Prediction of System Parameters of Carbon-Based Composite Structure for Different Carbon Fiber Orientations with Mode Information at Reference Angle Only

The prediction of system parameters is important for understanding the dynamic behavior of composite structures or selecting the configuration of laminated carbon in carbon-based composite (CBC) structures. The dynamic nature of CBC structures allows the representation of system parameters as modal parameters in the frequency domain, where all modal parameters depend on the carbon fiber orientations. In this study, the variation in the system parameters of a carbon fiber was derived from equivalent modal parameters, and the system parameters at a certain carbon fiber orientation were predicted using the modal information at the reference carbon fiber orientation only and a representative curve-fitted function. The target CBC structure was selected as a simple rectangular structure with five different carbon fiber orientations, and the modal parameters were formulated based on a previous study for all modes. Second-order curve-fitted polynomial functions were derived for all possible cases, and representative curve-fitting functions were derived by averaging the polynomial coefficients. The two system parameters were successfully predicted using the representative curve-fitting function and the modal information at only the reference carbon fiber orientation, and the feasibility of parameter prediction was discussed based on an analysis of the error between the measured and predicted parameters.

The empirical formula for calculating the incident air Kerma in intraoral radiographic imaging

Objectives: The aim of this paper is to determine the empirical formula for calculating the incident air kerma (Ki), used as a patient dose descriptor in the intraoral radiographic imaging. Methods: The data for the formula were collected during the regular annual inspection of intraoral dental X-ray units in 2018, 2019 and early 2020. The measurement data of 50 X-ray units were processed to develop the formula. Exposure factors for imaging molars of the upper jaw of an average patient in a clinical setting were used in the measurement. The formula validity was statistically evaluated using coefficient of correlation, standard error of the fitted function and the mean relative percentage deviation. Results: measurement values of the radiation doses and calculated values obtained by using the final formula showed good agreement - the mean relative percentage deviation values less than ±15%. Conclusions: Although there are differences in X-ray units, voltages, manufacturers and device architectures (single-phase and high-frequency), the measurement data comply well with computed ones in all cases.

Research on the Monocular Ranging Method of the Leading Vehicle in Multi-weather

In order to improve the accuracy of the monocular distance measurement of the vehicle in front under sunny, cloudy, rainy, snowy, and foggy weather, an improved pixel-mapping monocular distance measurement method is proposed. This method is based on eight-connected domains to detect the front vehicle, obtain the line pixels of the target vehicle in the image, and fit the image line pixels to the corresponding real longitudinal distance function, and combine the fitted function with the internal and external parameters of the camera. An improved pixel-mapping monocular ranging model is obtained. Set up a test environment under different weather to verify the feasibility of the algorithm. The results show that in the four environments, the detectable distances are within 70m, 60m, 30m, and 40m respectively; the error of the improved pixel-mapping monocular ranging method is reduced by 0.6% on average compared with before the improvement, up to 0.92% ; The improved algorithm ranging errors under the four weathers are 1.8513%, 2.6987%, 4.0137%, and 2.5795% respectively, which achieves the purpose of improving the accuracy of the monocular distance measurement of the vehicle in front under multiple weather conditions.

Physics-Guided Curve Fitting for Potential-Energy Functions of Diatomic Molecules

When computing the potential-energy curve of a diatomic molecule for predictive spectroscopy, high-level calculations are usually desired. The best calculations are expensive, so few points are usually available. The points are fitted to a continuous function, such as a polynomial. Ro-vibrational energy levels are then computed using the fitted function, and spectroscopic constants extracted. However, there may be problems with overfitting, with inadequate flexibility of the fitting function, or with dependence of results upon the choice of fitting function. More fundamentally, the fitting function is selected using aesthetics or convenience, instead of physics. Here we suggest using a lower-level, high-resolution ab initio potential as a guide. Instead of fitting the sparse, high-level data directly, the energy differences between the high-level points and the guiding potential are fitted. The results are improved even with an inexpensive guiding potential. This simple strategy involves little additional effort and can be recommended for routine use. It is similar to some interpolation strategies in the literature of polyatomic molecules. When the guiding potential extends beyond the high-level data, extrapolations are also improved.

