3,408 research outputs found
Exact simulation of a truncated Lévy subordinator
A truncated Lévy subordinator is a Lévy subordinator in R+ with Lévy measure restricted from above by a certain level b. In this article, we study the path and distribution properties of this type of process in detail and set up an exact simulation framework based on a marked renewal process. In particular, we focus on a typical specification of truncated Lévy subordinator, namely the truncated stable process. We establish an exact simulation algorithm for the truncated stable process, which is very accurate and efficient. Compared to the existing algorithm suggested in Chi, our algorithm outperforms over all parameter settings. Using the distributional decomposition technique, we also develop an exact simulation algorithm for the truncated tempered stable process and other related processes. We illustrate an application of our algorithm as a valuation tool for stochastic hyperbolic discounting, and numerical analysis is provided to demonstrate the accuracy and effectiveness of our methods. We also show that variations of the result can also be used to sample two-sided truncated Lévy processes, two-sided Lévy processes via subordinating Brownian motions, and truncated Lévy-driven Ornstein-Uhlenbeck processes
Examining the effect of oil price pass-through on the domestic prices: asymmetric versus symmetric adjustment modelling
We study the effect of oil price pass-through on the domestic prices, namely on the consumer price index (CPI) and producer price index (PPI), based on the asymmetric adjustment modelling approach. The behaviour of domestic prices in response to oil price changes was examined by comparing two groups of economies, namely the oil-importing versus oil-exporting countries. The results show that although the oil price has a significant influence on the domestic price inflation in the short-run and in the long-run for most of the oil-importers and oil-exporters, it is not the main factor affecting CPI and PPI inflation. Moreover, oil price inflation seems to trigger a higher impact on PPI inflation than CPI inflation. The pass-through of oil prices on CPI inflation is low, especially in the oil-importing countries while the main determinant of CPI and PPI inflation is gross domestic product (GDP). The results are found to hold for both groups of countries
The Taiwan ECDFS Near-Infrared Survey: Ultra-deep J and Ks Imaging in the Extended Chandra Deep Field-South
We present ultra-deep J and Ks imaging observations covering a 30' * 30' area
of the Extended Chandra Deep Field-South (ECDFS) carried out by our Taiwan
ECDFS Near-Infrared Survey (TENIS). The median 5-sigma limiting magnitudes for
all detected objects in the ECDFS reach 24.5 and 23.9 mag (AB) for J and Ks,
respectively. In the inner 400 arcmin^2 region where the sensitivity is more
uniform, objects as faint as 25.6 and 25.0 mag are detected at 5-sigma. So this
is by far the deepest J and Ks datasets available for the ECDFS. To combine the
TENIS with the Spitzer IRAC data for obtaining better spectral energy
distributions of high-redshift objects, we developed a novel deconvolution
technique (IRACLEAN) to accurately estimate the IRAC fluxes. IRACLEAN can
minimize the effect of blending in the IRAC images caused by the large
point-spread functions and reduce the confusion noise. We applied IRACLEAN to
the images from the Spitzer IRAC/MUSYC Public Legacy in the ECDFS survey
(SIMPLE) and generated a J+Ks selected multi-wavelength catalog including the
photometry of both the TENIS near-infrared and the SIMPLE IRAC data. We
publicly release the data products derived from this work, including the J and
Ks images and the J+Ks selected multiwavelength catalog.Comment: 25 pages, 25 figures, ApJS in pres
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A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation.
