423 research outputs found
Stochastic modeling and large-eddy simulation of heated concentric coaxial pipe flow
Turbulent concentric coaxial pipe flows are numerically investigated as
canonical problem addressing spanwise curvature effects on heat and momentum
transfer that are encountered in various engineering applications. It is
demonstrated that the wall-adapting local eddy-viscosity (WALE) model within a
large-eddy simulation (LES) framework, without model parameter recalibration,
has limited predictive capabilities as signalized by poor representation of
wall curvature effects and notable grid dependence. The identified lack in the
modeling of radial transport processes is therefore addressed here by utilizing
a stochastic one-dimensional turbulence (ODT) model. A standalone ODT
formulation for cylindrical geometry is used in order to asses to which extent
the predictability can be expected to improve by utilizing an advanced
wall-modeling modeling strategy. It is shown that ODT is capable of capturing
spanwise curvature and finite Reynolds number effects for fixed adjustable ODT
model parameters. Based on the analogy of heat and mass transfer, present
results yield new opportunities for modeling turbulent transfer process in
chemical, process, and thermal engineering.Comment: In: New Results in Numerical and Experimental Fluid Mechanics XIV --
Contributions to the 23rd STAB/DGLR Symposium Berlin, Germany, 2022, edited
by Andreas Dillmann, Gerd Heller, Ewald Kr\"amer, Claus Wagner, and Julien
Weis
Towards Optimizing with Large Language Models
In this work, we conduct an assessment of the optimization capabilities of
LLMs across various tasks and data sizes. Each of these tasks corresponds to
unique optimization domains, and LLMs are required to execute these tasks with
interactive prompting. That is, in each optimization step, the LLM generates
new solutions from the past generated solutions with their values, and then the
new solutions are evaluated and considered in the next optimization step.
Additionally, we introduce three distinct metrics for a comprehensive
assessment of task performance from various perspectives. These metrics offer
the advantage of being applicable for evaluating LLM performance across a broad
spectrum of optimization tasks and are less sensitive to variations in test
samples. By applying these metrics, we observe that LLMs exhibit strong
optimization capabilities when dealing with small-sized samples. However, their
performance is significantly influenced by factors like data size and values,
underscoring the importance of further research in the domain of optimization
tasks for LLMs
Rapid and sensitive insulated isothermal PCR for point-of-need feline leukaemia virus detection
Objectives: Feline leukaemia virus (FeLV), a gamma retrovirus, causes diseases of the feline haematopoietic system that are invariably fatal. Rapid and accurate testing at the point-of-need (PON) supports prevention of virus spread and management of clinical disease. This study evaluated the performance of an insulated isothermal PCR (iiPCR) that detects proviral DNA, and a reverse transcription (RT)-iiPCR that detects both viral RNA and proviral DNA, for FeLV detection at the PON. Methods: Mycoplasma haemofelis, feline coronavirus, feline herpesvirus, feline calicivirus and feline immunodeficiency virus were used to test analytical specificity. In vitro transcribed RNA, artificial plasmid, FeLV strain American Type Culture Collection VR-719 and a clinical FeLV isolate were used in the analytical sensitivity assays. A retrospective study including 116 clinical plasma and serum samples that had been tested with virus isolation, real-time PCR and ELISA, and a prospective study including 150 clinical plasma and serum samples were implemented to evaluate the clinical performances of the iiPCR-based methods for FeLV detection. Results: Ninety-five percent assay limit of detection was calculated to be 16 RNA and five DNA copies for the RT-iiPCR, and six DNA copies for the iiPCR. Both reactions had analytical sensitivity comparable to a reference real-time PCR (qPCR) and did not detect five non-target feline pathogens. The clinical performance of the RT-iiPCR and iiPCR had 98.82% agreement (kappa[κ] = 0.97) and 100% agreement (κ = 1.0), respectively, with the qPCR (n = 85). The agreement between an automatic nucleic extraction/RT-iiPCR system and virus isolation to detect FeLV in plasma or serum was 95.69% (κ = 0.95) and 98.67% (κ = 0.85) in a retrospective (n = 116) and a prospective (n = 150) study, respectively. Conclusions and relevance: These results suggested that both RT-iiPCR and iiPCR assays can serve as reliable tools for PON FeLV detection
MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games
This paper presents MiniZero, a zero-knowledge learning framework that
supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel
