scholarly journals An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Mustafa Yuksel ◽  
Suat Gonul ◽  
Gokce Banu Laleci Erturkmen ◽  
Ali Anil Sinaci ◽  
Paolo Invernizzi ◽  
...  
Keyword(s):  
Real Life ◽  
Case Series ◽  
Background Information ◽  
Data Sets ◽  
Local Data ◽  
Lombardy Region ◽  
Common Information ◽  
Spontaneous Reports ◽  
Wide Range ◽  
Common Information Model

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information.

scholarly journals A generic model for the context-aware representation and federation of educational datasets: Experience from the dataTEL challenge

2017 ◽  
pp. 143-159
Keyword(s):  
Large Scale ◽  
Generic Model ◽  
Data Sets ◽  
Context Aware ◽  
Data Set ◽  
Common Information ◽  
Common Information Model ◽  
E Learning ◽  
Current Systems ◽  
New Algorithms

Research on online interactions during a learning situation to better understand users' practices and to provide them with quality-oriented features, resources and services is attracting a large community. As a result, the interest for sharing educational data sets that translate the interactions of users with e-learning systems has become a hot topic today. However, the current systems aggregating social and usage data about their users suffer from a series of weaknesses. In particular, they lack a common information model that would allow for exchanges of interaction data at a large scale. To tackle this issue, we propose in this paper a generic model able to federate heterogeneous context metadata and to facilitate their share and reuse. This framework has been successfully applied to several data sets provided by the research community, and thus gives access to a big data set that could help researchers to increase efficiency of existing learning analytics technics, and promote research and development of new algorithms and services on top of these data.

VERIFICATION AND PREDICTION OF TIMED PROBABILISTIC PROPERTIES OVER THE DMTF CIM

2006 ◽  
Vol 15 (04) ◽  
pp. 633-658 ◽  
Author(s):  
IMAN POERNOMO ◽  
HEINZ SCHMIDT ◽  
JANE JAYAPUTERA
Keyword(s):  
Formal Semantics ◽  
Runtime Verification ◽  
State Transitions ◽  
Common Information ◽  
Truth Function ◽  
Wide Range ◽  
Common Information Model ◽  
Meta Object Facility ◽  
System Properties ◽  
Prediction Techniques

Understanding nonfunctional aspects of system behavior is an essential component of practical software development and maintenance. Many nonfunctional system properties, such as reliability and availability, involve time and probabilities. In this paper, we present a framework for runtime verification and prediction of timed and probabilistic nonfunctional properties of component-based architectures, built using the Meta-Object Facility and the Distributed Management Task Force's Common Information Model (CIM) standard. We describe a Microsoft .NET-based implementation of our framework. We define a language for describing timed probabilistic behavior based on Probabilistic Computational Tree Logic (PCTL). We provide a formal semantics for this language in terms of observed application execution traces. The semantics is interesting in that it permits checking of required timing behavior both over the overall average of traces and also over local "trends" in traces. The latter aspect of the semantics is achieved by incorporating exponential smoothing prediction techniques into the truth function for statements of our language. The semantics is generic over the aspects of an application that are represented by states and state transitions. This enables the language to be used to describe a wide range of nonfunctional properties for runtime verification and prediction purposes. We explain how statements of our language are used to define precise contracts for system monitoring, through relating the semantics to an extended CIM monitoring infrastructure.

scholarly journals Emotional agents - state of the art and applications

2015 ◽  
Vol 12 (4) ◽  
pp. 1121-1148 ◽  
Author(s):  
Mirjana Ivanovic ◽  
Zoran Budimac ◽  
Milos Radovanovic ◽  
Vladimir Kurbalija ◽  
Weihui Dai ◽  
...  
Keyword(s):  
Emotional Intelligence ◽  
State Of The Art ◽  
Real Life ◽  
Data Sets ◽  
Emotional Information ◽  
Intelligent Software ◽  
Research Activities ◽  
Intelligent Software Agents ◽  
Wide Range ◽  
Emotional Agents

last decade, intensive research on emotional intelligence has advanced significantly from its theoretical basis, analytical studies and processing technology to exploratory applications in a wide range of real-life domains. This paper brings new insights in the field of emotional, intelligent software agents. The first part is devoted to an overview of the state-of-the-art in emotional intelligence research with emphasis on emotional agents. A wide range of applications in different areas like modeling emotional agents, aspects of learning in emotional environments, interactive emotional systems and so on are presented. After that we suggest a systematic order of research steps with the idea of proposing an adequate framework for several possible real-life applications of emotional agents. We recognize that it is necessary to apply specific methods for dynamic data analysis in order to identify and discover new knowledge from available emotional information and data sets. The last part of the paper discusses research activities for designing an agent-based architecture, in which agents are capable of reasoning about and displaying some kind of emotions based on emotions detected in human speech, as well as online documents.

scholarly journals Extension of Common Information Model of Load Storage in Regional Energy System Based on IEC61970

