Approximate Values Research Articles

Impact of Neighbouring Excavation on Diaphragm Wall under Seismic Loading

The existing diaphragm walls may be affected by the new structure as well as any excavation work required for the surrounding projects. During an earthquake, this effect can be more pronounced. It is therefore, suggested to create the diaphragm wall and the neighbouring excavation models with the intention of researching the influence of excavation upon diaphragm wall under dynamic conditions. For the investigation, a case study involving a diaphragm wall located in Noida was taken into account. The diaphragm wall and nearby excavation were modelled utilizing the Plaxis 3D program. By altering the space between the excavation and the diaphragm wall and entering the time-history acceleration data from an earlier earthquake, it was possible to examine the impact of the nearby excavation for the new construction on the diaphragm wall under dynamic conditions. The outcomes of three-dimensional numerical analysis were compared. The study has revealed that the wall's horizontal displacement increases with increasing the space between the wall and the excavation until it arrives at an approximate value that resembles the wall's horizontal deflection without nearby excavation. Graphs of shear force and bending moment were also compared and similar variations were found.

A simple measure of anchoring for short-run expected inflation in FIRE models

A simple measure of anchoring for short-run expected inflation in FIRE models

GDT: Multi-agent reinforcement learning framework based on adaptive grouping dynamic topological space

GDT: Multi-agent reinforcement learning framework based on adaptive grouping dynamic topological space

Strategy to improve the micropropagation of sugarcane plants using carbon dioxide injection

Objective: To develop a strategy for the improvement of micropropagation of sugarcane plants in the central region of Veracruz, using carbon dioxide injection. Design/methodology/approach: Intelligent control and micropropagation techniques are used in this development. Results: Improved micropropagation of sugarcane plants using carbon dioxide injection is demonstrated using intelligent control techniques. Findings/conclusions: With this controlled carbon dioxide injection system, research can be carried out to obtain the most approximate values to contribute to better growth and adaptability in sugarcane crops. This can guarantee shorter adaptation times and thus generate greater economic gains for the producers.

Synthesis, characterization, proteolytic activity inhibition, ADMET prediction, and molecular docking studies of novel indole derivatives as potential SARS-CoV-2 protease inhibitors

Synthesis, characterization, proteolytic activity inhibition, ADMET prediction, and molecular docking studies of novel indole derivatives as potential SARS-CoV-2 protease inhibitors

Opinion response functions are key to understanding the tipping of social conventions

Abstract The extent to which committed minorities can overturn social conventions is an active area of research in the mathematical modeling of opinion dynamics. Researchers generally use simulations of agent-based models (ABMs) to compute approximate values for the minimum committed minority size needed to overturn a social convention. In this manuscript, we expand on previous work by studying an ABM’s mean-field behavior using ordinary differential equation models and a new tool, namely opinion response functions (ORFs). Using this method allows for formal analysis of the deterministic model, which can provide a theoretical explanation for observed behaviors, e.g. coexistence or overturning of opinions. In particular, ORFs are a method for characterizing equilibria in our social model. Our analysis confirms earlier numerical results and supplements them with a precise formula for computing the minimum committed minority size required to overturn a social convention.

Morphology and agents of urban transformation

The study aims to propose a method of analysis that promotes a clearer perception of the spatial transformation resulting from the action of certain social groups to shape the urban space according to their interests. The territorial transformation related to the role of different agents is investigated, through urban morphology, in order to understand the correlation between the Brazilian urban form with public management and the direction of public investments. To analyze how the city is shaping over time, the work was structured from a case study, which mapped the urban transformations of the municipalities of Cuiabá and Várzea Grande, during the 2006-2021 interval. The method adopted by the research proposes as tools for investigating the territory: the conception of thematic cartographies through the comparison of aerial images from Google Earth, the establishment of analysis categories that allow the identification of the different types of building transformations preponderant of the urban blocks and the main interventions on the road system and the impact of important events that occurred in the cities in the period studied. A quantitative analysis is presented, with the approximate values of areas in hectares (ha), which represent the categories of analysis indicated. As a result, it can be seen, through the maps, that the relationship between the different forms of urban land occupation and the road infrastructure implemented ends up reinforcing the process of socio-spatial segregation. It is concluded that the proposed method, combined with historical and socioeconomic studies, manages to reconstitute urbanization processes in order to understand them in order to intervene in the reality of our cities.

