Event Traces Research Articles

Abstract 128: Assessing the Temporal Trend in Survival to Hospital Admission Following Out-Of-Hospital Cardiac Arrest: Analysis From a Public Access Defibrillator Registry

Introduction: The AHA Get With the Guidelines Resuscitation Investigators recently identified that in-hospital cardiac arrest patients admitted during nights and weekends are less likely to survive to discharge. Our analysis aimed to determine if a similar relationship applied to out-of-hospital cardiac arrest (OHCA) patients. Methods: Worldwide data collection began in Oct 2012. Users of HeartSine SAM PAD public access defibrillators submitted electronic event data (comprising time/date of event and electrocardiogram traces) and an event report form (comprising patient demographics, location of arrest and survival to hospital outcome). First shock success was defined as termination of shockable rhythm for 5 seconds post-shock. Data was analysed using R. Results: A total of 3400 OHCA cases were collected. Median (IQR) age was 63 (50, 75) and males accounted for 72.4% of the dataset. A total of 1127 first shocks were delivered, and first shock success was 87.2% (983 shocks). Survival outcomes were reported in 2942 cases, and 783 (26.6%) patients survived to hospital admission. First shock success as a response to day of the week (weekday versus weekend [12am Saturday-11.59pm Sunday]) adjusted for patient age, gender and location of arrest, was assessed and there was no association found. When the same model was fitted with survival to hospital admission as a response to day of the week, it was determined that patients are approximately 20% less likely to survive to hospital admission at the weekend (OR=0.81, 95%CI [0.68, 0.95], p=0.01). There was a negative association between survival and OHCA occurring at home (OR=0.32, 95%CI [0.10, 0.94], p=0.03) and increasing age (per 1-year increase, OR=0.99, 95%CI [0.98, 1.00], p<0.001). Adjusting the model for time of day (morning [6am-11.59am], afternoon [12pm-5.59pm], evening [6pm-11.59pm] and night [12am-5.59am]) did not highlight an association with any particular time of day. Conclusions: OHCA patients are significantly less likely to survive to hospital admission at weekends compared to weekdays. Further analysis on the availability of PADs at professional and recreational locations and availability of trained medical rescuers at the weekend versus weekdays could account for the differences observed.

Local Self-Governments in Hungary: Recent Changes through Central European Lenses

This article provides an overview of the regulatory environment of the Hungarian system of local self-government based on the methods of legal dynamics and economic analyses in a historical perspective tracing events back to the aftermath of World War II. The starting point of the analysis is 1947, the launching of soviet type command economy in Hungary. Next is a detailed study of the regulation and evolution of local self-government since its beginnings in the early 1990s following the change of regime, with a brief international outlook on the post-soviet countries surrounding Hungary. In our economic analysis, emphasis is placed on the period following Hungary’s accession to the European Union, a period that held out considerable opportunities for Hungarian local self-governments, but ultimately evolved into bankruptcy. The article presents detailed reasons for the atypical nature of Hungarian local self-government indebtedness and the factors underlying this unfavourable process. Further on, the procedure of debt consolidation and the essential elements of the new regulatory environment created after 2011 are described. In a brief international comparison, debt portfolio developments are analysed through the examples of Slovenia, Poland, Slovakia and the Czech Republic as analogue Central European countries, in order to provide further proof of the atypical financial management of Hungarian local self-governments, i.e. non-compliance with the rules and the not always solid budgetary discipline. The focus of the research underlying this paper is the impact the Hungarian regulation of self-governments had on the financial sustainability of local self-governments’ financial management. The study confirmed the initial hypothesis that the business management rules set out with insufficient prudence, deficiencies in the control system, and excessive borrowing in foreign exchange led to bankruptcy of a number of local self-governments and consequently jeopardised the proper provision of public services.

On the Balance Equations and Error Estimators for Separating n Time Components of Runoff With One Stable Isotope Tracer

AbstractStarting from their first applications in the late 1960s, the mass balance equations for separating storm hydrographs have been analyzed with respect to their solvability and sensitivity to errors. By changing them into a time perspective, it is shown how an iterative extension of the standard two‐component separation can lead to a system of balance equations that allows for separating n time components using one single stable isotope tracer. This new approach is tested for the case n=6 by using the experimental data of the Zastler catchment (18.4 km2, southern Black Forest, Germany). The behavior of several time components is demonstrated. By separating the event water of the last and next‐to‐last event, it is shown how the event water of a certain rainfall‐runoff event contributes to stream discharge over the next two subsequent events. The new separation model offers the possibility of tracing event water over a much longer period after the initial event.

