Explore the vast range of titles available.

We have previously developed a new theory for pressure dependent outflow from the human eye, and tested the model using experimental data at intraocular pressures above normal eye pressures. In this paper, we use our model to analyze a hypotensive pressure-time dataset obtained following application of a Honan balloon. Here we show that the hypotensive pressure-time data can be successfully analyzed using our proposed pressure dependent outflow model. When the most uncertain initial data point is removed from the dataset, then parameter estimates are close to our previous parameter estimates, but clearly parameter estimates are very sensitive to assumptions. We further show that (i) for a measured intraocular pressure-time curve, the estimated model parameter for whole eye surface hydraulic conductivity is primarily a function of the ocular rigidity, and (ii) the estimated model parameter that controls the rate of decrease of outflow with increasing pressure is primarily a function of the convexity of the monotonic pressure-time curve. Reducing parameter uncertainty could be accomplished using new technologies to obtain higher quality datasets, and by gathering additional data to better define model parameter ranges for the normal eye. With additional research, we expect the pressure dependent outflow analysis described herein may find applications in the differential diagnosis, prognosis and monitoring of the glaucomatous eye.

The electro-mechanical impedance (EMI) change in Piezoelectric (PZT) sensors embedded in steel-fiber-reinforced mortar (SFRM) was investigated to assess the material setting time. The EMI was continuously monitored for 12 h by the PZT sensor embedded in SFRM having fiber volume fraction of 0.5%, 1.5%, and 2.0%. The initial and final setting time of the SFRM were estimated using EMI signal change. The penetration resistance test, a conventional test method for the setting time of cement mortar, was also conducted. In the penetration resistance test, it was observed that the initial and the final setting time of SFRM accelerated as the volume fraction of the steel fiber increased. On the other hand, in the EMI sensing technique, the initial and the final setting time of the SFRM were consistent regardless of the fiber volume fraction.

In this paper we set the previously reported pressure-dependent, ordinary differential equation outflow model by Smith and Gardiner for the human eye, into a new three-dimensional (3D) porous media outflow model of the eye, and calibrate model parameters using data reported in the literature. Assuming normal outflow through anterior pathways, we test the ability of 3D flow model to predict the pressure elevation with a silicone oil tamponade. Then assuming outflow across the retinal pigment epithelium is normal, we test the ability of the 3D model to predict the pressure elevation in Schwartz-Matsuo syndrome. For the first time we find the flow model can successfully model both conditions, which helps to build confidence in the validity and accuracy of the 3D pressure-dependent outflow model proposed here. We employ this flow model to estimate the translaminar pressure gradient within the optic nerve head of a normal eye in both the upright and supine postures, and during the day and at night. Based on a ratio of estimated and measured pressure gradients, we define a factor of safety against acute interruption of axonal transport at the laminar cribrosa. Using a completely independent method, based on the behaviour of dynein molecular motors, we compute the factor of safety against stalling the dynein molecule motors, and so compromising retrograde axonal transport. We show these two independent methods for estimating factors of safety agree reasonably well and appear to be consistent. Taken together, the new 3D pressure-dependent outflow model proves itself to capable of providing a useful modeling platform for analyzing eye behaviour in a variety of physiological and clinically useful contexts, including IOP elevation in Schwartz-Matsuo syndrome and with silicone oil tamponade, and potentially for risk assessment for optic glaucomatous neuropathy.

This study demonstrates the research and development of a visualization method called thermal performance simulation. The objective of this study is providing the results of thermal performance simulation results into building information modeling (BIM) models, displaying a series of thermal performance results, and enabling stakeholders to use the BIM tool as a common user interface in the early design stage. This method utilizes a combination of object-oriented physical modeling (OOPM) and BIM. To implement the suggested method, a specific BIM authoring tool called the application programming interface (API) was adopted, as well as an external database to maintain the thermal energy performance results from the OOPM tool. Based on this method, this study created a prototype called the thermal energy performance visualization (TEPV). The TEPV translates the information from the external database to the thermal energy performance indicator (TEPI) parameter in the BIM tool. In the TEPI, whenever BIM models are generated for building design, the thermal energy performance results are visualized by color-coding the building components in the BIM models. Visualization of thermal energy performance results enables non-engineers such as architects to explicitly inspect the simulation results. Moreover, the TEPV facilitates architects using BIM as an interface in building design to visualize building thermal energy performance, enhancing their design production at the early design stages.

The objective of this study is to develop hybrid models by combining data-driven models, including support vector machines (SVM) and generalized regression neural networks (GRNN), and wavelet decomposition for aggregation and disaggregation of rainfall. The wavelet-based support vector machines (WSVM) and wavelet-based generalized regression neural networks (WGRNN) models are obtained using mother wavelets, including db8, db10, sym8, sym10, coif6, and coif12. The developed models are evaluated in the Bocheong-stream catchment, an International Hydrological Program representative catchment, Republic of Korea. WSVM and WGRNN models with mother wavelet db10 yield the best performance as compared with other mother wavelets for estimating areal and disaggregated rainfalls, respectively. Among 12 rainfall stations, SVM, GRNN, WSVM (db10 and sym10), and WGRNN (db10 and sym10) models provide the best accuracies for estimating the disaggregated rainfalls at Samga (No. 7), and the worst accuracies for estimating the disaggregated rainfalls at Yiweon (No. 11) stations, respectively. Results obtained from this study indicate that the combination of data-driven models and wavelet decomposition can be a useful tool for estimating areal and disaggregated rainfalls satisfactorily, and can yield better efficiency than data-driven models.

