High-confidence discrimination of explosive materials on surfaces using a non-spectroscopic optical biomimetic sensing method

2018 ◽  
Author(s):  
Kevin J. Major ◽  
Kenneth J. Ewing ◽  
Jasbinder S. Sanghera ◽  
Thomas C. Hutchens ◽  
Menelaos K. Poutous ◽  
...  
Keyword(s):  
High Confidence ◽  
Explosive Materials

scholarly journals Discrimination Between Explosive Materials and Isomers Using a Human Color Vision-Inspired Sensing Method

2019 ◽  
Vol 73 (5) ◽  
pp. 520-528 ◽  
Author(s):  
Kevin J. Major ◽  
Thomas C. Hutchens ◽  
Christopher R. Wilson ◽  
Menelaos K. Poutous ◽  
Ishwar D. Aggarwal ◽  
...  
Keyword(s):  
Color Vision ◽  
Optical Filters ◽  
High Confidence ◽  
Absorption Bands ◽  
Vision Sensing ◽  
Explosive Materials ◽  
Human Color Vision ◽  
Ft Ir ◽  
Aluminum Substrates ◽  
Ft Ir Spectroscopy

This paper describes the application of a human color vision approach to infrared (IR) chemical sensing for the discrimination between multiple explosive materials deposited on aluminum substrates. This methodology classifies chemicals using the unique response of the chemical vibrational absorption bands to three broadband overlapping IR optical filters. For this effort, Fourier transform infrared (FT-IR) spectroscopy is first used to computationally examine the ability of the human color vision sensing approach to discriminate between three similar explosive materials, 1,3,5,-Trinitro-1,3,5-triazinane (RDX), 2,2-Bis[(nitrooxy)methyl]propane-1,3,-diyldinitrate (PETN), and 1,3,5,7-Tetranitro-1,3,5,7-tetrazocane (HMX). A description of a laboratory breadboard optical sensor designed for this approach is then provided, along with the discrimination results collected for these samples using this sensor. The results of these studies demonstrate that the human color vision approach is capable of high-confidence discrimination of the examined explosive materials.

The role of recollection in high-confidence know judgments

2010 ◽  
Author(s):  
Laura Mickes ◽  
Vivian Hwe ◽  
John T. Wixted
Keyword(s):  
High Confidence

High Confidence Heuristic Strategy for Minimal Reduction

2012 ◽  
Vol 38 (11) ◽  
pp. 1751
Author(s):  
Lin-Zi YIN ◽  
Yong-Gang LI ◽  
Chun-Hua YANG ◽  
Wei-Hua GUI
Keyword(s):  
High Confidence ◽  
Heuristic Strategy ◽  
Minimal Reduction

Standoff Raman Detection of Explosive Materials Using a Small Raman Spectroscopy System

2017 ◽  
Vol 20 (3) ◽  
pp. 60-66 ◽  
Author(s):  
Naseer M. Hadi ◽  
◽  
Mohammad R. Mohammad ◽  
Haider G. Abdulzahraa ◽  
Keyword(s):  
Raman Spectroscopy ◽  
Explosive Materials ◽  
Spectroscopy System

scholarly journals Exomic Sequencing of Medullary Thyroid Cancer Reveals Dominant and Mutually Exclusive Oncogenic Mutations in RET and RAS

2013 ◽  
Vol 98 (2) ◽  
pp. E364-E369 ◽  
Author(s):  
Nishant Agrawal ◽  
Yuchen Jiao ◽  
Mark Sausen ◽  
Rebecca Leary ◽  
Chetan Bettegowda ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Somatic Mutations ◽  
Medullary Thyroid Cancer ◽  
Driver Mutations ◽  
High Confidence ◽  
Kras Mutations ◽  
Protein Coding ◽  
Medullary Thyroid ◽  
Oncogenic Mutations ◽  
Independent Cohort

Abstract Context: Medullary thyroid cancer (MTC) is a rare thyroid cancer that can occur sporadically or as part of a hereditary syndrome. Objective: To explore the genetic origin of MTC, we sequenced the protein coding exons of approximately 21,000 genes in 17 sporadic MTCs. Patients and Design: We sequenced the exomes of 17 sporadic MTCs and validated the frequency of all recurrently mutated genes and other genes of interest in an independent cohort of 40 MTCs comprised of both sporadic and hereditary MTC. Results: We discovered 305 high-confidence mutations in the 17 sporadic MTCs in the discovery phase, or approximately 17.9 somatic mutations per tumor. Mutations in RET, HRAS, and KRAS genes were identified as the principal driver mutations in MTC. All of the other additional somatic mutations, including mutations in spliceosome and DNA repair pathways, were not recurrent in additional tumors. Tumors without RET, HRAS, or KRAS mutations appeared to have significantly fewer mutations overall in protein coding exons. Conclusions: Approximately 90% of MTCs had mutually exclusive mutations in RET, HRAS, and KRAS, suggesting that RET and RAS are the predominant driver pathways in MTC. Relatively few mutations overall and no commonly recurrent driver mutations other than RET, HRAS, and KRAS were seen in the MTC exome.

scholarly journals Standard Quality Banking Services of Islamic Banks

2018 ◽  
Vol 8 (1) ◽  
pp. 301
Author(s):  
Haneen A. Al-Khawaja ◽  
Barjoyai Bardai
Keyword(s):  
Islamic Law ◽  
Theoretical Aspect ◽  
Islamic Banking ◽  
Islamic Banks ◽  
High Confidence ◽  
Banking Services ◽  
Standard Quality ◽  
Definition Of

