Search in Publications
Found 6278 publications
The dynamic impact of oil price volatility on China's green bond market: An empirical analysis during economic shocks
Publication Name: Energy Strategy Reviews
Publication Date: 2026-03-01
Volume: 64
Issue: Unknown
Page Range: Unknown
Description:
The progressive financialization of oil, in tandem with the advancement of economic globalization, has led to a sharp increase in oil prices. The growing volatility in the global economic and financial landscape has had some impact on the green bond market. Emerging markets, such as China, are particularly interesting due to their rapid evolution. This paper empirically analyzes the dynamic impact of oil market price uncertainty on China's Green Bond (GB) using the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) model. The empirical findings indicate that the uncertainty of oil has a remarkable time-varying influence on China's green bonds. Specifically, when oil prices rise, the yields on green bonds decrease. Dynamic correlation analysis reveals that oil market uncertainty exhibits a negative correlation with green bonds, with a more pronounced impact during the COVID-19 pandemic. Furthermore, an impulse response analysis shows that long-term interactions between oil prices and green bonds gradually stabilize, and short-term fluctuations are frequent and complex due to market factors. These fluctuations were more pronounced during the COVID-19 pandemic, consistent with the above conclusions. Oil market uncertainty increases risk levels in the overall financial market, which may affect investors' perceptions of green bonds. Drawing on the research outcomes, this study presents targeted policy recommendations aimed at promoting the stable and sustainable development of China's GB market. These measures are designed to bolster the nation's transition toward a green economy and align with its long-term sustainability goals.
Open Access: Yes
Architecture of a Socialist Industrial Giant
Publication Name: Epites Epiteszettudomany
Publication Date: 2026-03-01
Volume: 54
Issue: 1-2
Page Range: 199-236
Description:
My study examines the industrial buildings realized between 1963 and 1990, the political transition in Hungary, developed through the collaboration between the Rába Hungarian Wagon and Machine Factory (Rába MVG) and the Győr Design Company (Győriterv), primarily from an architectural perspective. These industrial complexes represent a level of architectural and technical quality – broadly understood – that far exceeded the domestic average of the era. The quality-oriented and visionary client found a fitting professional partner in Győriterv’s architect, József Lőrincz. The halls, unprecedented in their time in both scale, formal and functional clarity, stand as exemplary cases of the exceptionally well-coordinated application of architectural and engineering knowledge. Owing to their success, similar facilities were also built for other actors in the Hungarian machinery industry. These buildings are of significance not only because of their industrial function, but also due to the role they played during the economic restructuring at the time of the regime change, forming a built legacy that remains in active use to this day. In addition to a brief overview of the factories themselves, the study focuses on the history of their construction – and in some cases, their design – while also outlining certain institutional aspects of the two socialist-era state-owned enterprises. The rich photographic documentation serves as a kind of time capsule, depicting how this industrial giant once looked and functioned. The primary sources of the research include archival materials, company publications, articles from the daily and professional press, as well as oral history interviews and an unpublished manuscript.
Open Access: Yes
High-Sensitivity SIW Sensor for Wide-Range Non-Invasive Blood Glucose Monitoring Using Complementary Split-Ring Resonator
Publication Name: Applied Biosciences
Publication Date: 2026-03-01
Volume: 5
Issue: 1
Page Range: Unknown
Description:
This work presents a compact microwave sensor for noninvasive blood glucose monitoring based on a substrate-integrated waveguide loaded with a complementary split-ring resonator on RO4350. The sensing principle uses shifts in resonance frequency and changes in S-parameters to track the dielectric dispersion of glucose-containing tissue. The resonator is constructed using Substrate-Integrated Waveguide (SIW) technology, which mimics the propagation characteristics of a conventional rectangular waveguide. To validate its versatility, the sensor implements three practical sample delivery modes: direct liquid contact with the sensing surface, a glass tube holder mounted over the active region, and a non-invasive fingertip interface. Electromagnetic simulations and benchtop measurements confirm clear glucose-dependent frequency shifts with stable matching and insertion levels. Across the physiological range of 20 to 200 mg·dL−1, the sensor exhibits clear glucose-dependent resonance shifts in all configurations. In direct contact mode, the resonance frequency shifts from 10.83 GHz to 10.45 GHz with sensitivities up to 2.47 MHz per mg·dL−1. The tube configuration shows a shift from 10.49 GHz to 10.38 GHz with sensitivity up to 0.80 MHz per mg·dL−1, while reducing contamination. In the non-invasive fingertip mode, the resonance shifts from 2.56 GHz to 2.52 GHz with sensitivities up to 0.25 MHz per mg·dL−1. These results confirm the sensor’s compactness, reliability, and suitability for portable, low-cost glucose monitoring. The results indicate that the proposed sensor can support practical continuous or spot monitoring and offers a clear path toward portable and low-cost glucose assessment.
