Bivariate Methods Research Articles

Spatial-Performance Evaluation of Primary Health Care Facilities: Evidence from Xi’an, China

Primary health care (PHC) facilities play a significant role in constructing a “people-oriented city” to promote sustainable urban development. However, existing studies exhibit gaps in the spatial-performance evaluation of PHC facilities at the block scale and in identifying spatial association types between facilities and the population. Therefore, we examined the elderly population, who rely heavily on PHC facilities, and developed a spatial-performance evaluation model for PHC facilities at the block scale using the Ga2SFCA method and the bivariate spatial autocorrelation method. The results revealed an evident concentric pattern and spatial mismatch between the accessibility of facilities and the elderly population. Facilities in the central area were inadequate due to the excessive density of the elderly population, whereas medical services in suburban areas were unsustainable due to poor accessibility. From a spatial-justice perspective, the spatial-performance evaluation at the block scale can identify spatial correlation types and distribution characteristics between PHC facilities and the elderly population.

Mathematical analysis of a combustible viscoelastic material in a cylindrical channel taking into account induced electric field: A spectral approach

Abstract In spite of the enormous applications of heating combustible materials due to exothermic chemical reactions, scientists and engineers still face a problem with these materials’ tendency to self-ignition, which can result in significant property damage if serious precautions are not taken. Therefore, the thermal decomposition of combustible viscoelastic material in a cylindrical channel is investigated in this study. With a third-order constitutive model considered for viscoelastic flow behavior, momentum and energy-balanced governing equations are provided. The chemical reaction of the material is assumed exothermic and thus follows Arrhenius’s kinetics. A numerical solution is provided for the boundary value problem via the bivariate spectral collocation method, and the impact of kinetics parameters on the combustible viscoelastic material is investigated. Our findings show that self-ignition is delayed with higher values of activation energy parameter ( ε \varepsilon ) and third-order parameter ( γ \gamma ), as well as lower values of magnetic field parameter ( M M ), current density parameter ( δ \delta ), and electrical conductivity exponent ( m m ).

Investigating the Joint Probability of High Coastal Sea Level and High Precipitation

The design strategies for flood risk reduction in coastal towns must be informed by the likelihood of flooding resulting from both precipitation and coastal storm surge. This paper discusses various bivariate extreme value methods to investigate the joint probability of the exceedance of thresholds in both precipitation and sea level and estimate their dependence structure. We present the results of the dependence structure obtained using the observational record at Bridgeport, CT, a station with long data records representative of coastal Connecticut. Furthermore, we evaluate the dependence structure after removing the effects of harmonics in the sea level data. Through this comprehensive analysis, our study seeks to contribute to the understanding of the joint occurrence of sea level and precipitation extremes, providing insights that are crucial for effective coastal management.

Impact of TV Advertising on Decision-Making of Consumers in Pakistan

Television advertising has proven to be an effective tool for introducing new products and influencing customer behavior and decision-making processes. This study analyzes the "Impact of Television Advertisement on Consumer Decision Making in Pakistan." The researcher collected data using the survey method and a questionnaire. 300 female consumers were chosen from three regions of Lahore (Karim Park, Gulshan e Ravi, and Defense) based on demographics such as age, education, and income. The data was examined using univariate and bivariate methods of statistical analysis, and conclusions were drawn. The hypothesis was verified using the test for statistical significance, Chi-Square, which confirmed that 'More Nesvita TV ads, more acceptances in actual life among customers'. It was discovered that television advertising had a significant impact on consumers' cognitive functions such as searching for information and alternative selection. The findings provide useful information about the efficiency of Nestlé Nesvita TV advertisements and their impact on consumer decision-making processes in the Pakistani market.

The Relationship between Knowledge & Attitude and the Ownership of Healthy Toilets in Drien Kipah Village, Southwest Aceh Regency

The ownership of healthy toilets is a fundamental aspect of sanitation that should be universally embraced by all households. Data obtained from the Health Office of Southwest Aceh Regency, specifically from the Bineh Krueng Community Health Center, reveals that only 41.05% of households possess healthy toilets. This study aims to investigate the factors influencing the ownership of healthy toilets in Drien Kipah Village, Southwest Aceh Regency. This study employed a quantitative approach with a cross-sectional design, analyzing a population of 112 households. 32 households were selected using the simple random sampling technique as per Slovin’s formula. Data collection was conducted through primary means, utilizing questionnaires. Furthermore, the analysis of the data involved both univariate and bivariate methods, employing the chi-squared test to discern relationships. The findings underscore that knowledge (p-value = 0.000), attitude (p-value = 0.000), education (p-value = 0.000), income (p-value = 0.006), and support from healthcare workers (p-value = 0.000) significantly correlate with the ownership of healthy toilets in Drien Kipah Village, Southwest Aceh District.