A $16\times8$ Digital-SiPM Array With Distributed Trigger Generator for Low SNR Particle Tracking

This letter describes a 16 × 8-pixel array based on single-photon avalanche diodes (SPADs) optimized for the readout of a tracking detector based on plastic scintillation fibers targeting ultrafast neutrons. Each pixel of 125 × 250 μm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> size contains 30 SPADs, an 80-ps 10-b time-to-digital converter (TDC), a 5-b intensity counter, a finite state machine (FSM) that manages the recording of data and a three-word-deep FIFO memory for parallel acquisition and readout, achieving 32.1% pixel fill factor. A combined, programmable current-based local, and global triggering mechanism correlates the photon detection activity in time to distinguish asynchronous charged particle trace events from background noise even with a poor SNR.

2139-P: Real-Time Monitoring and High-Resolution Analysis of Human Pancreatic Ductal Plasticity

Introduction: The exocrine compartment of the pancreas has been hypothesized to harbor progenitor cells. While their existence remains the subject of debate, the widespread consensus is that any such putative progenitors should express the pancreatic-duodenal homeobox 1 protein (PDX1). Progenitor cell stimulation often depends on concurrent TGFb inhibition and BMP activation. We further hypothesized that PDX1-expressing putative b-cell progenitors may respond to BMP-7. Our data (1) indicate that extrainsular PDX1+/ALK3+ cells do so by proliferating and subsequently, upon BMP-7 withdrawal, differentiating in a multilineage fashion. Here we present additional mechanistic data on b-cell regeneration using a novel human pancreatic slice culture system that allows for the observation of pancreatic tissue for 2 weeks. We further show single cell RNAseq analyses of sorted ALK3+ from the human pancreas, confirming the heterogeneity of the ductal compartment. Methods: HPS: Low melting point agarose-embedded, vibratome-sectioned live pancreatic slices were generated from human donors. Transduction with a CMV-[loxP]-dsRed-[loxP]-EGFP adenovirus + insulin promoter-Cre adenovirus was done in slices cultured atop optically clear perfluorcarbon (PFC)-based membranes. scRNAseq of ALK3+ sorted cells from human non-endocrine tissue (hNEPT, the leftover of islet isolations) was done on 1,000 cells/sample (250K reads/cell). Conclusions: We report the use of live HPS as a novel tool for the study of pancreatic regeneration. Our preliminary results confirm the feasibility of tracing and monitoring discrete transitional events in response to BMP signalling stimulation, as well as the existence of multiple ductal populations at various degrees of differentiation in healthy donor pancreata.

Synthesis and Validation of Operating Procedures Based on Untimed Automata

To facilitate efficient procedure synthesis, the extended finite automata are adopted in this work to model all components in a chemical process. The intended operation is divided into several stages and each characterized with a set of unique features, e.g., stable operation, condition adjustment, material charging and/or unloading, etc. The control specifications of every stage should then be stipulated accordingly and also described with automata. The observable event traces (OETs) embedded in this system can be produced by synchronizing all aforementioned automata. The candidate operating procedures are summarized with sequential function charts (SFCs) on the basis of these OETs. The commercial package ASPEN Plus Dynamic has been used to validate these SFCs in simulation studies.

Development of Dynamic Coupling Measurement of Distributed Object Oriented Software Based on Trace Events

Development of Dynamic Coupling Measurement of Distributed Object Oriented Software Based on Trace Events

Challenges and prospects for building radiocarbon chronologies of the earlier Holocene of the Levant

This paper explores the challenges of building radiocarbon chronologies of the earlier Holocene of South-West Asia. The analysis consists of a technical and a taphonomic review of a selection of the published 14C record, followed by a modelling study of a sub-section of that data. This sketches the kinds of chronological syntheses we can hope to construct, given the nature of the sites in the region. The key observation from the review of individual radiocarbon determinations is that reliable radiocarbon dating contexts are very limited. This is due to taphonomic ambiguity associated with charred plant remains and the persisting difficulties in dating skeletal remains from South-West Asia. The modelling study highlights the challenges of tracing events, such as site onset and abandonment, on complex, long-lived sites, and the large extent of chronological ambiguity stemming, to a large extent, from the taphonomic challenges. Many of these issues might be resolved through new 14C extraction techniques, the ongoing improvement of excavation methods, as well as rethinking chronological syntheses with a greater focus on relationships between specific contexts.

