Modeling Techniques Research Articles

Global value chains and carbon emission efficiency: evidence from 30 provinces in China

ABSTRACT The severity of global environmental change is a growing issue, primarily as an obvious result of carbon dioxide emissions. This article aims to recognize the causal relationship between Global Value Chains (GVCs) and Carbon Emission Efficiency (CEE) by using 30 provinces from 2000 to 2014 in China. This study calculates the GVCs level in the provincial level considering general trade, process trade, and intermediate trade agents; Besides, a model for the slacks-based measure of super-efficiency in data envelopment analysis (SBM-DEA) was used to measure the CEE. By applying fixed effect model techniques, our estimates reveal critical findings. First, we confirm the existence of the spatial-temporal evolution pattern of CEE in 30 provinces, showing an increased trend and noticeable east-west difference. Second, the econometric results suggest that the GVCs involvement is beneficiary for the CEE. Third, our results confirm that technological innovation and environmental regulation effects contribute to GVCs’ influence on CEE. These findings contribute to the formulation of appropriate carbon policies by the Chinese government, thereby advancing the objective of achieving carbon peaking by 2030 and carbon neutrality by 2050.

Influence of extended working hours and physical recovery on absenteeism in the footwear industry from a system dynamics model

Objectives. Work-related musculoskeletal disorders (WMSDs) are recurrent in the footwear industry, resulting in absenteeism. This study aimed to quantitatively analyze the influence of overtime work and physical recovery time on the occurrence of WMSD-related absenteeism using a system dynamics model. As ergonomic methods have limitations in quantitatively simulating the behavior of these relationships, the integration of computational modeling techniques has emerged as a methodological alternative to bridge this gap. Methods. An ergonomic work analysis (EWA) was developed in a production cell of a large company. A model of causal relationships (causal loop diagram) and a simulation model (flow and stock diagram) were then developed, where three scenarios for overtime and physical recovery time were analyzed. Results. Working an additional hour resulted in a 42% increase in physical overload, leading to 7.62 leave requests per year and 78.7 days of employee absenteeism. Increasing the physical recovery time by 15 min reduced the overload to 36.5%, resulting in 6.8 leave requests per year and 71.1 days of employee absenteeism. Conclusions. Properly managing excess workload and providing adequate physical recovery for professionals is necessary to mitigate the productivity impacts of absenteeism in the footwear industry.

Limited role of present-day onshore freshwater recharge in the emplacement of offshore freshened groundwater in the Canterbury Bight, New Zealand

ABSTRACT Offshore freshened groundwater (OFG) represents a significant, yet underexplored, component of the global freshwater system as it is found across various continental margins. In this study, a 3-D geological and groundwater model was developed for the Canterbury Plains and Bight (New Zealand) to assess the role of present-day onshore recharge in the emplacement of OFG. Topographic and bathymetric, seismic reflection and well data have been integrated to construct an onshore-offshore geological model. The facies property distribution and associated hydrodynamic parameters were determined using stochastic modelling techniques. The geological reconstruction was imported within a variable density groundwater model. Simulations, under transient regime, were run until equilibrium conditions between the involved aquifer portion and the adjacent ocean have been reached. Our results show that the geological model accurately captures the stratigraphic and sedimentary features of the area, and that onshore recharge at present contributes to OFG emplacement up to 15 km from the coast, which is equivalent to 25% of its maximum extent. Onshore recharge during sea-level lowstands is therefore the dominant OFG emplacement mechanism in the Canterbury Bight.