Understanding phase-transfer catalytic synthesis of fullerenol and its interference from carbon dioxide and ozone

Phase-transfer catalytic reaction involving the use of tetrabutylammonium hydroxide (TBAH) as catalyst and sodium hydroxide (NaOH) solution as the source of hydroxide ions is among the popular choices for synthesis of fullerenol, the polyhydroxylated fullerene. To further understand the process, two experiments were conducted to preliminarily explore the influences of the amount of TBAH and NaOH, respectively, in terms of the achieved level of hydroxylation (i.e. number of hydroxyl groups per fullerenol molecule). The process responded to the variation of the amount of TBAH (over a twofold series of 3–192 drops, average volume 0.0223 ± 0.0004 ml per drop) in a nonlinear manner with a local maximum achieved from 24 drops TBAH (giving 13 OH groups) and a local minimum from 48 drops (giving 8 groups). To the variation of the amount of NaOH (over the range of 0.5–8.0 ml NaOH), the fitted function of the process response resembled Freundlich adsorption isotherm, with an initially increasing trend before levelling off at 4.0 ml NaOH (giving 15 OH groups). It is therefore suggested that fullerene hydroxylation could be explained by liquid–solid adsorption. In addition, it was found that ambient carbon dioxide led to the existence of sodium carbonate in the bulk of the collected product (although not chemically bound). It was also discovered that ambient ozone adversely affected fullerenol synthesis by converting C60 fullerene into fullerene epoxide (C60O). The affected syntheses thus produced epoxide-containing fullerenol instead.

Estimating Smooth and Convex Functions

We propose a new method for estimating an unknown regression function $f_*:[\alpha, \beta] \rightarrow \mathbb{R}$ from a dataset $(X_1, Y_1), \dots, (X_n,$ $Y_n)$ when the only information available on $f_*$ is the fact that $f_*$ is convex and twice differentiable. In the proposed method, we fit a convex function to the dataset that minimizes the sum of the roughness of the fitted function and the average squared differences between the fitted function and $f_*$. We prove that the proposed estimator can be computed by solving a convex quadratic programming problem with linear constraints. Numerical results illustrate the superior performance of the proposed estimator compared to existing methods when i) $f_*$ is the price of a stock option as a function of the strike price and ii) $f_*$ is the steady-state mean waiting time of a customer in a single server queue.

Estimating survival probability using the terrestrial extinction history for the search for extraterrestrial life

Several exoplanets have been discovered to date, and the next step is the search for extraterrestrial life. However, it is difficult to estimate the number of life-bearing exoplanets because our only template is based on life on Earth. In this paper, a new approach is introduced to estimate the probability that life on Earth has survived from birth to the present based on its terrestrial extinction history. A histogram of the extinction intensity during the Phanerozoic Eon is modeled effectively with a log-normal function, supporting the idea that terrestrial extinction is a random multiplicative process. Assuming that the fitted function is a probability density function of extinction intensity per unit time, the estimated survival probability of life on Earth is ~0.15 from the beginning of life to the present. This value can be a constraint on fi in the Drake equation, which contributes to estimating the number of life-bearing exoplanets.

Removal Process of Nutrients and Heavy Metals in Tropical Biofilters

Biofilters are relatively new pollution control technology used to treat urban stormwater runoffs. Biofilters generally consist of vegetated top soil layer for nutrient uptake and sand-based filter media for heavy metals filtration. While the complex process of pollutant removal is studied for a temperate environment, only a few studies have been conducted under tropical climate conditions. This study aims to study the removal process of total nitrogen, total phosphorus and 6 heavy metals including copper, iron, manganese, nickel, lead, and zinc in a tropical biofiltration system. In this study, using the curve fitting analysis, the parabolic function was found to be the most fitted function to explain the relationship between pollutant concentration in the effluent and the infiltration rate of the system when the first flush phenomenon is simulated. Results demonstrated that the natural variation of infiltration rate during the saturation process of soil influences the performance of the system in removing some pollutants such as phosphorus, iron, and zinc.

