The Dependence of Ultrasonic Velocity in Ultra-Low Expansion Glass on Temperature

The coefficient of thermal expansion (CTE) is an important property of ultra-low expansion (ULE) glass, and the ultrasonic velocity method has shown excellent performance for the nondestructive measurement of CTE in large ULE glass. In this method, the accurate acquisition of the ultrasonic velocity in ULE glass is necessary. Herein, we present a correlation method to determine the ultrasonic TOF in ULE glass and to further obtain the ultrasonic longitudinal wave velocity (cL) indirectly. The performance of this method was verified by simulations. Considering the dependence of cL on temperature (T), we carried out the derivation of the analytical model between cL and T. Based on reasonable constant assumptions in the physical sense, a cL–T exponential model was produced, and some experimental results support this model. Additional experiments were carried out to validate the accuracy of the cL–T exponential model. The studies we conducted indicate that the cL–T exponential model can reliably predict the ultrasonic velocity in ULE glass at different temperatures, providing a means for the nondestructive CTE measurement of large ULE glass at a specified temperature.

Re-AbilityLab

This study aims to show the methodology of implementation of the Skills Laboratories (Re-AbilityLab) at the Institute of Physical Medicine and Rehabilitation of the Hospital das Clínicas of the Faculty of Medicine of the University of São Paulo. These Skill Labs offer activities to maximize patient performance by promoting specific functional outcomes, which are described in the International Classification of Functionality. The activities are dynamic and carried out by a multidisciplinary team in the areas of health, education, and management. Innovation and strategic aspects of the knowledge economy are structured in the management of this project to enhance the achievement of purposes and results. The implementation process includes solutions adopted, definition of responsibilities, difficulties faced, benefits, functionality of the methods applied, and lessons learned. Mapping the process from the current scenario to the desired contributes to the transition from a care model (linear, refractory, obsolete) to an exponential model of care (intangibles, incremental innovation).

Statistical models expressing relations between soil moisture, aggregate speed, and tillage depth at plowing and cultivation

The study is based on a one-year field experiment (2019) in the land of the Chirpan region located in central Bulgaria. The agrotechnical operations of plowing and cultivation, applied in technology for the production of sunflower, are studied. Four models (Linear, Exponential, Logarithmic, and Quadratic) were compared at p < 0.05, defining the relation between soil moisture, aggregate speed, and the uniformity of the soil index Tillage depth during plowing and cultivation. It was found that in plowing at a speed of 4 km/h the Quadratic model described the relation between soil moisture and tillage depth with the highest coefficient of determination (R2 = 0.682). Relating to plowing at a speed of 4.5 km/h the most suitable is the Exponential model (R2 = 0.729), i.e. about 68.2% and 72.9% of the variations in tillage depth are due to the influence of the moisture of the soil. The coefficients of determination, calculated when cultivating at speeds of 8 km/h (R2 = 0.526) and 9 km/h (R2 = 0.557), show that the Quadratic model most strongly (52.6% and 55.7%) determines the relation between soil moisture and tillage depth. The developed models could be used to optimize the control systems of agricultural machinery.

On prismatic and bending bifurcations of fiber-reinforced elastic membranes under swelling with application to aortic aneurysms

The influence of swelling on prismatic and bending bifurcation modes of inflated thin-walled cylinders under axial loading is examined. The bifurcation criteria for a membrane cylinder subjected to combined axial loading, internal pressure, and swelling is provided. We consider orthotropic materials with two preferred directions which are mechanically equivalent and symmetrically disposed. The mechanical behavior of the matrix is described by a swellable isotropic model. The isotropic material is augmented with two functions that are equal, each one of them accounting for the existence of a unidirectional reinforcement. Two reinforcing models that depend only on the stretch in the fiber direction are considered: the so-called standard reinforcing model and an exponential one. The analysis of bifurcation modes for these models under the conditions at hand may establish the connection with modeling of the normal and diseased aorta in arterial wall tissue. The effects of the axial stretch, the strength of the fiber reinforcement and the fiber winding angle on the onset of prismatic and bending bifurcations are investigated. It is shown that for membranes without fibers, prismatic bifurcation is not feasible. On the other hand, bending bifurcation is more likely to occur for swollen cylinders. However, for a particular model of fiber-reinforced membranes, the standard model, there exists a domain of deformation values together with material constant values that may trigger prismatic bifurcation. The exponential model does not allow prismatic bifurcations. Both models allow bending bifurcation and may or may not trigger it depending on the deformation together with material parameters.

Evaluation of microvascular invasion of hepatocellular carcinoma using whole-lesion histogram analysis with the stretched-exponential diffusion model

Objectives: To evaluate the potential role of histogram analysis of stretched exponential model (SEM) through whole-tumor volume for preoperative prediction of microvascular invasion (MVI) in single hepatocellular carcinoma (HCC). Methods: This study included 43 patients with pathologically proven HCCs by surgery who underwent multiple b-values diffusion-weighted imaging (DWI) and contrast-enhanced MRI.The histogram metrics of distributed diffusion coefficient (DDC) and heterogeneity index (α) from SEM were compared between HCCs with and without MVI, by using the independent t-test. Morphologic features of conventional MRI and clinical data were evaluated with chi-squared or Fisher’s exact tests. Receiver operating characteristic (ROC) and multivariable logistic regression analyses were performed to evaluate the diagnostic performance of different parameters for predicting MVI. Results: The tumor size and non-smooth tumor margin were significantly associated with MVI (all p < 0.05). The mean, fifth, 25th, 50th percentiles of DDC, and the fifth percentile of ADC between HCCs with and without MVI were statistically significant differences (all p < 0.05). The histogram parameters of α showed no statistically significant differences (all p > 0.05). At multivariate analysis,the fifth percentile of DDC was independent risk factor for MVI of HCC(p = 0.006). Conclusions: Histogram parameters DDC and ADC, but not the α value, are useful predictors of MVI. The fifth percentile of DDC was the most useful value to predict MVI of HCC. Advances in knowledge: There is limited literature addressing the role of SEM for evaluating MVI of HCC. Our findings suggest that histogram analysis of SEM based on whole-tumor volume can be useful for MVI prediction.