2022 ◽  
Vol 2160 (1) ◽  
pp. 012043
Author(s):  
Lin Cong ◽  
Xichao Zhou ◽  
Na Li ◽  
Haifeng Zhu ◽  
Ying Fan ◽  
...  
Keyword(s):  
High Efficiency ◽  
Energy System ◽  
Information Model ◽  
Local Conditions ◽  
Control Center ◽  
Common Information ◽  
Information Interaction ◽  
Wide Range ◽  
New Energy ◽  
Common Information Model

Abstract The need to reform the energy system is urgent. Choose new energy to supplement traditional energy according to local conditions, to build a comprehensive energy system will become more and more emerging development areas of the rigid demand. However, in the practical application of RIES, due to its high complexity and wide range of involvement, there are information islands between various equipment and systems, which cannot support its high efficiency and timeliness. Therefore, The common information model (CIM) modeling method can break the information interaction barriers between RIES.Taking a new area as an example, the CIM model expansion of photovoltaic generating electricity system, wind power system, EV charging equipment, substation class, thermoelectric conversion equipment and user load is established. The classes and class attributes required for the information interaction of RIES control center in the new area were designed, which laid the foundation for the interaction between different energy systems and the load and storage of the source network.

Home Learning in Times of COVID: Experiences of Parents

2020 ◽  
Vol 7 (1) ◽  
pp. 9 ◽  
Author(s):  
Shelina Bhamani ◽  
Areeba Zainab Makhdoom ◽  
Vardah Bharuchi ◽  
Nasreen Ali ◽  
Sidra Kaleem ◽  
...  
Keyword(s):  
Real Life ◽  
Sampling Technique ◽  
Online Classes ◽  
Google Docs ◽  
Learning Gap ◽  
Wide Range ◽  
Home Learning ◽  
Collection Data ◽  
Learning At Home ◽  
At Home

<p align="center"><em>The widespread prevalence of COVID-19 pandemic has affected academia and parents alike. Due to the sudden closure of schools, students are missing social interaction which is vital for better learning and grooming while most schools have started online classes. This has become a tough routine for the parents working online at home since they have to ensure their children’s education. The study presented was designed to explore the experiences of home learning in times of COVID-19. A descriptive qualitative study was planned to explore the experiences of parents about home learning and management during COVID-19 to get an insight into real-life experiences.  Purposive sampling technique was used for data collection.  Data were collected from 19 parents falling in the inclusion criteria. Considering the lockdown problem, the data were collected via Google docs form with open-ended questions related to COVID-19 and home learning. Three major themes emerged after the data analysis: impact of COVID on children learning; support given by schools; and strategies used by caregivers at home to support learning. It was analyzed that the entire nation and academicians around the world have come forward to support learning at home offering a wide range of free online avenues to support parents to facilitate home-learning. Furthermore, parents too have adapted quickly to address the learning gap that have emerged in their children’s learning in these challenging times. Measures should be adopted to provide essential learning skills to children at home. Centralized data dashboards and educational technology may be used to keep the students, parents and schools updated.</em></p>

scholarly journals mtDNAcombine: tools to combine sequences from multiple studies

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Eleanor F. Miller ◽  
Andrea Manica
Keyword(s):  
Sequence Data ◽  
Data Extraction ◽  
Bayesian Skyline Plot ◽  
Model Organisms ◽  
Data Sets ◽  
Data Handling ◽  
Online Database ◽  
Genetic Studies ◽  
Wide Range ◽  
Existing Data

Abstract Background Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms’ classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species’ demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Results Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing sequence data for Bayesian skyline plot demographic reconstructions. Conclusions There is now more genetic information available than ever before and large meta-data sets offer great opportunities to explore new and exciting avenues of research. However, compiling multi-study datasets still remains a technically challenging prospect. The mtDNAcombine package provides a pipeline to streamline the process of downloading, curating, and analysing sequence data, guiding the process of compiling data sets from the online database GenBank.

scholarly journals A Systematic Review and Qualitative Synthesis Resulting in a Typology of Elementary Classroom Movement Integration Interventions

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Spyridoula Vazou ◽  
Collin A. Webster ◽  
Gregory Stewart ◽  
Priscila Candal ◽  
Cate A. Egan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Teacher Collaboration ◽  
A Priori ◽  
Real Life ◽  
Dose Intensity ◽  
Routine Practice ◽  
Qualitative Synthesis ◽  
Wide Range ◽  
Meta Analyses ◽  
Movement Integration