Determining the approximate value of MD-Mahalanobis-Taguchi-Gram-Schmidt process by (K-MTGS) process

Determining the approximate value of MD-Mahalanobis-Taguchi-Gram-Schmidt process by (K-MTGS) process

A Simple Measure of Anchoring for Short-Run Expected Inflation in FIRE Models

We show that the fraction of non-reoptimizing firms that index prices to the inflation target, rather than lagged inflation, provides a simple measure of anchoring for short-run expected inflation in a New Keynesian model with full-information rational expectations. Higher values of the anchoring measure imply less sensitivity of rational inflation forecasts to movements in actual inflation. The approximate value of the model’s anchoring measure can be inferred from observable data generated by the model itself, as given by 1 minus the autocorrelation statistic for quarterly inflation. We show that a shift in the collective indexing behavior of firms allows the model to account for numerous features of evolving U.S. inflation behavior since 1960.

Fast Nonlinear Model Predictive Control Combining Online Trajectory Optimization and Value Function Regression

ABSTRACTModel predictive control (MPC) is a well‐developed method capable of handling complex control tasks. Implementation of an MPC requires solution of a deterministic finite horizon nonlinear optimal control (OC) problem. OC problems can be solved globally, explicitly expressing the optimal policy (and value function) as a function of the present state, or, locally, using online trajectory optimization, generating a solution that is only valid for the present state. For nonlinear problems however, neither is possible analytically, and the latter, finding a local solution online, is usually preferred. The difficulty with online trajectory optimization is that the solution must be available within a single sampling period. The main parameter affecting the computational demand of MPC is the length of the prediction horizon. The goal in this work is to reduce the length of the prediction horizon of a model predictive controller (MPC) to reduce computation time whilst preserving optimality guarantees. To this end, we propose approximation of the trajectory optimization problem for MPC by learning a finite horizon value function. The approximated value function is inserted into a truncated trajectory optimization problem so that the MPC can be attained with a reduced prediction horizon, ergo reduced computational load. By sampling the value function in a goal oriented way, we show that an effective approximate value function can be found by including both the function value and the gradients of the value function. The result is an accurate approximate MPC which leverages learning methodologies to reduce computational cost while still accounting for constraints.

A new approach to assess post-mortem interval: A machine learning-assisted label-free ATR-FTIR analysis of human vitreous humor

A crucial issue in forensics is determining the post-mortem interval (PMI), the time between death and the finding of a body. Despite various methods already employed for its estimation, only approximate values are currently achievable. Vitreous humor (VH) is an avascular tissue between the lens and the retina, mainly composed by a collagen fibers network, hyaluronic acid, and hyalocytes. Recently, it has received interest in forensic medicine, being easy to collect and susceptible to low microbiological contamination and putrefaction. Based on this evidence and thanks to the ability of Attenuated Total Reflectance - Fourier Transform InfraRed (ATR-FTIR) spectroscopy to perform fast analyses on a minimal sample amount, in this study, a new analytical approach to reliably estimate PMI is proposed combining ATR-FTIR analysis of VH human samples with multivariate statistical procedures, such as Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), for discriminant classification. Regression procedures, including Partial Least Squares Regression (PLSR), were performed: extremely positive results were obtained, and the most discriminant spectral features were highlighted (peaks at 1665, 1630, 1585, 1400, 1220, 1200, 1120, 854, 835, and 740cm-1) and associated to PMI classes (average accuracy over 80%). Specific and reliable markers able to correlate the macromolecular composition of VH with the PMI were identified, revealing a post-mortem protein degradation and amino acids deamination (decrease of proteins and increase of free amino acids and NH3), an increase of lactate, which diffuses from the retina to the VH, and changes in the hyaluronic acid component.