Trace amine associate receptor 1 (TAAR1) as a new target for the treatment of cognitive dysfunction in Alzheimer disease

Event Abstract Back to Event Trace amine associate receptor 1 (TAAR1) as a new target for the treatment of cognitive dysfunction in Alzheimer disease Damiana Leo1*, Stefano Espinoza2, Agnes Villers1, Raul Gainetdinov3 and Laurence Ris1 1 University of Mons, Belgium 2 Istituto Italiano di Tecnologia, Italy 3 Saint Petersburg State University, Russia Alzheimer disease (AD) is the main cause of dementia with approximately 27 million people affected worldwide. Beta-Amyloid peptide (Ab) is elevated in the brains of patients with AD and is believed to be causative in the disease process. Ab can reduce long-term potentiation (LTP), a form of synaptic plasticity that is closely associated with learning and memory [1]. LTP involves postsynaptic phosphorylation and glutamate receptor trafficking, particularly; it has been shown that amyloid can cause reduction of glutamatergic transmission and inhibition of synaptic plasticity via increased endocytosis of NMDA receptors. Trace Amines (TAs) are a family of endogenous compounds with strong structural similarity to the classical monoamine neurotransmitters. The molecular mechanism of the TAs involves binding to a novel G protein-coupled receptor, called TAAR (trace amine-associated receptor). TAAR1 is distributed in the CNS. Recently, it has been shown that selective activation of TAAR1 are able to reverse glutamatergic hypofunction induced by selective NMDA receptor antagonists suggesting that TAAR1 activation may enhance also glutamatergic function. There are several lines of evidence suggesting pro-cognitive action of TAAR1 agonists in various behavioral experimental protocols and there is evidence indicating that TAAR1 can modulate frontal cortex glutamate NMDA receptor– related functions. [2-5]. Objectives: 1. To study in vitro the role of TAAR1 agonists on basal cortical glutamatergic transmission and their beneficial effect on Ab-induced dysfunction. 2. To study, in vivo, the role of TAAR1 in cognitive dysfunction induced by Ab and the beneficial role of TAAR1 agonists on cognition in Alzheimer’s mouse models. Methods: In vitro experiments were conducted on primary cortical cultures. Cortices of E17 embryo from TAAR1 and control mice were isolated and incubated for 14 days at 37 °C and 5% CO2. Cells were then stimulated with Ab 1-42 (1 µM, AnaSpec, USA), TAAR1 agonist (RO5256390, Sigma Aldrich, Belgium, 1 µM) or both 1hr at 37°C and NMDA surface expression was assessed using biotinylation assay and Western blots. In vivo studies were performed using 10-weeks mice ICV injected with: Ab 1-42 (3 µl), TAAR1 agonist (3µl) or both and vehicle treated controls. 7 days later, a series of behavioral tests were performed to evaluate the effects of Ab 1-42 and TAAR1 agonist, including Morris Water Maze (MWM), novel object recognition (NOR) and open field. Results: In vitro data showed that, as expected in WT mice, Ab 1-42 significantly decreased NMDA surface (NR1: -35± 2.6%; NR2A: -38± 1.8%; NR2B: -47± 4.2% ) expression while TAAR1 agonist promotes their membrane localization (NR1: +48±4.8%; NR2A: +67±3.5%; NR2B: +52±3.8% p<0.05, Student t test) on cortical cells. Conclusion: Altogether, our results showed that in vitro, TAAR1 agonist displayed the ability of increasing NMDA receptors surface expression, suggesting the possibility of displaying therapeutic effect on cognitive Ab induced impairments. Whether these effects are reproducible in vivo, are currently addressed.

Application of the Theory of Convenience to a Case of Illegal Public Procurement of Health Care Services

We address the following research question in this article: how can convenience theory in terms of motive, opportunity, and willingness explain deviant behaviour in the case of public procurement of healthcare services in a Norwegian municipality? This research is important, as it can identify motives at the individual and organisational level, opportunities at the organisational and societal level, and willingness at the individual level, even when there is not necessarily corruption involved. The application of convenience theory is by no means an excuse for violations of laws and regulations. Rather, this article demonstrates where prevention of misconduct and crime needs attention. It is particularly at the organisational level, where opportunity structures tend to enable commitment and concealment of illegitimate financial transactions. When auditing and other forms of control are de facto absent, where the blame game occurs, and where it is impossible to trace events because documents and e-mails have disappeared, then misconduct and crime become convenient options.

Application of the theory of convenience to a case of illegal public procurement of healthcare services

We address the following research question in this article: how can convenience theory in terms of motive, opportunity, and willingness explain deviant behaviour in the case of public procurement of healthcare services in a Norwegian municipality? This research is important, as it can identify motives at the individual and organisational level, opportunities at the organisational and societal level, and willingness at the individual level, even when there is not necessarily corruption involved. The application of convenience theory is by no means an excuse for violations of laws and regulations. Rather, this article demonstrates where prevention of misconduct and crime needs attention. It is particularly at the organisational level, where opportunity structures tend to enable commitment and concealment of illegitimate financial transactions. When auditing and other forms of control are de facto absent, where the blame game occurs, and where it is impossible to trace events because documents and e-mails have disappeared, then misconduct and crime become convenient options.

