Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (38)

Search Parameters:
Keywords = Fuller distribution

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
22 pages, 4484 KiB  
Article
Automated Parcel Locker Configuration Using Discrete Event Simulation
by Eugen Rosca, Floriana Cristina Oprea, Anamaria Ilie, Stefan Burciu and Florin Rusca
Systems 2025, 13(7), 613; https://doi.org/10.3390/systems13070613 - 20 Jul 2025
Viewed by 505
Abstract
Automated parcel lockers (APLs) are transforming urban last-mile delivery by reducing failed distributions, decoupling delivery from recipient availability, optimizing carrier routes, reducing carbon foot-print and mitigating traffic congestion. The paper investigates the optimal design of APLs systems under stochastic demand and operational constraints, [...] Read more.
Automated parcel lockers (APLs) are transforming urban last-mile delivery by reducing failed distributions, decoupling delivery from recipient availability, optimizing carrier routes, reducing carbon foot-print and mitigating traffic congestion. The paper investigates the optimal design of APLs systems under stochastic demand and operational constraints, formulating the problem as a resource allocation optimization with service-level guarantees. We proposed a data-driven discrete-event simulation (DES) model implemented in ARENA to (i) determine optimal locker configurations that ensure customer satisfaction under stochastic parcel arrivals and dwell times, (ii) examine utilization patterns and spatial allocation to enhance system operational efficiency, and (iii) characterize inventory dynamics of undelivered parcels and evaluate system resilience. The results show that the configuration of locker types significantly influences the system’s ability to maintain high customers service levels. While flexibility in locker allocation helps manage excess demand in some configurations, it may also create resource competition among parcel types. The heterogeneity of locker utilization gradients underscores that optimal APLs configurations must balance locker units with their size-dependent functional interdependencies. The Dickey–Fuller GLS test further validates that postponed parcels exhibit stationary inventory dynamics, ensuring scalability for logistics operators. As a theoretical contribution, the paper demonstrates how DES combined with time-series econometrics can address APLs capacity planning in city logistics. For practitioners, the study provides a decision-support framework for locker sizing, emphasizing cost–service trade-offs. Full article
(This article belongs to the Special Issue Modelling and Simulation of Transportation Systems)
Show Figures

Figure 1

17 pages, 594 KiB  
Article
Environmental Degradation, Renewable Energy, and Non-Renewable Energy Consumption in Saudi Arabia: An ARDL Bound Testing Approach
by Kais Ben-Ahmed, Sahar J. Melebary and Turki K. Bawazir
Sustainability 2025, 17(11), 4970; https://doi.org/10.3390/su17114970 - 28 May 2025
Viewed by 616
Abstract
Saudi Arabia’s Vision 2030 is closely tied to CO2 emissions and energy consumption issues. This initiative aims to modernize the country’s economy, diversify its energy sources, and enhance sustainability. This paper examines the relationships among CO2 emissions, Renewable Energy Consumption (REC), [...] Read more.
Saudi Arabia’s Vision 2030 is closely tied to CO2 emissions and energy consumption issues. This initiative aims to modernize the country’s economy, diversify its energy sources, and enhance sustainability. This paper examines the relationships among CO2 emissions, Renewable Energy Consumption (REC), and Non-Renewable Energy Consumption (NREC) in Saudi Arabia, from 1990 to 2019. To assess the stationarity of the panel time-series data, the Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests were initially used. Given that the data exhibited a mixed order of integration, the Autoregressive Distributed Lag (ARDL) framework was employed. Three different lag selection criteria were applied for cointegration, using CO2 emissions as the dependent variable. Additionally, the direction and significance of causality were analyzed within the ARDL framework. Robust tests were conducted to evaluate the generalizability of the study’s findings. We demonstrated a significant long-term relationship between climate change and both REC and NREC in Saudi Arabia. The findings indicate that in the long run, a 1% increase in REC leads to a 0.21% decrease in CO2 emissions. Furthermore, a 1% increase in NREC corresponds to a substantial 53.4% reduction in CO2 emissions. Finally, policy recommendations were proposed in alignment with Saudi Arabia’s Vision 2030. Full article
Show Figures