Gaidai multivariate risk assessment method for cargo ship dynamics

ABSTRACT Contemporary cargo vessel transport constitutes a vital part of the global trade and economy. Thus, it is of primary engineering and design importance to further develop more efficient novel risk analysis and risk assessment methods for large cargo ships. Classical risk assessment and risk analysis methodsmay not always have advantages of efficiently dealing with dynamic system’s high dimensionality along with cross-correlations between various critical dimensions. Current study benchmarks state-of-art Gaidai spatiotemporal structural risk assessment method, suitable for multivariate structural dynamic systems versus a well-established bivariate risk assessment method. As an example, for this risk assessment study, an operating container vessel has been selected. The vessel hull had been subjected to large deck panel stresses and accelerations during cross-Atlantic sailing. Risks of losing cargo containers are caused by extreme dynamics being one of the primary concerns for vessel cargo transport. Gaidai multivariate risk assessment methodology, advocated here, opens up new possibilities of predicting efficiently, yet simply potential structural damage/failure risks for nonstationary, nonlinear, multivariate cargo ship dynamic systems, as a whole. Note that advocated novel multivariate risk assessment method may be applied to a wide range of complex marine and offshore engineering systems.

Calculation and Analysis of Equilibrium Position of Aerostatic Bearings Based on Bivariate Interpolation Method

The solution of equilibrium positions is a critical component in the calculation of the dynamic characteristic coefficients of aerostatic bearings. The movement of the rotor in one direction leads to bidirectional variations in the air film force, resulting in low efficiency when using conventional calculation methods. It can even lead to iterative divergence if the initial value is improperly selected. This study concentrates on the orifice throttling aerostatic bearings and proposes a novel method called the bivariate interpolation method (BIM) to calculate the equilibrium position. The equilibrium equation for the rotor under the combined influence of air film forces, gravity, and external loads is established. A calculation program based on the finite difference method is developed to determine the equilibrium position. The process of solving the equilibrium position and the convergence is compared with the secant method and the search method. Furthermore, the variation trend of the equilibrium position and stiffness when the external loads changes are studied based on the BIM. Finally, the correctness of the BIM to solve the equilibrium position is proved by comparing it with the experiment results. The calculation results indicate that the BIM successfully resolves the problem of initial value selection and exhibits superior computational efficiency and accuracy. The equilibrium position initially moves away from the direction of the external load as the load increases, and then this gradually approaches the load direction. The main stiffness increases with increases in the external load, while the variation in cross stiffness depends on the direction of the external load.

Trends in health inequalities in childhood and adolescence in Germany: Results of the HBSC study 2009/10 - 2022.

Many studies have identified health inequalities in childhood and adolescence. However, it is unclear how these have developed in recent years, particularly since the COVID-19 pandemic. Analyses are based on the German data from the international Health Behaviour in School-aged Children (HBSC) study from 2009/10 (n = 5,005), 2013/14 (n = 5,961), 2017/18 (n = 4,347), and 2022 (n = 6,475). A total of 21,788 students aged approximately between 11 and 15 years were included. Socioeconomic status (SES) was assessed using the Family Affluence Scale (FAS). Several health indicators were analysed stratified by gender using bivariate and multivariate analysis methods. In 2022, there are clear socioeconomic inequalities in life satisfaction, self-rated health, fruit and vegetable consumption, and physical activity. These inequalities remained largely constant or increased between 2009/10 and 2022. Between 2017/18 and 2022, no significant changes in inequalities were found. Health inequalities are persistent and reduce the chances of growing up healthy. There is no evidence that inequalities in the analysed outcomes have changed during the pandemic period (between 2017/18 and 2022). Rather, the changes in the health indicators seem to affect all adolescents in a similar way.

Understanding challenges related to menstrual hygiene management: Knowledge and practices among the adolescent girls in urban slums of Jaipur, India.

