111 research outputs found
Case-based reasoning approach to estimating the strength of sustainable concrete
Continuing from previous studies of sustainable concrete containing environmentally friendly materials and existing modeling approach to predicting concrete properties, this study developed an estimation methodology to predicting the strength of sustainable concrete using an advanced case-based reasoning approach. It was conducted in two steps: (i) establishment of a case database and (ii) development of an advanced case-based reasoning model. Through the experimental studies, a total of 144 observations for concrete compressive strength and tensile strength were established to develop the estimation model. As a result, the prediction accuracy of the A-CBR model (i.e., 95.214% for compressive strength and 92.448% for tensile strength) performed superior to other conventional methodologies (e.g., basic case-based reasoning and artificial neural network models). The developed methodology provides an alternative approach in predicting concrete properties and could be further extended to the future research area in durability of sustainable concrete
Particle-in-cell Monte Carlo and fluid simulations of argon-oxygen plasma : comparisons with experiments and validations
Particle-in-cell Monte Carlo collision (PIC-MCC) and fluid simulations of argon-oxygen plasmas in
capacitively and inductively coupled plasma reactors are presented. Potential profiles and electron/
ion kinetic information such as electron/ion energy distributions and temperatures are compared
with experimental data as well as with other analytical and numerical results. One-dimensional
PIC-MCC simulations compare favorably with experimental data obtained in capacitively coupled
reactors over a wide range of pressure and power. Two-dimensional fluid simulations of capacitive
discharges differs from the results of PIC-MCC simulations as nonlocal effects play an important
role in these discharges. Fluid simulations as nonlocal inductively coupled plasmas, however, agree
favorably with experimental observations
Nano encapsulation of Drug-loaded Lipid by Temperature induced Phase Transition
Pluronic nanoparticles (NPs) were prepared by means of a temperature-induced phase transition in the mixture composed of Pluronic F-68 and liquid Tween 80/soybean oil containing model drugs such as orlistat, caffeine, and ibuprofen sodium salt. Liquid
soybean oil/Tween 80 was used as a solubilizer for model drugs, and Pluronic F-68 was the polymer that stabilizes liquid soybean oil/Tween 80 containing model drugs. Field-emission scanning electron microscopy and particle size analyzer were used
to observe the morphology and size distribution of the prepared NPs. X-ray diffractometer was used to understand relationship between the crystalline state of the model drug and its solubility in the aqueous media. To observe the feasibility of Pluronic NPs as a
drug delivery system, the release pattern of model drugs was observed
Exact solutions for vibrational levels of the Morse potential via the asymptotic iteration method
Exact solutions for vibrational levels of diatomic molecules via the Morse
potential are obtained by means of the asymptotic iteration method. It is shown
that, the numerical results for the energy eigenvalues of are all
in excellent agreement with the ones obtained before. Without any loss of
generality, other states and molecules could be treated in a similar way
Parametrization of nonlinear and chaotic oscillations in driven beam-plasma diodes
Nonlinear phenomena in a driven plasma diode are studied using a fluid code and the particle-in-cell simulation code XPDPI. When a uniform electron beam is injected to a bounded diode filled with uniform ion background, the beam is destabilized by the Pierce instability and a perturbation grows to exhibit nonlinear oscillations including chaos. Two standard routes to chaos, period doubling and quasiperiodicity, are observed. Mode lockings of various winding numbers are observed in an ac driven system. A new diagnostic quantity is used to parametrize various nonlinear oscillations.open10
Diabetes, atherosclerosis, and stenosis by AI
OBJECTIVEThis study evaluates the relationship between atherosclerotic plaque characteristics (APCs) and angiographic stenosis severity in patients with and without diabetes. Whether APCs differ based on lesion severity and diabetes status is unknown.RESEARCH DESIGN AND METHODSWe retrospectively evaluated 303 subjects from the Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia (CREDENCE) trial referred for invasive coronary angiography with coronary computed tomographic angiography (CCTA) and classified lesions as obstructive (≥50% stenosed) or nonobstructive using blinded core laboratory analysis of quantitative coronary angiography. CCTA quantified APCs, including plaque volume (PV), calcified plaque (CP), noncalcified plaque (NCP), low-density NCP (LD-NCP), lesion length, positive remodeling (PR), high-risk plaque (HRP), and percentage of atheroma volume (PAV; PV normalized for vessel volume). The relationship between APCs, stenosis severity, and diabetes status was assessed.RESULTSAmong the 303 patients, 95 (31.4%) had diabetes. There were 117 lesions in the cohort with diabetes, 58.1% of which were obstructive. Patients with diabetes had greater plaque burden (P = 0.004). Patients with diabetes and nonobstructive disease had greater PV (P = 0.02), PAV (P = 0.02), NCP (P = 0.03), PAV NCP (P = 0.02), diseased vessels (P = 0.03), and maximum stenosis (P = 0.02) than patients without diabetes with nonobstructive disease. APCs were similar between patients with diabetes with nonobstructive disease and patients without diabetes with obstructive disease. Diabetes status did not affect HRP or PR. Patients with diabetes had similar APCs in obstructive and nonobstructive lesions.CONCLUSIONSPatients with diabetes and nonobstructive stenosis had an association to similar APCs as patients without diabetes who had obstructive stenosis. Among patients with nonobstructive disease, patients with diabetes had more total PV and NCP.Cardiolog
Dust in Supernovae and Supernova Remnants II: Processing and survival
Observations have recently shown that supernovae are efficient dust factories, as predicted for a long time by theoretical models. The rapid evolution of their stellar progenitors combined with their efficiency in precipitating refractory elements from the gas phase into dust grains make supernovae the major potential suppliers of dust in the early Universe, where more conventional sources like Asymptotic Giant Branch (AGB) stars did not have time to evolve. However, dust yields inferred from observations of young supernovae or derived from models do not reflect the net amount of supernova-condensed dust able to be expelled from the remnants and reach the interstellar medium. The cavity where the dust is formed and initially resides is crossed by the high velocity reverse shock which is generated by the pressure of the circumstellar material shocked by the expanding supernova blast wave. Depending on grain composition and initial size, processing by the reverse shock may lead to substantial dust erosion and even complete destruction. The goal of this review is to present the state of the art about processing and survival of dust inside supernova remnants, in terms of theoretical modelling and comparison to observations
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