Figure 1

53 pages, 1551 KiB  
Article
From Crisis to Algorithm: Credit Delinquency Prediction in Peru Under Critical External Factors Using Machine Learning
by Jomark Noriega, Luis Rivera, Jorge Castañeda and José Herrera
Data 2025, 10(5), 63; https://doi.org/10.3390/data10050063 - 28 Apr 2025
Viewed by 808
Abstract
Robust credit risk prediction in emerging economies increasingly demands the integration of external factors (EFs) beyond borrowers’ control. This study introduces a scenario-based methodology to incorporate EF—namely COVID-19 severity (mortality and confirmed cases), climate anomalies (temperature deviations, weather-induced road blockages), and social unrest—into [...] Read more.
Robust credit risk prediction in emerging economies increasingly demands the integration of external factors (EFs) beyond borrowers’ control. This study introduces a scenario-based methodology to incorporate EF—namely COVID-19 severity (mortality and confirmed cases), climate anomalies (temperature deviations, weather-induced road blockages), and social unrest—into machine learning (ML) models for credit delinquency prediction. The approach is grounded in a CRISP-DM framework, combining stationarity testing (Dickey–Fuller), causality analysis (Granger), and post hoc explainability (SHAP, LIME), along with performance evaluation via AUC, ACC, KS, and F1 metrics. The empirical analysis uses nearly 8.2 million records compiled from multiple sources, including 367,000 credit operations granted to individuals and microbusiness owners by a regulated Peruvian financial institution (FMOD) between January 2020 and September 2023. These data also include time series of delinquency by economic activity, external factor indicators (e.g., mortality, climate disruptions, and protest events), and their dynamic interactions assessed through Granger causality to evaluate both the intensity and propagation of external shocks. The results confirm that EF inclusion significantly enhances model performance and robustness. Time-lagged mortality (COVID MOV) emerges as the most powerful single predictor of delinquency, while compound crises (climate and unrest) further intensify default risk—particularly in portfolios without public support. Among the evaluated models, CNN and XGB consistently demonstrate superior adaptability, defined as their ability to maintain strong predictive performance across diverse stress scenarios—including pandemic, climate, and unrest contexts—and to dynamically adjust to varying input distributions and portfolio conditions. Post hoc analyses reveal that EF effects dynamically interact with borrower income, indebtedness, and behavioral traits. This study provides a scalable, explainable framework for integrating systemic shocks into credit risk modeling. The findings contribute to more informed, adaptive, and transparent lending decisions in volatile economic contexts, relevant to financial institutions, regulators, and risk practitioners in emerging markets. Full article
(This article belongs to the Section Information Systems and Data Management)
Show Figures

