influence of hydrodynamic nonideality are emphasized. These methods are shown to also apply to the collection of fluorescence data with the new Aviv FDS. Copyright © 2011 Elsevier B.V. All rights reserved.

The use of analytical sedimentation velocity to extract thermodynamic linkage

PubMed Central

Cole, James L.; Correia, John J.; Stafford, Walter F.

2011-01-01

For 25 years, the Gibbs Conference on Biothermodynamics has focused on the use of thermodynamics to extract information about the mechanism and regulation of biological processes. This includes the determination of equilibrium constants for macromolecular interactions by high precision physical measurements. These approaches further reveal thermodynamic linkages to ligand binding events. Analytical ultracentrifugation has been a fundamental technique in the determination of macromolecular reaction stoichiometry and energetics for 85 years. This approach is highly amenable to the extraction of thermodynamic couplings to small molecule binding in the overall reaction pathway. In the 1980’s this approach was extended to the use of sedimentation velocity techniques, primarily by the analysis of tubulin-drug interactions by Na and Timasheff. This transport method necessarily incorporates the complexity of both hydrodynamic and thermodynamic nonideality. The advent of modern computational methods in the last 20 years has subsequently made the analysis of sedimentation velocity data for interacting systems more robust and rigorous. Here we review three examples where sedimentation velocity has been useful at extracting thermodynamic information about reaction stoichiometry and energetics. Approaches to extract linkage to small molecule binding and the influence of hydrodynamic nonideality are emphasized. These methods are shown to also apply to the collection of fluorescence data with the new Aviv FDS. PMID:21703752

Is Andrographis paniculata extract and andrographolide anaphylactic?

PubMed

Richard, Edwin Jothie; Murugan, Sasikumar; Bethapudi, Bharathi; Illuri, Ramanaiah; Mundkinajeddu, Deepak; Chinampudur Velusami, Chandrasekaran

2017-01-01

Andrographis paniculata, "King of bitters" is a popularly known medicinal plant extensively used in many parts of the world for treatment of various diseases. Since recent past, anaphylactic/allergic type adverse events were reported upon A. paniculata usage, the study aimed to evaluate the anaphylactic and anaphylactoid potential of A. paniculata extract and andrographolide (a major phytoactive of A. paniculata ). The anaphylactic potential was evaluated using active systemic anaphylaxis (ASA) assay in guinea pigs. Further, the release of allergic mediators was measured in immunoglobulin E (IgE) sensitized and non-IgE sensitized Rat Basophilic Leukemia (RBL-2H3) cell lines in-vitro . A. paniculata extract or andrographolide sensitized guinea pigs following the challenge antigen administration orally and intravenously did not demonstrate any clinical signs of anaphylaxis. IgE sensitized and non- IgE sensitized RBL-2H3 cells treated with A. paniculata extract did not induce release of allergic mediators. Whereas IgE sensitized and non- IgE sensitized RBL-2H3 cells treated with andrographolide demonstrated mild to moderate release of allergic mediators. A. paniculata extract has no anaphylactic and anaphylactoid potential in in-vivo and in-vitro studies. Whereas, andrographolide effects on allergic mediators in in-vitro studies needs to be scrutinized if they are of biologically important.

Effect of database profile variation on drug safety assessment: an analysis of spontaneous adverse event reports of Japanese cases

PubMed Central

Nomura, Kaori; Takahashi, Kunihiko; Hinomura, Yasushi; Kawaguchi, Genta; Matsushita, Yasuyuki; Marui, Hiroko; Anzai, Tatsuhiko; Hashiguchi, Masayuki; Mochizuki, Mayumi

2015-01-01

Background The use of a statistical approach to analyze cumulative adverse event (AE) reports has been encouraged by regulatory authorities. However, data variations affect statistical analyses (eg, signal detection). Further, differences in regulations, social issues, and health care systems can cause variations in AE data. The present study examined similarities and differences between two publicly available databases, ie, the Japanese Adverse Drug Event Report (JADER) database and the US Food and Drug Administration Adverse Event Reporting System (FAERS), and how they affect signal detection. Methods Two AE data sources from 2010 were examined, ie, JADER cases (JP) and Japanese cases extracted from the FAERS (FAERS-JP). Three methods for signals of disproportionate reporting, ie, the reporting odds ratio, Bayesian confidence propagation neural network, and Gamma Poisson Shrinker (GPS), were used on drug-event combinations for three substances frequently recorded in both systems. Results The two databases showed similar elements of AE reports, but no option was provided for a shareable case identifier. The average number of AEs per case was 1.6±1.3 (maximum 37) in the JP and 3.3±3.5 (maximum 62) in the FAERS-JP. Between 5% and 57% of all AEs were signaled by three quantitative methods for etanercept, infliximab, and paroxetine. Signals identified by GPS for the JP and FAERS-JP, as referenced by Japanese labeling, showed higher positive sensitivity than was expected. Conclusion The FAERS-JP was different from the JADER. Signals derived from both datasets identified different results, but shared certain signals. Discrepancies in type of AEs, drugs reported, and average number of AEs per case were potential contributing factors. This study will help those concerned with pharmacovigilance better understand the use and pitfalls of using spontaneous AE data. PMID:26109846

Adverse drug events in hospital: pilot study with trigger tool

PubMed Central

Rozenfeld, Suely; Giordani, Fabiola; Coelho, Sonia

2013-01-01

OBJECTIVE To estimate the frequency of and to characterize the adverse drug events at a terciary care hospital. METHODS A retrospective review was carried out of 128 medical records from a hospital in Rio de Janeiro in 2007, representing 2,092 patients. The instrument used was a list of triggers, such as antidotes, abnormal laboratory analysis results and sudden suspension of treatment, among others. A simple random sample of patients aged 15 and over was extracted. Oncologic and obstetric patients were excluded as were those hospitalized for less than 48 hours or in the emergency room. Social and demographic characteristics and those of the disease of patients who underwent adverse events were compared with those of patients who did not in order to test for differences between the groups. RESULTS Around 70.0% of the medical records assessed showed at least one trigger. Adverse drug events triggers had an overall positive predictive value of 14.4%. The incidence of adverse drug events was 26.6 per 100 patients and 15.6% patients suffered one or more event. The median length of stay for patients suffering an adverse drug event was 35.2 days as against 10.7 days for those who did not (p < 0.01). The pharmacological classes most commonly associated with an adverse drug event were related to the cardiovascular system, nervous system and alimentary tract and metabolism. The most common active substances associated with an adverse drug event were tramadol, dypirone, glibenclamide and furosemide. Over 80.0% of events provoked or contributed to temporary harm to the patient and required intervention and 6.0% may have contributed to the death of the patient. It was estimated that in the hospital, 131 events involving drowsiness or fainting 33 involving falls, and 33 episodes of hemorrhage related to adverse drug effects occur annually. CONCLUSIONS Almost one-sixth of in-patients (16,0%) suffered an adverse drug event. The instrument used may prove useful as a technique for monitoring and evaluating patient care results. Psycothropic therapy should be critically appraised given the frequency of associated events, such as excessive sedation, lethargy, and hypotension. PMID:24626548

Heatwave Early Warning Systems and Adaptation Advice to Reduce Human Health Consequences of Heatwaves

PubMed Central

Lowe, Dianne; Ebi, Kristie L.; Forsberg, Bertil

2011-01-01

Introduction: With climate change, there has been an increase in the frequency, intensity and duration of heatwave events. In response to the devastating mortality and morbidity of recent heatwave events, many countries have introduced heatwave early warning systems (HEWS). HEWS are designed to reduce the avoidable human health consequences of heatwaves through timely notification of prevention measures to vulnerable populations. Objective: To identify the key characteristics of HEWS in European countries to help inform modification of current, and development of, new systems and plans. Methods: We searched the internet to identify HEWS policy or government documents for 33 European countries and requested information from relevant organizations. We translated the HEWS documents and extracted details on the trigger indicators, thresholds for action, notification strategies, message intermediaries, communication and dissemination strategies, prevention strategies recommended and specified target audiences. Findings and Conclusions: Twelve European countries have HEWS. Although there are many similarities among the HEWS, there also are differences in key characteristics that could inform improvements in heatwave early warning plans. PMID:22408593

Single-trial event-related potential extraction through one-unit ICA-with-reference

NASA Astrophysics Data System (ADS)

Lih Lee, Wee; Tan, Tele; Falkmer, Torbjörn; Leung, Yee Hong

2016-12-01

Objective. In recent years, ICA has been one of the more popular methods for extracting event-related potential (ERP) at the single-trial level. It is a blind source separation technique that allows the extraction of an ERP without making strong assumptions on the temporal and spatial characteristics of an ERP. However, the problem with traditional ICA is that the extraction is not direct and is time-consuming due to the need for source selection processing. In this paper, the application of an one-unit ICA-with-Reference (ICA-R), a constrained ICA method, is proposed. Approach. In cases where the time-region of the desired ERP is known a priori, this time information is utilized to generate a reference signal, which is then used for guiding the one-unit ICA-R to extract the source signal of the desired ERP directly. Main results. Our results showed that, as compared to traditional ICA, ICA-R is a more effective method for analysing ERP because it avoids manual source selection and it requires less computation thus resulting in faster ERP extraction. Significance. In addition to that, since the method is automated, it reduces the risks of any subjective bias in the ERP analysis. It is also a potential tool for extracting the ERP in online application.

Single-trial event-related potential extraction through one-unit ICA-with-reference.

PubMed

Lee, Wee Lih; Tan, Tele; Falkmer, Torbjörn; Leung, Yee Hong

2016-12-01

In recent years, ICA has been one of the more popular methods for extracting event-related potential (ERP) at the single-trial level. It is a blind source separation technique that allows the extraction of an ERP without making strong assumptions on the temporal and spatial characteristics of an ERP. However, the problem with traditional ICA is that the extraction is not direct and is time-consuming due to the need for source selection processing. In this paper, the application of an one-unit ICA-with-Reference (ICA-R), a constrained ICA method, is proposed. In cases where the time-region of the desired ERP is known a priori, this time information is utilized to generate a reference signal, which is then used for guiding the one-unit ICA-R to extract the source signal of the desired ERP directly. Our results showed that, as compared to traditional ICA, ICA-R is a more effective method for analysing ERP because it avoids manual source selection and it requires less computation thus resulting in faster ERP extraction. In addition to that, since the method is automated, it reduces the risks of any subjective bias in the ERP analysis. It is also a potential tool for extracting the ERP in online application.

Random-Effects Meta-Analysis of Time-to-Event Data Using the Expectation-Maximisation Algorithm and Shrinkage Estimators

ERIC Educational Resources Information Center

Simmonds, Mark C.; Higgins, Julian P. T.; Stewart, Lesley A.

2013-01-01

Meta-analysis of time-to-event data has proved difficult in the past because consistent summary statistics often cannot be extracted from published results. The use of individual patient data allows for the re-analysis of each study in a consistent fashion and thus makes meta-analysis of time-to-event data feasible. Time-to-event data can be…

An ensemble method for extracting adverse drug events from social media.

PubMed

Liu, Jing; Zhao, Songzheng; Zhang, Xiaodi

2016-06-01

Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them correctly and in a timely manner. With the development of Web 2.0, social media has become a large data source for information on ADEs. The objective of this study is to develop a relation extraction system that uses natural language processing techniques to effectively distinguish between ADEs and non-ADEs in informal text on social media. We develop a feature-based approach that utilizes various lexical, syntactic, and semantic features. Information-gain-based feature selection is performed to address high-dimensional features. Then, we evaluate the effectiveness of four well-known kernel-based approaches (i.e., subset tree kernel, tree kernel, shortest dependency path kernel, and all-paths graph kernel) and several ensembles that are generated by adopting different combination methods (i.e., majority voting, weighted averaging, and stacked generalization). All of the approaches are tested using three data sets: two health-related discussion forums and one general social networking site (i.e., Twitter). When investigating the contribution of each feature subset, the feature-based approach attains the best area under the receiver operating characteristics curve (AUC) values, which are 78.6%, 72.2%, and 79.2% on the three data sets. When individual methods are used, we attain the best AUC values of 82.1%, 73.2%, and 77.0% using the subset tree kernel, shortest dependency path kernel, and feature-based approach on the three data sets, respectively. When using classifier ensembles, we achieve the best AUC values of 84.5%, 77.3%, and 84.5% on the three data sets, outperforming the baselines. Our experimental results indicate that ADE extraction from social media can benefit from feature selection. With respect to the effectiveness of different feature subsets, lexical features and semantic features can enhance the ADE extraction capability. Kernel-based approaches, which can stay away from the feature sparsity issue, are qualified to address the ADE extraction problem. Combining different individual classifiers using suitable combination methods can further enhance the ADE extraction effectiveness. Copyright © 2016 Elsevier B.V. All rights reserved.

Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting.

PubMed

Vock, David M; Wolfson, Julian; Bandyopadhyay, Sunayan; Adomavicius, Gediminas; Johnson, Paul E; Vazquez-Benitez, Gabriela; O'Connor, Patrick J

2016-06-01

Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing patient care. Electronic health data (EHD) are appealing sources of training data because they provide access to large amounts of rich individual-level data from present-day patient populations. However, because EHD are derived by extracting information from administrative and clinical databases, some fraction of subjects will not be under observation for the entire time frame over which one wants to make predictions; this loss to follow-up is often due to disenrollment from the health system. For subjects without complete follow-up, whether or not they experienced the adverse event is unknown, and in statistical terms the event time is said to be right-censored. Most machine learning approaches to the problem have been relatively ad hoc; for example, common approaches for handling observations in which the event status is unknown include (1) discarding those observations, (2) treating them as non-events, (3) splitting those observations into two observations: one where the event occurs and one where the event does not. In this paper, we present a general-purpose approach to account for right-censored outcomes using inverse probability of censoring weighting (IPCW). We illustrate how IPCW can easily be incorporated into a number of existing machine learning algorithms used to mine big health care data including Bayesian networks, k-nearest neighbors, decision trees, and generalized additive models. We then show that our approach leads to better calibrated predictions than the three ad hoc approaches when applied to predicting the 5-year risk of experiencing a cardiovascular adverse event, using EHD from a large U.S. Midwestern healthcare system. Copyright © 2016 Elsevier Inc. All rights reserved.

Use of Narrative Nursing Records for Nursing Research

PubMed Central

Park, Hyeoun-Ae; Cho, InSook; Ahn, Hee-Jung

2012-01-01

To explore the usefulness of narrative nursing records documented using a standardized terminology-based electronic nursing records system, we conducted three different studies on (1) the gaps between the required nursing care time and the actual nursing care time, (2) the practice variations in pressure ulcer care, and (3) the surveillance of adverse drug events. The narrative nursing notes, documented at the point of care using standardized nursing statements, were extracted from the clinical data repository at a teaching hospital in Korea and analyzed. Our findings were: the pediatric and geriatric units showed relatively high staffing needs; overall incidence rate of pressure ulcer among the intensive-care patients was 15.0% and the nursing interventions provided for pressure-ulcer care varied depending on nursing units; and at least one adverse drug event was noted in 53.0% of the cancer patients who were treated with cisplatin. A standardized nursing terminology-based electronic nursing record system allowed us to explore answers to different various research questions. PMID:24199111

OGLE-2016-BLG-0168 Binary Microlensing Event: Prediction and Confirmation of the Microlens Parallax Effect from Space-based Observations

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

Shin, I.-G.; Yee, J. C.; Jung, Y. K.

The microlens parallax is a crucial observable for conclusively identifying the nature of lens systems in microlensing events containing or composed of faint (even dark) astronomical objects such as planets, neutron stars, brown dwarfs, and black holes. With the commencement of a new era of microlensing in collaboration with space-based observations, the microlens parallax can be routinely measured. In addition, space-based observations can provide opportunities to verify the microlens parallax measured from ground-only observations and to find a unique solution to the lensing light-curve analysis. Furthermore, since most space-based observations cannot cover the full light curves of lensing events, itmore » is also necessary to verify the reliability of the information extracted from fragmentary space-based light curves. We conduct a test based on the microlensing event OGLE-2016-BLG-0168, created by a binary lens system consisting of almost equal mass M-dwarf stars, to demonstrate that it is possible to verify the microlens parallax and to resolve degeneracies using the space-based light curve even though the observations are fragmentary. Since space-based observatories will frequently produce fragmentary light curves due to their short observing windows, the methodology of this test will be useful for next-generation microlensing experiments that combine space-based and ground-based collaboration.« less

Visualization of Traffic Accidents

NASA Technical Reports Server (NTRS)

Wang, Jie; Shen, Yuzhong; Khattak, Asad

2010-01-01

Traffic accidents have tremendous impact on society. Annually approximately 6.4 million vehicle accidents are reported by police in the US and nearly half of them result in catastrophic injuries. Visualizations of traffic accidents using geographic information systems (GIS) greatly facilitate handling and analysis of traffic accidents in many aspects. Environmental Systems Research Institute (ESRI), Inc. is the world leader in GIS research and development. ArcGIS, a software package developed by ESRI, has the capabilities to display events associated with a road network, such as accident locations, and pavement quality. But when event locations related to a road network are processed, the existing algorithm used by ArcGIS does not utilize all the information related to the routes of the road network and produces erroneous visualization results of event locations. This software bug causes serious problems for applications in which accurate location information is critical for emergency responses, such as traffic accidents. This paper aims to address this problem and proposes an improved method that utilizes all relevant information of traffic accidents, namely, route number, direction, and mile post, and extracts correct event locations for accurate traffic accident visualization and analysis. The proposed method generates a new shape file for traffic accidents and displays them on top of the existing road network in ArcGIS. Visualization of traffic accidents along Hampton Roads Bridge Tunnel is included to demonstrate the effectiveness of the proposed method.

OGLE-2016-BLG-0168 Binary Microlensing Event: Prediction and Confirmation of the Microlens Parallax Effect from Space-based Observations

NASA Astrophysics Data System (ADS)

Shin, I.-G.; Udalski, A.; Yee, J. C.; Calchi Novati, S.; Han, C.; Skowron, J.; Mróz, P.; Soszyński, I.; Poleski, R.; Szymański, M. K.; Kozłowski, S.; Pietrukowicz, P.; Ulaczyk, K.; Pawlak, M.; OGLE Collaboration; Albrow, M. D.; Gould, A.; Chung, S.-J.; Hwang, K.-H.; Jung, Y. K.; Ryu, Y.-H.; Zhu, W.; Cha, S.-M.; Kim, D.-J.; Kim, H.-W.; Kim, S.-L.; Lee, C.-U.; Lee, Y.; Park, B.-G.; Pogge, R. W.; KMTNet Group; Beichman, C.; Bryden, G.; Carey, S.; Gaudi, B. S.; Henderson, C. B.; Shvartzvald, Y.; Spitzer Team

2017-11-01

The microlens parallax is a crucial observable for conclusively identifying the nature of lens systems in microlensing events containing or composed of faint (even dark) astronomical objects such as planets, neutron stars, brown dwarfs, and black holes. With the commencement of a new era of microlensing in collaboration with space-based observations, the microlens parallax can be routinely measured. In addition, space-based observations can provide opportunities to verify the microlens parallax measured from ground-only observations and to find a unique solution to the lensing light-curve analysis. Furthermore, since most space-based observations cannot cover the full light curves of lensing events, it is also necessary to verify the reliability of the information extracted from fragmentary space-based light curves. We conduct a test based on the microlensing event OGLE-2016-BLG-0168, created by a binary lens system consisting of almost equal mass M-dwarf stars, to demonstrate that it is possible to verify the microlens parallax and to resolve degeneracies using the space-based light curve even though the observations are fragmentary. Since space-based observatories will frequently produce fragmentary light curves due to their short observing windows, the methodology of this test will be useful for next-generation microlensing experiments that combine space-based and ground-based collaboration.

Cloud-based serviced-orientated data systems for ocean observational data - an example from the coral reef community

NASA Astrophysics Data System (ADS)

Bainbridge, S.

2012-04-01

The advent of new observing systems, such as sensor networks, have dramatically increased our ability to collect marine data; the issue now is not data drought but data deluge. The challenge now is to extract data representing events of interest from the background data, that is how to deliver information and potentially knowledge from an increasing large store of base observations. Given that each potential user will have differing definitions of 'interesting' and that this is often defined by other events and data, systems need to deliver information or knowledge in a form and context defined by the user. This paper reports on a series of coral reef sensor networks set up under the Coral Reef Environmental Observation Network (CREON). CREON is a community of interest group deploying coral reef sensor networks with the goal of increasing capacity in coral reef observation, especially into developing areas. Issues such as coral bleaching, terrestrial runoff, human impacts and climate change are impacting reefs with one assessment indicating a quarter of the worlds reefs being severely degraded with another quarter under immediate threat. Increasing our ability to collect scientifically valid observations is fundamental to understanding these systems and ultimately in preserving and sustaining them. A cloud based data management system was used to store the base sensor data from each agency involved using service based agents to push the data from individual field sensors to the cloud. The system supports a range of service based outputs such as on-line graphs, a smart-phone application and simple event detection. A more complex event detection system was written that takes input from the cloud services and outputs natural language 'tweets' to Twitter as events occur. It therefore becomes possible to distil the entire data set down to a series of Twitter entries that interested parties can subscribe to. The next step is to allow users to define their own events and to deliver results, in context, to their preferred medium. The paper contrasts what has been achieved within a small community with well defined issues with what it would take to build equivalent systems to hold a wide range of cross community observational data addressing a wider range of potential issues. The role of discoverability, quality control, uncertainly, conformity and metadata are investigated along with a brief discussion of existing and emerging standards in this area. The elements of such as system are described along with the role of modelling and scenario tools in delivering a higher level of outputs linking what may have already occurred (event detection) with what may potentially occur (scenarios). The development of service based cloud computing open data systems coupled with complex event detection systems delivering through social media and other channels linked into model and scenario systems represents one vision for delivering value from the increasing store of ocean observations, most of which lie unknown, unused and unloved.

Estimating the Effective System Dead Time Parameter for Correlated Neutron Counting

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

Croft, Stephen; Cleveland, Steve; Favalli, Andrea

We present that neutron time correlation analysis is one of the main technical nuclear safeguards techniques used to verify declarations of, or to independently assay, special nuclear materials. Quantitative information is generally extracted from the neutron-event pulse train, collected from moderated assemblies of 3He proportional counters, in the form of correlated count rates that are derived from event-triggered coincidence gates. These count rates, most commonly referred to as singles, doubles and triples rates etc., when extracted using shift-register autocorrelation logic, are related to the reduced factorial moments of the time correlated clusters of neutrons emerging from the measurement items. Correctingmore » these various rates for dead time losses has received considerable attention recently. The dead time losses for the higher moments in particular, and especially for large mass (high rate and highly multiplying) items, can be significant. Consequently, even in thoughtfully designed systems, accurate dead time treatments are needed if biased mass determinations are to be avoided. In support of this effort, in this paper we discuss a new approach to experimentally estimate the effective system dead time of neutron coincidence counting systems. It involves counting a random neutron source (e.g. AmLi is a good approximation to a source without correlated emission) and relating the second and higher moments of the neutron number distribution recorded in random triggered interrogation coincidence gates to the effective value of dead time parameter. We develop the theoretical basis of the method and apply it to the Oak Ridge Large Volume Active Well Coincidence Counter using sealed AmLi radionuclide neutron sources and standard multiplicity shift register electronics. The method is simple to apply compared to the predominant present approach which involves using a set of 252Cf sources of wide emission rate, it gives excellent precision in a conveniently short time, and it yields consistent results as a function of the order of the moment used to extract the dead time parameter. In addition, this latter observation is reassuring in that it suggests the assumptions underpinning the theoretical analysis are fit for practical application purposes. However, we found that the effective dead time parameter obtained is not constant, as might be expected for a parameter that in the dead time model is characteristic of the detector system, but rather, varies systematically with gate width.« less

Estimating the Effective System Dead Time Parameter for Correlated Neutron Counting

DOE PAGES

Croft, Stephen; Cleveland, Steve; Favalli, Andrea; ...

2017-04-29

We present that neutron time correlation analysis is one of the main technical nuclear safeguards techniques used to verify declarations of, or to independently assay, special nuclear materials. Quantitative information is generally extracted from the neutron-event pulse train, collected from moderated assemblies of 3He proportional counters, in the form of correlated count rates that are derived from event-triggered coincidence gates. These count rates, most commonly referred to as singles, doubles and triples rates etc., when extracted using shift-register autocorrelation logic, are related to the reduced factorial moments of the time correlated clusters of neutrons emerging from the measurement items. Correctingmore » these various rates for dead time losses has received considerable attention recently. The dead time losses for the higher moments in particular, and especially for large mass (high rate and highly multiplying) items, can be significant. Consequently, even in thoughtfully designed systems, accurate dead time treatments are needed if biased mass determinations are to be avoided. In support of this effort, in this paper we discuss a new approach to experimentally estimate the effective system dead time of neutron coincidence counting systems. It involves counting a random neutron source (e.g. AmLi is a good approximation to a source without correlated emission) and relating the second and higher moments of the neutron number distribution recorded in random triggered interrogation coincidence gates to the effective value of dead time parameter. We develop the theoretical basis of the method and apply it to the Oak Ridge Large Volume Active Well Coincidence Counter using sealed AmLi radionuclide neutron sources and standard multiplicity shift register electronics. The method is simple to apply compared to the predominant present approach which involves using a set of 252Cf sources of wide emission rate, it gives excellent precision in a conveniently short time, and it yields consistent results as a function of the order of the moment used to extract the dead time parameter. In addition, this latter observation is reassuring in that it suggests the assumptions underpinning the theoretical analysis are fit for practical application purposes. However, we found that the effective dead time parameter obtained is not constant, as might be expected for a parameter that in the dead time model is characteristic of the detector system, but rather, varies systematically with gate width.« less

Estimating the effective system dead time parameter for correlated neutron counting

NASA Astrophysics Data System (ADS)

Croft, Stephen; Cleveland, Steve; Favalli, Andrea; McElroy, Robert D.; Simone, Angela T.

2017-11-01

Neutron time correlation analysis is one of the main technical nuclear safeguards techniques used to verify declarations of, or to independently assay, special nuclear materials. Quantitative information is generally extracted from the neutron-event pulse train, collected from moderated assemblies of 3He proportional counters, in the form of correlated count rates that are derived from event-triggered coincidence gates. These count rates, most commonly referred to as singles, doubles and triples rates etc., when extracted using shift-register autocorrelation logic, are related to the reduced factorial moments of the time correlated clusters of neutrons emerging from the measurement items. Correcting these various rates for dead time losses has received considerable attention recently. The dead time losses for the higher moments in particular, and especially for large mass (high rate and highly multiplying) items, can be significant. Consequently, even in thoughtfully designed systems, accurate dead time treatments are needed if biased mass determinations are to be avoided. In support of this effort, in this paper we discuss a new approach to experimentally estimate the effective system dead time of neutron coincidence counting systems. It involves counting a random neutron source (e.g. AmLi is a good approximation to a source without correlated emission) and relating the second and higher moments of the neutron number distribution recorded in random triggered interrogation coincidence gates to the effective value of dead time parameter. We develop the theoretical basis of the method and apply it to the Oak Ridge Large Volume Active Well Coincidence Counter using sealed AmLi radionuclide neutron sources and standard multiplicity shift register electronics. The method is simple to apply compared to the predominant present approach which involves using a set of 252Cf sources of wide emission rate, it gives excellent precision in a conveniently short time, and it yields consistent results as a function of the order of the moment used to extract the dead time parameter. This latter observation is reassuring in that it suggests the assumptions underpinning the theoretical analysis are fit for practical application purposes. However, we found that the effective dead time parameter obtained is not constant, as might be expected for a parameter that in the dead time model is characteristic of the detector system, but rather, varies systematically with gate width.

Boosted object hardware trigger development and testing for the Phase I upgrade of the ATLAS Experiment

NASA Astrophysics Data System (ADS)

Stark, Giordon; Atlas Collaboration

2015-04-01

The Global Feature Extraction (gFEX) module is a Level 1 jet trigger system planned for installation in ATLAS during the Phase 1 upgrade in 2018. The gFEX selects large-radius jets for capturing Lorentz-boosted objects by means of wide-area jet algorithms refined by subjet information. The architecture of the gFEX permits event-by-event local pile-up suppression for these jets using the same subtraction techniques developed for offline analyses. The gFEX architecture is also suitable for other global event algorithms such as missing transverse energy (MET), centrality for heavy ion collisions, and ``jets without jets.'' The gFEX will use 4 processor FPGAs to perform calculations on the incoming data and a Hybrid APU-FPGA for slow control of the module. The gFEX is unique in both design and implementation and substantially enhance the selectivity of the L1 trigger and increases sensitivity to key physics channels.

An integrated weather and sea-state forecasting system for the Arabian Peninsula (WASSF)

NASA Astrophysics Data System (ADS)

Kallos, George; Galanis, George; Spyrou, Christos; Mitsakou, Christina; Solomos, Stavros; Bartsotas, Nikolaos; Kalogrei, Christina; Athanaselis, Ioannis; Sofianos, Sarantis; Vervatis, Vassios; Axaopoulos, Panagiotis; Papapostolou, Alexandros; Qahtani, Jumaan Al; Alaa, Elyas; Alexiou, Ioannis; Beard, Daniel

2013-04-01

Nowadays, large industrial conglomerates such as the Saudi ARAMCO, require a series of weather and sea state forecasting products that cannot be found in state meteorological offices or even commercial data providers. The two major objectives of the system is prevention and mitigation of environmental problems and of course early warning of local conditions associated with extreme weather events. The management and operations part is related to early warning of weather and sea-state events that affect operations of various facilities. The environmental part is related to air quality and especially the desert dust levels in the atmosphere. The components of the integrated system include: (i) a weather and desert dust prediction system with forecasting horizon of 5 days, (ii) a wave analysis and prediction component for Red Sea and Arabian Gulf, (iii) an ocean circulation and tidal analysis and prediction of both Red Sea and Arabian Gulf and (iv) an Aviation part specializing in the vertical structure of the atmosphere and extreme events that affect air transport and other operations. Specialized data sets required for on/offshore operations are provided ate regular basis. State of the art modeling components are integrated to a unique system that distributes the produced analysis and forecasts to each department. The weather and dust prediction system is SKIRON/Dust, the wave analysis and prediction system is based on WAM cycle 4 model from ECMWF, the ocean circulation model is MICOM while the tidal analysis and prediction is a development of the Ocean Physics and Modeling Group of University of Athens, incorporating the Tidal Model Driver. A nowcasting subsystem is included. An interactive system based on Google Maps gives the capability to extract and display the necessary information for any location of the Arabian Peninsula, the Red Sea and Arabian Gulf.

FPGA-based trigger system for the LUX dark matter experiment

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

Akerib, D. S.; Araújo, H. M.; Bai, X.

LUX is a two-phase (liquid/gas) xenon time projection chamber designed to detect nuclear recoils resulting from interactions with dark matter particles. Signals from the detector are processed with an FPGA-based digital trigger system that analyzes the incoming data in real-time, with just a few microsecond latency. The system enables first pass selection of events of interest based on their pulse shape characteristics and 3D localization of the interactions. It has been shown to be >99% efficient in triggering on S2 signals induced by only few extracted liquid electrons. It is continuously and reliably operating since its full underground deployment inmore » early 2013. This document is an overview of the systems capabilities, its inner workings, and its performance.« less

FPGA-based trigger system for the LUX dark matter experiment

DOE PAGES

Akerib, D. S.; Araújo, H. M.; Bai, X.; ...

2016-02-17

We present that LUX is a two-phase (liquid/gas) xenon time projection chamber designed to detect nuclear recoils resulting from interactions with dark matter particles. Signals from the detector are processed with an FPGA-based digital trigger system that analyzes the incoming data in real-time, with just a few microsecond latency. The system enables first pass selection of events of interest based on their pulse shape characteristics and 3D localization of the interactions. It has been shown to be > 99% efficient in triggering on S2 signals induced by only few extracted liquid electrons. It is continuously and reliably operating since itsmore » full underground deployment in early 2013. Finally, this document is an overview of the systems capabilities, its inner workings, and its performance.« less

FPGA-based trigger system for the LUX dark matter experiment

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

Akerib, D. S.; Araújo, H. M.; Bai, X.

We present that LUX is a two-phase (liquid/gas) xenon time projection chamber designed to detect nuclear recoils resulting from interactions with dark matter particles. Signals from the detector are processed with an FPGA-based digital trigger system that analyzes the incoming data in real-time, with just a few microsecond latency. The system enables first pass selection of events of interest based on their pulse shape characteristics and 3D localization of the interactions. It has been shown to be > 99% efficient in triggering on S2 signals induced by only few extracted liquid electrons. It is continuously and reliably operating since itsmore » full underground deployment in early 2013. Finally, this document is an overview of the systems capabilities, its inner workings, and its performance.« less

Channel disturbances and morpho-dynamics: linking hydraulics, topographic changes and human impacts in a highly dynamic wandering river at multiple temporal scales

NASA Astrophysics Data System (ADS)

Vericat, Damià; Llena, Manel; Muñoz, Efrén; Ramos, Ester; Béjar, María; Brasington, James; Gibbins, Chris; Batalla, Ramon J.; Tena, Álvaro; Martínez-Casasnovas, José A.; Wheaton, Joe

2015-04-01

Episodic erosion, transport and deposition of sediments produce changes in river's channel morphology. These changes, although are directly related to flow hydraulics and bed material availability, supply and transport, could also be highly influenced by structural and local human impacts. Dams cut the continuity of sediment transfer and alter flood magnitude and frequency. In-channel gravel mining, however, disturbs channel beds locally, with a direct influence in upstream and downstream reaches. In this paper we present some of the preliminary results obtained in the background of MorphSed (www.morphsed.es). Morphsed is analysing the morpho-sedimentary dynamics of a mountain fluvial system located in the foothills of the Pyrenees, Iberian Peninsula. The study system is suffering major local alterations due to gravel mining. Changes on bed topography along a 12-km river reach have been analysed at two temporal scales: (i) decadal or historical and (ii) flood-based or contemporary. The study reach has suffered natural and human channel disturbances (i.e. major flood events, and gravel extractions and channel embankments, respectively). Preliminary results show how gravel mining occurred after the large flood event registered in October 1982 created a sedimentary disequilibrium in the reach. Additionally, the channel was heavily constrained associated to channel narrowing by embankments. The river has reached a new dynamic equilibrium by means of bed coarsening and channel incision, and changing from a braided to a wandering pattern. Contemporary competent flood events, however, cause severe damages in some of the embankments (i.e. lateral erosion). Gravel extractions in these sites are performed to protect these infrastructures and, in turn, are influencing local channel morpho-dynamics, increasing the sedimentary disequilibrium, exacerbating local channel incision processes, and modifying channel roughness and sediment transport dynamics. 2d hydraulic models show as these contemporary extractions influence on the magnitude and variability of hydraulic forces and, in turn, modify the conveyance of water and sediments through the study reach. All these changes have a direct influence on the ecological status of the river at different temporal and spatial scales. These links will be a key goal for progress towards the understanding of the interactions between river bed disturbance and ecological responses at multiple scales, and provide the basis for an integrated methodology that can be used to aid prediction, management and restoration of human stressed fluvial systems.