Online Health Information Seeking, eHealth Literacy, and Health Behaviors Among Chinese Internet Users: Cross-Sectional Survey Study.

The internet has become an increasingly vital platform for health-related information, especially in upper-middle-income countries such as China. While previous research has suggested that online health information seeking (OHIS) can significantly impact individuals' engagement in health behaviors, most research focused on patient-centered health communication. This study aims to examine how OHIS influences health behavior engagement among Chinese internet users, focusing on the role of eHealth literacy and perceived information quality in influencing relationships. An online cross-sectional survey was conducted in November 2021 among 10,000 Chinese internet users, using quota sampling based on sex, age, and urban and rural residence, in line with the 48th Statistical Report on Internet Development of China. Nonparametric tests were used to examine the differences in eHealth literacy across sociodemographic groups. Partial correlation analysis and stepwise linear regression were conducted to test the associations between key variables. Confirmatory factor analysis and structural equation modeling were conducted to test the hypotheses. Our study identified significant disparities in functional and critical eHealth literacy between urban and rural residents across age groups, income levels, education backgrounds, and health conditions (all P<.001). In terms of sex and regional differences, we found higher functional literacy among female users than male users, and critical literacy varied significantly across different regions. The proposed structural model showed excellent fit (χ2404=4183.6, χ2404=10.4,P<.001; root mean square error of approximation value of 0.031, 95% CI 0.030-.031; standardized root mean square residual value of 0.029; and comparative fit index value of 0.955), highlighting reciprocal associations between 2 types of eHealth literacy and OHIS. Participants' functional eHealth literacy, critical eHealth literacy, and OHIS have positive impacts on their health behavioral engagement. Perceived information quality was found to mediate the influence of OHIS on health behavior (b=0.003, 95% CI 0.002-0.003; P<.001). The study revealed the pathways linking sociodemographic factors, eHealth literacy, OHIS, and perceived information quality and how they together influenced health outcomes. The findings underscore the significance of enhancing eHealth literacy and improving information quality to promote better health outcomes among Chinese internet users.

Frequency identification method based on active aliasing of biprobes blade tip timing without once-per-revolution

Frequency identification method based on active aliasing of biprobes blade tip timing without once-per-revolution

Modified Hermite Wavelet Discrete Matrix Approach for the Brusselator Chemical Model

AbstractThe primary goal of this study is to create a wavelet collocation technique that can be used to solve nonlinear fractional order systems of ordinary differential equations, which are equations that arise in modeling problems related to auto‐catalytic chemical reactions. Using the Hermite wavelet collocation method (HWCM), the system of nonlinear ordinary differential equations of integer and fractional order is numerically solved. The nonlinear Brusselator system is transformed into an algebraic equation system using the collocation method and the fractional derivative operational matrices. The Newton‐Raphson method is used to solve these algebraic equations, and the approximate values of the derived unknown coefficients are substituted. Through the numerical examples, the method's computational effectiveness and correctness are illustrated with various model constraints. A numerical comparison is made between the current approach ND solver, RK method, and Haar wavelet method (HWM). The efficiency and reliability of the developed strategy's performance are shown in graphs and tables. The created Hermite wavelet collocation method is resilient and has good accuracy compared to current methods found in the literature. Numerical computations are performed through Mathematica, a mathematical software.

A note on the satisficing policy of the secretary problem

Wu and Li (2022) presented a satisficing policy for the secretary problem (SP). Moreover, Wu and Li (2022) derived asymptotic formulas of the maximum probability of choosing one of the k satisfactory applicants with special cases k = 2 and 3, respectively, in the satisficing policy. “Based on the work of Wu and Li (2022), this paper derives the asymptotic formulas for the probability of selecting one of the k satisfactory applicants and provides the equation for the approximate optimal cutoff value to achieve the asymptotic maximum probability in the general case of k satisfactory applicants under the satisficing policy.” Moreover, a series of computer simulations are conducted to test the theoretical results for k = 4 and 5.