This research discusses in detail the theoretical aspect of the quality standards of banking services of traditional Islamic banks. The criterion of "Shari'ah Compliance" was added by the researcher to the importance and role of dealing with Islamic banks, the definition of this standard and its importance, how to test it for banks as well as how, without the legitimate commitment of these banks to what is classified as Islamic from the foundation, we focus on the importance of the existence of a legal commitment to any Islamic bank to achieve the quality of Islamic banking services of high quality in accordance with Islamic law and laws to achieve a high confidence in the customers who belong to him and deal with his Conspiracy.

scholarly journals AB0140 A HIGH-CONFIDENCE DEFINITION OF THERAPEUTIC RESPONSE IN RHEUMATOID ARTHRITIS USING A MONTE CARLO SIMULATION APPROACH

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1097.2-1098
Author(s):  
V. Strand ◽  
S. Cohen ◽  
L. Zhang ◽  
T. Mellors ◽  
A. Jones ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Monte Carlo ◽  
Disease Activity ◽  
Health Assessment Questionnaire ◽  
Health Assessment ◽  
High Confidence ◽  
Response Status ◽  
Definition Of ◽  
Fidelity Score ◽  
Assessment Questionnaire

Background:Therapy choice and therapy change depend on the ability to accurately assess patients’ disease activity. The clinical assessments used to evaluate treatment response in rheumatoid arthritis have inherent variability, normally considered as measurement error, intra-observer variability or within subject variability. Each contribute to variability in deriving response status as defined by composite measures such as the ACR or EULAR criteria, particularly when a one-time observed measurement lies near the boundary defining response or non-response. To select an optimal therapeutic strategy in the burgeoning age of precision medicine in rheumatology, achieve the lowest disease activity and maximize long-term health outcomes for each patient, improved treatment response definitions are needed.Objectives:Develop a high-confidence definition of treatment response and non-response in rheumatoid arthritis that exceeds the expected variability of subcomponents in the composite response criteria.Methods:A Monte Carlo simulation approach was used to assess ACR50 and EULAR response outcomes in 100 rheumatoid arthritis patients who had been treated for 6 months with a TNF inhibitor therapy. Monte Carlo simulations were run with 2000 iterations implemented with measurement variability derived for each clinical assessment: tender joint count, swollen joint count, Health Assessment Questionnaire disability index (HAQ-DI), patient pain assessment, patient global assessment, physician global assessment, serum C-reactive protein level (CRP) and disease activity score 28-joint count with CRP.1-3 Each iteration of the Monte Carlo simulation generated one outcome with a value of 0 or 1 indicating non-responder or responder, respectively.Results:A fidelity score, calculated separately for ACR50 and EULAR response, was defined as an aggregated score from 2000 iterations reported as a fraction that ranges from 0 to 1. The fidelity score depicted a spectrum of response covering strong non-responders, inconclusive statuses and strong responders. A fidelity score around 0.5 typified a response status with extreme variability and inconclusive clinical response to treatment. High-fidelity scores were defined as >0.7 or <0.3 for responders and non-responders, respectively, meaning that the simulated clinical response status label among all simulations agreed at least 70% of the time. High-confidence true responders were considered as those patients with high-fidelity outcomes in both ACR50 and EULAR outcomes.Conclusion:A definition of response to treatment should exceed the expected variability of the clinical assessments used in the composite measure of therapeutic response. By defining high-confidence responders and non-responders, the true impact of therapeutic efficacy can be determined, thus forging a path to development of better treatment options and advanced precision medicine tools in rheumatoid arthritis.References:[1]Cheung, P. P., Gossec, L., Mak, A. & March, L. Reliability of joint count assessment in rheumatoid arthritis: a systematic literature review. Semin Arthritis Rheum43, 721-729, doi:10.1016/j.semarthrit.2013.11.003 (2014).[2]Uhlig, T., Kvien, T. K. & Pincus, T. Test-retest reliability of disease activity core set measures and indices in rheumatoid arthritis. Ann Rheum Dis68, 972-975, doi:10.1136/ard.2008.097345 (2009).[3]Maska, L., Anderson, J. & Michaud, K. Measures of functional status and quality of life in rheumatoid arthritis: Health Assessment Questionnaire Disability Index (HAQ), Modified Health Assessment Questionnaire (MHAQ), Multidimensional Health Assessment Questionnaire (MDHAQ), Health Assessment Questionnaire II (HAQ-II), Improved Health Assessment Questionnaire (Improved HAQ), and Rheumatoid Arthritis Quality of Life (RAQoL). Arthritis Care Res (Hoboken) 63 Suppl 11, S4-13, doi:10.1002/acr.20620 (2011).Disclosure of Interests:Vibeke Strand Consultant of: Abbvie, Amgen, Arena, BMS, Boehringer Ingelheim, Celltrion, Galapagos, Genentech/Roche, Gilead, GSK, Ichnos, Inmedix, Janssen, Kiniksa, Lilly, Merck, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Setpoint, UCB, Stanley Cohen: None declared, Lixia Zhang Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Ted Mellors Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Alex Jones Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Johanna Withers Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Viatcheslav Akmaev Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation

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