Efficacy and safety of biologic therapies for systemic lupus erythematosus treatment: systematic review and meta-analysis.

PubMed

Borba, Helena Hiemisch Lobo; Wiens, Astrid; de Souza, Thais Teles; Correr, Cassyano Januário; Pontarolo, Roberto

2014-04-01

The objectives of this study were to evaluate the efficacy, safety, and tolerability of biologic drugs compared with placebo for systemic lupus erythematosus (SLE) treatment. A systematic review evaluating the efficacy and safety of biologic therapies compared with placebo in adult SLE patients treatment was performed. Data from studies performed before September 2013 were collected from several databases (MEDLINE, Cochrane Library, SCIELO, Scopus, and International Pharmaceutical Abstracts). Study eligibility criteria included randomized, double-blind, placebo-controlled trials; regarding treatment with biologic agents in SLE adult patients; and published in English, German, Portuguese, and Spanish. Extracted data were statistically analyzed in a meta-analysis using the Review Manager (RevMan) 5.1 software. Efficacy outcomes included the SELENA-SLEDAI (Safety of Estrogens in Lupus Erythematosus National Assessment version of the SLE Disease Activity Index) score, the SRI (Systemic Lupus Erythematosus Responder Index), normalization of low C3 (<90 mg/dL), anti-double-stranded DNA positive to negative, and no new BILAG (British Isles Lupus Assessment Group index) 1A or 2B flares. Data on safety profile included adverse events, serious and severe adverse events, death, malignancy, infections, and infusion reactions. We also evaluated withdrawals from treatment due to lack of efficacy or adverse events. Thirteen randomized placebo-controlled trials met the criteria for data extraction for systematic review. A meta-analysis regarding the efficacy and safety of belimumab compared with placebo involving four of these trials was undertaken and the remainder contributed to a meta-analysis of the safety of biologic agents. In addition, two trials allowed the performance of a meta-analysis regarding the efficacy and safety of rituximab compared with placebo. Belimumab was more effective than placebo in most evaluated outcomes. No significant differences in the safety and tolerability data were observed between the belimumab and placebo groups. No differences were observed between the rituximab and placebo groups for the efficacy outcomes or safety parameters. Extracted data from the 13 studies were pooled, allowing assessment of the safety of biologic drugs. The meta-analysis revealed a satisfactory safety profile of these agents when used for SLE treatment, as there were no significant differences between the two evaluated groups (biologic agents and placebo) for all outcomes analyzed. Belimumab exhibited a satisfactory profile regarding efficacy, safety, and tolerability. Rituximab showed no superiority over placebo in terms of efficacy, despite its suitable safety profile. Biologic agents exhibited a good safety profile for SLE treatment, indicating that these agents are promising therapies and should be further investigated.

Rapid extraction of auditory feature contingencies.

PubMed

Bendixen, Alexandra; Prinz, Wolfgang; Horváth, János; Trujillo-Barreto, Nelson J; Schröger, Erich

2008-07-01

Contingent relations between sensory events render the environment predictable and thus facilitate adaptive behavior. The human capacity to detect such relations has been comprehensively demonstrated in paradigms in which contingency rules were task-relevant or in which they applied to motor behavior. The extent to which contingencies can also be extracted from events that are unrelated to the current goals of the organism has remained largely unclear. The present study addressed the emergence of contingency-related effects for behaviorally irrelevant auditory stimuli and the cortical areas involved in the processing of such contingency rules. Contingent relations between different features of temporally separate events were embedded in a new dynamic protocol. Participants were presented with the auditory stimulus sequences while their attention was captured by a video. The mismatch negativity (MMN) component of the event-related brain potential (ERP) was employed as an electrophysiological correlate of contingency detection. MMN generators were localized by means of scalp current density (SCD) and primary current density (PCD) analyses with variable resolution electromagnetic tomography (VARETA). Results show that task-irrelevant contingencies can be extracted from about fifteen to twenty successive events conforming to the contingent relation. Topographic and tomographic analyses reveal the involvement of the auditory cortex in the processing of contingency violations. The present data provide evidence for the rapid encoding of complex extrapolative relations in sensory areas. This capacity is of fundamental importance for the organism in its attempt to model the sensory environment outside the focus of attention.

Crew Recovery and Contingency Planning for a Manned Stratospheric Balloon Flight - the StratEx Program.

PubMed

Menon, Anil S; Jourdan, David; Nusbaum, Derek M; Garbino, Alejandro; Buckland, Daniel M; Norton, Sean; Clark, Johnathan B; Antonsen, Erik L

2016-10-01

The StratEx program used a self-contained space suit and balloon system to loft pilot Alan Eustace to a record-breaking altitude and skydive from 135,897 feet (41,422 m). After releasing from the balloon and a stabilized freefall, the pilot safely landed using a parachute system based on a modified tandem parachute rig. A custom spacesuit provided life support using a similar system to NASA's (National Aeronautics and Space Administration; Washington, DC USA) Extravehicular Mobility Unit. It also provided tracking, communications, and connection to the parachute system. A recovery support team, including at least two medical personnel and two spacesuit technicians, was charged with reaching the pilot within five minutes of touchdown to extract him from the suit and provide treatment for any injuries. The team had to track the flight at all times, be prepared to respond in case of premature release, and to operate in any terrain. Crew recovery operations were planned and tailored to anticipate outcomes during this novel event in a systematic fashion, through scenario and risk analysis, in order to minimize the probability and impact of injury. This analysis, detailed here, helped the team configure recovery assets, refine navigation and tracking systems, develop procedures, and conduct training. An extensive period of testing and practice culminated in three manned flights leading to a successful mission and setting the record for exit altitude, distance of fall with stabilizing device, and vertical speed with a stabilizing device. During this mission, recovery teams reached the landing spot within one minute, extracted the pilot, and confirmed that he was not injured. This strategy is presented as an approach to prehospital planning and care for improved safety during crew recovery in novel, extreme events. Menon AS , Jourdan D , Nusbaum DM , Garbino A , Buckland DM , Norton S , Clark JB , Antonsen EL . Crew recovery and contingency planning for a manned stratospheric balloon flight - the StratEx program. Prehosp Disaster Med. 2016;31(5):524-531.

Temporal dynamics of contingency extraction from tonal and verbal auditory sequences.

PubMed

Bendixen, Alexandra; Schwartze, Michael; Kotz, Sonja A

2015-09-01

Consecutive sound events are often to some degree predictive of each other. Here we investigated the brain's capacity to detect contingencies between consecutive sounds by means of electroencephalography (EEG) during passive listening. Contingencies were embedded either within tonal or verbal stimuli. Contingency extraction was measured indirectly via the elicitation of the mismatch negativity (MMN) component of the event-related potential (ERP) by contingency violations. MMN results indicate that structurally identical forms of predictability can be extracted from both tonal and verbal stimuli. We also found similar generators to underlie the processing of contingency violations across stimulus types, as well as similar performance in an active-listening follow-up test. However, the process of passive contingency extraction was considerably slower (twice as many rule exemplars were needed) for verbal than for tonal stimuli These results suggest caution in transferring findings on complex predictive regularity processing obtained with tonal stimuli directly to the speech domain. Copyright © 2014 Elsevier Inc. All rights reserved.

Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology

NASA Astrophysics Data System (ADS)

Al-Temeemy, Ali A.

2018-03-01

A descriptor is proposed for use in domiciliary healthcare monitoring systems. The descriptor is produced from chromatic methodology to extract robust features from the monitoring system's images. It has superior discrimination capabilities, is robust to events that normally disturb monitoring systems, and requires less computational time and storage space to achieve recognition. A method of human region segmentation is also used with this descriptor. The performance of the proposed descriptor was evaluated using experimental data sets, obtained through a series of experiments performed in the Centre for Intelligent Monitoring Systems, University of Liverpool. The evaluation results show high recognition performance for the proposed descriptor in comparison to traditional descriptors, such as moments invariant. The results also show the effectiveness of the proposed segmentation method regarding distortion effects associated with domiciliary healthcare systems.

Bio-inspired approach for intelligent unattended ground sensors

NASA Astrophysics Data System (ADS)

Hueber, Nicolas; Raymond, Pierre; Hennequin, Christophe; Pichler, Alexander; Perrot, Maxime; Voisin, Philippe; Moeglin, Jean-Pierre

2015-05-01

Improving the surveillance capacity over wide zones requires a set of smart battery-powered Unattended Ground Sensors capable of issuing an alarm to a decision-making center. Only high-level information has to be sent when a relevant suspicious situation occurs. In this paper we propose an innovative bio-inspired approach that mimics the human bi-modal vision mechanism and the parallel processing ability of the human brain. The designed prototype exploits two levels of analysis: a low-level panoramic motion analysis, the peripheral vision, and a high-level event-focused analysis, the foveal vision. By tracking moving objects and fusing multiple criteria (size, speed, trajectory, etc.), the peripheral vision module acts as a fast relevant event detector. The foveal vision module focuses on the detected events to extract more detailed features (texture, color, shape, etc.) in order to improve the recognition efficiency. The implemented recognition core is able to acquire human knowledge and to classify in real-time a huge amount of heterogeneous data thanks to its natively parallel hardware structure. This UGS prototype validates our system approach under laboratory tests. The peripheral analysis module demonstrates a low false alarm rate whereas the foveal vision correctly focuses on the detected events. A parallel FPGA implementation of the recognition core succeeds in fulfilling the embedded application requirements. These results are paving the way of future reconfigurable virtual field agents. By locally processing the data and sending only high-level information, their energy requirements and electromagnetic signature are optimized. Moreover, the embedded Artificial Intelligence core enables these bio-inspired systems to recognize and learn new significant events. By duplicating human expertise in potentially hazardous places, our miniature visual event detector will allow early warning and contribute to better human decision making.

A true real-time, on-line security system for waterborne pathogen surveillance

NASA Astrophysics Data System (ADS)

Adams, John A.; McCarty, David L.

2008-04-01

Over the past several years many advances have been made to monitor potable water systems for toxic threats. However, the need for real-time, on-line systems to detect the malicious introduction of deadly pathogens still exists. Municipal water distribution systems, government facilities and buildings, and high profile public events remain vulnerable to terrorist-related biological contamination. After years of research and development, an instrument using multi-angle light scattering (MALS) technology has been introduced to achieve on-line, real-time detection and classification of a waterborne pathogen event. The MALS system utilizes a continuous slip stream of water passing through a flow cell in the instrument. A laser beam, focused perpendicular to the water flow, strikes particles as they pass through the beam generating unique light scattering patterns that are captured by photodetectors. Microorganisms produce patterns termed 'bio-optical signatures' which are comparable to fingerprints. By comparing these bio-optical signatures to an on-board database of microorganism patterns, detection and classification occurs within minutes. If a pattern is not recognized, it is classified as an 'unknown' and the unidentified contaminant is registered as a potential threat. In either case, if the contaminant exceeds a customer's threshold, the system will immediately alert personnel to the contamination event while extracting a sample for confirmation. The system, BioSentry TM, developed by JMAR Technologies is now field-tested and commercially available. BioSentry is cost effective, uses no reagents, operates remotely, and can be used for continuous microbial surveillance in many water treatment environments. Examples of HLS installations will be presented along with data from the US EPA NHSRC Testing and Evaluation Facility.

Solute Response To Arid-Climate Managed-River Flow During Storm Events

NASA Astrophysics Data System (ADS)

McLean, B.; Shock, E.

2006-12-01

Storm pulses are widely used in unmanaged, temperate and subtropical river systems to resolve in-stream surface and subsurface flow components. Resulting catchment-scale hydrochemical mixing models yield insight into mechanisms of solute transport. Managed systems are far more complicated due to the human need for high quality water resources, which drives processes that are superimposed on most, if not all, of the unmanaged components. As an example, an increasingly large portion of the water supply for the Phoenix metropolitan area is derived from multiple surface water sources that are impounded, diverted and otherwise managed upstream from the urban core that consumes the water and produces anthropogenic impacts. During large storm events this managed system is perturbed towards natural behavior as it receives inputs from natural hydrologic pathways in addition to impervious surfaces and storm water drainage channels. Our goals in studying managed river systems during this critical transition state are to determine how the well- characterized behavior of natural systems break down as the system responds then returns to its managed state. Using storm events as perturbations we can contrast an arid managed system with the unmanaged system it approaches during the storm event. In the process, we can extract geochemical consequences specifically related to unknown urban components in the form of chemical fingerprints. The effects of river management on solute behavior were assessed by taking advantage of several anomalously heavy winter storm events in late 2004 and early 2005 using a rigorous sampling routine. Several hundred samples collected between January and October 2005 were analyzed for major ion, isotopic, and trace metal concentrations with 78 individual measurements for each sample. The data are used to resolve managed watershed processes, mechanisms of solute transport and river mixing from anthropogenic inputs. Our results show that concentrations of major solutes change slowly and are independent of discharge downstream from the dams on two major tributaries. This is indicative of reservoir release water. In addition, a third input is derived from the Colorado River via the Central Arizona Project canal system. Cross plots including concentrations of solutes such as nitrate and sulfate from downstream of the confluence indicate at least three end-member sources, as do Piper diagrams using major anion and cation data. Dynamic contributions from natural event water and urban inputs can be resolved from the slowly changing release water, and may dictate the short-term transport of pollutants during the storm-induced transition state.

Development and applications of the Veterans Health Administration's Stratification Tool for Opioid Risk Mitigation (STORM) to improve opioid safety and prevent overdose and suicide.

PubMed

Oliva, Elizabeth M; Bowe, Thomas; Tavakoli, Sara; Martins, Susana; Lewis, Eleanor T; Paik, Meenah; Wiechers, Ilse; Henderson, Patricia; Harvey, Michael; Avoundjian, Tigran; Medhanie, Amanuel; Trafton, Jodie A

2017-02-01

Concerns about opioid-related adverse events, including overdose, prompted the Veterans Health Administration (VHA) to launch an Opioid Safety Initiative and Overdose Education and Naloxone Distribution program. To mitigate risks associated with opioid prescribing, a holistic approach that takes into consideration both risk factors (e.g., dose, substance use disorders) and risk mitigation interventions (e.g., urine drug screening, psychosocial treatment) is needed. This article describes the Stratification Tool for Opioid Risk Mitigation (STORM), a tool developed in VHA that reflects this holistic approach and facilitates patient identification and monitoring. STORM prioritizes patients for review and intervention according to their modeled risk for overdose/suicide-related events and displays risk factors and risk mitigation interventions obtained from VHA electronic medical record (EMR)-data extracts. Patients' estimated risk is based on a predictive risk model developed using fiscal year 2010 (FY2010: 10/1/2009-9/30/2010) EMR-data extracts and mortality data among 1,135,601 VHA patients prescribed opioid analgesics to predict risk for an overdose/suicide-related event in FY2011 (2.1% experienced an event). Cross-validation was used to validate the model, with receiver operating characteristic curves for the training and test data sets performing well (>.80 area under the curve). The predictive risk model distinguished patients based on risk for overdose/suicide-related adverse events, allowing for identification of high-risk patients and enrichment of target populations of patients with greater safety concerns for proactive monitoring and application of risk mitigation interventions. Results suggest that clinical informatics can leverage EMR-extracted data to identify patients at-risk for overdose/suicide-related events and provide clinicians with actionable information to mitigate risk. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Revealing long-range multiparticle collectivity in small collision systems via subevent cumulants

NASA Astrophysics Data System (ADS)

Jia, Jiangyong; Zhou, Mingliang; Trzupek, Adam

2017-09-01

Multiparticle azimuthal cumulants, often used to study collective flow in high-energy heavy-ion collisions, have recently been applied in small collision systems such as p p and p +A to extract the second-order azimuthal harmonic flow v2. Recent observation of four-, six-, and eight-particle cumulants with "correct sign" c2{4 } <0 , c2{6 } >0 , c2{8 } <0 and approximate equality of the inferred single-particle harmonic flow, v2{4 } ≈v2{6 } ≈v2{8 } , have been used as strong evidence for a collective emission of all the soft particles produced in the collisions. We show that these relations in principle could be violated due to the non-Gaussianity in the event-by-event fluctuation of flow and/or nonflow. Furthermore, we show, using p p events generated with the pythia model, that c2{2 k } obtained with the standard cumulant method are dominated by nonflow from dijets. An alternative cumulant method based on two or more η -separated subevents is proposed to suppress the dijet contribution. The new method is shown to be able to recover a flow signal as low as 4% imposed on the pythia events, independently of how the event activity class is defined. Therefore the subevent cumulant method offers a more robust way of studying collectivity based on the existence of long-range azimuthal correlations between multiple distinct η ranges. The prospect of using the subevent cumulants to study collective flow in A +A collisions, in particular its longitudinal dynamics, is discussed.

Particulate Organic Matter Composition in Stream Runoff Following Large Storms: Role of POM Sources, Particle Size, and Event Characteristics

NASA Astrophysics Data System (ADS)

Johnson, Erin R.; Inamdar, Shreeram; Kan, Jinjun; Vargas, Rodrigo

2018-02-01

Large storm events possess significant erosive energy capable of mobilizing large amounts of sediment and particulate organic matter (POM) into fluvial systems. This study investigated how stream POM composition varied as a function of the watershed POM source, particle size, storm event magnitude, and seasonal timing. POM composition was characterized for multiple watershed sources and for stream POM following storms in a second-order forested stream. Carbon (C) and nitrogen (N) amount, C:N ratio and isotopic content (13C and 15N) were determined for solid phase POM, whereas dissolved organic C, total N concentrations, and fluorescence characteristics were determined for solution/extracted POM. Key findings from this study were the following: (1) Composition of POM varied greatly with watershed sources with forest floor litter being C and N rich and labile, while stream banks and bed were C and N poor and recalcitrant. (2) Summer storms mobilized more carbon and nitrogen-rich labile sources, while winter events mobilized more carbon- and nitrogen-poor refractory material from near-stream sources. (3) POM composition varied by size class, with the coarse POM showing more C and N rich and labile properties, while the fine POM displayed more degraded and refractory properties. If climate variability increases the magnitude and intensity of large storm events, our observations suggest that this will not only increase the inputs of POM to aquatic systems but also result in the delivery of coarser, C and N rich, and more bioavailable POM to the stream drainage network.

Revealing long-range multiparticle collectivity in small collision systems via subevent cumulants

DOE PAGES

Jia, Jiangyong; Zhou, Mingliang; Trzupek, Adam

2017-09-25

Multi-particle azimuthal cumulants, often used to study collective flow in high-energy heavy-ion collisions, have recently been applied in small collision systems such as pp and p+A to extract the second-order azimuthal harmonic flow v 2. Recent observation of four-, six- and eight-particle cumulants with “correct sign” c 2{4} < 0, c 2{6} > 0, c 2{8} < 0 and approximate equality of the inferred single-particle harmonic flow, v 2{4} ≈ v 2{6} ≈ v 2{8}, have been used as strong evidence for a collective emission of all soft particles produced in the collisions. In this paper, we show that thesemore » relations in principle could be violated due to the non-Gaussianity in the event-by-event fluctuation of flow and/or non-flow. Furthermore, we show, using pp events generated with the PYTHIA model, that c 2{2k} obtained with standard cumulant method are dominated by non-flow from dijets. An alternative cumulant method based on two or more η-separated subevents is proposed to suppress the dijet contribution. The new method is shown to be able to recover a flow signal as low as 4% imposed on the PYTHIA events, independently of how the event activity class is defined. Therefore the subevent cumulant method offers a more robust way of studying collectivity based on the existence of long-range azimuthal correlations between multiple distinct η ranges. Finally, the prospect of using the subevent cumulants to study collective flow in A+A collisions, in particular its longitudinal dynamics, is discussed.« less

A Wireless Intracranial Brain Deformation Sensing System for Blast-Induced Traumatic Brain Injury

PubMed Central

Song, S.; Race, N. S.; Kim, A.; Zhang, T.; Shi, R.; Ziaie, B.

2015-01-01

Blast-induced traumatic brain injury (bTBI) has been linked to a multitude of delayed-onset neurodegenerative and neuropsychiatric disorders, but complete understanding of their pathogenesis remains elusive. To develop mechanistic relationships between bTBI and post-blast neurological sequelae, it is imperative to characterize the initiating traumatic mechanical events leading to eventual alterations of cell, tissue, and organ structure and function. This paper presents a wireless sensing system capable of monitoring the intracranial brain deformation in real-time during the event of a bTBI. The system consists of an implantable soft magnet and an external head-mounted magnetic sensor that is able to measure the field in three dimensions. The change in the relative position of the soft magnet WITH respect to the external sensor as the result of the blast wave induces changes in the magnetic field. The magnetic field data in turn is used to extract the temporal and spatial motion of the brain under the blast wave in real-time. The system has temporal and spatial resolutions of 5 μs and 10 μm. Following the characterization and validation of the sensor system, we measured brain deformations in a live rodent during a bTBI. PMID:26586273

Short-term open-label chamomile (Matricaria chamomilla L.) therapy of moderate to severe generalized anxiety disorder.

PubMed

Keefe, John R; Mao, Jun J; Soeller, Irene; Li, Qing S; Amsterdam, Jay D

2016-12-15

Conventional drug treatments for Generalized Anxiety Disorder (GAD) are often accompanied by substantial side effects, dependence, and/or withdrawal syndrome. A prior controlled study of oral chamomile (Matricaria chamomilla L.) extract showed significant efficacy versus placebo, and suggested that chamomile may have anxiolytic activity for individuals with GAD. We hypothesized that treatment with chamomile extract would result in a significant reduction in GAD severity ratings, and would be associated with a favorable adverse event and tolerability profile. We report on the open-label phase of a two-phase randomized controlled trial of chamomile versus placebo for relapse-prevention of recurrent GAD. Subjects with moderate to severe GAD received open-label treatment with pharmaceutical-grade chamomile extract 1500mg/day for up to 8 weeks. Primary outcomes were the frequency of clinical response and change in GAD-7 symptom scores by week 8. Secondary outcomes included the change over time on the Hamilton Rating Scale for Anxiety, the Beck Anxiety Inventory, and the Psychological General Well Being Index. Frequency of treatment-emergent adverse events and premature treatment discontinuation were also examined. Of 179 subjects, 58.1% (95% CI: 50.9% to 65.5%) met criteria for response, while 15.6% prematurely discontinued treatment. Significant improvement over time was also observed on the GAD-7 rating (β=-8.4 [95% CI=-9.1 to -7.7]). A similar proportion of subjects demonstrated statistically significant and clinically meaningful reductions in secondary outcome ratings of anxiety and well-being. Adverse events occurred in 11.7% of subjects, although no serious adverse events occurred. Chamomile extract produced a clinically meaningful reduction in GAD symptoms over 8 weeks, with a response rate comparable to those observed during conventional anxiolytic drug therapy and a favorable adverse event profile. Future comparative effectiveness trials between chamomile and conventional drugs may help determine the optimal risk/benefit of these therapies for patients suffering from GAD. Copyright © 2016 Elsevier GmbH. All rights reserved.

Integrated Magneto-Chemical Sensor For On-Site Food Allergen Detection.

PubMed

Lin, Hsing-Ying; Huang, Chen-Han; Park, Jongmin; Pathania, Divya; Castro, Cesar M; Fasano, Alessio; Weissleder, Ralph; Lee, Hakho

2017-10-24

Adverse food reactions, including food allergies, food sensitivities, and autoimmune reaction (e.g., celiac disease) affect 5-15% of the population and remain a considerable public health problem requiring stringent food avoidance and epinephrine availability for emergency events. Avoiding problematic foods is practically difficult, given current reliance on prepared foods and out-of-home meals. In response, we developed a portable, point-of-use detection technology, termed integrated exogenous antigen testing (iEAT). The system consists of a disposable antigen extraction device coupled with an electronic keychain reader for rapid sensing and communication. We optimized the prototype iEAT system to detect five major food antigens in peanuts, hazelnuts, wheat, milk, and eggs. Antigen extraction and detection with iEAT requires <10 min and achieves high-detection sensitivities (e.g., 0.1 mg/kg for gluten, lower than regulatory limits of 20 mg/kg). When testing under restaurant conditions, we were able to detect hidden food antigens such as gluten within "gluten-free" food items. The small size and rapid, simple testing of the iEAT system should help not only consumers but also other key stakeholders such as clinicians, food industries, and regulators to enhance food safety.

Client-Side Event Processing for Personalized Web Advertisement

NASA Astrophysics Data System (ADS)

Stühmer, Roland; Anicic, Darko; Sen, Sinan; Ma, Jun; Schmidt, Kay-Uwe; Stojanovic, Nenad

The market for Web advertisement is continuously growing and correspondingly, the number of approaches that can be used for realizing Web advertisement are increasing. However, current approaches fail to generate very personalized ads for a current Web user that is visiting a particular Web content. They mainly try to develop a profile based on the content of that Web page or on a long-term user's profile, by not taking into account current user's preferences. We argue that by discovering a user's interest from his current Web behavior we can support the process of ad generation, especially the relevance of an ad for the user. In this paper we present the conceptual architecture and implementation of such an approach. The approach is based on the extraction of simple events from the user interaction with a Web page and their combination in order to discover the user's interests. We use semantic technologies in order to build such an interpretation out of many simple events. We present results from preliminary evaluation studies. The main contribution of the paper is a very efficient, semantic-based client-side architecture for generating and combining Web events. The architecture ensures the agility of the whole advertisement system, by complexly processing events on the client. In general, this work contributes to the realization of new, event-driven applications for the (Semantic) Web.

Wintertime Secondary Organic Aerosol (SOA) Formation from Oxidation of Volatile Organic Compounds (VOCs) Associated with Oil and Gas Extraction

NASA Astrophysics Data System (ADS)

Murphy, S. M.; Soltis, J.; Field, R. A.; Bates, T. S.; Quinn, P.; De Gouw, J. A.; Veres, P. R.; Warneke, C.; Graus, M.; Gilman, J.; Lerner, B. M.; Koss, A.

2013-12-01

The Uintah Basin is located in a lightly populated area of Northeastern Utah near Dinosaur National Monument. Oil and gas extraction activities in the basin have dramatically increased in recent years due to the application of hydraulic fracturing. The Uintah Basin has experienced numerous high-ozone events during the past several winters with concentrations often exceeding 100 ppb. PM 2.5 monitoring by the city of Vernal, located at the edge of the basin, have shown wintertime concentrations in excess of the EPA 8-hour national standard, though the source and composition of particulates during these events is unclear. The Energy and Environment - Uintah Basin Winter Ozone Study (E&E UBWOS) was conducted during the winters of 2012 and 2013. During the study, intensive measurements of aerosol composition and speciated VOCs were made at a monitoring site near oil and gas extraction activities. Organic aerosol was found to be a major component of PM 2.5 and organic aerosol formation was highly correlated with the production of secondary VOC's. This correlation suggests that the organic aerosol is secondary in nature even though O:C ratios suggest a less oxidized aerosol than often observed in summertime SOA. The ozone levels and organic aerosol mass during 2012 were much lower than those observed in 2013. Calculations of the aerosol yield during both years will be presented along with an analysis of how well observed yields match predictions based on smog-chamber data. The potential for additional aerosol formation in the system will also be discussed.

Remodeling of ribosomal genes in somatic cells by Xenopus egg extract

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

Ostrup, Olga, E-mail: osvarcova@gmail.com; Stem Cell Epigenetics Laboratory, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo; Norwegian Center for Stem Cell Research, Oslo

Highlights: {yields} Xenopus egg extract remodels nuclei and alter cell growth characteristics. {yields} Ribosomal genes are reprogrammed within 6 h after extract exposure. {yields} rDNA reprogramming involves promoter targeting of SNF2H remodeling complex. {yields} Xenopus egg extract does not initiate stress-related response in somatic cells. {yields} Aza-cytidine elicits a stress-induced response in reprogrammed cells. -- Abstract: Extracts from Xenopus eggs can reprogram gene expression in somatic nuclei, however little is known about the earliest processes associated with the switch in the transcriptional program. We show here that an early reprogramming event is the remodeling of ribosomal chromatin and gene expression.more » This occurs within hours of extract treatment and is distinct from a stress response. Egg extract elicits remodeling of the nuclear envelope, chromatin and nucleolus. Nucleolar remodeling involves a rapid and stable decrease in ribosomal gene transcription, and promoter targeting of the nucleolar remodeling complex component SNF2H without affecting occupancy of the transcription factor UBF and the stress silencers SUV39H1 and SIRT1. During this process, nucleolar localization of UBF and SIRT1 is not altered. On contrary, azacytidine pre-treatment has an adverse effect on rDNA remodeling induced by extract and elicits a stress-type nuclear response. Thus, an early event of Xenopus egg extract-mediated nuclear reprogramming is the remodeling of ribosomal genes involving nucleolar remodeling complex. Condition-specific and rapid silencing of ribosomal genes may serve as a sensitive marker for evaluation of various reprogramming methods.« less

Epileptic seizure onset detection based on EEG and ECG data fusion.

PubMed

Qaraqe, Marwa; Ismail, Muhammad; Serpedin, Erchin; Zulfi, Haneef

2016-05-01

This paper presents a novel method for seizure onset detection using fused information extracted from multichannel electroencephalogram (EEG) and single-channel electrocardiogram (ECG). In existing seizure detectors, the analysis of the nonlinear and nonstationary ECG signal is limited to the time-domain or frequency-domain. In this work, heart rate variability (HRV) extracted from ECG is analyzed using a Matching-Pursuit (MP) and Wigner-Ville Distribution (WVD) algorithm in order to effectively extract meaningful HRV features representative of seizure and nonseizure states. The EEG analysis relies on a common spatial pattern (CSP) based feature enhancement stage that enables better discrimination between seizure and nonseizure features. The EEG-based detector uses logical operators to pool SVM seizure onset detections made independently across different EEG spectral bands. Two fusion systems are adopted. In the first system, EEG-based and ECG-based decisions are directly fused to obtain a final decision. The second fusion system adopts an override option that allows for the EEG-based decision to override the fusion-based decision in the event that the detector observes a string of EEG-based seizure decisions. The proposed detectors exhibit an improved performance, with respect to sensitivity and detection latency, compared with the state-of-the-art detectors. Experimental results demonstrate that the second detector achieves a sensitivity of 100%, detection latency of 2.6s, and a specificity of 99.91% for the MAJ fusion case. Copyright © 2016 Elsevier Inc. All rights reserved.

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

Quantification of Dune Response over the Course of a 6-Day Nor'Easter, Outer Banks, NC

NASA Astrophysics Data System (ADS)

Brodie, K. L.; Spore, N.; Swann, C.

2014-12-01

The amount and type of foredune morphologic change during a storm event primarily scales with the level of inundation during that event. Specifically, external hydrodynamic forcing (total water level) can be compared with antecedent beach and foredune morphology to predict an impact regime that relates to the type of expected morphologic evolution of the system. For example, when total water levels are above the dune toe, but below the dune crest, the impact regime is classified as "collision" and the expected morphology response is slumping or scarping of the dune face. While the amount of dune retreat scales largely with the duration of wave attack to the dune face, characteristics of the dune other than its crest or toe elevation may also enhance or impede rates of morphologic change. The aftermath of Hurricane Sandy provided a unique opportunity to observe alongshore variations in dune response to a 6-day Nor'Easter (Hs >4 m in 6 m depth), as a variety of dunes were constructed (or not) by individual home owners in preparation for the winter storm season. Daily terrestrial lidar scans were conducted along 20 km of coastline in Duck, NC using Coastal Lidar And Radar Imaging System (CLARIS) during the first dune collision event following Sandy. Foredunes were grouped by their pre-storm form (e.g. vegetated, pushed, scarped, etc) using automated feature extraction tools based on surface curvature and slope, and daily rates of morphologic volume change were calculated. The highest dune retreat rates were focused along a 1.5 km region where cross-shore erosion of recently pushed, un-vegetated dunes reached 2 m/day. Variations in dune response were analyzed in relation to their pre-storm morphology, with care taken to normalize for alongshore variations in hydrodynamic forcing. Ongoing research is focused on identifying specific metrics that can be easily extracted from topographic DEMs to aid in dune retreat predictions.

A Translation System Reconstituted with Human Factors Proves That Processing of Encephalomyocarditis Virus Proteins 2A and 2B Occurs in the Elongation Phase of Translation without Eukaryotic Release Factors*

PubMed Central

Machida, Kodai; Mikami, Satoshi; Masutani, Mamiko; Mishima, Kurumi; Kobayashi, Tominari; Imataka, Hiroaki

2014-01-01

The genomic RNA of encephalomyocarditis virus (EMCV) encodes a single polyprotein, and the primary scission of the polyprotein occurs between nonstructural proteins 2A and 2B by an unknown mechanism. To gain insight into the mechanism of 2A-2B processing, we first translated the 2A-2B region in vitro with eukaryotic and prokaryotic translation systems. The 2A-2B processing occurred only in the eukaryotic systems, not in the prokaryotic systems, and the unprocessed 2A-2B protein synthesized by a prokaryotic system remained uncleaved when incubated with a eukaryotic cell extract. These results suggest that 2A-2B processing is a eukaryote-specific, co-translational event. To define the translation factors required for 2A-2B processing, we constituted a protein synthesis system with eukaryotic elongation factors 1 and 2, eukaryotic release factors 1 and 3 (eRF1 and eRF3), aminoacyl-tRNA synthetases, tRNAs, ribosome subunits, and a plasmid template that included the hepatitis C virus internal ribosome entry site. We successfully reproduced 2A-2B processing in the reconstituted system even without eRFs. Our results indicate that this unusual event occurs in the elongation phase of translation. PMID:25258322

Evaluating charge noise acting on semiconductor quantum dots in the circuit quantum electrodynamics architecture

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

Basset, J.; Stockklauser, A.; Jarausch, D.-D.

