18 October 2019
Previous studies using spatial statistical modeling that account for spatial associations between geographic areas are scarce. Therefore, this study examines the association between neighborhood environment and obesity using a Bayesian spatial multil...
Concerns about transportation energy consumption and emissions force urban planners and policy makers to pay more attention to the effects of car ownership and use on the environment in China. However, few studies have investigated the relationship b...
To ensure scientific reproducibility of metabolomics data, alternative statistical methods are needed. A paradigm shift away from the p-value toward an embracement of uncertainty and interval estimation of a metabolite’s true effect size may le...
SUVs (sport utility vehicles), as a car segment, have become a foundation within the automotive industry due to their versatility, which is used by a wide range of customers. Recognising the complex interplay between geographical and economic conditi...
The aim of this study is to reveal the effects of multilevel visual characteristics of greenways on thermal perception in hot and humid regions during summer and to explore the potential of visual design to enhance psychological thermal comfort. Data...
Real-world systems frequently exhibit hierarchical multipartite graph structures, yet existing graph neural network (GNN) approaches lack systematic frameworks for hyperparameter optimization in heterogeneous multi-level architectures, limiting their...
Bayesian modeling using Markov chain Monte Carlo (MCMC) estimation requires researchers to decide not only whether estimation has converged but also whether the Bayesian estimates are well-approximated by summary statistics from the chain. On the con...
25 August 2022
TB is preventable and treatable but remains the leading cause of death in South Africa. The deaths due to TB have declined, but in 2017, around 322,000 new cases were reported in the country. The need to eradicate the disease through research is incr...
Under overmodulation conditions, the capacitor voltages of half-bridge and full-bridge submodules in hybrid modular multilevel converters (MMCs) may become unbalanced. This imbalance not only gives rise to overvoltage stress on submodule capacitors,...
Construction projects are high-risk environments characterized by workforce mobility, fragmented operations, schedule pressure, and multilayer subcontracting. This study examines how team safety climate and workgroup-shared perceived organizational s...
This paper provides a critical narrative review of the literature on climate-related credit-risk and its implications for the banking sector. Banks’ exposure to physical and transition climate risks can significantly affect credit quality, lend...
29 August 2018
Although the impacts of built environment on car ownership and use have been extensively studied, limited evidence has been offered for the role of spatial effects in influencing the interaction between built environment and travel behavior. Ignoring...
28 May 2022
Background: Antenatal care is an operational public health intervention to minimize maternal and child morbidity and mortality. However, for varied reasons, many women fail to complete the recommended number of visits. The objective of this study was...
In recent years, increasing concerns over climate change and transportation energy consumption have sparked research into the influences of urban form and land use patterns on motorized travel, notably vehicle miles traveled (VMT). However, empirical...
The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and their vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the c...
Croon and van Veldhoven discussed a model for analyzing micro–macro multilevel designs in which a variable measured at the upper level is predicted by an explanatory variable that is measured at the lower level. Additionally, the authors propos...
Background: Pandemic outbreaks have emerged as a significant global threat, with the potential to cause waves of infections that challenge public health systems and disrupt societal norms. Understanding the underlying behavior of disease transmission...
Reading comprehension (RC) can be predicted from language comprehension (LC) and decoding, and all three constructs are responsive to structured teaching. Culturally responsive instruction, which explicitly connects students’ lived experiences...
Background: Globally, prostate cancer is the second leading cause of cancer deaths among males. It is the most commonly diagnosed cancer in Australia. The quality of life of prostate cancer patients is poorer when compared to the general population d...
Quantifying geographic variation is crucial for policy evaluation, yet researchers often rely on complex national surveys not designed for sub-national inference. This design-analysis mismatch creates two challenges when decomposing variance across d...
Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and...
Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations....
6 July 2022
The spread of the COVID-19 pandemic was spatially heterogeneous around the world; the transmission of the disease is driven by complex spatial and temporal variations in socioenvironmental factors. Spatial tools are useful in supporting COVID-19 cont...
Amalgamation of evidence in statistics is conducted in several ways. Within a study, multiple observations are combined by averaging, or as factors in a likelihood or prediction algorithm. In multilevel modeling or Bayesian analysis, population or pr...
The distributed dynamic load is difficult to obtain due to the complexity of loads in practical engineering, such as the aerodynamic loads of aircraft and the distributed dynamic loads of sea-crossing bridges. Thus, distributed dynamic load identific...
Synthetic datasets are increasingly used in education research for methodological validation, privacy-preserving data sharing, and reproducible equity analysis; however, most generative approaches prioritize marginal distributional similarity without...
