Adaptive Failure Search Using Critical States from Domain Experts

2021 ◽  
Author(s):  
Peter Du ◽  
Katherine Driggs-Campbell
Keyword(s):  
Critical States ◽  
Domain Experts

Characteristics of the etiological structure and susceptibility to antibiotics, antiseptics of infectious pathogens of respiratory organs in children in critical states

2018 ◽  
Vol 22 (2) ◽  
pp. 311-317
Author(s):  
O.A. Nazarchuk ◽  
A.I. Starodub ◽  
O.V. Rymsha ◽  
V.A. Starodub ◽  
S.A. Kolodii
Keyword(s):  
Antimicrobial Activity ◽  
Antibacterial Agents ◽  
Inflammatory Diseases ◽  
Diffusion Method ◽  
Chlorhexidine Digluconate ◽  
Gram Positive ◽  
Critical States ◽  
Results Of Treatment ◽  
Moderate Resistance ◽  
Staphylococcus Spp

The study of the etiological structure, the properties of pathogens of the respiratory infectious diseases in children and their resistance to antibacterial agents is particularly relevant in modern conditions, expands the search for new approaches to combating pathogens, improves the results of treatment and reduces the mortality of this pathology. The aim — study of etiological structure, sensitivity to antibiotics and antiseptics of pathogens of infectious and inflammatory diseases of respiratory organs in children. In the study there were enrolled 247 patients who were treated in Vinnytsia Regional Children’s Clinical Hospital (VRCCH) in 2016. The sensitivity of microorganisms to 23 antibacterial agents was determined by the disc-diffusion method according to the generally accepted method. The analysis of the antimicrobial activity of antiseptic drugs (decamethoxine, miramistin, chlorhexidine digluconate) was performed by a double serial dilution technique with the determination of the minimum inhibitory bacteriostatic (MIC) and bactericidal (MBcC) concentrations, by the method of successive serial dilutions of the drug in a liquid nutrient medium. In patients who were in inpatient treatment at the VRCCH in 2016 because of pneumonia there were found opportunistic microorganisms which were of etiological significance in the development of the infection. Among them there were Streptococci (47,3 %), Staphylococci (15,3 %), Candida (13,3 %), Enterococci (10,9 %), including a high proportion of owned non-fermenting gram negative bacilli (9,8%) and species of Enterobacteria (2,0 %). Isolated strains of microorganisms had moderate resistance to most modern antibiotic drugs. The sensitivity of isolated strains of microorganisms to reserved antibiotics as carbapenems, often being used in the treatment of critical states of patients in the intensive care units, was found to above 18,2%. The sensitivity to this antibiotic in Enterococcus spp. (7,1 %), Staphylococcus spp. (5,9 %) was also low. Carbapenems, fluoroquinolones (the 1st and 2nd generations), antibiotics and aminoglycosides were found to be effective against gram positive microorganisms in more then 45% of cases. According to this they were considered to be as drugs of choice in the treatment of infectious and purulent-inflammatory pathology of respiratory organs, caused metitcilin- and vancomycin-resistant strains of microorganisms. Resistance to these drugs among investigated strains did not exceed 9,0 %. The high bactericidal properties of antiseptics as decamethoxine was determined against S.pyogenes, Staphylococcus spp. Its MBcC against these bacteria (1,65±0,20 mkg/ml and 4,32±0,50 mkg/ml, respectively) proved the advantage of decamethoxine’s effectiveness in comparison with chlorhexidine digluconate 3,14 times, 2,44 times miramistin. Clinical strains of C.albicans showed the highest susceptibility to decamethoxine, which fungicidal activity was determined in the presence (16,17±2,33 mkg/ml), in comparison with chlorxedine (MFtsK 27,59±3,59 mg/ml) and miramistin activity (27,59±3,595 mkg/ml). In children with inflammatory diseases of the respiratory organs gram-positive cocci are among the predominant pathogens (73,5 %) of cases, in the association allocated – 8,0 % of pathogens. Allocated strains of microorganisms were moderately resistant to all antibiotics studied. For antimicrobial activity antiseptic drugs, especially decamethoxine, have advantages over antibiotics confirming the possibility of their use in combination with systemic antibacterials.

scholarly journals CSR Initiatives and Practices: Empirical Evidence From Indian Metal and Mining Companies