2014-08-11

We evaluate the charge noise acting on a GaAs/GaAlAs based semiconductor double quantum dot dipole-coupled to the voltage oscillations of a superconducting transmission line resonator. The in-phase (I) and the quadrature (Q) components of the microwave tone transmitted through the resonator are sensitive to charging events in the surrounding environment of the double dot with an optimum sensitivity of 8.5×10{sup −5} e/√(Hz). A low frequency 1/f type noise spectrum combined with a white noise level of 6.6×10{sup −6} e{sup 2}/Hz above 1 Hz is extracted, consistent with previous results obtained with quantum point contact charge detectors on similar heterostructures. The slope ofmore » the 1/f noise allows to extract a lower bound for the double-dot charge qubit dephasing rate which we compare to the one extracted from a Jaynes-Cummings Hamiltonian approach. The two rates are found to be similar emphasizing that charge noise is the main source of dephasing in our system.« less

Typicality and Misinformation: Two Sources of Distortion

ERIC Educational Resources Information Center

Luna, Karlos; Migueles, Malen

2008-01-01

This study examined the effect of two sources of memory error: exposure to post-event information and extracting typical contents from schemata. Participants were shown a video of a bank robbery and presented with high-and low-typicality misinformation extracted from two normative studies. The misleading suggestions consisted of either changes in…

Filing Sources after Oral P2Y12 Platelet Inhibitors to the Food and Drug Administration Adverse Event Reporting System (FAERS).

PubMed

Serebruany, Victor L; Cherepanov, Vasily; Kim, Moo Hyun; Litvinov, Oleg; Cabrera-Fuentes, Hector A; Marciniak, Thomas A

The US Food and Drug Administration Adverse Event Reporting System (FAERS) is a global passive surveillance database that relies on voluntary reporting by health care professionals and consumers as well as required mandatory reporting by pharmaceutical manufacturers. However, the initial filers and comparative patterns for oral P2Y12 platelet inhibitor reporting are unknown. We assessed who generated original FAERS reports for clopidogrel, prasugrel, and ticagrelor in 2015. From the FAERS database we extracted and examined adverse event cases coreported with oral P2Y12 platelet inhibitors. All adverse event filing originating sources were dichotomized into consumers, lawyers, pharmacists, physicians, other health care professionals, and unknown. Overall, 2015 annual adverse events were more commonly coreported with clopidogrel (n = 13,234) with known source filers (n = 12,818, or 96.9%) than with prasugrel (2,896; 98.9% out of 2,927 cases) or ticagrelor (2,163, or 82.3%, out of 2,627 cases, respectively). Overall, most adverse events were filed by consumers (8,336, or 44.4%), followed by physicians (5,290, or 28.2%), other health care professionals (2,997, or 16.0%), pharmacists (1,125, or 6.0%), and finally by lawyers (129, or 0.7%). The origin of 811 (4.7%) initial reports remains unknown. The adverse event filing sources differ among drugs. While adverse events coreported with clopidogrel and prasugrel were commonly originated by patients (40.4 and 84.3%, respectively), most frequently ticagrelor reports (42.5%) were filed by physicians. The reporting quality and initial sources differ among oral P2Y12 platelet inhibitors in FAERS. The ticagrelor surveillance in 2015 was inadequate when compared to clopidogrel and prasugrel. Patients filed most adverse events for clopidogrel and prasugrel, while physicians originated most ticagrelor complaints. These differences justify stricter compliance control for ticagrelor manufacturers and may be attributed to the confusion of treating physicians with unexpected fatal, cardiac, and thrombotic adverse events linked to ticagrelor. © 2017 S. Karger AG, Basel.

Statistical analysis of experimental multifragmentation events in 64Zn+112Sn at 40 MeV/nucleon

NASA Astrophysics Data System (ADS)

Lin, W.; Zheng, H.; Ren, P.; Liu, X.; Huang, M.; Wada, R.; Chen, Z.; Wang, J.; Xiao, G. Q.; Qu, G.

2018-04-01

A statistical multifragmentation model (SMM) is applied to the experimentally observed multifragmentation events in an intermediate heavy-ion reaction. Using the temperature and symmetry energy extracted from the isobaric yield ratio (IYR) method based on the modified Fisher model (MFM), SMM is applied to the reaction 64Zn+112Sn at 40 MeV/nucleon. The experimental isotope distribution and mass distribution of the primary reconstructed fragments are compared without afterburner and they are well reproduced. The extracted temperature T and symmetry energy coefficient asym from SMM simulated events, using the IYR method, are also consistent with those from the experiment. These results strongly suggest that in the multifragmentation process there is a freezeout volume, in which the thermal and chemical equilibrium is established before or at the time of the intermediate-mass fragments emission.

Occupational Fatalities Resulting from Falls in the Oil and Gas Extraction Industry, United States, 2005-2014.

PubMed

Mason, Krystal L; Retzer, Kyla D; Hill, Ryan; Lincoln, Jennifer M

2017-04-28

During 2003-2013, fatality rates for oil and gas extraction workers decreased for all causes of death except those associated with fall events, which increased 2% annually during 2003-2013 (1). To better understand risk factors for these events, CDC examined fatal fall events in the oil and gas extraction industry during 2005-2014 using data from case investigations conducted by the Occupational Safety and Health Administration (OSHA). Sixty-three fatal falls were identified, accounting for 15% of all fatal events. Among fatal falls, 33 (52%) workers fell from a height of >30 feet (9 meters), and 22 (35%) fell from the derrick board, the elevated work platform located in the derrick (structure used to support machinery on a drilling rig). Fall fatalities occurred most frequently when drilling rigs were being assembled or disassembled at the well site (rigging up or rigging down) (14; 22%) or when workers were removing or inserting drill pipe into the wellbore (14; 22%). Measures that target derrickmen and workers engaged in assembling and disassembling drilling rigs (rigging up and down) could reduce falls in this industry. Companies should annually update their fall protection plans and ensure effective fall prevention programs are in place for workers at highest risk for falls, including providing trainings on proper use, fit, and inspection of personal protective equipment.

Investigation of relationships between parameters of solar nano-flares and solar activity

NASA Astrophysics Data System (ADS)

Safari, Hossein; Javaherian, Mohsen; Kaki, Bardia

2016-07-01

Solar flares are one of the important coronal events which are originated in solar magnetic activity. They release lots of energy during the interstellar medium, right after the trigger. Flare prediction can play main role in avoiding eventual damages on the Earth. Here, to interpret solar large-scale events (e.g., flares), we investigate relationships between small-scale events (nano-flares) and large-scale events (e.g., flares). In our method, by using simulations of nano-flares based on Monte Carlo method, the intensity time series of nano-flares are simulated. Then, the solar full disk images taken at 171 angstrom recorded by SDO/AIA are employed. Some parts of the solar disk (quiet Sun (QS), coronal holes (CHs), and active regions (ARs)) are cropped and the time series of these regions are extracted. To compare the simulated intensity time series of nano-flares with the intensity time series of real data extracted from different parts of the Sun, the artificial neural networks is employed. Therefore, we are able to extract physical parameters of nano-flares like both kick and decay rate lifetime, and the power of their power-law distributions. The procedure of variations in the power value of power-law distributions within QS, CH is similar to AR. Thus, by observing the small part of the Sun, we can follow the procedure of solar activity.

Dynamic analysis and pattern visualization of forest fires.

PubMed

Lopes, António M; Tenreiro Machado, J A

2014-01-01

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

PubMed Central

Lopes, António M.; Tenreiro Machado, J. A.

2014-01-01

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns. PMID:25137393

Adverse-event profile of Crataegus spp.: a systematic review.

PubMed

Daniele, Claudia; Mazzanti, Gabriela; Pittler, Max H; Ernst, Edzard

2006-01-01

Crataegus spp. (hawthorn) monopreparations are predominantly used for treating congestive heart failure. The effectiveness of hawthorn preparations (flowers with leaves; berries) is documented in a number of clinical studies, reviews and meta-analyses. The aim of this article is to assess the safety data of all available human studies on hawthorn monopreparations. Systematic searches were conducted on MEDLINE, EMBASE, AMED, The Cochrane Library, the UK National Research Register and the US ClinicalTrials.gov (up to January 2005). Data were requested from the spontaneous reporting scheme of the WHO. Hand searches were also conducted in a sample of relevant medical journals, conference proceedings, reference lists of identified articles and our own files. Eight manufacturers of hawthorn-containing preparations were contacted and asked to supply any information on adverse events or drug interactions. Data from all clinical studies and reports were assessed. Only human studies on monopreparations were included. Data from hawthorn-containing combination preparations and homeopathic preparations were excluded. All studies were read and evaluated by one reviewer and independently verified by at least one additional reviewer.Twenty-nine clinical studies were identified, of which 24 met our inclusion criteria. A total of 7311 patients were enrolled, and data from 5,577 patients were available for analysis. The daily dose and duration of treatment with hawthorn monopreparations ranged from 160 to 1,800 mg and from 3 to 24 weeks, respectively. The extracts most used in the clinical trials were WS 1,442 (extract of hawthorn standardised to 18.75% oligomeric procyanidins) and LI 132 (extract of hawthorn standardised to 2.25% flavonoids). Overall, 166 adverse events were reported. Most of these adverse events were, in general, mild to moderate; eight severe adverse events have been reported with the LI 132 extract. The most frequent adverse events were dizziness/vertigo (n = 15), gastrointestinal complaints (n = 24), headache (n = 9), migraine (n = 8) and palpitation (n = 11). The WHO spontaneous reporting scheme received 18 case reports. In the identified trials, the most frequent adverse events were dizziness (n = 6), nausea (n = 5), fall (n = 2), gastrointestinal haemorrhage (n = 2), circulation failure (n = 2) and erythematous rash (n = 2). There were no reports of drug interactions. In conclusion, all data reviewed in this article seem to indicate that hawthorn is well tolerated even if some severe adverse events were reported; this suggests that further studies are needed to better assess the safety of hawthorn-containing preparations. Moreover, the unsupervised use of this drug can be associated with problems, especially if given with concomitant medications.

OAE: The Ontology of Adverse Events.

PubMed

He, Yongqun; Sarntivijai, Sirarat; Lin, Yu; Xiang, Zuoshuang; Guo, Abra; Zhang, Shelley; Jagannathan, Desikan; Toldo, Luca; Tao, Cui; Smith, Barry

2014-01-01

A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term 'adverse event' denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA. OAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e.g., vaccinee age) important for determining their clinical outcomes.

Dietary Supplement Adverse Event Report Data From the FDA Center for Food Safety and Applied Nutrition Adverse Event Reporting System (CAERS), 2004-2013.

PubMed

Timbo, Babgaleh B; Chirtel, Stuart J; Ihrie, John; Oladipo, Taiye; Velez-Suarez, Loy; Brewer, Vickery; Mozersky, Robert

2018-05-01

The Food and Drug Administration (FDA)'s Center for Food Safety and Applied Nutrition (CFSAN) oversees the safety of the nation's foods, dietary supplements, and cosmetic products. To present a descriptive analysis of the 2004-2013 dietary supplement adverse event report (AER) data from CAERS and evaluate the 2006 Dietary Supplements and Nonprescription Drug Consumer Protection Act as pertaining to dietary supplements adverse events reporting. We queried CAERS for data from the 2004-2013 AERs specifying at least 1 suspected dietary supplement product. We extracted the product name(s), the symptom(s) reported, age, sex, and serious adverse event outcomes. We examined time trends for mandatory and voluntary reporting and performed analysis using SAS v9.4 and R v3.3.0 software. Of the total AERs (n = 15 430) received from January 1, 2004, through December 31, 2013, indicating at least 1 suspected dietary supplement product, 66.9% were mandatory, 32.2% were voluntary, and 0.9% were both mandatory and voluntary. Reported serious outcomes included death, life-threatening conditions, hospitalizations, congenital anomalies/birth defects and events requiring interventions to prevent permanent impairments (5.1%). The dietary supplement adverse event reporting rate in the United States was estimated at ~2% based on CAERS data. This study characterizes CAERS dietary supplement adverse event data for the 2004-2013 period and estimates a reporting rate of 2% for dietary supplement adverse events based on CAERS data. The findings show that the 2006 Dietary Supplements and Nonprescription Drug Consumer Protection Act had a substantial impact on the reporting of adverse events.

REANALYSES OF ANOMALOUS GRAVITATIONAL MICROLENSING EVENTS IN THE OGLE-III EARLY WARNING SYSTEM DATABASE WITH COMBINED DATA

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

Jeong, J.; Park, H.; Han, C.

2015-05-01

We reanalyze microlensing events in the published list of anomalous events that were observed from the Optical Gravitational Lensing Experiment (OGLE) lensing survey conducted during the 2004–2008 period. In order to check the existence of possible degenerate solutions and extract extra information, we conduct analyses based on combined data from other survey and follow-up observation and consider higher-order effects. Among the analyzed events, we present analyses of eight events for which either new solutions are identified or additional information is obtained. We find that the previous binary-source interpretations of five events are better interpreted by binary-lens models. These events includemore » OGLE-2006-BLG-238, OGLE-2007-BLG-159, OGLE-2007-BLG-491, OGLE-2008-BLG-143, and OGLE-2008-BLG-210. With additional data covering caustic crossings, we detect finite-source effects for six events including OGLE-2006-BLG-215, OGLE-2006-BLG-238, OGLE-2006-BLG-450, OGLE-2008-BLG-143, OGLE-2008-BLG-210, and OGLE-2008-BLG-513. Among them, we are able to measure the Einstein radii of three events for which multi-band data are available. These events are OGLE-2006-BLG-238, OGLE-2008-BLG-210, and OGLE-2008-BLG-513. For OGLE-2008-BLG-143, we detect higher-order effects induced by the changes of the observer’s position caused by the orbital motion of the Earth around the Sun. In addition, we present degenerate solutions resulting from the known close/wide or ecliptic degeneracy. Finally, we note that the masses of the binary companions of the lenses of OGLE-2006-BLG-450 and OGLE-2008-BLG-210 are in the brown-dwarf regime.« less

Comprehensive Assessment of Models and Events based on Library tools (CAMEL)

NASA Astrophysics Data System (ADS)

Rastaetter, L.; Boblitt, J. M.; DeZeeuw, D.; Mays, M. L.; Kuznetsova, M. M.; Wiegand, C.

2017-12-01

At the Community Coordinated Modeling Center (CCMC), the assessment of modeling skill using a library of model-data comparison metrics is taken to the next level by fully integrating the ability to request a series of runs with the same model parameters for a list of events. The CAMEL framework initiates and runs a series of selected, pre-defined simulation settings for participating models (e.g., WSA-ENLIL, SWMF-SC+IH for the heliosphere, SWMF-GM, OpenGGCM, LFM, GUMICS for the magnetosphere) and performs post-processing using existing tools for a host of different output parameters. The framework compares the resulting time series data with respective observational data and computes a suite of metrics such as Prediction Efficiency, Root Mean Square Error, Probability of Detection, Probability of False Detection, Heidke Skill Score for each model-data pair. The system then plots scores by event and aggregated over all events for all participating models and run settings. We are building on past experiences with model-data comparisons of magnetosphere and ionosphere model outputs in GEM2008, GEM-CEDAR CETI2010 and Operational Space Weather Model challenges (2010-2013). We can apply the framework also to solar-heliosphere as well as radiation belt models. The CAMEL framework takes advantage of model simulations described with Space Physics Archive Search and Extract (SPASE) metadata and a database backend design developed for a next-generation Run-on-Request system at the CCMC.

GPS signal loss in the wide area monitoring system: Prevalence, impact, and solution

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

Yao, Wenxuan; Zhou, Dao; Zhan, Lingwei

The phasor measurement unit (PMUs), equipped with Global Positioning System (GPS) receivers for precise time synchronization, provides measurements of voltage and current phasors at different nodes of the wide area monitoring system. However, GPS receivers are likely to lose satellite signals due to various unpredictable factors. The prevalence of GPS signal loss (GSL) on PMUs is first investigated using real PMU data. The historical GSL events are extracted from a phasor data concentrator (PDC) and FNET/GridEye server. The correlation between GSL and time, spatial location, solar activity are explored via comprehensive statistical analysis. Furthermore, the impact of GSL on phasormore » measurement accuracy has been studied via experiments. Finally, several potential solutions to mitigate the impact of GSL on PMUs are discussed and compared.« less

GPS signal loss in the wide area monitoring system: Prevalence, impact, and solution

DOE PAGES

Yao, Wenxuan; Zhou, Dao; Zhan, Lingwei; ...

2017-03-19

The phasor measurement unit (PMUs), equipped with Global Positioning System (GPS) receivers for precise time synchronization, provides measurements of voltage and current phasors at different nodes of the wide area monitoring system. However, GPS receivers are likely to lose satellite signals due to various unpredictable factors. The prevalence of GPS signal loss (GSL) on PMUs is first investigated using real PMU data. The historical GSL events are extracted from a phasor data concentrator (PDC) and FNET/GridEye server. The correlation between GSL and time, spatial location, solar activity are explored via comprehensive statistical analysis. Furthermore, the impact of GSL on phasormore » measurement accuracy has been studied via experiments. Finally, several potential solutions to mitigate the impact of GSL on PMUs are discussed and compared.« less

Weak-value amplification as an optimal metrological protocol

NASA Astrophysics Data System (ADS)

Alves, G. Bié; Escher, B. M.; de Matos Filho, R. L.; Zagury, N.; Davidovich, L.

2015-06-01

The implementation of weak-value amplification requires the pre- and postselection of states of a quantum system, followed by the observation of the response of the meter, which interacts weakly with the system. Data acquisition from the meter is conditioned to successful postselection events. Here we derive an optimal postselection procedure for estimating the coupling constant between system and meter and show that it leads both to weak-value amplification and to the saturation of the quantum Fisher information, under conditions fulfilled by all previously reported experiments on the amplification of weak signals. For most of the preselected states, full information on the coupling constant can be extracted from the meter data set alone, while for a small fraction of the space of preselected states, it must be obtained from the postselection statistics.

Centrifugal contactor modified for end stage operation in a multistage system

DOEpatents

Jubin, Robert T.

1990-01-01

A cascade formed of a plurality of centrifugal contactors useful for countercurrent solvent extraction processes such as utilizable for the reprocessing of nuclear reactor fuels is modified to permit operation in the event one or both end stages of the cascade become inoperative. Weir assemblies are connected to each of the two end stages by suitable conduits for separating liquids discharged from an inoperative end stage based upon the weight of the liquid phases uses in the solvent extraction process. The weir assembly at one end stage is constructed to separate and discharge the heaviest liquid phase while the weir assembly at the other end stage is constructed to separate and discharge the lightest liquid phase. These weir assemblies function to keep the liquid discharge from an inoperative end stages on the same weight phase a would occur from an operating end stage.

SEE rate estimation based on diffusion approximation of charge collection

NASA Astrophysics Data System (ADS)

Sogoyan, Armen V.; Chumakov, Alexander I.; Smolin, Anatoly A.

2018-03-01

The integral rectangular parallelepiped (IRPP) method remains the main approach to single event rate (SER) prediction for aerospace systems, despite the growing number of issues impairing method's validity when applied to scaled technology nodes. One of such issues is uncertainty in parameters extraction in the IRPP method, which can lead to a spread of several orders of magnitude in the subsequently calculated SER. The paper presents an alternative approach to SER estimation based on diffusion approximation of the charge collection by an IC element and geometrical interpretation of SEE cross-section. In contrast to the IRPP method, the proposed model includes only two parameters which are uniquely determined from the experimental data for normal incidence irradiation at an ion accelerator. This approach eliminates the necessity of arbitrary decisions during parameter extraction and, thus, greatly simplifies calculation procedure and increases the robustness of the forecast.

Fast kinetics of chromatin assembly revealed by single-molecule videomicroscopy and scanning force microscopy

PubMed Central

Ladoux, Benoit; Quivy, Jean-Pierre; Doyle, Patrick; Roure, Olivia du; Almouzni, Geneviève; Viovy, Jean-Louis

2000-01-01

Fluorescence videomicroscopy and scanning force microscopy were used to follow, in real time, chromatin assembly on individual DNA molecules immersed in cell-free systems competent for physiological chromatin assembly. Within a few seconds, molecules are already compacted into a form exhibiting strong similarities to native chromatin fibers. In these extracts, the compaction rate is more than 100 times faster than expected from standard biochemical assays. Our data provide definite information on the forces involved (a few piconewtons) and on the reaction path. DNA compaction as a function of time revealed unique features of the assembly reaction in these extracts. They imply a sequential process with at least three steps, involving DNA wrapping as the final event. An absolute and quantitative measure of the kinetic parameters of the early steps in chromatin assembly under physiological conditions could thus be obtained. PMID:11114182

Low- ν Flux and Total Charged-current Cross Sections in MINERvA

NASA Astrophysics Data System (ADS)

Ren, Lu

2014-03-01

The MINER νA experiment measures neutrino and antineutrino interaction cross sections on carbon and other nuclei. Cross section measurements require accurate knowledge of the incident neutrino flux. The ``low- ν'' flux technique uses a standard-candle cross section for events with low energy transfer to to the hadronic system to determine the incident flux. MINER νA will use low- ν fluxes for neutrinos and antineutrinos to tune production models used in beam simulations and to extract total cross sections as a function of energy. We present the low- ν flux technique adapted for the MINER νA data samples and preliminary results for the extracted low- ν fluxes in MINER νA. MINER νA will extend the range of antineutino charged-current cross section measurements to lower energies which are of interest to future accelerator oscillation experiments.

Autocatalytic microtubule nucleation determines the size and mass of Xenopus laevis egg extract spindles

PubMed Central

Decker, Franziska; Oriola, David; Dalton, Benjamin

2018-01-01

Regulation of size and growth is a fundamental problem in biology. A prominent example is the formation of the mitotic spindle, where protein concentration gradients around chromosomes are thought to regulate spindle growth by controlling microtubule nucleation. Previous evidence suggests that microtubules nucleate throughout the spindle structure. However, the mechanisms underlying microtubule nucleation and its spatial regulation are still unclear. Here, we developed an assay based on laser ablation to directly probe microtubule nucleation events in Xenopus laevis egg extracts. Combining this method with theory and quantitative microscopy, we show that the size of a spindle is controlled by autocatalytic growth of microtubules, driven by microtubule-stimulated microtubule nucleation. The autocatalytic activity of this nucleation system is spatially regulated by the limiting amounts of active microtubule nucleators, which decrease with distance from the chromosomes. This mechanism provides an upper limit to spindle size even when resources are not limiting. PMID:29323637

Evaluation of advanced air bag deployment algorithm performance using event data recorders.

PubMed

Gabler, Hampton C; Hinch, John

2008-10-01

This paper characterizes the field performance of occupant restraint systems designed with advanced air bag features including those specified in the US Federal Motor Vehicle Safety Standard (FMVSS) No. 208 for advanced air bags, through the use of Event Data Recorders (EDRs). Although advanced restraint systems have been extensively tested in the laboratory, we are only beginning to understand the performance of these systems in the field. Because EDRs record many of the inputs to the advanced air bag control module, these devices can provide unique insights into the characteristics of field performance of air bags. The study was based on 164 advanced air bag cases extracted from NASS/CDS 2002-2006 with associated EDR data. In this dataset, advanced driver air bags were observed to deploy with a 50% probability at a longitudinal delta-V of 9 mph for the first stage, and at 26 mph for both inflator stages. In general, advanced air bag performance was as expected, however, the study identified cases of air bag deployments at delta-Vs as low as 3-4 mph, non-deployments at delta-Vs over 26 mph, and possible delayed air bag deployments.

Evaluation of Advanced Air Bag Deployment Algorithm Performance using Event Data Recorders

PubMed Central

Gabler, Hampton C.; Hinch, John

2008-01-01

This paper characterizes the field performance of occupant restraint systems designed with advanced air bag features including those specified in the US Federal Motor Vehicle Safety Standard (FMVSS) No. 208 for advanced air bags, through the use of Event Data Recorders (EDRs). Although advanced restraint systems have been extensively tested in the laboratory, we are only beginning to understand the performance of these systems in the field. Because EDRs record many of the inputs to the advanced air bag control module, these devices can provide unique insights into the characteristics of field performance of air bags. The study was based on 164 advanced air bag cases extracted from NASS/CDS 2002-2006 with associated EDR data. In this dataset, advanced driver air bags were observed to deploy with a 50% probability at a longitudinal delta-V of 9 mph for the first stage, and at 26 mph for both inflator stages. In general, advanced air bag performance was as expected, however, the study identified cases of air bag deployments at delta-Vs as low as 3-4 mph, non-deployments at delta-Vs over 26 mph, and possible delayed air bag deployments. PMID:19026234

Precise discussion of time-reversal asymmetries in B-meson decays

DOE PAGES

Morozumi, Takuya; Okane, Hideaki; Umeeda, Hiroyuki

2015-02-26

BaBar collaboration announced that they observed time reversal (T) asymmetry through B meson system. In the experiment, time dependencies of two distinctive processes, B_ →B¯ 0 and B¯ 0 → B_ (– expresses CP value) are compared with each other. In our study, we examine event number difference of these two processes. In contrast to the BaBar asymmetry, the asymmetry of events number includes the overall normalization difference for rates. Time dependence of the asymmetry is more general and it includes terms absent in one used by BaBar collaboration. Both of the BaBar asymmetry and ours are naively thought tomore » be T-odd since two processes compared are related with flipping time direction. We investigate the time reversal transformation property of our asymmetry. Using our notation, one can see that the asymmetry is not precisely a T-odd quantity, taking into account indirect CP and CPT violation of K meson systems. The effect of ϵK is extracted and gives rise to O(10 –3) contribution. The introduced parameters are invariant under rephasing of quarks so that the coefficients of our asymmetry are expressed as phase convention independent quantities. Some combinations of the asymmetry enable us to extract parameters for wrong sign decays of B d meson, CPT violation, etc. As a result, we also study the reason why the T-even terms are allowed to contribute to the asymmetry, and find that several conditions are needed for the asymmetry to be a T-odd quantity.« less

Incidence and preventability of adverse events requiring intensive care admission: a systematic review.

PubMed

Vlayen, Annemie; Verelst, Sandra; Bekkering, Geertruida E; Schrooten, Ward; Hellings, Johan; Claes, Neree

2012-04-01

Adverse events are unintended patient injuries or complications that arise from health care management resulting in death, disability or prolonged hospital stay. Adverse events that require critical care are a considerable financial burden to the health care system, but also their global impact on patients and society is probably underestimated. The objectives of this systematic review were to synthesize the best available evidence regarding the estimates of the incidence and preventability of adverse events that necessitate intensive care admission, to determine the type and consequences [mortality, length of intensive care unit (ICU) stay and costs] of these adverse events. MEDLINE (from 1966 to present), EMBASE (from 1974 to present) and CENTRAL (version 1-2010) were searched for studies reporting on unplanned admissions on ICUs. Several other sources were searched for additional studies. Only quantitative studies that used chart review for the detection of adverse events requiring intensive care admission were considered for eligibility. For the purposes of this systematic review, ICUs were defined as specialized hospital facilities which provide continuous monitoring and intensive care for acutely ill patients. Studies that were published in the English, Dutch, German, French or Spanish language were eligible for inclusion. Two reviewers independently extracted data and assessed the methodological quality of the included studies. A total of 27 studies were reviewed. Meta-analysis of the data was not appropriate because of methodological and statistical heterogeneity between studies; therefore, results are presented in a descriptive way. The percentage of surgical and medical adverse events that required ICU admission ranged from 1.1% to 37.2%. ICU readmissions varied from 0% to 18.3%. Preventability of the adverse events varied from 17% to 76.5%. Preventable adverse events are further synthesized by type of event. Consequences of the adverse events included a mean length of ICU stay that ranged from 1.5 days to 10.4 days for the patient's first stay in ICU and mortality percentages between 0% and 58%. Adverse events are an important reason for (re)admission to the ICU and a considerable proportion of these are preventable. It was not possible to estimate an overall incidence and preventability rate of these events as we found considerable heterogeneity. To decrease adverse events that necessitate ICU admission, several systems are recommended such as early detection of patients with clinical instability on general wards and the implementation of rapid response teams. Step-down or intermediate care units could be a useful strategy for patients who require monitoring to avoid ICU readmissions. However, the effectiveness of such systems needs to be investigated. © 2011 Blackwell Publishing Ltd.

A Survey of Insider Attack Detection Research

DTIC Science & Technology

2008-08-25

modeling of statistical features , such as the frequency of events, the duration of events, the co-occurrence of multiple events combined through...forms of attack that have been reported [Error! Reference source not found.]. For example: • Unauthorized extraction , duplication, or exfiltration...network level. Schultz pointed out that not one approach will work but solutions need to be based on multiple sensors to be able to find any combination

Climate scenarios for the Truckee-Carson River system

USGS Publications Warehouse

Dettinger, Michael; Sterle, Kelley; Simpson, Karen; Singletary, Loretta; Fitzgerald, Kelsey; McCarthy, Maureen

2017-01-01

In this study, the scenarios ultimately take the form of gridded, daily (maximum and minimum) temperatures and precipitation totals spanning the entire Truckee-Carson River System, from which meteorological inputs to various hydrologic, water-balance and watermanagement models can be extracted by other parts of the Water for the Seasons project and by other studies and stakeholders. Climate scenarios are constructed using: 1) survey data from interviews with 66 Truckee-Carson River System water-management and water-interest organizations to identify plausible drought and high-flow events that could stress the system irreparably; 2) input from the Stakeholder Affiliate Group and other modelers on the Water for the Seasons team to gain additional key stakeholder input with regard to organizational survey results and to identify the most pressing water-management issues being faced in the system; and 3) historical climate datasets used to simulate possible future conditions.

A Semantic Web-based System for Mining Genetic Mutations in Cancer Clinical Trials.

PubMed

Priya, Sambhawa; Jiang, Guoqian; Dasari, Surendra; Zimmermann, Michael T; Wang, Chen; Heflin, Jeff; Chute, Christopher G

2015-01-01

Textual eligibility criteria in clinical trial protocols contain important information about potential clinically relevant pharmacogenomic events. Manual curation for harvesting this evidence is intractable as it is error prone and time consuming. In this paper, we develop and evaluate a Semantic Web-based system that captures and manages mutation evidences and related contextual information from cancer clinical trials. The system has 2 main components: an NLP-based annotator and a Semantic Web ontology-based annotation manager. We evaluated the performance of the annotator in terms of precision and recall. We demonstrated the usefulness of the system by conducting case studies in retrieving relevant clinical trials using a collection of mutations identified from TCGA Leukemia patients and Atlas of Genetics and Cytogenetics in Oncology and Haematology. In conclusion, our system using Semantic Web technologies provides an effective framework for extraction, annotation, standardization and management of genetic mutations in cancer clinical trials.

Effect of Some High Consumption Spices on Hemoglobin Glycation

PubMed Central

Naderi, G. H.; Dinani, Narges J.; Asgary, S.; Taher, M.; Nikkhoo, N.; Boshtam, M.

2014-01-01

Formation of glycation products is major factor responsible in complications of diabetes. Worldwide trend is toward the use of natural additives in reducing the complications of diseases. Therefore, there is a growing interest in natural antiglycation found in plants. Herbs and spices are one of the most important targets to search for natural antiglycation from the point of view of safety. This study investigated the ability of some of the spices to inhibit glycation process in a hemoglobin/glucose model system and compared their potency with each other. For this subject the best concentration and time to incubate glucose with hemoglobin was investigated. Then the glycosylation degree of hemoglobin in the presence of extracts by the three concentrations 0.25, 0.5 and 1 μg/ml was measured colorimetrically at 520 nm. Results represent that some of extracts such as wild caraway, turmeric, cardamom and black pepper have inhibitory effects on hemoglobin glycation. But some of the extracts such as anise and saffron have not only inhibitory effects but also aggravated this event and have proglycation properties. In accordance with the results obtained we can conclude that wild caraway, turmeric, cardamom and black pepper especially wild caraway extracts are potent antiglycation agents, which can be of great value in the preventive glycation-associated complications in diabetes. PMID:25593391

Effect of some high consumption spices on hemoglobin glycation.

PubMed

Naderi, G H; Dinani, Narges J; Asgary, S; Taher, M; Nikkhoo, N; Boshtam, M

2014-01-01

Formation of glycation products is major factor responsible in complications of diabetes. Worldwide trend is toward the use of natural additives in reducing the complications of diseases. Therefore, there is a growing interest in natural antiglycation found in plants. Herbs and spices are one of the most important targets to search for natural antiglycation from the point of view of safety. This study investigated the ability of some of the spices to inhibit glycation process in a hemoglobin/glucose model system and compared their potency with each other. For this subject the best concentration and time to incubate glucose with hemoglobin was investigated. Then the glycosylation degree of hemoglobin in the presence of extracts by the three concentrations 0.25, 0.5 and 1 μg/ml was measured colorimetrically at 520 nm. Results represent that some of extracts such as wild caraway, turmeric, cardamom and black pepper have inhibitory effects on hemoglobin glycation. But some of the extracts such as anise and saffron have not only inhibitory effects but also aggravated this event and have proglycation properties. In accordance with the results obtained we can conclude that wild caraway, turmeric, cardamom and black pepper especially wild caraway extracts are potent antiglycation agents, which can be of great value in the preventive glycation-associated complications in diabetes.

Gradient field of undersea sound speed structure extracted from the GNSS-A oceanography

NASA Astrophysics Data System (ADS)

Yokota, Yusuke; Ishikawa, Tadashi; Watanabe, Shun-ichi

2018-06-01

After the twenty-first century, the Global Navigation Satellite System-Acoustic ranging (GNSS-A) technique detected geodetic events such as co- and postseismic effects following the 2011 Tohoku-oki earthquake and slip-deficit rate distributions along the Nankai Trough subduction zone. Although these are extremely important discoveries in geodesy and seismology, more accurate observation that can capture temporal and spatial changes are required for future earthquake disaster prevention. In order to upgrade the accuracy of the GNSS-A technique, it is necessary to understand disturbances in undersea sound speed structures, which are major error sources. In particular, detailed temporal and spatial variations are difficult to observe accurately, and their effect was not sufficiently extracted in previous studies. In the present paper, we reconstruct an inversion scheme for extracting the effect from GNSS-A data and experimentally apply this scheme to the seafloor sites around the Kuroshio. The extracted gradient effects are believed to represent not only a broad sound speed structure but also a more detailed structure generated in the unsteady disturbance. The accuracy of the seafloor positioning was also improved by this new method. The obtained results demonstrate the feasibility of using the GNSS-A technique to detect a seafloor crustal deformation for oceanography research.

