Chinese Medicine Student Clubs in Taipei, Taiwan

This thesis focuses on a communal form of transmission of Chinese medicine in contemporary Taiwan: Chinese medicine university student clubs. Offering fundamental Chinese medicine curricula to students and the interested public, the student clubs used to serve as a direct educational steppingstone towards licensed practice. Recent changes in medical education policy, however, made a university degree in Chinese medicine a requirement, thereby pushing informal ways of knowledge transmission into the realm of lay activity. Nevertheless, the clubs remain active and still serve as a community for people interested in Chinese medicine, including those wanting to pursue it professionally. Based on field research conducted in two such university clubs in Taipei in early 2018, this thesis first outlines the challenges and tensions faced and negotiated by those club members with professional ambitions. Not (yet) enrolled in “official” Chinese medicine programs at university but already deeply engaged in learning, they constitute a group of people rarely represented in academic literature, namely those just orienting themselves towards becoming Chinese medicine physicians. These processes of orientation and becoming are shaped by organizational, economic, and epistemological pressures and embedded in transnational movements, imaginaries, and regulatory regimes. Secondly, the thesis examines the function and position of the clubs in the changing landscape of Chinese medical education in Taiwan, as well as in the wider field of transmission of Chinese medicine. I argue that they foster continued interest in Chinese medicine in an environment that has favored biomedicine since the Japanese colonial era and that they, although through paths more winded than before, still contribute to the reproduction of professional Chinese medical expertise. In addition, they provide space for communal forms of healthcare. Lastly, they contribute to the maintenance of everyday healthcare competence in the wider public, or what Arthur Kleinman (1980) has called the “popular sector of healthcare.

A statistical test for Nested Sampling algorithms

Nested sampling is an iterative integration procedure that shrinks the prior volume towards higher likelihoods by removing a "live" point at a time. A replacement point is drawn uniformly from the prior above an ever-increasing likelihood threshold. Thus, the problem of drawing from a space above a certain likelihood value arises naturally in nested sampling, making algorithms that solve this problem a key ingredient to the nested sampling framework. If the drawn points are distributed uniformly, the removal of a point shrinks the volume in a well-understood way, and the integration of nested sampling is unbiased. In this work, I develop a statistical test to check whether this is the case. This "Shrinkage Test" is useful to verify nested sampling algorithms in a controlled environment. I apply the shrinkage test to a test-problem, and show that some existing algorithms fail to pass it due to over-optimisation. I then demonstrate that a simple algorithm can be constructed which is robust against this type of problem. This RADFRIENDS algorithm is, however, inefficient in comparison to MULTINEST.Comment: 11 pages, 7 figures. Published in Statistics and Computing, Springer, September 201

Neurofly 2008 abstracts : the 12th European Drosophila neurobiology conference 6-10 September 2008 Wuerzburg, Germany

This volume consists of a collection of conference abstracts

Collaborative Nested Sampling: Big Data vs. complex physical models

The data torrent unleashed by current and upcoming astronomical surveys demands scalable analysis methods. Many machine learning approaches scale well, but separating the instrument measurement from the physical effects of interest, dealing with variable errors, and deriving parameter uncertainties is often an after-thought. Classic forward-folding analyses with Markov Chain Monte Carlo or Nested Sampling enable parameter estimation and model comparison, even for complex and slow-to-evaluate physical models. However, these approaches require independent runs for each data set, implying an unfeasible number of model evaluations in the Big Data regime. Here I present a new algorithm, collaborative nested sampling, for deriving parameter probability distributions for each observation. Importantly, the number of physical model evaluations scales sub-linearly with the number of data sets, and no assumptions about homogeneous errors, Gaussianity, the form of the model or heterogeneity/completeness of the observations need to be made. Collaborative nested sampling has immediate application in speeding up analyses of large surveys, integral-field-unit observations, and Monte Carlo simulations.Comment: Resubmitted to PASP Focus on Machine Intelligence in Astronomy and Astrophysics after first referee report. Figure 6 demonstrates the scaling for Collaborative MultiNest, PolyChord and RadFriends implementations. Figure 10 application to MUSE IFU data. Implementation at https://github.com/JohannesBuchner/massivedatan

"Steeping" Of Health Expenditure Profiles

If health care expenditure for the elderly grows faster than for younger people, the expenditure profiles become "steeper" – we call that "steeping". Three instruments for measuring "steeping" are presented: (1) trend of the relation between per-capita-expenditure of the old and the young; (2) comparing the linear slopes of per-capita-expenditure in age groups; (3) trend in parameters of non-linear modelling of expenditure profiles. Using data of the largest German private health insurer over a period of 18 years, "steeping" could be observed by all three methods in most examined insurance plans. A prognosis for 2040 shows that per-capita-expenditure will increase by 128 %. --health care expenditure,expenditure profiles,demographics