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110326
Author(s):  
Ajay K. Singal
Keyword(s):  
Environmental Sustainability ◽  
Annual Reports ◽  
Local Domain ◽  
Internal Governance ◽  
Domain Experts ◽  
Analysis Technique ◽  
Extractive Sector ◽  
Second Tier ◽  
Corporate Social ◽  
Text Network Analysis

This study investigates the corporate social responsibility (CSR) discourse on community and environment by Indian metal and mining (extractive) sector. Specifically, we examine the change in internal governance and external implementation mechanisms in response to affirmative CSR policy actions. Applying text network analysis technique on CSR related expenditures provided in the annual reports and CSR annexures (2014–2018), our study reveals that CSR discourse of extractive firms improved significantly and became more focused after the introduction of post-affirmative policy. CSR initiatives in the extractive sector are primarily focused toward local social development, with little emphasis on the environmental sustainability. Furthermore, companies have adopted two-tier governance structures for managing CSR. The top tier comprises board members who formulate the CSR programs, while the second tier has executives responsible for the implementation. Another tier of governance involving local domain experts is emerging. The three-tier implementation mechanisms give firms a tighter control on spending and enhance the effectiveness of initiatives. We present the results visually in the form of network graphs.

scholarly journals Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms

2021 ◽  
Vol 18 (7) ◽  
pp. 3451
Author(s):  
Tabassom Sedighi ◽  
Liz Varga
Keyword(s):  
Risk Factors ◽  
Bovine Tuberculosis ◽  
Animal Health ◽  
Dynamic Bayesian Network ◽  
Policy Makers ◽  
Domain Experts ◽  
Actual Experience ◽  
Complex Evaluation ◽  
Risk Areas ◽  
Cattle Farms

Controlling bovine tuberculosis (bTB) disease in cattle farms in England is seen as a challenge for farmers, animal health, environment and policy-makers. The difficulty in diagnosis and controlling bTB comes from a variety of factors: the lack of an accurate diagnostic test which is higher in specificity than the currently available skin test; isolation periods for purchased cattle; and the density of active badgers, especially in high-risk areas. In this paper, to enable the complex evaluation of bTB disease, a dynamic Bayesian network (DBN) is designed with the help of domain experts and available historical data. A significant advantage of this approach is that it represents bTB as a dynamic process that evolves periodically, capturing the actual experience of testing and infection over time. Moreover, the model demonstrates the influence of particular risk factors upon the risk of bTB breakdown in cattle farms.

Regulations and Norms for Reuse of Residual Clinical Biospecimens and Health Data

2021 ◽  
pp. 019394592110292
Author(s):  
Elizabeth E. Umberfield ◽  
Sharon L. R. Kardia ◽  
Yun Jiang ◽  
Andrea K. Thomer ◽  
Marcelline R. Harris
Keyword(s):  
Informed Consent ◽  
Scoping Review ◽  
Real World ◽  
Genetic Information ◽  
Final Analysis ◽  
Health Data ◽  
Federal Regulations ◽  
Secondary Research ◽  
Domain Experts ◽  
Key Issues

Nurse scientists are increasingly interested in conducting secondary research using real world collections of biospecimens and health data. The purposes of this scoping review are to (a) identify federal regulations and norms that bear authority or give guidance over reuse of residual clinical biospecimens and health data, (b) summarize domain experts’ interpretations of permissions of such reuse, and (c) summarize key issues for interpreting regulations and norms. Final analysis included 25 manuscripts and 23 regulations and norms. This review illustrates contextual complexity for reusing residual clinical biospecimens and health data, and explores issues such as privacy, confidentiality, and deriving genetic information from biospecimens. Inconsistencies make it difficult to interpret, which regulations or norms apply, or if applicable regulations or norms are congruent. Tools are necessary to support consistent, expert-informed consent processes and downstream reuse of residual clinical biospecimens and health data by nurse scientists.

scholarly journals Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5476
Author(s):  
Ana Pajić Simović ◽  
Slađan Babarogić ◽  
Ognjen Pantelić ◽  
Stefan Krstović
Keyword(s):  
Process Mining ◽  
Modeling Language ◽  
Sufficient Information ◽  
Event Data ◽  
Erp Systems ◽  
Domain Experts ◽  
Domain Specific ◽  
Event Logs ◽  
Domain Specific Modeling ◽  
Specific Modeling