In this paper, a hierarchical prior model based on the Haar transformation and an appropriate Bayesian computational method for X-ray CT reconstruction are presented. Given the piece-wise continuous property of the object, a multilevel Haar transform...
A wide range of machine-learning-based approaches have been developed in the past decade, increasing our ability to accurately model nonlinear and nonadditive response surfaces. This has improved performance for inferential tasks such as estimating a...
This study presents an integrated statistical framework for the analysis of biomonitoring data in environmental toxicology, with a focus on xenobiotic exposure in maternal–neonatal systems. Such data are typically characterized by strong right-...
Interpretable and scalable data-driven methodologies providing high granularity baseline predictions of energy use in buildings are essential for the accurate measurement and verification of energy renovation projects and have the potential of unlock...
Unusual levels of agricultural product waste are becoming one of the issues and dangers that human societies face in their efforts to achieve food security. Therefore, reducing agricultural product waste is one of the main strategies for the optimal...
At present, reducing the impact of the construction industry on the environment is the key to achieving sustainable development. Countries all over the world are using software systems for bridge environmental impact assessment. However, due to the c...
The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis of such datasets often requires highly parameterized models with diffe...
This review examines neural operator architectures for learning solution operators of parametric partial differential equations (PDEs), with an emphasis on conceptual clarity and practical implementation. The work analyzes key models, including DeepO...
For billions of people living in remote and rural communities in the developing countries, small water systems are the only source of clean drinking water. Due to the rural nature of such water systems, site visits may occur infrequently. This means...
With the rapid advancement of deep learning technology, deep learning-based methods have become the mainstream approach for detecting potential safety hazards in transmission lines, playing a crucial role in power grid safety monitoring. However, exi...
Background/Objectives: Research on the relationship between small-area-level deprivation and cancer survival, particularly for colorectal cancer (CRC), is lacking. Therefore, we investigated the relationship among small area-level deprivation, indivi...
21 July 2015
Developing countries face a huge burden of infectious diseases, a number of which co-exist. This paper estimates the pattern and variation of malaria and diarrhea coexistence in Chikhwawa, a district in Southern Malawi using bivariate multilevel mode...
This work addresses statistical inference for multi-level step-stress accelerated life testing. Under the assumption that product lifetime follows the Gompertz distribution at each stress level, featuring a common shape parameter and stress-varying s...
Divergent thinking tests are popular instruments to measure a person’s creativity. They often involve scoring fluency, which refers to the count of ideas generated in response to a prompt. The two-parameter Poisson counts model (2PPCM), a gener...
Remote sensing technology has been modernized by artificial intelligence, which has made it possible for deep learning algorithms to extract useful information from images. However, overfitting and lack of uncertainty quantification, high-resolution...
Bayesian MCMC is a widely used model estimation technique, and software from the BUGS family, such as JAGS, have been popular for over two decades. Recently, Stan entered the market with promises of higher efficiency fueled by advanced and more sophi...
As global super-large open-pit mines expand in scale and extraction depth, conventional single-stage planning cannot meet the combined demands of productivity and resource recovery, making the shift to underground block caving inevitable. This study...
Small and medium-sized enterprises (SMEs) constitute the backbone of the EU economy, yet their uneven digital transformation raises challenges for competitiveness and territorial cohesion. This article examines the organizational and spatial aspects...
This study investigates the relationship between educational leadership, ICT-related factors, and students’ reading performance using the PISA 2022 dataset for Türkiye. Drawing data from 7250 students and 196 school principals, we employed...
Concentrating on geographically hierarchical data structures and using large-scale satisfaction survey data in Nanjing, this study employs Bayesian spatial multilevel model (MLM) to evaluate Nanjing’s perceived sustainable urbanization. In this...
This study explores the perception of (Austrian) standard German and Austro-Bavarian dialect varieties by 111 adult speakers of German as a second language (L2) in Austria, tested through ‘smart’ and ‘friendly’ judgements in a...
Tropical plants are expected to have a higher variety of defensive traits, such as a more diverse array of secondary metabolic compounds in response to greater pressures of antagonistic interactions, than their temperate counterparts. We test this hy...
Background/Objectives: Birth preparedness and complication readiness (BPCR) is a cornerstone of maternal health strategies designed to minimize the “three delays” in seeking, reaching, and receiving skilled care. In Ethiopia, uptake of BP...
The accurate prediction of secondary structures of proteins (SSPs) is a critical challenge in molecular biology and structural bioinformatics. Despite recent advancements, this task remains complex and demands further exploration. This study presents...
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