Figure 1

15 pages, 3380 KiB  
Article
Study on the Effect of Coal Gangue Particle Size Distribution for the Preparation of Kaolin by Shaking Table Separation
by Xinkai Hou, Wenjuan Ji, Hao Li, Xiaoqi Fan and Ying Wang
Coatings 2025, 15(4), 430; https://doi.org/10.3390/coatings15040430 - 6 Apr 2025
Viewed by 566
Abstract
The presence of pyrite in coal gangue significantly degrades the performance of its prepared kaolin in ceramic and coating applications. Implementing separation techniques to remove pyrite can markedly enhance the quality of kaolin products. However, there is no research on the effect of [...] Read more.
The presence of pyrite in coal gangue significantly degrades the performance of its prepared kaolin in ceramic and coating applications. Implementing separation techniques to remove pyrite can markedly enhance the quality of kaolin products. However, there is no research on the effect of material particle size distribution on the separation effect in the current study on shaking table separation. For this reason, the coal gangue was crushed to different maximum particle sizes in this study, and its particle size distribution was fitted and analyzed. Based on the fitting results, the Rosin–Rammler–Sperling–Bennet (RRSB) distribution with a uniformity coefficient n of 0.74 was used to study the influence of the characteristic particle size de on the separation effect. Fuller distribution with distribution modulus q of 0.45 was also used to study the impact of maximum particle size dmax. The results showed that the Fuller distribution reduced the contents of SO3 and Fe2O3 by 30.85% and 25.71%, respectively, compared with the raw materials. In comparison, the RRSB distribution reduced the contents of SO3 and Fe2O3 by 41.01% and 30.85%, respectively, indicating that the separation effect of the RRSB distribution was better than that of the Fuller distribution. In addition, when the characteristic particle size de of the RRSB distribution was 37–42 μm, the content of SO3 and Fe2O3 in the tailings varied very little, and the separation effect was stable. This study demonstrates that the particle size distribution significantly influences the separation efficiency of the shaking table, providing a novel idea for enhancing shaking table separation processes. Future studies may further explore the effect of another parameter or two-parameter coupling of RRSB distribution and Fuller distribution on the separation effect of the shaking table. Full article
(This article belongs to the Special Issue Ceramic and Glass Material Coatings)
Show Figures

Figure 1

19 pages, 13346 KiB  
Article
Study on Fluctuating Wind Characteristics and Non-Stationarity at U-Shaped Canyon Bridge Site
by Zhe Sun, Zhuoyi Zou, Jiaying Wang, Xue Zhao and Feng Wang
Appl. Sci. 2025, 15(3), 1482; https://doi.org/10.3390/app15031482 - 31 Jan 2025
Viewed by 815
Abstract
To investigate the non-stationary characteristics of the wind field at the U-shaped canyon bridge site and its impact on fluctuating wind characteristics, a wind observation tower was installed near a cable-stayed bridge. The Augmented Dickey–Fuller (ADF) test was employed to assess the stationarity [...] Read more.
To investigate the non-stationary characteristics of the wind field at the U-shaped canyon bridge site and its impact on fluctuating wind characteristics, a wind observation tower was installed near a cable-stayed bridge. The Augmented Dickey–Fuller (ADF) test was employed to assess the stationarity of wind speed series, while the discrete wavelet transform (DWT) was applied to reconstruct the time-varying mean wind and analyze its effect on fluctuating wind characteristics. Results indicate that wind speeds in this region exhibit bimodal distribution characteristics, with the Weibull-Gamma mixed distribution model providing the best fit. The proportion of non-stationary samples increases with height. Autocorrelation function (ACF), partial autocorrelation function (PACF) tests, and power spectral density (PSD) analysis determined the optimal wavelet decomposition level for wind speed in this region. Analysis of non-stationary samples using db10 wavelet reconstruction reveals that the stationary wind speed model overestimates turbulence intensity but underestimates the turbulence integral scale. The downwind spectrum deviates from the Kaimal spectrum in both low- and high-frequency bands, whereas the vertical spectrum aligns well with the Panofsky spectrum. The findings demonstrate that the wavelet reconstruction method more accurately captures fluctuating wind characteristics under the complex terrain conditions of this canyon area. Full article
(This article belongs to the Section Civil Engineering)
Show Figures