Enterprise resource planning (ERP) systems are often seen as viable sources of data for process mining analysis. To perform most of the existing process mining techniques, it is necessary to obtain a valid event log that is fully compliant with the eXtensible Event Stream (XES) standard. In ERP systems, such event logs are not available as the concept of business activity is missing. Extracting event data from an ERP database is not a trivial task and requires in-depth knowledge of the business processes and underlying data structure. Therefore, domain experts require proper techniques and tools for extracting event data from ERP databases. In this paper, we present the full specification of a domain-specific modeling language for facilitating the extraction of appropriate event data from transactional databases by domain experts. The modeling language has been developed to support complex ambiguous cases when using ERP systems. We demonstrate its applicability using a case study with real data and show that the language includes constructs that enable a domain expert to easily model data of interest in the log extraction step. The language provides sufficient information to extract and transform data from transactional ERP databases to the XES format.

scholarly journals Robust diagnostic classification via Q-learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Victor Ardulov ◽  
Victor R. Martinez ◽  
Krishna Somandepalli ◽  
Shuting Zheng ◽  
Emma Salzman ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Decision Function ◽  
Diagnostic Classification ◽  
Decision Making Process ◽  
Domain Experts ◽  
Q Learning ◽  
School Aged Children ◽  
Hyperactivity Disorder ◽  
Clinical Diagnoses ◽  
Learning Frameworks

AbstractMachine learning (ML) models have demonstrated the power of utilizing clinical instruments to provide tools for domain experts in gaining additional insights toward complex clinical diagnoses. In this context these tools desire two additional properties: interpretability, being able to audit and understand the decision function, and robustness, being able to assign the correct label in spite of missing or noisy inputs. This work formulates diagnostic classification as a decision-making process and utilizes Q-learning to build classifiers that meet the aforementioned desired criteria. As an exemplary task, we simulate the process of differentiating Autism Spectrum Disorder from Attention Deficit-Hyperactivity Disorder in verbal school aged children. This application highlights how reinforcement learning frameworks can be utilized to train more robust classifiers by jointly learning to maximize diagnostic accuracy while minimizing the amount of information required.

scholarly journals A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2514
Author(s):  
Tharindu Kaluarachchi ◽  
Andrew Reis ◽  
Suranga Nanayakkara
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Review Paper ◽  
Learning Systems ◽  
Learning Approaches ◽  
Application Development ◽  
Research Gaps ◽  
Domain Experts ◽  
Working Definition ◽  
Real World Application

After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in algorithms, and researchers and users have raised concerns regarding the usability and adoptability of Deep Learning systems. These concerns, coupled with the increasing human-AI interactions, have created the emerging field that is Human-Centered Machine Learning (HCML). We present this review paper as an overview and analysis of existing work in HCML related to DL. Firstly, we collaborated with field domain experts to develop a working definition for HCML. Secondly, through a systematic literature review, we analyze and classify 162 publications that fall within HCML. Our classification is based on aspects including contribution type, application area, and focused human categories. Finally, we analyze the topology of the HCML landscape by identifying research gaps, highlighting conflicting interpretations, addressing current challenges, and presenting future HCML research opportunities.

Model-based diagnosis of the space shuttle main engine

1992 ◽  
Vol 6 (3) ◽  
pp. 131-148 ◽  
Author(s):  
Martin O. Hofmann ◽  
Thomas L. Cost ◽  
Michael Whitley
Keyword(s):  
Space Shuttle ◽  
Diagnostic System ◽  
End User ◽  
Reasoning Process ◽  
Domain Experts ◽  
Model Based ◽  
Knowledge Based ◽  
Modeling Analysis ◽  
Engine Design ◽  
Main Engine

The process of reviewing test data for anomalies after a firing of the Space Shuttle Main Engine (SSME) is a complex, time-consuming task. A project is under way to provide the team of SSME experts with a knowledge-based system to assist in the review and diagnosis task. A model-based approach was chosen because it can be adapted to changes in engine design, is easier to maintain, and can be explained more easily. A complex thermodynamic fluid system like the SSME introduces problems during modeling, analysis, and diagnosis which have as yet been insufficiently studied. We developed a qualitative constraint-based diagnostic system inspired by existing qualitative modeling and constraint-based reasoning methods which addresses these difficulties explicitly. Our approach combines various diagnostic paradigms seamlessly, such as the model-based and heuristic association-based paradigms, in order to better approximate the reasoning process of the domain experts. The end-user interface allows expert users to actively participate in the reasoning process, both by adding their own expertise and by guiding the diagnostic search performed by the system.

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