Compressive Properties and Energy Absorption Characteristics of Co-Continuous Interlocking PDMS/PLA Lattice Composites

Co-continuous interlocking lattice structures usually present superior compressive properties and energy absorption characteristics. In this study, co-continuous interlocking polydimethylsiloxane/polylactic acid (PDMS/PLA) lattice composites were designed with different strut diameters, and successfully manufactured by combining the fused deposition modeling (FDM) technique and the infiltration method. This fabrication method can realize the change and control of structure parameters. The effects of the strut diameter on the compressive properties and energy absorption behavior of PDMS/PLA lattice composites were investigated by using quasi-static compression tests. The compressive properties of the co-continuous interlocking PDMS/PLA lattice composites can be adjusted in a narrow density range by a linear correlation. The energy absorption density of the co-continuous interlocking PDMS/PLA lattice composites increases with the increase in the PLA strut diameter and presents a higher efficiency peak and wider plateau region. The PLA lattice acts as a skeleton and plays an important role in bearing the compressive load and in energy absorption. The indexes of the compressive properties/energy absorption characteristics and PLA volume fraction of co-continuous interlocking PDMS/PLA lattice composites show linear relationships in logarithmic coordinates. The effect of the PLA volume fraction increasing on the plateau stress is more sensitive than the compressive strength and energy absorption density.

Cognitive-Inspired Deep Learning Models for Aspect-Based Sentiment Analysis: A Retrospective Overview and Bibliometric Analysis

AbstractAs cognitive-inspired computation approaches, deep neural networks or deep learning (DL) models have played important roles in allowing machines to reach human-like performances in various complex cognitive tasks such as cognitive computation and sentiment analysis. This paper offers a thorough examination of the rapidly developing topic of DL-assisted aspect-based sentiment analysis (DL-ABSA), focusing on its increasing importance and implications for practice and research advancement. Leveraging bibliometric indicators, social network analysis, and topic modeling techniques, the study investigates four research questions: publication and citation trends, scientific collaborations, major themes and topics, and prospective research directions. The analysis reveals significant growth in DL-ABSA research output and impact, with notable contributions from diverse publication sources, institutions, and countries/regions. Collaborative networks between countries/regions, particularly between the USA and China, underscore global engagement in DL-ABSA research. Major themes such as syntax and structure analysis, neural networks for sequence modeling, and specific aspects and modalities in sentiment analysis emerge from the analysis, guiding future research endeavors. The study identifies prospective avenues for practitioners, emphasizing the strategic importance of syntax analysis, neural network methodologies, and domain-specific applications. Overall, this study contributes to the understanding of DL-ABSA research dynamics, providing a roadmap for practitioners and researchers to navigate the evolving landscape and drive innovations in DL-ABSA methodologies and applications.

Natural resource abundance, governance, and government expenditure: Empirical insights from environmental sustainability

AbstractThis study examines the quest for environmental sustainability in Africa by analyzing the roles of natural resource abundance, governance quality, and government expenditure. It explores the relationships between these variables, employing the N‐shaped hypothesis across 42 African countries from 1986 to 2020 grouped into resource‐rich and resource‐poor countries. Utilizing the Lewbel 2SLS modeling technique, the research evaluates how these factors interact and impact carbon and nitrous emissions in the region. The findings reveal distinct patterns: resource‐poor countries exhibit an N‐shaped relationship between natural resource abundance and emissions. In contrast, resource‐rich countries show such patterns between government expenditure and carbon emissions. Moreover, in resource‐rich countries, higher natural resource abundance, government expenditure, and governance effectiveness tend to increase carbon emissions but decrease nitrous emissions. Conversely, in resource‐poor economies, carbon emissions decrease with natural resource abundance and governance quality but increase with government expenditure and effectiveness. Additionally, regulatory quality positively correlates with nitrous emissions across all contexts. The study's insights offer valuable guidance for policymakers aiming to foster environmental sustainability, emphasizing tailored strategies based on the diverse impacts of natural resources, governance, and government spending across different economic contexts.

On the intrusiveness of phosphor thermometry for metal surface temperature measurements in reciprocating engines: An experimental and heat conduction modeling study