Figure 1

24 pages, 2007 KiB  
Article
Greening the Gulf: A Deep-Dive into the Synergy Between Natural Resources, Institutional Quality, Foreign Direct Investment, and Pathways to Environmental Sustainability
by Feng Qin and Ali Imran
Sustainability 2024, 16(24), 11250; https://doi.org/10.3390/su162411250 - 22 Dec 2024
Cited by 3 | Viewed by 1190
Abstract
Environmental quality is a global concern, especially in Gulf Cooperation Council (GCC) countries where abundant mineral resources, economic growth, and globalization have strained the environment through urbanization and resource exploitation. This study examines the impact of globalization (GLOL), urbanization (URBN), natural resource extraction [...] Read more.
Environmental quality is a global concern, especially in Gulf Cooperation Council (GCC) countries where abundant mineral resources, economic growth, and globalization have strained the environment through urbanization and resource exploitation. This study examines the impact of globalization (GLOL), urbanization (URBN), natural resource extraction (NRER), institutional quality (INSQ), and foreign direct investment (FDI) on environmental quality in GCC countries from 1999 to 2021. Cross-sectional dependence (CSD) was assessed using the Lagrange Multiplier (LM) and cross-dependence (CD) techniques, and stationarity was confirmed with the Levin–Lin–Chu test. The Augmented Dickey–Fuller (ADF) co-integration test verified long-term relationships, and Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) methodology assessed short- and long-term effects. Our findings show that FDI, GLOL, and INSQ have negative long-term impacts on environmental quality, while NRER and URBN are beneficial. In the short term, FDI and INSQ improve green quality, while GLOL, URBN, and NRER have detrimental effects. Policy recommendations include discouraging FDI in non-renewable projects, promoting sustainable FDI, addressing income inequality to improve environmental quality, and investing in urban development to reduce ecological footprints (ECFTs) and enhance environmental quality in GCC countries. Full article
Show Figures

Figure 1

12 pages, 1013 KiB  
Article
Investigating the Impact of Energy Consumption and Economic Activities on CO2 Emissions from Transport in Saudi Arabia
by Abdullah Al Shammre
Energies 2024, 17(17), 4448; https://doi.org/10.3390/en17174448 - 5 Sep 2024
Cited by 2 | Viewed by 1246
Abstract
This study examines the relationships between CO2 emissions, gross domestic product (GDP), financial development, energy export, sustainable power, unsustainable power depletion, and commercial growth in the Kingdom of Saudi Arabia (KSA) from 1990 to 2022 by using the auto-regressive distributed lag (ARDL) [...] Read more.
This study examines the relationships between CO2 emissions, gross domestic product (GDP), financial development, energy export, sustainable power, unsustainable power depletion, and commercial growth in the Kingdom of Saudi Arabia (KSA) from 1990 to 2022 by using the auto-regressive distributed lag (ARDL) approach and the vector error correction model (VECM) approach. In the first step, we have used tests such as the augmented Dickey–Fuller (ADF) test and the Dickey–Fuller generalized least squares (DF-GLS) to capture the order of integration of the variables, and the results show that all the variables are stationary in regard to the first difference. In the second step, we have applied the examination of bounds in order to validate the presence of long-term cointegration relationships between the variables. The results of the ARDL approach show that financial development, sustainable energy, and commercial openness have a negative impact on CO2 emissions. However, GDP, energy export, and unsustainable energy lead to an increase in environmental degradation. Finally, the Granger causality test shows mixed causality relationship among the variables. Accordingly, governments should encourage the development and use of sustainable energy alternatives, such as solar power, wind power, and hydroelectric power, through incentives and subsidies, in addition to conducting new research concerning the topic and starting new initiatives. Protecting and expanding green areas is crucial to mitigate CO2 emissions, and strategies for transitioning to cleaner energy alternatives should be developed. Additionally, facilitating the transfer of sustainable energy technologies and promoting collaboration in research and development can accelerate the adoption of clean energy solutions. These policy actions can contribute to reducing CO2 levels, as well as promoting sustainable energy practices in the country. Full article
(This article belongs to the Section C: Energy Economics and Policy)
Show Figures