Extraction, quantification and characterization of uterine magnetomyographic activity--a proof of concept case study.

PubMed

Eswaran, Hari; Govindan, Rathinaswamy B; Furdea, Adrian; Murphy, Pam; Lowery, Curtis L; Preissl, Hubert T

2009-05-01

The objective was to extract, quantify and characterize the uterine magnetomyographic (MMG) signals that correspond to the electrophysiological activity of the uterus. Transabdominal MMG recordings with high spatial-temporal resolution were performed with the use of the 151 non-invasive magnetic sensor system. The extraction, quantification and characterization procedures were developed and applied to representative MMG signals that were recorded from a pregnant woman at regular intervals starting at 37 weeks of gestation until the subject reached active labor. Multiple MMG recordings were successfully performed on the subject before she went into active labor. The extracted MMG burst activity showed a statistically significant correlation (r=0.2; p<0.001) with the contractile events perceived by mothers. The time-frequency analysis of the burst activity showed a power shift towards higher-frequency at 48 h before the subject went into active labor as compared to earlier recordings. Further there was a gradual increase in the synchrony in the higher-frequency band as the subject reached close to active labor. The non-invasive recording of the magnetic signals of pregnant uterus with high spatial-temporal resolution can provide an insight into the preparatory phase of labor and has the potential of predicting term and preterm labor.

Learning temporal rules to forecast instability in continuously monitored patients

PubMed Central

Dubrawski, Artur; Wang, Donghan; Hravnak, Marilyn; Clermont, Gilles; Pinsky, Michael R

2017-01-01

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may improve adoption and use of data-driven decision support systems clinically via face validity. In this work, we explore whether we can reliably and informatively forecast cardiorespiratory instability (CRI) in step-down unit (SDU) patients utilizing data from continuous monitoring of physiologic vital sign (VS) measurements. We use a temporal association rule extraction technique in conjunction with a rule fusion protocol to learn how to forecast CRI in continuously monitored patients. We detail our approach and present and discuss encouraging empirical results obtained using continuous multivariate VS data from the bedside monitors of 297 SDU patients spanning 29 346 hours (3.35 patient-years) of observation. We present example rules that have been learned from data to illustrate potential benefits of comprehensibility of the extracted models, and we analyze the empirical utility of each VS as a potential leading indicator of an impending CRI event. PMID:27274020

Extracting Value from Ensembles for Cloud-Free Forecasting

DTIC Science & Technology

2011-09-01

event. It should follow that the decision maker also prefers the movie over the sporting event. 3) If the movie ticket comes with popcorn , neither...the popcorn nor the movie ticket can be valued more than the movie ticket and popcorn together, assuming there are no other economic factors to

Cueing Animations: Dynamic Signaling Aids Information Extraction and Comprehension

ERIC Educational Resources Information Center

Boucheix, Jean-Michel; Lowe, Richard K.; Putri, Dian K.; Groff, Jonathan

2013-01-01

The effectiveness of animations containing two novel forms of animation cueing that target relations between event units rather than individual entities was compared with that of animations containing conventional entity-based cueing or no cues. These relational event unit cues ("progressive path" and "local coordinated" cues) were specifically…

A new approach to generating research-quality phenology data: The USA National Phenology Monitoring System

NASA Astrophysics Data System (ADS)

Denny, Ellen; Miller-Rushing, Abraham; Haggerty, Brian; Wilson, Bruce; Weltzin, Jake

2010-05-01

The USA National Phenology Network (www.usanpn.org) has recently initiated a national effort to encourage people at different levels of expertise—from backyard naturalists to professional scientists—to observe phenological events and contribute to a national database that will be used to greatly improve our understanding of spatio-temporal variation in phenology and associated phenological responses to climate change. Traditional phenological observation protocols identify specific single dates at which individual phenological events are observed, but the scientific usefulness of long-term phenological observations can be improved with a more carefully structured protocol. At the USA-NPN we have developed a new approach that directs observers to record each day that they observe an individual plant, and to assess and report the state of specific life stages (or phenophases) as occurring or not occurring on that plant for each observation date. Evaluation is phrased in terms of simple, easy-to-understand, questions (e.g. "Do you see open flowers?"), which makes it very appropriate for a broad audience. From this method, a rich dataset of phenological metrics can be extracted, including the duration of a phenophase (e.g. open flowers), the beginning and end points of a phenophase (e.g. traditional phenological events such as first flower and last flower), multiple distinct occurrences of phenophases within a single growing season (e.g multiple flowering events, common in drought-prone regions), as well as quantification of sampling frequency and observational uncertainties. The system also includes a mechanism for translation of phenophase start and end points into standard traditional phenological events to facilitate comparison of contemporary data collected with this new "phenophase status" monitoring approach to historical datasets collected with the "phenological event" monitoring approach. These features greatly enhance the utility of the resulting data for statistical analyses addressing questions such as how phenological events vary in time and space, and in response to global change.

Initial development of the Systems Approach to Home Medication Management (SAHMM) model.

PubMed

Doucette, William R; Vinel, Shanrae'l; Pennathur, Priyadarshini

Adverse drug events and medication nonadherence are two problems associated with prescription medication use for chronic conditions. These issues often develop because patients have difficulty managing their medications at home. To guide patients and providers for achieving safe and effective medication use at home, the Systems Approach to Home Medication Management (SAHMM) model was derived from a systems engineering model for health care workplace safety. To explore how well concepts from the SAHMM model can represent home medication management by using patient descriptions of how they take prescription medications at home. Twelve patients were interviewed about home medication management using an interview guide based on the factors of the SAHMM model. Each interview was audio-taped and then transcribed verbatim. Interviews were coded to identify themes for home medication management using MAXQDA for Windows. SAHMM concepts extracted from the coded interview transcripts included work system components of person, tasks, tools & technology, internal environment, external environment, and household. Concepts also addressed work processes and work outcomes for home medication management. Using the SAHMM model for studying patients' home medication management is a promising approach to improving our understanding of the factors that influence patient adherence to medication and the development of adverse drug events. Copyright © 2016 Elsevier Inc. All rights reserved.

Reconstructing the flight kinematics of swarming and mating in wild mosquitoes

PubMed Central

Butail, Sachit; Manoukis, Nicholas; Diallo, Moussa; Ribeiro, José M.; Lehmann, Tovi; Paley, Derek A.

2012-01-01

We describe a novel tracking system for reconstructing three-dimensional tracks of individual mosquitoes in wild swarms and present the results of validating the system by filming swarms and mating events of the malaria mosquito Anopheles gambiae in Mali. The tracking system is designed to address noisy, low frame-rate (25 frames per second) video streams from a stereo camera system. Because flying A. gambiae move at 1–4 m s−1, they appear as faded streaks in the images or sometimes do not appear at all. We provide an adaptive algorithm to search for missing streaks and a likelihood function that uses streak endpoints to extract velocity information. A modified multi-hypothesis tracker probabilistically addresses occlusions and a particle filter estimates the trajectories. The output of the tracking algorithm is a set of track segments with an average length of 0.6–1 s. The segments are verified and combined under human supervision to create individual tracks up to the duration of the video (90 s). We evaluate tracking performance using an established metric for multi-target tracking and validate the accuracy using independent stereo measurements of a single swarm. Three-dimensional reconstructions of A. gambiae swarming and mating events are presented. PMID:22628212

Time difference of arrival to blast localization of potential chemical/biological event on the move

NASA Astrophysics Data System (ADS)

Morcos, Amir; Desai, Sachi; Peltzer, Brian; Hohil, Myron E.

2007-10-01

Integrating a sensor suite with ability to discriminate potential Chemical/Biological (CB) events from high-explosive (HE) events employing a standalone acoustic sensor with a Time Difference of Arrival (TDOA) algorithm we developed a cueing mechanism for more power intensive and range limited sensing techniques. Enabling the event detection algorithm to locate to a blast event using TDOA we then provide further information of the event as either Launch/Impact and if CB/HE. The added information is provided to a range limited chemical sensing system that exploits spectroscopy to determine the contents of the chemical event. The main innovation within this sensor suite is the system will provide this information on the move while the chemical sensor will have adequate time to determine the contents of the event from a safe stand-off distance. The CB/HE discrimination algorithm exploits acoustic sensors to provide early detection and identification of CB attacks. Distinct characteristics arise within the different airburst signatures because HE warheads emphasize concussive and shrapnel effects, while CB warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. Differences characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. The discrete wavelet transform (DWT) is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 3km. Highly reliable discrimination is achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition. The development of an adaptive noise floor to provide early event detection assists in minimizing the false alarm rate and increasing the confidence whether the event is blast event or back ground noise. The integration of these algorithms with the TDOA algorithm provides a complex suite of algorithms that can give early warning detection and highly reliable look direction from a great stand-off distance for a moving vehicle to determine if a candidate blast event is CB and if CB what is the composition of the resulting cloud.

Ontology-Based Combinatorial Comparative Analysis of Adverse Events Associated with Killed and Live Influenza Vaccines

PubMed Central

Sarntivijai, Sirarat; Xiang, Zuoshuang; Shedden, Kerby A.; Markel, Howard; Omenn, Gilbert S.; Athey, Brian D.; He, Yongqun

2012-01-01

Vaccine adverse events (VAEs) are adverse bodily changes occurring after vaccination. Understanding the adverse event (AE) profiles is a crucial step to identify serious AEs. Two different types of seasonal influenza vaccines have been used on the market: trivalent (killed) inactivated influenza vaccine (TIV) and trivalent live attenuated influenza vaccine (LAIV). Different adverse event profiles induced by these two groups of seasonal influenza vaccines were studied based on the data drawn from the CDC Vaccine Adverse Event Report System (VAERS). Extracted from VAERS were 37,621 AE reports for four TIVs (Afluria, Fluarix, Fluvirin, and Fluzone) and 3,707 AE reports for the only LAIV (FluMist). The AE report data were analyzed by a novel combinatorial, ontology-based detection of AE method (CODAE). CODAE detects AEs using Proportional Reporting Ratio (PRR), Chi-square significance test, and base level filtration, and groups identified AEs by ontology-based hierarchical classification. In total, 48 TIV-enriched and 68 LAIV-enriched AEs were identified (PRR>2, Chi-square score >4, and the number of cases >0.2% of total reports). These AE terms were classified using the Ontology of Adverse Events (OAE), MedDRA, and SNOMED-CT. The OAE method provided better classification results than the two other methods. Thirteen out of 48 TIV-enriched AEs were related to neurological and muscular processing such as paralysis, movement disorders, and muscular weakness. In contrast, 15 out of 68 LAIV-enriched AEs were associated with inflammatory response and respiratory system disorders. There were evidences of two severe adverse events (Guillain-Barre Syndrome and paralysis) present in TIV. Although these severe adverse events were at low incidence rate, they were found to be more significantly enriched in TIV-vaccinated patients than LAIV-vaccinated patients. Therefore, our novel combinatorial bioinformatics analysis discovered that LAIV had lower chance of inducing these two severe adverse events than TIV. In addition, our meta-analysis found that all previously reported positive correlation between GBS and influenza vaccine immunization were based on trivalent influenza vaccines instead of monovalent influenza vaccines. PMID:23209624

Utilizing Intrinsic Properties of Polyaniline to Detect Nucleic Acid Hybridization through UV-Enhanced Electrostatic Interaction.

PubMed

Sengupta, Partha Pratim; Gloria, Jared N; Amato, Dahlia N; Amato, Douglas V; Patton, Derek L; Murali, Beddhu; Flynt, Alex S

2015-10-12

Detection of specific RNA or DNA molecules by hybridization to "probe" nucleic acids via complementary base-pairing is a powerful method for analysis of biological systems. Here we describe a strategy for transducing hybridization events through modulating intrinsic properties of the electroconductive polymer polyaniline (PANI). When DNA-based probes electrostatically interact with PANI, its fluorescence properties are increased, a phenomenon that can be enhanced by UV irradiation. Hybridization of target nucleic acids results in dissociation of probes causing PANI fluorescence to return to basal levels. By monitoring restoration of base PANI fluorescence as little as 10(-11) M (10 pM) of target oligonucleotides could be detected within 15 min of hybridization. Detection of complementary oligos was specific, with introduction of a single mismatch failing to form a target-probe duplex that would dissociate from PANI. Furthermore, this approach is robust and is capable of detecting specific RNAs in extracts from animals. This sensor system improves on previously reported strategies by transducing highly specific probe dissociation events through intrinsic properties of a conducting polymer without the need for additional labels.

Improved Microseismicity Detection During Newberry EGS Stimulations

DOE Data Explorer

Templeton, Dennise

2013-10-01

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.

Improved Microseismicity Detection During Newberry EGS Stimulations

DOE Data Explorer

Templeton, Dennise

2013-11-01

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.

Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

2015-12-01

A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Extreme temperature indices analyses: A case study of five meteorological stations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Hasan, Husna; Salleh, Nur Hanim Mohd

2015-10-01

Extreme temperature events affect many human and natural systems. Changes in extreme temperature events can be detected and monitored by developing the indices based on the extreme temperature data. As an effort to provide the understanding of these changes to the public, a study of extreme temperature indices is conducted at five meteorological stations in Peninsular Malaysia. In this study, changes in the means and extreme events of temperature are assessed and compared using the daily maximum and minimum temperature data for the period of 2004 to 2013. The absolute extreme temperature indices; TXx, TXn, TXn and TNn provided by Expert Team on Climate Change Detection and Indices (ETCCDI) are utilized and linear trends of each index are extracted using least square likelihood method. The results indicate that there exist significant decreasing trend in the TXx index for Kota Bharu station and increasing trend in TNn index for Chuping and Kota Kinabalu stations. The comparison between the trend in mean and extreme temperatures show the same significant tendency for Kota Bharu and Kuala Terengganu stations.

Combining spiral and target wave detection to analyze excitable media dynamics

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2010-01-01

Excitable media dynamics is the lossless active transmission of waves of excitation over a field of coupled elements, such as electrical excitation in heart tissue or nerve fibers, cAMP signaling in the slime mold Dictyostelium discoideum or waves of chemical activity in the Belousov-Zhabotinsky reaction. All these systems follow essentially the same generic dynamics, including undamped wave transmission and the self-organized emergence of circular target and self-sustaining spiral waves. We combine spiral recognition, using the established phase singularity technique, and a novel three-dimensional fitting algorithm for noise-resistant target wave recognition to extract all important events responsible for the layout of the asymptotic large-scale pattern. Space-time plots of these combined events reveal signatures of events leading to spiral formation, illuminating the microscopic mechanisms at work. This strategy can be applied to arbitrary excitable media data from either models or experiments, giving insight into for example the microscopic causes for formation of pathological spiral waves in heart tissue, which could lead to novel techniques for diagnosis, risk evaluation and treatment.

FamPlex: a resource for entity recognition and relationship resolution of human protein families and complexes in biomedical text mining.

PubMed

Bachman, John A; Gyori, Benjamin M; Sorger, Peter K

2018-06-28

For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers, a process known as named entity linking or "grounding." Correct grounding is essential for resolving relationships among mined information, curated interaction databases, and biological datasets. The accuracy of this process is largely dependent on the availability of machine-readable resources associating synonyms and abbreviations commonly found in biomedical literature with uniform identifiers. In a task involving automated reading of ∼215,000 articles using the REACH event extraction software we found that grounding was disproportionately inaccurate for multi-protein families (e.g., "AKT") and complexes with multiple subunits (e.g."NF- κB"). To address this problem we constructed FamPlex, a manually curated resource defining protein families and complexes as they are commonly encountered in biomedical text. In FamPlex the gene-level constituents of families and complexes are defined in a flexible format allowing for multi-level, hierarchical membership. To create FamPlex, text strings corresponding to entities were identified empirically from literature and linked manually to uniform identifiers; these identifiers were also mapped to equivalent entries in multiple related databases. FamPlex also includes curated prefix and suffix patterns that improve named entity recognition and event extraction. Evaluation of REACH extractions on a test corpus of ∼54,000 articles showed that FamPlex significantly increased grounding accuracy for families and complexes (from 15 to 71%). The hierarchical organization of entities in FamPlex also made it possible to integrate otherwise unconnected mechanistic information across families, subfamilies, and individual proteins. Applications of FamPlex to the TRIPS/DRUM reading system and the Biocreative VI Bioentity Normalization Task dataset demonstrated the utility of FamPlex in other settings. FamPlex is an effective resource for improving named entity recognition, grounding, and relationship resolution in automated reading of biomedical text. The content in FamPlex is available in both tabular and Open Biomedical Ontology formats at https://github.com/sorgerlab/famplex under the Creative Commons CC0 license and has been integrated into the TRIPS/DRUM and REACH reading systems.

Efficacy and safety of Vitex agnus-castus extract for treatment of premenstrual syndrome in Japanese patients: a prospective, open-label study.

PubMed

Momoeda, Mikio; Sasaki, Hidetaka; Tagashira, Eiko; Ogishima, Masayuki; Takano, Yuichi; Ochiai, Kazunori

2014-03-01

Herbal medicine containing Vitex agnus-castus (VAC) extract is widely used by women with premenstrual syndrome (PMS) in Europe, however, in Japan, clinical evidence remains to be determined. This study attempted to investigate the efficacy and safety profiles of VAC extract in Japanese patients with PMS. A multi-center, prospective, open-label, single-arm, phase 3 study was performed in Japanese women with PMS and aged 18-44 years. The patients received Prefemin® (Max Zeller Söhne AG, Romanshorn, Switzerland), containing 20 mg of VAC extract, once daily for three menstrual cycles. The efficacy profile was examined based on the intensity of ten PMS symptoms-irritability, depressed mood, anger, headache, bloating, breast fullness, skin disorder, fatigue, drowsiness, and sleeplessness-recorded by patients via a visual analog scale (VAS). In addition, the responder rate was calculated based on the total VAS score defined by the sum of the VAS scores of the first six symptoms mentioned above. Furthermore, physician's global assessment (PGA) scores were recorded. Adverse events including vital signs and laboratory test values were monitored as safety evaluation. Sixty-nine patients received Prefemin®. After the first menstrual cycle, a statistically significant decrease in total VAS score was observed (P<0.001), and the score continued to diminish for the following two cycles. Each of the ten symptom scores decreased significantly in this manner. In addition, the responder rate increased in a time-dependent manner; the rate at the third menstrual cycle was 91.0%, and almost all of the patients were without symptoms or exhibited only mild symptoms based on PGA. Eight patients exhibited non-serious adverse events, one of which was allergic dermatitis whose causal relationship with VAC was not ruled out. VAC extract improved PMS symptoms in Japanese patients, with no substantial adverse events. This is the first study to report the effect of VAC extract in Japanese patients.

Measurement of the mass of the top quark in decays with a J/ ψ meson in pp collisions at 8 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Nuttens, C.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; El-khateeb, E.; Elgammal, S.; Mohamed, A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Peltola, T.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Lomidze, D.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kieseler, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Seitz, C.; Spannagel, S.; Stefaniuk, N.; Trippkewitz, K. D.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Barth, C.; Baus, C.; Berger, J.; Butz, E.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Bahinipati, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhowmik, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Rane, A.; Sharma, S.; Behnamian, H.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Chiorboli, M.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Biasotto, M.; Bisello, D.; Boletti, A.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Fanzago, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Ventura, S.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; SavoyNavarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; La Licata, C.; Schizzi, A.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. 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A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Gavrilenko, M.; Golunov, A.; Golutvin, I.; Gorbounov, N.; Kamenev, A.; Karjavin, V.; Korenkov, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Mitsyn, V. V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Skatchkov, N.; Smirnov, V.; Tikhonenko, E.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Chadeeva, M.; Markin, O.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Rusakov, S. V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Korneeva, N.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; Blinov, V.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras De Saa, J. R.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Hammer, J.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Kousouris, K.; Krammer, M.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Wardle, N.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Yang, Y.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Tzeng, Y. M.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; Hauser, J.; Ignatenko, M.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mccoll, N.; Mullin, S. D.; Ovcharova, A.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Apresyan, A.; Bendavid, J.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Azzolini, V.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Bruner, C.; Castle, J.; Forthomme, L.; Kenny, R. P.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Malta Rodrigues, A.; Meier, F.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Baumgartel, D.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Kumar, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2016-12-01

A first measurement of the top quark mass in the decay channel t → (W → ℓν) (b → J/ ψ + X → μ + μ - + X) is presented. The analysis uses events selected from the proton-proton collisions recorded by the CMS detector at the LHC at a center-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 fb-1, with 666 toverline{t} and single top quark candidate events containing a reconstructed J/ ψ candidate decaying into an oppositely-charged muon pair. The mass of the (J/ ψ + ℓ) system, where ℓ is an electron or a muon from W boson decay, is used to extract a top quark mass of 173.5 ± 3.0 (stat) ± 0.9 (syst) GeV. [Figure not available: see fulltext.

Liver injury with novel oral anticoagulants: assessing post-marketing reports in the US Food and Drug Administration adverse event reporting system.

PubMed

Raschi, Emanuel; Poluzzi, Elisabetta; Koci, Ariola; Salvo, Francesco; Pariente, Antoine; Biselli, Maurizio; Moretti, Ugo; Moore, Nicholas; De Ponti, Fabrizio

2015-08-01

We assessed the hepatic safety of novel oral anticoagulants (NOACs) analyzing the publicly available US-FDA adverse event reporting system (FAERS). We extracted reports of drug-induced liver injury (DILI) associated with NOACs, including acute liver failure (ALF) events. Based on US marketing authorizations, we performed disproportionality analyses, calculating reporting odds ratios (RORs) with 95% confidence interval (CI), also to test for event- and drug-related competition bias, and case-by-case evaluation for concomitant medications. DILI reports represented 3.7% (n = 146) and 1.7% (n = 222) of all reports for rivaroxaban and dabigatran, respectively. No statistically significant association was found for dabigatran, in primary and secondary analyses. Disproportionality signals emerged for rivaroxaban in primary analysis (ALF: n = 25, ROR = 2.08, 95% CI 1.34, 3.08). In a large proportion of DILI reports concomitant hepatotoxic and/or interacting drugs were recorded: 42% and 37% (rivaroxaban and dabigatran, respectively), especially statins, paracetamol and amiodarone. Among ALF reports, fatal outcome occurred in 49% of cases (44% and 51%, rivaroxaban and dabigatran, respectively), whereas rapid onset of the event (<1 week) was detected in 46% of patients (47% and 44%, respectively). The disproportionality signal for rivaroxaban calls for further comparative population-based studies to characterize and quantify the actual DILI risk of NOACs, taking into account drug- and patient-related risk factors. As DILI is unpredictable, our findings strengthen the role of (a) timely pharmacovigilance to detect post-marketing signals of DILI through FAERS and other data sources, (b) clinicians to assess early, on a case-by-case basis, the potential responsibility of NOACs when they diagnose a liver injury. © 2015 The British Pharmacological Society.

SEP Time-to-Maximum (TTM) Studies and the Ionic Charge States of Solar Heavy Ions

NASA Technical Reports Server (NTRS)

Tylka, Allan J.; Dietrich, William F.

2004-01-01

1. We published a report on the TTM method and presented the results at the 28 International Cosmic Ray Conference. Included in this paper were our results on the energy-dependent charge state of Fe in the 200 1 April 15 ground- level event, the largest of Cycle 23. We showed that our results agreed well with direct measurements from SAMPEX in this event. We also presented results for the 2001 April 14 event, one of the largest impulsive events of Cycle 23. 2. We extracted TTM values for protons and ions of various energies in approx. 50 SEP events in Cycle 23, using time profiles measured by ACE, Wind, GOES, IMPS, SOHO, and SAMPEX. This event sample included many large gradual events, as well as several impulsive events. The TTM analyses typically yielded approx. 300 datapoints per event. 3. We used these data to make preliminary event classifications according to: (a) shapes of the rigidity and/or speed dependence of TTMs in each event; (b) behavior of proton TTMs compared to that of heavier ions; and (c) the behavior of Fe TTMs compared to that of lighter Z greater than I ions. 4. We cross-checked proton fluence and TTM values from 8 instruments on 6 satellites, so as to understand the origin of systematic instrument-to-instrument discrepancies. By also comparing the observed proton spectra, it was possible to extract correction factors to the nominal proton energy bins that removed or greatly reduced the instrument-to-instrument spread among proton TTMs. 5. We began comparisons of proton and He-4 TTM values in some particularly well measured, large SEP events measured by IMP8 in Cycles 21 and 22 when the instruments onboard were functioning better. It is hoped that these data will provide a better understanding of event-to-event variation in the functional dependence of TTMs on velocity and rigidity.

Deaths and cardiovascular injuries due to device-assisted implantable cardioverter–defibrillator and pacemaker lead extraction

PubMed Central

Hauser, Robert G.; Katsiyiannis, William T.; Gornick, Charles C.; Almquist, Adrian K.; Kallinen, Linda M.

2010-01-01

Aims An estimated 10 000–15 000 pacemaker and implantable cardioverter–defibrillator (ICD) leads are extracted annually worldwide using specialized tools that disrupt encapsulating fibrous tissue. Additional information is needed regarding the safety of the devices that have been approved for lead extraction. The aim of this study was to determine whether complications due to device-assisted lead extraction might be more hazardous than published data suggest, and whether procedural safety precautions are effective. Methods and results We searched the US Food and Drug Administration's (FDA) Manufacturers and User Defined Experience (MAUDE) database from 1995 to 2008 using the search terms ‘lead extraction and death’ and ‘lead extraction and injury’. Additional product specific searches were performed for the terms ‘death’ and ‘injury’. Between 1995 and 2008, 57 deaths and 48 serious cardiovascular injuries associated with device-assisted lead extraction were reported to the FDA. Owing to underreporting, the FDA database does not contain all adverse events that occurred during this period. Of the 105 events, 27 deaths and 13 injuries occurred in 2007–2008. During these 2 years, 23 deaths were linked with excimer laser or mechanical dilator sheath extractions. The majority of deaths and injuries involved ICD leads, and most were caused by lacerations of the right atrium, superior vena cava, or innominate vein. Overall, 62 patients underwent emergency surgical repair of myocardial perforations and venous lacerations and 35 (56%) survived. Conclusion These findings suggest that device-assisted lead extraction is a high-risk procedure and that serious complications including death may not be mitigated by emergency surgery. However, skilled standby cardiothoracic surgery is essential when performing pacemaker and ICD lead extractions. Although the incidence of these complications is unknown, the results of our study imply that device-assisted lead extractions should be performed by highly qualified physicians and their teams in specialized centres. PMID:19946113

Comparison of transdermal diclofenac patch with oral diclofenac as an analgesic modality following multiple premolar extractions in orthodontic patients: A cross over efficacy trial

PubMed Central

Bhaskar, Hemant; Kapoor, Pranav; Ragini

2010-01-01

Aims: This study was performed to compare the degree of post operative analgesia, patient compliance, and frequency of adverse events with the use of oral diclofenac tablets and transdermal diclofenac patch following multiple premolar extractions in patients undergoing orthodontic treatment. Materials and Methods: Twenty young pre-orthodontic patients requiring bilateral maxillary and mandibular first premolar extractions were selected for the study. The right maxillary and mandibular first premolars were extracted first and 50 mg oral diclofenac sodium tablets were prescribed to be taken thrice a day for three days. In the next appointment, the contralateral first premolars were extracted and a 100 mg transdermal diclofenac patch was applied once a day for three days. Pain relief and pain intensity with both the diclofenac formulations was recorded for each of the three postoperative days using 5-point Verbal Pain Intensity and Pain Relief Score Charts. Results and Conclusions: Statistical analyses revealed that there was a gradual increase in pain relief scores and a gradual decrease in pain intensity scores with the use of oral diclofenac tablets as well as with the transdermal patch. However, subjects reported that they were more comfortable using the transdermal patch particularly due to the once-a-day application and lesser frequency of systemic adverse effects. Results of this study indicate that the transdermal diclofenac patch provides as potent analgesia as the oral diclofenac tablets with the added advantage of better patient compliance and may be used for routine post extraction analgesia. PMID:22114407

The Water Level Fall of Lake Megali Prespa (N Greece): an Indicator of Regional Water Stress Driven by Climate Change and Amplified by Water Extraction?

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Giannakopoulos, Christos

2014-05-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change, with future projections predicting an increase in excessive drought events and declining rainfall. Regional freshwater ecosystems are particularly threatened: precipitation decreases, while extreme droughts increase and human impacts intensify (e.g. water extraction, drainage, pollution and dam-building). Many Mediterranean lake-wetland systems have shrunk or disappeared over the past two decades. Protecting the remaining systems is extremely important for supporting global biodiversity and for ensuring sustainable water availability. This protection should be based on a clear understanding of lake-wetland hydrological responses to natural and human-induced changes, which is currently lacking in many parts of the Mediterranean. The interconnected Prespa-Ohrid Lake system is a global hotspot of biodiversity and endemism. The unprecedented fall in water level (~8m) of Lake Megali Prespa threatens this system, but causes remain debated. Modelling suggests that the S Balkan will experience rainfall and runoff decreases of ~30% by 2050. However, projections revealing the potential impact of these changes on future lake level are unavailable as lake regime is not understood. A further drop in lake level may have serious consequences. The Prespa Lakes contribute ~25% of the total inflow into Lake Ohrid through underground karst channels; falling lake levels decrease this discharge. Lake Ohrid, in turn, feeds the Drim River. This entire catchment may therefore be affected by falling lake levels; its water resources are of great importance for Greece, Albania, FYROM and Montenegro (e.g. tourism, agriculture, hydro-energy, urban & industrial use). This new work proves that annual water level fluctuations of Lake Megali Prespa are predominantly related to precipitation during the first 7 months (Oct-Apr) of the hydrological year (Oct-Sep). Lake level is very sensitive to regional and Mediterranean wet-dry events during this period. There are robust indications for a link between lake level and the North Atlantic Oscillation, which is known to strongly influence Mediterranean winter precipitation. Hydro-climatic records show a complicated picture, but tentatively support the conclusion that the unprecedented lake level fall is principally related to climate change. The available fluvial discharge record and most existing snowfall records show statistically significant decreases in annual averages. Annual rainfall only shows a statistically significant decrease of the 25th percentile; 7-month rainfall (Oct-Apr) additionally shows a statistically significant but non-robust decrease of the mean. The modest amount of water extraction (annually: ~14*103m3, ~0.004% of total lake volume) exerts a progressive and significant impact on lake level over the longer term, accounting for ~25% of the observed fall. Lake level lowering ends when lake-surface area shrinkage has led to a decrease in lake-surface evaporation that is equivalent to the amount of water extracted. The adjustment of lake level to stable extraction rates requires two to three decades. This work aims to steer adaptation and mitigation strategies by informing on lake response under different climate change and extraction scenarios. Lake protection is a cost effective solution for supporting global biodiversity and for providing sustainable water resources.

Temporal integration: intentional sound discrimination does not modulate stimulus-driven processes in auditory event synthesis.

PubMed

Sussman, Elyse; Winkler, István; Kreuzer, Judith; Saher, Marieke; Näätänen, Risto; Ritter, Walter

2002-12-01

Our previous study showed that the auditory context could influence whether two successive acoustic changes occurring within the temporal integration window (approximately 200ms) were pre-attentively encoded as a single auditory event or as two discrete events (Cogn Brain Res 12 (2001) 431). The aim of the current study was to assess whether top-down processes could influence the stimulus-driven processes in determining what constitutes an auditory event. Electroencepholagram (EEG) was recorded from 11 scalp electrodes to frequently occurring standard and infrequently occurring deviant sounds. Within the stimulus blocks, deviants either occurred only in pairs (successive feature changes) or both singly and in pairs. Event-related potential indices of change and target detection, the mismatch negativity (MMN) and the N2b component, respectively, were compared with the simultaneously measured performance in discriminating the deviants. Even though subjects could voluntarily distinguish the two successive auditory feature changes from each other, which was also indicated by the elicitation of the N2b target-detection response, top-down processes did not modify the event organization reflected by the MMN response. Top-down processes can extract elemental auditory information from a single integrated acoustic event, but the extraction occurs at a later processing stage than the one whose outcome is indexed by MMN. Initial processes of auditory event-formation are fully governed by the context within which the sounds occur. Perception of the deviants as two separate sound events (the top-down effects) did not change the initial neural representation of the same deviants as one event (indexed by the MMN), without a corresponding change in the stimulus-driven sound organization.

Large-Scale Event Extraction from Literature with Multi-Level Gene Normalization

PubMed Central

Wei, Chih-Hsuan; Hakala, Kai; Pyysalo, Sampo; Ananiadou, Sophia; Kao, Hung-Yu; Lu, Zhiyong; Salakoski, Tapio; Van de Peer, Yves; Ginter, Filip

2013-01-01

Text mining for the life sciences aims to aid database curation, knowledge summarization and information retrieval through the automated processing of biomedical texts. To provide comprehensive coverage and enable full integration with existing biomolecular database records, it is crucial that text mining tools scale up to millions of articles and that their analyses can be unambiguously linked to information recorded in resources such as UniProt, KEGG, BioGRID and NCBI databases. In this study, we investigate how fully automated text mining of complex biomolecular events can be augmented with a normalization strategy that identifies biological concepts in text, mapping them to identifiers at varying levels of granularity, ranging from canonicalized symbols to unique gene and proteins and broad gene families. To this end, we have combined two state-of-the-art text mining components, previously evaluated on two community-wide challenges, and have extended and improved upon these methods by exploiting their complementary nature. Using these systems, we perform normalization and event extraction to create a large-scale resource that is publicly available, unique in semantic scope, and covers all 21.9 million PubMed abstracts and 460 thousand PubMed Central open access full-text articles. This dataset contains 40 million biomolecular events involving 76 million gene/protein mentions, linked to 122 thousand distinct genes from 5032 species across the full taxonomic tree. Detailed evaluations and analyses reveal promising results for application of this data in database and pathway curation efforts. The main software components used in this study are released under an open-source license. Further, the resulting dataset is freely accessible through a novel API, providing programmatic and customized access (http://www.evexdb.org/api/v001/). Finally, to allow for large-scale bioinformatic analyses, the entire resource is available for bulk download from http://evexdb.org/download/, under the Creative Commons – Attribution – Share Alike (CC BY-SA) license. PMID:23613707

Lunar laser ranging data identification and management

NASA Technical Reports Server (NTRS)

1979-01-01

Activity under the subject grant during the first half of fiscal year 1979 at the University of Texas at Austin is reported. Raw lunar laser ranging data submitted by McDonald Observatory, Fort Davis, Texas and by the Australian Division of National Mapping at Orroral Valley, Australia were processed. This processing includes the filtering of signal events from noise photons, normal point formation, data archive management, and data distribution. System-wide program maintenance and up-grade carried out wherever and whenever necessary. Lunar laser ranging data is being transmitted from Austin to Paris for the extraction of earth rotation information during the EROLD campaign.