Abstract Lifetime-based phosphor thermometry has been applied in a wide variety of surface temperature measurement applications due to its relative ease of implementation and robustness to background interference when compared to other optical temperature measurement methods. It is often assumed that the technique is minimally intrusive if the thickness of the applied phosphor coating is < 20 µm. To evaluate this assumption, high-speed phosphor surface temperature and thermocouple measurements were performed on 4140 steel substrates installed in the cylinder head of an optically-accessible internal-combustion engine for four operating conditions. For phosphor thermometry measurements, four substrates were studied, each coated with a phosphor layer of different thickness ranging between 6 µm and 47 µm. The phosphor thermometry measured temperature swings during combustion were shown to be heavily impacted by the presence of the phosphor coatings, increasing by roughly a factor of 2 - 2.5 when increasing the thickness from 6 µm to 30 µm. A technique was implemented which utilizes the temperature data in combination with a heat conduction model to provide estimates of the temperature swing and heat transfer flux in the absence of the phosphor coating. It was shown that even the 6 µm phosphor coating could lead to an order of magnitude increase in the temperature swing relative to the uncoated 4140 steel substrate. Despite the intrusiveness of phosphor thermometry for the surface temperature measurements, reasonable agreement was demonstrated between heat flux estimates determined with the heat transfer modeling technique and those deduced from temperature-swing measurements using two different high-speed thermocouples. The results indicate that phosphor surface thermometry can be a reliable surface temperature and heat flux diagnostic for transient high heat flux environments, as long as proper care is taken to account for the impact of the phosphor layer on the measurement.

Non-linear turbine selection for an OWC wave energy converter

Turbine-induced damping is a critical parameter affecting the performance of oscillating water column (OWC) wave energy converters. Therefore, selecting the appropriate turbine-chamber combination is an essential step in their design. In this work, a methodology is developed to determine the optimum turbine diameter for a given chamber, i.e., the diameter which maximizes the pneumatic energy capture of the chamber under an extensive set of wave conditions—covering virtually the entire range of wave conditions relevant for wave energy exploitation. This novel approach combines physical and numerical modelling with dimensional analysis. Importantly, it results in a turbine diameter that enables the turbine to operate at maximum efficiency. Through the different modelling techniques applied, the methodology accounts for air compressibility effects and other non-linear effects. It is applicable to non-linear turbines, with the study focusing on the promising biradial turbine. The results indicate that using the proposed methodology to select the turbine diameter significantly improves the capture-width ratio of the OWC, with increases of up to 100% for individual sea states. Two turbine diameters were identified as appropriate for the proposed OWC chamber design, 1.1 m for low-energy sites, and 1.4 m for mid- and high-energy sites.

Demystifying youth’s play intention of multiplayer online mobile game: an UTAUT3 model perspective

Purpose The primary objective of this study is to identify and examine the effects of the various determinants of the unified theory of acceptance and use of technology (UTAUT3) model on multiplayer online mobile games (MPOMGs) adoption and actual play behaviour of young gamers. Design/methodology/approach The research used an online survey method to collect data from a sample of 685 Indian youth. The participants were selected using a convenience sampling procedure. Structural equation modelling technique was used to evaluate the sufficiency and structural relationship between the various dimensions of the UTAUT3 model in the context of MPOMG. Findings The findings of the study indicate that the dimensions of “Price Value” and “Facilitating Condition” did not show a significant relationship with the play intention of MPOMG among youth. However, the newly introduced dimension, “Personal Innovativeness,” was found to have a significant impact on predicting the play intention of MPOMG. Research limitations/implications This study was limited to young Indian gamers. Therefore, future study is needed to analyse across cultures and regions. Moreover, this study contributes to the existing scholarly literature on the implementation of a newly established technological framework, namely, UTAUT3, in the context of MPOMG research. Hence, this study offers a fresh viewpoint for comprehending the youth’s inclination towards MPOMG. Additionally, various determinants the affects the MPOMG adoption and play behaviour is highly relevant for industry managers and game developers to create MPOMG, that are more likely to attract and retain users, leading to increased levels of engagement and success. Originality/value UTAUT3 is a novel framework to determine the technology adoption in a different context. UTAUT3 model is still unexplored and adopted in MPOMG play intention research. Therefore, this study provides a novel perspective to understand the youth’s intention to play the MPOMG in the newly developed technology adoption model perspective.

