There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf

The future of employment: How susceptible are jobs to computerisation?

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

During active disease, patients with systemic-onset juvenile chronic arthritis (S-JCA) demonstrate a rise and fall in serum interleukin-6 (IL-6) that parallels the classic quotidian fever. To investigate the possibility that this cytokine profile results from a difference in the control of IL-6 expression, we examined the 5' flanking region of the IL-6 gene for polymorphisms. A G/C polymorphism was detected at position -174. In a group of 383 healthy men and women from a general practice in North London, the frequency of the C allele was 0.403 (95% confidence interval 0.37-0.44). In comparison, 92 patients with S-JCA had a different overall genotype frequency, especially those with onset of disease at < 5 yr of age. This was mainly due to the statistically significant lower frequency of the CC genotype in this subgroup. When comparing constructs of the 5' flanking region (-550-+61 bp) in a luciferase reporter vector transiently transfected into HeLa cells, the -174C construct showed 0.624+/-0.15-fold lower expression than the -174G construct. After stimulation with LPS or IL-1, expression from the -174C construct did not significantly change after 24 h, whereas expression from the -174G construct increased by 2.35+/-0.10- and 3.60+/-0.26-fold, respectively, compared with the unstimulated level. Plasma levels of IL-6 were also measured in 102 of the healthy subjects, and the C allele was found to be associated with significantly lower levels of plasma IL-6. These results suggest that there is a genetically determined difference in the degree of the IL-6 response to stressful stimuli between individuals. The reduced frequency of the potentially protective CC genotype in young S-JCA patients may contribute to its pathogenesis. Similarly the individual's IL-6 genotype may be highly relevant in other conditions where IL-6 has been implicated, such as atherosclerosis.

/pdf/the-effect-of-novel-polymorphisms-in-the-interleukin-6-il-6-1ex1zrvxnz.pdf

The effect of novel polymorphisms in the interleukin-6 (IL-6) gene on IL-6 transcription and plasma IL-6 levels, and an association with systemic-onset juvenile chronic arthritis.

This paper explores how the remaining useful life (RUL) can be assessed for complex systems whose internal state variables are either inaccessible to sensors or hard to measure under operational conditions. Consequently, inference and estimation techniques need to be applied on indirect measurements, anticipated operational conditions, and historical data for which a Bayesian statistical approach is suitable. Models of electrochemical processes in the form of equivalent electric circuit parameters were combined with statistical models of state transitions, aging processes, and measurement fidelity in a formal framework. Relevance vector machines (RVMs) and several different particle filters (PFs) are examined for remaining life prediction and for providing uncertainty bounds. Results are shown on battery data.

Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework

Prognostics is an emerging concept in condition based maintenance (CBM) of critical systems. Along with developing the fundamentals of being able to confidently predict Remaining Useful Life (RUL), the technology calls for fielded applications as it inches towards maturation. This requires a stringent performance evaluation so that the significance of the concept can be fully exploited. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few issues. Instead, the research community has used a variety of metrics based largely on convenience with respect to their respective requirements. Very little attention has been focused on establishing a common ground to compare different efforts. This paper surveys the metrics that are already used for prognostics in a variety of domains including medicine, nuclear, automotive, aerospace, and electronics. It also considers other domains that involve prediction-related tasks, such as weather and finance. Differences and similarities between these domains and health maintenance have been analyzed to help understand what performance evaluation methods may or may not be borrowed. Further, these metrics have been categorized in several ways that may be useful in deciding upon a suitable subset for a specific application. Some important prognostic concepts have been defined using a notational framework that enables interpretation of different metrics coherently. Last, but not the least, a list of metrics has been suggested to assess critical aspects of RUL predictions before they are fielded in real applications.

https://ti.arc.nasa.gov/m/profile/schwabac/PHM_Metrics_Final.pdf

Metrics for evaluating performance of prognostic techniques

In this article, we examine prognostics and health management (PHM) issues using battery health management of Gen 2 cells, an 18650-size lithium-ion cell, as a test case. We will show where advanced regression, classification, and state estimation algorithms have an important role in the solution of the problem and in the data collection scheme for battery health management that we used for this case study.

https://ti.arc.nasa.gov/m/pub-archive/1460h/1460%20%28Goebel%29.pdf

Prognostics in Battery Health Management

The estimation of remaining useful life (RUL) of a faulty component is at the centre of system prognostics and health management. It gives operators a potent tool in decision making by quantifying ...

https://ti.arc.nasa.gov/m/pub-archive/1454h/1454%20(Saha).pdf

Comparison of prognostic algorithms for estimating remaining useful life of batteries

Prognostic performance evaluation has gained significant attention in the past few years. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.

http://papers.phmsociety.org/index.php/ijphm/article/download/1336/324

Bhaskar Saha

Papers

Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework

Metrics for evaluating performance of prognostic techniques

Prognostics in Battery Health Management

Comparison of prognostic algorithms for estimating remaining useful life of batteries

Metrics for Offline Evaluation of Prognostic Performance