Figure 1

16 pages, 2682 KiB  
Article
Morphological and Pigment Responses to Far-Red and Photosynthetically Active Radiation in an Olive Cultivar Suitable for Super-High-Density Orchards
by Federico J. Ladux, Carina V. González, Eduardo R. Trentacoste, Peter S. Searles and M. Cecilia Rousseaux
Plants 2024, 13(13), 1822; https://doi.org/10.3390/plants13131822 - 2 Jul 2024
Cited by 1 | Viewed by 1411
Abstract
Plant density is increasing in modern olive orchards to improve yields and facilitate mechanical harvesting. However, greater density can reduce light quantity and modify its quality. The objective was to evaluate plant morphology, biomass, and photosynthetic pigments under different red/far-red ratios and photosynthetically [...] Read more.
Plant density is increasing in modern olive orchards to improve yields and facilitate mechanical harvesting. However, greater density can reduce light quantity and modify its quality. The objective was to evaluate plant morphology, biomass, and photosynthetic pigments under different red/far-red ratios and photosynthetically active radiation (PAR) combinations in an olive cultivar common to super-high-density orchards. In a greenhouse, young olive trees (cv. Arbequina) were exposed to low (L) or high (H) PAR with or without lateral FR supplementation (L+FR, L-FR, H+FR, H-FR) using neutral-density shade cloth and FR light-emitting diode (LED) modules. Total plant and individual organ biomass were much lower in plants under low PAR than under high PAR, with no response to +FR supplementation. In contrast, several plant morphological traits, such as main stem elongation, individual leaf area, and leaf angle, did respond to both low PAR and +FR. Total chlorophyll content decreased with +FR when PAR was low, but not when PAR was high (i.e., a significant FR*PAR interaction). When evaluating numerous plant traits together, a greater response to +FR under low PAR than under high PAR appeared to occur. These findings suggest that consideration of light quality in addition to quantity facilitates a fuller understanding of olive tree responses to a light environment. The +FR responses found here could lead to changes in hedgerow architecture and light distribution within the hedgerow. Full article
Show Figures

Figure 1

26 pages, 5452 KiB  
Article
The Impact of Economic Growth on the Ecological Environment and Renewable Energy Production: Evidence from Azerbaijan and Hungary
by Sugra Ingilab Humbatova, Nargiz Hajiyeva, Monika Garai Fodor, Kiran Sood and Simon Grima
J. Risk Financial Manag. 2024, 17(7), 275; https://doi.org/10.3390/jrfm17070275 - 30 Jun 2024
Cited by 7 | Viewed by 2725
Abstract
This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic [...] Read more.
This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic growth on the ecological environment and renewable energy production. Due to limitations in the general dataset, the study considers the period of 1997–2022 for CO2 emissions causing environmental pollution, 2007–2022 for renewable energy production in Azerbaijan, and 2000–2021 for the same in Hungary. Information regarding wind and solar energy in Azerbaijan has been available since 2013. Temporal sequences have been utilised in the research, employing Augmented Dickey–Fuller and Phillips–Perron (PP) unit root tests to examine the stationarity of the time series. An Autoregressive Distributed Lag (ARDL) model has been constructed, and the credibility of the model has been verified using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) models. The findings reveal that in Azerbaijan, the long-term impact of economic growth on hydro-energy has been negative, while dependence on biomass and waste has been insignificant but positive. The influence on wind and solar energy production has also been negative and insignificant, akin to hydro-energy production. However, energy supply from renewable sources has been positively affected by the aggregate indicator of economic growth, albeit insignificantly. The impact of economic growth on carbon dioxide has been significant in two magnitudes, whereas in other cases, it has been insignificant but positive. In Hungary, economic growth has positively affected renewable energy production. However, the impact on carbon dioxide has been negative, meaning that this indicator has decreased as economic growth has increased. The study concludes that the impact of economic growth on indicators of both countries has been more effective in Hungary, which can be attributed to economic development. Full article
(This article belongs to the Section Energy and Environment: Economics, Finance and Policy)
Show Figures