Characterization, processing, and modeling of industrial recycled polyolefins

AbstractThis study aims to establish a systematic approach for characterizing recycled polyolefins of unknown composition, with a specific focus on predicting their performance in film extrusion. We explore various characterization techniques, including differential scanning calorimetry (DSC), Fourier‐transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and rheometry to assess their effectiveness in identifying the polyethylene (PE) fractions within polypropylene (PP) recyclates. By integrating experimental data with modeling techniques, we aim to provide insights into the predictive capabilities of these techniques in determining processing behaviors. The research highlights the superior fidelity of DSC in predicting the relative fraction and type of PE in a PP recyclate. FTIR is also identified as a high‐fidelity approach, albeit requiring application‐specific calibration. TGA, capillary, and oscillatory rheometry are recognized for their ability to distinguish between grades of recycled polyolefins but provide aggregate behaviors rather than detailed constituent information. 3D flow simulation of the cast film extrusion investigated the effect of the viscosity characterization method, non‐isothermal assumption, and process settings but could not fully replicate the observed variations in the cast film processing of two industrial polyolefins with similar melt flow rates and viscosity behaviors. This underscores the practical challenge of predicting processing issues prior to actual processing, necessitating reliance on reliable instrumentation suites and human expertise for diagnosing and remedying variations.Highlights Two industrial recycled polypropylene materials having similar melt flow rates exhibit drastically different cast film processing behaviors. DSC and FTIR provide reasonable approaches for identifying constituent materials. Modeling of the melt viscosities characterized by capillary and parallel plate rheology suggests that viscosity variations relative to the power‐law behavior assumed in the coat hanger die design is a predominant driver of cast film instabilities.

A bi-level model and heuristic techniques with various neighborhood strategies for covering interdiction problem with fortification

A bi-level model and heuristic techniques with various neighborhood strategies for covering interdiction problem with fortification

Theoretical Probability Distribution Model and Reduction Techniques Based on Interleaved DFT Spread for PAPR in Digital Sub-carrier Multiplexing System

Theoretical Probability Distribution Model and Reduction Techniques Based on Interleaved DFT Spread for PAPR in Digital Sub-carrier Multiplexing System

Tectonic geomorphology and paleoseismology of the Angelochori fault segment of the Anthemountas extensional detachment fault, Central Macedonia, Greece: Paleoseismic evidence from the 1677 CE earthquake

This study presents the results of a geomorphological and paleoseismological investigation on the Angelochori normal fault. This fault controls the southern boundary of the Anthemountas basin and constitutes the western segment of the Anthemountas extensional detachment fault (AEDF), a ∼48 km-long, E-W-trending, north-dipping low-angle normal fault in Central Macedonia, Greece. To assess the relative tectonic activity of the Angelochori fault and to determine the number, timing, and displacement of surface-faulting earthquakes, we conducted detailed field mapping and paleoseismological investigations. Our approach involved utilizing geomorphic indices, analyzing stratigraphic and structural relations, considering luminescence ages, and employing OxCal modeling techniques. The acquired data reveal, for the first time, the Middle-Late Holocene activity of the Anghelochori fault, providing constraints on the age of three strong (M > 6) surface-rupturing earthquakes over the last ∼7.7 ka. The youngest of these events aligns with the historical earthquake of the Anthemountas basin in 1677 CE. The observed minimum displacement per event ranges from 0.48 m to 0.65 m, consistent with a fault length estimated at about 24–28 km, suggesting an earthquake magnitude on the order of 6.6. The cumulative slip rate over the recorded period averages 0.21 ± 0.02 mm/a, with an average open recurrence interval of 2.6 ± 0.2 ka. Nonetheless, the displacement pattern displays alternating intervals of rapid slip at 0.60 ± 0.16 mm/a and slower slip at 0.08 ± 0.01 mm/a. Classified as Class 1, the Angelochori fault signifies an active tectonic structure posing a significant seismic hazard for the Thessaloniki metropolitan area.

