The author sees through the modern healthcare system with his x-rays enabled eyes and reveals his astonishing discoveries. First, the author empowers readers, in the preface 1, with an innovative thinking tool: the time point view/time line view methodology. This demystified highly simplified approach in viewing controversial issues can be used widely beyond healthcare issue. In preface 2, the author sums up his opinions on current healthcare reform from perspective of diagnosing doctor. Secondly, in chapter 1-4, author conducts a virtue biopsy into our healthcare system and reveals four shocking findings. "Our system is truly a diseased care system instead of healthcare system". "Americans are paying billions for an interest-conflicting finance-sucking giant---a trading middleman, representing administrator (for providers) and a paying gateman (for claims) all in one---a handcuff preventing from fully and freely access to healthcare". "We are farming many our diseases instead of curing them". "Our system is only serving and attracting the most costly bands of cares in the whole healthcare spectrum". Thirdly, in chapter 5-7, author further pinpoints the places where the disease in the system resides and suggests the multiple approaches to cure it. Author also emphasizes the importance of mindset change before changing the healthcare system by comparing two types of diseases solution approaches-conventional modern medicine and traditional natural medicine. Fourthly, in chapter 8, author analyses the two most typical healthcare systems, which reside in the two opposite extreme ends, and proposes a completely new system based on the two. Therefore, the solution proposed is not only for the two extreme situations but also for all situations in between. The all proposed resolutions together may completely change the landscape of current healthcare infrastructure, reshape the mindset of Americans on healthcare, and reverse the high cost low efficacy of current healthcare system.
In this monograph, the graphene-based field-effect transistor (FET) biosensors are shown to be an emerging sensing platform. Divided into two parts the first set of chapters are devoted to basic knowledge of graphene, graphene FET and its biosensing. In the second part of this book the applications of graphene FET biosensors combined with various biotechnologies are presented. As well as discussing the existing technologies the authors also introduce their own ideas and concepts. Finally the remaining problems in graphene FET biosensors are discussed, along with proposed solutions and prospects for future applications. This monograph allows readers to grasp the basic knowledge and future direction of graphene-based FET biosensors.
This book focuses on the effects of L1 cognitive resources on L2 reading e.g. the effects of L1 reading ability, the ability in L1 mental-structure building, L1 cognitive use in L2 reading, and other related cognitive mechanisms and capacities of EFL learners in China. It integrated test-based and product-oriented as well as VPA-based (verbal protocol analysis) and process-oriented experiments to address the problems of reading in a second language. This book provides several theoretical, methodological and pedagogical insights, including the multidimensional nature of L2 reading and Vygotskyan sociocultural theory as a suitable L2 reading framework, combined approaches on L2 studies, and the rewarding active use of L1 cognitive resources in L2 learning.
As China races towards modernity, its cities are experiencing an unprecedented surge in urbanisation, characterised by a relentless influx of migrants and sprawling expansion into suburban realms. Shiyu Yang draws upon Henri Lefebvre's influential theoretical framework and applies it to case studies of two urban villages in Beijing to examine how migrants shape the social production of space in these districts. With a wealth of first-hand material from the field, this study provides essential insights into the ongoing processes and social dynamics that resonate with scholars from cross-disciplinary urban studies as well as practitioners in governance and urban planning.
Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.
The author sees through the modern healthcare system with his x-rays enabled eyes and reveals his astonishing discoveries. First, the author empowers readers, in the preface 1, with an innovative thinking tool: the time point view/time line view methodology. This demystified highly simplified approach in viewing controversial issues can be used widely beyond healthcare issue. In preface 2, the author sums up his opinions on current healthcare reform from perspective of diagnosing doctor. Secondly, in chapter 1-4, author conducts a virtue biopsy into our healthcare system and reveals four shocking findings. "Our system is truly a diseased care system instead of healthcare system". "Americans are paying billions for an interest-conflicting finance-sucking giant---a trading middleman, representing administrator (for providers) and a paying gateman (for claims) all in one---a handcuff preventing from fully and freely access to healthcare". "We are farming many our diseases instead of curing them". "Our system is only serving and attracting the most costly bands of cares in the whole healthcare spectrum". Thirdly, in chapter 5-7, author further pinpoints the places where the disease in the system resides and suggests the multiple approaches to cure it. Author also emphasizes the importance of mindset change before changing the healthcare system by comparing two types of diseases solution approaches-conventional modern medicine and traditional natural medicine. Fourthly, in chapter 8, author analyses the two most typical healthcare systems, which reside in the two opposite extreme ends, and proposes a completely new system based on the two. Therefore, the solution proposed is not only for the two extreme situations but also for all situations in between. The all proposed resolutions together may completely change the landscape of current healthcare infrastructure, reshape the mindset of Americans on healthcare, and reverse the high cost low efficacy of current healthcare system.
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