A summary and integration of research concerning single pilot IFR operational problems

NASA Technical Reports Server (NTRS)

Chapman, G. C.

1983-01-01

A review of seven research studies pertaining to Single Pilot IFR (SPIFR) operations was performed. Two studies were based on questionnaire surveys; two based on National Transportation Safety Board (NTSB) reports; two were based on Aviation Safety Reporting System (ASRS) incident reports, and one report used event analysis and statistics to forecast problems. The results obtained in each study were extracted and integrated. Results were synthesized and key issues pertaining to SPIFR operations problems were identified. The research that was recommended by the studies and that addressed the key issues is catalogued for each key issue.

N-linked glycoprotein analysis using dual-extraction ultrahigh-performance liquid chromatography and electrospray tandem mass spectrometry.

PubMed

Siu, S O; Lam, Maggie P Y; Lau, Edward; Yeung, William S B; Cox, David M; Chu, Ivan K

2010-01-01

Although reverse-phase liquid chromatography (RP-LC) is a common technique for peptide separation in shotgun proteomics and glycoproteomics, it often provides unsatisfactory results for the analysis of glycopeptides and glycans. This bias against glycopeptides makes it difficult to study glycoproteins. By coupling mass spectrometry (MS) with a combination of RP-LC and normal-phase (NP)-LC as an integrated front-end separation system, we demonstrate that effective identification and characterization of both peptides and glycopeptides mixtures, and their constituent glycan structures, can be achieved from a single sample injection event.

PSGMiner: A modular software for polysomnographic analysis.

PubMed

Umut, İlhan

2016-06-01

Sleep disorders affect a great percentage of the population. The diagnosis of these disorders is usually made by polysomnography. This paper details the development of new software to carry out feature extraction in order to perform robust analysis and classification of sleep events using polysomnographic data. The software, called PSGMiner, is a tool, which visualizes, processes and classifies bioelectrical data. The purpose of this program is to provide researchers with a platform with which to test new hypotheses by creating tests to check for correlations that are not available in commercially available software. The software is freely available under the GPL3 License. PSGMiner is composed of a number of diverse modules such as feature extraction, annotation, and machine learning modules, all of which are accessible from the main module. Using the software, it is possible to extract features of polysomnography using digital signal processing and statistical methods and to perform different analyses. The features can be classified through the use of five classification algorithms. PSGMiner offers an architecture designed for integrating new methods. Automatic scoring, which is available in almost all commercial PSG software, is not inherently available in this program, though it can be implemented by two different methodologies (machine learning and algorithms). While similar software focuses on a certain signal or event composed of a small number of modules with no expansion possibility, the software introduced here can handle all polysomnographic signals and events. The software simplifies the processing of polysomnographic signals for researchers and physicians that are not experts in computer programming. It can find correlations between different events which could help predict an oncoming event such as sleep apnea. The software could also be used for educational purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection of a repeated transit signature in the light curve of the enigma star KIC 8462852: A possible 928-day period

NASA Astrophysics Data System (ADS)

Kiefer, F.; Lecavelier des Étangs, A.; Vidal-Madjar, A.; Hébrard, G.; Bourrier, V.; Wilson, P. A.

2017-12-01

As revealed by its peculiar Kepler light curve, the enigmatic star KIC 8462852 undergoes short and deep flux dimmings at a priori unrelated epochs. This star presents nonetheless all other characteristics of a quiet 1 Gyr old F3V star. These dimmings resemble the absorption features expected for the transit of dust cometary tails. The exocomet scenario is therefore most commonly advocated. We reanalysed the Kepler data and extracted a new high-quality light curve to allow for the search of shallow signatures of single or a few exocomets. We discovered that among the 22 flux dimming events that we identified, two events present a striking similarity. These events occurred 928.25 days apart and lasted for 4.4 days with a drop in the star brightness by 1000 ppm. We show that the light curve of these events is well explained by the occultation of the star by a giant ring system or by the transit of a string of half a dozen exocomets with a typical dust production rate of 105-106 kg s-1. Assuming that these two similar events are related to the transit of the same object, we derive a period of 928.25 days. The following transit was expected in March 2017 but bad weather prohibited us from detecting it from ground-based spectroscopy. We predict that the next event will occur between 3-8 October 2019.

Detecting the red tide based on remote sensing data in optically complex East China Sea

NASA Astrophysics Data System (ADS)

Xu, Xiaohui; Pan, Delu; Mao, Zhihua; Tao, Bangyi; Liu, Qiong

2012-09-01

Red tide not only destroys marine fishery production, deteriorates the marine environment, affects coastal tourist industry, but also causes human poison, even death by eating toxic seafood contaminated by red tide organisms. Remote sensing technology has the characteristics of large-scale, synchronized, rapid monitoring, so it is one of the most important and most effective means of red tide monitoring. This paper selects the high frequency red tides areas of the East China Sea as study area, MODIS/Aqua L2 data as the data source, analysis and compares the spectral differences in the red tide water bodies and non-red tide water bodies of many historical events. Based on the spectral differences, this paper develops the algorithm of Rrs555/Rrs488> 1.5 to extract the red tide information. Apply the algorithm on red tide event happened in the East China Sea on May 28, 2009 to extract the information of red tide, and found that the method can determine effectively the location of the occurrence of red tide; there is a good corresponding relationship between red tide extraction result and chlorophyll a concentration extracted by remote sensing, shows that these algorithm can determine effectively the location and extract the red tide information.

Event-Related fMRI of Category Learning: Differences in Classification and Feedback Networks

ERIC Educational Resources Information Center

Little, Deborah M.; Shin, Silvia S.; Sisco, Shannon M.; Thulborn, Keith R.

2006-01-01

Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification…

Acquiring Information from Wider Scope to Improve Event Extraction

DTIC Science & Technology

2012-05-01

film ”. 2.3.2 Argument Constraint Even if the scenario is well detected, there is no guarantee of identifying the event correctly. Think about words...from 2003 newswire, with the same genre and time period as ACE 2005 data to avoid possible influences of variations in the genre or time period on the

A Visual Analytics Framework for Identifying Topic Drivers in Media Events.

PubMed

Lu, Yafeng; Wang, Hong; Landis, Steven; Maciejewski, Ross

2017-09-14

Media data has been the subject of large scale analysis with applications of text mining being used to provide overviews of media themes and information flows. Such information extracted from media articles has also shown its contextual value of being integrated with other data, such as criminal records and stock market pricing. In this work, we explore linking textual media data with curated secondary textual data sources through user-guided semantic lexical matching for identifying relationships and data links. In this manner, critical information can be identified and used to annotate media timelines in order to provide a more detailed overview of events that may be driving media topics and frames. These linked events are further analyzed through an application of causality modeling to model temporal drivers between the data series. Such causal links are then annotated through automatic entity extraction which enables the analyst to explore persons, locations, and organizations that may be pertinent to the media topic of interest. To demonstrate the proposed framework, two media datasets and an armed conflict event dataset are explored.

Auris System: Providing Vibrotactile Feedback for Hearing Impaired Population

PubMed Central

Pereira Fonseca Dutra, Savio; Eduardo Coelho Freire Batista, Carlos

2017-01-01

Deafness, an issue that affects millions of people around the globe, is manifested in different intensities and related to many causes. This impairment negatively affects different aspects of the social life of the deaf people, and music-centered situations (concerts, religious events, etc.) are obviously not inviting for them. The Auris System was conceived to provide the musical experimentation for people who have some type of hearing loss. This system is able to extract musical information from audio and create a representation for music pieces using different stimuli, a new media format to be interpreted by other senses than the hearing. In addition, the system defines a testing methodology based on a noninvasive brain activity recording using an electroencephalographic (EEG) device. The results of the tests are being used to better understand the human musical cognition, in order to improve the accuracy of the Auris musical representation. PMID:29138749

A Generalized Mechanism for Perception of Pitch Patterns

PubMed Central

Loui, Psyche; Wu, Elaine H.; Wessel, David L.; Knight, Robert T.

2009-01-01

Surviving in a complex and changeable environment relies upon the ability to extract probable recurring patterns. Here we report a neurophysiological mechanism for rapid probabilistic learning of a new system of music. Participants listened to different combinations of tones from a previously-unheard system of pitches based on the Bohlen-Pierce scale, with chord progressions that form 3:1 ratios in frequency, notably different from 2:1 frequency ratios in existing musical systems. Event-related brain potentials elicited by improbable sounds in the new music system showed emergence over a one-hour period of physiological signatures known to index sound expectation in standard Western music. These indices of expectation learning were eliminated when sound patterns were played equiprobably, and co-varied with individual behavioral differences in learning. These results demonstrate that humans utilize a generalized probability-based perceptual learning mechanism to process novel sound patterns in music. PMID:19144845

The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

NASA Astrophysics Data System (ADS)

Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-06-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for collecting and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This requires strong competence and experience in understanding and discovering problems and root causes, and often the meaningful information is not in the single message or update, but in the aggregated behavior in a certain time-line. The AAL project is meant at reducing the man power needs and at assuring a constant high quality of problem detection by automating most of the monitoring tasks and providing real-time correlation of data-taking and system metrics. This project combines technologies coming from different disciplines, in particular it leverages on an Event Driven Architecture to unify the flow of data from the ATLAS infrastructure, on a Complex Event Processing (CEP) engine for correlation of events and on a message oriented architecture for components integration. The project is composed of 2 main components: a core processing engine, responsible for correlation of events through expert-defined queries and a web based front-end to present real-time information and interact with the system. All components works in a loose-coupled event based architecture, with a message broker to centralize all communication between modules. The result is an intelligent system able to extract and compute relevant information from the flow of operational data to provide real-time feedback to human experts who can promptly react when needed. The paper presents the design and implementation of the AAL project, together with the results of its usage as automated monitoring assistant for the ATLAS data taking infrastructure.

Finding the Cause: Verbal Framing Helps Children Extract Causal Evidence Embedded in a Complex Scene

ERIC Educational Resources Information Center

Butler, Lucas P.; Markman, Ellen M.

2012-01-01

In making causal inferences, children must both identify a causal problem and selectively attend to meaningful evidence. Four experiments demonstrate that verbally framing an event ("Which animals make Lion laugh?") helps 4-year-olds extract evidence from a complex scene to make accurate causal inferences. Whereas framing was unnecessary when…

Predicting Key Events in the Popularity Evolution of Online Information.

PubMed

Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

Predicting Key Events in the Popularity Evolution of Online Information

PubMed Central

Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the “burst”, “peak”, and “fade” key events together as a representative summary of popularity evolution. We propose a novel prediction task—predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify “burst”, “peak”, and “fade” in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution. PMID:28046121

SNIa detection in the SNLS photometric analysis using Morphological Component Analysis

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

Möller, A.; Ruhlmann-Kleider, V.; Neveu, J.

2015-04-01

Detection of supernovae (SNe) and, more generally, of transient events in large surveys can provide numerous false detections. In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources. Optimizing the detection of transient events is thus an important issue for both present and future surveys. We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation. The 3-year analysis provided 300,000more » detections dominated by signals of bright objects that were not perfectly subtracted. Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination. We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis. This technique exploits the morphological diversity of objects to be detected to extract the signal of interest. At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes. A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction. We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal. SNIa Monte-Carlo (MC) generated images were used to study detection efficiency and coordinate resolution. When tested on SNLS 3-year data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint ones. MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.« less

Roles of Chemical Complexity and Evolutionary Theory in Some Hepatic and Intestinal Enzymatic Systems in Chemical Reproducibility and Clinical Efficiency of Herbal Derivatives

PubMed Central

2014-01-01

Despite the great marketing success, most physicians attribute poor efficacy to herbals. This perception is due to two situations that are an integral part of the herbal topic. The first is the poor phytochemical reproducibility obtained during the production process of herbal extracts, as herbal extracts are not always standardized in the whole manufacturing process, but only in their titer. The second problem is linked to the evolution of important enzymatic systems: cytochromes and ABC proteins. They are both enzyme classes with detoxifying properties and seem to have evolved from the molecular mould provided by active plant substances. During the evolution, as still happens today, polyphenols, saponins, terpenes, and alkaloids were ingested together with food. They do not possess any nutritional value but seem to be provided with a potential pharmacological activity. Cytochromes and ABC proteins, which evolved over time to detoxify food from vegetable chemical “actives,” now seem to limit the action of herbal derivatives. The comprehension of these 2 events may explain the origin of the widespread scepticism of physicians about herbal medicine and suggests that, after correct herbal standardization, use of antagonists of cytochromes and ABC systems will make it possible to recover their pharmacological potential. PMID:24977222

Roles of chemical complexity and evolutionary theory in some hepatic and intestinal enzymatic systems in chemical reproducibility and clinical efficiency of herbal derivatives.

PubMed

Di Pierro, Francesco

2014-01-01

Despite the great marketing success, most physicians attribute poor efficacy to herbals. This perception is due to two situations that are an integral part of the herbal topic. The first is the poor phytochemical reproducibility obtained during the production process of herbal extracts, as herbal extracts are not always standardized in the whole manufacturing process, but only in their titer. The second problem is linked to the evolution of important enzymatic systems: cytochromes and ABC proteins. They are both enzyme classes with detoxifying properties and seem to have evolved from the molecular mould provided by active plant substances. During the evolution, as still happens today, polyphenols, saponins, terpenes, and alkaloids were ingested together with food. They do not possess any nutritional value but seem to be provided with a potential pharmacological activity. Cytochromes and ABC proteins, which evolved over time to detoxify food from vegetable chemical "actives," now seem to limit the action of herbal derivatives. The comprehension of these 2 events may explain the origin of the widespread scepticism of physicians about herbal medicine and suggests that, after correct herbal standardization, use of antagonists of cytochromes and ABC systems will make it possible to recover their pharmacological potential.

Detailed investigation of Long-Period activity at Campi Flegrei by Convolutive Independent Component Analysis

NASA Astrophysics Data System (ADS)

Capuano, P.; De Lauro, E.; De Martino, S.; Falanga, M.

2016-04-01

This work is devoted to the analysis of seismic signals continuously recorded at Campi Flegrei Caldera (Italy) during the entire year 2006. The radiation pattern associated with the Long-Period energy release is investigated. We adopt an innovative Independent Component Analysis algorithm for convolutive seismic series adapted and improved to give automatic procedures for detecting seismic events often buried in the high-level ambient noise. The extracted waveforms characterized by an improved signal-to-noise ratio allows the recognition of Long-Period precursors, evidencing that the seismic activity accompanying the mini-uplift crisis (in 2006), which climaxed in the three days from 26-28 October, had already started at the beginning of the month of October and lasted until mid of November. Hence, a more complete seismic catalog is then provided which can be used to properly quantify the seismic energy release. To better ground our results, we first check the robustness of the method by comparing it with other blind source separation methods based on higher order statistics; secondly, we reconstruct the radiation patterns of the extracted Long-Period events in order to link the individuated signals directly to the sources. We take advantage from Convolutive Independent Component Analysis that provides basic signals along the three directions of motion so that a direct polarization analysis can be performed with no other filtering procedures. We show that the extracted signals are mainly composed of P waves with radial polarization pointing to the seismic source of the main LP swarm, i.e. a small area in the Solfatara, also in the case of the small-events, that both precede and follow the main activity. From a dynamical point of view, they can be described by two degrees of freedom, indicating a low-level of complexity associated with the vibrations from a superficial hydrothermal system. Our results allow us to move towards a full description of the complexity of the source, which can be used, by means of the small-intensity precursors, for hazard-model development and forecast-model testing, showing an illustrative example of the applicability of the CICA method to regions with low seismicity in high ambient noise.

Efficacy and safety of Curcuma domestica extracts compared with ibuprofen in patients with knee osteoarthritis: a multicenter study

PubMed Central

Kuptniratsaikul, Vilai; Dajpratham, Piyapat; Taechaarpornkul, Wirat; Buntragulpoontawee, Montana; Lukkanapichonchut, Pranee; Chootip, Chirawan; Saengsuwan, Jittima; Tantayakom, Kesthamrong; Laongpech, Supphalak

2014-01-01

Objective To determine the efficacy and safety of Curcuma domestica extracts in pain reduction and functional improvement. Methods 367 primary knee osteoarthritis patients with a pain score of 5 or higher were randomized to receive ibuprofen 1,200 mg/day or C. domestica extracts 1,500 mg/day for 4 weeks. The main outcomes were Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total, WOMAC pain, WOMAC stiffness, and WOMAC function scores. Adverse events (AEs) were also recorded. Results 185 and 182 patients were randomly assigned into C. domestica extracts and ibuprofen groups, respectively. The baseline characteristics were no different between groups. The mean of all WOMAC scores at weeks 0, 2, and 4 showed significant improvement when compared with the baseline in both groups. After using the noninferiority test, the mean difference (95% confidence interval) of WOMAC total, WOMAC pain, and WOMAC function scores at week 4 adjusted by values at week 0 of C. domestica extracts were noninferior to those for the ibuprofen group (P=0.010, P=0.018, and P=0.010, respectively), except for the WOMAC stiffness subscale, which showed a trend toward significance (P=0.060). The number of patients who developed AEs was no different between groups. However, the number of events of abdominal pain/discomfort was significantly higher in the ibuprofen group than that in the C. domestica extracts group (P=0.046). Most subjects (96%–97%) were satisfied with the treatment, and two-thirds rated themselves as improved in a global assessment. Conclusion C. domestica extracts are as effective as ibuprofen for the treatment of knee osteoarthritis. The side effect profile was similar but with fewer gastrointestinal AE reports in the C. domestica extracts group. PMID:24672232

Methodological issues on the use of administrative data in healthcare research: the case of heart failure hospitalizations in Lombardy region, 2000 to 2012.

PubMed

Mazzali, Cristina; Paganoni, Anna Maria; Ieva, Francesca; Masella, Cristina; Maistrello, Mauro; Agostoni, Ornella; Scalvini, Simonetta; Frigerio, Maria

2016-07-08

Administrative data are increasingly used in healthcare research. However, in order to avoid biases, their use requires careful study planning. This paper describes the methodological principles and criteria used in a study on epidemiology, outcomes and process of care of patients hospitalized for heart failure (HF) in the largest Italian Region, from 2000 to 2012. Data were extracted from the administrative data warehouse of the healthcare system of Lombardy, Italy. Hospital discharge forms with HF-related diagnosis codes were the basis for identifying HF hospitalizations as clinical events, or episodes. In patients experiencing at least one HF event, hospitalizations for any cause, outpatient services utilization, and drug prescriptions were also analyzed. Seven hundred one thousand, seven hundred one heart failure events involving 371,766 patients were recorded from 2000 to 2012. Once all the healthcare services provided to these patients after the first HF event had been joined together, the study database totalled about 91 million records. Principles, criteria and tips utilized in order to minimize errors and characterize some relevant subgroups are described. The methodology of this study could represent the basis for future research and could be applied in similar studies concerning epidemiology, trend analysis, and healthcare resources utilization.

wayGoo: a platform for geolocating and managing indoor and outdoor spaces

NASA Astrophysics Data System (ADS)

Thomopoulos, Stelios C. A.; Karafylli, Christina; Karafylli, Maria; Motos, Dionysis; Lampropoulos, Vassilis; Dimitros, Kostantinos; Margonis, Christos

2016-05-01

wayGoo2 is a platform for Geolocating and Managing indoor and outdoor spaces and content with multidimensional indoor and outdoor Navigation and Guidance. Its main components are a Geographic Information System, a back-end server, front-end applications and a web-based Content Management System (CMS). It constitutes a fully integrated 2D/3D space and content management system that creates a repository that consists of a database, content components and administrative data. wayGoo can connect to any third party database and event management data-source. The platform is secure as the data is only available through a Restful web service using https security protocol in conjunction with an API key used for authentication. To enhance users experience, wayGoo makes the content available by extracting components out of the repository and constructing targeted applications. The wayGoo platform supports geo-referencing of indoor and outdoor information and use of metadata. It also allows the use of existing information such as maps and databases. The platform enables planning through integration of content that is connected either spatially, temporally or contextually, and provides immediate access to all spatial data through interfaces and interactive 2D and 3D representations. wayGoo constitutes a mean to document and preserve assets through computerized techniques and provides a system that enhances the protection of your space, people and guests when combined with wayGoo notification and alert system. It constitutes a strong marketing tool providing staff and visitors with an immersive tool for navigation in indoor spaces and allowing users to organize their agenda and to discover events through wayGoo event scheduler and recommendation system. Furthermore, the wayGoo platform can be used in Security applications and event management, e.g. CBRNE incidents, man-made and natural disasters, etc., to document and geolocate information and sensor data (off line and real time) on one end, and offer navigation capabilities in indoor and outdoor spaces. Furthermore, the wayGoo platform can be used for the creation of immersive environments and experiences in conjunction with VR/AR (Virtual and Augmented Reality) technologies.

Final Technical Report on Quantifying Dependability Attributes of Software Based Safety Critical Instrumentation and Control Systems in Nuclear Power Plants

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

Smidts, Carol; Huang, Funqun; Li, Boyuan

With the current transition from analog to digital instrumentation and control systems in nuclear power plants, the number and variety of software-based systems have significantly increased. The sophisticated nature and increasing complexity of software raises trust in these systems as a significant challenge. The trust placed in a software system is typically termed software dependability. Software dependability analysis faces uncommon challenges since software systems’ characteristics differ from those of hardware systems. The lack of systematic science-based methods for quantifying the dependability attributes in software-based instrumentation as well as control systems in safety critical applications has proved itself to be amore » significant inhibitor to the expanded use of modern digital technology in the nuclear industry. Dependability refers to the ability of a system to deliver a service that can be trusted. Dependability is commonly considered as a general concept that encompasses different attributes, e.g., reliability, safety, security, availability and maintainability. Dependability research has progressed significantly over the last few decades. For example, various assessment models and/or design approaches have been proposed for software reliability, software availability and software maintainability. Advances have also been made to integrate multiple dependability attributes, e.g., integrating security with other dependability attributes, measuring availability and maintainability, modeling reliability and availability, quantifying reliability and security, exploring the dependencies between security and safety and developing integrated analysis models. However, there is still a lack of understanding of the dependencies between various dependability attributes as a whole and of how such dependencies are formed. To address the need for quantification and give a more objective basis to the review process -- therefore reducing regulatory uncertainty -- measures and methods are needed to assess dependability attributes early on, as well as throughout the life-cycle process of software development. In this research, extensive expert opinion elicitation is used to identify the measures and methods for assessing software dependability. Semi-structured questionnaires were designed to elicit expert knowledge. A new notation system, Causal Mechanism Graphing, was developed to extract and represent such knowledge. The Causal Mechanism Graphs were merged, thus, obtaining the consensus knowledge shared by the domain experts. In this report, we focus on how software contributes to dependability. However, software dependability is not discussed separately from the context of systems or socio-technical systems. Specifically, this report focuses on software dependability, reliability, safety, security, availability, and maintainability. Our research was conducted in the sequence of stages found below. Each stage is further examined in its corresponding chapter. Stage 1 (Chapter 2): Elicitation of causal maps describing the dependencies between dependability attributes. These causal maps were constructed using expert opinion elicitation. This chapter describes the expert opinion elicitation process, the questionnaire design, the causal map construction method and the causal maps obtained. Stage 2 (Chapter 3): Elicitation of the causal map describing the occurrence of the event of interest for each dependability attribute. The causal mechanisms for the “event of interest” were extracted for each of the software dependability attributes. The “event of interest” for a dependability attribute is generally considered to be the “attribute failure”, e.g. security failure. The extraction was based on the analysis of expert elicitation results obtained in Stage 1. Stage 3 (Chapter 4): Identification of relevant measurements. Measures for the “events of interest” and their causal mechanisms were obtained from expert opinion elicitation for each of the software dependability attributes. The measures extracted are presented in this chapter. Stage 4 (Chapter 5): Assessment of the coverage of the causal maps via measures. Coverage was assessed to determine whether the measures obtained were sufficient to quantify software dependability, and what measures are further required. Stage 5 (Chapter 6): Identification of “missing” measures and measurement approaches for concepts not covered. New measures, for concepts that had not been covered sufficiently as determined in Stage 4, were identified using supplementary expert opinion elicitation as well as literature reviews. Stage 6 (Chapter 7): Building of a detailed quantification model based on the causal maps and measurements obtained. Ability to derive such a quantification model shows that the causal models and measurements derived from the previous stages (Stage 1 to Stage 5) can form the technical basis for developing dependability quantification models. Scope restrictions have led us to prioritize this demonstration effort. The demonstration was focused on a critical system, i.e. the reactor protection system. For this system, a ranking of the software dependability attributes by nuclear stakeholders was developed. As expected for this application, the stakeholder ranking identified safety as the most critical attribute to be quantified. A safety quantification model limited to the requirements phase of development was built. Two case studies were conducted for verification. A preliminary control gate for software safety for the requirements stage was proposed and applied to the first case study. The control gate allows a cost effective selection of the duration of the requirements phase.« less

Disturbance Driven Rainfall in O`ahu, Hawai`i (1990-2010)

NASA Astrophysics Data System (ADS)

Longman, R. J.; Elison Timm, O.; Giambelluca, T. W.; Kaiser, L.; Newman, A. J.; Arnold, J.; Clark, M. P.

2017-12-01

Trade wind orographic rainfall is the most prevalent synoptic weather pattern in Hawai`i and provides a year-round source of moisture to the windward areas across the Island chain. Significant contributions to total and extreme precipitation have also been linked to one of four atmospheric disturbance situations that include: cold fronts, Kona storms, upper-tropospheric disturbances (upper level lows), and tropical systems. The primary objective of this research is to determine how these disturbance types contribute to total wet-season rainfall (RF) on the Island of O`ahu, Hawai`i and to identify any significant changes in the frequency of occurrence and or the intensity of these events. Atmospheric fronts that occurred in the Hawai`i region (17-26°N, 150-165°W) were extracted from a global dataset and combined with a Kona low and upper level low dataset to create a daily categorical weather classification time series (1990-2010). Mean rainfall was extracted from gridded daily O`ahu RF maps. Results show that the difference between a wet and dry year is predominantly explained by the RF contributions from disturbance events (r2 = 0.57, p < 0.01), in particularly, the contributions coming from Kona low and cold fronts that cross the Island. During the wettest season on record, disturbances accounted for 48% of the total RF, while during the driest season they accounted for only 6% of the total RF. The event-based RF analysis also compared the RF intensity in the absence of disturbance events with the average RF intensity on days when atmospheric fronts are present but do not cross the island. The results show that non-crossing fronts reduce the average RF intensity. A possible explanation is that these events are too far away to produce RF, but close enough to disrupt normal trade wind flow, thus limiting orographic RF on the island. This new event-based RF analysis has important implications for the projection of regional climate change in Hawai`i. Our results suggest that if storm tracks were to shift poleward, O`ahu wet season RF would be reduced. The most obvious effect is that fronts crossing the Island would likely occur less frequently reducing the number of days per year with heavy cold front rainfall. In addition, non-crossing fronts could occur more often and hence reducing the orographic RF.

Annotation and prediction of stress and workload from physiological and inertial signals.

PubMed

Ghosh, Arindam; Danieli, Morena; Riccardi, Giuseppe

2015-08-01

Continuous daily stress and high workload can have negative effects on individuals' physical and mental well-being. It has been shown that physiological signals may support the prediction of stress and workload. However, previous research is limited by the low diversity of signals concurring to such predictive tasks and controlled experimental design. In this paper we present 1) a pipeline for continuous and real-life acquisition of physiological and inertial signals 2) a mobile agent application for on-the-go event annotation and 3) an end-to-end signal processing and classification system for stress and workload from diverse signal streams. We study physiological signals such as Galvanic Skin Response (GSR), Skin Temperature (ST), Inter Beat Interval (IBI) and Blood Volume Pulse (BVP) collected using a non-invasive wearable device; and inertial signals collected from accelerometer and gyroscope sensors. We combine them with subjects' inputs (e.g. event tagging) acquired using the agent application, and their emotion regulation scores. In our experiments we explore signal combination and selection techniques for stress and workload prediction from subjects whose signals have been recorded continuously during their daily life. The end-to-end classification system is described for feature extraction, signal artifact removal, and classification. We show that a combination of physiological, inertial and user event signals provides accurate prediction of stress for real-life users and signals.

DAPNe with micro-capillary separatory chemistry-coupled to MALDI-MS for the analysis of polar and non-polar lipid metabolism in one cell

NASA Astrophysics Data System (ADS)

Hamilton, Jason S.; Aguilar, Roberto; Petros, Robby A.; Verbeck, Guido F.

2017-05-01

The cellular metabolome is considered to be a representation of cellular phenotype and cellular response to changes to internal or external events. Methods to expand the coverage of the expansive physiochemical properties that makeup the metabolome currently utilize multi-step extractions and chromatographic separations prior to chemical detection, leading to lengthy analysis times. In this study, a single-step procedure for the extraction and separation of a sample using a micro-capillary as a separatory funnel to achieve analyte partitioning within an organic/aqueous immiscible solvent system is described. The separated analytes are then spotted for MALDI-MS imaging and distribution ratios are calculated. Initially, the method is applied to standard mixtures for proof of partitioning. The extraction of an individual cell is non-reproducible; therefore, a broad chemical analysis of metabolites is necessary and will be illustrated with the one-cell analysis of a single Snu-5 gastric cancer cell taken from a cellular suspension. The method presented here shows a broad partitioning dynamic range as a single-step method for lipid analysis demonstrating a decrease in ion suppression often present in MALDI analysis of lipids.

A new approach to generating research-quality phenology data: The USA National Phenology Monitoring System

NASA Astrophysics Data System (ADS)

Denny, E. G.; Miller-Rushing, A. J.; Haggerty, B. P.; Wilson, B. E.

2009-12-01

The USA National Phenology Network has recently initiated a national effort to encourage people at different levels of expertise—from backyard naturalists to professional scientists—to observe phenological events and contribute to a national database that will be used to greatly improve our understanding of spatio-temporal variation in phenology and associated phenological responses to climate change. Traditional phenological observation protocols identify specific single dates at which individual phenological events are observed, but the scientific usefulness of long-term phenological observations can be improved with a more carefully structured protocol. At the USA-NPN we have developed a new approach that directs observers to record each day that they observe an individual plant, and to assess and report the state of specific life stages (or phenophases) as occurring or not occurring on that plant for each observation date. Evaluation is phrased in terms of simple, easy-to-understand, questions (e.g. “Do you see open flowers?”), which makes it very appropriate for a broad audience. From this method, a rich dataset of phenological metrics can be extracted, including the duration of a phenophase (e.g. open flowers), the beginning and end points of a phenophase (e.g. traditional phenological events such as first flower and last flower), multiple distinct occurrences of phenophases within a single growing season (e.g multiple flowering events, common in drought-prone regions), as well as quantification of sampling frequency and observational uncertainties. The system also includes a mechanism for translation of phenophase start and end points into standard traditional phenological events to facilitate comparison of contemporary data collected with this new “phenophase status” monitoring approach to historical datasets collected with the “phenological event” monitoring approach. These features greatly enhance the utility of the resulting data for statistical analyses addressing questions such as how phenological events vary in time and space, and in response to global change.

Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

NASA Astrophysics Data System (ADS)

Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

2007-12-01

The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of rainfall-runoff event analysis for model development as well as model diagnostics.

Climatological attribution of wind power ramp events in East Japan and their probabilistic forecast based on multi-model ensembles downscaled by analog ensemble using self-organizing maps

NASA Astrophysics Data System (ADS)

Ohba, Masamichi; Nohara, Daisuke; Kadokura, Shinji

2016-04-01

Severe storms or other extreme weather events can interrupt the spin of wind turbines in large scale that cause unexpected "wind ramp events". In this study, we present an application of self-organizing maps (SOMs) for climatological attribution of the wind ramp events and their probabilistic prediction. The SOM is an automatic data-mining clustering technique, which allows us to summarize a high-dimensional data space in terms of a set of reference vectors. The SOM is applied to analyze and connect the relationship between atmospheric patterns over Japan and wind power generation. SOM is employed on sea level pressure derived from the JRA55 reanalysis over the target area (Tohoku region in Japan), whereby a two-dimensional lattice of weather patterns (WPs) classified during the 1977-2013 period is obtained. To compare with the atmospheric data, the long-term wind power generation is reconstructed by using a high-resolution surface observation network AMeDAS (Automated Meteorological Data Acquisition System) in Japan. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of wind ramp events. Probabilistic forecasts to wind power generation and ramps are conducted by using the obtained SOM. The probability are derived from the multiple SOM lattices based on the matching of output from TIGGE multi-model global forecast to the WPs on the lattices. Since this method effectively takes care of the empirical uncertainties from the historical data, wind power generation and ramp is probabilistically forecasted from the forecasts of global models. The predictability skill of the forecasts for the wind power generation and ramp events show the relatively good skill score under the downscaling technique. It is expected that the results of this study provides better guidance to the user community and contribute to future development of system operation model for the transmission grid operator.

Antenna Measurements: Test & Analysis of the Radiated Emissions/Immunity of the NASA/Orion Spacecraft Dart Parachute Simulator & Prototype Capsule - The Crew Exploration Vehicle

NASA Technical Reports Server (NTRS)

Norgard, John D.