Relativistic reflection from accretion disks in the population of Active Galactic Nuclei at z=0.5-4

We report the detection of relativistically broadened iron K alpha emission in the X-ray spectra of AGN detected in the 4Ms CDF-S. Using the Bayesian X-ray analysis (BXA) package, we fit 199 hard band (2-7 keV) selected sources in the redshift range z=0.5--4 with three models: (i) an absorbed power-law, (ii) the first model plus a narrow reflection component, and (iii) the second model with an additional relativistic broadened reflection. The Bayesian evidence for the full sample of sources selects the model with the additional broad component as being 10^5 times more probable to describe the data better than the second model. For the two brightest sources in our sample, CID 190 (z=0.734) and CID 104 (z=0.543), BXA reveals the relativistic signatures in the individual spectra. We estimate the fraction of sources containing a broad component to be 54^{+35}_{-37}% (107/199 sources). Considering that the low signal-to-noise ratio of some spectra prevents the detection of the broad iron K alpha line, we infer an intrinsic fraction with broad emission of around two thirds. The detection of relativistic signatures in the X-ray spectra of these sources suggests that they are powered by a radiatively efficient accretion disk. Preliminary evidence is found that the spin of the black hole is high, with a maximally spinning Kerr BH model (a=1) providing a significantly better fit than a Schwarzschild model (a=0). Our analysis demonstrate the potential of X-ray spectroscopy to measure this key parameter in typical SMBH systems at the peak of BH growth.Comment: 10 pages, 5 figures, accepted for publication in MNRA

Regional and Sub-Global Climate Blocs.A Game-Theoretic Perspective on Bottom-up Climate Regimes

No international regime on climate change is going to be fully effective in controlling GHG emissions without the involvement of countries such as China, India, the United States, Australia, and possibly other developing countries. This highlights an unambiguous weakness of the Kyoto Protocol, where the aforementioned countries either have no binding emission targets or have decided not to comply with their targets. Therefore, when discussing possible post-Kyoto scenarios, it is crucial to prioritise participation incentives for all countries, especially those without explicit or with insufficient abatement targets. This paper offers a bottom-up game-theoretic perspective on participation incentives. Rather than focusing on issue linkage, transfers or burden sharing as tools to enhance the incentives to participate in a climate agreement, this paper aims at exploring whether a different policy approach could lead more countries to adopt effective climate control policies. This policy approach is explicitly bottom-up, namely it gives each country the freedom to sign agreements and deals, bilaterally or multilaterally, with other countries, without being constrained by any global protocol or convention. This study provides a game-theoretic assessment of this policy approach and then evaluates empirically the possible endogenous emergence of single or multiple climate coalitions. Welfare and technological consequences of different multiple bloc climate regimes will be assessed and their overall environmental effectiveness will be discussed.Agreements, Climate, Incentives, Negotiations, Policy

Emissions Trading Regimes and Incentives to Participate in International Climate Agreements

This paper analyses whether different emissions trading regimes provide different incentives to participate in a cooperative climate agreement. Different incentive structures are discussed for those countries, namely the US, Russia and China, that are most important in the climate negotiation process. Our analysis confirms the conjecture that, by appropriately designing the emission trading regime, it is possible to enhance the incentives to participate in a climate agreement. Therefore, participation and optimal policy should be jointly analysed. Moreover, our results show that the US, Russia and China have different most preferred climate coalitions and therefore adopt conflicting negotiation strategies.Agreements, Climate, Incentives, Negotiations, Policy

Economic and Environmental Effectiveness of a Technology-based Climate Protocol

The present stalemate in climate negotiations has led policy analysts and economists to explore the possible emergence of alternative climate regimes. This paper explores the idea of replacing international cooperation on greenhouse gas emission control with international cooperation on climate-related technological innovation and diffusion. This idea – recently proposed among others by Barrett (2001) and Benedick (2001) – is based on the insight that incentives to free-ride are much smaller in the case of technological cooperation than in the case of cooperation on emission control. This paper provides a first applied game theory analysis of a technology-based climate protocol by assessing: (i) the self-enforcingness (namely, the absence of incentives to free ride) of the coalition that would form when countries negotiate on climate-related technological cooperation; (ii) the environmental effectiveness of a technology-based climate protocol. The analysis is carried out by using a model in which endogenous and induced technical change are explicitly modelled and in which international technological spillovers are also quantified. The results of our analysis partly support Barrett’s and Benedick’s conjecture. On the one hand, a self-enforcing agreement is more likely to emerge when countries cooperate on environmental technological innovation and diffusion than when they cooperate on emission abatement. However, technological cooperation – without any commitment to emission control – may not lead to a sufficient abatement of greenhouse gas concentrations.Agreements, Climate, Incentives, Technological change, Policy