Developing Theoretical Models for Atherosclerotic Lesions: A Methodological Approach Using Interdisciplinary Insights

Atherosclerosis, a leading cause of cardiovascular disease, necessitates advanced and innovative modeling techniques to better understand and predict plaque dynamics. The present work presents two distinct hypothetical models inspired by different research fields: the logistic map from chaos theory and Markov models from stochastic processes. The logistic map effectively models the nonlinear progression and sudden changes in plaque stability, reflecting the chaotic nature of atherosclerotic events. In contrast, Markov models, including traditional Markov chains, spatial Markov models, and Markov random fields, provide a probabilistic framework to assess plaque stability and transitions. Spatial Markov models, visualized through heatmaps, highlight the spatial distribution of transition probabilities, emphasizing local interactions and dependencies. Markov random fields incorporate complex spatial interactions, inspired by advances in physics and computational biology, but present challenges in parameter estimation and computational complexity. While these hypothetical models offer promising insights, they require rigorous validation with real-world data to confirm their accuracy and applicability. This study underscores the importance of interdisciplinary approaches in developing theoretical models for atherosclerotic plaques.

A Data Analytics and Machine Learning Approach to Develop a Technology Roadmap for Next-Generation Logistics Utilizing Underground Systems

The increasing density of urban populations has spurred interest in utilizing underground space. Underground logistics systems (ULS) are gaining traction due to their effective utilization of this space to enhance urban spatial efficiency. However, research on technological advancements in related fields remains limited. To address this gap, we applied a data-driven approach using patent data related to the ULS to develop a technology roadmap for the field. We employed Latent Dirichlet Allocation (LDA), a machine learning-based topic modeling technique, to categorize and identify six specific technology areas within the ULS domain. Subsequently, we conducted portfolio analytics to pinpoint technology areas with high technological value and to identify the major patent applicants in these areas. Finally, we assessed the technology market potential by mapping the technology life cycle for the identified high-value areas. Among the six technology areas identified, Topic 1 (Underground Material Handling System) and Topic 4 (Underground Transportation System) showed significant patent activity from companies and research institutions in China, the United States, South Korea, and Germany compared to other countries. These areas have the top 10 patent applicants, accounting for 20.8% and 13.6% of all patent applications, respectively. Additionally, technology life cycle analytics revealed a growth trajectory for these identified areas, indicating their rapid expansion and high innovation potential. This study provides a data-driven methodology to develop a technology roadmap that offers valuable insights for researchers, engineers, and policymakers in the ULS industry and supports informed decision-making regarding the field’s future direction.

Discrete Choice Model Applications for Air Passenger Airport Choices: A Literature Review

Airport development is a critical factor for regional growth, improving connectivity, and stimulating economic growth. Considering the complexity of planning and policy making in this area, multiple models and frameworks have been introduced to support decision-making processes. Among these, Discrete Choice Models (DCM) stand out for their capacity to project market flows, assess the validity and benefits of implementing airport modifications, tailor policies, improve the operations’ service level, and boost revenues. Given their extensive use and importance, a thorough review of DCM applications within the context of air transportation is both timely and necessary. This review organizes and evaluates the use of DCMs in air transport research. Both descriptive and predictive applications of DCMs are analyzed, focusing on choices related to airports and related levels, such as access mode and airline decisions. Each reviewed study is classified based on the type of model used, application context, data characteristics, employed variables, and methodological contributions. Through this analysis, six prevailing gaps are identified in the current state of DCM application in air transportation: improve data quality, enhance models with detailed trip and passenger information, explore advanced modeling techniques, incorporate general correlation and substitution structures, consider non-compensatory decision-making processes, and extend applications to new geographic and temporal contexts.

Forecasting of coronavirus active cases by utilizing logistic growth model and fuzzy time series techniques