2012-01-01

For future NASA Manned Space Exploration of the Moon and Mars, a blunt body capsule, called the Orion Crew Exploration Vehicle (CEV), composed of a Crew Module (CM) and a Service Module (SM), with a parachute decent assembly is planned for reentry back to Earth. A Capsule Parachute Assembly System (CPAS) is being developed for preliminary prototype parachute drop tests at the Yuma Proving Ground (YPG) to simulate high-speed reentry to Earth from beyond Low-Earth-Orbit (LEO) and to provide measurements of position, velocity, acceleration, attitude, temperature, pressure, humidity, and parachute loads. The primary and secondary (backup) avionics systems on CPAS also provide mission critical firing events to deploy, reef, and release the parachutes in three stages (extraction, drogues, mains) using mortars and pressure cartridge assemblies. In addition, a Mid-Air Delivery System (MDS) is used to separate the capsule from the sled that is used to eject the capsule from the back of the drop plane. Also, high-speed and high-definition cameras in a Video Camera System (VCS) are used to film the drop plane extraction and parachute landing events. Intentional and unintentional radiation emitted from and received by antennas and electronic devices on/in the CEV capsule, the MDS sled, and the VCS system are being tested for radiated emissions/immunity (susceptibility) (RE/RS). To verify Electromagnetic Compatibility (EMC) of the Orion capsule, Electromagnetic Interference (EMI) measurements are being made inside a semi-anechoic chamber at NASA/JSC on the components of the CPAS system. Measurements are made at 1m from the components-under-test (CUT). In addition, EMI measurements of the integrated CEV system are being made inside a hanger at YPG. These measurements are made in a complete circle, at 30? angles or less, around the Orion Capsule, the spacecraft system under-test (SUT). Near-field B-Dot probe measurements on the surface of the Orion capsule are being extrapolated outward to the 1m standard distance for comparison to the MIL-STD radiated emissions limit, and far-field hybrid antenna measurements at 3m are being extrapolated inward to the 1m distance for similar comparisons.

Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

PubMed

Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

2016-10-28

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection

PubMed Central

2014-01-01

Background Independent data sources can be used to augment post-marketing drug safety signal detection. The vast amount of publicly available biomedical literature contains rich side effect information for drugs at all clinical stages. In this study, we present a large-scale signal boosting approach that combines over 4 million records in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and over 21 million biomedical articles. Results The datasets are comprised of 4,285,097 records from FAERS and 21,354,075 MEDLINE articles. We first extracted all drug-side effect (SE) pairs from FAERS. Our study implemented a total of seven signal ranking algorithms. We then compared these different ranking algorithms before and after they were boosted with signals from MEDLINE sentences or abstracts. Finally, we manually curated all drug-cardiovascular (CV) pairs that appeared in both data sources and investigated whether our approach can detect many true signals that have not been included in FDA drug labels. We extracted a total of 2,787,797 drug-SE pairs from FAERS with a low initial precision of 0.025. The ranking algorithm combined signals from both FAERS and MEDLINE, significantly improving the precision from 0.025 to 0.371 for top-ranked pairs, representing a 13.8 fold elevation in precision. We showed by manual curation that drug-SE pairs that appeared in both data sources were highly enriched with true signals, many of which have not yet been included in FDA drug labels. Conclusions We have developed an efficient and effective drug safety signal ranking and strengthening approach We demonstrate that large-scale combining information from FAERS and biomedical literature can significantly contribute to drug safety surveillance. PMID:24428898

Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection.

PubMed

Xu, Rong; Wang, QuanQiu

2014-01-15

Independent data sources can be used to augment post-marketing drug safety signal detection. The vast amount of publicly available biomedical literature contains rich side effect information for drugs at all clinical stages. In this study, we present a large-scale signal boosting approach that combines over 4 million records in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and over 21 million biomedical articles. The datasets are comprised of 4,285,097 records from FAERS and 21,354,075 MEDLINE articles. We first extracted all drug-side effect (SE) pairs from FAERS. Our study implemented a total of seven signal ranking algorithms. We then compared these different ranking algorithms before and after they were boosted with signals from MEDLINE sentences or abstracts. Finally, we manually curated all drug-cardiovascular (CV) pairs that appeared in both data sources and investigated whether our approach can detect many true signals that have not been included in FDA drug labels. We extracted a total of 2,787,797 drug-SE pairs from FAERS with a low initial precision of 0.025. The ranking algorithm combined signals from both FAERS and MEDLINE, significantly improving the precision from 0.025 to 0.371 for top-ranked pairs, representing a 13.8 fold elevation in precision. We showed by manual curation that drug-SE pairs that appeared in both data sources were highly enriched with true signals, many of which have not yet been included in FDA drug labels. We have developed an efficient and effective drug safety signal ranking and strengthening approach We demonstrate that large-scale combining information from FAERS and biomedical literature can significantly contribute to drug safety surveillance.

Exploring Spanish health social media for detecting drug effects.

PubMed

Segura-Bedmar, Isabel; Martínez, Paloma; Revert, Ricardo; Moreno-Schneider, Julián

2015-01-01

Adverse Drug reactions (ADR) cause a high number of deaths among hospitalized patients in developed countries. Major drug agencies have devoted a great interest in the early detection of ADRs due to their high incidence and increasing health care costs. Reporting systems are available in order for both healthcare professionals and patients to alert about possible ADRs. However, several studies have shown that these adverse events are underestimated. Our hypothesis is that health social networks could be a significant information source for the early detection of ADRs as well as of new drug indications. In this work we present a system for detecting drug effects (which include both adverse drug reactions as well as drug indications) from user posts extracted from a Spanish health forum. Texts were processed using MeaningCloud, a multilingual text analysis engine, to identify drugs and effects. In addition, we developed the first Spanish database storing drugs as well as their effects automatically built from drug package inserts gathered from online websites. We then applied a distant-supervision method using the database on a collection of 84,000 messages in order to extract the relations between drugs and their effects. To classify the relation instances, we used a kernel method based only on shallow linguistic information of the sentences. Regarding Relation Extraction of drugs and their effects, the distant supervision approach achieved a recall of 0.59 and a precision of 0.48. The task of extracting relations between drugs and their effects from social media is a complex challenge due to the characteristics of social media texts. These texts, typically posts or tweets, usually contain many grammatical errors and spelling mistakes. Moreover, patients use lay terminology to refer to diseases, symptoms and indications that is not usually included in lexical resources in languages other than English.

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 statistical power to detect the variation in reporting rates across years. The identified vaccine-event combinations with significant different reporting rates over years suggested potential safety issues due to changes in vaccines which require further investigation. We developed a statistical model to detect safety signals arising from heterogeneity of reporting rates of a given vaccine-event combinations across reporting years. This method detects variation in reporting rates over years with high power. The temporal trend of reporting rate across years may reveal the impact of vaccine update on occurrence of adverse events and provide evidence for further investigations.

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials

PubMed Central

Federer, Callie; Yoo, Minjae

2016-01-01

Abstract Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov (https://clinicaltrials.gov/), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov. Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs. PMID:27631620

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

PubMed

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

ScienceCinema

Danuso, Francesco

2017-12-22

A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

Bioactivities in the tamarind seed extracts: A preliminary study

NASA Astrophysics Data System (ADS)

Garg, Sukant; Muangman, Thanchanok; Huifu, He; Ling, Li; Kaul, Sunil C.; Wadhwa, Renu

2018-01-01

Stress is a state that triggers change in normal physiology and recognized by human body and brain as an unfavorable event causing concern, worry or anxiety. It may vary from physical, metabolic, physiological or emotional often culminating into wide range of ailments that may range from common cold, decline in functional efficacy of body systems or even cancer. Skin is the largest tissue of the body and makes the first interface with the environment. Skin color and characteristics are highly influenced by environment stress. A variety of natural compounds have been used for anti-stress and disease preventive potentials in worldwide traditional home medicine systems. They have recently attracted attention in research laboratories to dissect their mode of action to promote safe and economic drug development. We have earlier identified anti-stress and anti-aging activities in Withania somnifera, Helicteres angustifolia and honeybee propolis using human cultured normal and cancer cells. In the present study, we explored the effect of tamarind seed extracts prepared in water or 95% ethanol. In cell-based assays, we found that the extracts were safe to use in viable cells (in the range of 0.01-1.0%, for at least 4 weeks). Consistently, molecular studies revealed no effect on the expression/activity of cancer promoting proteins. We recruited oxidative stress models, such as, hydrogen peroxide (H2O2), ultraviolet radiation (UV) and diacylglycerol 1-oleoyl-2-acetyl-sn-glycerol (OAG). Investigation on anti-stress potential of the extracts revealed that they do not offer remarkable protection against stress caused by either H2O2 or UV, however, significantly compromised OAG-induced melanogenesis. The preliminary data warrant further investigations on the active components and mechanism of action to develop useful natural compounds/extracts for manipulation of melanogenesis that plays important role in response of cells to UV and its consequences including DNA damage, oxidative stress and related diseases.

Clinical Assessment of Tribulus terrestris Extract in the Treatment of Female Sexual Dysfunction

PubMed Central

Gama, Carlos RB; Lasmar, Ricardo; Gama, Gustavo F; Abreu, Camila S; Nunes, Carlos P; Geller, Mauro; Oliveira, Lisa; Santos, Alessandra

2014-01-01

This is a qualitative–quantitative study based on hospital records of female patients of reproductive age, presenting sexual dysfunction, and treated with 250 mg Tribulus terrestris extract (1 tablet thrice daily for 90 days). Safety monitoring included vital signs, physical examination, laboratory tests, and occurrence of adverse events. Efficacy analysis included results of the Female Sexual Function Index (FSFI), dehydroepiandrosterone (DHEA) levels together with total and free testosterone, and the patient and physician assessments. There was a statistically significant improvement in total FSFI scores (P < 0.0001) post-treatment, with improvement among 106 (88.33%) subjects. There was a statistically significant (P < 0.0001) increase in the level of DHEA, while the levels of both serum testosterone (P = 0.284) and free testosterone decreased (P < 0.0001). Most adverse events recorded were related to the gastrointestinal tract. Physical examination showed no significant changes post-treatment. Based on the results, it is concluded that the T. terrestris extract is safe and effective in the treatment of female sexual dysfunction. PMID:25574150

Clinical Assessment of Tribulus terrestris Extract in the Treatment of Female Sexual Dysfunction.

PubMed

Gama, Carlos Rb; Lasmar, Ricardo; Gama, Gustavo F; Abreu, Camila S; Nunes, Carlos P; Geller, Mauro; Oliveira, Lisa; Santos, Alessandra

2014-01-01

This is a qualitative-quantitative study based on hospital records of female patients of reproductive age, presenting sexual dysfunction, and treated with 250 mg Tribulus terrestris extract (1 tablet thrice daily for 90 days). Safety monitoring included vital signs, physical examination, laboratory tests, and occurrence of adverse events. Efficacy analysis included results of the Female Sexual Function Index (FSFI), dehydroepiandrosterone (DHEA) levels together with total and free testosterone, and the patient and physician assessments. There was a statistically significant improvement in total FSFI scores (P < 0.0001) post-treatment, with improvement among 106 (88.33%) subjects. There was a statistically significant (P < 0.0001) increase in the level of DHEA, while the levels of both serum testosterone (P = 0.284) and free testosterone decreased (P < 0.0001). Most adverse events recorded were related to the gastrointestinal tract. Physical examination showed no significant changes post-treatment. Based on the results, it is concluded that the T. terrestris extract is safe and effective in the treatment of female sexual dysfunction.

Surface Contamination by Radon Daughters Measured by Ionization-Heat NTD Germanium Detectors

NASA Astrophysics Data System (ADS)

Navick, X.-F.

2008-05-01

The discrimination power of the NTD ionization-heat detectors to distinguish nuclear recoils from electron recoils is affected by events interpreted as surface events. On the basis of the data from EDELWEISS I and first data taking of EDELWEISS-2, we present a coherent interpretation and direct evidence that surface events occur and are due to radon daughter deposition on detector surface and close-by surfaces. The estimation of the surface activities of contaminated surface are extracted from the new data taking.

Intermittent muscle activity in the feedback loop of postural control system during natural quiet standing.

PubMed

Tanabe, Hiroko; Fujii, Keisuke; Kouzaki, Motoki

2017-09-06

The origin of continual body oscillation during quiet standing is a neural-muscular-skeletal closed feedback loop system that includes insufficient joint stiffness and a time delay. Thus, muscle activity and joint oscillations are nonlinear during quiet standing, making it difficult to demonstrate the muscular-skeletal relationship experimentally. Here we experimentally revealed this relationship using intermittent control theory, in which non-actuation works to stabilize the skeletal system towards equilibrium. We found that leg muscles were activated/inactivated when the state point was located in the opposite/same direction as the direction of anatomical action, which was associated with joint torque actuating the body towards equilibrium. The derivative values of stability index defined in the phase space approximately 200 ms before muscle inactivation were also larger than those before activation for some muscles. These results indicate that bipedal standing might be achieved by monitoring the rate of change of stability/instability components and generating joint torque to stabilize the body. In conclusion, muscles are likely to activate in an event-driven manner during quiet standing and a possible metric for on/off switching is SI dot, and our methodology of EMG processing could allows us to extract such event-driven intermittent muscle activities.

Validation of the French national health insurance information system as a tool in vaccine safety assessment: application to febrile convulsions after pediatric measles/mumps/rubella immunization.

PubMed

Hanf, Matthieu; Quantin, Catherine; Farrington, Paddy; Benzenine, Eric; Hocine, N Mounia; Velten, Michel; Tubert-Bitter, Pascale; Escolano, Sylvie

2013-12-02

In the French national health insurance information system (SNIIR-AM), routine records of health claimed reimbursements are linked to hospital admissions for the whole French population. The main focus of this work is the usability of this system for vaccine safety assessment programme. Self-controlled case series analyses were performed using an exhaustive SNIIR-AM extraction of French children aged less than 3 years, to investigate the relationship between MMR immunization and children hospitalizations for febrile convulsions, a well-documented rare adverse event, over 2009-2010. The results suggest a significant increase of febrile convulsions during the 6-11 days period following any MMR immunization (IRR=1.49, 95% CI=1.22, 1.83; p=0.0001) and no increase 15-35 days post any MMR immunization (IRR=1.03, 95% CI=0.89, 1.18; p=0.72). These results are in accordance with other results obtained from large epidemiologic studies, which suggest the usability of the SNIIR-AM as a relevant database to study the occurrence of adverse events associated with immunization. For future use, results associated with risk of convulsion during the day of vaccination should nevertheless be considered with particular caution. Copyright © 2013 Elsevier Ltd. All rights reserved.

Design of extraction system in BRing at HIAF

NASA Astrophysics Data System (ADS)

Ruan, Shuang; Yang, Jiancheng; Zhang, Jinquan; Shen, Guodong; Ren, Hang; Liu, Jie; Shangguan, Jingbing; Zhang, Xiaoying; Zhang, Jingjing; Mao, Lijun; Sheng, Lina; Yin, Dayu; Wang, Geng; Wu, Bo; Yao, Liping; Tang, Meitang; Cai, Fucheng; Chen, Xiaoqiang

2018-06-01

The Booster Ring (BRing), which is the key part of HIAF (High Intensity heavy ion Accelerator Facility) complex at IMP (Institute of Modern Physics, Chinese Academy of Sciences), can provide uranium (A / q = 7) beam with a wide extraction energy range of 200-800 MeV/u. To fulfill a flexible beam extraction for multi-purpose experiments, both fast and slow extraction systems will be accommodated in the BRing. The fast extraction system is used for extracting short bunched beam horizontally in single-turn. The slow extraction system is used to provide quasi-continuous beam by the third order resonance and RF-knockout scheme. To achieve a compact structure, the two extraction systems are designed to share the same extraction channel. The general design of the fast and slow extraction systems and simulation results are discussed in this paper.

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

Chang, L. C.; Yang, S. N.; Kuo, C. L.; Wang, Y. F.

2017-12-01

This study proposes a prototype of the regional early flood inundation warning system in Tainan City, Taiwan. The AI technology is used to forecast multi-step-ahead regional flood inundation maps during storm events. The computing time is only few seconds that leads to real-time regional flood inundation forecasting. A database is built to organize data and information for building real-time forecasting models, maintaining the relations of forecasted points, and displaying forecasted results, while real-time data acquisition is another key task where the model requires immediately accessing rain gauge information to provide forecast services. All programs related database are constructed in Microsoft SQL Server by using Visual C# to extracting real-time hydrological data, managing data, storing the forecasted data and providing the information to the visual map-based display. The regional early flood inundation warning system use the up-to-date Web technologies driven by the database and real-time data acquisition to display the on-line forecasting flood inundation depths in the study area. The friendly interface includes on-line sequentially showing inundation area by Google Map, maximum inundation depth and its location, and providing KMZ file download of the results which can be watched on Google Earth. The developed system can provide all the relevant information and on-line forecast results that helps city authorities to make decisions during typhoon events and make actions to mitigate the losses.

Benefits, barriers, and limitations on the use of Hospital Incident Command System.

PubMed

Shooshtari, Shahin; Tofighi, Shahram; Abbasi, Shirin

2017-01-01

Hospital Incident Command System (HICS) has been established with the mission of prevention, response, and recovery in hazards. Regarding the key role of hospitals in medical management of events, the present study is aimed at investigating benefits, barriers, and limitations of applying HICS in hospital. Employing a review study, articles related to the aforementioned subject published from 1995 to 2016 were extracted from accredited websites and databases such as PubMed, Google Scholar, Elsevier, and SID by searching keywords such as HICS, benefits, barriers, and limitations. Then, those articles were summarized and reported. Using of HICS can cause creating preparedness in facing disasters, constructive management in strategies of controlling events, and disasters. Therefore, experiences indicate that there are some limitations in the system such as failure to assess the strength and severity of vulnerabilities of hospital, no observation of standards for disaster management in the design, constructing and equipping hospitals, and the absence of a model for evaluating the system. Accordingly, the conducted studies were investigated for probing the performance HICS. With regard to the role of health in disaster management, it requires advanced international methods in facing disasters. Using accurate models for assessing, the investigation of preparedness of hospitals in precrisis conditions based on components such as command, communications, security, safety, development of action plans, changes in staff's attitudes through effective operational training and exercises and creation of required maneuvers seems necessary.

Apparatus for hydrocarbon extraction

DOEpatents

Bohnert, George W.; Verhulst, Galen G.

2013-03-19

Systems and methods for hydrocarbon extraction from hydrocarbon-containing material. Such systems and methods relate to extracting hydrocarbon from hydrocarbon-containing material employing a non-aqueous extractant. Additionally, such systems and methods relate to recovering and reusing non-aqueous extractant employed for extracting hydrocarbon from hydrocarbon-containing material.

Evaluation of the efficacy of Withania somnifera (Ashwagandha) root extract in patients with obsessive-compulsive disorder: A randomized double-blind placebo-controlled trial.

PubMed

Jahanbakhsh, Seyedeh Pardis; Manteghi, Ali Akhondpour; Emami, Seyed Ahmad; Mahyari, Saman; Gholampour, Beheshteh; Mohammadpour, Amir Hooshang; Sahebkar, Amirhossein

2016-08-01

Obsessive-compulsive disorder (OCD) is a chronic psychiatric disorder that is causally linked to dysregulation of the serotonergic system. The aim of this study is to investigate the efficacy of Withania somnifera (W. somnifera) root extract as an adjunct therapy to standard OCD treatment. Thirty patients with a confirmed diagnosis of OCD according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria participated in this randomized double-blind placebo-controlled trial and were randomly assigned to the treatment group (W. somnifera extract, 120mg/day; n=15) or the placebo group (n=15). All patients were under treatment with Selective Serotonin Re-uptake Inhibitors (SSRIs), and were instructed to take 4 capsules of the extract or placebo per day, preferably after meals, for a period of six weeks. The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was used in order to assess the severity of OCD symptoms at baseline and at the end of the trial. Statistical analyses were performed using SPSS software and Y-BOCS values were presented as median and range (Min-Max). Comparison of the change in Y-BOCS score during the course of the trial revealed a significantly greater effect of W. somnifera (26 (14-40) [pre-treatment] versus 14 (4-40) [post-treatment]; change: -8 (-23 to 0)) versus placebo (18 (11-33) [pre-treatment] versus 16 (10-31) [post-treatment]; change: -2 (-4 to 0)) (P<0.001). The extract was safe and no adverse event was reported during the trial. W. somnifera extract may be beneficial as a safe and effective adjunct to SSRIs in the treatment of OCD. Copyright © 2016. Published by Elsevier Ltd.

Analysis of mutagenic activity of biohazardous organics in Kanawha River sediments. Technical completion report

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

White, A.R.; Waldron, M.C.

1988-01-01

Residual chemical contamination of Kanawha River sediments may constitute a health hazard. Sediment cores have been analyzed using a coupled bioassay/chemical fractionation procedure. Both bacterial mutagenicity and sister chromatid exchange (SCE) analyses were conducted on sediment samples. Pocatalico River sediments extracts showed no response in either bacterial mutagenicity assay or SCE assay. Extracts from Armour Creek and the Kanawha River induced mutagenicities in the presence of S9 enzymes. The same extracts produced a significant increase in human chromosomal cross-over events.

Systemic administration of defined extracts from Withania somnifera (Indian Ginseng) and Shilajit differentially affects cholinergic but not glutamatergic and GABAergic markers in rat brain.

PubMed

Schliebs, R; Liebmann, A; Bhattacharya, S K; Kumar, A; Ghosal, S; Bigl, V

1997-02-01

Although some promising results have been achieved by acetylcholinesterase inhibitors, an effective therapeutic intervention in Alzheimer's disease still remains an important goal. Sitoindosides VII-X, and withaferin-A, isolated from aqueous methanol extract from the roots of cultivated varieties of Withania somnifera (known as Indian Ginseng), as well as Shilajit, a pale-brown to blackish brown exudation from steep rocks of the Himalaya mountain, are used in Indian medicine to attenuate cerebral functional deficits, including amnesia, in geriatric patients. The present investigation was conducted to assess whether the memory-enhancing effects of plant extracts from Withania somnifera and Shilajit are owing to neurochemical alterations of specific transmitter systems. Therefore, histochemistry to analyse acetylcholinesterase activity as well as receptor autoradiography to detect cholinergic, glutamatergic and GABAergic receptor subtypes were performed in brain slices from adult male Wistar rats, injected intraperitoneally daily with an equimolar mixture of sitoindosides VII-X and withaferin-A (prepared from Withania somnifera) or with Shilajit, at doses of 40 mg/kg of body weight for 7 days. Administration of Shilajit led to reduced acetylcholinesterase staining, restricted to the basal forebrain nuclei including medial septum and the vertical limb of the diagonal band. Systemic application of the defined extract from Withania somnifera, however, led to differential effects on AChE activity in basal forebrain nuclei: slightly enhanced AChE activity was found in the lateral septum and globus pallidus, whereas in the vertical diagonal band AChE activity was reduced following treatment with sitoindosides VII-X and withaferin-A. These changes were accompanied by enhanced M1-muscarinic cholinergic receptor binding in lateral and medial septum as well as in frontal cortices, whereas the M2-muscarinic receptor binding sites were increased in a number of cortical regions including cingulate, frontal, piriform, parietal and retrosplenial cortex. Treatment with Shilajit or the defined extract from Withania somnifera affected neither GABAA and benzodiazepine receptor binding nor NMDA and AMPA glutamate receptor subtypes in any of the cortical or subcortical regions studied. The data suggest that Shilajit and the defined extract from Withania somnifera affect preferentially events in the cortical and basal forebrain cholinergic signal transduction cascade. The drug-induced increase in cortical muscarinic acetylcholine receptor capacity might partly explain the cognition-enhancing and memory-improving effects of extracts from Withania somnifera observed in animals and humans.

[Medicine in Sardinia between XIXth and XXth century: Buggerru Mining Hospital].

PubMed

Porro, Alessandro

2007-01-01

In Italy, the town of Buggerru, Sardinia, could be considered the cradle of zinc extractive industries. Around Malfidano mine developed a mining village, that reached a population of 8000 inhabitants. It was a peculiar environment since the population included a lot of younger people, women and children workers. The extractive activity exposed all of them to health and life hazards. A hospital was founded in 1868, but was reorganized at the beginning of 20th century. Medical records enable to study the activity of Buggerru hospital, providing information on the complex health events of its inhabitants. For the history of public health and medicine, the events of these hospitals are a subject of interest, being the reflection of major episodes of those times.

On the use of orientation filters for 3D reconstruction in event-driven stereo vision

PubMed Central

Camuñas-Mesa, Luis A.; Serrano-Gotarredona, Teresa; Ieng, Sio H.; Benosman, Ryad B.; Linares-Barranco, Bernabe

2014-01-01

The recently developed Dynamic Vision Sensors (DVS) sense visual information asynchronously and code it into trains of events with sub-micro second temporal resolution. This high temporal precision makes the output of these sensors especially suited for dynamic 3D visual reconstruction, by matching corresponding events generated by two different sensors in a stereo setup. This paper explores the use of Gabor filters to extract information about the orientation of the object edges that produce the events, therefore increasing the number of constraints applied to the matching algorithm. This strategy provides more reliably matched pairs of events, improving the final 3D reconstruction. PMID:24744694

Waveform Analysis Optimization for the 45Ca Beta Decay Experiment

NASA Astrophysics Data System (ADS)

Whitehead, Ryan; ⁴⁵Ca Collaboration

2017-09-01

The 45Ca experiment is searching for a non-zero Fierz interference term, which would imply a tensor type contribution to the low-energy weak interaction, possibly signaling Beyond-the-Standard-Model (BSM) physics. Beta spectrum measurements are being performed at LANL, using the segmented, large area, Si detectors developed for the Nab and UCNB experiments. 109 events have been recorded, with 38 of the 254 pixels instrumented, during the summers of 2016 and 2017. An important step to extracting the energy spectra is the correction of the waveform for pile-up events. A set of analysis tools has been developed to address this issue. A trapezoidal filter has been characterized and optimized for the experimental waveforms. This filter is primarily used for energy extraction, but, by adjusting certain parameters, it has been modified to identify pile-up events. The efficiency varies with the total energy of the particle and the amount deposited with each detector interaction. Preliminary results of this analysis will be presented.

Experimental evidence of a dual endocrine control of biosynthesis in the main nidamental glands of Sepia officinalis L. by factors from the central nervous system and the ovary.

PubMed

Henry, J; Boucaud-Camou, E

1993-12-01

1. A rapid, reliable and quantitative in vitro bioassay was developed to study the endocrine control of the biosynthesis of the egg capsule: incorporation of 14C-labelled D-glucose in polysaccharides and glycoproteins increased in dispersed-cell suspensions of main nidamental glands from maturing females. 2. Brain, optic lobes (OL) and ovary extracts from mature and maturing females stimulated the incorporation of 14C-labelled D-glucose in polysaccharidic and glycoproteic fractions of a nidamental cell suspension, whereas optic gland (OG) had no effect. 3. These results bring the first experimental evidence that one of the spawning events (egg-capsule edification) is controlled by the central nervous system and the ovary in a cephalopod.

Ambulatory REACT: real-time seizure detection with a DSP microprocessor.

PubMed

McEvoy, Robert P; Faul, Stephen; Marnane, William P

2010-01-01

REACT (Real-Time EEG Analysis for event deteCTion) is a Support Vector Machine based technology which, in recent years, has been successfully applied to the problem of automated seizure detection in both adults and neonates. This paper describes the implementation of REACT on a commercial DSP microprocessor; the Analog Devices Blackfin®. The primary aim of this work is to develop a prototype system for use in ambulatory or in-ward automated EEG analysis. Furthermore, the complexity of the various stages of the REACT algorithm on the Blackfin processor is analysed; in particular the EEG feature extraction stages. This hardware profile is used to select a reduced, platform-aware feature set, in order to evaluate the seizure classification accuracy of a lower-complexity, lower-power REACT system.

Evaluation of superconducting wiggler designs and free-electron laser support: Final report

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

NONE

1990-10-12

This report consists of copies of previous progress reports, and copies of viewgraphs presented in a talk at Los Alamos. The report describes activities carried out as part of a project to evaluate the design and performance of a superconducting wiggler magnet design. It includes work on evaluating the appropriate materials for the magnet coils and poles, and stress evaluations for the design. It includes work on beam optics through the magnet, and design considerations to optimize extraction: work on the cryocooling system; weight minimization efforts; and design work on the vacuum liner for the magnet. A major concern inmore » all of this design work is heat loads which will be dissipated in different parts of the system during operation, as well as transient events.« less

Apparatus and methods for hydrocarbon extraction

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

Bohnert, George W.; Verhulst, Galen G.

Systems and methods for hydrocarbon extraction from hydrocarbon-containing material. Such systems and methods relate to extracting hydrocarbon from hydrocarbon-containing material employing a non-aqueous extractant. Additionally, such systems and methods relate to recovering and reusing non-aqueous extractant employed for extracting hydrocarbon from hydrocarbon-containing material.

Conversion of Questionnaire Data

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

Powell, Danny H; Elwood Jr, Robert H

During the survey, respondents are asked to provide qualitative answers (well, adequate, needs improvement) on how well material control and accountability (MC&A) functions are being performed. These responses can be used to develop failure probabilities for basic events performed during routine operation of the MC&A systems. The failure frequencies for individual events may be used to estimate total system effectiveness using a fault tree in a probabilistic risk analysis (PRA). Numeric risk values are required for the PRA fault tree calculations that are performed to evaluate system effectiveness. So, the performance ratings in the questionnaire must be converted to relativemore » risk values for all of the basic MC&A tasks performed in the facility. If a specific material protection, control, and accountability (MPC&A) task is being performed at the 'perfect' level, the task is considered to have a near zero risk of failure. If the task is performed at a less than perfect level, the deficiency in performance represents some risk of failure for the event. As the degree of deficiency in performance increases, the risk of failure increases. If a task that should be performed is not being performed, that task is in a state of failure. The failure probabilities of all basic events contribute to the total system risk. Conversion of questionnaire MPC&A system performance data to numeric values is a separate function from the process of completing the questionnaire. When specific questions in the questionnaire are answered, the focus is on correctly assessing and reporting, in an adjectival manner, the actual performance of the related MC&A function. Prior to conversion, consideration should not be given to the numeric value that will be assigned during the conversion process. In the conversion process, adjectival responses to questions on system performance are quantified based on a log normal scale typically used in human error analysis (see A.D. Swain and H.E. Guttmann, 'Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications,' NUREG/CR-1278). This conversion produces the basic event risk of failure values required for the fault tree calculations. The fault tree is a deductive logic structure that corresponds to the operational nuclear MC&A system at a nuclear facility. The conventional Delphi process is a time-honored approach commonly used in the risk assessment field to extract numerical values for the failure rates of actions or activities when statistically significant data is absent.« less

Applying traditional signal processing techniques to social media exploitation for situational understanding

NASA Astrophysics Data System (ADS)

Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

2016-05-01

Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

A Tool for Empirical Forecasting of Major Flares, Coronal Mass Ejections, and Solar Particle Events from a Proxy of Active-Region Free Magnetic Energy

NASA Technical Reports Server (NTRS)

Barghouty, A. F.; Falconer, D. A.; Adams, J. H., Jr.

2010-01-01

This presentation describes a new forecasting tool developed for and is currently being tested by NASA s Space Radiation Analysis Group (SRAG) at JSC, which is responsible for the monitoring and forecasting of radiation exposure levels of astronauts. The new software tool is designed for the empirical forecasting of M and X-class flares, coronal mass ejections, as well as solar energetic particle events. Its algorithm is based on an empirical relationship between the various types of events rates and a proxy of the active region s free magnetic energy, determined from a data set of approx.40,000 active-region magnetograms from approx.1,300 active regions observed by SOHO/MDI that have known histories of flare, coronal mass ejection, and solar energetic particle event production. The new tool automatically extracts each strong-field magnetic areas from an MDI full-disk magnetogram, identifies each as an NOAA active region, and measures a proxy of the active region s free magnetic energy from the extracted magnetogram. For each active region, the empirical relationship is then used to convert the free magnetic energy proxy into an expected event rate. The expected event rate in turn can be readily converted into the probability that the active region will produce such an event in a given forward time window. Descriptions of the datasets, algorithm, and software in addition to sample applications and a validation test are presented. Further development and transition of the new tool in anticipation of SDO/HMI is briefly discussed.

Neural networks for simultaneous classification and parameter estimation in musical instrument control

NASA Astrophysics Data System (ADS)

Lee, Michael; Freed, Adrian; Wessel, David

1992-08-01

In this report we present our tools for prototyping adaptive user interfaces in the context of real-time musical instrument control. Characteristic of most human communication is the simultaneous use of classified events and estimated parameters. We have integrated a neural network object into the MAX language to explore adaptive user interfaces that considers these facets of human communication. By placing the neural processing in the context of a flexible real-time musical programming environment, we can rapidly prototype experiments on applications of adaptive interfaces and learning systems to musical problems. We have trained networks to recognize gestures from a Mathews radio baton, Nintendo Power GloveTM, and MIDI keyboard gestural input devices. In one experiment, a network successfully extracted classification and attribute data from gestural contours transduced by a continuous space controller, suggesting their application in the interpretation of conducting gestures and musical instrument control. We discuss network architectures, low-level features extracted for the networks to operate on, training methods, and musical applications of adaptive techniques.

Autocatalytic microtubule nucleation determines the size and mass of Xenopus laevis egg extract spindles.

PubMed

Decker, Franziska; Oriola, David; Dalton, Benjamin; Brugués, Jan

2018-01-11

Regulation of size and growth is a fundamental problem in biology. A prominent example is the formation of the mitotic spindle, where protein concentration gradients around chromosomes are thought to regulate spindle growth by controlling microtubule nucleation. Previous evidence suggests that microtubules nucleate throughout the spindle structure. However, the mechanisms underlying microtubule nucleation and its spatial regulation are still unclear. Here, we developed an assay based on laser ablation to directly probe microtubule nucleation events in Xenopus laevis egg extracts. Combining this method with theory and quantitative microscopy, we show that the size of a spindle is controlled by autocatalytic growth of microtubules, driven by microtubule-stimulated microtubule nucleation. The autocatalytic activity of this nucleation system is spatially regulated by the limiting amounts of active microtubule nucleators, which decrease with distance from the chromosomes. This mechanism provides an upper limit to spindle size even when resources are not limiting. © 2018, Decker et al.