There is a poor understanding of how the physiology of polymicrobial communities in cystic fibrosis (CF) lungs contributes to pulmonary exacerbations and lung function decline. In this study, a microbial culture system based on the principles of the Winogradsky column (WinCF system) was developed to study the physiology of CF microbes. The system used glass capillary tubes filled with artificial sputum medium to mimic a clogged airway bronchiole. Chemical indicators were added to observe microbial physiology within the tubes. Characterization of sputum samples from seven patients showed variation in pH, respiration, biofilm formation and gas production, indicating that the physiology of CF microbial communities varied among patients. Incubation of homogenized tissues from an explant CF lung mirrored responses of a Pseudomonas aeruginosa pure culture, supporting evidence that end-stage lungs are dominated by this pathogen. Longitudinal sputum samples taken through two exacerbation events in a single patient showed that a two-unit drop in pH and a 30% increase in gas production occurred in the tubes prior to exacerbation, which was reversed with antibiotic treatment. Microbial community profiles obtained through amplification and sequencing of the 16S rRNA gene showed that fermentative anaerobes became more abundant during exacerbation and were then reduced during treatment where P. aeruginosa became the dominant bacterium. Results from the WinCF experiments support the model where two functionally different CF microbial communities exist, the persistent Climax Community and the acute Attack Community. Fermentative anaerobes are hypothesized to be the core members of the Attack Community and production of acidic and gaseous products from fermentation may drive developing exacerbations. Treatment targeting the Attack Community may better resolve exacerbations and resulting lung damage
Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4
Purpose: To assess the alignment of GPT-4-based evaluation to human clinician
experts, for the evaluation of responses to ophthalmology-related patient
queries generated by fine-tuned LLM chatbots. Methods: 400 ophthalmology
questions and paired answers were created by ophthalmologists to represent
commonly asked patient questions, divided into fine-tuning (368; 92%), and
testing (40; 8%). We find-tuned 5 different LLMs, including LLAMA2-7b,
LLAMA2-7b-Chat, LLAMA2-13b, and LLAMA2-13b-Chat. For the testing dataset,
additional 8 glaucoma QnA pairs were included. 200 responses to the testing
dataset were generated by 5 fine-tuned LLMs for evaluation. A customized
clinical evaluation rubric was used to guide GPT-4 evaluation, grounded on
clinical accuracy, relevance, patient safety, and ease of understanding. GPT-4
evaluation was then compared against ranking by 5 clinicians for clinical
alignment. Results: Among all fine-tuned LLMs, GPT-3.5 scored the highest
(87.1%), followed by LLAMA2-13b (80.9%), LLAMA2-13b-chat (75.5%),
LLAMA2-7b-Chat (70%) and LLAMA2-7b (68.8%) based on the GPT-4 evaluation. GPT-4
evaluation demonstrated significant agreement with human clinician rankings,
with Spearman and Kendall Tau correlation coefficients of 0.90 and 0.80
respectively; while correlation based on Cohen Kappa was more modest at 0.50.
Notably, qualitative analysis and the glaucoma sub-analysis revealed clinical
inaccuracies in the LLM-generated responses, which were appropriately
identified by the GPT-4 evaluation. Conclusion: The notable clinical alignment
of GPT-4 evaluation highlighted its potential to streamline the clinical
evaluation of LLM chatbot responses to healthcare-related queries. By
complementing the existing clinician-dependent manual grading, this efficient
and automated evaluation could assist the validation of future developments in
LLM applications for healthcare.Comment: 13 Pages, 1 Figure, 8 Table
The Taiwan ECDFS Near-Infrared Survey: Very Bright End of the Luminosity Function at z>7
The primary goal of the Taiwan ECDFS Near-Infrared Survey (TENIS) is to find
well screened galaxy candidates at z>7 (z' dropout) in the Extended Chandra
Deep Field-South (ECDFS). To this end, TENIS provides relatively deep J and Ks
data (~25.3 ABmag, 5-sigma) for an area of 0.5*0.5 degree. Leveraged with
existing data at mid-infrared to optical wavelengths, this allows us to screen
for the most luminous high-z objects, which are rare and thus require a survey
over a large field to be found. We introduce new color selection criteria to
select a z>7 sample with minimal contaminations from low-z galaxies and
Galactic cool stars; to reduce confusion in the relatively low angular
resolution IRAC images, we introduce a novel deconvolution method to measure
the IRAC fluxes of individual sources. Illustrating perhaps the effectiveness
at which we screen out interlopers, we find only one z>7 candidate, TENIS-ZD1.
The candidate has a weighted z_phot of 7.8, and its colors and luminosity
indicate a young (45M years old) starburst galaxy with a stellar mass of
3.2*10^10 M_sun. The result matches with the observational luminosity function
analysis and the semi-analytic simulation result based on the Millennium
Simulations, which may over predict the volume density for high-z massive
galaxies. The existence of TENIS-ZD1, if confirmed spectroscopically to be at
z>7, therefore poses a challenge to current theoretical models for how so much
mass can accumulate in a galaxy at such a high redshift.Comment: 14 pages, 11 figures, ApJ accepte
Model-Based Design (MBD) For Autonomous Underwater Vehicle
This project is to enhanced and upgraded a depth controller for Autonomous Underwater Vehicle (AUV) to submerge precisely at the certain depth. This poster demonstrated an AUV equipped with integrated sensor and depth controller based on the pressure sensing which able to continuously sending the depth data to controller. The depth Simulink Arduino algorithm is implemented on an Arduino Mega using ModelBased Design (MBD) with MATLAB and Simulink. MBD used to model, simulate and verify the Simulink control algorithm after obtained data through open-loop experiment test. Then, it deploys and tests the algorithm on the embedded AUV hardware. The focus was in controlling the AUV vertical trajectory as the AUV tried to remain stationary at the selected depth and consuming its rise time Tr, overshoot Os, and settling time Ts are minimized. The comparative study for the AUV depth-control by On-Off, Proportional Integral Derivative (PID) controller and Fuzzy
Logic Controller (FLC) controllers. MBD has faster implementation with fewer coding error when deploy to AUV hardware
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