Coronavirus has long been considered a global epidemic. It caused the deaths of nearly 7.01 million individuals and caused an economic downturn. The number of verified coronavirus cases is increasing daily, putting the whole human race at danger and putting strain on medical experts to eradicate the disease as rapidly as possible. As a consequence, it is vital to predict the upcoming coronavirus positive patients in order to plan actions in the future. Furthermore, it has been discovered all across the globe that asymptomatic coronavirus patients play a significant part in the disease’s transmission. This prompted us to incorporate similar examples in order to accurately forecast trends. A typical strategy for analysing the rate of pandemic infection is to use time-series forecasting technique. This would assist us in developing better decision support systems. To anticipate COVID-19 active cases for a few countries, we recommended a hybrid model utilizing a fuzzy time series (FTS) model mixed with a non-linear growth model. The coronavirus positive case outbreak has been evaluated for Italy, Brazil, India, Germany, Pakistan, and Myanmar through June 5, 2020 in phase-1, and January 15, 2022 in phase-2, and forecasts active cases for the next 26 and 14 days respectively. The proposed framework fitting effect outperforms individual logistic growth and the fuzzy time series techniques, with R-scores of 0.9992 in phase-1 and 0.9784 in phase-2. The proposed model provided in this article may be utilised to comprehend a country’s epidemic pattern and assist the government in developing better effective interventions.

Leveraging Technology Innovations to Boost Africa’s Industrialisation

The study employed using dynamic panel modelling technique to examine the effects of technology innovations on industrialization in Africa using annual panel data from 2011 to 2022. The findings show that per capita income, total national reserves, and remittances positively affect industrialisation processes in Africa. With regards to technology innovations, the findings show that technological innovations positively influence industrialisation in Africa. The major policy implication is that Africa’s industrialisation could be realised by targeting technology innovation in the continent. The study therefore recommends that African countries should increase investments in innovation, strengthen and build institutions that support technology innovation.

Graph-theoretic modeling reveals connectivity hotspots for herbivorous reef fishes in a restored tropical island system

ContextSeascape connectivity refers to how the spatial configuration of marine habitats facilitates or hinders the movement of organisms, nutrients, materials or energy. Predicting and ranking potential connectivity among habitat patches for coral reef fishes helps to understand how reef fishes could utilize and connect multiple habitat types through the flow of nutrients, energy and biomass across the wider seascape during foraging movements.ObjectivesTo advance a spatially explicit understanding of connectivity linkages within a tropical atoll system by modeling, mapping and quantifying potential seascape connectivity for two locally abundant herbivorous reef fish species, the parrotfish, Chlorurus spilurus (pahoro hohoni or pa’ati pa’apa’a auahi), and the surgeonfish, Acanthurus triostegus (manini).MethodsWe applied a two-step modeling approach by first mapping habitat suitability for the focal species. A graph-theoretic modeling technique was then applied to model and measure the contribution of benthic habitat patches to species-specific potential connectivity within the seascape.ResultsHabitat suitability was higher and less fragmented for C. spilurus than for A. triostegus. Potential ecological connectivity estimates for C. spilurus were higher across the entire seascape, with differences between species likely driven by local-scale benthic habitat patch configuration and species home ranges. Hotspots of ecological connectivity across the atoll were mapped for both species.ConclusionsDespite advances in the application of graph-theoretic techniques in the coastal environment, few marine conservation and restoration measures currently integrate spatial information on ecological connectivity. This two-step spatial modeling approach holds great potential for rapid application of connectivity modeling at multiple spatial scales, which may predict ecological responses to conservation actions including active habitat restoration.

Semi-analytical modelling of realistic tire-pavement contact: an analysis of pavement surface cracking damage under critical driving conditions

This paper aims to evaluate the surface cracking phenomenon on a flexible pavement subjected to diverse vehicle running conditions. Top-down cracking initiation is addressed through a continuum damage framework coupled with a semi-analytical model of tire-pavement rolling contact. The acceleration, braking and cornering scenarios were selected to represent the effect of combining normal and tangential loads. The differences between these loading cases are accurately computed by simulating the realistic contact stresses on the pavement surface through semi-analytical modelling. The computational cost of this modelling technique is reduced, allowing it to be used in industrial applications. It is assumed that tires and pavement are linear elastic multilayered half-spaces. The critical locations of the cracks are identified for each loading scenario and the cracking directions are discussed. This study emphasises the influence of driving conditions on premature pavement cracking which is not typically considered in the current pavement design guides. It is shown that a standard axle load may cause about 9 times more surface damage on a circular intersection compared to a straight-line pavement section.