Open Access: Yes
Optimal scheduling of electric vehicle charging and discharging using two optimization paradigms
Publication Name: Results in Engineering
Publication Date: 2026-03-01
Volume: 29
Issue: Unknown
Page Range: Unknown
Description:
Electric Vehicles (EVs) play a pivotal role in advancing environmental sustainability and accelerating the transition toward clean energy systems. However, large-scale EV adoption poses significant operational challenges, particularly when charging and discharging activities are uncoordinated, potentially leading to elevated peak demand and increased grid stress. Effective scheduling techniques are therefore essential to ensure reliable integration of EVs into modern power systems. This study provides a rigorous comparative evaluation of two metaheuristic optimization paradigms for EV charging and discharging scheduling: the traditional Particle Swarm Optimization (PSO) algorithm and the more recent Transit Search Optimization (TSO) algorithm. Using an identical system configuration and EV dataset, the study assesses the performance of both approaches based on peak power reduction, cost minimization, and overall system efficiency. Results demonstrate that while enhanced PSO scenarios exhibit noticeable improvements over earlier literature, TSO consistently achieves superior outcomes due to its stronger exploration-exploitation balance. In particular, TSO attains a 46.23 % reduction in average EV charging cost and achieves the lowest power-loss levels across all tested scenarios. Relative to the best previously published benchmarks, TSO further improves peak power consumption by 1.6 % and total charging cost by 6.1 %. These findings highlight TSO’s strong potential as a high-efficiency scheduling tool for large-scale EV integration in future smart grid environments.
Open Access: Yes
Elaboration and characterization of composite material based on epoxy resin and Cynara scolymus fibers: Weibull statistics analysis
Publication Name: Journal of Materials Research and Technology
Publication Date: 2026-03-01
Volume: 41
Issue: Unknown
Page Range: 6512-6527
Description:
The research will fill the increasing demand of sustainable composite materials by designing and characterizing an epoxy based biocomposite that is reinforced with natural fibers that are derived through the Cynara scolumus (artichoke stem) agricultural waste. The study methodically examines how fiber reinforcement influences the performance of the composite under a controlled extraction of the fibers, and also the unidirectional laminates of the composite were produced with single, double, and triple ply. The fibers were methodologically described in physical properties with the help of water absorption kinetics based on the Peleg equation, and mechanical performance with tensile tests and impact tests according to the ASTM standards, including SEM and EDX tests. The most important findings include the fact that the mechanical properties are greatly increased with the number of fiber plies: single-ply composite reached the ultimate tensile strength of about 15 MPa, double-ply composite tensile strength was 32 MPa, and the triple-ply composite tensile strength was 60 MPa with better strain at break (about 2.2%). The resistance to impact also improved with the number of ply and the adhesion of fibers to the matrix was also confirmed by SEM with a small number of voids and EDX gave a fiber composition of 56.49% carbon and 34.05% oxygen. The paper presents the new application of the Cynara scolymus fibers, which are an untested agricultural waste, in epoxy composites, and is the first use of Weibull statistical analysis to describe the consistency and reliability of these fibers as a sustainable reinforcement. The paper concludes that Cynara scolymus fibers are an effective, renewable reinforcement, with a very good balance of low density, better specific strength, and acceptable moisture uptake, thus contributing to the valorization of agricultural residues to support the eco-friendly structural and semi-structural composites.
Open Access: Yes
Reproductive Success Beyond Pollinators: Microhabitat Effects and Pollen Dynamics in Epipactis bugacensis, a Traditionally Obligately Autogamous Orchid
Publication Name: Plants
Publication Date: 2026-03-01
Volume: 15
Issue: 5
Page Range: Unknown
Description:
Orchid pollination is traditionally considered to rely on intact pollinarium transfer by animal vectors. Species lacking a functional viscidium are generally classified as obligately autogamous. In this study, we investigated the reproductive biology of Epipactis bugacensis, a taxon long regarded as strictly self-pollinating. Floral visitor activity was assessed through repeated field observations, and pollinator dependence was tested using a pollinator-exclusion (net-covering) experiment at two Hungarian populations, combined with measurements of fruit set, capsule volume, seed number, and seed density. We documented a previously unreported pollen-transfer mechanism in E. bugacensis, whereby halictid bees fragment pollinia and transfer these fragments in their scopa to neighboring flowers enabling geitonogamous deposition and suggesting the potential for xenogamous pollen transfer. Other visitor taxa showed no evidence of effective pollen transport. Mesh coverage increased fruit set, capsule volume, and seed number, while seed density remained unchanged. Reproductive output declined from basal to apical positions along flowering shoots, revealing strong internal resource-allocation constraints. Overall, E. bugacensis is predominantly self-pollinating but not strictly obligate autogamous, and its reproductive success is governed primarily by microhabitat quality rather than pollinator availability.