Traditional PK-PD Indices for Efficacy – Can We Do Better?

Background The relationship between antimicrobial activity and exposure relative to MIC is typically evaluated using one of three PK-PD indices, AUC:MIC ratio, Cmax:MIC ratio, and %T>MIC. However, under certain circumstances, none of these PK-PD indices may be the most optimal. These include when the fitted Hill functions for each of the PK-PD indices do not allow for sufficient discrimination, the variability about the fitted functions is wide, and/or the pattern of dose fractionation data is non-informative. Relationships fit using the traditional PK-PD indices may be suboptimal for drugs which exhibit extreme PK characteristics such as abnormally short or long half-lives. As described herein, we explored the use of a fourth PK-PD index for such instances, AUC/τ:MIC ratio (τ = dosing interval). Methods Previously-described ceftolozane dose-fractionation data from a study using a neutropenic murine thigh-infection model were evaluated [AAC 2013; 57(4):1577–82]. In this prior study, mice were infected with E. coli ATCC 25922 (MIC = 0.5 mg/L) or K. pneumoniae ATCC 43816 (MIC = 1.4 mg/L). Ceftolozane doses ranged from 1.56 to 1600 mg/kg/24h given q3h, q6h, q12h, or q24h. Relationships between log10 colony forming units (CFU) at 24 hours and AUC:MIC ratio, Cmax:MIC ratio, %T>MIC, and AUC/τ:MIC ratio were evaluated by pathogen and pooled using Hill-type models and non-linear least squares regression. Results For evaluations of data by pathogen, AUC/τ:MIC ratio best described changes in log10 CFU at 24 hours. The coefficients of determination (r2) for these pathogens were improved by 0.20 and 0.11, respectively, relative to the highest r2 achieved using any of the traditional PK-PD indices. Similar results were observed when the data were evaluated using a pooled approach (Figure 1). Conclusion AUC/τ:MIC ratio may be useful to evaluate drugs demonstrating the extremes of PK. Accordingly, this PK-PD index best described ceftolozane PK-PD, an agent with a very short murine plasma half-life (<15 minutes). The use of the PK-PD index that allows for the best fit of the data to the Hill function and reduced variability about the fitted function will not only improve the characterization of PK-PD but will also improve the accuracy of future dose selection analyses. Disclosures All authors: No reported disclosures.

Permeability Estimation

Because it is a measure of flow, permeability is a vector quantity, as contrasted with conventional petrophysical log data, which are responses to static properties of the rock. In the absence of a direct measurement of permeability, predictions must be inferred from the rock framework characteristics that control the ability of fluids to move through the rock. In this chapter, we consider methods that predict absolute permeability, that is, permeability with respect to a single fluid. This is the most widely used meaning of the term and would be immediately applicable to aquifers. In engineering applications to reservoirs, a relative permeability is assigned to each fluid phase, so that relative fluid rates and volumes can be characterized explicitly. Although the fundamental physics of permeability in tubes has been understood for many years, reliable estimations are difficult to make in all but the simplest rock types. As we shall see, one approach attempts to adapt modifications to a tube model to accommodate the complexity of pore-system geometry. This model-driven methodology tends to be favored by engineers and contrasts with a data-driven geological approach that applies empirical relationships from core data from mercury porosimetry measurements. The most fundamental property used to predict permeability is that of pore volume. Both porosity and permeability are routine measurements from core analysis. If a useable relationship can be developed to predict permeability from porosity, then predictions of permeability can be made in wells that were logged with conventional measurements but not cored. The simplest quantitative methods used to predict permeability from logs have been keyed to empirical equations of the type: . . . log k = P +Q.Φ or log k = P +Q.log Φ. . . where P and Q are constants determined from core measurements and applied to log measurements of porosity (Φ) to generate predictions of permeability (k). These equations are the basis for statistical predictions of permeability in regression analysis, where porosity is the independent variable and logarithmically scaled permeability is the dependent variable. The fitted function minimizes the sum of the squared deviations of the permeability about the trend line.