METHOD OF DETERMINING WEIGHTS OF TEMPORAL RULES IN MARKOV LOGIC NETWORK FOR BUILDING KNOWLEDGE BASE IN INFORMATION CONTROL SYSTEMS

The problem of constructing and expanding the temporal knowledge base for the information-control system is considered. This knowledge base is formally represented by the Markov logic network. It is shown that the behavior of the control object of a given class can be reflected in the form of a set of weighted temporal rules. These rules are formed on the basis of identifying links between events that reflect known variants of the behavior of the control object. A method is proposed for calculating the weights of temporal rules in a Markov logic network for a given level of detail of the control object. The level of detail is determined by the context for executing the sequences of control actions and for weighted temporal rules is specified by selecting subsets of the event attributes. The method includes such basic phases: preparation of a subset of temporal rules for a given level of detail; finding the weights of the rules taking into account the a priori probabilities of the event traces. The method creates conditions for supporting management decisions in information management systems at various levels of detail of complex management objects. Decision support is provided by predicting the probability of success in executing a sequence of actions that implement the management function in the current situation. These probabilities are determined using the weights of the temporal rules.

Optimal Process Mining for Large and Complex Event Logs

This paper addresses the problem of process discovery from large and complex event logs. We depart from the existing literature and formulate the problem of optimal process discovery. A formal mathematical programming model is given based on a novel hierarchical structuration of the event logs. Desired properties of event trace score functions are described, and the properties of optimal process models are proved. A combination of Monte Carlo optimization and tabu search is proposed to overcome the complexity related to the huge size of the event logs and the combinatorial solution space. Numerical results show that our approach is suitable for large event logs and that it performs better than the state-of-the-art approaches. We also demonstrate the applicability of our method on a real case study in health care. This paper illustrates the benefits of combining techniques from the operational research and the process mining fields. Note to Practitioners —Though directly applicable to general business process discovery, this paper is motivated by our collaboration with the company HEVA (Lyon, France) and health practitioners on patient care pathway discovery. The French hospitalization database that contains hospitalization history of all patients is used for this purpose and our goal is to determine the most meaningful process model of the patient hospitalization history. The hierarchical event structure of this paper provides a natural way of representing relationship between hospitalization events and is readily obtainable from the classical ICD-10 codes. The formal mathematical model and our optimization algorithm allow the end users to best balance between the faithfulness of the process model and its complexity. A case study of cardiovascular patients is presented to show the capability of the proposed approach to clearly capture the major patient pathways before and after the implementation of defibrillators. The results of this paper are highly valuable for doctors and public health decision makers, as crucial information is provided on patient care pathways for any selected cohort.

Modelling the Embedded Control System Using iUML-B Pattern State Machine

Developing the formal model based on the Event-B design pattern is an excellent method to improve the development efficiency of the embedded control system and improve the reusability of the formal model. However, the instantiation of the Event-B design pattern requires the manual writing of a large number of model codes, which brings a great deal of learning cost and coding burden to the engineering staff. In this paper, we propose a modelling approach for formal development of control systems based on the application of iUML-B state machine patterns to model the four synchronization patterns of the typical control system. Then, we use the instantiation of iUML-B pattern state machine to establish a typical multilevel control system's Event-B model. The simulation results show that the event trace of the model obtained using our method is the same as that of the corresponding model obtained using the traditional Event-B design pattern. Compared with the traditional Event-B design pattern method, our method can greatly reduce the manual coding burden in the modelling process. The system model expressed using the iUML-B pattern state machine can be easily mapped to the labelled transition system so as to verify the behavioural properties of the model.

Discovering Interpretable Medical Workflow Models.

Medical workflow discovery and analysis can help teams better understand their practice and potentially improve patient outcomes. In the past, medical experts designed hand-made workflow models for this purpose. These models usually needed iterative revision for the experts to reach consensus. Actual practice, however, often deviates from a perceived ideal workflow model. Automatic workflow discovery algorithms have recently been proposed to learn a workflow model from observed activity or event traces. These algorithms, however, can produce spaghetti-like graphical models, with many branches and loops. Although model interpretability is an initial requirement of medical process analysis, it is often difficult or impossible for medical experts to extract knowledge from these chaotic models. We present an algorithm for discovering interpretable medical workflow models that addresses these limitations. We show our preliminary results and evaluate our approach on a real-world medical process.