Analytical solution of ground vibration of a half-space induced by sub- and super-critical harmonic moving loads: Theory and application

Analytical solution of ground vibration of a half-space induced by sub- and super-critical harmonic moving loads: Theory and application

The influence of precursor solutions containing an amount of silver bismuth sulfide nanoparticles (AgBiS2 NPs) on the characteristics of CH3NH3PbI3 perovskites solar cells

The influence of precursor solutions containing an amount of silver bismuth sulfide nanoparticles (AgBiS2 NPs) on the characteristics of CH3NH3PbI3 perovskites solar cells

Application of semiclassical approximation to stochastic differential equations

Abstract A method for calculating the characteristics of stochastic differential equations using semiclassical approximation is proposed. For a stochastic differential equation arising in the study of the pure birth process (Yule process) and the Cox Ingersoll Ross (CIR) model, an analysis of the accuracy of the semiclassical approximation was carried out. This analysis is based on a comparison of approximate values with exact values for the mathematical expectation of a solution to the equation.

Development and Validation of a Scale to Measure Violence against Women among Myanmar Migrant Women in Thailand

Introduction: Violence against women (VAW) is a serious human rights violation with significant implications for public health. VAW affects the well-being of women, children, and families. This study aims to develop and validate a scale specifically designed for identifying and assisting migrant women who have experienced violence. Methods: A cross-sectional survey using stratified sampling was conducted among 295 Myanmar migrant women in Thailand. Violence among these women was assessed using self-administered questionnaires with data collection taking 15–20 min per participant between September and December 2023. The construct validity of the Violence against Migrant Women Scale (VAMWS) was confirmed through exploratory factor analysis (EFA) estimated by weighted least squares means and variance with Geomin rotation in Mplus software. Results: The EFA revealed a 13-item scale with a four-factor structure that fit the data exceptionally well, as indicated by the high comparative fit index of 0.99 and low root mean square error of approximation value of 0.02. Communalities ranged from 0.58 to 0.99 and rotated factor correlations between 0.36 and 0.53. The four dimensions were as follows: F1 – physical (4 items, loadings 0.51–0.73), F2 – sexual (2 items, loadings 0.66–0.99), F3 – psychological (3 items, loadings 0.57–0.73), and F4 – economic (3 items, loadings 0.50–0.78). VAMWS had Cronbach’s alpha of 0.90 and corrected item–total correlation values from 0.53 to 0.74. Physical violence, experienced by 50% of respondents, was most common, primarily by spouses, then siblings, acquaintances, employers, parents, and friends. Conclusion: VAMWS is applicable for assessing violence prevalence across multiple sectors, including health care, social services, law enforcement, and future research endeavors.

A Wind Tunnel Experiment Study on Splash Functions During Sand Saltation

AbstractSplash functions delineate the intricate interaction between wind‐driven particles and the bed. However, due to limitations in measurement methods, achieving a comprehensive understanding of splash functions remains challenging. In this study, we utilized a high‐speed system and particle trajectory tracking algorithm to reconstruct 857 collision events involving natural sand particles obtained from field samples and artificial glass microspheres interacting with a bed composed of analogous particles in a wind tunnel. During the experiments, the ratio of the wind shear velocity (u*) to the impact threshold (u*ti) consistently ranged between approximately 1.22 and 1.79. Our findings indicate that the impact angle remains independent of both impact velocity and particle size, maintaining an approximate value of 10.5 ± 6.5°. The evaluation of splash functions depends on the criterion used to define ejection, that is, the ratio of the centroid's height of the liftoff particles to their particle size (H/d). Additionally, at the same critical height (H/d = 1.5), our splash functions show differences of varying degrees from previous experiments and theoretical studies performed under no wind conditions. We believe that the main reason for these differences may be that the energy exchange between the bed surface and the airflow increases the looseness of the large‐particle (&gt;0.1 mm) bed surface. These findings hold significant implications for accurately modeling sand‐bed collisions in natural environments.