Figure 1

17 pages, 3890 KiB  
Article
Study on the Influence of Particle Size Distribution on the Separation of Pyrite from Coal Gangue by Jigging
by Xinkai Hou, Zhentong Xi, Xiangfeng Wang and Wenjuan Ji
Coatings 2024, 14(5), 610; https://doi.org/10.3390/coatings14050610 - 11 May 2024
Cited by 2 | Viewed by 1396
Abstract
The presence of pyrite poses a significant impediment to the comprehensive utilization of coal gangue, which is a prevalent solid waste in industrial production. However, the current efficacy of jig separation for pyrite in fine-grade coal gangue remains unsatisfactory. To investigate the influence [...] Read more.
The presence of pyrite poses a significant impediment to the comprehensive utilization of coal gangue, which is a prevalent solid waste in industrial production. However, the current efficacy of jig separation for pyrite in fine-grade coal gangue remains unsatisfactory. To investigate the influence of particle size distribution on the jig separation of pyrite in fine-grade coal gangue, the raw material was crushed to less than 2 mm using a jaw crusher and subsequently sieved to obtain its particle size distribution curve. Upon fitting the curve, it was observed that it tends towards the Rosin-Rammler (RRSB) and Fuller distributions. Leveraging these two-parameter distribution curves, adjustments were made to determine the mass within each particle size range before conducting thorough mixing followed by jig separation. The results indicate that for fine-grade gangue particles smaller than 2 mm, the RRSB distribution with a uniformity coefficient of n = 0.85 exhibits the most effective separation, although it is comparable to the separation achieved using the size distribution of raw ore. On the other hand, employing the Fuller distribution with modulus of distribution q = 1.5 yields superior separation performance. In comparison to the raw ore, the concentrate shows an increase in sulfur (S) and iron (Fe) content by factors of 3.4 and 2.4, respectively. Furthermore, compared to the RRSB distribution, there is an increase in S and Fe content by 1.91% and 2.30%, respectively; the contents of S and Fe in tailings is 0.71% and 2.72%, which can be directly used as raw materials for coating materials. Therefore, for fine-grade coal gangue particles, jigging under the Fuller distribution demonstrates better effectiveness than under the RRSB distribution. Full article
(This article belongs to the Section Ceramic Coatings and Engineering Technology)
Show Figures

Figure 1

24 pages, 5387 KiB  
Article
Method for the Statistical Analysis of the Signals Generated by an Acquisition Card for Pulse Measurement
by Yaquelin Verenice Pantoja-Pacheco and Javier Yáñez-Mendiola
Mathematics 2024, 12(6), 923; https://doi.org/10.3390/math12060923 - 21 Mar 2024
Cited by 3 | Viewed by 1575
Abstract
This article shows a method for the statistical analysis of signals. Firstly, this method was applied to analyze the processing of signs generated by an acquisition card for pulse measurement using the synchronous demodulation method. The application of the method allowed the study [...] Read more.
This article shows a method for the statistical analysis of signals. Firstly, this method was applied to analyze the processing of signs generated by an acquisition card for pulse measurement using the synchronous demodulation method. The application of the method allowed the study of each signal consisting of a descriptive statistical analysis, followed by the analysis of the trend and dynamics of the movement using the augmented Dickey–Fuller test and Hurst exponent, respectively. Secondarily, the method presented here supported the comparison between the pulse signals obtained by synchronous demodulation and plethysmography methods. In addition, the residuals from the pulse comparison of both methods were analyzed. To quantify the differences between the signals, these were compared using the mean-squared error, the root-mean-square error, the mean absolute error, the mean error, the mean absolute percentage error, and the mean percentage error. After this research, it was possible to analyze the signals knowing characteristics such as the following: the presence of normal, exponential, lognormal, and uniform distributions, stationary trend, and dynamic movement anti-persistent. The novelty that this article proposes is the use of concepts traditionally used in the study of time series and models of demand administration, now focused on supporting improvements over the different stages of design and conceptualization of signal processing devices. Full article
(This article belongs to the Special Issue Data-Driven Statistical Methods)
Show Figures