This study aimed to determine the factors associated with knowledge and practices related to menstrual hygiene management among adolescent girls in urban slums in Jaipur, India. A cross-sectional study among 417 adolescent girls was conducted. Descriptive statistics, Chi-square, and bivariate and multivariate logistic regression methods were used to analyze the data and determine the associated factors. Only 48.7% of girls had a correct understanding of menstruation. In addition, 55.1% of the menstruating girls had faced health problems related to mensuration in the last 6 months; however, only 47.6% visited a health facility for treatment. Educational status of the girl (AOR = 1.89, 95% CI = 0.88-4.06), mother's education (AOR = 2.19, 95% CI = 1.30-3.67) and income (AOR = 1.89, 95% CI = 0.67-3.95), father's income (AOR = 1.42, 95% CI = 0.76-2.95), and counseling by field health workers (AOR = 2.08, 95% CI = 1.23-3.51) were found to be associated with knowledge about menstruation. Girl's education (AOR = 1.49, 95% CI = 0.74-2.95), mother's education (AOR = 1.46, 95% CI = 0.7-2.84) and income (AOR = 1.314, 95% CI = 0.44-2.02), father's education (AOR = 1.64, 95% CI = 0.55-3.08) and income (AOR = 2.0, 95% CI = 0.86-3.28), and counseling by field health workers (AOR = 1.48, 95% CI = 0.76-2.64) were found to be associated with the type of absorbents used. The findings from the study show that the awareness about mensuration and utilization of health services among adolescent girls is low. There is a need to create an enabling environment for girls to access knowledge and health services related to menstruation by creating awareness at the community level, strengthening outreach by field health workers, and ensuring privacy in healthcare facilities.

A framework model to integrate sources and pathways in the assessment of river water pollution

Metal and nutrient pollution, soil erosion, and alterations in climate and hydrology are prevalent issues that impact the water quality of riverine systems. However, integrated approaches to assess and isolate causes and paths of river water pollution are scarce, especially in the case of watersheds impacted by multiple hazardous activities. Therefore, a framework model for investigating the multiple sources of river water pollution was developed. The chosen study area was the Paraopeba River basin located in the Minas Gerais, Brazil. Besides multiple agriculture, industrial, and urban pollution sources, this region was profoundly affected by the rupture of the B1 tailings dam (in January 2019) at the Córrego do Feijão mine, resulting in the release of metal-rich waste. Considering this situation, thirty-nine physicochemical and hydromorphological parameters were examined in the Paraopeba River basin, in the 2019–2023 period. The analysis involved various statistical techniques, including bivariate and multivariate methods such as correlation analysis, principal component analysis, and clustering. The Paraopeba River was mainly impacted by metal contamination resulting from the dam collapse, whereas nutrient contamination, mainly from urban and industrial discharges, predominantly affected its tributaries. Additionally, the elevated concentrations of aluminum, iron, nitrate, and sulfate in both main river and tributaries can be attributed to diffuse and point source pollution. In terms of hydromorphology and soil type, the interaction between woody vegetation and erosion-resistant soils, especially latosols, contributes to the stability of riverbanks in the main river. Meanwhile, in the tributaries, the presence of neosols and sparse vegetation in urbanized areas promoted riverbank erosion potentially amplifying pollution. While the study was conducted in a particular watershed, the findings are based on a methodology that can be applied universally. Hence, the insights on surface water quality from this research can be a valuable resource for researchers studying watersheds with diverse pollution sources.

Analysing spatio-temporal drought characteristics and copula-based return period in Indian Gangetic Basin (1901-2021).

Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in theIndo-Gangetic plainregion. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901-2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100years of return occurred during 2008-2011 and 2016-2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010-2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts.

Modelling the coupled heterogeneities of the lacustrine microbialite-bearing carbonate reservoir of the Yacoraite Formation (Salta, Argentina)

The Yacoraite Formation is a complex lacustrine microbialite-bearing carbonate formation whose heterogeneity is due to different sedimentary facies associations and several microbialite geobodies. The bi-variate plurigaussian geostatistical method is applied to simulate in parallel these two types of heterogeneity in a 3D reservoir-scale geological model. Each variable is simulated by a complete plurigaussian method based on geological interpretation and field observations and quantifications. They are coupled through the occurrence of the microbialites within the sedimentary facies and associated into combined facies giving a one-glance representation of the reservoir heterogeneity, then used to constrain the porosity simulation.