In this research, the moisture diffusion model for concrete was inversely estimated using artificial neural network (ANN) and the data collected from virtual experiments. In addition, the moisture distribution was predicted using the ANN model in numerical analysis. For inverse estimation, virtual experimental data were used. The virtual experimental data were generated by adding noise to the moisture distribution obtained by a numerical simulation using a known moisture diffusion model. ANNs of two architectures were used in the inverse estimation. For performance test, the inversely estimated ANN model and the known moisture diffusion model were compared. The predicted humidity distribution using the ANN and virtual experiment data were also compared. The inversely estimated ANN model was in a good agreement with the known moisture diffusion model used for the virtual experiment.

This work is a novel attempt to incorporate computational fluid dynamics (CFD) techniques in the analysis of hemodynamic parameters of Moyamoya disease (MMD). Highly prevalent in Asian countries, MMD is characterised by progressive occlusion of the intracranial Internal Carotid Arteries (ICA). We intend to identify a reliable hemodynamic parameter that can be used to gauge treatment outcome. This will aid surgeons in the perioperative management of MMD patients. We carried out CFD analysis on eight patients (5 female, 3 male) with MMD treated by EDAS (encephalo-duro-arterio-synangiosis) between 2011 and 2012. All the eight patients presented with haemorrhage, with subsequent 4–12 month follow-up done using Magnetic Resonance Angiography (MRA) to capture auto-remodelling. We calculated percentage change in flow rate and pressure drop indicator (ΡDI) across the Left and Right ICA. Pressure drop indicator (PDI) is defined as the difference of pressure reduction within the carotid arteries, measured at post-op and follow up, using patient specific inflow rates. The measured percentage flow change and pressure reduction showed an increase at follow up for improved patients (characterised by angiography according to the method of Matsushima), who did not develop any complications after surgery. The inverse was observed in patients who were clinically classified as no change and retrogressed (according to the method of Matsushima) cases post-operation. This elucidates that our findings have instituted a new parameter that may well play a critical role as an assistive clinical decision making tool in MMD.

Blast furnace slag (SL) is an amorphous calcium aluminosilicate material that exhibits both pozzolanic and latent hydraulic activities. It has been successfully used to reduce the heat of hydration in mass concrete. However, SL currently available in the market generally experiences pre-treatment to increase its reactivity to be closer to that of portland cement. Therefore, using such pre-treated SL may not be applicable for reducing the heat of hydration in mass concrete. In this work, the adiabatic and semi-adiabatic temperature rise of concretes with 20% and 40% SL (mass replacement of cement) containing calcium sulfate were investigated. Isothermal calorimetry and thermal analysis (TGA) were used to study the hydration kinetics of cement paste at 23 and 50 °C. Results were compared with those with control cement and 20% replacements of silica fume, fly ash, and metakaolin. Results obtained from adiabatic calorimetry and isothermal calorimetry testing showed that the concrete with SL had somewhat higher maximum temperature rise and heat release compared to other materials, regardless of SL replacement levels. However, there was a delay in time to reach maximum temperature with increasing SL replacement level. At 50 °C, a significant acceleration was observed for SL, which is more likely related to the pozzolanic reaction than the hydraulic reaction. Semi-adiabatic calorimetry did not show a greater temperature rise for the SL compared to other materials; the differences in results between semi-adiabatic and adiabatic calorimetry are important and should be noted. Based on these results, it is concluded that the use of blast furnace slag should be carefully considered if used for mass concrete applications.

The perception of rings in graphs is widely used in many fields of science and engineering. Algorithms developed in the chemistry community, called smallest set of smallest rings (SSSR), applicable only for simple graphs or chemical structures. In contrast, algorithms developed by the computer science community, called minimum cycle basis (MCB) are identical to SSSR yet exhibit greater robustness. MCB-based algorithms can correctly reveal all rings in any complex graph. However, they are slow when applied to large complex graphs due to the inherent limitations of the algorithms used. Here, we suggest a heuristic method called RP-Path. This method is a robust, simple, and fast search method with O(n³) runtime algorithm that correctly identifies the SSSR of all of the test case of complex graphs by using approach different from the MCB-based method. Both the robustness and improvement in speed are achieved by using a path-included distance matrix and describing the characteristic features of rings in the matrix. This method is accurate and faster than any other methods and may find many application in various fields of science and engineering that use complicated graphs with thousands of nodes.

The decrease in dynamic elastic modulus is a primary indicator of quantitative damage in concrete. To quantitatively assess depth-by-depth damage within a concrete structure, cylindrical specimens obtained through coring can be cut into disk specimens to measure the dynamic elastic modulus of concrete at each depth. To minimize external damage during coring, it is essential to extract cylinders with the smallest possible diameter. In addition, for higher resolution in depth-based damage assessment, creating disk specimens with the smallest possible thickness is necessary. However, there is no information available in the literature on experimental limitation of smallest possible diameter and thickness for dynamic elastic modulus of disk-shaped specimens. This study evaluated whether the dynamic modulus measured from various sizes of concrete disk specimens provided sufficient reliability compared to reference values obtained from cylinders. Moreover, the study examined how the presence of coarse aggregate and variation in the water–cement ratio significantly influenced the dynamic modulus measurement. In addition, test results from impulse excitation technique (IET) and impact resonance (IR) were compared to find a more reliable test method for dynamic elastic modulus of disk specimen. The experimental findings revealed that as the thickness-to-radius ratio of the disk specimens decreased, measured data variation increased. Mortar specimens without coarse aggregates showed less variability compared to concrete specimens, and the variation in dynamic modulus measured by IR was lower than that measured by IET.