Open Access: Yes
Mapping municipal debt risks: A spatiotemporal analysis of China's prefecture-level cities
Publication Name: International Review of Economics and Finance
Publication Date: 2026-03-01
Volume: 106
Issue: Unknown
Page Range: Unknown
Description:
Addressing the risks associated with local government debt is crucial for economic development and fiscal security. This paper analyzes the spatiotemporal distribution of municipal government debt risks using panel data from 271 prefecture-level cities in China from 2015 to 2021, employing Exploratory Spatial Data Analysis (ESDA) and the Spatial Durbin Model. The prime objective of this research is to analyze the spatiotemporal distribution of municipal government debt in different regions of China, including the central, western, eastern regions. Key findings include: (1) Local government debt risk exhibits a fluctuating upward trend characterized by significant regional, administrative, and debt-type disparities. (2) Risk levels in central and western regions have increased, while major urban agglomerations have maintained medium or lower risk levels. (3) Local government debt risk demonstrates significant global spatial correlation, with low-low (LL) agglomerations evolving from multi-centered to dual-centered distributions. (4) Notably, a 1 % increase in neighboring debt risk leads to a 0.2467 % rise in local debt risk. (5) Fiscal pressure, urbanization rates, and economic scale are primary drivers of local government debt risk, whereas industrial structure, land transfer income, and financial development serve to mitigate it. These findings underscore the intra-regional and inter-regional heterogeneity and geographical differences, providing valuable insights for managing municipal government debt risk.
Open Access: Yes
Fractal geometry-based Klein-Gordon model for heat and mass transfer in a cylindrical cavity with variable thermal conductivity
Publication Name: Propulsion and Power Research
Publication Date: 2026-03-01
Volume: 15
Issue: 1
Page Range: 179-196
Description:
This study presents a generalized framework of vector calculus for non-integer dimensional spaces, motivated by the prevalence of fractals in nature. The work formulates first- and second-order differential operators, including gradient, divergence, and scalar and vector Laplacian, for scalar and rotationally covariant vector functions. This framework is applied to the thermoelastic response of an infinite fractal medium with a cylindrical cavity, a problem that incorporates thermoelastic mass diffusion and variable thermal conductivity through the Kirchhoff transformation. The system is analyzed under combined thermal and chemical shocks at the boundary, with the medium remaining mechanically fixed. The governing equations are solved using the Laplace transform method, and Zakian technique is employed for numerical inversion. The computational results indicate that parameters such as delay time and fractal dimension significantly influence the material's response. The graphical analysis visually examines the effects of different kernel functions, fractal dimension, variable thermal conductivity, nonlocal length and time scales on the thermoelastic response, providing a clear illustration of their impact. Specifically, an increase in fractal dimension leads to a more pronounced reduction in the thermoelastic response near the cylindrical cavity. Furthermore, an examination of different memory-dependent kernel functions reveals that nonlinear kernels demonstrate superior performance compared to linear kernels within this theoretical framework.
Open Access: Yes
Hybrid Brown-Bear and Hippopotamus Optimization with Quasi-Opposition-Based Learning for Optimal Power Flow with Renewable Energy Integration
Publication Name: Computers and Electrical Engineering
Publication Date: 2026-03-01
Volume: 131
Issue: Unknown
Page Range: Unknown
Description:
The optimal power flow (OPF) problem is a highly nonlinear and complex multi-dimension optimization problem, especially with the increased penetration of uncertain renewable energies (RES). In this line, this paper presents the Hybrid Brown-Bear and Hippopotamus Optimization Algorithms with Quasi-Opposition-Based Learning (HBOA-QOBL) to enhance multi-dimension OPF solution. The algorithm combines the strengths of Brown-Bear optimizer, which excels in exploration and adaptive search mechanisms, and the Hippopotamus optimizer, known for its social behavior modeling and localized search strategies. By integrating QOBL, the HBOA-QOBL improves exploration through the generation of quasi-opposite solutions, allowing for a wider search of the solution space and reducing the risk of premature convergence. Adaptive search mechanisms embedded in HBOA-QOBL enhance exploitation by dynamically adjusting search behaviors during iterative power dispatch tuning, enabling improved fine-tuning of generation schedules and voltage profiles. The effectiveness of the proposed method is evaluated on the IEEE 30-bus, 57-bus, and 118-bus test systems for multiple dimension OPF objectives, including fuel cost minimization, emission reduction, power loss reduction, voltage deviation minimization, reactive power loss reduction and the voltage stability indicator (L-index). Simulation results indicate faster convergence compared to conventional techniques, achieving near-optimal solutions within 200 iterations, with a standard deviation of 63.8%, demonstrating superior technical and economic performance relative to previous research. Key convergence parameters such as population size, maximum iterations, and learning factor are explicitly tuned to enhance both exploration and exploitation. Simulation results confirm that HBOA-QOBL outperforms conventional optimization techniques in terms of solution quality, convergence speed, and stability, establishing significant improvement in the technical and economic issues.
Open Access: Yes