Figure 1

42 pages, 5213 KiB  
Article
Quantitative Modeling of Financial Contagion: Unraveling Market Dynamics and Bubble Detection Mechanisms
by Ionuț Nica, Ștefan Ionescu, Camelia Delcea and Nora Chiriță
Risks 2024, 12(2), 36; https://doi.org/10.3390/risks12020036 - 8 Feb 2024
Cited by 5 | Viewed by 4168
Abstract
This study explored the complex interplay and potential risk of financial contagion across major financial indices, focusing on the Bucharest Exchange Trading Investment Funds Index (BET-FI), along with global indices like the S&P 500, Nasdaq Composite (IXIC), and Dow Jones Industrial Average (DJIA). [...] Read more.
This study explored the complex interplay and potential risk of financial contagion across major financial indices, focusing on the Bucharest Exchange Trading Investment Funds Index (BET-FI), along with global indices like the S&P 500, Nasdaq Composite (IXIC), and Dow Jones Industrial Average (DJIA). Our analysis covered an extensive period from 2012 to 2023, with a particular emphasis on Romania’s financial market. We employed Autoregressive Distributed Lag (ARDL) modeling to examine the interrelations among these indices, treating the BET-FI index as our primary variable. Our research also integrated Exponential Curve Fitting (EXCF) and Generalized Supremum Augmented Dickey–Fuller (GSADF) models to identify and scrutinize potential price bubbles in these indices. We analyzed moments of high volatility and deviations from typical market trends, influenced by diverse factors like government policies, presidential elections, tech sector performance, the COVID-19 pandemic, and geopolitical tensions, specifically the Russia–Ukraine conflict. The ARDL model revealed a stable long-term relationship among the variables, indicating their interconnectedness. Our study also highlights the significance of short-term market shifts leading to long-term equilibrium, as shown in the Error Correction Model (ECM). This suggests the existence of contagion effects, where small, short-term incidents can trigger long-term, domino-like impacts on the financial markets. Furthermore, our variance decomposition examined the evolving contributions of different factors over time, shedding light on their changing interactions and impact. The Cholesky factors demonstrated the interdependence between indices, essential for understanding financial contagion effects. Our research thus uncovered the nuanced dynamics of financial contagion, offering insights into market variations, the effectiveness of our models, and strategies for detecting financial bubbles. This study contributes valuable knowledge to the academic field and offers practical insights for investors in turbulent financial environments. Full article
Show Figures

Figure 1

15 pages, 2038 KiB  
Article
Multi-Objective Taguchi Optimization of Cement Concrete Incorporating Recycled Mixed Plastic Fine Aggregate Using Modified Fuller’s Equation
by Kevin Jia Le Lee and Sook Fun Wong
Buildings 2023, 13(4), 893; https://doi.org/10.3390/buildings13040893 - 28 Mar 2023
Cited by 6 | Viewed by 2228
Abstract
Motivated by the multiple benefits of recycling plastic ingredients in cementitious materials, the present study focuses on the design of sustainable cement concrete incorporating recycled mixed plastic fine aggregate (MPFA) as a partial replacement of natural sand (NS). The MPFA produced in this [...] Read more.
Motivated by the multiple benefits of recycling plastic ingredients in cementitious materials, the present study focuses on the design of sustainable cement concrete incorporating recycled mixed plastic fine aggregate (MPFA) as a partial replacement of natural sand (NS). The MPFA produced in this work is composed of a combination of polymer types with similar concoctions to those observed in the postconsumer waste streams. This study approach is vastly different from past reported studies on the use of sorted, highly purified single-type recycled plastic aggregate in cement concrete. A multi-criteria decision-making technique, Best-Worst Method (BWM), was integrated with the Taguchi method to maximize the quality of MPFA concrete based on the Fuller–Thompson theory. More specifically, an L9 (34) Taguchi orthogonal array with four three-level design factors was adopted to optimize the fresh, durability, and mechanical properties of MPFA concrete. The results showed that MPFA concrete produced with 400 kg/m3 cement content, 0.43 water/cement ratio, 0.43 fine aggregate/total aggregate ratio, and 10 vol% MPFA content exhibited the highest quality. Findings from the present work also revealed that MPFA concrete produced with tailored particle size distribution of MPFA NS fine aggregate system achieved superior, if not comparable, qualities to those of conventional concrete. Full article
(This article belongs to the Special Issue Sustainable Cement-Based Materials)
Show Figures