AlphaZero, and Gumbel MuZero. While these algorithms have demonstrated
super-human performance in many games, it remains unclear which among them is
most suitable or efficient for specific tasks. Through MiniZero, we
systematically evaluate the performance of each algorithm in two board games,
9x9 Go and 8x8 Othello, as well as 57 Atari games. For two board games, using
more simulations generally results in higher performance. However, the choice
of AlphaZero and MuZero may differ based on game properties. For Atari games,
both MuZero and Gumbel MuZero are worth considering. Since each game has unique
characteristics, different algorithms and simulations yield varying results. In
addition, we introduce an approach, called progressive simulation, which
progressively increases the simulation budget during training to allocate
computation more efficiently. Our empirical results demonstrate that
progressive simulation achieves significantly superior performance in two board
games. By making our framework and trained models publicly available, this
paper contributes a benchmark for future research on zero-knowledge learning
algorithms, assisting researchers in algorithm selection and comparison against
these zero-knowledge learning baselines. Our code and data are available at
https://rlg.iis.sinica.edu.tw/papers/minizero.Comment: Submitted to IEEE Transactions on Games, under revie
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Anti-Neuroinflammatory Effects of the Calcium Channel Blocker Nicardipine on Microglial Cells: Implications for Neuroprotection
Background/Objective Nicardipine is a calcium channel blocker that has been widely used to control blood pressure in severe hypertension following events such as ischemic stroke, traumatic brain injury, and intracerebral hemorrhage. However, accumulating evidence suggests that inflammatory processes in the central nervous system that are mediated by microglial activation play important roles in neurodegeneration, and the effect of nicardipine on microglial activation remains unresolved. Methodology/Principal Findings In the present study, using murine BV-2 microglia, we demonstrated that nicardipine significantly inhibits microglia-related neuroinflammatory responses. Treatment with nicardipine inhibited microglial cell migration. Nicardipine also significantly inhibited LPS plus IFN-γ-induced release of nitric oxide (NO), and the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Furthermore, nicardipine also inhibited microglial activation by peptidoglycan, the major component of the Gram-positive bacterium cell wall. Notably, nicardipine also showed significant anti-neuroinflammatory effects on microglial activation in mice in vivo. Conclusion/Significance The present study is the first to report a novel inhibitory role of nicardipine on neuroinflammation and provides a new candidate agent for the development of therapies for inflammation-related neurodegenerative diseases
A Pan-Dengue Virus Reverse Transcription-Insulated Isothermal PCR Assay Intended for Point-of-Need Diagnosis of Dengue Virus Infection by Use of the POCKIT Nucleic Acid Analyzer
Dengue virus (DENV) infection is considered a major public health problem in developing tropical countries where the virus is endemic and continues to cause major disease outbreaks every year. Here, we describe the development of a novel, inexpensive, and user-friendly diagnostic assay based on a reverse transcription-insulated isothermal PCR (RT-iiPCR) method for the detection of all four serotypes of DENV in clinical samples. The diagnostic performance of the newly established pan-DENV RT-iiPCR assay targeting a conserved 3′ untranslated region of the viral genome was evaluated. The limit of detection with a 95% confidence was estimated to be 10 copies of in vitro-transcribed (IVT) RNA. Sensitivity analysis using RNA prepared from 10-fold serial dilutions of tissue culture fluid containing DENVs suggested that the RT-iiPCR assay was comparable to the multiplex real-time quantitative RT-PCR (qRT-PCR) assay for DENV-1, -3, and -4 detection but 10-fold less sensitive for DENV-2 detection. Subsequently, plasma collected from patients suspected of dengue virus infection (n = 220) and individuals not suspected of dengue virus infection (n = 45) were tested by the RT-iiPCR and compared to original test results using a DENV NS1 antigen rapid test and the qRT-PCR. The diagnostic agreement of the pan-DENV RT-iiPCR, NS1 antigen rapid test, and qRT-PCR tests was 93.9%, 84.5%, and 97.4%, respectively, compared to the composite reference results. This new RT-iiPCR assay along with the portable POCKIT nucleic acid analyzer could provide a highly reliable, sensitive, and specific point-of-need diagnostic assay for the diagnosis of DENV in clinics and hospitals in developing countries
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