Estimation of the displacements among distant events based on parallel tracking of events in seismic traces under uncertainty

The method we propose in this paper seeks to estimate interface displacements among strata related with reflection seismic events, in comparison to the interfaces at other reference points. To do so, we search for reflection events in the reference point of a second seismic trace taken from the same 3D survey and close to a well. However, the nature of the seismic data introduces uncertainty in the results. Therefore, we perform an uncertainty analysis using the standard deviation results from several experiments with cross-correlation of signals. To estimate the displacements of events in depth between two seismic traces, we create a synthetic seismic trace with an empirical wavelet and the sonic log of the well, close to the second seismic trace. Then, we relate the events of the seismic traces to the depth of the sonic log. Finally, we test the method with data from the Namorado Field in Brazil. The results show that the accuracy of the event estimated depth depends on the results of parallel cross-correlation, primarily those from the procedures used in the integration of seismic data with data from the well. The proposed approach can correctly identify several similar events in two seismic traces without requiring all seismic traces between two distant points of interest to correlate strata in the subsurface.

SEQUIN: a grammar inference framework for analyzing malicious system behavior

Targeted attacks on IT systems are a rising threat to the confidentiality of sensitive data and the availability of critical systems. The emergence of Advanced Persistent Threats (APTs) made it paramount to fully understand the particulars of such attacks in order to improve or devise effective defense mechanisms. Grammar inference paired with visual analytics (VA) techniques offers a powerful foundation for the automated extraction of behavioral patterns from sequential event traces. To facilitate the interpretation and analysis of APTs, we present SEQUIN, a grammar inference system based on the Sequitur compression algorithm that constructs a context-free grammar (CFG) from string-based input data. In addition to recursive rule extraction, we expanded the procedure through automated assessment routines capable of dealing with multiple input sources and types. This automated assessment enables the accurate identification of interesting frequent or anomalous patterns in sequential corpora of arbitrary quantity and origin. On the formal side, we extended the CFG with attributes that help describe the extracted (malicious) actions. Discovery-focused pattern visualization of the output is provided by our dedicated KAMAS VA prototype.

Recovering disk storage metrics from low‐level trace events

SummaryBlock devices such as magnetic disks are nonvolatile data storage devices that transfer data in fixed‐size chunks. They are the main nonvolatile memory that holds the file system, and they are also used in virtual memory mechanisms such swapping and page fault handling. Investigating storage performance issues requires a full insight into the operating system internals. Kernel tracing offers an efficient mechanism to gather information about the storage subsystem at runtime. Still, the tracing output is often huge and difficult to analyze manually.In this paper, we introduce a framework to compute meaningful storage performance metrics from low‐level trace events generated by LTTng. A stateful approach is used to model the state of the storage subsystem. Efficient data structures and algorithms are proposed to offer a reasonable response time, allowing the user to navigate throughout the trace and to retrieve metrics from any time range. The framework includes a visualization system that provides different graphical views that represent the collected information in a convenient way. These views are synchronized together, forming a comprehensive perspective that makes storage performance investigation a much more comfortable task. Different use cases are presented to show the usefulness of the framework in real‐world applications.

Visual Analysis of Parallel Interval Events

System logs typically contain lines with time stamps that each describes an event. Where these events semantically form start and end events, they can be combined into interval events. For visual event analytics, the analysis of interval events is more complex than that of point events, since not only the order of events, but also temporal overlaps have to be taken into account. To address this increased complexity and for the purpose of system understanding and analysis, we present SELE, a domain-independent tool for visualizing parallel interval events. SELE is intended to be used on a single long trace of events. A visual technique named strata timeline is developed to handle visual scalability issues. Finally, a multi-core parallel graph searching algorithm is analyzed to demonstrate SELE.

A LTS Approach to Control in Event-B

In Event-B, people need to use control variables to constrain the order of events, which is a time-consuming and error-prone process. This paper presents a method of combining labeled transition system and iUML-B to complete the behavior modeling of system, which is more convenient and practical for engineers who are accustomed to using the automaton to build a system behavior model. First, we use labeled transition system to establish the behavior model of the system. Then we simulate and verify the event traces of the labeled transition system behavior model. Finally, we convert labeled transition system model into iUML-B state machine and use it to generate the corresponding control flow model. We use Abrial’s bounded retransmission protocol to demonstrate the practicality of our approach. The simulation results show that the system behavior model generated by the iUML-B state machine has the same event trace as the corresponding labeled transition system model.