Cross-domain dynamics: How geopolitical and climate policy uncertainties shape tourism patterns in the United States

Predicting tourism demand is crucial for policymakers and stakeholders in the tourism industry, enabling them to enhance promotional strategies, optimize marketing efforts, align investments, and achieve operational efficiency. While existing research has highlighted the negative impact of global risk factors such as geopolitical risks, economic policy uncertainty, and climate changes on tourism demand, the specific influence of climate policy changes and their differential impact on tourist arrivals has been less explored. Addressing this gap, our study employs bivariate, multiple, and partial wavelet methods to analyze the differential impact of climate policy uncertainty and geopolitical risk on tourism arrivals in the United States. Utilizing recent monthly data from January 1996 to August 2022, we uncover significant time-frequency varying dependencies between these factors and tourism demand. Our causality analysis reveals that both geopolitical risk and climate policy uncertainty are key determinants of tourism demand in the U.S. Furthermore, the Nonlinear Autoregressive Distributed Lag model corroborates the findings of the wavelet analysis, highlighting asymmetrical interactions in the long run. These findings offer valuable insights and have significant implications for policymakers and industry stakeholders, suggesting the need for adaptive and responsive tourism strategies that consider the evolving landscape of geopolitical and climate policy uncertainties.

Data-driven sensor delay estimation in industrial processes using multivariate projection methods

A key step in preparing industrial data for multivariate statistical modelling of (batch-)continuous processes is the estimation of sensor delays along the production line, to use as a correction for understanding relationships between them. Without such a correction, the measurements collected from the sensors do not all relate to the same portion of material travelling through the plant, which is where from a physical point of view the correlations are expected to arise from. Most methods to do these corrections currently reported in literature are limited in that they optimize only correlations bivariately between the different sensors, despite the eventual goal of being understood as a multivariate process model. This work proposes several methods for multivariate sensor delay estimation, based on multivariate projection methods, and critically investigates these using simulated and empirical process data from two industrial facilities. The objective is to provide more clarity on if, how, and why taking into account these multivariate correlations using such projection methods is beneficial. One of the proposed methods, named PLS-SEQ, was shown to outperform bivariate sensor delay estimation, which is regarded as benchmark method in this work, for all datasets. The average reduction in delay estimation error achieved by using PLS-SEQ is between 6% and 64%. The other newly proposed multivariate projection-based methods did not show such unanimous improvement in accuracy, but helped identifying the presence of sensor clusters in industrial data as a novel key challenge for sensor delay estimation. The presented results illustrate that projection-based multivariate methods, in particular the newly proposed method PLS-SEQ, show promising potential for sensor delay estimation, outperforming the bivariate sensor delay estimation methods used as benchmark. Ultimately, using these methods can improve the predictive and descriptive quality of statistical models for key industrial processes.

Dynamics of accelerating and decelerating flows: A boundary layer examination with non-similar approach and convective boundary condition

Moisture/air-flow over the aircraft wing and bonnet of a moving car in aerodynamical systems exhibit dynamic behavior characterized by accelerating and decelerating flows. These analysis is essential and applicable in various fields, including physics, engineering, and fluid mechanics. The present investigation aim to explore the dynamics of accelerating and decelerating flows within the framework of boundary layer examination. To achieve these objectives, a non-similar group of transformations is employed to convert the governing dimensional two-variable dynamical system into a dimensionless differential form, with η and ξ as the independent variables. To gain physical understanding of the mathematical equations governing the flow, an efficient bivariate spectral collocation method (BSCM) is employed for analyzing the flow dynamics. This method allows for a thorough investigation of the behavior and characteristics of the accelerating and decelerating Casson flows. Subject to the convergence and residual error analysis of the numerical results, the effects of pertinent parameters on the flow variables were investigated. The findings of this study show that the effects of flow parameters on decelerating and accelerating flows are not completely opposite. Additionally, the Biot parameter positively impacts the velocity and temperature profiles of the two dynamical flows. However, an increase in the Casson fluid parameter β has an opposing effect on the temperature and concentration profiles of both flows.

A bivariate spectral linear partition method for solving nonlinear evolution equations

This work develops a method for solving nonlinear evolution equations. The method, termed a bivariate spectral linear partition method (BSLPM), combines the Chebyshev spectral collocation method, bivariate Lagrange interpolation, and a linear partition technique as an underlying linearization method. It is developed for an th‐order nonlinear differential equation and then used to solve three known evolution problems. The results are compared with known exact solutions from literature. The method's applicability, reliability, and accuracy are confirmed by the congruence between the numerical and exact solutions. Tables, error graphs, and convergence graphs were generated using MATLAB (R2015a), to confirm the order of accuracy of the method and verify its convergence. The performance of the method is also observed against other methods performing well in these types of differential equations and is found to be comparable in terms of accuracy. The proposed method is also efficient as it uses minimal computation time.