Bi-exponential modelling of $$W^{^{\prime}}$$ reconstitution kinetics in trained cyclists

Purpose The aim of this study was to investigate the individual $$W^{^{\prime}}$$ W ′ reconstitution kinetics of trained cyclists following repeated bouts of incremental ramp exercise, and to determine an optimal mathematical model to describe $$W^{^{\prime}}$$ W ′ reconstitution. Methods Ten trained cyclists (age 41 ± 10 years; mass 73.4 ± 9.9 kg; $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max 58.6 ± 7.1 mL kg min−1) completed three incremental ramps (20 W min−1) to the limit of tolerance with varying recovery durations (15–360 s) on 5–9 occasions. $$W^{^{\prime}}$$ W ′ reconstitution was measured following the first and second recovery periods against which mono-exponential and bi-exponential models were compared with adjusted R2 and bias-corrected Akaike information criterion (AICc). Results A bi-exponential model outperformed the mono-exponential model of $$W^{^{\prime}}$$ W ′ reconstitution (AICc 30.2 versus 72.2), fitting group mean data well (adjR2 = 0.999) for the first recovery when optimised with parameters of fast component (FC) amplitude = 50.67%; slow component (SC) amplitude = 49.33%; time constant (τ)FC = 21.5 s; τSC = 388 s. Following the second recovery, W′ reconstitution reduced by 9.1 ± 7.3%, at 180 s and 8.2 ± 9.8% at 240 s resulting in an increase in the modelled τSC to 716 s with τFC unchanged. Individual bi-exponential models also fit well (adjR2 = 0.978 ± 0.017) with large individual parameter variations (FC amplitude 47.7 ± 17.8%; first recovery: (τ)FC = 22.0 ± 11.8 s; (τ)SC = 377 ± 100 s; second recovery: (τ)FC = 16.3.0 ± 6.6 s; (τ)SC = 549 ± 226 s). Conclusions W′ reconstitution kinetics were best described by a bi-exponential model consisting of distinct fast and slow phases. The amplitudes of the FC and SC remained unchanged with repeated bouts, with a slowing of W′ reconstitution confined to an increase in the time constant of the slow component.

Effects of Pause Design on the Decline in Pulling Effort and the Evaluation of Perceived Effort in Pulling Tasks

Pulling is one of the manual material handling activities that could lead to work-related musculoskeletal disorders. The objectives of this study were to explore the development of muscular fatigue when performing intermittent pulling tasks and to establish models to predict the pull strength decrease due to performing the tasks. A simulated truck pulling experiment was conducted. Eleven healthy male adults participated. The participants pulled a handle with a load of 40 kg, which resulted in a pulling force of approximately 123 N. The pulling tasks lasted for 9 or 12 min with one, two, or three pauses embedded. The total time period of the embedded pauses was 3 min. The pull strength after each pull and rest was measured. Ratings of the perceived exertion on body parts after each pull were also recorded. The results showed insignificant differences regarding the development of muscular fatigue related to rest frequency. We found that the development of muscular fatigue for pulling tasks with embedded pauses was significantly slower than that for continuous pulls. The forearm had a higher CR-10 score than the other body parts indicating that the forearm was the body part suffering early muscle fatigue. An exponential model was developed to predict the pull strength of the pulling tasks with embedded pauses. This model may be used to assess the developing of muscular fatigue for pulling tasks.

A Prognostics Method Based on Back Propagation Neural Network for Corroded Pipelines

A method that employs the back propagation (BP) neural network is used to predict the growth of corrosion defect in pipelines. This method considers more diversified parameters that affect the pipeline’s corrosion rate, including pipe parameters, service life, corrosion type, corrosion location, corrosion direction, and corrosion amount in a three-dimensional direction. The initial corrosion time is also considered, and, on this basis, the uncertainties of the initial corrosion time and the corrosion size are added to the BP neural network model. In this paper, three kinds of pipeline corrosion growth models are constructed: the traditional corrosion model, the corrosion model considering the uncertainties of initial corrosion time and corrosion depth, and corrosion model also considering the uncertainties of corrosion size (length, width, depth). The rationality and effectiveness of the proposed prediction models are verified by three case studies: the uniform model, the exponential model, and the gamma process model. The proposed models can be widely used in the prediction and management of pipeline corrosion.

VARIANCE GAMMA PROCESS WITH MONTE CARLO SIMULATION AND CLOSED FORM APPROACH FOR EUROPEAN CALL OPTION PRICE DETERMINATION

The Option is widely applied in the financial sector. The Black-Scholes-Merton model is often used in calculating option prices on a stock price movement. The model uses geometric Brownian motion which assumes that the data is normally distributed. However, in reality, stock price movements can cause sharp spikes in data, resulting in nonnormal data distribution. So we need a stock price model that is not normally distributed. One of the fastest growing stock price models today is the process exponential model. The process has the ability to model data that has excess kurtosis and a longer tail (heavy tail) compared to the normal distribution. One of the members of the process is the Variance Gamma (VG) process. The VG process has three parameters which each of them, to control volatility, kurtosis and skewness. In this research, the secondary data samples of options and stocks of two companies were used, namely zoom video communications, Inc. (ZM) and Nokia Corporation (NOK). The price of call options is determined by using closed form equations and Monte Carlo simulation. The Simulation was carried out for various values until convergent result was obtained.