Atmospheric influence on the distribution of organic pollutants in the Guadalquivir River estuary, SW Spain.

PubMed

Fernández-Gómez, Cristal; López-López, José Antonio; Matamoros, Victor; Díez, Sergi; García-Vargas, Manuel; Moreno, Carlos

2013-04-01

In the lower Guadalquivir river basin, a system stressed by a wide variety of anthropogenic activities, eight pesticides (four triazines, two chloroacetanilide herbicides, one organochlorine, and one organophosphorus insecticide); and four emerging pollutants (two personal care products, one organophosphorous flame retardant, and one xanthine alkaloid) were analyzed in river water during a 2-year monitoring program, and after rain episodes. Samples were extracted using the solid phase extraction (SPE) technique prior to determination of compounds using gas chromatograph coupled to a mass spectrometer detector. Except for caffeine, recoveries were mostly above 80 %, while limits of detection and quantification were in the low nanograms per liter level (except for dimethoate). Terbuthylazine, simazine (triazine herbicides), and dimethoate (organophosphorus insecticide), present in agrochemicals, were predominant in the river water, although concentrations were below the quality standards established by the EU Water-Framework-Directive. A general trend to increase concentration was observed after rain events, in particular for pesticides, possibly as a consequence of surface runoff.

Impact of an intense rainfall event on soil properties following a wildfire in a Mediterranean environment (North-East Spain).

PubMed

Francos, Marcos; Pereira, Paulo; Alcañiz, Meritxell; Mataix-Solera, Jorge; Úbeda, Xavier

2016-12-01

Intense rainfall events after severe wildfires can have an impact on soil properties, above all in the Mediterranean environment. This study seeks to examine the immediate impact and the effect after a year of an intense rainfall event on a Mediterranean forest affected by a high severity wildfire. The work analyses the following soil properties: soil aggregate stability, total nitrogen, total carbon, organic and inorganic carbon, the C/N ratio, carbonates, pH, electrical conductivity, extractable calcium, magnesium, sodium, potassium, available phosphorous and the sodium and potassium adsorption ratio (SPAR). We sampled soils in the burned area before, immediately after and one year after the rainfall event. The results showed that the intense rainfall event did not have an immediate impact on soil aggregate stability, but a significant difference was recorded one year after. The intense precipitation did not result in any significant changes in soil total nitrogen, total carbon, inorganic carbon, the C/N ratio and carbonates during the study period. Differences were only registered in soil organic carbon. The soil organic carbon content was significantly higher after the rainfall than in the other sampling dates. The rainfall event did increase soil pH, electrical conductivity, major cations, available phosphorous and the SPAR. One year after the fire, a significant decrease in soil aggregate stability was observed that can be attributed to high SPAR levels and human intervention, while the reduction in extractable elements can be attributed to soil leaching and vegetation consumption. Overall, the intense rainfall event, other post-fire rainfall events and human intervention did not have a detrimental impact on soil properties in all probability owing to the flat plot topography. Copyright © 2016 Elsevier B.V. All rights reserved.

Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.

PubMed

Tudor, Catalina O; Ross, Karen E; Li, Gang; Vijay-Shanker, K; Wu, Cathy H; Arighi, Cecilia N

2015-01-01

Protein phosphorylation is a reversible post-translational modification where a protein kinase adds a phosphate group to a protein, potentially regulating its function, localization and/or activity. Phosphorylation can affect protein-protein interactions (PPIs), abolishing interaction with previous binding partners or enabling new interactions. Extracting phosphorylation information coupled with PPI information from the scientific literature will facilitate the creation of phosphorylation interaction networks of kinases, substrates and interacting partners, toward knowledge discovery of functional outcomes of protein phosphorylation. Increasingly, PPI databases are interested in capturing the phosphorylation state of interacting partners. We have previously developed the eFIP (Extracting Functional Impact of Phosphorylation) text mining system, which identifies phosphorylated proteins and phosphorylation-dependent PPIs. In this work, we present several enhancements for the eFIP system: (i) text mining for full-length articles from the PubMed Central open-access collection; (ii) the integration of the RLIMS-P 2.0 system for the extraction of phosphorylation events with kinase, substrate and site information; (iii) the extension of the PPI module with new trigger words/phrases describing interactions and (iv) the addition of the iSimp tool for sentence simplification to aid in the matching of syntactic patterns. We enhance the website functionality to: (i) support searches based on protein roles (kinases, substrates, interacting partners) or using keywords; (ii) link protein entities to their corresponding UniProt identifiers if mapped and (iii) support visual exploration of phosphorylation interaction networks using Cytoscape. The evaluation of eFIP on full-length articles achieved 92.4% precision, 76.5% recall and 83.7% F-measure on 100 article sections. To demonstrate eFIP for knowledge extraction and discovery, we constructed phosphorylation-dependent interaction networks involving 14-3-3 proteins identified from cancer-related versus diabetes-related articles. Comparison of the phosphorylation interaction network of kinases, phosphoproteins and interactants obtained from eFIP searches, along with enrichment analysis of the protein set, revealed several shared interactions, highlighting common pathways discussed in the context of both diseases. © The Author(s) 2015. Published by Oxford University Press.

Role of atopy patch test for diagnosis of food allergy-related gastrointestinal symptoms in children.

PubMed

Boonyaviwat, Onsuree; Pacharn, Punchama; Jirapongsananuruk, Orathai; Vichyanond, Pakit; Visitsunthorn, Nualanong

2015-12-01

Double-blind, placebo-controlled food challenge is the gold standard for diagnosing food allergy. However, it is a time-consuming procedure and requires onsite medical supervision and resuscitating medicines and devices on hand. The objective of this study was to compare the atopy patch test (APT) with the oral food challenge test (OFC) in children with suspected food allergy-related gastrointestinal (GI) symptoms. A prospective self-controlled study enrolled children with a history of suspected food allergy-related GI symptoms. Skin prick test (SPT) and APT using lyophilized and commercial allergen extracts for cow's milk, egg, wheat, soy, and shrimp were evaluated, and OFC was performed. Thirty-nine patients (25 boys, median age 2.4 yrs) with 76 events of suspected food allergy-related GI symptoms were enrolled. SPT was positive in 11/76 events (14.5%). Sensitivity, specificity, predictive values, and likelihood ratio were calculated related to the food challenge outcome. Of 41 OFC, 30 (73.2%) were positive. APT using lyophilized allergen extracts yielded high sensitivity (80%) and high positive predictive value (85.7%). APT using commercial allergen extracts yielded low sensitivity (30%) but high specificity (90%). The negative predictive value of APT using lyophilized and commercial allergen extracts was 53.8% and 32.2%, respectively. All cases with positive APT using lyophilized allergen extracts together with positive SPT also had positive OFC. In contrast to commercial extracts, APT with lyophilized allergen extracts is reliable, safe, and maybe useful for the diagnosis of suspected food allergy-related GI symptoms in children. OFC is still needed in most of the cases. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Topical herbal therapies for treating osteoarthritis

PubMed Central

Cameron, Melainie; Chrubasik, Sigrun

2014-01-01

Background Before extraction and synthetic chemistry were invented, musculoskeletal complaints were treated with preparations from medicinal plants. They were either administered orally or topically. In contrast to the oral medicinal plant products, topicals act in part as counterirritants or are toxic when given orally. Objectives To update the previous Cochrane review of herbal therapy for osteoarthritis from 2000 by evaluating the evidence on effectiveness for topical medicinal plant products. Search methods Databases for mainstream and complementary medicine were searched using terms to include all forms of arthritis combined with medicinal plant products. We searched electronic databases (Cochrane Central Register of Controlled Trials (CENTRAL),MEDLINE, EMBASE, AMED, CINAHL, ISI Web of Science, World Health Organization Clinical Trials Registry Platform) to February 2013, unrestricted by language. We also searched the reference lists from retrieved trials. Selection criteria Randomised controlled trials of herbal interventions used topically, compared with inert (placebo) or active controls, in people with osteoarthritis were included. Data collection and analysis Two review authors independently selected trials for inclusion, assessed the risk of bias of included studies and extracted data. Main results Seven studies (seven different medicinal plant interventions; 785 participants) were included. Single studies (five studies, six interventions) and non-comparable studies (two studies, one intervention) precluded pooling of results. Moderate evidence from a single study of 174 people with hand osteoarthritis indicated that treatment with Arnica extract gel probably results in similar benefits as treatment with ibuprofen (non-steroidal anti-inflammatory drug) with a similar number of adverse events. Mean pain in the ibuprofen group was 44.2 points on a 100 point scale; treatment with Arnica gel reduced the pain by 4 points after three weeks: mean difference (MD) −3.8 points (95% confidence intervals (CI) −10.1 to 2.5), absolute reduction 4% (10% reduction to 3% increase). Hand function was 7.5 points on a 30 point scale in the ibuprofen-treated group; treatment with Arnica gel reduced function by 0.4 points (MD −0.4, 95% CI −1.75 to 0.95), absolute improvement 1% (6% improvement to 3% decline)). Total adverse events were higher in the Arnica gel group (13% compared to 8% in the ibuprofen group): relative risk (RR) 1.65 (95% CI 0.72 to 3.76). Moderate quality evidence from a single trial of 99 people with knee osteoarthritis indicated that compared with placebo, Capsicum extract gel probably does not improve pain or knee function, and is commonly associated with treatment-related adverse events including skin irritation and a burning sensation. At four weeks follow-up, mean pain in the placebo group was 46 points on a 100 point scale; treatment with Capsicum extract reduced pain by 1 point (MD −1, 95%CI −6.8 to 4.8), absolute reduction of 1%(7%reduction to 5% increase). Mean knee function in the placebo group was 34.8 points on a 96 point scale at four weeks; treatment with Capsicum extract improved function by a mean of 2.6 points (MD −2.6, 95% CI −9.5 to 4.2), an absolute improvement of 3% (10% improvement to 4% decline). Adverse event rates were greater in the Capsicum extract group (80% compared with 20% in the placebo group, rate ratio 4.12, 95% CI 3.30 to 5.17). The number needed to treat to result in adverse events was 2 (95% CI 1 to 2). Moderate evidence from a single trial of 220 people with knee osteoarthritis suggested that comfrey extract gel probably improves pain without increasing adverse events. At three weeks, the mean pain in the placebo group was 83.5 points on a 100 point scale. Treatment with comfrey reduced pain by a mean of 41.5 points (MD −41.5, 95% CI −48 to −34), an absolute reduction of 42% (34% to 48% reduction). Function was not reported. Adverse events were similar: 6%(7/110) reported adverse events in the comfrey group compared with 14% (15/110) in the placebo group (RR 0.47, 95% CI 0.20 to 1.10). Although evidence from a single trial indicated that adhesive patches containing Chinese herbal mixtures FNZG and SJG may improve pain and function, the clinical applicability of these findings are uncertain because participants were only treated and followed up for seven days. We are also uncertain if other topical herbal products (Marhame-Mafasel compress, stinging nettle leaf) improve osteoarthritis symptoms due to the very low quality evidence from single trials. No serious side effects were reported. Authors’ conclusions Although the mechanism of action of the topical medicinal plant products provides a rationale basis for their use in the treatment of osteoarthritis, the quality and quantity of current research studies of effectiveness are insufficient. Arnica gel probably improves symptoms as effectively as a gel containing non-steroidal anti-inflammatory drug, but with no better (and possibly worse) adverse event profile. Comfrey extract gel probably improves pain, and Capsicum extract gel probably will not improve pain or function at the doses examined in this review. Further high quality, fully powered studies are required to confirm the trends of effectiveness identifed in studies so far. PMID:23728701

Serious adverse events after HPV vaccination: a critical review of randomized trials and post-marketing case series.

PubMed

Martínez-Lavín, Manuel; Amezcua-Guerra, Luis

2017-10-01

This article critically reviews HPV vaccine serious adverse events described in pre-licensure randomized trials and in post-marketing case series. HPV vaccine randomized trials were identified in PubMed. Safety data were extracted. Post-marketing case series describing HPV immunization adverse events were reviewed. Most HPV vaccine randomized trials did not use inert placebo in the control group. Two of the largest randomized trials found significantly more severe adverse events in the tested HPV vaccine arm of the study. Compared to 2871 women receiving aluminum placebo, the group of 2881 women injected with the bivalent HPV vaccine had more deaths on follow-up (14 vs. 3, p = 0.012). Compared to 7078 girls injected with the 4-valent HPV vaccine, 7071 girls receiving the 9-valent dose had more serious systemic adverse events (3.3 vs. 2.6%, p = 0.01). For the 9-valent dose, our calculated number needed to seriously harm is 140 (95% CI, 79–653) [DOSAGE ERROR CORRECTED] . The number needed to vaccinate is 1757 (95% CI, 131 to infinity). Practically, none of the serious adverse events occurring in any arm of both studies were judged to be vaccine-related. Pre-clinical trials, post-marketing case series, and the global drug adverse reaction database (VigiBase) describe similar post-HPV immunization symptom clusters. Two of the largest randomized HPV vaccine trials unveiled more severe adverse events in the tested HPV vaccine arm of the study. Nine-valent HPV vaccine has a worrisome number needed to vaccinate/number needed to harm quotient. Pre-clinical trials and post-marketing case series describe similar post-HPV immunization symptoms.

Legionnaires' Disease in Hotels and Passenger Ships: A Systematic Review of Evidence, Sources, and Contributing Factors.

PubMed

Mouchtouri, Varvara A; Rudge, James W

2015-01-01

Travel-associated Legionnaires' disease (LD) is a serious problem, and hundreds of cases are reported every year among travelers who stayed at hotels, despite the efforts of international and governmental authorities and hotel operators to prevent additional cases. A systematic review of travel-associated LD events (cases, clusters, outbreaks) and of environmental studies of Legionella contamination in accommodation sites was conducted. Two databases were searched (PubMed and EMBASE). Data were extracted from 50 peer-reviewed articles that provided microbiological and epidemiological evidence for linking the accommodation sites with LD. The strength of evidence was classified as strong, possible, and probable. Three of the 21 hotel-associated events identified and four of nine ship-associated events occurred repeatedly on the same site. Of 197 hotel-associated cases, 158 (80.2%) were linked to hotel cooling towers and/or potable water systems. Ship-associated cases were most commonly linked to hot tubs (59/83, 71.1%). Common contributing factors included inadequate disinfection, maintenance, and monitoring; water stagnation; poor temperature control; and poor ventilation. Across all 30 events, Legionella concentrations in suspected water sources were >10,000 cfu/L, <10,000 cfu/L, and unknown in 11, 3, and 13 events, respectively. In five events, Legionella was not detected only after repeated disinfections. In environmental studies, Legionella was detected in 81.1% of ferries (23/28) and 48.9% of hotels (587/1,200), while all 12 cruise ships examined were negative. This review highlights the need for LD awareness strategies targeting operators of accommodation sites. Increased standardization of LD investigation and reporting, and more rigorous follow-up of LD events, would help generate stronger, more comparable evidence on LD sources, contributing factors, and control measure effectiveness. © 2015 International Society of Travel Medicine.

Real-world experience with 0.2 μg/day fluocinolone acetonide intravitreal implant (ILUVIEN) in the United Kingdom

PubMed Central

Bailey, C; Chakravarthy, U; Lotery, A; Menon, G; Talks, J; Bailey, Clare; Kamal, Aintree; Ghanchi, Faruque; Khan, Calderdale; Johnston, Robert; McKibbin, Martin; Varma, Atul; Mustaq, Bushra; Brand, Christopher; Talks, James; Glover,, Nick

2017-01-01

Aims To compare safety outcomes and visual function data acquired in the real-world setting with FAME study results in eyes treated with 0.2 μg/day fluocinolone acetonide (FAc). Methods Fourteen UK clinical sites contributed to pseudoanonymised data collected using the same electronic medical record system. Data pertaining to eyes treated with FAc implant for diabetic macular oedema (DMO) was extracted. Intraocular pressure (IOP)-related adverse events were defined as use of IOP-lowering medication, any rise in IOP>30 mm Hg, or glaucoma surgery. Other measured outcomes included visual acuity, central subfield thickness (CSFT) changes and use of concomitant medications. Results In total, 345 eyes had a mean follow-up of 428 days. Overall, 13.9% of patients required IOP-lowering drops (included initiation, addition and switching of current drops), 7.2% had IOP elevation >30 mm Hg and 0.3% required glaucoma surgery. In patients with prior steroid exposure and no prior IOP-related event, there were no new IOP-related events. In patients without prior steroid use and without prior IOP-related events, 10.3% of eyes required IOP-lowering medication and 4.3% exhibited IOP >30 mm Hg at some point during follow-up. At 24 months, mean best-recorded visual acuity increased from 51.9 to 57.2 letters and 20.8% achieved ≥15-letter improvement. Mean CSFT reduced from 451.2 to 355.5 μm. Conclusions While overall IOP-related emergent events were observed in similar frequency to FAME, no adverse events were seen in the subgroup with prior steroid exposure and no prior IOP events. Efficacy findings confirm that the FAc implant is a useful treatment option for chronic DMO. PMID:28737758

Industrial application of semantic process mining

NASA Astrophysics Data System (ADS)

Espen Ingvaldsen, Jon; Atle Gulla, Jon

2012-05-01

Process mining relates to the extraction of non-trivial and useful information from information system event logs. It is a new research discipline that has evolved significantly since the early work on idealistic process logs. Over the last years, process mining prototypes have incorporated elements from semantics and data mining and targeted visualisation techniques that are more user-friendly to business experts and process owners. In this article, we present a framework for evaluating different aspects of enterprise process flows and address practical challenges of state-of-the-art industrial process mining. We also explore the inherent strengths of the technology for more efficient process optimisation.

Classifying and Tracking Dust Plumes from Passive Remote Sensing

NASA Astrophysics Data System (ADS)

Bachl, Fabian E.; Garbe, Christoph S.

2012-03-01

Recent studies emphasize the role mineral dust aerosols play in terms of the earth's climate system, its radiation budget and microbial nutrition cycles. In order to gain further insight into the genesis and long term characteristics of dust events, processing setellite imagery is inevitable. We propose a fully Bayesian multispectral classification method that significantly facilitates this task. Using MSG-SEVIRI imagery we show that our technique allows to extract dust activity well enough to pave the way for a tracking scheme. Based on this procedure we derive an approach to identify regions that are likely to be the origin of emerging dust plumes.

The influence of systemic hemodynamics and oxygen transport on cerebral oxygen saturation in neonates after the Norwood procedure.

PubMed

Li, Jia; Zhang, Gencheng; Holtby, Helen; Guerguerian, Anne-Marie; Cai, Sally; Humpl, Tilman; Caldarone, Christopher A; Redington, Andrew N; Van Arsdell, Glen S

2008-01-01

Ischemic brain injury is an important morbidity in neonates after the Norwood procedure. Its relationship to systemic hemodynamic oxygen transport is poorly understood. Sixteen neonates undergoing the Norwood procedure were studied. Continuous cerebral oxygen saturation was measured by near-infrared spectroscopy. Continuous oxygen consumption was measured by respiratory mass spectrometry. Pulmonary and systemic blood flow, systemic vascular resistance, oxygen delivery, and oxygen extraction ratio were derived with measurements of arterial, and superior vena cava and pulmonary venous gases and pressures at 2- to 4-hour intervals during the first 72 hours in the intensive care unit. Mean cerebral oxygen saturation was 66% +/- 12% before the operation, reduced to 51% +/- 13% on arrival in the intensive care unit, and remained low during the first 8 hours; it increased to 56% +/- 9% at 72 hours, still significantly lower than the preoperative level (P < .05). Postoperatively, cerebral oxygen saturation was closely and positively correlated with systemic arterial pressure, arterial oxygen saturation, and arterial oxygen tension and negatively with oxygen extraction ratio (P < .0001 for all). Cerebral oxygen saturation was moderately and positively correlated with systemic blood flow and oxygen delivery (P < .0001 for both). It was weakly and positively correlated with pulmonary blood flow (P = .001) and hemoglobin (P = .02) and negatively correlated with systemic vascular resistance (P = .003). It was not correlated with oxygen consumption (P > .05). Cerebral oxygen saturation decreased significantly in neonates during the early postoperative period after the Norwood procedure and was significantly influenced by systemic hemodynamic and metabolic events. As such, hemodynamic interventions to modify systemic oxygen transport may provide further opportunities to reduce the risk of cerebral ischemia and improve neurodevelopmental outcomes.

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.

Characterization of extreme flood and drought events in Singapore and investigation of their relationships with ENSO

NASA Astrophysics Data System (ADS)

Li, Xin; Babovic, Vladan

2016-04-01

Flood and drought are hydrologic extreme events that have significant impact on human and natural systems. Characterization of flood and drought in terms of their start, duration and strength, and investigation of the impact of natural climate variability (i.e., ENSO) and anthropogenic climate change on them can help decision makers to facilitate adaptions to mitigate potential enormous economic costs. To date, numerous studies in this area have been conducted, however, they are primarily focused on extra-tropical regions. Therefore, this study presented a detailed framework to characterize flood and drought events in a tropical urban city-state (i.e., Singapore), based on daily data from 26 precipitation stations. Flood and drought events are extracted from standardized precipitation anomalies from monthly to seasonal time scales. Frequency, duration and magnitude of flood and drought at all the stations are analyzed based on crossing theory. In addition, spatial variation of flood and drought characteristics in Singapore is investigated using ordinary kriging method. Lastly, the impact of ENSO condition on flood and drought characteristics is analyzed using regional regression method. The results show that Singapore can be prone to extreme flood and drought events at both monthly and seasonal time scales. ENSO has significant influence on flood and drought characteristics in Singapore, but mainly during the South West Monsoon season. During the El Niño phase, drought can become more extreme. The results have implications for water management practices in Singapore.

Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database.

PubMed

Dereymaeker, Anneleen; Ansari, Amir H; Jansen, Katrien; Cherian, Perumpillichira J; Vervisch, Jan; Govaert, Paul; De Wispelaere, Leen; Dielman, Charlotte; Matic, Vladimir; Dorado, Alexander Caicedo; De Vos, Maarten; Van Huffel, Sabine; Naulaers, Gunnar

2017-09-01

To assess interrater agreement based on majority voting in visual scoring of neonatal seizures. An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on 'majority voting' and interrater agreement was estimated using Fleiss' Kappa. The influences of different factors on agreement were determined. 1919 Events extracted from 280h EEG of 71 neonates were reviewed by 4 raters. Majority voting was applied to assign a seizure/non-seizure classification. 44% of events were classified with high, 36% with moderate, and 20% with poor agreement, resulting in a Kappa value of 0.39. 68% of events were labelled as seizures, and in 46%, all raters were convinced about electrographic seizures. The most common seizure duration was <30s. Raters agreed best for seizures lasting 60-120s. There was a significant difference in electrographic characteristics of seizures versus dubious events, with seizures having longer duration, higher power and amplitude. There is a wide variability in identifying rhythmic ictal and non-ictal EEG events, and only the most robust ictal patterns are consistently agreed upon. Database composition and electrographic characteristics are important factors that influence interrater agreement. The use of well-described databases and input of different experts will improve neonatal EEG interpretation and help to develop uniform seizure definitions, useful for evidence-based studies of seizure recognition and management. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Stable individual characteristics in the perception of multiple embedded patterns in multistable auditory stimuli

PubMed Central

Denham, Susan; Bõhm, Tamás M.; Bendixen, Alexandra; Szalárdy, Orsolya; Kocsis, Zsuzsanna; Mill, Robert; Winkler, István

2014-01-01

The ability of the auditory system to parse complex scenes into component objects in order to extract information from the environment is very robust, yet the processing principles underlying this ability are still not well understood. This study was designed to investigate the proposal that the auditory system constructs multiple interpretations of the acoustic scene in parallel, based on the finding that when listening to a long repetitive sequence listeners report switching between different perceptual organizations. Using the “ABA-” auditory streaming paradigm we trained listeners until they could reliably recognize all possible embedded patterns of length four which could in principle be extracted from the sequence, and in a series of test sessions investigated their spontaneous reports of those patterns. With the training allowing them to identify and mark a wider variety of possible patterns, participants spontaneously reported many more patterns than the ones traditionally assumed (Integrated vs. Segregated). Despite receiving consistent training and despite the apparent randomness of perceptual switching, we found individual switching patterns were idiosyncratic; i.e., the perceptual switching patterns of each participant were more similar to their own switching patterns in different sessions than to those of other participants. These individual differences were found to be preserved even between test sessions held a year after the initial experiment. Our results support the idea that the auditory system attempts to extract an exhaustive set of embedded patterns which can be used to generate expectations of future events and which by competing for dominance give rise to (changing) perceptual awareness, with the characteristics of pattern discovery and perceptual competition having a strong idiosyncratic component. Perceptual multistability thus provides a means for characterizing both general mechanisms and individual differences in human perception. PMID:24616656

Stable individual characteristics in the perception of multiple embedded patterns in multistable auditory stimuli.

PubMed

Denham, Susan; Bõhm, Tamás M; Bendixen, Alexandra; Szalárdy, Orsolya; Kocsis, Zsuzsanna; Mill, Robert; Winkler, István

2014-01-01

The ability of the auditory system to parse complex scenes into component objects in order to extract information from the environment is very robust, yet the processing principles underlying this ability are still not well understood. This study was designed to investigate the proposal that the auditory system constructs multiple interpretations of the acoustic scene in parallel, based on the finding that when listening to a long repetitive sequence listeners report switching between different perceptual organizations. Using the "ABA-" auditory streaming paradigm we trained listeners until they could reliably recognize all possible embedded patterns of length four which could in principle be extracted from the sequence, and in a series of test sessions investigated their spontaneous reports of those patterns. With the training allowing them to identify and mark a wider variety of possible patterns, participants spontaneously reported many more patterns than the ones traditionally assumed (Integrated vs. Segregated). Despite receiving consistent training and despite the apparent randomness of perceptual switching, we found individual switching patterns were idiosyncratic; i.e., the perceptual switching patterns of each participant were more similar to their own switching patterns in different sessions than to those of other participants. These individual differences were found to be preserved even between test sessions held a year after the initial experiment. Our results support the idea that the auditory system attempts to extract an exhaustive set of embedded patterns which can be used to generate expectations of future events and which by competing for dominance give rise to (changing) perceptual awareness, with the characteristics of pattern discovery and perceptual competition having a strong idiosyncratic component. Perceptual multistability thus provides a means for characterizing both general mechanisms and individual differences in human perception.

Polyvinylidene fluoride sensor-based method for unconstrained snoring detection.

PubMed

Hwang, Su Hwan; Han, Chung Min; Yoon, Hee Nam; Jung, Da Woon; Lee, Yu Jin; Jeong, Do-Un; Park, Kwang Suk

2015-07-01

We established and tested a snoring detection method using a polyvinylidene fluoride (PVDF) sensor for accurate, fast, and motion-artifact-robust monitoring of snoring events during sleep. Twenty patients with obstructive sleep apnea participated in this study. The PVDF sensor was located between a mattress cover and mattress, and the patients' snoring signals were unconstrainedly measured with the sensor during polysomnography. The power ratio and peak frequency from the short-time Fourier transform were used to extract spectral features from the PVDF data. A support vector machine was applied to the spectral features to classify the data into either the snore or non-snore class. The performance of the method was assessed using manual labelling by three human observers as a reference. For event-by-event snoring detection, PVDF data that contained 'snoring' (SN), 'snoring with movement' (SM), and 'normal breathing' epochs were selected for each subject. As a result, the overall sensitivity and the positive predictive values were 94.6% and 97.5%, respectively, and there was no significant difference between the SN and SM results. The proposed method can be applied in both residential and ambulatory snoring monitoring systems.

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Convolutional neural networks for event-related potential detection: impact of the architecture.

PubMed

Cecotti, H

2017-07-01

The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

Five-Body Cluster Structure of the Double-{Lambda} Hypernucleus {sub {Lambda}{Lambda}}{sup 11}Be

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

Hiyama, E.; Kamimura, M.; Yamamoto, Y.

2010-05-28

Energy levels of the double {Lambda} hypernucleus, {sub {Lambda}{Lambda}}{sup 11}Be are calculated within the framework of a {alpha}{alpha}n{Lambda}{Lambda} five-body model. Interactions between constituent particles are determined so as to reproduce reasonably the observed low-energy properties of the {alpha}{alpha}, {alpha}{alpha}n nuclei and the existing data for {Lambda}-binding energies of the {alpha}{Lambda}, {alpha}{alpha}{Lambda}, {alpha}n{Lambda}, and {alpha}{alpha}n{Lambda} systems. An effective {Lambda}{Lambda} interaction is constructed so as to reproduce, within the {alpha}{Lambda}{Lambda} three-body model, the B{sub {Lambda}{Lambda}}of {sub {Lambda}{Lambda}}{sup 6}He, which was extracted from the emulsion experiment, the NAGARA event. With no adjustable parameters for the {alpha}{alpha}n{Lambda}{Lambda} system, B{sub {Lambda}{Lambda}}of the ground and boundmore » excited states of {sub {Lambda}{Lambda}}{sup 11}Be are calculated with the Gaussian expansion method. The Hida event, recently observed at KEK-E373 experiment, is interpreted as an observation of the ground state of the {sub {Lambda}{Lambda}}{sup 11}Be.« less

A pro-apoptotic 15-kDa protein from Bacopa monnieri activates caspase-3 and downregulates Bcl-2 gene expression in mouse mammary carcinoma cells.

PubMed

Kalyani, Manjula Ishwara; Lingaraju, Sheela Mysore; Salimath, Bharathi P

2013-01-01

In diseases such as cancer, induction of apoptosis has been a new target for mechanism-based drug discovery. The central component of the process of apoptosis is a proteolytic system involving a family of proteases called caspases. Apoptosis involves characteristic morphological and biochemical events ultimately leading to cell demise. Apoptotic induction is evidently central to the mechanism of action of plant-derived anticancer drugs. Extract of the medicinal plant, Bacopa monnieri, inhibits tumor cell proliferation and accumulation of malignant ascites fluid. The crude sample when subjected to Soxhlet extraction yielded different solvent extracts of which the aqueous extract showed biological activity of apoptosis in Ehrlich ascites tumor cell lines (EAT). Bacopa monnieri water extract (BMWE) treatment of EAT cells produced apoptotic morphological characteristics and in-vivo DNA fragmentation, which is due to the activity of an endogenous endonuclease. The endonuclease responsible for DNA fragmentation acts downstream of caspase-3 activity and is also referred to as caspase-activated DNase (CAD). The CAD constitutively expressed in the cell cytoplasm is translocated into the nucleus upon BMWE treatment, as verified by Western blotting, leading to DNA fragmentation and to programmed cell death. The expression of the pro-apoptotic gene Bax was increased and the expression of the anti-apoptotic gene Bcl-2 was decreased by BMWE treatment. Considering the above results, BMWE was able induce apoptosis in EAT cells via Bax-related caspase-3 activation. This may provide experimental data for the further clinical use of BMWE in cancer.

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.

Adverse drug event reporting systems: a systematic review

PubMed Central

Peddie, David; Wickham, Maeve E.; Badke, Katherin; Small, Serena S.; Doyle‐Waters, Mary M.; Balka, Ellen; Hohl, Corinne M.

2016-01-01

Aim Adverse drug events (ADEs) are harmful and unintended consequences of medications. Their reporting is essential for drug safety monitoring and research, but it has not been standardized internationally. Our aim was to synthesize information about the type and variety of data collected within ADE reporting systems. Methods We developed a systematic search strategy, applied it to four electronic databases, and completed an electronic grey literature search. Two authors reviewed titles and abstracts, and all eligible full‐texts. We extracted data using a standardized form, and discussed disagreements until reaching consensus. We synthesized data by collapsing data elements, eliminating duplicate fields and identifying relationships between reporting concepts and data fields using visual analysis software. Results We identified 108 ADE reporting systems containing 1782 unique data fields. We mapped them to 33 reporting concepts describing patient information, the ADE, concomitant and suspect drugs, and the reporter. While reporting concepts were fairly consistent, we found variability in data fields and corresponding response options. Few systems clarified the terminology used, and many used multiple drug and disease dictionaries such as the Medical Dictionary for Regulatory Activities (MedDRA). Conclusion We found substantial variability in the data fields used to report ADEs, limiting the comparability of ADE data collected using different reporting systems, and undermining efforts to aggregate data across cohorts. The development of a common standardized data set that can be evaluated with regard to data quality, comparability and reporting rates is likely to optimize ADE data and drug safety surveillance. PMID:27016266

Adverse drug event reporting systems: a systematic review.

PubMed

Bailey, Chantelle; Peddie, David; Wickham, Maeve E; Badke, Katherin; Small, Serena S; Doyle-Waters, Mary M; Balka, Ellen; Hohl, Corinne M

2016-07-01

Adverse drug events (ADEs) are harmful and unintended consequences of medications. Their reporting is essential for drug safety monitoring and research, but it has not been standardized internationally. Our aim was to synthesize information about the type and variety of data collected within ADE reporting systems. We developed a systematic search strategy, applied it to four electronic databases, and completed an electronic grey literature search. Two authors reviewed titles and abstracts, and all eligible full-texts. We extracted data using a standardized form, and discussed disagreements until reaching consensus. We synthesized data by collapsing data elements, eliminating duplicate fields and identifying relationships between reporting concepts and data fields using visual analysis software. We identified 108 ADE reporting systems containing 1782 unique data fields. We mapped them to 33 reporting concepts describing patient information, the ADE, concomitant and suspect drugs, and the reporter. While reporting concepts were fairly consistent, we found variability in data fields and corresponding response options. Few systems clarified the terminology used, and many used multiple drug and disease dictionaries such as the Medical Dictionary for Regulatory Activities (MedDRA). We found substantial variability in the data fields used to report ADEs, limiting the comparability of ADE data collected using different reporting systems, and undermining efforts to aggregate data across cohorts. The development of a common standardized data set that can be evaluated with regard to data quality, comparability and reporting rates is likely to optimize ADE data and drug safety surveillance. © 2016 The British Pharmacological Society.

Development of a behavioural marker system for scrub practitioners' non-technical skills (SPLINTS system).