Abstract Background/Objective Movement integration (MI) involves infusing physical activity into normal classroom time. A wide range of MI interventions have succeeded in increasing children’s participation in physical activity. However, no previous research has attempted to unpack the various MI intervention approaches. Therefore, this study aimed to systematically review, qualitatively analyze, and develop a typology of MI interventions conducted in primary/elementary school settings. Subjects/Methods Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to identify published MI interventions. Irrelevant records were removed first by title, then by abstract, and finally by full texts of articles, resulting in 72 studies being retained for qualitative analysis. A deductive approach, using previous MI research as an a priori analytic framework, alongside inductive techniques were used to analyze the data. Results Four types of MI interventions were identified and labeled based on their design: student-driven, teacher-driven, researcher-teacher collaboration, and researcher-driven. Each type was further refined based on the MI strategies (movement breaks, active lessons, other: opening activity, transitions, reward, awareness), the level of intrapersonal and institutional support (training, resources), and the delivery (dose, intensity, type, fidelity). Nearly half of the interventions were researcher-driven, which may undermine the sustainability of MI as a routine practice by teachers in schools. An imbalance is evident on the MI strategies, with transitions, opening and awareness activities, and rewards being limitedly studied. Delivery should be further examined with a strong focus on reporting fidelity. Conclusions There are distinct approaches that are most often employed to promote the use of MI and these approaches may often lack a minimum standard for reporting MI intervention details. This typology may be useful to effectively translate the evidence into practice in real-life settings to better understand and study MI interventions.

scholarly journals Zolpidem for Insomnia: A Double-Edged Sword. A Systematic Literature Review on Zolpidem-Induced Complex Sleep Behaviors

2021 ◽  
pp. 025371762199237
Author(s):  
Niti Mittal ◽  
Rakesh Mittal ◽  
M. C. Gupta
Keyword(s):  
Adverse Reactions ◽  
Case Reports ◽  
Case Series ◽  
Eligibility Criteria ◽  
Study Objective ◽  
Spontaneous Reports ◽  
Cochrane Database ◽  
Sleep Behaviors ◽  
Therapeutic Doses ◽  
Favorable Side Effect Profile

Background: Being a nonbenzodiazepine, zolpidem is believed to have a favorable side-effect profile and is widely prescribed for insomnia. However, in the past few years, numerous neuropsychiatric adverse reactions, particularly complex sleep behaviors (CSBs), have been reported with zolpidem. Objective: To conduct a systematic review of zolpidem-associated CSBs. Data Sources: An electronic search was conducted using MEDLINE, Embase, PubMed, and Cochrane database of systematic reviews to extract relevant articles till July 2020. Study Eligibility Criteria: Any type of literature article (case report, case series, and observational or interventional study) reporting CSBs associated with zolpidem. Results: In this review, we present aggregate summarized data from 148 patients presenting with zolpidem-induced CSBs (79 patients from 23 case reports and 5 case series; 69 patients out of 1454 taking zolpidem [4.7%] from three observational clinical studies). Various types of CSBs associated with zolpidem were reported, most common being sleepwalking/somnambulism and sleep-related eating disorder. On causality assessment, around 88% of cases were found to have a probable association with zolpidem. Limitations: Extraction of data from observational studies and spontaneous reports, due to nonavailability of any randomized controlled trials relevant to the study objective. Conclusion and Implication of Key Findings: Zolpidem-induced CSBs, although not very common, may develop when the drug is used at therapeutic doses for insomnia. Doctors need to be alert to monitor such adverse effects of zolpidem and exercise caution while prescribing it.

scholarly journals MUREN: a robust and multi-reference approach of RNA-seq transcript normalization

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yance Feng ◽  
Lei M. Li
Keyword(s):  
Biological Significance ◽  
Housekeeping Genes ◽  
R Package ◽  
Data Sets ◽  
Statistical Regression ◽  
Rna Seq ◽  
Least Trimmed Squares ◽  
Standard Data ◽  
Wide Range ◽  
Multiple References

Abstract Background Normalization of RNA-seq data aims at identifying biological expression differentiation between samples by removing the effects of unwanted confounding factors. Explicitly or implicitly, the justification of normalization requires a set of housekeeping genes. However, the existence of housekeeping genes common for a very large collection of samples, especially under a wide range of conditions, is questionable. Results We propose to carry out pairwise normalization with respect to multiple references, selected from representative samples. Then the pairwise intermediates are integrated based on a linear model that adjusts the reference effects. Motivated by the notion of housekeeping genes and their statistical counterparts, we adopt the robust least trimmed squares regression in pairwise normalization. The proposed method (MUREN) is compared with other existing tools on some standard data sets. The goodness of normalization emphasizes on preserving possible asymmetric differentiation, whose biological significance is exemplified by a single cell data of cell cycle. MUREN is implemented as an R package. The code under license GPL-3 is available on the github platform: github.com/hippo-yf/MUREN and on the conda platform: anaconda.org/hippo-yf/r-muren. Conclusions MUREN performs the RNA-seq normalization using a two-step statistical regression induced from a general principle. We propose that the densities of pairwise differentiations are used to evaluate the goodness of normalization. MUREN adjusts the mode of differentiation toward zero while preserving the skewness due to biological asymmetric differentiation. Moreover, by robustly integrating pre-normalized counts with respect to multiple references, MUREN is immune to individual outlier samples.

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