The timing of antenatal care access for adolescent pregnancies in Cape Town, South Africa.

Late antenatal care (ANC)-seeking among pregnant adolescents threatens their health outcomes, and the health outcomes of their new-borns. South Africa has experienced a rapid increase in adolescent pregnancies during the COVID-19 pandemic, adding to the existing concerns around adolescent pregnancy care-seeking behaviour. The main aim of this study was to investigate the causes and covariates of late ANC access among adolescents in the Cape Town Metropole, South Africa. Three public healthcare facilities in the Cape Town Metropole, 2018-2019. A retrospective, cross-sectional study on ANC seeking behaviour was conducted, surveying 202 adolescents. Late attendance was defined as attending ≥ 3 months. For this study, adolescents were defined as women aged 16-18 years. The sample was restricted to adolescents who used public healthcare facilities or who did not attend at all. Data were analysed using univariate, bivariate and multivariate methods. A total of 50.8% (n= 99/195) of the pregnant adolescents in the sample had their first ANC visit 3 months. 14.9% (n= 29/195) did not attend at all. Major contributors to delayed care-seeking include poor pregnancy identification (n= 45/99, 45.5%), and a lack of information about ANC. Age, education, and alcohol consumption were significant predictors of delayed care-seeking. Delayed ANC attendance contributes to negative long-term health outcomes for pregnant adolescents and their new-borns. Improving access to pregnancy tests in the public sector could benefit adolescents with earlier pregnancy identification. Adolescents need to be made aware of their care seeking options.Contribution:There is evidence of long-term health impacts of late ANC attendance by pregnant adolescents, but there is an absence of evidence on the timing and barriers of late care-seeking behaviour. In this study, late ANC attendance among adolescents was associated with late pregnancy identification and poor knowledge of care options.

Factors Influencing the Incidence of Stunting in Toddlers in Sukamaju Village, Kadudampit Health Center Working Area, Sukabumi District

Aims: This study was to determine the effect of immunization, economic status, maternal motivation, and family support on the incidence of stunting in toddlers. Methods: The study involved 223 toddlers in Sukamaju Village, Kadudampit Health Center Working Area, Sukabumi Regency, with data collected through questionnaires and analyzed using univariate and bivariate methods, passing an ethical review. Results: There is a significant effect of immunization on the incidence of stunting (p-value, 0.031), economic status on the incidence of stunting (p-value, 0.000), maternal motivation on the incidence of stunting (p-value, 0.000), family support on the incidence of stunting (p-value, 0.000). Conclusion: There is an effect of immunization, economic status, maternal motivation, and family support on the incidence of stunting in toddlers.

Dynamic bivariate correlation methods comparison study in fMRI

Dynamic bivariate correlation methods comparison study in fMRI

The socio-economic factors influencing adolescent childbirth in Indonesia

Adolescent childbirth (ages 15-19) is a global issue that can result in morbidity and mortality among adolescents. The rate of adolescent childbirth is of particular concern to the Indonesian government as it has not yet reached the desired targets. The aim of this research is to analyze the socio-economic factors influencing adolescent childbirth (ages 15-19) in Indonesia based on data from the 2017 Indonesian Demographic and Health Survey (IDHS). This study utilizes secondary data from the 2017 Indonesian Demographic and Health Survey, with a sample size of 7,930 adolescents. Data were analyzed using univariate, bivariate, and multivariate descriptive statistical methods. Adolescent childbirth in Indonesia among ages 15-19 is observed in 416 adolescents (5.2%). Based on multivariate analysis, it was found that variables significantly associated with adolescent childbirth are educational level and economic status. Adolescents with low education are 27 times more likely to experience childbirth (aOR: 27.756; 95% CI: 12.007 - 64.163) compared to those with higher education. Furthermore, adolescents with the lowest economic status have a 2 times higher risk (aOR: 2.644; 95% CI: 2.014 - 3.470) of experiencing adolescent childbirth compared to those with the highest economic status. Adolescent childbirth is a health issue that warrants attention in Indonesia. Enhancing education, empowerment, awareness, and support for adolescent girls, along with policy implementation, is crucial for reducing the adolescent childbirth rate.