PubMed

Mitchell, Lucy; Flin, Rhona; Yule, Steven; Mitchell, Janet; Coutts, Kathy; Youngson, George

2013-04-01

Adverse events still occur despite ongoing efforts to reduce harm to patients. Contributory factors to adverse events are often due to limitations in clinicians' non-technical skills (e.g. communication, situation awareness), rather than deficiencies in technical competence. We developed a behavioural rating system to provide a structured means for teaching and assessing scrub practitioners' (i.e. nurse, technician, operating department practitioner) non-technical skills. Psychologists facilitated focus groups (n = 4) with experienced scrub practitioners (n = 16; 4 in each group) to develop a preliminary taxonomy. Focus groups reviewed lists of non-technical-skill-related behaviours that were extracted from an interview study. The focus groups labelled skill categories and elements and also provided examples of good and poor behaviours for those skills. An expert panel (n = 2 psychologists; n = 1 expert nurse) then used an iterative process to individually and collaboratively review and refine those data to produce a prototype skills taxonomy. A preliminary taxonomy containing eight non-technical skill categories with 28 underlying elements was produced. The expert panel reduced this to three categories (situation awareness, communication and teamwork, task management), each with three underlying elements. The system was called the Scrub Practitioners' List of Intraoperative Non-Technical Skills system. A scoring system and a user handbook were also developed. A prototype behavioural rating system for scrub practitioners' non-technical skills was developed, to aid in teaching and providing formative assessment. This important aspect of performance is not currently explicitly addressed in any educational route to qualify as a scrub practitioner. © 2012 Blackwell Publishing Ltd.

Immune-related adverse events for anti-PD-1 and anti-PD-L1 drugs: systematic review and meta-analysis

PubMed Central

Baxi, Shrujal; Yang, Annie; Gennarelli, Renee L; Khan, Niloufer; Wang, Ziwei; Boyce, Lindsay

2018-01-01

Abstract Objective To evaluate rates of serious organ specific immune-related adverse events, general adverse events related to immune activation, and adverse events consistent with musculoskeletal problems for anti-programmed cell death 1 (PD-1) drugs overall and compared with control treatments. Design Systematic review and meta-analysis. Data sources Medline, Embase, Cochrane Library, Web of Science, and Scopus searched to 16 March 2017 and combined with data from ClinicalTrials.gov. Study selection Eligible studies included primary clinical trial data on patients with cancer with recurrent or metastatic disease. Data extraction Three independent investigators extracted data on adverse events from ClinicalTrials.gov and the published studies. Risk of bias was assessed using the Cochrane tool by three independent investigators. Results 13 relevant studies were included; adverse event data were available on ClinicalTrials.gov for eight. Studies compared nivolumab (n=6), pembrolizumab (5), or atezolizumab (2) with chemotherapy (11), targeted drugs (1), or both (1). Serious organ specific immune-related adverse events were rare, but compared with standard treatment, rates of hypothyroidism (odds ratio 7.56, 95% confidence interval 4.53 to 12.61), pneumonitis (5.37, 2.73 to 10.56), colitis (2.88, 1.30 to 6.37), and hypophysitis (3.38, 1.02 to 11.08) were increased with anti-PD-1 drugs. Of the general adverse events related to immune activation, only the rate of rash (2.34, 2.73 to 10.56) increased. Incidence of fatigue (32%) and diarrhea (19%) were high but similar to control. Reporting of adverse events consistent with musculoskeletal problems was inconsistent; rates varied but were over 20% in some studies for arthraligia and back pain. Conclusions Organ specific immune-related adverse events are uncommon with anti-PD-1 drugs but the risk is increased compared with control treatments. General adverse events related to immune activation are largely similar. Adverse events consistent with musculoskeletal problems are inconsistently reported but adverse events may be common. PMID:29540345

Cavity Optical Pulse Extraction: ultra-short pulse generation as seeded Hawking radiation.

PubMed

Eilenberger, Falk; Kabakova, Irina V; de Sterke, C Martijn; Eggleton, Benjamin J; Pertsch, Thomas

2013-01-01

We show that light trapped in an optical cavity can be extracted from that cavity in an ultrashort burst by means of a trigger pulse. We find a simple analytic description of this process and show that while the extracted pulse inherits its pulse length from that of the trigger pulse, its wavelength can be completely different. Cavity Optical Pulse Extraction is thus well suited for the development of ultrashort laser sources in new wavelength ranges. We discuss similarities between this process and the generation of Hawking radiation at the optical analogue of an event horizon with extremely high Hawking temperature. Our analytic predictions are confirmed by thorough numerical simulations.

Cavity Optical Pulse Extraction: ultra-short pulse generation as seeded Hawking radiation

PubMed Central

Eilenberger, Falk; Kabakova, Irina V.; de Sterke, C. Martijn; Eggleton, Benjamin J.; Pertsch, Thomas

2013-01-01

We show that light trapped in an optical cavity can be extracted from that cavity in an ultrashort burst by means of a trigger pulse. We find a simple analytic description of this process and show that while the extracted pulse inherits its pulse length from that of the trigger pulse, its wavelength can be completely different. Cavity Optical Pulse Extraction is thus well suited for the development of ultrashort laser sources in new wavelength ranges. We discuss similarities between this process and the generation of Hawking radiation at the optical analogue of an event horizon with extremely high Hawking temperature. Our analytic predictions are confirmed by thorough numerical simulations. PMID:24060831

Method and system for analyzing and classifying electronic information

DOEpatents

McGaffey, Robert W.; Bell, Michael Allen; Kortman, Peter J.; Wilson, Charles H.

2003-04-29

A data analysis and classification system that reads the electronic information, analyzes the electronic information according to a user-defined set of logical rules, and returns a classification result. The data analysis and classification system may accept any form of computer-readable electronic information. The system creates a hash table wherein each entry of the hash table contains a concept corresponding to a word or phrase which the system has previously encountered. The system creates an object model based on the user-defined logical associations, used for reviewing each concept contained in the electronic information in order to determine whether the electronic information is classified. The data analysis and classification system extracts each concept in turn from the electronic information, locates it in the hash table, and propagates it through the object model. In the event that the system can not find the electronic information token in the hash table, that token is added to a missing terms list. If any rule is satisfied during propagation of the concept through the object model, the electronic information is classified.

Learning multisensory representations for auditory-visual transfer of sequence category knowledge: a probabilistic language of thought approach.

PubMed

Yildirim, Ilker; Jacobs, Robert A

2015-06-01

If a person is trained to recognize or categorize objects or events using one sensory modality, the person can often recognize or categorize those same (or similar) objects and events via a novel modality. This phenomenon is an instance of cross-modal transfer of knowledge. Here, we study the Multisensory Hypothesis which states that people extract the intrinsic, modality-independent properties of objects and events, and represent these properties in multisensory representations. These representations underlie cross-modal transfer of knowledge. We conducted an experiment evaluating whether people transfer sequence category knowledge across auditory and visual domains. Our experimental data clearly indicate that we do. We also developed a computational model accounting for our experimental results. Consistent with the probabilistic language of thought approach to cognitive modeling, our model formalizes multisensory representations as symbolic "computer programs" and uses Bayesian inference to learn these representations. Because the model demonstrates how the acquisition and use of amodal, multisensory representations can underlie cross-modal transfer of knowledge, and because the model accounts for subjects' experimental performances, our work lends credence to the Multisensory Hypothesis. Overall, our work suggests that people automatically extract and represent objects' and events' intrinsic properties, and use these properties to process and understand the same (and similar) objects and events when they are perceived through novel sensory modalities.

Ar-39-Ar-40 Evidence for Early Impact Events on the LL Parent Body

NASA Technical Reports Server (NTRS)

Dixon, E. T.; Bogard, D. D.; Garrison, D. H.; Rubin, A. E.

2006-01-01

We determined Ar-39-Ar-40 ages of eight LL chondrites, and one igneous inclusion from an LL chondrite, with the object of understanding the thermal history of the LL-chondrite parent body. The meteorites in this study have a range of petrographic types from LL3.3 to LL6, and shock stages from S1 to S4. These meteorites reveal a range of K-Ar ages from 23.66 to 24.50 Ga, and peak ages from 23.74 to 24.55 Ga. Significantly, three of the eight chondrites (LL4, 5, 6) have K-Ar ages of -4.27 Ga. One of these (MIL99301) preserves an Ar-39-Ar-40 age of 4.23 +/- 0.03 Ga from low-temperature extractions, and an older age of 4.52 +/- 0.08 Ga from the highest temperature extractions. In addition, an igneous-textured impact melt DOM85505,22 has a peak Ar-39-Ar-40 age of >= 4.27 Ga. We interpret these results as evidence for impact events that occurred at about 4.27 Ga on the LL parent body that produced local impact melts, reset the Ar-39-Ar-40 ages of some meteorites, and exhumed (or interred) others, resulting in a range of cooling ages. The somewhat younger peak age of 3.74 Ga from GR095658 (LL3.3) suggests an additional impact event close to timing of impact-reset ages of some other ordinary chondrites between 3.6-3.8 Ga. The results from MIL99301 suggest that some apparently unshocked (Sl) chondrites may have substantially reset Ar-39-Ar-40 ages. A previous petrographic investigation of MIL99301 suggested that reheating to temperatures less than or equal to type 4 petrographic conditions (600C) caused fractures in olivine to anneal, resulting in a low apparent shock stage of S1 (unshocked). The Ar-39-Ar-40 age spectrum of MIL99301 is consistent with this interpretation. Older ages from high-T extractions may date an earlier impact event at 4.52 +/- 0.08 Ga, whereas younger ages from lower-T extractions date a later impact event at 4.23 Ar-39-Ar-40 0.03 Ga that may have caused annealing of feldspar and olivine

Classification of single-trial auditory events using dry-wireless EEG during real and motion simulated flight.

PubMed

Callan, Daniel E; Durantin, Gautier; Terzibas, Cengiz

2015-01-01

Application of neuro-augmentation technology based on dry-wireless EEG may be considerably beneficial for aviation and space operations because of the inherent dangers involved. In this study we evaluate classification performance of perceptual events using a dry-wireless EEG system during motion platform based flight simulation and actual flight in an open cockpit biplane to determine if the system can be used in the presence of considerable environmental and physiological artifacts. A passive task involving 200 random auditory presentations of a chirp sound was used for evaluation. The advantage of this auditory task is that it does not interfere with the perceptual motor processes involved with piloting the plane. Classification was based on identifying the presentation of a chirp sound vs. silent periods. Evaluation of Independent component analysis (ICA) and Kalman filtering to enhance classification performance by extracting brain activity related to the auditory event from other non-task related brain activity and artifacts was assessed. The results of permutation testing revealed that single trial classification of presence or absence of an auditory event was significantly above chance for all conditions on a novel test set. The best performance could be achieved with both ICA and Kalman filtering relative to no processing: Platform Off (83.4% vs. 78.3%), Platform On (73.1% vs. 71.6%), Biplane Engine Off (81.1% vs. 77.4%), and Biplane Engine On (79.2% vs. 66.1%). This experiment demonstrates that dry-wireless EEG can be used in environments with considerable vibration, wind, acoustic noise, and physiological artifacts and achieve good single trial classification performance that is necessary for future successful application of neuro-augmentation technology based on brain-machine interfaces.

Evaluation of anthrax vaccine safety in 18 to 20 year olds: A first step towards age de-escalation studies in adolescents.

PubMed

King, James C; Gao, Yonghong; Quinn, Conrad P; Dreier, Thomas M; Vianney, Cabrini; Espeland, Eric M

2015-05-15

Anthrax vaccine adsorbed (AVA, BioThrax(®)) is recommended for post-exposure prophylaxis administration for the US population in response to large-scale Bacillus anthracis spore exposure. However, no information exists on AVA use in children and ethical barriers exist to performing pre-event pediatric AVA studies. A Presidential Ethics Commission proposed a potential pathway for such studies utilizing an age de-escalation process comparing safety and immunogenicity data from 18 to 20 year-olds to older adults and if acceptable proceeding to evaluations in younger adolescents. We conducted exploratory summary re-analyses of existing databases from 18 to 20 year-olds (n=74) compared to adults aged 21 to 29 years (n=243) who participated in four previous US government funded AVA studies. Data extracted from studies included elicited local injection-site and systemic adverse events (AEs) following AVA doses given subcutaneously at 0, 2, and 4 weeks. Additionally, proportions of subjects with ≥4-fold antibody rises from baseline to post-second and post-third AVA doses (seroresponse) were obtained. Rates of any elicited local AEs were not significantly different between younger and older age groups for local events (79.2% vs. 83.8%, P=0.120) or systemic events (45.4% vs. 50.5%, P=0.188). Robust and similar proportions of seroresponses to vaccination were observed in both age groups. AVA was safe and immunogenic in 18 to 20 year-olds compared to 21 to 29 year-olds. These results provide initial information to anthrax and pediatric specialists if AVA studies in adolescents are required. Copyright © 2015 Elsevier Ltd. All rights reserved.

Non-causal spike filtering improves decoding of movement intention for intracortical BCIs

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2014-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain-computer interfaces (BCIs). Intracortically-recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. Conclusions Non-causally filtering neural signals prior to extracting threshold crossing events may be a simple yet effective way to condition intracortically recorded neural activity for direct control of external devices through BCIs. PMID:25128256

Industrial accidents triggered by lightning.

PubMed

Renni, Elisabetta; Krausmann, Elisabeth; Cozzani, Valerio

2010-12-15

Natural disasters can cause major accidents in chemical facilities where they can lead to the release of hazardous materials which in turn can result in fires, explosions or toxic dispersion. Lightning strikes are the most frequent cause of major accidents triggered by natural events. In order to contribute towards the development of a quantitative approach for assessing lightning risk at industrial facilities, lightning-triggered accident case histories were retrieved from the major industrial accident databases and analysed to extract information on types of vulnerable equipment, failure dynamics and damage states, as well as on the final consequences of the event. The most vulnerable category of equipment is storage tanks. Lightning damage is incurred by immediate ignition, electrical and electronic systems failure or structural damage with subsequent release. Toxic releases and tank fires tend to be the most common scenarios associated with lightning strikes. Oil, diesel and gasoline are the substances most frequently released during lightning-triggered Natech accidents. Copyright © 2010 Elsevier B.V. All rights reserved.

A Maximum NEC Criterion for Compton Collimation to Accurately Identify True Coincidences in PET

PubMed Central

Chinn, Garry; Levin, Craig S.

2013-01-01

In this work, we propose a new method to increase the accuracy of identifying true coincidence events for positron emission tomography (PET). This approach requires 3-D detectors with the ability to position each photon interaction in multi-interaction photon events. When multiple interactions occur in the detector, the incident direction of the photon can be estimated using the Compton scatter kinematics (Compton Collimation). If the difference between the estimated incident direction of the photon relative to a second, coincident photon lies within a certain angular range around colinearity, the line of response between the two photons is identified as a true coincidence and used for image reconstruction. We present an algorithm for choosing the incident photon direction window threshold that maximizes the noise equivalent counts of the PET system. For simulated data, the direction window removed 56%–67% of random coincidences while retaining > 94% of true coincidences from image reconstruction as well as accurately extracted 70% of true coincidences from multiple coincidences. PMID:21317079

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network.

PubMed

Yoon, Jaehong; Lee, Jungnyun; Whang, Mincheol

2018-01-01

Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain-computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network

PubMed Central

2018-01-01

Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain–computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

Eye movement and brake reactions to real world brake-capacity forward collision warnings--a naturalistic driving study.

PubMed

Wege, Claudia; Will, Sebastian; Victor, Trent

2013-09-01

The purpose of this field operational test study is to assess visual attention allocation and brake reactions in response to a brake-capacity forward collision warning (B-FCW), which is designed similarly to all forward collision warnings on the market for trucks. Truck drivers' reactions immediately after the warning (threat-period) as well as a few seconds after the warning (post-threat-recovery-period) are analyzed, both with and without taking into consideration the predictability of an event and driver distraction. A B-FCW system interface should immediately direct visual attention toward the threat and allow the driver to make a quick decision about whether or not to brake. To investigate eye movement reactions, we analyzed glances 30s before and 15s after 60 naturally occurring collision warning events. The B-FCW events were extracted from the Volvo euroFOT database, which contains data from 30 Volvo trucks driving for approximately 40000 h for four million kilometers. Statistical analyses show that a B-FCW leads to immediate attention allocation toward the roadway and drivers hit the brake. In addition to this intended effect during the threat-period, a rather unexpected effect within the post-threat-recovery-period was discovered in unpredictable events and events with distracted drivers. A few seconds after a warning is issued, eye movements are directed away from the road toward the warning source in the instrument cluster. This potentially indicates that the driver is seeking to understand the circumstances of the warning. Potential reasons for this are discussed: properties relating to the termination of the warning information, the position of the visual and/or audio warning, the conspicuity of the warning, the duration of the warning, and the modality of the warning. The present results are particularly valuable because all on-market collision warning systems in trucks (and almost all in cars) involve visual warnings positioned in the instrument cluster like the one in this study. Acknowledging the fact that human machine interface (HMI)-design is challenging, the conclusions lead the way toward HMI design recommendations for collision warning systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Sequential pattern data mining and visualization

DOEpatents

Wong, Pak Chung [Richland, WA; Jurrus, Elizabeth R [Kennewick, WA; Cowley, Wendy E [Benton City, WA; Foote, Harlan P [Richland, WA; Thomas, James J [Richland, WA

2011-12-06

One or more processors (22) are operated to extract a number of different event identifiers therefrom. These processors (22) are further operable to determine a number a display locations each representative of one of the different identifiers and a corresponding time. The display locations are grouped into sets each corresponding to a different one of several event sequences (330a, 330b, 330c. 330d, 330e). An output is generated corresponding to a visualization (320) of the event sequences (330a, 330b, 330c, 330d, 330e).

Sequential pattern data mining and visualization

DOEpatents

Wong, Pak Chung [Richland, WA; Jurrus, Elizabeth R [Kennewick, WA; Cowley, Wendy E [Benton City, WA; Foote, Harlan P [Richland, WA; Thomas, James J [Richland, WA

2009-05-26

One or more processors (22) are operated to extract a number of different event identifiers therefrom. These processors (22) are further operable to determine a number a display locations each representative of one of the different identifiers and a corresponding time. The display locations are grouped into sets each corresponding to a different one of several event sequences (330a, 330b, 330c. 330d, 330e). An output is generated corresponding to a visualization (320) of the event sequences (330a, 330b, 330c, 330d, 330e).

Beauty photoproduction using decays into electrons at HERA

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

Chekanov, S.; Derrick, M.; Magill, S.

Photoproduction of beauty quarks in events with two jets and an electron associated with one of the jets has been studied with the ZEUS detector at HERA using an integrated luminosity of 120 pb{sup -1}. The fractions of events containing b quarks, and also of events containing c quarks, were extracted from a likelihood fit using variables sensitive to electron identification as well as to semileptonic decays. Total and differential cross sections for beauty and charm production were measured and compared with next-to-leading-order QCD calculations and Monte Carlo models.

Developing an Approach to Prioritize River Restoration using Data Extracted from Flood Risk Information System Databases.

NASA Astrophysics Data System (ADS)

Vimal, S.; Tarboton, D. G.; Band, L. E.; Duncan, J. M.; Lovette, J. P.; Corzo, G.; Miles, B.

2015-12-01

Prioritizing river restoration requires information on river geometry. In many states in the US detailed river geometry has been collected for floodplain mapping and is available in Flood Risk Information Systems (FRIS). In particular, North Carolina has, for its 100 Counties, developed a database of numerous HEC-RAS models which are available through its Flood Risk Information System (FRIS). These models that include over 260 variables were developed and updated by numerous contractors. They contain detailed surveyed or LiDAR derived cross-sections and modeled flood extents for different extreme event return periods. In this work, over 4700 HEC-RAS models' data was integrated and upscaled to utilize detailed cross-section information and 100-year modelled flood extent information to enable river restoration prioritization for the entire state of North Carolina. We developed procedures to extract geomorphic properties such as entrenchment ratio, incision ratio, etc. from these models. Entrenchment ratio quantifies the vertical containment of rivers and thereby their vulnerability to flooding and incision ratio quantifies the depth per unit width. A map of entrenchment ratio for the whole state was derived by linking these model results to a geodatabase. A ranking of highly entrenched counties enabling prioritization for flood allowance and mitigation was obtained. The results were shared through HydroShare and web maps developed for their visualization using Google Maps Engine API.

Exploring the evolution of node neighborhoods in Dynamic Networks

NASA Astrophysics Data System (ADS)

Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

2017-09-01

Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

Production of transgenic strawberries by temporary immersion bioreactor system and verification by TAIL-PCR

PubMed Central

Hanhineva, Kati J; Kärenlampi, Sirpa O

2007-01-01

Background Strawberry (Fragaria × ananassa) is an economically important soft fruit crop with polyploid genome which complicates the breeding of new cultivars. For certain traits, genetic engineering offers a potential alternative to traditional breeding. However, many strawberry varieties are quite recalcitrant for Agrobacterium-mediated transformation, and a method allowing easy handling of large amounts of starting material is needed. Also the genotyping of putative transformants is challenging since the isolation of DNA for Southern analysis is difficult due to the high amount of phenolic compounds and polysaccharides that complicate efficient extraction of digestable DNA. There is thus a need to apply a screening method that is sensitive and unambiguous in identifying the different transformation events. Results Hygromycin-resistant strawberries were developed in temporary immersion bioreactors by Agrobacterium-mediated gene transfer. Putative transformants were screened by TAIL-PCR to verify T-DNA integration and to distinguish between the individual transformation events. Several different types of border sequence arrangements were detected. Conclusion This study demonstrates that temporary immersion bioreactor system suits well for the regeneration of transgenic strawberry plants as a labour-efficient technique. Small amount of DNA required by TAIL-PCR is easily recovered even from a small transformant, which allows rapid verification of T-DNA integration and detection of separate gene transfer events. These techniques combined clearly facilitate the generation of transgenic strawberries but should be applicable to other plants as well. PMID:17309794

Versatile Mobile and Stationary Low-Cost Approaches for Hydrological Measurements

NASA Astrophysics Data System (ADS)

Kröhnert, M.; Eltner, A.

2018-05-01

In the last decades, an increase in the number of extreme precipitation events has been observed, which leads to increasing risks for flash floods and landslides. Thereby, conventional gauging stations are indispensable for monitoring and prediction. However, they are expensive in construction, management, and maintenance. Thus, density of observation networks is rather low, leading to insufficient spatio-temporal resolution to capture hydrological extreme events that occur with short response times especially in small-scale catchments. Smaller creeks and rivers require permanent observation, as well, to allow for a better understanding of the underlying processes and to enhance forecasting reliability. Today's smartphones with inbuilt cameras, positioning sensors and powerful processing units may serve as wide-spread measurement devices for event-based water gauging during floods. With the aid of volunteered geographic information (VGI), the hydrological network of water gauges can be highly densified in its spatial and temporal domain even for currently unobserved catchments. Furthermore, stationary low-cost solutions based on Raspberry Pi imaging systems are versatile for permanent monitoring of hydrological parameters. Both complementary systems, i.e. smartphone and Raspberry Pi camera, share the same methodology to extract water levels automatically, which is explained in the paper in detail. The annotation of 3D reference data by 2D image measurements is addressed depending on camera setup and river section to be monitored. Accuracies for water stage measurements are in range of several millimetres up to few centimetres.

Mining patterns in persistent surveillance systems with smart query and visual analytics

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.; Shirkhodaie, Amir

2013-05-01

In Persistent Surveillance Systems (PSS) the ability to detect and characterize events geospatially help take pre-emptive steps to counter adversary's actions. Interactive Visual Analytic (VA) model offers this platform for pattern investigation and reasoning to comprehend and/or predict such occurrences. The need for identifying and offsetting these threats requires collecting information from diverse sources, which brings with it increasingly abstract data. These abstract semantic data have a degree of inherent uncertainty and imprecision, and require a method for their filtration before being processed further. In this paper, we have introduced an approach based on Vector Space Modeling (VSM) technique for classification of spatiotemporal sequential patterns of group activities. The feature vectors consist of an array of attributes extracted from generated sensors semantic annotated messages. To facilitate proper similarity matching and detection of time-varying spatiotemporal patterns, a Temporal-Dynamic Time Warping (DTW) method with Gaussian Mixture Model (GMM) for Expectation Maximization (EM) is introduced. DTW is intended for detection of event patterns from neighborhood-proximity semantic frames derived from established ontology. GMM with EM, on the other hand, is employed as a Bayesian probabilistic model to estimated probability of events associated with a detected spatiotemporal pattern. In this paper, we present a new visual analytic tool for testing and evaluation group activities detected under this control scheme. Experimental results demonstrate the effectiveness of proposed approach for discovery and matching of subsequences within sequentially generated patterns space of our experiments.

Constructing and Modifying Sequence Statistics for relevent Using informR in 𝖱

PubMed Central

Marcum, Christopher Steven; Butts, Carter T.

2015-01-01

The informR package greatly simplifies the analysis of complex event histories in 𝖱 by providing user friendly tools to build sufficient statistics for the relevent package. Historically, building sufficient statistics to model event sequences (of the form a→b) using the egocentric generalization of Butts’ (2008) relational event framework for modeling social action has been cumbersome. The informR package simplifies the construction of the complex list of arrays needed by the rem() model fitting for a variety of cases involving egocentric event data, multiple event types, and/or support constraints. This paper introduces these tools using examples from real data extracted from the American Time Use Survey. PMID:26185488

An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms.

PubMed

Andreotti, Fernando; Behar, Joachim; Zaunseder, Sebastian; Oster, Julien; Clifford, Gari D

2016-05-01

Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphological features from the NI-FECG. However, due to the shortage of available public databases, the large variety of performance measures employed and the lack of open-source reference algorithms, most contributions cannot be meaningfully assessed. This article attempts to address these issues by presenting a standardised methodology for stress testing NI-FECG algorithms, including absolute data, as well as extraction and evaluation routines. To that end, a large database of realistic artificial signals was created, totaling 145.8 h of multichannel data and over one million FQRS complexes. An important characteristic of this dataset is the inclusion of several non-stationary events (e.g. foetal movements, uterine contractions and heart rate fluctuations) that are critical for evaluating extraction routines. To demonstrate our testing methodology, three classes of NI-FECG extraction algorithms were evaluated: blind source separation (BSS), template subtraction (TS) and adaptive methods (AM). Experiments were conducted to benchmark the performance of eight NI-FECG extraction algorithms on the artificial database focusing on: FQRS detection and morphological analysis (foetal QT and T/QRS ratio). The overall median FQRS detection accuracies (i.e. considering all non-stationary events) for the best performing methods in each group were 99.9% for BSS, 97.9% for AM and 96.0% for TS. Both FQRS detections and morphological parameters were shown to heavily depend on the extraction techniques and signal-to-noise ratio. Particularly, it is shown that their evaluation in the source domain, obtained after using a BSS technique, should be avoided. Data, extraction algorithms and evaluation routines were released as part of the fecgsyn toolbox on Physionet under an GNU GPL open-source license. This contribution provides a standard framework for benchmarking and regulatory testing of NI-FECG extraction algorithms.

Dimension reduction: additional benefit of an optimal filter for independent component analysis to extract event-related potentials.

PubMed

Cong, Fengyu; Leppänen, Paavo H T; Astikainen, Piia; Hämäläinen, Jarmo; Hietanen, Jari K; Ristaniemi, Tapani

2011-09-30

The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the number of sources) simultaneously. We demonstrated these effects using two datasets, one containing visual and the other auditory ERPs. The results showed that the method including OF and ICA extracted much more reliable components than the sole ICA without OF did, and that OF removed some non-targeted sources and made the underdetermined model of EEG recordings approach to the determined one. Thus, we suggest designing an OF based on the properties of an ERP to filter recordings before using ICA decomposition to extract the targeted ERP component. Copyright © 2011 Elsevier B.V. All rights reserved.

Semantic Location Extraction from Crowdsourced Data

NASA Astrophysics Data System (ADS)

Koswatte, S.; Mcdougall, K.; Liu, X.

2016-06-01

Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

Extraction of $$\\sin^2\\theta^{\\rm lept}_{\\rm eff}$$ and indirect measurement of $$m_w$$ from the 9 fb$$^{-1}$$ full run ii sample of $$\\mu^+\\mu^-$$ events at cdf

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

Bodek, A.

2014-09-19

We report on the extraction ofmore » $$\\sin^2\\theta^{\\rm lept}_{\\rm eff}$$ and indirect measurement of the mass of the W boson from the forward-backward asymmetry of $$\\mu^+\\mu^-$$ events in the $Z$ boson mass region. The data sample collected by the CDF detector corresponds to the full 9 fb$$^{-1}$$ run II sample. We measure $$\\sin^2 \\theta^{\\rm lept}_{\\rm eff} = 0.2315 \\pm 0.0010$$,$$ \\sin^2 \\theta_W = 0.2233 \\pm 0.0009$$ and $$M_W ({\\rm indirect}) = 80.365 \\pm 0.047 \\;{\\rm GeV}/c^2$$, where each uncertainty includes both statistical and systematic contributions.« less

Visual content highlighting via automatic extraction of embedded captions on MPEG compressed video

NASA Astrophysics Data System (ADS)

Yeo, Boon-Lock; Liu, Bede

1996-03-01

Embedded captions in TV programs such as news broadcasts, documentaries and coverage of sports events provide important information on the underlying events. In digital video libraries, such captions represent a highly condensed form of key information on the contents of the video. In this paper we propose a scheme to automatically detect the presence of captions embedded in video frames. The proposed method operates on reduced image sequences which are efficiently reconstructed from compressed MPEG video and thus does not require full frame decompression. The detection, extraction and analysis of embedded captions help to capture the highlights of visual contents in video documents for better organization of video, to present succinctly the important messages embedded in the images, and to facilitate browsing, searching and retrieval of relevant clips.

sin 2 θ eff lept and M W(indirect) extracted from 9 fb -1 μ +μ - event sample at CDF

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

Bodek, A.

2016-05-31

Here, we report on the extraction ofmore » $$\\sin^2\\theta^{\\rm lept}_{\\rm eff}$$ and indirect measurement of the mass of the W boson from the forward-backward asymmetry of $$\\mu^+\\mu^-$$ events in the $Z$ boson mass region. The data sample collected by the CDF detector corresponds to the full 9 fb$$^{-1}$$ run II sample. We measure $$\\sin^2 \\theta^{\\rm lept}_{\\rm eff} = 0.2315 \\pm 0.0010$$, $$ \\sin^2 \\theta_W = 0.2233 \\pm 0.0009$$ and $$M_W ({\\rm indirect}) = 80.365 \\pm 0.047 \\;{\\rm GeV}/c^2$$, where each uncertainty includes both statistical and systematic contributions. Comparison with the results of the D0 collaboration are presented.« less

Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

NASA Astrophysics Data System (ADS)

Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

2016-12-01

Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River Basin (2015) are obtained using generated data. We compared 100-year probable rainfall calculated by this method with other traditional method. New developed method enables us to generate extreme rainfall events considering time and spatial scale and produce extreme rainfall scenario.

Analysis and suppression of passive noise in surface microseismic data

NASA Astrophysics Data System (ADS)

Forghani-Arani, Farnoush

Surface microseismic surveys are gaining popularity in monitoring the hydraulic fracturing process. The effectiveness of these surveys, however, is strongly dependent on the signal-to-noise ratio of the acquired data. Cultural and industrial noise generated during hydraulic fracturing operations usually dominate the data, thereby decreasing the effectiveness of using these data in identifying and locating microseismic events. Hence, noise suppression is a critical step in surface microseismic monitoring. In this thesis, I focus on two important aspects in using surface-recorded microseismic seismic data: first, I take advantage of the unwanted surface noise to understand the characteristics of these noise and extract information about the propagation medium from the noise; second, I propose effective techniques to suppress the surface noise while preserving the waveforms that contain information about the source of microseisms. Automated event identification on passive seismic data using only a few receivers is challenging especially when the record lengths span over long durations of time. I introduce an automatic event identification algorithm that is designed specifically for detecting events in passive data acquired with a small number of receivers. I demonstrate that the conventional STA/LTA (Short-term Average/Long-term Average) algorithm is not sufficiently effective in event detection in the common case of low signal-to-noise ratio. With a cross-correlation based method as an extension of the STA/LTA algorithm, even low signal-to-noise events (that were not detectable with conventional STA/LTA) were revealed. Surface microseismic data contains surface-waves (generated primarily from hydraulic fracturing activities) and body-waves in the form of microseismic events. It is challenging to analyze the surface-waves on the recorded data directly because of the randomness of their source and their unknown source signatures. I use seismic interferometry to extract the surface-wave arrivals. Interferometry is a powerful tool to extract waves (including body-wave and surface-waves) that propagate from any receiver in the array (called a pseudo source) to the other receivers across the array. Since most of the noise sources in surface microseismic data lie on the surface, seismic interferometry yields pseudo source gathers dominated by surface-wave energy. The dispersive characteristics of these surface-waves are important properties that can be used to extract information necessary for suppressing these waves. I demonstrate the application of interferometry to surface passive data recorded during the hydraulic fracturing operation of a tight gas reservoir and extract the dispersion properties of surface-waves corresponding to a pseudo-shot gather. Comparison of the dispersion characteristics of the surface waves from the pseudo-shot gather with that of an active shot-gather shows interesting similarities and differences. The dispersion character (e.g. velocity change with frequency) of the fundamental mode was observed to have the same behavior for both the active and passive data. However, for the higher mode surface-waves, the dispersion properties are extracted at different frequency ranges. Conventional noise suppression techniques in passive data are mostly stacking-based that rely on enforcing the amplitude of the signal by stacking the waveforms at the receivers and are unable to preserve the waveforms at the individual receivers necessary for estimating the microseismic source location and source mechanism. Here, I introduce a technique based on the tau - p transform, that effectively identifies and separates microseismic events from surface-wave noise in the tau -p domain. This technique is superior to conventional stacking-based noise suppression techniques, because it preserves the waveforms at individual receivers. Application of this methodology to microseismic events with isotropic and double-couple source mechanism, show substantial improvement in the signal-to-noise ratio. Imaging of the processed field data also show improved imaging of the hypocenter location of the microseismic source. In the case of double-couple source mechanism, I suggest two approaches for unifying the polarities at the receivers, a cross-correlation approach and a semblance-based prediction approach. The semblance-based approach is more effective at unifying the polarities, especially for low signal-to-noise ratio data.