Figure 1

20 pages, 10238 KiB  
Article
Experimental Study on the Size of Rock Fragments Ejected from Boreholes Drilled in Coal Mine Roadway Floors
by Mengxiong Fu, Shuaishuai Huang, Shaowei Liu and Housheng Jia
Minerals 2023, 13(3), 392; https://doi.org/10.3390/min13030392 - 10 Mar 2023
Cited by 2 | Viewed by 1902
Abstract
Borehole drilling is required if floor heave in underground mines is to be controlled using bolts through the floor. How well the bolt is anchored depends, in part, on the borehole’s quality. A major factor that can reduce borehole quality is the difficulty [...] Read more.
Borehole drilling is required if floor heave in underground mines is to be controlled using bolts through the floor. How well the bolt is anchored depends, in part, on the borehole’s quality. A major factor that can reduce borehole quality is the difficulty of discharging rock fragments from a small-diameter borehole drilled at a downward angle. Therefore, a fuller understanding of the sizes of the rock fragments will aid attempts to achieve smooth fragment discharge. In this study, drilling experiments in the laboratory and SEM imaging were carried out to determine the size and shape of the fragments generated when drilling boreholes in three sedimentary rocks typically found in roadway floors. The results show that the size distribution of the rock fragments conformed to the three-parameter generalized extreme value distribution. The mean fragment size increased with rock density and the mean size of the fragments larger than 1.5 mm increased with the rock’s uniaxial compressive strength. The fractal dimension of the cracks in the fragments was lower for high-density rocks and the mean fragment size was larger for rocks whose cracks had a lower fractal dimension. When a drill rod drills through very dense or high-strength rock, the mean size of the fragments will increase and the discharge power should be increased to prevent fragment discharge blockages. This paper may provide a theoretical basis and a data reference for discharge power settings and discharge channel optimization. Full article
Show Figures

Figure 1

20 pages, 1321 KiB  
Article
The Nexus between Higher Education and Unemployment—Evidence from Romania
by Daniela-Emanuela Dănăcică, Ana-Gabriela Babucea, Lucia Paliu-Popa, Gabriela Bușan and Irina-Elena Chirtoc
Sustainability 2023, 15(4), 3641; https://doi.org/10.3390/su15043641 - 16 Feb 2023
Cited by 4 | Viewed by 3589
Abstract
The aim of this research is to analyze, from a macro-economic perspective, the dynamic relationship between higher education and the unemployment rate in Romania. After the political changes at the end of 1989, in Romania the number of individuals enrolled in universities and [...] Read more.
The aim of this research is to analyze, from a macro-economic perspective, the dynamic relationship between higher education and the unemployment rate in Romania. After the political changes at the end of 1989, in Romania the number of individuals enrolled in universities and the number of highly educated graduates increased substantially. Through the research carried out in this article, we analyze whether this explosion of highly educated individuals is sustainable and is a factor in the evolution of the unemployment rate, specifically, whether higher education causes a short and/or a long-run decrease or increase of the unemployment rate, or whether the variables are independent. The autoregressive distributed lag (ARDL) model, the augmented Dickey-Fuller (ADF) procedure, and other econometric techniques specific to the dynamic analysis of time series were used as methodological approaches. The results prove that, at the macro-economic level, higher education and unemployment rate are not co-integrated in the long-run. However, for the analyzed period, there was a significant but modest short-run positive effect of higher education on unemployment rate. Our study emphasizes the importance, for a balanced and sustainable labor market, of correlating the number of individuals enrolled in higher education institutions with the needs of employers. We underline that a non-sustainable increase in the number of highly educated graduates may become a cause of the increase of unemployment and permanent migration of highly educated individuals. The obtained results can be useful for policy makers and can contribute to the development of effective strategies focused on higher education. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
Show Figures

Figure 1

Back to TopTop